Reset23/the-stack-v2-python · Datasets at Hugging Face

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/xai/brain/wordbase/nouns/_syphon.py

1ef3547d3d666728720ba4bfc26206b8a9d76bc4

[ "MIT" ]

permissive

cash2one/xai

de7adad1758f50dd6786bf0111e71a903f039b64

e76f12c9f4dcf3ac1c7c08b0cc8844c0b0a104b6

refs/heads/master

2021-01-19T12:33:54.964379

2017-01-28T02:00:50

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#calss header class _SYPHON(): def __init__(self,): self.name = "SYPHON" self.definitions = [u'a siphon noun '] self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.specie = 'nouns' def run(self, obj1 = [], obj2 = []): return self.jsondata

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

5916126d6b2b7816ef167915954b5ddf8cb45d8f

54b238d50baee4f483c0690d77d106ebc30a4c0a

/tests/test_space_time/test_type_helpers.py

cb9dab6c31fed82502d58d190cd6d40c0ba43739

[ "MIT" ]

permissive

David-Durst/aetherling

4a5d663a98428769834e8ebbf7e9b63cb7788319

91bcf0579608ccbf7d42a7bddf90ccd4257d6571

refs/heads/master

2021-08-16T01:48:20.476097

2020-06-19T19:25:46

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2021-03-29T17:44:39

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from aetherling.space_time.space_time_types import * from aetherling.space_time.type_helpers import * def test_same_type(): x = ST_TSeq(3, 0, ST_Int()) y = ST_TSeq(3, 0, ST_Int()) shared_diff = get_shared_and_diff_subtypes(x,y) assert shared_diff.diff_input == ST_Tombstone() assert shared_diff.diff_output == ST_Tombstone() assert shared_diff.shared_inner == x assert shared_diff.shared_outer == ST_Tombstone() def test_same_type_nested(): x = ST_TSeq(3, 0, ST_SSeq(4, ST_Int)) y = ST_TSeq(3, 0, ST_SSeq(4, ST_Int)) shared_diff = get_shared_and_diff_subtypes(x,y) assert shared_diff.diff_input == ST_Tombstone() assert shared_diff.diff_output == ST_Tombstone() assert shared_diff.shared_inner == x assert shared_diff.shared_outer == ST_Tombstone() def test_diff_no_outer_same(): x = ST_SSeq(6, ST_TSeq(3, 0, ST_SSeq(4, ST_Int))) y = ST_TSeq(3, 0, ST_SSeq(6, ST_SSeq(4, ST_Int))) shared_diff = get_shared_and_diff_subtypes(x,y) assert shared_diff.diff_input == ST_SSeq(6, ST_TSeq(3, 0, ST_Tombstone())) assert shared_diff.diff_output == ST_TSeq(3, 0, ST_SSeq(6, ST_Tombstone())) assert shared_diff.shared_inner == x.t.t assert shared_diff.shared_outer == ST_Tombstone() def test_diff_with_outer_same(): x = ST_TSeq(9, 2, ST_SSeq(6, ST_TSeq(3, 0, ST_SSeq(4, ST_Int)))) y = ST_TSeq(9, 2, ST_TSeq(3, 0, ST_SSeq(6, ST_SSeq(4, ST_Int)))) shared_diff = get_shared_and_diff_subtypes(x,y) assert shared_diff.diff_input == ST_SSeq(6, ST_TSeq(3, 0, ST_Tombstone())) assert shared_diff.diff_output == ST_TSeq(3, 0, ST_SSeq(6, ST_Tombstone())) assert shared_diff.shared_inner == x.t.t.t assert shared_diff.shared_outer == ST_TSeq(9, 2, ST_Tombstone()) def test_diff_with_partially_diff_inner(): x = ST_TSeq(9, 2, ST_SSeq(6, ST_SSeq(7, ST_TSeq(3, 0, ST_SSeq(4, ST_Int))))) y = ST_TSeq(9, 2, ST_TSeq(3, 0, ST_SSeq(7, ST_SSeq(6, ST_SSeq(4, ST_Int))))) shared_diff = get_shared_and_diff_subtypes(x,y) assert shared_diff.diff_input == ST_SSeq(6, ST_SSeq(7, ST_TSeq(3, 0, ST_Tombstone()))) assert shared_diff.diff_output == ST_TSeq(3, 0, ST_SSeq(7, ST_SSeq(6, ST_Tombstone()))) assert shared_diff.shared_inner == x.t.t.t.t assert shared_diff.shared_outer == ST_TSeq(9, 2, ST_Tombstone()) def test_diff_depths(): x = ST_TSeq(4, 12, ST_Int()) y = ST_TSeq(2, 2, ST_TSeq(2, 2, ST_Int())) shared_diff = get_shared_and_diff_subtypes(x,y) assert shared_diff.diff_input == ST_TSeq(4, 12, ST_Tombstone()) assert shared_diff.diff_output == ST_TSeq(2, 2, ST_TSeq(2, 2, ST_Tombstone())) assert shared_diff.shared_inner == ST_Int() assert shared_diff.shared_outer == ST_Tombstone()

[ "davidbdurst@gmail.com" ]

davidbdurst@gmail.com

a95c8e9ee9b4167c2ef845c2453d3b7c424026ec

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/tracker-visual/read_cluster.py

3739ddc9ef84e61e5178f922a6728920b78a1a44

[ "MIT" ]

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will-fawcett/trackerSW

6f71a8ab9e2013e439e1e24326c1cc59f7be1e7f

fc097b97539d0b40a15e1d6e112f4048cb4122b4

refs/heads/master

2021-04-25T21:39:17.321302

2018-06-14T13:31:13

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""" Quick script to dump FCCSW tracker validation data to plaintext spacepoints. Requires podio, fcc-edm in pythonpath and ld-library-path. """ from EventStore import EventStore import numpy as np import sys filename = sys.argv[1] basefilename = filename.replace(".root", "") events = EventStore([filename]) print 'number of events: ', len(events) pos_b = [] ids_b = [] pos_e = [] ids_e = [] barrel_ids = [] nEventsMax = 100000 #nEventsMax = 1 for i, store in enumerate(events): # Only run over 100000 events if i > nEventsMax: break # <class 'ROOT.fcc.PositionedTrackHitCollection'> clusters = store.get('positionedHits') #print clusters layerIdmax = 0 for c in clusters: #c is of type <class 'ROOT.fcc.PositionedTrackHit'> # <class 'ROOT.fcc.Point'> cor = c.position() layerId = (c.cellId() / 32) %32 if layerId > 20: print c.cellId(), c.cellId() % 32, c.cellId() / 32, (c.cellId() / 32) %32 if layerId > layerIdmax: layerIdmax = layerId if (c.cellId() % 32) == 0: # Select only the triplet layers #if (c.cellId() / 32) %32 == 20 or (c.cellId() / 32) %32 == 21 (c.cellId() / 32) %32 == 22: if (c.cellId() / 32) %32 == 1: # or (c.cellId() / 32) %32 == 21 (c.cellId() / 32) %32 == 22: pass pos_b.append([cor.x, cor.y, cor.z]) ids_b.append([c.bits(), c.cellId()]) #print c.cellId() % 32, np.sqrt(cor.x**2 + cor.y**2) #else: # pos_e.append([cor.x, cor.y, cor.z]) # ids_e.append([c.bits(), c.cellId()]) pos_e = np.array(pos_e) ids_e = np.array(ids_e) pos_b = np.array(pos_b) ids_b = np.array(ids_b) print "number of endcap hits: ", len(pos_e) print "number of barrel hits: ", len(pos_b) np.savetxt(basefilename + 'hit_positions_e.dat', pos_e) np.savetxt(basefilename + 'hit_ids_e.dat', ids_e, fmt="%i") np.savetxt(basefilename + 'hit_positions_b.dat', pos_b) np.savetxt(basefilename + 'hit_ids_b.dat', ids_b, fmt="%i")

[ "william.fawcett@cern.ch" ]

william.fawcett@cern.ch

99f477ff8ee5eee19b30adddfcaa704802c97c42

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/repoData/Floobits-flootty/allPythonContent.py

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aCoffeeYin/pyreco

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refs/heads/master

2020-12-14T14:10:05.763693

2016-06-27T05:15:15

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__FILENAME__ = api import sys import base64 import json try: from urllib.request import Request, urlopen assert Request and urlopen except ImportError: from urllib2 import Request, urlopen try: from . import shared as G, utils assert G and utils except (ImportError, ValueError): import shared as G import utils def get_basic_auth(): # TODO: use api_key if it exists basic_auth = ('%s:%s' % (G.USERNAME, G.SECRET)).encode('utf-8') basic_auth = base64.encodestring(basic_auth) return basic_auth.decode('ascii').replace('\n', '') def api_request(url, data=None): if data: data = json.dumps(data).encode('utf-8') r = Request(url, data=data) r.add_header('Authorization', 'Basic %s' % get_basic_auth()) r.add_header('Accept', 'application/json') r.add_header('Content-type', 'application/json') r.add_header('User-Agent', 'Flootty py-%s.%s' % (sys.version_info[0], sys.version_info[1])) return urlopen(r, timeout=5) def create_workspace(post_data): url = 'https://%s/api/workspace/' % G.DEFAULT_HOST return api_request(url, post_data) def get_workspace_by_url(url): result = utils.parse_url(url) api_url = 'https://%s/api/workspace/%s/%s/' % (result['host'], result['owner'], result['workspace']) return api_request(api_url) def get_workspace(owner, workspace): api_url = 'https://%s/api/workspace/%s/%s/' % (G.DEFAULT_HOST, owner, workspace) return api_request(api_url) def get_workspaces(): api_url = 'https://%s/api/workspace/can/view/' % (G.DEFAULT_HOST) return api_request(api_url) def get_now_editing_workspaces(): api_url = 'https://%s/api/workspaces/now_editing/' % (G.DEFAULT_HOST) return api_request(api_url) def get_orgs(): api_url = 'https://%s/api/orgs/' % (G.DEFAULT_HOST) return api_request(api_url) def get_orgs_can_admin(): api_url = 'https://%s/api/orgs/can/admin/' % (G.DEFAULT_HOST) return api_request(api_url) def send_error(data): try: api_url = 'https://%s/api/error/' % (G.DEFAULT_HOST) return api_request(api_url, data) except Exception as e: print(e) return None ########NEW FILE######## __FILENAME__ = cert CA_CERT = '''-----BEGIN CERTIFICATE----- MIIHyTCCBbGgAwIBAgIBATANBgkqhkiG9w0BAQUFADB9MQswCQYDVQQGEwJJTDEW MBQGA1UEChMNU3RhcnRDb20gTHRkLjErMCkGA1UECxMiU2VjdXJlIERpZ2l0YWwg Q2VydGlmaWNhdGUgU2lnbmluZzEpMCcGA1UEAxMgU3RhcnRDb20gQ2VydGlmaWNh dGlvbiBBdXRob3JpdHkwHhcNMDYwOTE3MTk0NjM2WhcNMzYwOTE3MTk0NjM2WjB9 MQswCQYDVQQGEwJJTDEWMBQGA1UEChMNU3RhcnRDb20gTHRkLjErMCkGA1UECxMi U2VjdXJlIERpZ2l0YWwgQ2VydGlmaWNhdGUgU2lnbmluZzEpMCcGA1UEAxMgU3Rh cnRDb20gQ2VydGlmaWNhdGlvbiBBdXRob3JpdHkwggIiMA0GCSqGSIb3DQEBAQUA A4ICDwAwggIKAoICAQDBiNsJvGxGfHiflXu1M5DycmLWwTYgIiRezul38kMKogZk pMyONvg45iPwbm2xPN1yo4UcodM9tDMr0y+v/uqwQVlntsQGfQqedIXWeUyAN3rf OQVSWff0G0ZDpNKFhdLDcfN1YjS6LIp/Ho/u7TTQEceWzVI9ujPW3U3eCztKS5/C Ji/6tRYccjV3yjxd5srhJosaNnZcAdt0FCX+7bWgiA/deMotHweXMAEtcnn6RtYT Kqi5pquDSR3l8u/d5AGOGAqPY1MWhWKpDhk6zLVmpsJrdAfkK+F2PrRt2PZE4XNi HzvEvqBTViVsUQn3qqvKv3b9bZvzndu/PWa8DFaqr5hIlTpL36dYUNk4dalb6kMM Av+Z6+hsTXBbKWWc3apdzK8BMewM69KN6Oqce+Zu9ydmDBpI125C4z/eIT574Q1w +2OqqGwaVLRcJXrJosmLFqa7LH4XXgVNWG4SHQHuEhANxjJ/GP/89PrNbpHoNkm+ Gkhpi8KWTRoSsmkXwQqQ1vp5Iki/untp+HDH+no32NgN0nZPV/+Qt+OR0t3vwmC3 Zzrd/qqc8NSLf3Iizsafl7b4r4qgEKjZ+xjGtrVcUjyJthkqcwEKDwOzEmDyei+B 26Nu/yYwl/WL3YlXtq09s68rxbd2AvCl1iuahhQqcvbjM4xdCUsT37uMdBNSSwID AQABo4ICUjCCAk4wDAYDVR0TBAUwAwEB/zALBgNVHQ8EBAMCAa4wHQYDVR0OBBYE FE4L7xqkQFulF2mHMMo0aEPQQa7yMGQGA1UdHwRdMFswLKAqoCiGJmh0dHA6Ly9j ZXJ0LnN0YXJ0Y29tLm9yZy9zZnNjYS1jcmwuY3JsMCugKaAnhiVodHRwOi8vY3Js LnN0YXJ0Y29tLm9yZy9zZnNjYS1jcmwuY3JsMIIBXQYDVR0gBIIBVDCCAVAwggFM BgsrBgEEAYG1NwEBATCCATswLwYIKwYBBQUHAgEWI2h0dHA6Ly9jZXJ0LnN0YXJ0 Y29tLm9yZy9wb2xpY3kucGRmMDUGCCsGAQUFBwIBFilodHRwOi8vY2VydC5zdGFy dGNvbS5vcmcvaW50ZXJtZWRpYXRlLnBkZjCB0AYIKwYBBQUHAgIwgcMwJxYgU3Rh cnQgQ29tbWVyY2lhbCAoU3RhcnRDb20pIEx0ZC4wAwIBARqBl0xpbWl0ZWQgTGlh YmlsaXR5LCByZWFkIHRoZSBzZWN0aW9uICpMZWdhbCBMaW1pdGF0aW9ucyogb2Yg dGhlIFN0YXJ0Q29tIENlcnRpZmljYXRpb24gQXV0aG9yaXR5IFBvbGljeSBhdmFp bGFibGUgYXQgaHR0cDovL2NlcnQuc3RhcnRjb20ub3JnL3BvbGljeS5wZGYwEQYJ YIZIAYb4QgEBBAQDAgAHMDgGCWCGSAGG+EIBDQQrFilTdGFydENvbSBGcmVlIFNT TCBDZXJ0aWZpY2F0aW9uIEF1dGhvcml0eTANBgkqhkiG9w0BAQUFAAOCAgEAFmyZ 9GYMNPXQhV59CuzaEE44HF7fpiUFS5Eyweg78T3dRAlbB0mKKctmArexmvclmAk8 jhvh3TaHK0u7aNM5Zj2gJsfyOZEdUauCe37Vzlrk4gNXcGmXCPleWKYK34wGmkUW FjgKXlf2Ysd6AgXmvB618p70qSmD+LIU424oh0TDkBreOKk8rENNZEXO3SipXPJz ewT4F+irsfMuXGRuczE6Eri8sxHkfY+BUZo7jYn0TZNmezwD7dOaHZrzZVD1oNB1 ny+v8OqCQ5j4aZyJecRDjkZy42Q2Eq/3JR44iZB3fsNrarnDy0RLrHiQi+fHLB5L EUTINFInzQpdn4XBidUaePKVEFMy3YCEZnXZtWgo+2EuvoSoOMCZEoalHmdkrQYu L6lwhceWD3yJZfWOQ1QOq92lgDmUYMA0yZZwLKMS9R9Ie70cfmu3nZD0Ijuu+Pwq yvqCUqDvr0tVk+vBtfAii6w0TiYiBKGHLHVKt+V9E9e4DGTANtLJL4YSjCMJwRuC O3NJo2pXh5Tl1njFmUNj403gdy3hZZlyaQQaRwnmDwFWJPsfvw55qVguucQJAX6V um0ABj6y6koQOdjQK/W/7HW/lwLFCRsI3FU34oH7N4RDYiDK51ZLZer+bMEkkySh NOsF/5oirpt9P/FlUQqmMGqz9IgcgA38corog14= -----END CERTIFICATE-----''' ########NEW FILE######## __FILENAME__ = flootty #!/usr/bin/env python # coding: utf-8 try: unicode() except NameError: unicode = str # Heavily influenced by the work of Joshua D. Bartlett # see: http://sqizit.bartletts.id.au/2011/02/14/pseudo-terminals-in-python/ # original copyright # Copyright (c) 2011 Joshua D. Bartlett # # 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. # boilerplate to allow running as script directly if __name__ == "__main__" and __package__ is None: import sys import os # The following assumes the script is in the top level of the package # directory. We use dirname() to help get the parent directory to add to # sys.path, so that we can import the current package. This is necessary # since when invoked directly, the 'current' package is not automatically # imported. parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) sys.path.insert(0, parent_dir) import flootty assert flootty __package__ = str("flootty") del sys, os import atexit import fcntl import json import optparse import array import os import pty import select import socket import ssl import sys import tempfile import termios import tty import signal import time import base64 import collections import errno PY2 = sys.version_info < (3, 0) try: import __builtin__ input = getattr(__builtin__, 'raw_input') except (ImportError, AttributeError): pass try: from . import api, cert, shared as G, utils, version assert api and cert and G and utils except (ImportError, ValueError): import api import cert import shared as G import utils import version PROTO_VERSION = '0.11' CLIENT = 'flootty %s' % version.FLOOTTY_VERSION INITIAL_RECONNECT_DELAY = 1000 FD_READ_BYTES = 65536 # Seconds SELECT_TIMEOUT = 0.1 NET_TIMEOUT = 10 MAX_BYTES_TO_BUFFER = 65536 DEFAULT_HOST = "floobits.com" DEFAULT_PORT = 3448 def read_floorc(): settings = {} p = os.path.expanduser('~/.floorc') try: fd = open(p, 'rb') except IOError as e: if e.errno == 2: return settings raise data = fd.read().decode('utf-8') fd.close() for line in data.split('\n'): position = line.find(' ') if position < 0: continue settings[line[:position]] = line[position + 1:] return settings def write(fd, b): if (not PY2) and isinstance(b, str): b = b.encode('utf-8') elif PY2 and isinstance(b, unicode): b = b.encode('utf-8') while len(b): try: n = os.write(fd, b) b = b[n:] except (IOError, OSError): pass def read(fd): buf = b'' while True: try: d = os.read(fd, FD_READ_BYTES) if not d or d == '': break buf += d except (IOError, OSError): break return buf def out(*args): buf = "%s\r\n" % " ".join(args) write(pty.STDOUT_FILENO, buf) def err(*args): buf = "%s\r\n" % " ".join(args) write(pty.STDERR_FILENO, buf) def die(*args): err(*args) sys.exit(1) usage = '''usage: %prog [options] [terminal_name]\n For more help, see https://github.com/Floobits/flootty''' def main(): settings = read_floorc() parser = optparse.OptionParser(usage=usage) parser.add_option("-u", "--username", dest="username", default=settings.get('username'), help="Your Floobits username") parser.add_option("-s", "--secret", dest="secret", default=settings.get('secret'), help="Your Floobits secret (api key)") parser.add_option("-c", "--create", dest="create", default=False, action="store_true", help="The terminal name to create") parser.add_option("--host", dest="host", default=DEFAULT_HOST, help="The host to connect to. Deprecated. Use --url instead.") parser.add_option("-p", "--port", dest="port", default=DEFAULT_PORT, help="The port to connect to. Deprecated. Use --url instead.") parser.add_option("-w", "--workspace", dest="workspace", help="The workspace name. --owner is required with this option. Deprecated. Use --url instead.") parser.add_option("-o", "--owner", dest="owner", help="The workspace owner. --workspace is required with this option. Deprecated. Use --url instead.") parser.add_option("-l", "--list", dest="list", default=False, action="store_true", help="List all terminals in the workspace") parser.add_option("--unsafe", dest="safe", default=True, action="store_false", help="Less safe terminal. This allows other users to send enter in your terminal.") parser.add_option("--no-ssl", dest="use_ssl", default=True, action="store_false", help="Do not use this option unless you know what you are doing!") parser.add_option("--url", dest="workspace_url", default=None, help="The URL of the workspace to connect to.") parser.add_option("--resize", dest="resize", default=False, action="store_true", help="Resize your terminal to the host terminal size.") parser.add_option("-P", "--preserve-ps1", dest="set_prompt", default=True, action="store_false", help="Don't change $PS1 (bash/zsh prompt)") parser.add_option("-v", "--version", dest="version", default=False, action="store_true", help="Print version") options, args = parser.parse_args() if options.version: print(CLIENT) return G.USERNAME = options.username G.SECRET = options.secret default_term_name = "" if options.create: default_term_name = "ftty" term_name = args and args[0] or default_term_name if options.workspace and options.owner and options.workspace_url: # TODO: confusing parser.error("You can either specify --workspace and --owner, or --url, but not both.") if bool(options.workspace) != bool(options.owner): parser.error("You must specify a workspace and owner or neither.") for opt in ['owner', 'workspace']: if getattr(options, opt): print('%s is deprecated. Please use --url instead.' % opt) if not options.workspace or not options.owner: floo = {} if options.workspace_url: floo = utils.parse_url(options.workspace_url) else: for floo_path in walk_up(os.path.realpath('.')): try: floo = json.loads(open(os.path.join(floo_path, '.floo'), 'rb').read().decode('utf-8')) floo = utils.parse_url(floo['url']) except Exception: pass else: break options.host = floo.get('host') options.workspace = floo.get('workspace') options.owner = floo.get('owner') options.use_ssl = floo.get('secure') if not options.port: options.port = floo.get('port') if not options.host: options.host = floo.get('host') if not options.workspace or not options.owner: now_editing = api.get_now_editing_workspaces() now_editing = json.loads(now_editing.read().decode('utf-8')) if len(now_editing) == 1: options.workspace = now_editing[0]['name'] options.owner = now_editing[0]['owner'] # TODO: list possible workspaces to join if > 1 is active if options.list: if len(term_name) != 0: die("I don't understand why you gave me a positional argument.") for opt in ['workspace', 'owner', 'username', 'secret']: if not getattr(options, opt): parser.error('%s not given' % opt) color_reset = '\033[0m' if options.safe: green = '\033[92m' print('%sTerminal is safe. Other users will not be able to send [enter]%s' % (green, color_reset)) else: yellorange = '\033[93m' print('%sTerminal is unsafe. Other users will be able to send [enter]. Be wary!%s' % (yellorange, color_reset)) f = Flootty(options, term_name) atexit.register(f.cleanup) f.connect_to_internet() f.select() def walk_up(path): step_up = lambda x: os.path.realpath(os.path.join(x, '..')) parent = step_up(path) while parent != path: yield path path = parent parent = step_up(path) yield path class FD(object): def __init__(self, fileno, reader=None, writer=None, errer=None, name=None): self.fileno = fileno self.reader = reader self.writer = writer self.errer = errer self.name = name def __getitem__(self, key): return getattr(self, key, None) def __str__(self): return str(self.name) class Flootty(object): '''Mostly OK at sharing a shell''' def __init__(self, options, term_name): self.master_fd = None self.original_wincher = None self.fds = {} self.readers = set() self.writers = set() self.errers = set() self.empty_selects = 0 self.reconnect_timeout = None self.buf_out = collections.deque() self.buf_in = b'' self.host = options.host self.port = int(options.port) self.workspace = options.workspace self.owner = options.owner self.options = options self.term_name = term_name self.authed = False self.term_id = None self.orig_stdin_atts = None self.orig_stdout_atts = None self.last_stdin = 0 self.reconnect_delay = INITIAL_RECONNECT_DELAY def add_fd(self, fileno, **kwargs): try: fileno = fileno.fileno() except: fileno = fileno fd = FD(fileno, **kwargs) self.fds[fileno] = fd if fd.reader: self.readers.add(fileno) if fd.writer: self.writers.add(fileno) if fd.errer: self.errers.add(fileno) def remove_fd(self, fileno): self.readers.discard(fileno) self.writers.discard(fileno) self.errers.discard(fileno) try: del self.fds[fileno] except KeyError: pass def transport(self, name, data): data['name'] = name self.buf_out.append(data) def select(self): ''' ''' attrs = ('errer', 'reader', 'writer') while True: utils.call_timeouts() if len(self.buf_out) == 0 and self.sock: self.writers.remove(self.sock.fileno()) try: # NOTE: you will never have to write anything without reading first from a different one _in, _out, _except = select.select(self.readers, self.writers, self.errers, SELECT_TIMEOUT) except (IOError, OSError) as e: continue except (select.error, socket.error, Exception) as e: # Interrupted system call. if e[0] == 4: continue self.reconnect() continue finally: if self.sock: self.writers.add(self.sock.fileno()) for position, fds in enumerate([_except, _in, _out]): attr = attrs[position] for fd in fds: # the handler can remove itself from self.fds... handler = self.fds.get(fd) if handler is None: continue handler = handler[attr] if handler: handler(fd) else: raise Exception('no handler for fd: %s %s' % (fd, attr)) def cloud_read(self, fd): buf = b'' try: while True: d = self.sock.recv(FD_READ_BYTES) if not d: break buf += d except (socket.error, TypeError): pass if buf: self.empty_selects = 0 self.handle(buf) else: self.empty_selects += 1 if (int(self.empty_selects * SELECT_TIMEOUT)) > NET_TIMEOUT: err('No data from sock.recv() {0} times.'.format(self.empty_selects)) return self.reconnect() def cloud_write(self, fd): new_buf_out = collections.deque() try: while True: item = self.buf_out.popleft() data = json.dumps(item) + '\n' if self.authed or item['name'] == 'auth': if not PY2: data = data.encode('utf-8') self.sock.sendall(data) else: new_buf_out.append(item) except socket.error: self.buf_out.appendleft(item) self.reconnect() except IndexError: pass self.buf_out.extendleft(new_buf_out) def cloud_err(self, err): out('reconnecting because of %s' % err) self.reconnect() def handle(self, req): self.buf_in += req while True: before, sep, after = self.buf_in.partition(b'\n') if not sep: break data = json.loads(before.decode('utf-8'), encoding='utf-8') self.handle_event(data) self.buf_in = after def handle_event(self, data): name = data.get('name') if not name: return out('no name in data?!?') func = getattr(self, "on_%s" % (name), None) if not func: return func(data) def on_room_info(self, ri): self.authed = True self.ri = ri def list_terms(terms): term_name = "" for term_id, term in terms.items(): owner = str(term['owner']) term_name = term['term_name'] out('terminal %s created by %s' % (term['term_name'], ri['users'][owner]['username'])) return term_name if self.options.create: buf = self._get_pty_size() term_name = self.term_name i = 0 term_names = [term['term_name'] for term_id, term in ri['terms'].items()] while term_name in term_names: i += 1 term_name = self.term_name + str(i) self.term_name = term_name return self.transport('create_term', {'term_name': self.term_name, 'size': [buf[1], buf[0]]}) elif self.options.list: out('Terminals in %s::%s' % (self.owner, self.workspace)) list_terms(ri['terms']) return die() elif not self.term_name: if len(ri['terms']) == 0: out('There is no active terminal in this workspace. Do you want to share your terminal? (y/n)') choice = input().lower() self.term_name = "_" if choice == 'y': self.options.create = True buf = self._get_pty_size() return self.transport('create_term', {'term_name': self.term_name, 'size': [buf[1], buf[0]]}) else: die('If you ever change your mind, you can share your terminal using the --create [super_awesome_name] flag.') elif len(ri['terms']) == 1: term_id, term = list(ri['terms'].items())[0] self.term_id = int(term_id) self.term_name = term['term_name'] else: out('More than one active term exists in this workspace.') example_name = list_terms(ri['terms']) die('Please pick a workspace like so: flootty %s' % example_name) else: for term_id, term in ri['terms'].items(): if term['term_name'] == self.term_name: self.term_id = int(term_id) break if self.term_id is None: die('No terminal with name %s' % self.term_name) return self.join_term() def on_ping(self, data): self.transport('pong', {}) def on_disconnect(self, data): reason = data.get('reason') out('Disconnected by server!') if reason: # TODO: don't kill terminal until current process is done or something die('Reason: %s' % reason) self.reconnect() def on_error(self, data): if self.term_id is None: die(data.get('msg')) else: out('Error from server: %s' % data.get('msg')) def on_create_term(self, data): if data.get('term_name') != self.term_name: return self.term_id = data.get('id') self.create_term() def on_delete_term(self, data): if data.get('id') != self.term_id: return die('User %s killed the terminal. Exiting.' % (data.get('username'))) def on_update_term(self, data): if data.get('id') != self.term_id: return self._set_pty_size() def on_term_stdin(self, data): if data.get('id') != self.term_id: return if not self.options.create: return self.handle_stdio(base64.b64decode(data['data']), data.get('user_id')) def on_term_stdout(self, data): if data.get('id') != self.term_id: return self.handle_stdio(data['data']) def reconnect(self): if self.reconnect_timeout: return new_buf_out = collections.deque() total_len = 0 while True: try: item = self.buf_out.popleft() except IndexError: break if item['name'] == 'term_stdout': total_len += len(item['data']) if total_len > MAX_BYTES_TO_BUFFER: continue new_buf_out.appendleft(item) self.buf_out = new_buf_out if self.sock: self.remove_fd(self.sock.fileno()) try: self.sock.shutdown(2) except Exception: pass try: self.sock.close() except Exception: pass self.sock = None self.authed = False self.reconnect_delay *= 1.5 if self.reconnect_delay > 10000: self.reconnect_delay = 10000 self.reconnect_timeout = utils.set_timeout(self.connect_to_internet, self.reconnect_delay) def send_auth(self): self.buf_out.appendleft({ 'name': 'auth', 'username': self.options.username, 'secret': self.options.secret, 'room': self.workspace, 'room_owner': self.owner, 'client': CLIENT, 'platform': sys.platform, 'version': PROTO_VERSION }) def connect_to_internet(self): self.empty_selects = 0 self.reconnect_timeout = None self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) if self.options.use_ssl: self.cert_fd = tempfile.NamedTemporaryFile() self.cert_fd.write(cert.CA_CERT.encode('utf-8')) self.cert_fd.flush() self.sock = ssl.wrap_socket(self.sock, ca_certs=self.cert_fd.name, cert_reqs=ssl.CERT_REQUIRED) elif self.port == 3448: self.port = 3148 out('Connecting to %s' % self.workspace_url()) try: self.sock.connect((self.host, self.port)) if self.options.use_ssl: self.sock.do_handshake() except socket.error as e: out('Error connecting: %s.' % e) return self.reconnect() self.sock.setblocking(0) out('Connected!') self.send_auth() self.add_fd(self.sock, reader=self.cloud_read, writer=self.cloud_write, errer=self.cloud_err, name='net') self.reconnect_delay = INITIAL_RECONNECT_DELAY def workspace_url(self): proto = {True: "https", False: "http"} proto_str = proto[self.options.use_ssl] port_str = '' if self.options.use_ssl: if self.port != 3448: port_str = ':%s' % self.port else: if self.port != 3148: port_str = ':%s' % self.port return '%s://%s%s/%s/%s' % (proto_str, self.host, port_str, self.owner, self.workspace) def join_term(self): out('Successfully joined %s' % (self.workspace_url())) self.orig_stdout_atts = tty.tcgetattr(sys.stdout) stdout = sys.stdout.fileno() tty.setraw(stdout) fl = fcntl.fcntl(stdout, fcntl.F_GETFL) fcntl.fcntl(stdout, fcntl.F_SETFL, fl | os.O_NONBLOCK) self.orig_stdin_atts = tty.tcgetattr(sys.stdin) stdin = sys.stdin.fileno() tty.setraw(stdin) fl = fcntl.fcntl(stdin, fcntl.F_GETFL) fcntl.fcntl(stdin, fcntl.F_SETFL, fl | os.O_NONBLOCK) def ship_stdin(fd): data = read(fd) if data: self.transport("term_stdin", {'data': base64.b64encode(data).decode('utf8'), 'id': self.term_id}) if 'term_stdin' in self.ri['perms']: out('You have permission to write to this terminal. Remember: With great power comes great responsibility.') self.add_fd(stdin, reader=ship_stdin, name='join_term_stdin') else: out('You do not have permission to write to this terminal.') def stdout_write(buf): write(stdout, base64.b64decode(buf)) self.handle_stdio = stdout_write self._set_pty_size(self.ri['terms'][str(self.term_id)]['size']) def create_term(self): ''' Create a spawned process. Based on the code for pty.spawn(). ''' if self.master_fd: # reconnected. don't spawn a new shell out('Reconnected to %s' % (self.workspace_url())) return shell = os.environ['SHELL'] out('Successfully joined %s' % (self.workspace_url())) self.child_pid, self.master_fd = pty.fork() if self.child_pid == pty.CHILD: os.execlpe(shell, shell, '--login', os.environ) self.orig_stdin_atts = tty.tcgetattr(sys.stdin.fileno()) tty.setraw(pty.STDIN_FILENO) self.original_wincher = signal.signal(signal.SIGWINCH, self._signal_winch) self._set_pty_size() def slave_death(fd): die('Exiting flootty because child exited.') self.extra_data = b'' def stdout_write(fd): ''' Called when there is data to be sent from the child process back to the user. ''' try: data = self.extra_data + os.read(fd, FD_READ_BYTES) except: data = None if not data: return die("Time to go!") self.transport("term_stdout", {'data': base64.b64encode(data).decode('utf8'), 'id': self.term_id}) write(pty.STDOUT_FILENO, data) self.add_fd(self.master_fd, reader=stdout_write, errer=slave_death, name='create_term_stdout_write') def stdin_write(fd): data = os.read(fd, FD_READ_BYTES) if data: write(self.master_fd, data) now = time.time() # Only send stdin event if it's been > 2 seconds. This prevents people from figuring out password lengths if now - self.last_stdin > 2: self.transport("term_stdin", {'data': ' ', 'id': self.term_id}) self.last_stdin = now self.add_fd(pty.STDIN_FILENO, reader=stdin_write, name='create_term_stdin_write') def net_stdin_write(buf, user_id=None): if self.options.safe: if buf.find('\n') != -1 or buf.find('\r') != -1: to = user_id or [] self.transport('datamsg', { 'to': to, 'data': { 'name': 'safe_term', 'term_id': self.term_id, 'msg': 'Terminal %s is in safe mode. Other users are not allowed to press enter.' % self.term_name, }}) self.transport('term_stdout', { 'id': self.term_id, 'data': base64.b64encode('\a').decode('utf8'), }) buf = buf.replace('\n', '') buf = buf.replace('\r', '') if not buf: return write(self.master_fd, buf) self.handle_stdio = net_stdin_write color_green = '\\[\\e[32m\\]' color_reset = '\\[\\033[0m\\]' color_yellorange = '\\[\\e[93m\\]' # TODO: other shells probably use weird color escapes if 'zsh' in shell: color_green = "%{%F{green}%}" color_reset = "%{%f%}" color_yellorange = "%{%F{yellow}%}" if self.options.set_prompt: term_color = color_yellorange if self.options.safe: term_color = color_green # Not confusing at all </sarcasm> cmd = 'PS1="%s%s::%s::%s%s%s%s $PS1"\n' % (color_green, self.owner, self.workspace, color_reset, term_color, self.term_name, color_reset) write(self.master_fd, cmd) def _signal_winch(self, signum, frame): ''' Signal handler for SIGWINCH - window size has changed. ''' self._set_pty_size() def _get_pty_size(self): buf = array.array('h', [0, 0, 0, 0]) fcntl.ioctl(pty.STDOUT_FILENO, termios.TIOCGWINSZ, buf, True) return buf def _set_pty_size(self, size=None): ''' Sets the window size of the child pty based on the window size of our own controlling terminal. ''' # Get the terminal size of the real terminal, set it on the pseudoterminal. buf = self._get_pty_size() if size: buf[0] = size[1] buf[1] = size[0] if self.options.create: assert self.master_fd is not None fcntl.ioctl(self.master_fd, termios.TIOCSWINSZ, buf) if self.term_id: self.transport('update_term', {'id': self.term_id, 'size': [buf[1], buf[0]]}) else: # XXXX: this resizes the window :/ if self.options.resize: os.write(pty.STDOUT_FILENO, "\x1b[8;{rows};{cols}t".format(rows=buf[0], cols=buf[1])) fcntl.ioctl(pty.STDOUT_FILENO, termios.TIOCSWINSZ, buf) def cleanup(self): if self.orig_stdout_atts: self.orig_stdout_atts[3] = self.orig_stdout_atts[3] | termios.ECHO tty.tcsetattr(sys.stdout, tty.TCSAFLUSH, self.orig_stdout_atts) if self.orig_stdin_atts: self.orig_stdin_atts[3] = self.orig_stdin_atts[3] | termios.ECHO tty.tcsetattr(sys.stdin, tty.TCSAFLUSH, self.orig_stdin_atts) if self.original_wincher: signal.signal(signal.SIGWINCH, self.original_wincher) try: self.cert_fd.close() except Exception: pass print('ciao.') if __name__ == '__main__': main() ########NEW FILE######## __FILENAME__ = shared import os __VERSION__ = '' __PLUGIN_VERSION__ = '' # Config settings USERNAME = '' SECRET = '' API_KEY = '' DEBUG = False SOCK_DEBUG = False ALERT_ON_MSG = True LOG_TO_CONSOLE = False BASE_DIR = os.path.expanduser(os.path.join('~', 'floobits')) # Shared globals DEFAULT_HOST = 'floobits.com' DEFAULT_PORT = 3448 SECURE = True SHARE_DIR = None COLAB_DIR = '' PROJECT_PATH = '' JOINED_WORKSPACE = False PERMS = [] STALKER_MODE = False AUTO_GENERATED_ACCOUNT = False PLUGIN_PATH = None WORKSPACE_WINDOW = None CHAT_VIEW = None CHAT_VIEW_PATH = None TICK_TIME = 100 AGENT = None IGNORE_MODIFIED_EVENTS = False VIEW_TO_HASH = {} FLOORC_PATH = os.path.expanduser(os.path.join('~', '.floorc')) ########NEW FILE######## __FILENAME__ = utils import re import time from collections import defaultdict try: from urllib.parse import urlparse assert urlparse except ImportError: from urlparse import urlparse try: from . import shared as G assert G except (ImportError, ValueError): import shared as G top_timeout_id = 0 cancelled_timeouts = set() timeout_ids = set() timeouts = defaultdict(list) def set_timeout(func, timeout, *args, **kwargs): global top_timeout_id timeout_id = top_timeout_id top_timeout_id += 1 if top_timeout_id > 100000: top_timeout_id = 0 def timeout_func(): timeout_ids.discard(timeout_id) if timeout_id in cancelled_timeouts: cancelled_timeouts.remove(timeout_id) return func(*args, **kwargs) then = time.time() + (timeout / 1000.0) timeouts[then].append(timeout_func) timeout_ids.add(timeout_id) return timeout_id def cancel_timeout(timeout_id): if timeout_id in timeout_ids: cancelled_timeouts.add(timeout_id) def call_timeouts(): now = time.time() to_remove = [] for t, tos in timeouts.copy().items(): if now >= t: for timeout in tos: timeout() to_remove.append(t) for k in to_remove: del timeouts[k] def parse_url(workspace_url): secure = G.SECURE owner = None workspace_name = None parsed_url = urlparse(workspace_url) port = parsed_url.port if not port: port = G.DEFAULT_PORT if parsed_url.scheme == 'http': if not port: port = 3148 secure = False result = re.match('^/([-\@\+\.\w]+)/([-\@\+\.\w]+)/?$', parsed_url.path) if not result: result = re.match('^/r/([-\@\+\.\w]+)/([-\@\+\.\w]+)/?$', parsed_url.path) if result: (owner, workspace_name) = result.groups() else: raise ValueError('%s is not a valid Floobits URL' % workspace_url) return { 'host': parsed_url.hostname, 'owner': owner, 'port': port, 'workspace': workspace_name, 'secure': secure, } ########NEW FILE######## __FILENAME__ = version FLOOTTY_VERSION = '2.1.4' ########NEW FILE########

[ "dyangUCI@github.com" ]

dyangUCI@github.com

dc5c45a0d9c44cc2b7f3bb35d23198d69dbd715b

e73430ff79c2d9325037bd07d0dbdf9cc7c93d84

/main.py

96f07d51325003fb5c336ddcad218beaa913f938

[]

no_license

GianBkk/python_les3_syntra

8232b6773f6d82ff819c1a6a9823d21cd471a5b0

1abb1c57c862fbc29d1a1b7245ede151e24b15f2

refs/heads/master

2023-07-10T23:32:59.059183

2021-08-20T22:38:45

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null

UTF-8

Python

false

35

py

# Hello Word print('Hello World7')

[ "gian200308@gmail.com" ]

gian200308@gmail.com

ee27313bde085575df70e1d42550c376748fe931

08a9dc04e6defa9dc9378bfbfbe0b6185af6a86a

/manager/views.py

78b92fee93ead9c43d6d958d58f90642c7277c7f

[]

no_license

Felicity-jt/50.008-Project-1

8ecc63d2302b2eaa4060f4c900d7fed2e958927c

960b5e57a39bfda1c31653798c23ddc051a2ff19

refs/heads/master

2021-08-24T00:40:27.886634

2017-12-07T09:14:12

null

0

null

UTF-8

Python

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2,191

py

from json import loads from django.http import Http404 from django.shortcuts import render from django.core.exceptions import PermissionDenied from django.views.decorators.http import require_POST from common.db import sql, page from common.utils import pagination from common.messages import NOT_STAFF from common.decorators import json_response @require_POST @json_response def new(request): """Add item or entity into inventory.""" if not request.user.is_staff: raise PermissionDenied(NOT_STAFF) s = """INSERT INTO item (id, name) VALUES (DEFAULT, %s)""" try: rq = loads(request.body) # sanitize before inserting values = (rq['name'],) except (ValueError, KeyError): return None sql(s, *values) return {} @json_response def stock(request, item_id): """Get or update current stock.""" if not request.user.is_staff: raise PermissionDenied(NOT_STAFF) q = 'SELECT id, price, quantity FROM item WHERE id = %s' if request.method == 'POST': # update price and/or quantity from post data s = """UPDATE item SET quantity = %s WHERE id = %s""" try: rq = loads(request.body) # sanitize before inserting values = (int(rq['quantity']),) except (ValueError, KeyError): return None sql(s, *values, item_id) try: r = sql(q, item_id)[0] except IndexError: raise Http404 return { 'id': r[0], 'price': r[1], 'quantity': r[2], } @json_response def stats(request, entity, year, month): """Get stats for entity.""" if not request.user.is_staff: raise PermissionDenied(NOT_STAFF) if entity not in ('item', 'company', 'creator'): raise Http404 q = """SELECT item_id, SUM(quantity) AS total FROM purchase_item INNER JOIN purchase p ON p.id = purchase_item.purchase_id WHERE YEAR(p.made_on) = %s AND MONTH(p.made_on) = %s GROUP BY item_id""" pg = pagination(request) pg['sort'].append('-total') return sql(q + page(**pg), year, month)

[ "kwokshungit@gmail.com" ]

kwokshungit@gmail.com

3761f78794812b198b0c941d3b519e3150947df5

88dde3533d8283452b780fd120d8da94a2231876

/lab1/encoders.py

e670db5d8e2da9dfbcba5f7d55128dd8dacf95cf

[]

no_license

jando16407/ControlofMobileRobots

035e654cd556138321eb8c442a8c8f535edbcfdb

10806892b812296bb5fc83124094a802596760b4

refs/heads/master

2020-03-28T17:45:50.229926

2018-09-16T01:49:10

148,688,281

0

null

UTF-8

Python

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2,469

py

import time import RPi.GPIO as GPIO import signal import sys import tty import termios # Pins that the encoders are connected to LENCODER = 17 RENCODER = 18 left = 0 right = 0 # declare tuple #counts = ("Left count : ", str(left), ", RIght count : ", str(right)); # The det_ch method will determine which key has been pressed def det_ch(): aa = sys.stdin.fileno() settings = termios.tcgetattr(aa) try: tty.setraw(sys.stdin.fileno()) key = sys.stdin.read(1) finally: termios.tcsetattr(aa, termios.TCSADRAIN, settings) return key # This function is called when the left encoder detects a rising edge signal. def onLeftEncode(pin): global left left += 1 display_ticks() # This function is called when the right encoder detects a rising edge signal. def onRightEncode(pin): global right right += 1 display_ticks() # This function displays current number of left and right ticks def display_ticks(): sys.stdout.write('\r') sys.stdout.write("Left encoder ticked! ") sys.stdout.write(str(left)) sys.stdout.write(" : Right encoder ticked! ") sys.stdout.write(str(right)) sys.stdout.flush() # This function is called when Ctrl+C is pressed. # It's intended for properly exiting the program. def ctrlC(signum, frame): print(str(left)) print("\n", str(right)) print("\nExiting") GPIO.cleanup() exit() # This function resets the tick count def resetCounts(): print("RESETCOUNTS CALLED") global left global right left = 0 right = 0 # This function return the tuple of tick counts def getCounts(): print("GETCOUNTS CALLED\n") return (str(left), str(right)) # Attach the Ctrl+C signal interrupt signal.signal(signal.SIGINT, ctrlC) # Set the pin numbering scheme to the numbering shown on the robot itself. GPIO.setmode(GPIO.BCM) # Set encoder pins as input # Also enable pull-up resistors on the encoder pins # This ensures a clean 0V and 3.3V is always outputted from the encoders. GPIO.setup(LENCODER, GPIO.IN, pull_up_down=GPIO.PUD_UP) GPIO.setup(RENCODER, GPIO.IN, pull_up_down=GPIO.PUD_UP) # Attach a rising edge interrupt to the encoder pins GPIO.add_event_detect(LENCODER, GPIO.RISING, onLeftEncode) GPIO.add_event_detect(RENCODER, GPIO.RISING, onRightEncode) # Prevent the program from exiting by adding a looping delay. while True: time.sleep(1) key_input = det_ch() if key_input == "g": print(getCounts()) elif key_input == "r": resetCounts() elif key_input == "c": GPIO.cleanup() print("Exiting") exit()

[ "jando16407c@gmail.com" ]

jando16407c@gmail.com

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'''tzinfo timezone information for US/Indiana_minus_Starke.''' from zpt._pytz.tzinfo import DstTzInfo from zpt._pytz.tzinfo import memorized_datetime as d from zpt._pytz.tzinfo import memorized_ttinfo as i class Indiana_minus_Starke(DstTzInfo): '''US/Indiana_minus_Starke timezone definition. See datetime.tzinfo for details''' zone = 'US/Indiana_minus_Starke' _utc_transition_times = [ d(1,1,1,0,0,0), d(1918,3,31,8,0,0), d(1918,10,27,7,0,0), d(1919,3,30,8,0,0), d(1919,10,26,7,0,0), d(1942,2,9,8,0,0), d(1945,8,14,23,0,0), d(1945,9,30,7,0,0), d(1947,4,27,8,0,0), d(1947,9,28,7,0,0), d(1948,4,25,8,0,0), d(1948,9,26,7,0,0), d(1949,4,24,8,0,0), d(1949,9,25,7,0,0), d(1950,4,30,8,0,0), d(1950,9,24,7,0,0), d(1951,4,29,8,0,0), d(1951,9,30,7,0,0), d(1952,4,27,8,0,0), d(1952,9,28,7,0,0), d(1953,4,26,8,0,0), d(1953,9,27,7,0,0), d(1954,4,25,8,0,0), d(1954,9,26,7,0,0), d(1955,4,24,8,0,0), d(1955,10,30,7,0,0), d(1956,4,29,8,0,0), d(1956,10,28,7,0,0), d(1957,4,28,8,0,0), d(1957,9,29,7,0,0), d(1958,4,27,8,0,0), d(1958,9,28,7,0,0), d(1959,4,26,8,0,0), d(1959,10,25,7,0,0), d(1960,4,24,8,0,0), d(1960,10,30,7,0,0), d(1961,4,30,8,0,0), d(1961,10,29,7,0,0), d(1962,4,29,8,0,0), d(1963,10,27,7,0,0), d(1967,4,30,8,0,0), d(1967,10,29,7,0,0), d(1968,4,28,8,0,0), d(1968,10,27,7,0,0), d(1969,4,27,8,0,0), 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d(2008,3,9,7,0,0), d(2008,11,2,6,0,0), d(2009,3,8,7,0,0), d(2009,11,1,6,0,0), d(2010,3,14,7,0,0), d(2010,11,7,6,0,0), d(2011,3,13,7,0,0), d(2011,11,6,6,0,0), d(2012,3,11,7,0,0), d(2012,11,4,6,0,0), d(2013,3,10,7,0,0), d(2013,11,3,6,0,0), d(2014,3,9,7,0,0), d(2014,11,2,6,0,0), d(2015,3,8,7,0,0), d(2015,11,1,6,0,0), d(2016,3,13,7,0,0), d(2016,11,6,6,0,0), d(2017,3,12,7,0,0), d(2017,11,5,6,0,0), d(2018,3,11,7,0,0), d(2018,11,4,6,0,0), d(2019,3,10,7,0,0), d(2019,11,3,6,0,0), d(2020,3,8,7,0,0), d(2020,11,1,6,0,0), d(2021,3,14,7,0,0), d(2021,11,7,6,0,0), d(2022,3,13,7,0,0), d(2022,11,6,6,0,0), d(2023,3,12,7,0,0), d(2023,11,5,6,0,0), d(2024,3,10,7,0,0), d(2024,11,3,6,0,0), d(2025,3,9,7,0,0), d(2025,11,2,6,0,0), d(2026,3,8,7,0,0), d(2026,11,1,6,0,0), d(2027,3,14,7,0,0), d(2027,11,7,6,0,0), d(2028,3,12,7,0,0), d(2028,11,5,6,0,0), d(2029,3,11,7,0,0), d(2029,11,4,6,0,0), d(2030,3,10,7,0,0), d(2030,11,3,6,0,0), d(2031,3,9,7,0,0), d(2031,11,2,6,0,0), d(2032,3,14,7,0,0), d(2032,11,7,6,0,0), d(2033,3,13,7,0,0), d(2033,11,6,6,0,0), d(2034,3,12,7,0,0), d(2034,11,5,6,0,0), d(2035,3,11,7,0,0), d(2035,11,4,6,0,0), d(2036,3,9,7,0,0), d(2036,11,2,6,0,0), d(2037,3,8,7,0,0), d(2037,11,1,6,0,0), ] _transition_info = [ i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CWT'), i(-18000,3600,'CPT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-21600,0,'CST'), 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i(-18000,3600,'CDT'), i(-21600,0,'CST'), i(-18000,3600,'CDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), i(-14400,3600,'EDT'), i(-18000,0,'EST'), ] Indiana_minus_Starke = Indiana_minus_Starke()

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#!/usr/bin/env python import util from collections import defaultdict import numpy as np import pandas as pd import csv_io import math def get_date_dataframe(date_column): return pd.DataFrame({ "SaleYear": [d.year for d in date_column], "SaleMonth": [d.month for d in date_column], "SaleDay": [d.day for d in date_column] }, index=date_column.index) def preprocess(): train, test = util.get_train_test_df() columns = set(train.columns) #columns.remove("SalesID") #columns.remove("SalePrice") #columns.remove("saledate") #train_fea = get_date_dataframe(train["saledate"]) #test_fea = get_date_dataframe(test["saledate"]) #parseColumns = ["UsageBand"] parseColumns = [ "UsageBand","fiBaseModel","fiModelSeries","fiModelDescriptor","ProductSize","ProductGroup","Drive_System","Enclosure","Forks","Pad_Type","Ride_Control","Stick","Transmission","Turbocharged","Blade_Extension","Blade_Width","Enclosure_Type","Engine_Horsepower","Hydraulics","Pushblock","Ripper","Scarifier","Tip_ControlCoupler","Coupler_System","Grouser_Tracks","Hydraulics_Flow","Track_Type","Thumb","Pattern_Changer","Grouser_Type","Backhoe_Mounting","Blade_Type","Travel_Controls","Differential_Type","Steering_Controls"] #"auctioneerID","state","ProductGroupDesc",,"fiSecondaryDesc" # this is redundant "fiModelDesc", and has too many options... # Q, AC, AL AR AS colDict = {} for col in parseColumns: colDict[col] = [] colMap = {} notInTest = [] for index, col in enumerate(train.columns): print "MAP:", col, index colMap[col] = index if col in parseColumns: #print "start" s = set(x for x in train[col].fillna(0)) # 0 if x == "" or not isinstance(x, float) else x s.update(x for x in test[col].fillna(0)) # math.isnan(x) colDict[col] = s print s if col == "fiBaseModel": a = set(x for x in train[col].fillna(0)) b = set(x for x in test[col].fillna(0)) print "fiBaseModel" print print # found 11 type in test not in train print [x for x in b if x not in a] print print # found several hundred in train that are not in test, try dropping these... print [x for x in a if x not in b] notInTest = [x for x in a if x not in b] SaleIDArr = [] trainSalePriceArr = [] count = 0 csv_io.delete_file("train1.csv") for row in train.iterrows(): trainSalePrice = [] rowVals = row[1].fillna(0) newSet = [] newRow = [] if rowVals["fiBaseModel"] not in notInTest: continue trainSalePrice.append(rowVals["SalePrice"]) trainSalePriceArr.append(trainSalePrice) SaleID = [] SaleID.append(rowVals["SalesID"]) SaleIDArr.append(SaleID) for col in colDict.keys(): for val in colDict[col]: if val == rowVals[col] : newRow.append(1) else: newRow.append(0) #newRow.append(rowVals["YearMade"]) # need to calculate age, sale date minus year newRow.append(rowVals["MachineHoursCurrentMeter"]) count += 1 if count % 10000 == 0: print "Count", count newSet.append(newRow) csv_io.write_delimited_file("train1.csv", newSet ,header=None, delimiter=",", filemode="a") csv_io.write_delimited_file("target.csv", trainSalePriceArr ,header=None, delimiter=",") csv_io.write_delimited_file("train_salesID.csv", SaleIDArr ,header=None, delimiter=",") # ------------------------------------------- SaleIDArr = [] count = 0 csv_io.delete_file("test1.csv") for row in test.iterrows(): rowVals = row[1].fillna(0) newSet = [] newRow = [] SaleID = [] SaleID.append(rowVals["SalesID"]) SaleIDArr.append(SaleID) for col in colDict.keys(): for val in colDict[col]: if val == rowVals[col] : newRow.append(1) else: newRow.append(0) #newRow.append(rowVals["YearMade"]) # need to calculate age, sale date minus year newRow.append(rowVals["MachineHoursCurrentMeter"]) count += 1 if count % 10000 == 0: print "Count", count newSet.append(newRow) csv_io.write_delimited_file("test1.csv", newSet ,header=None, delimiter=",", filemode="a") csv_io.write_delimited_file("test_salesID.csv", SaleIDArr ,header=None, delimiter=",") if __name__=="__main__": preprocess()

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""" WSGI config for mpproj project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/2.1/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'mpproj.settings') application = get_wsgi_application()

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import numpy as np from pyFTS.common import FuzzySet,FLR import fts class SeasonalFLRG(fts.FTS): def __init__(self, seasonality): self.LHS = seasonality self.RHS = [] def append(self, c): self.RHS.append(c) def __str__(self): tmp = str(self.LHS) + " -> " tmp2 = "" for c in sorted(self.RHS, key=lambda s: s.name): if len(tmp2) > 0: tmp2 = tmp2 + "," tmp2 = tmp2 + c.name return tmp + tmp2 class SeasonalFTS(fts.FTS): def __init__(self, name): super(SeasonalFTS, self).__init__(1, "SFTS") self.name = "Seasonal FTS" self.detail = "Chen" self.seasonality = 1 self.hasSeasonality = True def generateFLRG(self, flrs): flrgs = [] season = 1 for flr in flrs: if len(flrgs) < self.seasonality: flrgs.append(SeasonalFLRG(season)) flrgs[season].append(flr.RHS) season = (season + 1) % (self.seasonality + 1) if season == 0: season = 1 return (flrgs) def train(self, data, sets, seasonality): self.sets = sets self.seasonality = seasonality tmpdata = FuzzySet.fuzzySeries(data, sets) flrs = FLR.generateRecurrentFLRs(tmpdata) self.flrgs = self.generateFLRG(flrs) def forecast(self, data): ndata = np.array(data) l = len(ndata) ret = [] for k in np.arange(1, l): flrg = self.flrgs[data[k]] mp = self.getMidpoints(flrg) ret.append(sum(mp) / len(mp)) return ret

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from django.contrib import admin from .models import Course admin.site.register(Course)

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Senha = True resposta = input("Qual é a senha") while Senha: if resposta=="desisto": Senha = False else: Senha = True return resposta print("Você acertou a senha!")

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you@example.com

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#!/Users/jiwenyu/PycharmProjects/MyAI/venv/bin/python # EASY-INSTALL-ENTRY-SCRIPT: 'pip==9.0.1','console_scripts','pip' __requires__ = 'pip==9.0.1' import re import sys from pkg_resources import load_entry_point if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit( load_entry_point('pip==9.0.1', 'console_scripts', 'pip')() )

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665

py

#!/usr/bin/env python """Django's command-line utility for administrative tasks.""" import os import sys def main(): """Run administrative tasks.""" os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'recipebox.settings') try: from django.core.management import execute_from_command_line except ImportError as exc: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) from exc execute_from_command_line(sys.argv) if __name__ == '__main__': main()

[ "danielle@oakandivymedia.com" ]

danielle@oakandivymedia.com

d4efd4910a49742035a254ce235200d20ebfb4ca

e77027cb5ffa4754a5ac1cf8d1cd1e2035710cfe

/VectorComplexLibrary.py

75f3378e79e5fcb97984b6c1edbeea7dd22f7ffb

[]

no_license

wilmer-rodriguez-r/LibraryComplexVectors

36e5fc8bb19219cee3db327ace7c2406c61aead3

9fa83a829aaeb1e869376e4000389cf9b2ca941f

refs/heads/master

2023-03-02T17:04:03.423077

2021-02-09T15:07:34

336,027,282

0

null

UTF-8

Python

false

5,704

py

# Librería de funciones para vectores y matrices complejos import numpy as np def auxiliar(matriz_vector): # función que corrobora si es una matriz o un arreglo devolviendo la cantidad de columnas de este try: column = len(matriz_vector[0]) return column except TypeError: column = 1 return column def auxiliar_1(matriz_vector): # función que corrobora si es una matriz o un arreglo devolviendo un valor booleano try: len(matriz_vector[0]) return True except TypeError: return False def auxiliar_2(num_complex): # función que conjuga los números complejos real = num_complex.real imaginaria = -1 * num_complex.imag if imaginaria == 0: imaginaria = 0 if imaginaria < 0: num = str(real) + str(imaginaria) + 'j' else: num = str(real) + '+' + str(imaginaria) + 'j' return complex(num) def vectorSumaComplex(vector_1, vector_2): for i in range(len(vector_1)): vector_1[i] = vector_1[i] + vector_2[i] return vector_1[:] def vectorInverComplex(vector): for i in range(len(vector)): vector[i] = -1 * vector[i] return vector[:] def vectorMultEsComplex(vector, escalar): for i in range(len(vector)): vector[i] = escalar * vector[i] return vector[:] def matrizSumaComplex(vector_1, vector_2): rows = len(vector_1) colums = len(vector_1[0]) for i in range(rows): for j in range(colums): vector_1[i][j] = vector_1[i][j] + vector_2[i][j] return vector_1[:] def matrizInverComplex(matriz): matriz = [[-1 * matriz[j][k] for k in range(len(matriz[0]))] for j in range(len(matriz))] return matriz[:] def matrizMultEsComplex(matriz, escalar): matriz = [[escalar * matriz[j][k] for k in range(len(matriz[0]))] for j in range(len(matriz))] return matriz[:] def trasMatrizVector (matriz_vector): rows = len(matriz_vector) column = auxiliar(matriz_vector) if auxiliar_1(matriz_vector): aux = [[matriz_vector[k][j] for k in range(rows)] for j in range(column)] aux = (aux[0] if len(aux) == 1 else aux) else: aux = [[matriz_vector[j] for k in range(column)] for j in range(rows)] return aux def conjMatrizVector(matriz_vector): rows = len(matriz_vector) column = auxiliar(matriz_vector) if auxiliar_1(matriz_vector): for j in range(rows): for k in range(column): matriz_vector[j][k] = auxiliar_2(matriz_vector[j][k]) else: for j in range(rows): matriz_vector[j] = auxiliar_2(matriz_vector[j]) return matriz_vector[:] def adjuntMatrizVector (matriz_vector): return trasMatrizVector(conjMatrizVector(matriz_vector)) def multMatrices (matriz_a, matriz_b): rows_a, rows_b, column_a, column_b = len(matriz_a), len(matriz_b), auxiliar(matriz_a), auxiliar(matriz_b) if rows_b == column_a: aux = [[0 for i in range(column_b)] for j in range(rows_a)] for h in range(column_b): for j in range(rows_a): for k in range(column_a): aux[j][h] += matriz_a[j][k] * matriz_b[k][h] return aux else: return 'Las matrices no se pueden operar' def accion(matriz, vector): rows, columns, size = len(matriz), len(matriz[0]), len(vector) aux = [0 for i in range(rows)] for j in range(rows): for k in range(columns): aux[j] += matriz[j][k] * vector[k] return aux def dotProduct (vector_a, vector_b): size = len(vector_a) try: for i in range(size): int(vector_a[i]) suma = 0 for j in range(size): suma += vector_a[j] * vector_b[j] return suma except TypeError: vector_a = conjMatrizVector(vector_a[:]) suma = 0 for j in range(size): suma += complex(vector_a[j]) * complex(vector_b[j]) return suma def normVector(vector): try: for i in range(len(vector)): int(vector[i]) return (dotProduct(vector[:], vector[:]))**(1/2) except TypeError: return (dotProduct(vector[:], vector[:]))**(1/2) def disVectors(vector_a, vector_b): vector = vectorSumaComplex(vectorInverComplex(vector_a), vector_b) return normVector(vector) def matrizHermitian(matriz): matriz_a = conjMatrizVector(trasMatrizVector(matriz[:])) if matriz_a == matriz: return True else: return False def matrizUnitary(matriz): size = len(matriz) identidad = [[(1 if j == k else 0) for k in range(size)]for j in range(size)] matriz = multMatrices(matriz, conjMatrizVector(trasMatrizVector(matriz[:]))) if matriz == identidad: return True else: return False def tensorProduct(matriz_vector_0,matriz_vector_1): rows_0, columns_0, valor = len(matriz_vector_0), auxiliar(matriz_vector_0), auxiliar_1(matriz_vector_1) if columns_0 == 1 and valor: for j in range(rows_0): matriz_vector_0[j] = matrizMultEsComplex(matriz_vector_1[:], matriz_vector_0[j]) elif columns_0 == 1: for j in range(rows_0): matriz_vector_0[j] = vectorMultEsComplex(matriz_vector_1[:], matriz_vector_0[j]) elif columns_0 != 1 and valor: for j in range(rows_0): for k in range(columns_0): matriz_vector_0[j][k] = matrizMultEsComplex(matriz_vector_1[:], matriz_vector_0[j][k]) else: for j in range(rows_0): for k in range(columns_0): matriz_vector_0[j][k] = vectorMultEsComplex(matriz_vector_1[:], matriz_vector_0[j][k]) return matriz_vector_0[:]

[ "wilmer.rodriguez-r@mail.escuelaing.edu.co" ]

wilmer.rodriguez-r@mail.escuelaing.edu.co

a37479b83e3e6ebdfa280a2339adbc632b8a3439

2611d6ab0963ba5da8cec69559a6ad4b7efb92d9

/emojisss.py

f95a3d4789d4e416f67fe803c0f0d48a4f73054b

[]

no_license

myke-oliveira/curso-em-video-python3

f4108eebc8dc5fde1574dc2a8ab0f6eff7650e5d

97dc244ff50720190a134a1eb2fef9f8b43cdae3

refs/heads/master

2021-05-12T11:34:28.036631

2018-01-16T19:28:44

117,392,606

0

null

UTF-8

Python

false

54

py

import emoji print(emoji.emojize(':thumbs_up_sign:'))

[ "mykeapo@gmail.com" ]

mykeapo@gmail.com

511fe8b79650e5129209a33e6c7d768af423c6e6

2a1f4c4900693c093b2fcf4f84efa60650ef1424

/py/dome/backend/apps.py

fc8e9e1db58cfc9dbc955eb7df36461f862fe2b5

[ "BSD-3-Clause" ]

permissive

bridder/factory

b925f494303728fa95017d1ba3ff40ac5cf6a2fd

a1b0fccd68987d8cd9c89710adc3c04b868347ec

refs/heads/master

2023-08-10T18:51:08.988858

2021-09-21T03:25:28

null

0

null

UTF-8

Python

false

294

py

# Copyright 2016 The Chromium OS Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. from __future__ import unicode_literals from django.apps import AppConfig class BackendConfig(AppConfig): name = 'backend'

[ "chrome-bot@chromium.org" ]

chrome-bot@chromium.org

9d0d9428ad332411b938df93cd900f02fefc493a

f921b215086d6556885da0c50b68e4de861216ac

/src/helpers/operations.py

b533530fbdc6a9316593c2f4f7a1a166640e31d8

[]

no_license

tonaflcastelan/prueba-ing-backend

afee173d31d78139306a38a55d4e98f219281068

7c114be5e4c59c0e2b0fd3775ba237ac94e6f4a4

refs/heads/master

2022-12-03T23:58:36.924155

2020-08-04T00:17:54

284,596,408

0

null

2020-08-03T03:42:34

2020-08-03T03:42:33

null

UTF-8

Python

false

241

py

def get_average(value1, value2) -> float: """ Get average """ return (value1 + value2) / 2 def get_percent(dividend, divider) -> float: """ Get percent """ return round((float(dividend / divider)), 2) * 100

[ "tona.castelan16@gmail.com" ]

tona.castelan16@gmail.com

cb5e4cf9e89b4161efe98de831afd47a6290f0db

1c8a05b18d1e895a99e92c9d9d48f30296342a76

/2. socket通信.py

98e28c13d8edce629a2e35f4eaa157199c53bdfa

[]

no_license

codingtruman/socket-UDP

1190bbd1a5055bf6461d6cb2b499a81e234760f0

6b4e9839b14571f6472f6fc7b37514c31f353789

refs/heads/master

2023-01-04T18:38:37.356220

2020-11-04T01:20:21

null

0

null

UTF-8

Python

false

1,374

py

from socket import * # 创建TCP socket tcpSocket = socket(AF_INET, SOCK_STREAM) print('TCP socket created') # 设置地址，端口和要发送的数据 sendAddr = ('192.168.0.19', 3306) # 如果此处没写b，下面使用sendData时要变成sendData.encode('utf-8') sendData = b'ok, tcp' # 连接服务器和发送 # tcpSocket.connect(sendAddr) # tcpSocket.send(sendData) # 关闭socket tcpSocket.close() ############################################## # 创建UDP socket udpSocket = socket(AF_INET, SOCK_DGRAM) print('UDP socket created') # 绑定本地信息，如果一个网络程序不稳定，系统就会随机分配。但一般情况作为接收方时需要绑定 # bind()参数是个元祖 #IP一般不用写，表示本机任何一个IP，有几个网卡就几个IP udpSocket.bind(('', 3304)) # 设置地址，端口和要发送的数据 sendAddr = ('192.168.0.19', 3306) sendData = 'ok, 尼玛123' # 在这里就他妈的提前转换好编码 sendData = sendData.encode('utf-8') # 连接服务器和发送 udpSocket.sendto(sendData, sendAddr) # 等待接收方发送数据 # 设置一次只接收1024 bytes recvdata = udpSocket.recvfrom(1024) # recvData是个元祖 content, host_info = recvdata # 如果接收的是中文消息，用utf-8解码会报错的！ content = content.decode('gb2312') print(content, host_info) # 关闭socket udpSocket.close()

[ "maplewong04@gmail.com" ]

maplewong04@gmail.com

cc43cf0ec8d3d75f01f17a65aa8ee501efb3738b

6d08b4d926519dbb47b45addc53cd92f5f75e569

/app.py

799df4c64b398e9bacee9edcd9e21d237bd2a496

[]

no_license

elieu17/bellybuttonhmwk

f09daf2f381c9a23ce3b686e89d9d639d8a459ca

4a8439667aff6ec36a83e50af278c5546b797d77

refs/heads/master

2020-04-29T08:57:08.234124

2019-04-17T22:57:35

176,005,682

0

null

UTF-8

Python

false

2,886

py

import os import pandas as pd import numpy as np import sqlalchemy from sqlalchemy.ext.automap import automap_base from sqlalchemy.orm import Session from sqlalchemy import create_engine from flask import Flask, jsonify, render_template from flask_sqlalchemy import SQLAlchemy app = Flask(__name__) ################################################ # Database Setup ################################################# app.config["SQLALCHEMY_DATABASE_URI"] = "sqlite:///db/bellybutton.sqlite" db = SQLAlchemy(app) # reflect an existing database into a new model Base = automap_base() # reflect the tables Base.prepare(db.engine, reflect=True) # Save references to each table Samples_Metadata = Base.classes.sample_metadata Samples = Base.classes.samples @app.route("/") def index(): """Return the homepage.""" return render_template("index.html") @app.route("/names") def names(): """Return a list of sample names.""" # Use Pandas to perform the sql query stmt = db.session.query(Samples).statement df = pd.read_sql_query(stmt, db.session.bind) # Return a list of the column names (sample names) return jsonify(list(df.columns)[2:]) @app.route("/metadata/<sample>") def sample_metadata(sample): """Return the MetaData for a given sample.""" sel = [ Samples_Metadata.sample, Samples_Metadata.ETHNICITY, Samples_Metadata.GENDER, Samples_Metadata.AGE, Samples_Metadata.LOCATION, Samples_Metadata.BBTYPE, Samples_Metadata.WFREQ, ] results = db.session.query(*sel).filter(Samples_Metadata.sample == sample).all() # Create a dictionary entry for each row of metadata information sample_metadata = {} for result in results: sample_metadata["sample"] = result[0] sample_metadata["ETHNICITY"] = result[1] sample_metadata["GENDER"] = result[2] sample_metadata["AGE"] = result[3] sample_metadata["LOCATION"] = result[4] sample_metadata["BBTYPE"] = result[5] sample_metadata["WFREQ"] = result[6] print(sample_metadata) return jsonify(sample_metadata) @app.route("/samples/<sample>") def samples(sample): """Return `otu_ids`, `otu_labels`,and `sample_values`.""" stmt = db.session.query(Samples).statement df = pd.read_sql_query(stmt, db.session.bind) # Filter the data based on the sample number and # only keep rows with values above 1 sample_data = df.loc[df[sample] > 1, ["otu_id", "otu_label", sample]] sample_data.sort_values(by =[sample], ascending=False, inplace=True) # Format the data to send as json data = { "otu_ids": sample_data.otu_id.values.tolist(), "sample_values": sample_data[sample].values.tolist(), "otu_labels": sample_data.otu_label.tolist(), } return jsonify(data) if __name__ == "__main__": app.run()

[ "noreply@github.com" ]

elieu17.noreply@github.com

b217f0ad3fe6dbfaa9f4171e6b8a876290441a13

b80ab06996845b63d78158e9713e4f1ad7229ee7

/main.py

e14d58e06f9e5dcfadc2df6bf0025c32e3c3c5c5

[]

no_license

Pepega123/tracker

1bd96244a1d65f06292e20a3a81e07c86d70ba65

ad639d19cd1657d06e04afb32e91979603afd88f

refs/heads/master

2022-09-10T22:16:36.226686

2020-06-05T12:04:30

269,622,023

0

null

UTF-8

Python

false

6,171

py

import datetime import hashlib import logging import os import psutil import psycopg2 import time import atexit from db import * logger = logging.getLogger('tracker') logger.setLevel(logging.DEBUG) TOTAL_MINUTES = 0 NEW_DAY = False START_TIME = 0 CURRENT_DATE = datetime.date.today() CONN = psycopg2.connect(**config()) CUR = CONN.cursor() def get_hash(filename): # make a hash object h = hashlib.sha1() # open file for reading in binary mode with open(filename,'rb') as file: # loop till the end of the file chunk = 0 while chunk != b'': # read only 1024 bytes at a time chunk = file.read(1024) h.update(chunk) # return the hex representation of digest return h.hexdigest() def find_proc_by_hash(hash="fdd2fe36c6e859779f8e5e65155acf55d625f7f1"): #find by hash for p in psutil.process_iter(): try: #reduce computational intensity, remove for more thorough search if("C:\\Program Files (x86)\\" in p.exe()): if get_hash(p.exe()) == hash: return True except (psutil.AccessDenied, FileNotFoundError): pass return False def calc_time_diff(start_time, end_time): return int(time.mktime(end_time.timetuple()) - time.mktime(start_time.timetuple())) / 60 def execute_stmt(date, minutes, cur): global NEW_DAY #print(NEW_DAY) #new day, create new entry: if(NEW_DAY): stmnt = "INSERT INTO times(date, minutes) VALUES (\'" + str(date) + "\', " + str(minutes) + ");" NEW_DAY = False #same day, update entry: else: stmnt = "UPDATE times SET minutes = " + str(minutes) + " WHERE date = \'" + str(date) + "\';" logger.debug(stmnt) cur.execute(stmnt) def init(): fh = logging.FileHandler('log/spam.log') fh.setLevel(logging.DEBUG) info = logging.FileHandler('log/info.log') info.setLevel(logging.INFO) formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') fh.setFormatter(formatter) logger.addHandler(fh) logger.addHandler(info) logger.debug("-------------------------------") logger.debug("STARTING APPLICATION") def main(): logger.info("Initializing tracker") init() stmnt = "" global TOTAL_MINUTES global NEW_DAY global START_TIME global CURRENT_DATE UPDATE_INTERVAL = 10 INITIAL_INTERVAL = 10 CURRENT_DATE = datetime.date.today() params = config() conn = psycopg2.connect(**params) cur = conn.cursor() #proc_closed = True #queried_after_close = False #print(get_hash("C:\\Program Files (x86)\\World of Warcraft\\_classic_\\abc.exe")) # get date from previous run stmnt = "SELECT date FROM last_run;" cur.execute(stmnt) last_run_date = cur.fetchall()[0][0] logger.debug(stmnt) logger.debug(str(last_run_date)) if str(last_run_date) != str(CURRENT_DATE): NEW_DAY = True #same day, start counting from already counted hours else: stmnt = "SELECT minutes FROM times WHERE date = \'" + str(CURRENT_DATE) + "\';" cur.execute("SELECT minutes FROM times WHERE date = \'" + str(CURRENT_DATE) + "\';") TOTAL_MINUTES += cur.fetchall()[0][0] logger.debug(stmnt) logger.debug(str(TOTAL_MINUTES)) #TODO: maybe close connection to DB here and reopen at end? #outer while, wait for application to be opened while(True): time.sleep(INITIAL_INTERVAL) process_running = "WowClassic.exe" in (p.name() for p in psutil.process_iter()) or find_proc_by_hash() #process found if(process_running): logger.info("Process started!") START_TIME = datetime.datetime.now() #inner while, count time app is open while("WowClassic.exe" in (p.name() for p in psutil.process_iter()) or find_proc_by_hash()): logger.info("WoW running still...") #TODO: ADD LOGGING STATEMENTS time.sleep(UPDATE_INTERVAL) #wait 10 seconds between checks end_time = datetime.datetime.now() #calculate amount of time application was open elapsed_minutes = calc_time_diff(START_TIME, end_time) TOTAL_MINUTES = TOTAL_MINUTES + elapsed_minutes #wait for process to start else: continue logger.info("Total time active this session: " + str(elapsed_minutes)) logger.info("Total time active today: " + str(TOTAL_MINUTES)) #update last_run cur.execute("UPDATE last_run SET date = \'" + str(CURRENT_DATE) + "\';") #update/insert into times execute_stmt(CURRENT_DATE, TOTAL_MINUTES, cur) #update times #new day, create new entry: # if(NEW_DAY): # stmnt = "INSERT INTO times(date, minutes) VALUES (\'" + str(CURRENT_DATE) + "\', " + str(TOTAL_MINUTES) + ");" # logger.debug(stmnt) # cur.execute(stmnt) # #process has been closed, if it is opened again later it is (most likely) on the same day # NEW_DAY = False # #same day, update entry: # else: # stmnt = "UPDATE times SET minutes = " + str(TOTAL_MINUTES) + " WHERE date = \'" + str(CURRENT_DATE) + "\';" # logger.debug(stmnt) # cur.execute("UPDATE times SET minutes = " + str(TOTAL_MINUTES) + " WHERE date = \'" + str(CURRENT_DATE) + "\';") # cur.execute(stmnt) conn.commit() #start counting fresh next time process is opened #TOTAL_MINUTES = 0 #never reached, maybe close/open before each update instead? #conn.close() #cleanup, log times before exiting atexit.register(execute_stmt, CURRENT_DATE, TOTAL_MINUTES, CUR) if __name__ == "__main__": main()

[ "noreply@github.com" ]

Pepega123.noreply@github.com

091a0e98da2ac80625b44ff0b4fd86db82597c27

0e50b69d115d90eccec55b7049e5d8f5ee438ba3

/brabbl/accounts/migrations/0013_user_image.py

6b2bb515e6d0afc8c80631c7a3cc8641dcf7ed27

[]

no_license

strader07/brabbl-backend-django

bd7a5d3e328e3ff975e450e9fd8de933b2a3992c

795113ee7e1c3d7ed3b093f8c9435777a29bfd10

refs/heads/master

2023-05-15T05:31:51.422840

2021-06-04T16:12:23

373,679,407

2

0

null

UTF-8

Python

false

464

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('accounts', '0012_auto_20160308_1500'), ] operations = [ migrations.AddField( model_name='user', name='image', field=models.ImageField(blank=True, null=True, upload_to='images/profiles/', verbose_name='Profilbild'), ), ]

[ "v7sion@topdogtek.com" ]

v7sion@topdogtek.com

9532029f8f9affb83b76eb28c4c4b4ce1d9c037f

bf3d802cf7b75ab84fc0bfae125d9b0cc1aed1e4

/API/manager/salt.py

c39acfedaf0ef0d82652fed0385c66ddd4be0276

[]

no_license

AlesKas/BAK

cf93c6b2a7475139bbfc8833e811264efcf0d8ff

56f4ac00a523c4ac02da0b7e33590d0b3dd2b190

refs/heads/master

2023-04-21T10:46:44.359788

2021-05-12T14:17:40

197,364,568

0

null

UTF-8

Python

false

378

py

import json from utils.logger import initLogging from .base import GetRequest, BaseException from utils.db.model import NtwSalt from peewee import DoesNotExist LOGGER = initLogging() class Salt(GetRequest): @classmethod def handle_get(cls, **kwargs): salt = NtwSalt.get().salt response = {} response['salt'] = salt return response

[ "akaspare@redhat.com" ]

akaspare@redhat.com

c55382d209d32058d1850a42aceb160d7068f6a1

9a65cdc78a860ecc176985860f2d02a841b72ef2

/editors/vinegar.py

bef3383bb94eb863957f44686bc9bb7a51fb3207

[]

no_license

akanevs/dsp

4da0354c78b8c0b33bce94af471d3d65ef3e7c0c

7e97f2fbfdfd0a6647affcd74303ee8e4a30bde6

refs/heads/master

2021-01-22T18:15:30.340275

2017-09-18T02:26:01

100,755,288

0

null

2017-08-18T22:42:07

null

UTF-8

Python

false

123

py

print('This is not my first or even second file created using vim') print('This was was created by Alex in Millburn, NJ!')

[ "noreply@github.com" ]

akanevs.noreply@github.com

2baf8dc9a7b2bfb654cb56694bc8420624a2c939

7cb5a8a08d21f2e4ae2b5b0de3cd53b1074f772c

/aws_django/webproj/homepage/views.py

67a0fd3691812ad271e7c1d06af89b09fdcee0ac

[]

no_license

KDT-Hot6/Coogle

29d8778f8510dd14cc10dd7de8f11aab9cfe1e46

9dd742a022f209215df650f016f06bb2cbb0d3b9

refs/heads/main

2023-05-04T23:51:09.554583

2021-05-30T07:15:03

353,909,037

0

2

null

UTF-8

Python

false

5,005

py

from django.shortcuts import render from rest_framework.views import APIView from rest_framework.response import Response from rest_framework import status from elasticsearch import Elasticsearch from sentence_transformers import SentenceTransformer, util import numpy as np import json import re # Create your views here. ######################################## return html page ########################################## # def main(request): # return render(request, 'main.html', {}) # 식당 리스트를 보여주는 페이지 def getResListpage(request): print(request.GET) search = request.GET.get('q', '') if 'search_key' in request.GET: search = request.GET.get('search_key') info = getInfo(search) res_list = groupingBoard((jsonPaser(info))) content = {'res_list': res_list,} return render(request, 'res_list_page.html', content) # 메인 검색 페이지 def getSearchPage(request): return render(request, 'coogle_search.html') ####################################################################### ########################## elastic search ############################# ####################################################################### model_path = '/home/ubuntu/hot6/bh/KoSentenceBERT_SKTBERT/output/training_stsbenchmark_skt_kobert_model_-2021-03-28_05-25-43_best' embedder = SentenceTransformer(model_path) client = Elasticsearch() res_size = 18 #120 def getInfo(search): query = search vectors = embedder.encode(query, convert_to_tensor=True) query_vector = [vector.tolist() for vector in vectors] script_query = { "script_score": { "query": {"match_all": {}}, "script": { "source": "cosineSimilarity(params.query_vector, doc['comment_vector']) + 1.0", "params": {"query_vector": query_vector} } } } response = client.search( index='revd', body={ "size": res_size, "query": script_query # "_source": {"includes": ["res_id", "res_name", "comment", "adress", "keywords"]} } ) # data_list = response['hits'] return response ################################## funcs to preprocess restaurant infomation ####################### ###### elastic search에서 받아온 json 정보를 html에서 보여줄 수 있도록 파싱 def jsonPaser(info): # res_info_key = info['hits']['hits'][0]['_source'].keys() res_list = {} number = 0 for i in range(len(info['hits']['hits'])): # 'res_id', 'res_name', 'adress', 'comment', 'keywords' number += 1 res_comments = [] res_number = number res_id = info['hits']['hits'][i]['_source']['res_id'] res_name = info['hits']['hits'][i]['_source']['res_name'] res_addr = info['hits']['hits'][i]['_source']['adress'] res_comment = info['hits']['hits'][i]['_source']['comment'] res_keywords = info['hits']['hits'][i]['_source']['keywords'] #식당 주소 전처리 ('\n' -> ' ') res_addr = preprocessAddr(res_addr) # 리뷰 데이터가 1개만 있어서 type이 string일 때, type을 리스트로 만들어준다. # (만약, 같은 식당이 나오면 리스트들끼리 병합하기 위해) if type(res_comment) != type([]): res_comments.append(res_comment) else: res_comments = res_comment # res_id를 기준으로 같은 식당이 나오는지 검사 if res_list.get(res_id) == None: res_comments.sort(reverse=True) res_info = {'res_name':res_name, 'res_addr':res_addr, 'res_comment':res_comments, 'res_keywords':res_keywords, 'res_number': res_number, } res_list[res_id] = res_info else: comments = res_list[res_id]['res_comment'] + res_comments comments.sort(reverse=True) res_list[res_id]['res_comment'] = comments number -= 1 return res_list ###### 식당들을 6개씩 그룹핑 def groupingBoard(info): res_list = [] group = [] count = 0 for v in info.values(): if count == 0: group = [] group.append(v) count += 1 if count == 6: res_list.append(group) count = 0 return res_list def groupingPage(info): res_list = [] group = [] count = 0 for res_board in info: if count == 0: group = [] group.append(res_board) count += 1 if count == 2: res_list.append(group) count = 0 return res_list def preprocessAddr(addr): addr2 = re.sub('\n', '    ', addr) return addr2

[ "kbh122369@gmail.com" ]

kbh122369@gmail.com

395c2604b50278ae902f02181ae78d04c84bb3d9

23acc2a4c8ad278d998cde78eb2340bc138844de

/alibaba_scrawl/listen.py

ec93c236eb4a877cbf9570a6e3b9a5f763bef6ed

[]

no_license

jorliang/pthion_basic_learning

f915b137abd9116819cd0692d5d859285d68616c

425e01b322324947c93cfc9c345cfc2bafb492fe

refs/heads/master

2022-12-12T18:29:13.250193

2022-12-03T01:42:51

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py

import winsound import win32com.client import time import speech # speak_out = win32com.client.Dispatch('SAPI.SPVOICE') # speak_out = win32com.client.Dispatch('Word.Application') # def speak(str): # print(str) # speak_out.Speak(str) # winsound.PlaySound(str,winsound.SND_ASYNC) # # # ak='簡単' # time.sleep(1) # speak(ak) speech.say('でわ')

[ "liangjiao@imagingdynamics.com" ]

liangjiao@imagingdynamics.com

52b11a09076f3904dc2f45e1e998edf62a885d87

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/leetcode/algorithm/4.median-of-two-sorted-arrays.py

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[]

no_license

KIDJourney/algorithm

81c00186a6dfdc278df513d25fad75c78eb1bf68

e1cf8e12050b9f1419a734ff93f9c626fc10bfe0

refs/heads/master

2022-11-24T09:30:16.692316

2022-11-06T09:33:51

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# # @lc app=leetcode id=4 lang=python3 # # [4] Median of Two Sorted Arrays # # @lc code=start class Solution: def findMedianSortedArrays(self, nums1, nums2) -> float: return self.easy(nums1, nums2) def easy(self, nums1, nums2): result = [] idx1, idx2 = 0, 0 while True: if idx1 == len(nums1) and idx2 == (len(nums2)): break if idx1 == len(nums1): result.append(nums2[idx2]) idx2 += 1 continue if idx2 == len(nums2): result.append(nums1[idx1]) idx1 += 1 continue if nums1[idx1] > nums2[idx2]: result.append(nums2[idx2]) idx2 += 1 else: result.append(nums1[idx1]) idx1 += 1 mid = len(result) // 2 if len(result) % 2 == 0: return (result[mid] + result[mid-1]) / 2.0 else: return (result[mid]) # @lc code=end

[ "kingdeadfish@qq.com" ]

kingdeadfish@qq.com

de68899e48dd15c7bcd79c0be0f42079daac4b5c

05b9797a76bf0ee17f3d6ef812e5dd2a186a17fa

/jogo/models/conta.py

ab32d99b26083355e15848f3edf07d53d93b7565

[]

no_license

renatoaloi/desafio-jogo

e9b99d39ad46bfeca006297d492615782e008179

c2bb464f17132df2ece18e99d5bb35a767dfaa53

refs/heads/main

2023-03-06T20:57:29.912528

2021-02-22T15:34:53

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from sqlalchemy import Column, Integer, String, Float, ForeignKey from jogo.dao.database import Base class Conta(Base): __tablename__ = 'conta' id = Column(Integer, primary_key=True) jogo_id = Column(Integer, ForeignKey('jogo.id'), nullable=False) jogador_id = Column(Integer, ForeignKey('jogador.id'), nullable=True) saldo = Column(Float, nullable=False) def __init__(self, jogo_id, jogador_id, saldo): self.jogo_id = jogo_id self.jogador_id = jogador_id self.saldo = saldo def __repr__(self): return '<Conta %r>' % self.saldo

[ "renato.aloi@gmail.com" ]

renato.aloi@gmail.com

e56f0bd33da3d74267fd6ab2971ead15aa9263b8

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/experimental/serengeti/blankIBCC.py

649a35a733279dc7605d90eb8296b4e245101794

[ "Apache-2.0" ]

permissive

JiaminXuan/aggregation

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refs/heads/master

2020-12-11T01:49:42.977664

2015-05-22T16:21:15

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#!/usr/bin/env python __author__ = 'greghines' import numpy as np import matplotlib.pyplot as plt import csv import sys import os import pymongo import matplotlib.cbook as cbook sys.path.append("/home/greg/github/pyIBCC/python") import ibcc client = pymongo.MongoClient() db = client['serengeti_2014-07-28'] collection = db["serengeti_classifications"] collection2 = db["serengeti_subjects"] subjects = [] users = [] classifications = [] class_count = {} blank_count = {} retiredBlanks = {} with open("/home/greg/Databases/serengeti_ibcc.py","wb") as f: f.write("import numpy as np\n") f.write("scores = np.array([0,1])\n") f.write("nScores = len(scores)\n") f.write("nClasses = 2\n") f.write("inputFile = \"/home/greg/Databases/serengeti_ibcc.csv\"\n") f.write("outputFile = \"/home/greg/Databases/serengeti_ibcc.out\"\n") f.write("confMatFile = \"/home/greg/Databases/serengeti_ibcc.mat\"\n") f.write("nu0 = np.array([30,70])\n") f.write("alpha0 = np.array([[3, 1], [1,3]])\n") with open("/home/greg/Databases/serengeti_ibcc.csv","wb") as f: f.write("a,b,c\n") import datetime def update(individual_classifications): #start by removing all temp files try: os.remove("/home/greg/Databases/serengeti_ibcc.out") except OSError: pass try: os.remove("/home/greg/Databases/serengeti_ibcc.mat") except OSError: pass try: os.remove("/home/greg/Databases/serengeti_ibcc.csv.dat") except OSError: pass with open("/home/greg/Databases/serengeti_ibcc.csv","a") as f: for u, s, b in individual_classifications: f.write(str(u)+","+str(s)+","+str(b)+"\n") print datetime.datetime.time(datetime.datetime.now()) ibcc.runIbcc("/home/greg/Databases/serengeti_ibcc.py") print datetime.datetime.time(datetime.datetime.now()) def analyze(): with open("/home/greg/Databases/serengeti_ibcc.out","rb") as f: reader = csv.reader(f,delimiter=" ") for subject_index,p0,p1 in reader: subject_index = int(float(subject_index)) subject_id = subjects[subject_index] c = class_count[subject_id] if (float(p1) >= 0.995) and (c>= 2): if not(subject_id in retiredBlanks): retiredBlanks[subject_id] = c #print str(c) + " :: " + str(p1) i = 0 unknownUsers = [] for r in collection.find({"tutorial": {"$ne": True}}): try: user_name = r["user_name"] except KeyError: unknownUsers.append(r["user_ip"]) continue zooniverse_id = r["subjects"][0]["zooniverse_id"] if zooniverse_id in retiredBlanks: continue if ((i%10000) == 0) and (i > 0): print i update(classifications) classifications = [] analyze() if not(user_name in users): users.append(user_name) if not(zooniverse_id in subjects): subjects.append(zooniverse_id) class_count[zooniverse_id] = 0 blank_count[zooniverse_id] = 0 i += 1 user_index = users.index(user_name) subject_index = subjects.index(zooniverse_id) class_count[zooniverse_id] += 1 a = r["annotations"] if not("nothing" in a[-1]): assert('species' in a[0]) blank = 0 else: blank = 1 blank_count[zooniverse_id] += 1 classifications.append((user_index,subject_index,blank)) if i >= 300000: break #print len(unknownUsers) #print len(list(set(unknownUsers))) tBlank = 0 fBlank = 0 speciesList = ['blank','elephant','zebra','warthog','impala','buffalo','wildebeest','gazelleThomsons','dikDik','giraffe','gazelleGrants','lionFemale','baboon','hippopotamus','ostrich','human','otherBird','hartebeest','secretaryBird','hyenaSpotted','mongoose','reedbuck','topi','guineaFowl','eland','aardvark','lionMale','porcupine','koriBustard','bushbuck','hyenaStriped','jackal','cheetah','waterbuck','leopard','reptiles','serval','aardwolf','vervetMonkey','rodents','honeyBadger','batEaredFox','rhinoceros','civet','genet','zorilla','hare','caracal','wildcat'] errors = {s.lower():0 for s in speciesList} for zooniverse_id in retiredBlanks: r = collection2.find_one({"zooniverse_id" : zooniverse_id}) retire_reason = r["metadata"]["retire_reason"] if retire_reason in ["blank", "blank_consensus"]: tBlank += 1 else: fBlank += 1 print zooniverse_id + " :: " + str(r["location"]["standard"][0]) f = max(r["metadata"]["counters"].items(), key = lambda x:x[1]) print f try: errors[f[0].lower()] += 1 print str(blank_count[zooniverse_id]) + "/" + str(class_count[zooniverse_id]) except KeyError: print "---***" #print str(r["metadata"]["counters"].values()) print "==---" print tBlank print fBlank print np.mean(retiredBlanks.values()) print np.median(retiredBlanks.values()) print "===---" for s in speciesList: if errors[s.lower()] != 0: print s + " - " + str(errors[s.lower()])

[ "greg@zooniverse.org" ]

greg@zooniverse.org

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68ff38f2dd0188909737b395ac227ec0e205d024

/Project-2/src/UtilsModule.py

d2d03210a398be119b8953bc2db5d6cfbc88b347

[]

no_license

kushagraThapar/Data-Mining

7c3992c5efe820185e5197c8098168ae92e68cf9

658f3fdc8c4ea91d717cb36d5504d5e1fb803960

refs/heads/master

2021-01-18T15:40:23.412283

2017-01-29T08:49:04

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import sys def write_file(filename, text): try: f = open(filename, "w") f.write(text) f.close() except IOError: print("IOError occurred in file [" + filename + "]") exit_program() return def read_file(filename): try: f = open(filename, "rU") text = f.read() f.close() return text except FileNotFoundError: print("File not found with name [" + filename + "]") except IOError: print("IOError occurred in file [" + filename + "]") exit_program() def process_tweets(tweet_data): if tweet_data is None or tweet_data.strip() is "": print("Tweet Data is Empty") exit_program() for single_row in tweet_data.split("\n"): single_row = single_row.strip() single_row_array = single_row.split(",", 3) if len(single_row_array) >= 3: last_index = single_row_array[3].rfind("\"") tweet = single_row_array[3][0:last_index + 1] tweet_class = single_row_array[3][last_index + 2:last_index + 3] def exit_program(): print("Program will exit now... ") sys.exit(1)

[ "kthapa2@uic.edu" ]

kthapa2@uic.edu

82f5cd9bfe71e1f9c34be4f1d8c1789d269f969b

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/apps/forums/migrations/0002_auto_20190408_2007.py

b928de461230382f7b0e27ca992d15780a476ae9

[]

no_license

xiaoyaochen/ACshare

8f7e294724d90925f9fb80799c9fbd3680c01057

482985231e0e6d8632c8504a30f994ba246a060a

refs/heads/master

2020-05-07T11:57:43.663344

2019-04-20T14:55:55

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# Generated by Django 2.0 on 2019-04-08 20:07 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('forums', '0001_initial'), ] operations = [ migrations.RenameField( model_name='forumscomment', old_name='reviewer', new_name='user', ), ]

[ "1595029296@qq.com" ]

1595029296@qq.com

15e3cb84a94201fa536f06f31f13a17e5a8b6dfb

5f809898a9f153d8645205aa601b2b3083beafa1

/krrThomas/searchStat/plot_structs_near_best.py

e0263c56ba0312ee7915e88edc7e6a07acbb6a67

[]

no_license

MaltheBisbo/learningForces

ea1b258e115327e1e0876a60345366f349afb1ac

7a726a5931454534585563dd607faf75c5d706c6

refs/heads/master

2021-01-23T22:31:02.654738

2018-12-25T21:48:54

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2018-12-25T21:48:55

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import numpy as np from scipy.spatial.distance import euclidean from scipy.spatial.distance import cdist import matplotlib.pyplot as plt from ase.io import read, write from ase.visualize import view from gaussComparator import gaussComparator from featureCalculators_multi.angular_fingerprintFeature_cy import Angular_Fingerprint from delta_functions_multi.delta import delta as deltaFunc from krr_errorForce import krr_class def plot_near_best(traj, MLmodel): Ndata = len(traj) # Sort traj after energy E = np.array([a.get_potential_energy() for a in traj]) index_best = np.argmin(E) a_best = traj[index_best] f_traj = MLmodel.featureCalculator.get_featureMat(traj) f_best = MLmodel.featureCalculator.get_feature(a_best) d = cdist(f_best.reshape((1,len(f_best))), f_traj, metric='euclidean') index_closest = np.argsort(d[0])[:5] print('d:\n', d[0][index_closest]) print('E:\n', E[index_closest]) traj_nearby = [traj[i] for i in index_closest] return traj_nearby if __name__ == '__main__': n = 2 i = 0 traj_init = read('/home/mkb/DFT/gpLEA/anatase/step/sanity_check/test_new_calc/runs{}/run{}/global{}_initTrain.traj'.format(n,i,i), index=':') traj_sp = read('/home/mkb/DFT/gpLEA/anatase/step/sanity_check/test_new_calc/runs{}/run{}/global{}_spTrain.traj'.format(n,i,i), index=':') traj = traj_init + traj_sp #ref = read('/home/mkb/DFTB/TiO_2layer/ref/Ti13O26_GM_done.traj', index='0') ### Set up feature ### # Template structure a = traj[0] # Radial part Rc1 = 6 binwidth1 = 0.2 sigma1 = 0.2 # Angular part Rc2 = 4 Nbins2 = 30 sigma2 = 0.2 gamma = 2 # Radial/angular weighting eta = 20 use_angular = True # Initialize feature featureCalculator = Angular_Fingerprint(a, Rc1=Rc1, Rc2=Rc2, binwidth1=binwidth1, Nbins2=Nbins2, sigma1=sigma1, sigma2=sigma2, gamma=gamma, eta=eta, use_angular=use_angular) ### Set up KRR-model ### comparator = gaussComparator(featureCalculator=featureCalculator, max_looks_like_dist=0.2) delta_function = deltaFunc(atoms=a, rcut=6) krr = krr_class(comparator=comparator, featureCalculator=featureCalculator, delta_function=delta_function, bias_std_add=0) traj_nearby = plot_near_best(traj, krr) view(traj_nearby)

[ "mkb@s81n11.grendel.cscaa.dk" ]

mkb@s81n11.grendel.cscaa.dk

7859135534e30b04d89d94a136f8d0e24d12d03c

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/plots.py

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[ "MIT" ]

permissive

ivastar/wfc3_gyro

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refs/heads/master

2021-01-15T08:37:50.860268

2016-11-16T14:59:51

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import matplotlib import matplotlib.pyplot as plt from matplotlib.figure import Figure import matplotlib.gridspec as gridspec import pylab import unicorn import astropy from astropy.table import Table as table from astropy.io import fits import numpy as np import glob, os def mag_radius(): from matplotlib.ticker import ScalarFormatter import my_python.mk_region_file gabe = table.read('../REF/cosmos-wide_v0.3_drz_bkg_sci.cat', format='ascii.sextractor') orig = table.read('/3DHST/Photometry/Release/v4.0/COSMOS/Detection/cosmos_3dhst.v4.0.F160W_orig.cat', format='ascii.sextractor') cat = table.read('test7_drz_sci.cat', format='ascii.sextractor') top = 0.075 bottom = 0.1 left = 0.15 fig = unicorn.catalogs.plot_init(xs=10,aspect=0.5, left=left, right=0.1, bottom=bottom, top=top, NO_GUI=False) fig.subplots_adjust(wspace=0.15) fig.subplots_adjust(hspace=0.1) fs = 10 matplotlib.rc('xtick',labelsize=fs) matplotlib.rc('ytick',labelsize=fs) gs1 = gridspec.GridSpec(1,2) ax1 = fig.add_subplot(gs1[0,0], ylim=[0.8, 20], xlim=[14,26]) ax1.plot(orig['MAG_AUTO'],orig['FLUX_RADIUS']*0.06/0.1, '.', color='0.7',markersize=0.5) ax1.plot(cat['MAG_AUTO'],cat['FLUX_RADIUS'], 'o', color='black', markersize=1, alpha=0.5) ax1.set_xlabel('MAG_AUTO F160W') ax1.set_ylabel('FLUX_RADIUS') ax1.set_yscale('log') cr = (cat['FLUX_RADIUS']*0.1/0.06 < 2.) stars = (cat['MAG_AUTO'] > 15.) & (cat['MAG_AUTO'] < 22.) & (cat['FLUX_APER_5']/cat['FLUX_APER'] > 1.1) & (cat['FLUX_APER_5']/cat['FLUX_APER'] < 1.2) #stars = (cat['MAG_AUTO'] > 15.) & (cat['MAG_AUTO'] < 23.) & (cat['FLUX_RADIUS']*0.1/0.06 < 5.15 - 0.115*cat['MAG_AUTO']) & (cat['FLUX_RADIUS']*0.1/0.06 > 2.1) #ax1.plot(cat['MAG_AUTO'][cr],cat['FLUX_RADIUS'][cr], 'o', color='blue', markersize=2, alpha=1.0) ax1.plot(cat['MAG_AUTO'][stars],cat['FLUX_RADIUS'][stars], 'o', color='red', markersize=2, alpha=1.0, markeredgecolor='red') print 'STARS: mean: {} / median{}'.format(np.mean(cat['FWHM_IMAGE'][stars]), np.median(cat['FWHM_IMAGE'][stars])) #yy_select = -0.115*np.array([14.,23.]) +5.15 #ax1.plot(np.array([14.,23.]), yy_select,'--',color='red') #ax1.plot([23.,23.], np.array([2.1, yy_select[-1]]), '--',color='red') #ax1.plot([14.,23.], [2.1,2.1],'--',color='red') ax1.yaxis.set_major_formatter(ScalarFormatter()) ax2 = fig.add_subplot(gs1[0,1], ylim=[0.5,4], xlim=[14,26]) #ax2.plot(orig['MAG_AUTO'],orig['FLUX_RADIUS'], '.', color='0.7',markersize=0.5) #ax2.plot(gabe['MAG_AUTO'],gabe['FLUX_RADIUS']*0.1/0.06, 'o', color='red', markersize=1., alpha=0.5) ax2.plot(orig['MAG_AUTO'], orig['FLUX_APER_5']/orig['FLUX_APER'], '.', color='0.7',markersize=0.5) ax2.plot(cat['MAG_AUTO'], cat['FLUX_APER_5']/cat['FLUX_APER'], 'o', color='black', markersize=1., alpha=0.5) ax2.plot(cat['MAG_AUTO'][stars], cat['FLUX_APER_5'][stars]/cat['FLUX_APER'][stars], 'o', color='red', markersize=2., alpha=1.0, markeredgecolor='red') ax2.plot(cat['MAG_AUTO'][cr], cat['FLUX_APER_5'][cr]/cat['FLUX_APER'][cr], 'o', color='blue', markersize=2., alpha=1.0) ax2.set_xlabel('MAG_AUTO F160W') ax2.set_ylabel('Flux (2.0\")/Flux (0.5\")') #ax2.set_title('PIPELINE FLTS (GABE)') ax2.yaxis.set_major_formatter(ScalarFormatter()) my_python.mk_region_file.mk_region_file_from_lists(cat['X_WORLD'][stars],cat['Y_WORLD'][stars],outfile = 'stars', printids='no', color='cyan') my_python.mk_region_file.mk_region_file_from_lists(cat['X_WORLD'][cr],cat['Y_WORLD'][cr],outfile = 'cr', printids='no', color='yellow') plt.show(block=False) fig.savefig('mag_radius.pdf', dpi=200, transparent=False) fig.savefig('mag_radius.png', dpi=200, transparent=False) def noise_distribution(master_root='icxe15010'): import threedhst import stwcs import scipy import scipy.optimize import unicorn import matplotlib import matplotlib.pyplot as plt from matplotlib.ticker import MaxNLocator import matplotlib.gridspec as gridspec import drizzlepac from drizzlepac import astrodrizzle master_asn = threedhst.utils.ASNFile('{}_asn.fits'.format(master_root)) #print 'Read files...' ref = fits.open('{}_drz_sci.fits'.format(master_root)) ref_wcs = stwcs.wcsutil.HSTWCS(ref, ext=0) seg = fits.open('{}_drz_seg.fits'.format(master_root)) seg_data = np.cast[np.float32](seg[0].data) yi, xi = np.indices((1014,1014)) # read candels candels = table.read('candels_noise.txt', format='ascii') # Make plot fs=8. matplotlib.rc('xtick',labelsize=fs) matplotlib.rc('ytick',labelsize=fs) fig = unicorn.catalogs.plot_init(xs=10., aspect=0.5, fontsize=fs, left=0.1, right=0.1, top=0.1, bottom=0.1) gs = gridspec.GridSpec(2,4,top=0.95, bottom=0.1) fig.subplots_adjust(wspace=0.05) fig.subplots_adjust(hspace=0.1) fp = open('sigma_table.txt','a') #### Loop through the pointings in this orbit for j, root in enumerate(master_asn.exposures): asn = threedhst.utils.ASNFile('{}_asn.fits'.format(root)) ax = fig.add_subplot(gs[j]) if j == 0: flt_color='blue' else: flt_color='red' #### Loop through FLTs for exp in asn.exposures: NSAMP = len(asn.exposures) flt = fits.open('{}_flt.fits'.format(exp)) flt_wcs = stwcs.wcsutil.HSTWCS(flt, ext=1) if flt[1].header['BG_SUB'] == 'No': flt[1].data -= flt[1].header['MDRIZSKY'] if exp == asn.exposures[0]: print 'Segmentation image: {}_blot.fits'.format(exp) blotted_seg = astrodrizzle.ablot.do_blot(seg_data, ref_wcs, flt_wcs, 1, coeffs=True, interp='nearest', sinscl=1.0, stepsize=10, wcsmap=None) mask = (blotted_seg == 0) & (flt['DQ'].data == 0) & (xi > 10) & (yi > 10) & (xi < 1004) & (yi < 1004) n, bin_edge, patch = ax.hist(flt[1].data[mask], bins=300, range=[-3,3], color='0.5', alpha=0.5, histtype='step', normed=True) if exp == asn.exposures[0]: centers = (bin_edge[:-1] + (bin_edge[1:] - bin_edge[:-1])/2) flt_coeff, flt_var = scipy.optimize.curve_fit(gauss, centers, n, p0=[np.max(n),0.,1.]) drz = fits.open('{}_drz_sci.fits'.format(root)) drz_wcs = stwcs.wcsutil.HSTWCS(drz, ext=0) drz_sh = np.shape(drz[0].data) dyi, dxi = np.indices(drz_sh) blotted_seg = astrodrizzle.ablot.do_blot(seg_data, ref_wcs, drz_wcs, 1, coeffs=False, interp='nearest', sinscl=1.0, stepsize=10, wcsmap=None) mask = (blotted_seg == 0) & (dxi > 10) & (dyi > 10) & (dxi < drz_sh[1]-10) & (dyi < drz_sh[0]-10) n, bin_edge, patch = ax.hist(drz[0].data[mask], bins=100, range=[-1.,1.], color='black', alpha=1.0, histtype='step', normed=True) centers = (bin_edge[:-1] + (bin_edge[1:] - bin_edge[:-1])/2) coeff, var = scipy.optimize.curve_fit(gauss, centers, n, p0=[np.max(n),0.,1.]) flt = fits.open('{}_flt.fits'.format(root)) flt_wcs = stwcs.wcsutil.HSTWCS(flt, ext=1) blotted_seg = astrodrizzle.ablot.do_blot(seg_data, ref_wcs, flt_wcs, 1, coeffs=True, interp='nearest', sinscl=1.0, stepsize=10, wcsmap=None) mask = (blotted_seg == 0) & (flt['DQ'].data == 0) & (xi > 10) & (yi > 10) & (xi < 1004) & (yi < 1004) n, bin_edge, patch = ax.hist(flt[1].data[mask], bins=100, range=[-1.,1.], color=flt_color, alpha=1.0, histtype='step', normed=True) centers = (bin_edge[:-1] + (bin_edge[1:] - bin_edge[:-1])/2) flt_orig_coeff, flt_orig_var = scipy.optimize.curve_fit(gauss, centers, n, p0=[np.max(n),0.,1.]) if root == master_asn.exposures[0]: flag = 0 else: flag = 1 fp.write('{}\t{:7.4f}\t{:7.4f}\t{:7.2f}\t{:7.4f}\t{}\n'.format(root, np.abs(flt_orig_coeff[2]), np.abs(coeff[2]), flt[1].header['SAMPTIME'], flt[1].header['MDRIZSKY'],flag)) ### plot candels #ax.bar(candels['centers'], 4.5*candels['n']/np.max(candels['n']), width=0.001, align='center', edgecolor='orange', color='orange', alpha=0.3) ax.set_ylim([0, 5.0]) ax.set_xlim([-3.0, 3.0]) ax.yaxis.set_major_locator(MaxNLocator(integer=True)) if j == 0 or j==4: ax.set_ylabel('Normalized N', fontsize=fs) else: ax.set_yticklabels([]) if j > 3: ax.set_xlabel('e$^-$/s', fontsize=fs) else: ax.set_xticklabels([]) ax.set_title(root, fontsize=fs) ax.text(-2.5, 4.5,'$\sigma_{reads}$ = %4.3f' % (flt_coeff[2]), color='0.5', fontsize=fs) ax.text(-2.5, 4.,'$\sigma_{FLT}$ = %4.3f' % (flt_orig_coeff[2]), color=flt_color, fontsize=fs) ax.text(-2.5, 3.5,'$\sigma_{DRZ}$ = %4.3f' % (coeff[2]), color='black', fontsize=fs) #ax.text(-2.5, 3.0,'$\sigma_{CAND}$ = %4.3f' % (4.44509564e-03), color='orange', fontsize=fs) plt.show(block=False) fig.savefig('{}_noise.png'.format(master_root), dpi=200, transparent=False) def candels_mosaic_noise(): import scipy mos = fits.open('/3DHST/Photometry/Release/v4.0/COSMOS/HST_Images/cosmos_3dhst.v4.0.F160W_orig_sci.fits') wht = fits.open('/3DHST/Photometry/Release/v4.0/COSMOS/HST_Images/cosmos_3dhst.v4.0.F160W_orig_wht.fits') seg = fits.open('/3DHST/Photometry/Release/v4.0/COSMOS/Detection/cosmos_3dhst.v4.0.F160W_seg.fits.gz') mask = (seg[0].data == 0) & (wht[0].data != 0) n, bin_edge = np.histogram(mos[0].data[mask], bins=100, range=[-0.05,0.05], normed=True) centers = (bin_edge[:-1] + (bin_edge[1:] - bin_edge[:-1])/2) coeff, var = scipy.optimize.curve_fit(gauss, centers, n, p0=[np.max(n),0.,0.01]) print 'Gaussian coeffs: {}'.format(coeff) t = table([centers,n], names =('centers','n')) t.write('candels_noise.txt', format='ascii') def overall_offsets(): import glob import matplotlib.colors as colors import matplotlib.cm as cmx files = glob.glob('shifts_icxe*010.txt') fig = unicorn.catalogs.plot_init(xs=10.,aspect=0.24, left=0.12, right=0.05, bottom=0.15, top=0.15, NO_GUI=False) gs = gridspec.GridSpec(1,4,top=0.9, bottom=0.15) fig.subplots_adjust(wspace=0.17) fig.subplots_adjust(hspace=0.1) fs = 8 jet = cm = plt.get_cmap('jet_r') cNorm = colors.Normalize(vmin=0, vmax=9) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) for j, file in enumerate(files): print file, '{}'.format(file.split('_')[1].split('.')[0]) ax = fig.add_subplot(gs[j]) if file.startswith('shifts_icxe15'): ax.set_xlim([-5.,70.]) ax.set_ylim([-5.,20.]) if file.startswith('shifts_icxe16'): ax.set_xlim([-5.,50.]) ax.set_ylim([-10.,5.]) if file.startswith('shifts_icxe17'): ax.set_xlim([-50.,5.]) ax.set_ylim([-10.,5.]) if file.startswith('shifts_icxe18'): ax.set_xlim([-40.,5.]) ax.set_ylim([-5.,40.]) ax.set_xlabel('$\Delta$ x [pix]', fontsize=fs, labelpad=0.1) if j == 0: ax.set_ylabel('$\Delta$ y [pix]', fontsize=fs) ax.set_title('{}'.format(file.split('_')[1].split('.')[0]), fontsize=fs) cc = 0. with open(file) as f: for line in f: if not line.startswith('#'): data = line.split() cc += 1. color = scalarMap.to_rgba(cc) #ax.arrow(0.,0., float(data[1]), float(data[2]), head_width=0., head_length=0., fc=color, ec = color) ax.annotate("",xy=(float(data[1]), float(data[2])), xytext=(0,0), arrowprops=dict(arrowstyle='->', color=color)) plt.show(block=False) fig.savefig('overall_offsets.png', dpi=200, transparent=False) def overall_offsets_vs_distance(): import glob import matplotlib.colors as colors import matplotlib.cm as cmx files = glob.glob('shifts_icxe*010.txt') fig = unicorn.catalogs.plot_init(xs=10.,aspect=0.47, left=0.2, right=0.05, bottom=0.15, top=0.15, NO_GUI=False) gs = gridspec.GridSpec(1,2,top=0.9, bottom=0.15) fig.subplots_adjust(wspace=0.2) fig.subplots_adjust(hspace=0.2) fs = 10 matplotlib.rc('xtick',labelsize=fs) matplotlib.rc('ytick',labelsize=fs) jet = cm = plt.get_cmap('jet_r') cNorm = colors.Normalize(vmin=0, vmax=8) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) ax1 = fig.add_subplot(gs[0]) ax2 = fig.add_subplot(gs[1]) lines = ['-','--','-.',':'] labels = ['COSMOS-15', 'COSMOS-16', 'COSMOS-17','COSMOS-18'] for j, file in enumerate(files): print file root = '{}'.format(file.split('_')[1].split('.')[0]) ax1.set_xlim([-0.5,9.]) ax1.set_ylim([-0.005,0.15]) ax1.set_xlabel('Commanded Offset Relative to First Position\n[arcmin]', fontsize=fs, labelpad=0.1) ax1.set_ylabel('Offset from Commanded Position\n[arcmin]', fontsize=fs) root = '{}'.format(file.split('_')[1].split('.')[0]) data = table.read(file, format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) small_off = np.sqrt(data['x']**2 + data['y']**2)*0.12/60. #colors = (scalarMap.to_rgba(cc) for cc in range(len(small_off))) big_off = [0.0] drift_rate = [0.0] origin = fits.open(data['file'][0]) x_orig, y_orig = origin[1].header['CRVAL1'], origin[1].header['CRVAL2'] for k, file in enumerate(data['file'][1:]): flt = fits.open(file) x, y = flt[1].header['CRVAL1'], flt[1].header['CRVAL2'] big_off.append(60.*np.sqrt((x_orig-x)**2 + (y_orig-y)**2)) if k+1 < 4: t_exp = 255 else: t_exp = 277 drift = table.read(file.split('_')[0]+'_shifts.txt', format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) drift_rate.append(25.*np.sqrt((drift['x'][0]-drift['x'][-1])**2 + (drift['y'][0]-drift['y'][-1])**2)/t_exp) print len(small_off), len(big_off) ax1.plot(big_off, small_off,linestyle=lines[j], color='0.5', label=labels[j], zorder=0) ax1.scatter(big_off, small_off, c=range(len(small_off)), cmap='jet', s=35., edgecolors='black', alpha=0.7) ax1.legend(loc='upper left', frameon=False, labelspacing=0.8, fontsize=9) ax2.set_xlim([-0.5, 9.]) ax2.set_ylim([-0.01,0.5]) ax2.set_xlabel('Commanded Offset Relative to First Position\n[arcmin]', fontsize=fs, labelpad=0.1) ax2.set_ylabel('Drift Rate During Observations\n[pix per 25 seconds]', fontsize=fs) ax2.plot(big_off, drift_rate,linestyle=lines[j], color='0.5', zorder=0) ax2.scatter(big_off, drift_rate, c=range(len(small_off)), cmap='jet', s=35., edgecolors='black', alpha=0.7) plt.show(block=False) fig.savefig('overall_offsets_vs_distance.png', dpi=200, transparent=False) def overall_offsets_vs_time(): import glob import matplotlib.colors as colors import matplotlib.cm as cmx files = glob.glob('shifts_icxe*010.txt') fig = unicorn.catalogs.plot_init(xs=10.,aspect=0.47, left=0.2, right=0.05, bottom=0.15, top=0.15, NO_GUI=False) gs = gridspec.GridSpec(1,2,top=0.9, bottom=0.15) fig.subplots_adjust(wspace=0.2) fig.subplots_adjust(hspace=0.2) fs = 10 matplotlib.rc('xtick',labelsize=fs) matplotlib.rc('ytick',labelsize=fs) jet = cm = plt.get_cmap('jet_r') cNorm = colors.Normalize(vmin=0, vmax=8) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) ax1 = fig.add_subplot(gs[0]) ax2 = fig.add_subplot(gs[1]) time = np.array([0, 368, 713, 1060, 1405, 1777, 2147, 2519]) + 333. lines = ['-','--','-.',':'] labels = ['COSMOS-15', 'COSMOS-16', 'COSMOS-17','COSMOS-18'] for j, file in enumerate(files): root = '{}'.format(file.split('_')[1].split('.')[0]) ax1.set_xlim([-5., 3100.]) ax1.set_ylim([-0.005,0.15*60.]) ax1.set_xlabel('Time Since Beginning of Orbit\n[seconds]', fontsize=fs) ax1.set_ylabel('Offset from Commanded Position\n[arcsec]', fontsize=fs) root = '{}'.format(file.split('_')[1].split('.')[0]) data = table.read(file, format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) small_off = np.sqrt(data['x']**2 + data['y']**2)*0.12 #colors = (scalarMap.to_rgba(cc) for cc in range(len(small_off))) drift_rate = [0.0] for k, file in enumerate(data['file'][1:]): if k+1 < 4: t_exp = 255 else: t_exp = 277 drift = table.read(file.split('_')[0]+'_shifts.txt', format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) drift_rate.append(25.*np.sqrt((drift['x'][0]-drift['x'][-1])**2 + (drift['y'][0]-drift['y'][-1])**2)/t_exp) ax1.plot(time, small_off, linestyle=lines[j], color='0.5', label=labels[j], zorder=0) ax1.scatter(time, small_off, c=range(len(small_off)), cmap='jet', s=35., edgecolors='black', alpha=0.7) ax1.legend(loc='upper left', frameon=False, labelspacing=0.8, fontsize=9) ax2.set_xlim([-5., 3100.]) ax2.set_ylim([-0.01,0.5]) ax2.set_xlabel('Time Since Beginning of Orbit\n[seconds]', fontsize=fs) ax2.set_ylabel('Drift Rate During Pointing\n[pix per 25 seconds]', fontsize=fs) ax2.plot(time, drift_rate,linestyle=lines[j], color='0.5', zorder=0) ax2.scatter(time, drift_rate, c=range(len(small_off)), cmap='jet', s=35., edgecolors='black', alpha=0.7) plt.show(block=False) fig.savefig('overall_offsets_vs_time.png', dpi=200, transparent=False) fig.savefig('overall_offsets_vs_time.pdf', dpi=200, transparent=False) def gyro_drift(): import glob import matplotlib.colors as colors import matplotlib.cm as cmx import threedhst files = glob.glob('icxe*010_asn.fits') fig = unicorn.catalogs.plot_init(xs=10.,aspect=0.24, left=0.12, right=0.05, bottom=0.15, top=0.15, NO_GUI=False) gs = gridspec.GridSpec(1,4,top=0.9, bottom=0.15) fig.subplots_adjust(wspace=0.17) fig.subplots_adjust(hspace=0.1) fs = 8 jet = cm = plt.get_cmap('jet_r') cNorm = colors.Normalize(vmin=0, vmax=9) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) for j, file in enumerate(files): print file ax = fig.add_subplot(gs[j]) ax.set_xlabel('$\Delta$ x [pix]', fontsize=fs, labelpad=0.1) if j == 0: ax.set_ylabel('$\Delta$ y [pix]', fontsize=fs) ax.set_title('{}'.format(file.split('_')[0]), fontsize=fs) ax.set_xlim([-3., 3.]) ax.set_ylim([-3., 3.]) asn = threedhst.utils.ASNFile(file) cc = 1. for exp in asn.exposures[1:]: data = table.read(exp+'_shifts.txt', format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) cc += 1. color = scalarMap.to_rgba(cc) ax.plot(data['x'], data['y'], '-', color=color, alpha=0.5, linewidth=1.5) ax.plot(data['x'], data['y'], 'o', color=color, markersize=3., alpha=0.5, markeredgecolor=None) plt.show(block=False) fig.savefig('gyro_drift.png', dpi=200, transparent=False) def footprints_plot(root='icxe15010'): import unicorn.survey_paper as sup import matplotlib.colors as colors import matplotlib.cm as cmx if root == 'icxe15010': aspect = 1.75 xlim = [150.265, 150.157] ylim = [2.45, 2.64] xticklab = [r'$10^\mathrm{h}01^\mathrm{m}00^\mathrm{s}$', r'$10^\mathrm{h}00^\mathrm{m}45^\mathrm{s}$'] xtickv = [sup.degrees(10,01,00, hours=True),sup.degrees(10,00,45, hours=True)] yticklab = [r'$+02^\circ30^\prime00^{\prime\prime}$',r'$+02^\circ35^\prime00^{\prime\prime}$'] ytickv = [sup.degrees(2, 30, 00, hours=False),sup.degrees(2, 35, 00, hours=False)] label = 'COSMOS-15' factor=10. if root == 'icxe16010': aspect=0.9 xlim = [150.265, 150.1] ylim = [2.607, 2.74] xticklab = [r'$10^\mathrm{h}01^\mathrm{m}00^\mathrm{s}$', r'$10^\mathrm{h}00^\mathrm{m}45^\mathrm{s}$',r'$10^\mathrm{h}00^\mathrm{m}30^\mathrm{s}$'] xtickv = [sup.degrees(10,01,00, hours=True),sup.degrees(10,00,45, hours=True),sup.degrees(10,00,30, hours=True)] yticklab = [r'$+02^\circ38^\prime00^{\prime\prime}$',r'$+02^\circ40^\prime00^{\prime\prime}$', r'$+02^\circ42^\prime00^{\prime\prime}$', r'$+02^\circ44^\prime00^{\prime\prime}$'] ytickv = [sup.degrees(2, 38, 00, hours=False),sup.degrees(2, 40, 00, hours=False),sup.degrees(2, 42, 00, hours=False),sup.degrees(2, 44, 00, hours=False)] label='COSMOS-16' factor=20. if root == 'icxe17010': aspect=1.4 xlim = [150.2, 150.06] ylim = [2.52, 2.72] xticklab = [r'$10^\mathrm{h}00^\mathrm{m}45^\mathrm{s}$', r'$10^\mathrm{h}00^\mathrm{m}30^\mathrm{s}$',r'$10^\mathrm{h}00^\mathrm{m}15^\mathrm{s}$'] xtickv = [sup.degrees(10,00,45, hours=True),sup.degrees(10,00,30, hours=True),sup.degrees(10,00,15, hours=True)] yticklab = [r'$+02^\circ35^\prime00^{\prime\prime}$',r'$+02^\circ40^\prime00^{\prime\prime}$'] ytickv = [sup.degrees(2, 35, 00, hours=False),sup.degrees(2, 40, 00, hours=False)] label='COSMOS-17' factor=240. if root == 'icxe18010': aspect=1.577 xlim = [150.14, 150.01] ylim = [2.53, 2.735] xticklab = [r'$10^\mathrm{h}00^\mathrm{m}30^\mathrm{s}$', r'$10^\mathrm{h}00^\mathrm{m}20^\mathrm{s}$',r'$10^\mathrm{h}00^\mathrm{m}10^\mathrm{s}$'] xtickv = [sup.degrees(10,00,30, hours=True),sup.degrees(10,00,20, hours=True),sup.degrees(10,00,10, hours=True)] yticklab = [r'$+02^\circ35^\prime00^{\prime\prime}$',r'$+02^\circ40^\prime00^{\prime\prime}$'] ytickv = [sup.degrees(2, 35, 00, hours=False),sup.degrees(2, 40, 00, hours=False)] label='COSMOS-18' factor=240. fig = unicorn.catalogs.plot_init(square=True, xs=5., aspect=aspect, fontsize=8, left=0.18, right=0.02, bottom=0.10, top=0.10) ax = fig.add_subplot(111) jet = cm = plt.get_cmap('jet') cNorm = colors.Normalize(vmin=0, vmax=9) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) reg_file = root+'_asn.reg' poly = [] with open(reg_file) as f: for line in f: if not line.startswith('fk5'): region = line.split('#')[0] poly.append(sup.polysplit(region=region, get_shapely=True)) shifts = table.read('shifts_{}.txt'.format(root), format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) cc = 0 xcen_all = [] ycen_all = [] for j,(pp, x_off, y_off, file) in enumerate(zip(poly, shifts['x'], shifts['y'], shifts['file'])): cc += 1. color = scalarMap.to_rgba(cc) x, y = pp.exterior.xy flt = fits.open(file) xcen = flt[1].header['CRVAL1O'] ycen = flt[1].header['CRVAL2O'] x_off = (flt[1].header['CRVAL1B']-flt[1].header['CRVAL1O'])*20. y_off = (flt[1].header['CRVAL2B']-flt[1].header['CRVAL2O'])*20. print file, xcen, xcen+x_off, ycen, ycen+y_off #xcen = (np.mean(x[:-1])) #ycen = (np.mean(y[:-1])) xcen_all.append(xcen) ycen_all.append(ycen) ax.plot(x,y,'-', color=color) #ax.annotate("",xy=(xcen+(x_off*0.12)/factor, ycen+(y_off*0.12)/factor), xytext=(xcen, ycen), # arrowprops=dict(arrowstyle='->', color=color)) #ax.plot([xcen, xcen+x_off], [ycen, ycen+y_off], '-') ax.annotate("",xy=(xcen+x_off, ycen+y_off), xytext=(xcen, ycen), arrowprops=dict(arrowstyle='->', color=color)) ax.plot(xcen_all, ycen_all, '+:', markersize=10., color='0.5', alpha=0.5) ax.set_xlim(xlim) ax.set_ylim(ylim) ax.set_xticklabels(xticklab) xtick = ax.set_xticks(xtickv) ax.set_yticklabels(yticklab) ytick = ax.set_yticks(ytickv) ax.set_title(label) plt.show(block=False) fig.savefig('footprint_{}.png'.format(label.lower()), dpi=200, transparent=False) def footprints_all(): import unicorn.survey_paper as sup import matplotlib.colors as colors import matplotlib.cm as cmx fig = unicorn.catalogs.plot_init(square=True, xs=10., aspect=1.1, fontsize=8, left=0.18, right=0.02, bottom=0.10, top=0.10) ax = fig.add_subplot(111) jet = cm = plt.get_cmap('jet') cNorm = colors.Normalize(vmin=0, vmax=9) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) xlim = [150.270, 149.99] ylim = [2.45, 2.751] xticklab = [r'$10^\mathrm{h}01^\mathrm{m}00^\mathrm{s}$', r'$10^\mathrm{h}00^\mathrm{m}45^\mathrm{s}$',r'$10^\mathrm{h}00^\mathrm{m}30^\mathrm{s}$',r'$10^\mathrm{h}00^\mathrm{m}15^\mathrm{s}$',r'$10^\mathrm{h}00^\mathrm{m}00^\mathrm{s}$'] xtickv = [sup.degrees(10,01,00, hours=True),sup.degrees(10,00,45, hours=True),sup.degrees(10,00,30, hours=True),sup.degrees(10,00,15, hours=True),sup.degrees(10,00,00, hours=True)] yticklab = [r'$+02^\circ30^\prime00^{\prime\prime}$',r'$+02^\circ35^\prime00^{\prime\prime}$', r'$+02^\circ40^\prime00^{\prime\prime}$',r'$+02^\circ45^\prime00^{\prime\prime}$'] ytickv = [sup.degrees(2, 30, 00, hours=False),sup.degrees(2, 35, 00, hours=False),sup.degrees(2, 40, 00, hours=False),sup.degrees(2, 45, 00, hours=False)] factor=20. roots = ['icxe15010', 'icxe16010', 'icxe17010','icxe18010'] labels = ['COSMOS-15', 'COSMOS-16','COSMOS-17','COSMOS-18'] lines = ['-','--','-.',':'] for root, label, linestyle in zip(roots, labels, lines): reg_file = root+'_asn.reg' poly = [] with open(reg_file) as f: for line in f: if not line.startswith('fk5'): region = line.split('#')[0] poly.append(sup.polysplit(region=region, get_shapely=True)) shifts = table.read('shifts_{}.txt'.format(root), format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) cc = 0 xcen_all = [] ycen_all = [] for j,(pp, file) in enumerate(zip(poly, shifts['file'])): cc += 1. color = scalarMap.to_rgba(cc) x, y = pp.exterior.xy flt = fits.open(file) xcen = flt[1].header['CRVAL1O'] ycen = flt[1].header['CRVAL2O'] x_off = (flt[1].header['CRVAL1B']-flt[1].header['CRVAL1O'])*factor y_off = (flt[1].header['CRVAL2B']-flt[1].header['CRVAL2O'])*factor xcen_all.append(xcen) ycen_all.append(ycen) ax.plot(x,y,'-', color=color) ax.annotate("",xy=(xcen+x_off, ycen+y_off), xytext=(xcen, ycen), arrowprops=dict(arrowstyle='->', color=color)) ax.text(xcen, ycen+0.005, file.split('_')[0], fontsize=9, va='top', ha='center') ax.plot(xcen_all, ycen_all, linestyle=linestyle, markersize=10., color='0.5', alpha=0.7, label=label) ax.plot(xcen_all, ycen_all, '+', markersize=10., color='0.5', alpha=0.7) ax.text(xcen_all[0], ycen_all[0]-0.005, label, fontsize=10, va='top', ha='center') ax.set_xlim(xlim) ax.set_ylim(ylim) ax.set_xticklabels(xticklab) xtick = ax.set_xticks(xtickv) ax.set_yticklabels(yticklab) ytick = ax.set_yticks(ytickv) ax.legend(loc='lower right', frameon=False, labelspacing=0.8, fontsize=9, handlelength=10, borderpad=5.) #ax.set_title(label) plt.show(block=False) fig.savefig('footprints_all.png'.format(label.lower()), dpi=200, transparent=False) def make_hist_plot_bw(): import astropy.io.ascii as ascii from matplotlib.ticker import MultipleLocator, FormatStrFormatter,AutoMinorLocator, ScalarFormatter minorLocator = MultipleLocator(10) matplotlib.rc('xtick',labelsize=10) matplotlib.rc('ytick',labelsize=10) data = ascii.read('/3DHST/Spectra/Work/HOPR/GYRO/gyro_shifts.txt') fig = unicorn.catalogs.plot_init(square=True, xs=6., aspect=0.9, fontsize=10., left=0.15, right=0.05, top=0.1, bottom=0.15) ax = fig.add_subplot(111) ax.fill_between([0.,0.5], 0, 30, color='0.85', alpha=0.9) nn, bins, patches = ax.hist(data['rate']*25., bins=60, range=[0.,6.], color='black', histtype='step', linestyle='dotted') test_val = data['rate'][data['root'] == 'ib2u22prq'] ax.arrow(test_val*25., 17.1, 0., -1., head_length=0.5, head_width=0.1, fc='red', ec='red') ax.text(0., 18.0, 'Fig. 1 Example', ha='left', va='center', fontsize=13, fontweight='heavy') ax.arrow(0., 21., 0.5, 0., head_length=0.05, head_width=0.30, fc='black', ec='black', length_includes_head=True) ax.arrow(0.5, 21., -0.5, 0., head_length=0.05, head_width=0.30, fc='black', ec='black', length_includes_head=True) ax.text(0.0, 22.5, 'Expected Drift', ha='left', va='center', fontsize=15, fontweight='heavy') ax.text(1.1, 5, 'gyro\nproblem', fontsize=12.5, fontweight=0.1, multialignment='center') ax.text(4.3, 5, 'failed\nguide star\nacquisition', fontsize=12.5, fontweight=0.1, multialignment='center') shift_files = glob.glob('shifts_icxe*010.txt') drift_rate = [] for shift_file in shift_files: data = table.read(shift_file, format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) for k, file in enumerate(data['file'][1:]): if k+1 < 4: t_exp = 255 else: t_exp = 277 drift = table.read(file.split('_')[0]+'_shifts.txt', format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) drift_rate.append(25.*np.sqrt((drift['x'][0]-drift['x'][-1])**2 + (drift['y'][0]-drift['y'][-1])**2)/t_exp) nn_sh, bins_sh, patches_sh = ax.hist(drift_rate, bins=5, range=[0.,0.5], color='red', histtype='step', lw=3) print "Mean drift: {}\nMedian drift: {}".format(np.mean(drift_rate), np.median(drift_rate)) ax.set_xlim([-0.15, 2.7]) ax.set_ylim([0., 25]) ax.set_xlabel('Drift in WFC3/IR Pixels per 25 Seconds', fontsize=12) ax.set_ylabel('Number of Images') ax.tick_params(axis='both', which='major',labelsize=12) minorLocator = AutoMinorLocator() ax.xaxis.set_minor_locator(minorLocator) minorLocator = AutoMinorLocator(5) ax.yaxis.set_minor_locator(minorLocator) ax.tick_params(which='minor', length=2) plt.show(block=False) plt.savefig('drift_hist_bw.png',dpi=100,transparent=False) plt.savefig('drift_hist_bw.pdf',dpi=100,transparent=False) def xy_shifts(): import scipy # x gaussian: [ 3.41423523 1.29066909 6.73498474] or uniform [-70, 70np.] # y gaussian: [ 5.27724105 -0.78413847 -4.80223471] tab = table.read('allshifts.txt', format='ascii') nn, bins, patches = plt.hist(tab['col2'], bins=50, range=[-70,70], color='red', alpha=0.5) centers = 0.5*(bins[1:]+bins[:-1]) coeff_g, var_g = scipy.optimize.curve_fit(gauss, centers , nn, p0=[np.max(nn),0.,100.]) fit_g = gauss(centers, *coeff_g) plt.plot(centers, fit_g, color='red') print coeff_g, np.min() nn1, bins1, patches = plt.hist(tab['col3'], bins=bins, range=[-70,70], color='blue', alpha=0.5) centers1 = 0.5*(bins1[1:]+bins1[:-1]) coeff_g, var_g = scipy.optimize.curve_fit(gauss, centers1 , nn1, p0=[np.max(nn1),0.,100.]) fit_g = gauss(centers, *coeff_g) plt.plot(centers1, fit_g, color='blue') print coeff_g plt.show(block=False) def gauss(x, *p): A, mu, sigma = p return A*np.exp(-(x-mu)**2/(2.*sigma**2)) def area_mag(): import unicorn import unicorn.survey_paper as sup from my_python.phot_paper import determine_outline as determine_outline import matplotlib.pyplot as plt from matplotlib.ticker import MultipleLocator, FormatStrFormatter,AutoMinorLocator fig = unicorn.catalogs.plot_init(square=True, xs=5, aspect=1.0, fontsize=10, left=0.15, right=0.02, top=0.03, bottom=0.12) ax = fig.add_subplot(111) WFC3_IR_AREA = 4.6 # arcmin2 imaging = {'UDF/XDF':(236.1e3/3000, 1*WFC3_IR_AREA, 150, 0.3), 'HUDF09-1': (13, 1*WFC3_IR_AREA,350,0.25), 'HUDF09-2':(19, 1*WFC3_IR_AREA, 350,0.25), 'CANDELS-Deep': (12, 0.04*3600, 350,0.07), 'CANDELS-Wide': (2./3., 0.2*3600, 0, 0.3), 'CLASH': (2, 25*WFC3_IR_AREA, 0,0.3), 'FF clusters': (24, 6*WFC3_IR_AREA, 150, 0.3)} for key in imaging.keys(): mag = 2.5*np.log10(np.sqrt(imaging[key][0]/0.125))+25.5 ax.plot(imaging[key][1],mag, 's', markersize=7, color='black') ax.text(imaging[key][1]+imaging[key][2], mag+imaging[key][3], key, ha='center', va='top', fontsize=9) print key, mag if key == 'HUDF09-1': ax.plot([13+50, 13+130], [mag, mag+0.17], color='black', lw=1.) if key == 'HUDF09-2': ax.plot([19+50, 19+130], [mag, mag+0.17], color='black', lw=1.) if key == 'FF clusters': ax.plot() ax.plot([2000.], [25.0], 's', markersize=12, color='red') ax.text(2000., 25.3, 'GO-14114', multialignment='center', color='red',fontsize=10, ha='center', va='top') ax.text(1200, 28.5, 'HST/WFC3 F160W\n imaging', fontsize =12, multialignment='center') ax.set_xlim([-100, 2490.]) ax.set_ylim([24.65, 29.5]) ax.set_xlabel('Area [arcmin$^2$]', fontsize=12) ax.set_ylabel('5$\sigma$ Point Source Depth [AB mag]', fontsize=12) minorLocator = AutoMinorLocator() ax.xaxis.set_minor_locator(minorLocator) minorLocator = AutoMinorLocator(5) ax.yaxis.set_minor_locator(minorLocator) yticklab = ['25.0', '26.0', '27.0', '28.0', '29.0'] ytickv = [25.0, 26.0, 27.0, 28.0, 29.0] ax.set_yticklabels(yticklab) ytick = ax.set_yticks(ytickv) plt.show(block=False) fig.savefig('area_mag.png', dpi=200, transparent=False) fig.savefig('area_mag.pdf', dpi=200, transparent=False) def mosaic_demo(): mosaic = fits.open('test7_drz_sci.fits') ### open COSMOS-15 mosaics cos15 = fits.open('icxe15010_test_drz_sci.fits') ### open CANDELS mosaic candels = fits.open('cosmos_3dhst_cutout.fits') fig = unicorn.catalogs.plot_init(square=True, xs=10., aspect=0.835, fontsize=8, left=0.02, right=0.02, bottom=0.02, top=0.02) gs1 = gridspec.GridSpec(1,1) gs2 = gridspec.GridSpec(2,1, left=0.65, right=0.98, top=0.8, bottom=0.4) gs3 = gridspec.GridSpec(1,2, left=0.40, right=0.88, top = 0.3, bottom=0.05) fig.subplots_adjust(wspace=0.05) fig.subplots_adjust(hspace=0.05) ax1 = fig.add_subplot(gs1[0,0], xlim=[0,12200], ylim=[0,10200]) im1 = ax1.imshow(mosaic[0].data, cmap = pylab.cm.Greys, vmin=-0.01, vmax=0.5, interpolation='None') ax1.plot([2150,3050,3050,2150,2150],[3250,3250,3850,3850,3250],'-',color='black') ax1.plot([1900,2125,2125,1900,1900],[5250,5250,5400,5400,5250],'-',color='black') ax1.tick_params(axis='both',which='both',top='off',bottom='off', right='off', left='off') ax1.axis('off') ax1.set_xticklabels([]) ax1.set_yticklabels([]) ### plot mosaic with boxes at the correct positions ### plot candels outline ### plot zooms of the unsmeared and smeared mosaics ax2 = fig.add_subplot(gs2[0,0], xlim=[0,225], ylim=[0,150]) im2 = ax2.imshow(mosaic[0].data[5250:5400,1900:2125], cmap = pylab.cm.Greys, vmin=-0.01, vmax=0.4, interpolation='bicubic') ax2.tick_params(axis='both',which='both',top='off',bottom='off', right='off', left='off') ax2.text(20,15,'COSMOS-DASH Mosaic', fontsize=10) ax2.set_xticklabels([]) ax2.set_yticklabels([]) ax3 = fig.add_subplot(gs2[1,0], xlim=[0,225], ylim=[0,150]) im3 = ax3.imshow(cos15[0].data[5250:5400,1900:2125], cmap = pylab.cm.Greys, vmin=-0.01, vmax=0.4, interpolation='bicubic') ax3.text(20,15,'Uncorrected (smeared) image', fontsize=10) ax3.tick_params(axis='both',which='both',top='off',bottom='off', right='off', left='off') ax3.set_xticklabels([]) ax3.set_yticklabels([]) ### plot zooms of our mosaic and CANDELS ax4 = fig.add_subplot(gs3[0,0], xlim=[0,900], ylim=[0,600]) im4 = ax4.imshow(mosaic[0].data[3250:3850,2150:3050], cmap = pylab.cm.Greys, vmin=-0.01, vmax=0.5, interpolation='bicubic') ax4.text(50,50,'COSMOS-DASH Mosaic', fontsize=10) ax4.tick_params(axis='both',which='both',top='off',bottom='off', right='off', left='off') ax4.set_xticklabels([]) ax4.set_yticklabels([]) ax5 = fig.add_subplot(gs3[0,1], xlim=[0,1500], ylim=[0,1000]) im5 = ax5.imshow(candels[0].data[880:1880,610:2110], cmap = pylab.cm.Greys, vmin=-0.01, vmax=0.1, interpolation='bicubic') ax5.text(50,83,'CANDELS Mosaic', fontsize=10) ax5.tick_params(axis='both',which='both',top='off',bottom='off', right='off', left='off') ax5.set_xticklabels([]) ax5.set_yticklabels([]) plt.show(block=False) fig.savefig('mosaic_demo.png', dpi=200, transparent=False) fig.savefig('mosaic_demo.pdf', dpi=200, transparent=False) def plot_galfit(): """ Makes the plot comparing the GALFIT derived parameters from the new mosaics to CANDELS. """ import threedhst from my_python.pyspherematch import spherematch from matplotlib.ticker import ScalarFormatter, MultipleLocator, FormatStrFormatter fs=9 matplotlib.rc('xtick',labelsize=fs) matplotlib.rc('ytick',labelsize=fs) mag_limit=21. ### read in CANDELS size measurements old = table.read('F160W_galfit_v4.0.cat.FITS') big_cat = table.read('/3DHST/Photometry/Release/v4.1/COSMOS/Catalog/cosmos_3dhst.v4.1.cat.FITS') old = old[(old['mag'] <= mag_limit) & (old['f'] < 2) & (big_cat['use_phot'] == 1)] ### read in new data from Arjen: H_v2.cat print 'Reading H_v4.cat' new = table.read('H_v4.cat', format='ascii') new = new[(new['mag'] <= mag_limit) & (new['f'] < 2)] ### cross-match coordinates idx_n, idx_o, d = spherematch(new['RA'], new['DEC'], old['ra'], old['dec'],tol = 0.5/3600.) print 'Total matches: {}'.format(len(idx_n)) ### make plot fig = unicorn.catalogs.plot_init(square=True, xs=8., aspect=1.0, fontsize=8, left=0.15, right=0.1, bottom=0.15, top=0.05) gs = gridspec.GridSpec(2,2) fig.subplots_adjust(wspace=0.20) fig.subplots_adjust(hspace=0.20) ax1 = fig.add_subplot(gs[0,0], xlim=[16,22], ylim=[16,22]) ax1.plot([0,100],[0,100],':', color='gray', alpha=0.8) ax1.plot(new['mag'][idx_n],old['mag'][idx_o],'o', color='0.5', alpha=0.5, markersize=4.) ax1.set_xlabel('COSMOS-DASH F160W Magnitude', fontsize=fs) ax1.set_ylabel('CANDELS F160W Magnitude', fontsize=fs) diff = new['mag'][idx_n] - old['mag'][idx_o] print 'Magnitude: \nMEDIAN: {}\nNMAD: {}\n\n'.format(np.median(diff), threedhst.utils.nmad(diff)) ax2 = fig.add_subplot(gs[0,1], xlim=[0.1,3.5], ylim=[0.1,3.5]) ax2.plot([0.01,5],[0.01,5],':', color='gray', alpha=0.8) ax2.plot(new['re'][idx_n],old['re'][idx_o],'o', color='0.5', alpha=0.5, markersize=4.) ax2.set_xlabel('COSMOS-DASH $R_{eff}$ [arcsec]', fontsize=fs) ax2.set_ylabel('CANDELS $R_{eff}$ [arcsec]', fontsize=fs, labelpad=0) ax2.set_xscale('log') ax2.xaxis.set_major_formatter(ScalarFormatter()) ax2.xaxis.set_major_locator(MultipleLocator(1)) ax2.xaxis.set_major_formatter(FormatStrFormatter('%d')) ax2.set_yscale('log') ax2.yaxis.set_major_formatter(ScalarFormatter()) ax2.yaxis.set_major_locator(MultipleLocator(1)) ax2.yaxis.set_major_formatter(FormatStrFormatter('%d')) diff = np.log10(new['re'][idx_n]) - np.log10(old['re'][idx_o]) print 'log(Reff): \nMEDIAN: {}\nNMAD: {}\n\n'.format(np.median(diff), threedhst.utils.nmad(diff)) print np.median(new['re'][idx_n]/old['re'][idx_o]) ax3 = fig.add_subplot(gs[1,0], xlim=[0.6, 8.9], ylim=[0.6,8.9]) ax3.plot([-1,100],[-1,100],':', color='gray', alpha=0.8) ax3.plot(new['n'][idx_n],old['n'][idx_o],'o', color='0.5', alpha=0.5, markersize=4.) ax3.set_xlabel("COSMOS-DASH Sersic Index", fontsize=fs) ax3.set_ylabel("CANDELS Sersic Index", fontsize=fs, labelpad=0) ax3.set_xscale('log') ax3.xaxis.set_major_formatter(ScalarFormatter()) ax3.xaxis.set_major_locator(MultipleLocator(1)) ax3.xaxis.set_major_formatter(FormatStrFormatter('%d')) ax3.set_yscale('log') ax3.yaxis.set_major_formatter(ScalarFormatter()) ax3.yaxis.set_major_locator(MultipleLocator(1)) ax3.yaxis.set_major_formatter(FormatStrFormatter('%d')) diff = (new['n'][idx_n]) - (old['n'][idx_o]) print 'log(n): \nMEDIAN: {}\nNMAD: {}\n\n'.format(np.median(diff), threedhst.utils.nmad(diff)) ax4 = fig.add_subplot(gs[1,1], xlim=[0,1.0], ylim=[0,1.0]) ax4.plot([0,100],[0,100],':', color='gray', alpha=0.8) ax4.plot(new['q'][idx_n],old['q'][idx_o],'o', color='0.5', alpha=0.5, markersize=4.) ax4.set_xlabel('COSMOS-DASH Axis Ratio', fontsize=fs) ax4.set_ylabel('CANDELS Axis Ratio', fontsize=fs) diff = new['q'][idx_n] - old['q'][idx_o] print 'Axis ratio: \nMEDIAN: {}\nNMAD: {}\n\n'.format(np.median(diff), threedhst.utils.nmad(diff)) plt.show(block=False) fig.savefig('galfit_gyro_comp.pdf', dpi=200) fig.savefig('galfit_gyro_comp.png', dpi=200) def mag_depth(): orig = table.read('/3DHST/Photometry/Release/v4.0/COSMOS/Detection/cosmos_3dhst.v4.0.F160W_orig.cat', format='ascii.sextractor') cat = table.read('test7_drz_sci.cat', format='ascii.sextractor') fig = unicorn.catalogs.plot_init(square=True, xs=6., aspect=0.9, fontsize=10., left=0.15, right=0.15, top=0.1, bottom=0.15) ax = fig.add_subplot(111) n_orig, bins, patches = ax.hist(orig['MAG_AUTO'], bins=25, range=[16., 30.], color='0.5', alpha=0.5, lw=2, histtype='step') n_cat, bins, patches = ax.hist(cat['MAG_AUTO'], bins=bins, range=[16., 30.], color='red', alpha=0.5, histtype='step', lw=2) ax.set_xlim([17.,28.]) ax.set_ylim([0, 8e3]) ax.set_xlabel('F160W Magnitude', fontsize=12) ax.set_ylabel('N') ax2 = ax.twinx()#fig.add_subplot(111, sharex=ax, frameon=False) bin_c = bins[:-1] + (bins[1:] - bins[:-1])/2 width = np.mean(bins[1:] - bins[:-1]) ax2.plot(bin_c+width/2, (n_cat/142.429)/(n_orig/183.9), color='black', lw=2, alpha=0.8) ax2.plot([15.,31.], [1.0, 1.0], linestyle='dashed', color='0.8', alpha=0.5) ax2.plot([15.,31.], [0.9, 0.9], linestyle='dashed', color='0.8', alpha=0.5) ax2.plot([15.,31.], [0.75,0.75], linestyle='dashed', color='0.8', alpha=0.5) ax2.plot([15.,31.], [0.5, 0.5], linestyle='dashed', color='0.8', alpha=0.5) ax2.set_ylim([0.,1.3]) ax2.set_xlim([17.,28.]) ax2.set_ylabel('Fraction') plt.show(block=False) fig.savefig('mag_depth.pdf', dpi=200) fig.savefig('mag_depth.png', dpi=200) def psf_plot(): psf = fits.open('test7_psf_v2.fits') wht = fits.open('test7_wht_v2.fits') ### make plot fig = unicorn.catalogs.plot_init(square=True, xs=6., aspect=0.6, fontsize=8, left=0.05, right=0.05, bottom=0.1, top=0.00) gs = gridspec.GridSpec(1,2) fig.subplots_adjust(wspace=0.10) fig.subplots_adjust(hspace=0.10) ax1 = fig.add_subplot(gs[0], xlim=[0,68], ylim=[0,68]) ax1.axis('off') ax2 = fig.add_subplot(gs[1], xlim=[0,68], ylim=[0,68]) ax2.axis('off') im1 = ax1.imshow(psf[0].data/np.max(psf[0].data), cmap = pylab.cm.Greys_r, vmin=0.0, vmax=0.015, interpolation='None') cbar_ax1 = fig.add_axes([0.06, 0.12, 0.40, 0.07]) cbar1 = plt.colorbar(im1, cax = cbar_ax1,orientation='horizontal', ticks = [0.0, 0.005, 0.010, 0.015]) cbar1.ax.set_xticklabels([0.0, 0.005, 0.010, 0.015]) im2 = ax2.imshow(wht[0].data/np.max(wht[0].data), cmap = pylab.cm.Greys_r, vmin=0.7, vmax=1., interpolation='None') cbar_ax2 = fig.add_axes([0.54, 0.12, 0.40, 0.07]) cbar2 = plt.colorbar(im2, cax = cbar_ax2,orientation='horizontal', ticks = [0.7,0.8,0.9,1.0]) cbar2.ax.set_xticklabels([0.7,0.8,0.9,1.0]) plt.show(block=False) fig.savefig('psf_plot.pdf', dpi=200) fig.savefig('psf_plot.png', dpi=200) def rotation_check(): import unicorn.survey_paper as sup from my_python.pyspherematch import spherematch as psh import matplotlib.colors as colors import matplotlib.cm as cmx os.chdir('/3DHST/Spectra/Work/14114/PREPARE/') REF_CAT = '../REF/IPAC_ACS.fits' NEW_CAT = 'test7_drz_sci.cat' ref_cat = table.read(REF_CAT) new_cat = table.read(NEW_CAT, format='ascii.sextractor') idx1, idx2, dd = psh(new_cat['X_WORLD'], new_cat['Y_WORLD'], ref_cat['ra'], ref_cat['dec'], tol=1./3600.) fig = unicorn.catalogs.plot_init(square=True, xs=10., aspect=1.1, fontsize=8, left=0.18, right=0.02, bottom=0.10, top=0.10) ax = fig.add_subplot(111) jet = cm = plt.get_cmap('jet') cNorm = colors.Normalize(vmin=0, vmax=9) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) xlim = [150.270, 149.99] ylim = [2.45, 2.751] xticklab = [r'$10^\mathrm{h}01^\mathrm{m}00^\mathrm{s}$', r'$10^\mathrm{h}00^\mathrm{m}45^\mathrm{s}$',r'$10^\mathrm{h}00^\mathrm{m}30^\mathrm{s}$',r'$10^\mathrm{h}00^\mathrm{m}15^\mathrm{s}$',r'$10^\mathrm{h}00^\mathrm{m}00^\mathrm{s}$'] xtickv = [sup.degrees(10,01,00, hours=True),sup.degrees(10,00,45, hours=True),sup.degrees(10,00,30, hours=True),sup.degrees(10,00,15, hours=True),sup.degrees(10,00,00, hours=True)] yticklab = [r'$+02^\circ30^\prime00^{\prime\prime}$',r'$+02^\circ35^\prime00^{\prime\prime}$', r'$+02^\circ40^\prime00^{\prime\prime}$',r'$+02^\circ45^\prime00^{\prime\prime}$'] ytickv = [sup.degrees(2, 30, 00, hours=False),sup.degrees(2, 35, 00, hours=False),sup.degrees(2, 40, 00, hours=False),sup.degrees(2, 45, 00, hours=False)] factor=20. ax.quiver(new_cat['X_WORLD'][idx1], new_cat['Y_WORLD'][idx1], (new_cat['X_WORLD'][idx1]-ref_cat['ra'][idx2])*3600.*2, (new_cat['Y_WORLD'][idx1]-ref_cat['dec'][idx2])*3600.*2, width=0.8, linewidth=0.3, units='dots', headwidth=4, minshaft=1, headlength=5, pivot='tail', scale=0.025) print np.median(new_cat['X_WORLD'][idx1]-ref_cat['ra'][idx2])*3600., np.median(new_cat['Y_WORLD'][idx1]-ref_cat['dec'][idx2])*3600. roots = ['icxe15010', 'icxe16010', 'icxe17010','icxe18010'] labels = ['COSMOS-15', 'COSMOS-16','COSMOS-17','COSMOS-18'] lines = ['-','--','-.',':'] for root, label, linestyle in zip(roots, labels, lines): reg_file = root+'_asn.reg' poly = [] with open(reg_file) as f: for line in f: if not line.startswith('fk5'): region = line.split('#')[0] poly.append(sup.polysplit(region=region, get_shapely=True)) shifts = table.read('shifts_{}.txt'.format(root), format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) cc = 0 xcen_all = [] ycen_all = [] for j,(pp, file) in enumerate(zip(poly, shifts['file'])): cc += 1. color = scalarMap.to_rgba(cc) x, y = pp.exterior.xy flt = fits.open(file) xcen = flt[1].header['CRVAL1O'] ycen = flt[1].header['CRVAL2O'] x_off = (flt[1].header['CRVAL1B']-flt[1].header['CRVAL1O'])*factor y_off = (flt[1].header['CRVAL2B']-flt[1].header['CRVAL2O'])*factor xcen_all.append(xcen) ycen_all.append(ycen) ax.plot(x,y,'-', color=color) #ax.annotate("",xy=(xcen+x_off, ycen+y_off), xytext=(xcen, ycen), # arrowprops=dict(arrowstyle='->', color=color)) #ax.text(xcen, ycen+0.005, file.split('_')[0], fontsize=9, va='top', ha='center') ax.plot(xcen_all, ycen_all, linestyle=linestyle, markersize=10., color='black', alpha=0.7, label=label) ax.plot(xcen_all, ycen_all, '+', markersize=10., color='0.5', alpha=0.7) #ax.text(xcen_all[0], ycen_all[0]-0.005, label, fontsize=10, va='top', ha='center') ax.set_xlim(xlim) ax.set_ylim(ylim) ax.set_xticklabels(xticklab) xtick = ax.set_xticks(xtickv) ax.set_yticklabels(yticklab) ytick = ax.set_yticks(ytickv) ax.legend(loc='lower right', frameon=False, labelspacing=0.8, fontsize=9, handlelength=10, borderpad=5.) plt.show(block=False) fig.savefig('rotation_check.png'.format(label.lower()), dpi=200, transparent=False) def rotation_fits(): import glob import matplotlib.colors as colors import matplotlib.cm as cmx files = glob.glob('PREP_ROT/shifts_icxe*010.txt') fig = unicorn.catalogs.plot_init(xs=10.,aspect=0.45, left=0.2, right=0.05, bottom=0.15, top=0.15, NO_GUI=False) gs = gridspec.GridSpec(1,2,top=0.9, bottom=0.15) fig.subplots_adjust(wspace=0.2) fig.subplots_adjust(hspace=0.2) fs = 10 matplotlib.rc('xtick',labelsize=fs) matplotlib.rc('ytick',labelsize=fs) jet = cm = plt.get_cmap('jet_r') cNorm = colors.Normalize(vmin=0, vmax=8) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) ax1 = fig.add_subplot(gs[0]) ax2 = fig.add_subplot(gs[1]) time = np.array([0, 368, 713, 1060, 1405, 1777, 2147, 2519]) + 333. lines = ['-','--','-.',':'] labels = ['COSMOS-15', 'COSMOS-16', 'COSMOS-17','COSMOS-18'] for j, file in enumerate(files): root = '{}'.format(file.split('_')[1].split('.')[0]) ax1.set_xlim([-0.5, 13]) ax1.set_ylim([-0.075,0.075]) ax1.set_xlabel('Read Number', fontsize=fs) ax1.set_ylabel('Rotation [deg]', fontsize=fs) root = '{}'.format(file.split('_')[1].split('.')[0]) data = table.read(file, format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) rot_rate = [0.0] for k, file in enumerate(data['file'][1:]): if k+1 < 4: t_exp = 255 else: t_exp = 277 drift = table.read('PREP_ROT/'+file.split('_')[0]+'_shifts.txt', format='ascii', names=('file','x','y','rot','scale','x_rms','y_rms')) rot = drift['rot'] tt = (drift['rot'] > 180.) rot[tt] = drift['rot'][tt] - 360. rot_rate.append(rot[0]-rot[-1]) ax1.plot(np.arange(len(drift['rot']))+1, drift['rot'], linestyle=lines[j], color='0.5', label=labels[j], zorder=0) ax1.scatter(np.arange(len(drift['rot']))+1, drift['rot'], c='0.5', s=10., edgecolors='black', alpha=0.7) ax2.set_xlim([-5., 3100.]) ax2.set_ylim([-0.075,0.075]) ax2.set_xlabel('Time Since Beginning of Orbit\n[seconds]', fontsize=fs) ax2.set_ylabel('Rotation During Pointing [deg]', fontsize=fs) ax2.plot(time, np.array(rot_rate),linestyle=lines[j], color='0.5', zorder=0) ax2.scatter(time, np.array(rot_rate), c=range(len(rot_rate)), cmap='jet', s=35., edgecolors='black', alpha=0.7) print rot_rate plt.show(block=False) fig.savefig('rotation_fits.png', dpi=200, transparent=False) #fig.savefig('overall_offsets_vs_time.pdf', dpi=200, transparent=False) def mag_radius_test(): from matplotlib.ticker import ScalarFormatter import my_python.mk_region_file orig = table.read('test7_drz_sci_1.8.cat', format='ascii.sextractor') cat = table.read('test7_drz_sci_0.8.cat', format='ascii.sextractor') top = 0.075 bottom = 0.1 left = 0.15 fig = unicorn.catalogs.plot_init(xs=10,aspect=0.5, left=left, right=0.1, bottom=bottom, top=top, NO_GUI=False) fig.subplots_adjust(wspace=0.15) fig.subplots_adjust(hspace=0.1) fs = 10 matplotlib.rc('xtick',labelsize=fs) matplotlib.rc('ytick',labelsize=fs) gs1 = gridspec.GridSpec(1,2) ax1 = fig.add_subplot(gs1[0,0], ylim=[0.8, 20], xlim=[14,26]) ax1.plot(orig['MAG_AUTO'],orig['FLUX_RADIUS'], '.', color='0.4',markersize=0.9) ax1.plot(cat['MAG_AUTO'],cat['FLUX_RADIUS'], 'o', color='black', markersize=1, alpha=0.5) ax1.set_xlabel('MAG_AUTO F160W') ax1.set_ylabel('FLUX_RADIUS') ax1.set_yscale('log') cr = (cat['FLUX_RADIUS']*0.1/0.06 < 2.) stars = (cat['MAG_AUTO'] > 15.) & (cat['MAG_AUTO'] < 22.) & (cat['FLUX_APER_5']/cat['FLUX_APER'] > 1.1) & (cat['FLUX_APER_5']/cat['FLUX_APER'] < 1.2) #ax1.plot(cat['MAG_AUTO'][stars],cat['FLUX_RADIUS'][stars], 'o', color='red', markersize=2, alpha=1.0, markeredgecolor='red') print 'STARS: mean: {} / median{}'.format(np.mean(cat['FWHM_IMAGE'][stars]), np.median(cat['FWHM_IMAGE'][stars])) ax1.yaxis.set_major_formatter(ScalarFormatter()) ax2 = fig.add_subplot(gs1[0,1], ylim=[0.5,4], xlim=[14,26]) ax2.plot(orig['MAG_AUTO'], orig['FLUX_APER_5']/orig['FLUX_APER'], '.', color='0.4',markersize=0.9) ax2.plot(cat['MAG_AUTO'], cat['FLUX_APER_5']/cat['FLUX_APER'], 'o', color='black', markersize=1., alpha=0.5) #ax2.plot(cat['MAG_AUTO'][stars], cat['FLUX_APER_5'][stars]/cat['FLUX_APER'][stars], 'o', color='red', markersize=2., alpha=1.0, markeredgecolor='red') ax2.plot(cat['MAG_AUTO'][cr], cat['FLUX_APER_5'][cr]/cat['FLUX_APER'][cr], 'o', color='blue', markersize=2., alpha=1.0) ax2.set_xlabel('MAG_AUTO F160W') ax2.set_ylabel('Flux (2.0\")/Flux (0.5\")') ax2.yaxis.set_major_formatter(ScalarFormatter()) my_python.mk_region_file.mk_region_file_from_lists(cat['X_WORLD'][stars],cat['Y_WORLD'][stars],outfile = 'stars', printids='no', color='cyan') my_python.mk_region_file.mk_region_file_from_lists(cat['X_WORLD'][cr],cat['Y_WORLD'][cr],outfile = 'cr', printids='no', color='yellow') plt.show(block=False) #fig.savefig('mag_radius_test.pdf', dpi=200, transparent=False) #fig.savefig('mag_radius_test.png', dpi=200, transparent=False) def signal_to_noise_test(): import threedhst.utils top = 0.05 bottom = 0.15 left = 0.15 fig = unicorn.catalogs.plot_init(xs=10,aspect=0.5, left=left, right=0.05, bottom=bottom, top=top, NO_GUI=False) fig.subplots_adjust(wspace=0.01) fig.subplots_adjust(hspace=0.01) fs = 9 matplotlib.rc('xtick',labelsize=fs) matplotlib.rc('ytick',labelsize=fs) etc_mag = [18.,19.,20.,21.,22.,23.,24.,25.] etc_sn = np.array([509.,318.,195.8,116.7,65.1,33.1,15.2,6.5]) etc_sn_high = np.array([493.,295.,166.9,85.9,39.97,17.2,7.09,2.87]) factor = (1.-(0.8/3/2.75)) #0.678 gs = gridspec.GridSpec(2,4) asn_files = glob.glob('icxe1*010_asn.fits') for file in asn_files: asn = threedhst.utils.ASNFile(file) for ii, exp in enumerate(asn.exposures): cat = table.read('/3DHST/Spectra/Work/14114/TEST_SEXTR/{}_drz_sci.cat'.format(exp), format='ascii.sextractor') ax = fig.add_subplot(gs[ii], ylim=[3., 200], xlim=[21,25.5]) ax.plot(cat['MAG_APER'], cat['FLUX_APER']/(cat['FLUXERR_APER']/factor), '.', color='0.6',markersize=0.9) stars = (cat['MAG_AUTO'] > 15.) & (cat['MAG_AUTO'] < 22.) & (cat['FLUX_APER_6']/cat['FLUX_APER_1'] > 1.1) & (cat['FLUX_APER_6']/cat['FLUX_APER_1'] < 1.2) ax.plot(cat['MAG_APER'][stars], cat['FLUX_APER'][stars]/(cat['FLUXERR_APER'][stars]/factor), '^', color='black', markersize=2, alpha=1.0, markeredgecolor='0.3') if file == 'icxe18010_asn.fits': ax.text(24,70,'Pointing {}'.format(ii+1), fontsize=9, va='top', ha='center') #ax.plot(etc_mag,etc_sn_high, 'o', color='#b10026',markersize=2) ax.plot(etc_mag,etc_sn_high, '--', color='#b10026',markersize=2) ax.plot(etc_mag,etc_sn_high/1.07, '-', color='#b10026',markersize=2) #ax.plot(etc_mag,etc_sn, 'o', color='black',markersize=2) ax.plot(etc_mag,etc_sn, '--', color='black',markersize=2) ax.plot(etc_mag,etc_sn/1.37, '-', color='black',markersize=2) ax.plot([10,30],[5.,5.], ':', color='0.5') #ax.plot([10,30],[4.,4.], ':', color='0.5') ax.plot([25.,25.],[1.,3000.], ':', color='0.5') ax.set_yscale('log') if (ii == 0) or (ii == 4): ax.set_ylabel('S/N [r = 0.2" aperture]', fontsize=fs) else: ax.set_yticklabels([]) if (ii < 3): ax.set_xticklabels([]) else: ax.set_xlabel('AB Magnitude\n[r = 0.2" aperture]', fontsize=fs) ax.set_xticklabels([22,23,24,25], fontsize=fs) xtick = ax.set_xticks([22,23,24,25]) plt.show(block=False) fig.savefig('signal_to_noise_test.pdf', dpi=200, transparent=False) fig.savefig('signal_to_noise_test.png', dpi=200, transparent=False) def sources_of_noise(): top = 0.075 bottom = 0.1 left = 0.15 fig = unicorn.catalogs.plot_init(xs=10,aspect=0.5, left=left, right=0.1, bottom=bottom, top=top, NO_GUI=False) fig.subplots_adjust(wspace=0.15) fig.subplots_adjust(hspace=0.1) fs = 8 matplotlib.rc('xtick',labelsize=fs) matplotlib.rc('ytick',labelsize=fs) gs1 = gridspec.GridSpec(1,2) ax1 = fig.add_subplot(gs1[0,0], ylim=[0.0,0.27], xlim=[0.1,2.5]) exptime=275. rdnoise = 15. xx = np.linspace(0.2,2.4,10) noise_15 = np.sqrt(rdnoise**2+xx*exptime + (xx*exptime*0.002)**2 + (0.17*exptime))/exptime rd_15 = np.sqrt(rdnoise**2)/exptime bg_15 = np.sqrt(xx*exptime)/exptime rdnoise = np.sqrt(11)*15. noise_21_11 = np.sqrt(rdnoise**2+xx*exptime + (xx*exptime*0.002)**2 + (0.17*exptime))/exptime rd_21_11 = np.sqrt(rdnoise**2)/exptime rdnoise = np.sqrt(2)*21. noise_21_2 = np.sqrt(rdnoise**2+xx*exptime + (xx*exptime*0.002)**2 + (0.17*exptime))/exptime rd_21_2 = np.sqrt(rdnoise**2)/exptime rdnoise = np.sqrt(4)*21. noise_21_4 = np.sqrt(rdnoise**2+xx*exptime + (xx*exptime*0.002)**2 + (0.17*exptime))/exptime rd_21_4 = np.sqrt(rdnoise**2)/exptime ax1.plot(xx, noise_21_11, '-',color='#b10026',lw=1, label=r'RDN = 15$\times\sqrt{11}$ e$^{-}$: (11$\times$25 sec exp (w/ ramp fits))') ax1.plot([0.,3.], [rd_21_11,rd_21_11], ':',color='#b10026',lw=1) ax1.plot(xx, noise_21_4, '-',color='#fc4e2a',lw=1, label=r'RDN = 21$\times\sqrt{4}$ e$^{-}$') ax1.plot([0.,3.], [rd_21_4,rd_21_4], ':',color='#fc4e2a',lw=1) ax1.plot(xx, noise_21_2, '-',color='#feb24c',lw=1, label=r'RDN = 21$\times\sqrt{2}$ e$^{-}$') ax1.plot([0.,3.], [rd_21_2,rd_21_2], ':',color='#feb24c',lw=1) ax1.plot(xx, noise_15, '-',color='black',lw=1, label=r'RDN = 15 e$^{-}$: one 275 sec exp (/w ramp fit)') ax1.plot([0.,3.], [rd_15,rd_15], ':',color='black',lw=1) ax1.plot(xx, bg_15, '--',color='black',lw=1) ax1.text(2.0,0.105,'full noise model', rotation=11, va='center', ha='center', fontsize=fs, backgroundcolor='white', alpha=0.7) ax1.text(2.0,0.085,'sky noise', rotation=12, va='center', ha='center', fontsize=fs, backgroundcolor='white', alpha=0.7) ax1.text(2.0,0.053,'read noise',va='center', ha='center', fontsize=fs, backgroundcolor='white', alpha=0.7) #ax1.fill_between([0.6,0.8], 0.,2.,color='0.5', alpha=0.5) ax1.legend(loc='upper left', fontsize=fs, frameon=False) ax1.set_ylabel('$\sigma [e^-/s]$', fontsize=fs) ax1.set_xlabel('Background [e$^-$/s]', fontsize=fs) ax2 = fig.add_subplot(gs1[0,1], ylim=[0.2,1.25], xlim=[0.1,2.5]) ax2.plot(xx, 2.5*np.log10(noise_21_11/noise_15), '-',color='#b10026',lw=1) ax2.plot(xx, 2.5*np.log10(noise_21_4/noise_15), '-',color='#fc4e2a',lw=1) ax2.plot(xx, 2.5*np.log10(noise_21_2/noise_15), '-',color='#feb24c',lw=1) ax2.grid(True, linestyle=':',linewidth=0.5) ax2.fill_between([0.6,0.8], 0.,2.,color='0.5', alpha=0.5) ax2.fill_between([2.1,2.3], 0.,2.,color='0.5', alpha=0.5) ax2.text(0.7, 1.1,'nominal\nbackground', rotation=90., va='center', ha='center', fontsize=8) ax2.text(2.2, 0.9,'Oct. 2015\nbackground', rotation=90., va='center', ha='center', fontsize=8) ax2.set_ylabel('2.5*log$_{10}$($\sigma/\sigma_{15}$) [mag]', fontsize=fs) ax2.set_xlabel('Background [e$^-$/s]', fontsize=fs) plt.show(block=False) fig.savefig('sources_of_noise.pdf', dpi=200, transparent=False) fig.savefig('sources_of_noise.png', dpi=200, transparent=False) def plot_empty_apertures(): import glob import matplotlib.colors as colors import matplotlib.cm as cmx import threedhst.utils from scipy.interpolate import interp1d import scipy growth = table.read('COSMOS_growth_curve.dat', format='ascii') fp = interp1d(growth['radius_arcsec'],growth['fraction']) fig = unicorn.catalogs.plot_init(xs=10.,aspect=0.45, left=0.2, right=0.05, bottom=0.15, top=0.15, NO_GUI=False) gs = gridspec.GridSpec(1,2,top=0.9, bottom=0.15) fig.subplots_adjust(wspace=0.2) fig.subplots_adjust(hspace=0.2) fs = 10 matplotlib.rc('xtick',labelsize=fs) matplotlib.rc('ytick',labelsize=fs) jet = cm = plt.get_cmap('jet') cNorm = colors.Normalize(vmin=0, vmax=8) scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=jet) ax1 = fig.add_subplot(gs[0], ylim=[0.1,1.], xlim=[0.1,0.5]) ax2 = fig.add_subplot(gs[1], ylim=[10.,15.], xlim=[0.1,2]) files = glob.glob('icxe*0_asn.fits') for file in files: asn = threedhst.utils.ASNFile('{}'.format(file)) for j, exp in enumerate(asn.exposures): data = table.read('{}_drz_sci.apertures.F160W.v4.0.dat'.format(exp), format='ascii') color = scalarMap.to_rgba(j+1) ax1.plot(data['radius_pix']*0.12825, data['sigma'], 'o-', color=color, alpha=0.8, mfc=color, mec=color) fp1 = interp1d(data['radius_pix']*0.12825, data['sigma']) if (file == 'icxe15010_asn.fits') & ((j == 0) | (j == 7)): coeff, var = scipy.optimize.curve_fit(sigma, data['radius_pix'], data['sigma'], p0=[0.1, 1]) ax1.plot(data['radius_pix']*0.12825, 0.175*coeff[0]*data['radius_pix']**2,'--',color='black') ax1.plot(data['radius_pix']*0.12825, 0.175*coeff[0]*data['radius_pix'],'--',color='black') growth_y = fp(data['radius_pix']*0.12825) ax2.plot(data['radius_pix']*0.12825, -2.5*np.log10(5*(data['sigma']**2/fp(data['radius_pix']*0.12825))*15369.)+25. ,'o-', color=color, alpha=0.8, mfc=color, mec=color) ax1.set_ylabel('$\sigma$ [e-/s]') ax1.set_xlabel('Radius [arcsec]') #ax2.plot(growth['radius_arcsec'],1/growth['fraction'],'-') #ax2.plot(growth['radius_arcsec'], 1/fp(growth['radius_arcsec']),'o') guided = glob.glob('../TEST_HOPR_COOPER/REDUCE/ibt355*_drz_sci.apertures.F160W.v4.0.dat') dash = glob.glob('../TEST_HOPR_COOPER/REDUCE/ibt305*_drz_sci.apertures.F160W.v4.0.dat') #ax1.set_yscale('log') for file in guided: data = table.read(file, format='ascii') #ax1.plot(data['radius_pix']*0.128, data['sigma'], 'o-', color='black', alpha=0.8) for file in dash: data = table.read(file, format='ascii') #ax1.plot(data['radius_pix']*0.128, data['sigma'], 'o-', color='gray', alpha=0.8) plt.show(block=False) def gauss(x, *p): A, mu, sigma = p return A*np.exp(-(x-mu)**2/(2.*sigma**2)) def sigma(x, *p): alpha, beta = p sigma1 = 0.175 return sigma1*alpha*x**beta

[ "ivelina.momcheva@yale.edu" ]

ivelina.momcheva@yale.edu

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kevinliu007/CRM

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""" WSGI config for LkCRM project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/2.1/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'LkCRM.settings') application = get_wsgi_application()

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snorey/lexical-tools

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2021-01-24T00:44:20.052004

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import datetime import os import re import time import urllib import urllib2 dirr="C:\\Code\\Naver" def naverextract(text): title=text.split("<title>")[1].split(":")[0].strip() if "'" in title: title=title.split("'")[1].split("'")[0].strip() pieces=text.split('')[1:] pieces=[x.split("")[0] for x in pieces] pieces=[re.sub("\<.*?\>","",x) for x in pieces] pieces=[re.sub("[\<\(\,\[\r\n].*","",x) for x in pieces] glosses=[x.strip() for x in pieces] return title,glosses def naverextract_ko(text): pass def naverloop(directory=dirr): files=os.listdir(directory) files=[os.path.join(directory,x) for x in files if "G" not in x] # skip Googley files outlines=[] for f in files: stamp=f.split("\\")[-1].split(".")[0] print stamp text=open(f).read() if not text: continue title,glosses=naverextract(text) outlines.append(stamp+"\t"+title+"\t"+", ".join(glosses)) print stamp,str(glosses) return outlines def googleextract(text): catchstring1='<meta name="description" content="' catchstring2="- Google" if catchstring1 not in text: return "","" caught=text.split(catchstring1)[1].split(catchstring2)[0].strip() if '"' in caught: caught=caught.split('"')[0].strip() if ":" not in caught: return "","" title=caught.split(":")[0].strip() glosses=caught.split(":")[1].split(";") glosses=[x.strip() for x in glosses] return title,glosses def googloop(directory=dirr): files=os.listdir(directory) files=[os.path.join(directory,x) for x in files if "G" in x] # Googles only outlines=[] for f in files: stamp=f.split("\\")[-1].split(".")[0] print stamp text=open(f).read() if not text: continue title,glosses=googleextract(text) outlines.append(stamp+"\t"+title+"\t"+", ".join(glosses)) print stamp,str(glosses) return outlines def list2voc(path="C:\\Code\\koreanvocab2.txt"): import pie vocab=pie.Vocabulary(filter=False,language="Korean") text=open(path).read() text=text.decode("utf-8","ignore") lines=text.split("\n") lines=[tuple(x.split("\t")) for x in lines if "\t" in x] for line in lines: rank=line[0] print rank.encode('utf-8','ignore') if rank: try: tally=1000000/int(rank) except: tally=0 else: tally=0 word=line[1] newword=pie.Word(text=word) newword.tally=tally vocab.allwords.add(newword) return vocab def combine(file1,file2):# TSV of CSV glosses dixie={} dixie2={} for line in file1.split("\n"): #files come in as text, not handles parts=line.split("\t") dixie[parts[1]]=[x.strip() for x in parts[2].split(",") if x.strip()] for line in file2.split("\n"): parts=line.split("\t") if parts[1] in dixie.keys(): dixie[parts[1]].extend([x.strip() for x in parts[2].split(",") if x.strip()]) else: dixie[parts[1]]=[x.strip() for x in parts[2].split(",") if x.strip()] for d in dixie.keys(): newlist=[] newlist2=[] countlist=[] for i in dixie[d]: newlist.extend([x.strip() for x in re.split("[^a-zA-Z0-9\-\s]+",i) if x]) for n in newlist: testers=["a","an","the","to"] for t in testers: if (n.startswith(t+" ") or n.startswith(t.title()+" ")) and len(n) > 1+len(t): n=n[len(t):].strip() break newlist2.append(n) countlist=list(set((newlist2.count(x),x) for x in newlist2)) countlist.sort() countlist.reverse() dixie[d]=newlist2 dixie2[d]=countlist return dixie,dixie2 def get_naver_en(word): pass def get_naver_ko(word): import urllib, urllib2 url="http://krdic.naver.com/search.nhn?dic_where=krdic&query=%s&kind=keyword" % urllib.quote(word) page=urllib2.urlopen(url,timeout=60).read() matcher=re.escape('<a class="fnt15" href="') + '([^\"]*)' + re.escape('">') + '([^\<]*)' + re.escape('<') # trailing "<" excludes partial headword matches pieces=re.findall(matcher,page) defs=[] for p in pieces: # keep this simple for now; don't bother actually chasing to next page if word not in p: # print "No words!" continue else: # print "Yay!" pass try: chunk=page.split(p[0])[1].split("")[1].split("<div")[0].split("<p")[0] except Exception, e: print "Caught",e continue chunk=re.sub("\<[^\>]*\>","",chunk) chunk=chunk.replace("<","<").replace(">",">") lines=[x.strip() for x in chunk.split("\n") if x.strip()] defs.append(" / ".join(lines)) return defs def naver_ko_loop(inpath,outpath="",directory="C:\\Code"): if not outpath: outpath=os.path.join(directory,"testdefs-"+datetime.date.today().isoformat()+".txt") words=open(inpath).read().split("\n") output="" words=[x.strip() for x in words if x.strip()] print len(words) for w in words: done=False print words.index(w) while not done: try: defs=get_naver_ko(w) time.sleep(1) except Exception, e: print str(e) time.sleep(5) continue done=True if defs: defstring=" // ".join(defs) output+=w+"\t"+defstring+"\n" else: output+=w+"\t\n" if outpath: try: open(outpath,"w").write(output) print outpath except Exception, e: print str(e) outdefs=dict([tuple(x.split("\t")) for x in output.split("\n") if x.strip()]) return outpath,outdefs def get_examples_naver(word,kill_html=True): #UTF8-encoded hangul string url="http://krdic.naver.com/search.nhn?kind=all&scBtn=true&query="+urllib.quote(word) print url output=[] done=False while not done: try: page=urllib2.urlopen(url).read() done=True except Exception, e: print e continue try: section=page.split('')[1].split("</ul>")[0] except IndexError, e: print str(e) return output lines=section.split("<li>")[1:] lines=[x.split("")[1].split("","",x) for x in lines] return lines

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/13-Intro-to-Trees-master/pitchscrape/reviews/settings.py

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abendm/Pandas-Stuff

d9c13e3cd2ff5f0a210aed83fed3cc0531b590b9

f623d42100e53602ece47f079cb6b80288fbef55

refs/heads/master

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# -*- coding: utf-8 -*- # Scrapy settings for reviews project # # For simplicity, this file contains only settings considered important or # commonly used. You can find more settings consulting the documentation: # # https://doc.scrapy.org/en/latest/topics/settings.html # https://doc.scrapy.org/en/latest/topics/downloader-middleware.html # https://doc.scrapy.org/en/latest/topics/spider-middleware.html BOT_NAME = 'reviews' SPIDER_MODULES = ['reviews.spiders'] NEWSPIDER_MODULE = 'reviews.spiders' # Crawl responsibly by identifying yourself (and your website) on the user-agent #USER_AGENT = 'reviews (+http://www.yourdomain.com)' # Obey robots.txt rules ROBOTSTXT_OBEY = True # Configure maximum concurrent requests performed by Scrapy (default: 16) #CONCURRENT_REQUESTS = 32 # Configure a delay for requests for the same website (default: 0) # See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay # See also autothrottle settings and docs #DOWNLOAD_DELAY = 3 # The download delay setting will honor only one of: #CONCURRENT_REQUESTS_PER_DOMAIN = 16 #CONCURRENT_REQUESTS_PER_IP = 16 # Disable cookies (enabled by default) #COOKIES_ENABLED = False # Disable Telnet Console (enabled by default) #TELNETCONSOLE_ENABLED = False # Override the default request headers: #DEFAULT_REQUEST_HEADERS = { # 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', # 'Accept-Language': 'en', #} # Enable or disable spider middlewares # See https://doc.scrapy.org/en/latest/topics/spider-middleware.html #SPIDER_MIDDLEWARES = { # 'reviews.middlewares.ReviewsSpiderMiddleware': 543, #} # Enable or disable downloader middlewares # See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html #DOWNLOADER_MIDDLEWARES = { # 'reviews.middlewares.ReviewsDownloaderMiddleware': 543, #} # Enable or disable extensions # See https://doc.scrapy.org/en/latest/topics/extensions.html #EXTENSIONS = { # 'scrapy.extensions.telnet.TelnetConsole': None, #} # Configure item pipelines # See https://doc.scrapy.org/en/latest/topics/item-pipeline.html #ITEM_PIPELINES = { # 'reviews.pipelines.ReviewsPipeline': 300, #} # Enable and configure the AutoThrottle extension (disabled by default) # See https://doc.scrapy.org/en/latest/topics/autothrottle.html #AUTOTHROTTLE_ENABLED = True # The initial download delay #AUTOTHROTTLE_START_DELAY = 5 # The maximum download delay to be set in case of high latencies #AUTOTHROTTLE_MAX_DELAY = 60 # The average number of requests Scrapy should be sending in parallel to # each remote server #AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0 # Enable showing throttling stats for every response received: #AUTOTHROTTLE_DEBUG = False # Enable and configure HTTP caching (disabled by default) # See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings #HTTPCACHE_ENABLED = True #HTTPCACHE_EXPIRATION_SECS = 0 #HTTPCACHE_DIR = 'httpcache' #HTTPCACHE_IGNORE_HTTP_CODES = [] #HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'

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abendm@gmail.com

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renauddahou/bip_utils

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2023-07-16T05:08:45.042084

2021-08-19T09:33:03

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# Copyright (c) 2021 Emanuele Bellocchia # # 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. # Imports import os from enum import IntEnum, unique from typing import List, Union @unique class Bip39EntropyBitLen(IntEnum): """ Enumerative for BIP-0039 entropy bit lengths. """ BIT_LEN_128 = 128, BIT_LEN_160 = 160, BIT_LEN_192 = 192, BIT_LEN_224 = 224, BIT_LEN_256 = 256, class Bip39EntropyGeneratorConst: """ Class container for BIP39 entropy generator constants. """ # Accepted entropy lengths in bit ENTROPY_BIT_LEN: List[Bip39EntropyBitLen] = [ Bip39EntropyBitLen.BIT_LEN_128, Bip39EntropyBitLen.BIT_LEN_160, Bip39EntropyBitLen.BIT_LEN_192, Bip39EntropyBitLen.BIT_LEN_224, Bip39EntropyBitLen.BIT_LEN_256, ] class Bip39EntropyGenerator: """ Entropy generator class. It generates random entropy bytes with the specified length. """ def __init__(self, bits_len: Union[int, Bip39EntropyBitLen]) -> None: """ Construct class by specifying the bits length. Args: bits_len (int or Bip39EntropyBitLen): Entropy length in bits Raises: ValueError: If the bit length is not valid """ if not self.IsValidEntropyBitLen(bits_len): raise ValueError("Entropy bit length is not valid (%d)" % bits_len) self.m_bits_len = bits_len def Generate(self) -> bytes: """ Generate random entropy bytes with the length specified during construction. Returns: bytes: Generated entropy bytes """ return os.urandom(self.m_bits_len // 8) @staticmethod def IsValidEntropyBitLen(bits_len: Union[int, Bip39EntropyBitLen]) -> bool: """ Get if the specified entropy bit length is valid. Args: bits_len (int or Bip39EntropyBitLen): Entropy length in bits Returns: bool: True if valid, false otherwise """ return bits_len in Bip39EntropyGeneratorConst.ENTROPY_BIT_LEN @staticmethod def IsValidEntropyByteLen(bytes_len: int) -> bool: """ Get if the specified entropy byte length is valid. Args: bytes_len (int): Entropy length in bytes Returns: bool: True if valid, false otherwise """ return Bip39EntropyGenerator.IsValidEntropyBitLen(bytes_len * 8)

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ziriuz/udacity_learn

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# import the sklearn module for GaussianNB from sklearn.naive_bayes import GaussianNB def classify(features_train, labels_train): # create classifier gnb = GaussianNB() # fit the classifier on the training features and labels cls = gnb.fit(features_train, labels_train) # return the fit classifier return cls

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RamiliaR/django

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refs/heads/master

2021-01-10T18:50:07.143708

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('congratulation', '0002_auto_20150714_1310'), ] operations = [ migrations.AddField( model_name='customer', name='email', field=models.CharField(null=True, max_length=75), ), migrations.AddField( model_name='customer', name='password', field=models.CharField(null=True, max_length=30), ), migrations.AddField( model_name='customer', name='username', field=models.CharField(null=True, max_length=30), ), ]

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[]

no_license

Vamanan/inf553

114e6186f5349da996fc18c00773fc1ecb799edd

b2b826d3d0e2939eeba12b4b8df3f6bbd2b673da

refs/heads/master

2021-01-19T05:01:14.230363

2015-11-06T02:17:05

42,913,613

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py

import MapReduce import sys import re """ tf df Example in the Simple Python MapReduce Framework """ mr = MapReduce.MapReduce() # ============================= # Do not modify above this line def mapper(record): # key: document identifier # value: document contents dname = record[0] content = record[1].lower() words = content.split() for w in set(words): if re.match(r'\w+$', w): mr.emit_intermediate(w, (dname,words.count(w))) def reducer(key, list_of_values): # key: word # value: df along with individual tf tuples dftotal = len(list_of_values) mr.emit((key, dftotal,list_of_values)) # Do not modify below this line # ============================= if __name__ == '__main__': inputdata = open(sys.argv[1]) mr.execute(inputdata, mapper, reducer)

[ "passmaster10@bitbucket.org" ]

passmaster10@bitbucket.org

cd2694476723a2181a5d941f4cd30cf0eec0d1b6

035df9fcfd3737dbb18c804c7c396b5f94bed435

/WatershedFermeture/watershed/Watershed - femeture.py

1ae445772cdcc995e3d744876151f5ea11d20d4b

[]

no_license

ASTAugustin/IMA_P1_Projet

01d93759eaa8c180ec809de7e6359b9e3249061d

d48bc5b3d3f12acde0a1f2cee0ff6b1dcb4f197c

refs/heads/master

2020-07-30T09:11:55.913404

2019-11-05T10:08:38

210,168,008

0

null

UTF-8

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py

import numpy as np from collections import deque import cv2 # Implementation of: # Pierre Soille, Luc M. Vincent, "Determining watersheds in digital pictures via # flooding simulations", Proc. SPIE 1360, Visual Communications and Image Processing # '90: Fifth in a Series, (1 September 1990); doi: 10.1117/12.24211; # http://dx.doi.org/10.1117/12.24211 class Watershed(object): MASK = -2 WSHD = 0 INIT = -1 INQE = -3 def __init__(self, levels=256): self.levels = levels # Neighbour (coordinates of) pixels, including the given pixel. def _get_neighbors(self, height, width, pixel): return np.mgrid[ max(0, pixel[0] - 1):min(height, pixel[0] + 2), max(0, pixel[1] - 1):min(width, pixel[1] + 2) ].reshape(2, -1).T '''使用示例： Ex.返回包括自己的邻居 >>> np.mgrid[0:3,0:3].reshape(2,-1).T array([[0, 0], [0, 1], [0, 2], [1, 0], [1, 1], [1, 2], [2, 0], [2, 1], [2, 2]]) ''' def apply(self, image): current_label = 0 flag = False fifo = deque() # 堆栈 height, width = image.shape total = height * width labels = np.full((height, width), self.INIT, np.int32) ## self 表示 this #形成一个元素为-1的矩阵 reshaped_image = image.reshape(total) ## grey level of one degree # [y, x] pairs of pixel coordinates of the flattened image. pixels = np.mgrid[0:height, 0:width].reshape(2, -1).T # Coordinates of neighbour pixels for each pixel. neighbours = np.array([self._get_neighbors(height, width, p) for p in pixels]) ## Not Clear if len(neighbours.shape) == 3: # Case where all pixels have the same number of neighbours. neighbours = neighbours.reshape(height, width, -1, 2) else: # Case where pixels may have a different number of pixels. neighbours = neighbours.reshape(height, width) indices = np.argsort(reshaped_image) ## sort of index from small value to big value sorted_image = reshaped_image[indices] ## At hte beginning of this array locate the ligntest pixel sorted_pixels = pixels[indices] ## At hte beginning of this array locate the index of the ligntest pixel # self.levels evenly spaced steps from minimum to maximum. levels = np.linspace(sorted_image[0], sorted_image[-1], self.levels) ## return an array from the min to the max containing levels numbers. level_indices = [] current_level = 0 # Get the indices that deleimit pixels with different values. for i in range(total): if sorted_image[i] > levels[current_level]: ## higher than sea level # Skip levels until the next highest one is reached. while sorted_image[i] > levels[current_level]: current_level += 1 level_indices.append(i) ## a ladder array level_indices.append(total) start_index = 0 for stop_index in level_indices: # Mask all pixels at the current level. for p in sorted_pixels[start_index:stop_index]: labels[p[0], p[1]] = self.MASK # Initialize queue with neighbours of existing basins at the current level. for q in neighbours[p[0], p[1]]: # p == q is ignored here because labels[p] < WSHD if labels[q[0], q[1]] >= self.WSHD: labels[p[0], p[1]] = self.INQE fifo.append(p) break # Extend basins. while fifo: p = fifo.popleft() # Label p by inspecting neighbours. for q in neighbours[p[0], p[1]]: # Don't set lab_p in the outer loop because it may change. lab_p = labels[p[0], p[1]] lab_q = labels[q[0], q[1]] if lab_q > 0: if lab_p == self.INQE or (lab_p == self.WSHD and flag): labels[p[0], p[1]] = lab_q elif lab_p > 0 and lab_p != lab_q: labels[p[0], p[1]] = self.WSHD flag = False elif lab_q == self.WSHD: if lab_p == self.INQE: labels[p[0], p[1]] = self.WSHD flag = True elif lab_q == self.MASK: labels[q[0], q[1]] = self.INQE fifo.append(q) # Detect and process new minima at the current level. for p in sorted_pixels[start_index:stop_index]: # p is inside a new minimum. Create a new label. if labels[p[0], p[1]] == self.MASK: current_label += 1 fifo.append(p) labels[p[0], p[1]] = current_label while fifo: q = fifo.popleft() for r in neighbours[q[0], q[1]]: if labels[r[0], r[1]] == self.MASK: fifo.append(r) labels[r[0], r[1]] = current_label start_index = stop_index return labels if __name__ == "__main__": import numpy as np np.set_printoptions(threshold=np.inf) ##from Watershed import Watershed from PIL import Image import matplotlib.pyplot as plt import cv2 w = Watershed() image = np.array(cv2.imread('Ex1.PNG', 0)) print(image) kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2, 2)) ## Here, (2,2) means the two diameters of the ellipse. binary = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel) print(binary) plt.imshow(binary) plt.show() ##gray = cv2.cvtColor('Ex1.PNG', cv2.COLOR_RGB2GRAY) ##ret, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU) ##kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3)) ##binary = cv2.morphologyEx(binary, cv2.MORPH_CLOSE, kernel) ##print("xxxxxxxx") ##/labels = w.apply(binary) #label = w.apply(image) #print(labels) ##plt.imshow(labels, cmap='Paired', interpolation='nearest') ##/plt.imshow(labels) ##/plt.show()

[ "celestine_jinyi@163.com" ]

celestine_jinyi@163.com

c74987a27b063d67e8ce049ee6e834b52db5fe03

c09b899e42e867e20993488e5f4e3d79c4eb779f

/movies/views.py

1aa3c1ecd81aa00297a088047aaa610c2979330b

[]

no_license

JaycobDuffel/Vidly

33913b50096ac8b1cd54bcc62c503287d1b11c47

b0aa76e6e9634a7ab64b50652db941577567932a

refs/heads/master

2022-12-23T14:26:34.360432

2020-10-07T02:37:18

300,044,549

0

null

UTF-8

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425

py

from django.http import HttpResponse, Http404 from django.shortcuts import render, get_object_or_404 from .models import Movie # Create your views here. def index(request): movies = Movie.objects.all() return render(request, "movies/index.html", {"movies": movies}) def detail(request, movie_id): movie = get_object_or_404(Movie, pk=movie_id) return render(request, "movies/detail.html", {"movie": movie})

[ "jbdcoding@gmail.com" ]

jbdcoding@gmail.com

3fd8971af0057cfe6f9120d8654640df8c971099

99e76e9e4c8031418c4c50217b48adf1d880cf2f

/setup.py

6974fdc5b21fd1b544eac798d4363569ad4198d7

[ "MIT" ]

permissive

grow/grow-ext-responsive-styles

d75a5abb070613641e3da9f3f4cf7dc07e88c51f

bb3d8f68edc1f3e1bdf508bb5df8d5b296574e9b

refs/heads/master

2021-01-03T14:04:15.882718

2020-05-20T20:38:09

240,096,948

0

MIT

2020-05-20T20:34:58

2020-02-12T19:27:42

HTML

UTF-8

Python

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349

py

from setuptools import setup setup( name='grow-ext-responsive-styles', version='1.0.0', zip_safe=False, license='MIT', author='Grow Authors', author_email='hello@grow.io', include_package_data=True, packages=[ 'responsive_styles', ], package_data={ 'responsive_styles': ['*.html'], }, )

[ "jeremydw@gmail.com" ]

jeremydw@gmail.com

5a46605486c336baa1b97ab5f88da4b51e4a3852

4425cd9025e430735ad81cc09d126d0ce9929e07

/order/api/serializers.py

135e26fec2699d1787648ba38587774330d16a14

[]

no_license

omkarrane/ecommerce-api

e7c611776977be0c753157fe9d2819f08bf86f78

f1d11277571df9cadbba7c8f1d2892cf8895b43c

refs/heads/master

2020-03-19T21:11:11.065801

2018-06-11T13:44:09

136,931,627

0

null

UTF-8

Python

false

1,058

py

from django.contrib.contenttypes.models import ContentType from django.contrib.auth import get_user_model from django.db.models import Q from django.contrib.sites.shortcuts import get_current_site from django.utils.encoding import force_bytes, force_text from django.utils.http import urlsafe_base64_encode, urlsafe_base64_decode from django.template.loader import render_to_string from django.contrib.auth.models import User from django.core.mail import EmailMessage from accounts.api.utils import generateToken, decodeToken import random from rest_framework.serializers import ( CharField, EmailField, HyperlinkedIdentityField, ModelSerializer, SerializerMethodField, ValidationError, PrimaryKeyRelatedField ) from retail.models import ( Retail_Info, Retail_Warehouse, Retail_Product ) from order.models import ( Order, ) User = get_user_model() class OrderSerializer(ModelSerializer): class Meta: model = Order fields = [ 'item_list', 'total_cost' ]

[ "omkarrane10@gmail.com" ]

omkarrane10@gmail.com

17ebad59e8fb8cac9e54303768189e0f854b5502

e8fa6b783794bbd636d4ba815fd90390aabb4d73

/integration/combination/test_state_machine_with_api.py

20deaad43f516f96a4e5f315b5d52d5a729aa9ee

[ "MIT", "Apache-2.0" ]

permissive

Skarlso/serverless-application-model

eb74d7dee11bf0a911e1e0dbb70bd03d4cbbbad7

172c832c053b3b5405dd4e85853386cc5a98841e

refs/heads/develop

2023-08-21T09:24:32.577637

2022-10-28T23:14:59

325,041,387

1

Apache-2.0

2022-10-31T17:41:47

2020-12-28T15:01:05

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UTF-8

Python

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py

from unittest.case import skipIf from integration.helpers.base_test import BaseTest from integration.helpers.common_api import get_policy_statements from integration.helpers.resource import current_region_does_not_support from integration.config.service_names import STATE_MACHINE_WITH_APIS @skipIf( current_region_does_not_support([STATE_MACHINE_WITH_APIS]), "StateMachine with APIs is not supported in this testing region", ) class TestStateMachineWithApi(BaseTest): def test_state_machine_with_api(self): self.create_and_verify_stack("combination/state_machine_with_api") outputs = self.get_stack_outputs() region = outputs["Region"] partition = outputs["Partition"] state_name_machine_arn = outputs["MyStateMachineArn"] implicit_api_role_name = outputs["MyImplicitApiRoleName"] implicit_api_role_arn = outputs["MyImplicitApiRoleArn"] explicit_api_role_name = outputs["MyExplicitApiRoleName"] explicit_api_role_arn = outputs["MyExplicitApiRoleArn"] rest_apis = self.get_stack_resources("AWS::ApiGateway::RestApi") implicit_rest_api_id = next( (x["PhysicalResourceId"] for x in rest_apis if x["LogicalResourceId"] == "ServerlessRestApi"), None ) explicit_rest_api_id = next( (x["PhysicalResourceId"] for x in rest_apis if x["LogicalResourceId"] == "ExistingRestApi"), None ) self._test_api_integration_with_state_machine( implicit_rest_api_id, "POST", "/pathpost", implicit_api_role_name, implicit_api_role_arn, "MyStateMachinePostApiRoleStartExecutionPolicy", state_name_machine_arn, partition, region, ) self._test_api_integration_with_state_machine( explicit_rest_api_id, "GET", "/pathget", explicit_api_role_name, explicit_api_role_arn, "MyStateMachineGetApiRoleStartExecutionPolicy", state_name_machine_arn, partition, region, ) def _test_api_integration_with_state_machine( self, api_id, method, path, role_name, role_arn, policy_name, state_machine_arn, partition, region ): apigw_client = self.client_provider.api_client resources = apigw_client.get_resources(restApiId=api_id)["items"] resource = get_resource_by_path(resources, path) post_method = apigw_client.get_method(restApiId=api_id, resourceId=resource["id"], httpMethod=method) method_integration = post_method["methodIntegration"] self.assertEqual(method_integration["credentials"], role_arn) # checking if the uri in the API integration is set for Step Functions State Machine execution expected_integration_uri = "arn:" + partition + ":apigateway:" + region + ":states:action/StartExecution" self.assertEqual(method_integration["uri"], expected_integration_uri) # checking if the role used by the event rule to trigger the state machine execution is correct start_execution_policy = get_policy_statements(role_name, policy_name, self.client_provider.iam_client) self.assertEqual(len(start_execution_policy), 1, "Only one statement must be in Start Execution policy") start_execution_policy_statement = start_execution_policy[0] self.assertTrue(type(start_execution_policy_statement["Action"]) != list) policy_action = start_execution_policy_statement["Action"] self.assertEqual( policy_action, "states:StartExecution", "Action referenced in event role policy must be 'states:StartExecution'", ) self.assertTrue(type(start_execution_policy_statement["Resource"]) != list) referenced_state_machine_arn = start_execution_policy_statement["Resource"] self.assertEqual( referenced_state_machine_arn, state_machine_arn, "State machine referenced in event role policy is incorrect", ) def get_resource_by_path(resources, path): return next((resource for resource in resources if resource["path"] == path), None)

[ "noreply@github.com" ]

Skarlso.noreply@github.com

9202483cde896d82ddfe2dbd4a5a205224bd657e

8c8eaf2a82d74d9652fbe23e23b0f5856a947e7e

/tokens/models.py

6fc0c00181648dcf65eb4b1f0060c3ce5fc4f7a9

[]

no_license

CallistoNetwork/Galileo-Backend

2cb0c1dbe20f43a56cab566ee77338cc68f8fda8

beec34cc9e480b49b6efbe0bd1cd19ddcfcb8340

refs/heads/master

2020-04-03T02:29:00.910607

2019-01-27T21:12:07

151,890,661

1

0

null

UTF-8

Python

false

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py

from django.db import models from explorer.models import TimeStampModel class Token(TimeStampModel): """ * name -> Name of token | String | optional * symbol -> Trading symbol | String | optional * total_supply -> The total supply if the token | Decimal | optional * decimals -> Number of decimal place the token can be subdivided to | Int | optional * type -> type of Token | String | required * cataloged -> if token information has been cataloged | Boolean | optional * contract_address_hash -> Foreign key to address | ForeignKey | required """ name = models.CharField( max_length=255, blank=True ) symbol = models.CharField( max_length=50, blank=True ) total_supply = models.DecimalField( null=True, max_digits=120, decimal_places=0 ) decimals = models.PositiveIntegerField( null=True ) token_type = models.CharField( max_length=100, ) cataloged = models.BooleanField( null=True ) contract_address_hash = models.ForeignKey( 'address.Address', on_delete=models.PROTECT ) class TokenTransfer(TimeStampModel): """ * amount -> token transfer amount | Decimal | Optional * from_address_hash -> Address send token | Foreign Key | Required * to_address_hash -> Address received token | Foreign Key | Required * token_contract_address_hash -> Address of the token contract | Forreign Key | Required * token_id -> Id of the token, only ERC-721 tokens | Optional * transaction_hash -> Transaction token | Foreign Key | Required * log_index -> Index of the corresponding Log in the transaction | Positive Int | Required """ amount = models.DecimalField( null=True, max_digits=120, decimal_places=0 ) from_address_hash = models.ForeignKey( 'address.Address', on_delete=models.PROTECT, related_name='token_transfer_from_address' ) to_address_hash = models.ForeignKey( 'address.Address', on_delete=models.PROTECT, related_name='token_transfer_to_address' ) token_contract_address_hash = models.ForeignKey( 'address.Address', on_delete=models.PROTECT, related_name='token_contract_address' ) token_id = models.PositiveIntegerField( null=True ) transaction_hash = models.ForeignKey( 'transactions.Transaction', on_delete=models.PROTECT ) log_index = models.PositiveIntegerField()

[ "gollum23@gmail.com" ]

gollum23@gmail.com

af935ba661ffbdb6c3921e41c3c65c2ba9235ccd

843d9f17acea5cfdcc5882cf8b46da82160c251c

/adafruit_stepper.py

8e9319c17ea13b32312acbe50d018791ab2ea40a

[]

no_license

gunny26/raspberry

7c1da63785c86412af9fa467ea231b19a97f4384

e4eb0d2f537b319d41b6c50b59e69fb297c62d25

refs/heads/master

2016-09-06T14:02:30.122102

2014-01-29T16:31:08

null

0

null

UTF-8

Python

false

1,335

py

import RPi.GPIO as GPIO import time GPIO.cleanup() GPIO.setmode(GPIO.BCM) enable_pin = 18 coil_A_1_pin = 4 coil_A_2_pin = 17 coil_B_1_pin = 23 coil_B_2_pin = 24 GPIO.setup(enable_pin, GPIO.OUT) GPIO.setup(coil_A_1_pin, GPIO.OUT) GPIO.setup(coil_A_2_pin, GPIO.OUT) GPIO.setup(coil_B_1_pin, GPIO.OUT) GPIO.setup(coil_B_2_pin, GPIO.OUT) GPIO.output(enable_pin, 1) def forward(delay, steps): for i in range(0, steps): setStep(1, 0, 1, 0) time.sleep(delay) setStep(0, 1, 1, 0) time.sleep(delay) setStep(0, 1, 0, 1) time.sleep(delay) setStep(1, 0, 0, 1) time.sleep(delay) def backwards(delay, steps): for i in range(0, steps): setStep(1, 0, 0, 1) time.sleep(delay) setStep(0, 1, 0, 1) time.sleep(delay) setStep(0, 1, 1, 0) time.sleep(delay) setStep(1, 0, 1, 0) time.sleep(delay) def setStep(w1, w2, w3, w4): GPIO.output(coil_A_1_pin, w1) GPIO.output(coil_A_2_pin, w2) GPIO.output(coil_B_1_pin, w3) GPIO.output(coil_B_2_pin, w4) while True: try: delay = raw_input("Delay between steps (milliseconds)?") steps = raw_input("How many steps forward? ") forward(int(delay) / 1000.0, int(steps)) steps = raw_input("How many steps backwards? ") backwards(int(delay) / 1000.0, int(steps)) except KeyboardInterrupt: GPIO.cleanup()

[ "arthur.messner@gmail.com" ]

arthur.messner@gmail.com

f7675475bf4180ae4b05a6af1aebe4521077a136

e131e752d826ae698e12e7bc0583362741f9d942

/AWS.py

c886890f56cf208b48066e6c151d54611fc0b574

[]

no_license

abalberchak/TouchFace

ba30565be91b848126524aa47377789253370e04

d093ece8890b68c72e0855a024d908105df99b94

refs/heads/master

2021-01-11T01:43:35.067808

2016-09-29T03:41:13

69,530,129

1

0

null

UTF-8

Python

false

1,318

py

#----------------------------------------- Intent Schema Below:------------------------------ { "intents": [ { "intent": "AMAZON.ResumeIntent" }, { "intent": "AMAZON.PauseIntent" }, { "intent": "DojoInfoIntent" }, { "intent": "AMAZON.HelpIntent" }, { "intent": "AMAZON.StopIntent" }, { "intent": "TextBrendenIntent" }, { "intent": "GetTouchFaceIntent" }, { "intent": "DojoBrendenIntent" }, { "intent": "AskBrendan" }, { "intent": "twilioIntent" }, { "intent": "GroupTextIntent", "slots": [ { "name": "Name", "type": "MEMBERS" } ] } ] } #----------------------------------------- Utterances Below:------------------------------ DojoInfoIntent what is the coding dojo DojoInfoIntent tell me about the coding dojo TextBrendenIntent Text Brendan GetTouchFaceIntent Tell what does Brenden say DojoBrendenIntent who is brenden AskBrendan what is touchface twilioIntent hi annet GroupTextIntent text {Name}

[ "minhpn.org.ec@gmail.com" ]

minhpn.org.ec@gmail.com

4f21bdabf36e65773d6c9289dad471ce6aa16e31

178ae62be7de20a50f96361e80bdcff5a5493ae2

/koica/templatetags/koica.py

36b3a706fcb6f684e4f9896f13b5cc8b25353d75

[ "MIT" ]

permissive

synw/django-koica

a043800c15fad69f2024557e62fcf0ac4808ffae

d8b1c9fa70c428f0aa0db0c523524e9d2ef27377

refs/heads/master

2021-01-10T03:15:24.570691

2015-12-09T14:55:29

46,188,691

0

2

null

UTF-8

Python

false

200

py

from django import template from koica.utils import sanitize_html register = template.Library() @register.filter(is_safe=True) def remove_pre(value): return sanitize_html(value, remove_pre=True)

[ "synwe@yahoo.fr" ]

synwe@yahoo.fr

0389e54314c5db68c26748f6b8dc17cb73d58775

fc2eb6f42183d7ca0142a039400548194130ff47

/items.py

23c16a8d8a825dcbafff96eb5e47f06777634b2e

[]

no_license

vinaygulani1/RealEstatePricePrediction

5e3cf7ab5659f1f28a3cf81853fca2a42e4044ac

8cb30eea4c10147b4dba69058620e092b06617a1

refs/heads/master

2021-01-10T01:27:21.865451

2015-11-20T08:15:18

46,197,917

1

2

null

UTF-8

Python

false

615

py

# -*- 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 Property(scrapy.Item): data_code = scrapy.Field() latitude = scrapy.Field() longtitude = scrapy.Field() property_type = scrapy.Field() address = scrapy.Field() city = scrapy.Field() askprice = scrapy.Field() sellingprice = scrapy.Field() year_built = scrapy.Field() living_area = scrapy.Field() num_parking = scrapy.Field() num_bath = scrapy.Field() num_bed = scrapy.Field() num_room = scrapy.Field() sold_date = scrapy.Field()

[ "vinay.gulani@relishly.com" ]

vinay.gulani@relishly.com

630cda4283ce85c051de8920c72c86b1b92d2ca7

a305456a1b6509437883bb3de8d0c3f2968694a1

/apis/connect/auth.py

55e8b22c76ffb214dbba1f656da60e331a09384f

[]

no_license

yoshow/tornado-quick-start

6ebeeb87e09b5a9c357cdc2332c7d80fdaa96d06

6e00dd3a873e624c1a39cc5f94d47ddc1a366a00

refs/heads/master

2021-01-18T15:27:31.410263

2018-06-19T16:21:59

86,654,471

0

null

UTF-8

Python

false

6,223

py

# -*- coding: utf-8 -*- """ OAuth 2.0 """ import uuid import json from sqlalchemy import select, text import x.data.orm from x.web.apis import WebApiResponse from models.membership import AccountInfo, MemberInfo from models.connect import ConnectAuthorizationCodeInfo, ConnectAccessTokenInfo class Auth(object): """ 验证管理 """ def authorize(self, req, res=WebApiResponse()): """ 授权验证 :param clientId: 客户端应用 :param redirectUri: 重定向地址 :param responseType: 响应类型 :param scope: 授权范围 :param style: 样式自定义样式 :param loginName: 登录名 :param password: 密码 :returns: this is a description of what is returned :raises keyError: raises an exception """ clientId = req.get("clientId") redirectUri = req.get("redirectUri") responseType = req.get("responseType") scope = req.get("scope") style = req.get("style") loginName = req.get("loginName") password = req.get("password") session = x.data.orm.createSession() # 获取当前用户信息 account = session.query(AccountInfo).filter( text("loginName='" + loginName + "' and password='" + password + "'")).first() if account is None: if responseType is None: res.message.returnCode = 1 res.message.value = u"帐号或者密码错误。" return res else: # 如果响应类型 # TODO: 输出登录页面 pass else: # 检验是否有授权码 # cliendId account authorizationCode = session.query(ConnectAuthorizationCodeInfo).filter( text("appKey='" + clientId + "' and accountId='" + account.id + "'")).first() # 如果不存在则新增授权码信息 if authorizationCode is None: # 设置对象信息 authorizationCode = ConnectAuthorizationCodeInfo() authorizationCode.id = str(uuid.uuid4()) authorizationCode.appKey = clientId authorizationCode.accountId = account.id authorizationCode.authorizationScope = scope == '' and "public" or scope session.add(authorizationCode) # 写数据库，但并不提交 session.flush() session.commit() # 设置访问令牌 # 设置会话信息 accessToken = session.query(ConnectAccessTokenInfo).filter( text("appKey='" + clientId + "' and accountId='" + account.id + "'")).first() # 如果不存在则新增授权码信息 if accessToken is None: accessToken = ConnectAccessTokenInfo(id=str(uuid.uuid4())) # 设置对象信息 accessToken.id = str(uuid.uuid4()) accessToken.appKey = clientId accessToken.accountId = account.id accessToken.authorizationScope = scope == '' and "public" or scope session.add(accessToken) # 写数据库，但并不提交 # session.flush() session.commit() # 记录日志 res.data = accessToken res.message.returnCode = 0 res.message.value = u"验证成功。" return res print "authorize loginName:" + loginName + " password:" + password res.message.returnCode = 0 res.message.value = u"执行成功。" return res def token(self, req, res=WebApiResponse()): """ 获取令牌信息 :param code: 授权码信息 :returns: this is a description of what is returned :raises keyError: raises an exception """ code = req.get("code") session = x.data.orm.createSession() authorizationCode = session.query(ConnectAuthorizationCodeInfo).filter_by( id=code).first() # 如果不存在则新增授权码信息 if authorizationCode is None: res.message.returnCode = 1 res.message.value = "authorization code not find" return res accessToken = session.query(ConnectAccessTokenInfo).filter( text("appKey='" + authorizationCode.appKey + "' and accountId='" + authorizationCode.accountId + "'")).first() if accessToken is None: res.message.returnCode = 1 res.message.value = "access code not find" return res return res def refresh(self, req, res=WebApiResponse()): """ 刷新令牌信息 """ print "token" return "connect.auth.refresh" def me(self, req, res=WebApiResponse()): """ 当前用户信息 """ token = req.get("token") session = x.data.orm.createSession() accessToken = session.query( ConnectAccessTokenInfo).filter_by(id=token).first() if accessToken is None: res.message.returnCode = 1 res.message.value = "people not find" return res else: # 根据访问令牌返回当前湖用户 # IMemberInfo member = # MembershipManagement.Instance.MemberService[accessTokenInfo.AccountId] member = session.query(MemberInfo).filter_by( id=accessToken.accountId).first() if member is None: res.message.returnCode = 1 res.message.value = "people not find" return res # 输出个人信息 res.data = member res.message.returnCode = 0 res.message.value = "success" return res def ToPeopleJson(self, account): """ 将人员信息格式化为特定格式 """ return { "id": account.id, "name": account.name, "loginName": account.loginName, # "certifiedAvatar": account.certifiedAvatar, "status": account.status }

[ "ruanyu@live.com" ]

ruanyu@live.com

ed949aaf72486dd9f746cc86f1ee975b0529cb89

3bc7c8a96be2cf2b60f8c1757e71a980140bd43b

/bus_plotter.py

91c2983b5b0cd903810a8fe00e57eba7302aea54

[]

no_license

chrisjkuch/busdata

98bff373efaacdd4cb6d1e618165d3de63296d69

f68ba523191dbcb50d6ffaeb20c73e7fc6225c0e

refs/heads/master

2020-12-31T06:56:27.346245

2017-05-17T03:15:27

80,571,966

0

null

UTF-8

Python

false

2,629

py

# -*- coding: utf-8 -*- """ Created on Tue Aug 9 17:28:01 2016 @author: chris """ import pandas as pd import matplotlib.pyplot as plt import matplotlib.dates as md import numpy as np import datetime as dt def dayTimeToDateTime(fltime): hours = int(fltime * 24) minutes = int(fltime * 24 * 60 - hours * 60) seconds = 0 #int(fltime * 24 * 3600 - hours * 60 * 60 - minutes * 60) return(dt.datetime(2016,8,1,hours,minutes,seconds)) def setSameDay(dt_obj): return(dt.datetime(2016,8,1,dt_obj.hour,dt_obj.minute,dt_obj.second)) # Temporary: Pick the stop we are interested in stop = u'Sherman/Foster' etoc = pd.read_csv('evanstontochicago.csv') ctoe = pd.read_csv('chicagotoevanston.csv') # Get the x-coordinates of vertical lines marking scheduled times # Read the log data from the spreadsheet busdata = pd.read_csv('test.csv') bd = busdata[[u'Stop Name', u'Time']] bd[u'Time'] = bd[u'Time'].astype('datetime64').apply(lambda x: md.date2num(setSameDay(x))) groupedstops = bd.groupby(u'Stop Name') curStop = bd.groupby(u'Stop Name').groups[stop] times = bd.iloc[curStop, 1] #times = times.apply(lambda x: md.date2num(setSameDay(x))) # Set up the histogram fig = plt.figure() my_bins = md.date2num(dt.datetime(2016,8,1,0,0,0)) + np.linspace(6,24,(18*60)+1)/24. hfmt = md.DateFormatter('%H:%M') thisroute = etoc thesestops = list(thisroute.columns.values) nplots = len(thesestops) i = 1 all_axes = [] for stop in thesestops: if(i > 1): fig.add_subplot(nplots, 1, i, sharex=all_axes[0], sharey=all_axes[0]) else: fig.add_subplot(nplots, 1, 1) i += 1 curStop = groupedstops.groups[stop] curTimes = bd.iloc[curStop, 1] ax = curTimes.plot.hist(bins=my_bins) ax2 = curTimes[-1:].plot.hist(bins=my_bins) all_axes.append(ax) #nboundsched = etoc[stop].apply(lambda x: md.date2num(dayTimeToDateTime(x))) cursched = thisroute[stop].apply(lambda x: md.date2num(dayTimeToDateTime(x))) top = 6 #y1n = [0] * len(nboundsched) #y2n = [top] * len(nboundsched) y1 = [0] * len(cursched) y2 = [top] * len(cursched) plt.vlines(cursched, y1, y2) ax.xaxis.set_major_locator(md.HourLocator()) ax.xaxis.set_major_formatter(hfmt) ax.yaxis.set_ticks([]) ax.yaxis.set_label_position('right') plt.ylabel(stop, rotation=0) #stopdata = scheduledata[stop].apply(lambda x: md.date2num(dayTimeToDateTime(x))) #y1 = [0] * len(stopdata) #y2 = [2] * len(stopdata) plt.xticks(rotation=45) plt.xlim([md.date2num(dt.datetime(2016,8,1,6,0,0)), md.date2num(dt.datetime(2016,8,1,23,59,0))]) plt.gcf().subplots_adjust(hspace=0) plt.show()

[ "noreply@github.com" ]

chrisjkuch.noreply@github.com

3b9a743d044c3344202f2e666d176447cdb0156d

d8fa64b4176c8c434e8812faed51bc246e6794d7

/pythoncode/homework_api/test_tag_manage.py

a36ea37af271617e587d652c840657a68702532f

[]

no_license

tanya931117/TestDev

0103ff216af48d80811e81ac91756fdc878ef43d

3eba391c1405238e6a7ccc267b1f3722364a0a5c

refs/heads/master

2022-12-09T18:42:29.940915

2020-09-10T11:38:07

270,223,394

0

null

UTF-8

Python

false

2,658

py

#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2020/8/8 13:27 # @Author : tanya # @File : test_tag_manage.py # @Software: PyCharm import pytest import yaml from pythoncode.PO.contact_tag_api import ContactTagApi from pythoncode.PO.we_work_api import WeWorkApi @pytest.mark.usefixtures("start_case") class TestTagManage(): def setup_class(self): self.contact_tag = ContactTagApi() wework =WeWorkApi() self.token = wework.get_token(self.contact_tag._contact_secret) #用钩子函数pytest_generate_tests加载参数 func_params = {"test_all": ["tagname", "add_tag_api.yml"], "test_tag_mem":["tagid,userlist","add_tag_mem_api.yml"]} def get_params(path): with open(path, "r",encoding="utf-8") as f: params = yaml.safe_load(f) return params @pytest.mark.skip def test_all(self,tagname): response = self.contact_tag.get_tag_list(self.token) result = response.json() #{'errcode': 0, 'errmsg': 'ok', 'taglist': [{'tagid': 1, 'tagname': '标签一'}, {'tagid': 2, 'tagname': '标签二'}]} if len(result["taglist"]) >0: for tag in result["taglist"]: if tag["tagname"] == tagname: self.contact_tag.del_tag({"tagid":tag["tagid"]},self.token) break tag = { "tagname": tagname } res = self.contact_tag.add_tag(tag,self.token) assert res.json()["errmsg"].startswith("created") def test_tag_mem(self,tagid,userlist): response = self.contact_tag.get_tag_mems({"tagid":tagid},self.token) result = response.json() #{'errcode': 0, 'errmsg': 'ok', 'userlist': [{'userid': 'LiTan', 'name': '李土云'}, {'userid': 'Miao', 'name': '张世锋'}, {'userid': 'eunhyuk.lee', 'name': 'LeeEunHyuk'}, {'userid': 'donghae.lee', 'name': 'LeeDongHae'}], 'partylist': [], 'tagname': '标签一'} if len(result["userlist"]) > 0: userlist_del = [] for user in result["userlist"]: if user["userid"] in userlist: userlist_del.append(user["userid"]) if len(userlist_del) > 0 : params = { "tagid": tagid, "userlist": userlist_del } self.contact_tag.del_tag_mem(params,self.token) params = { "tagid": tagid, "userlist": userlist } res = self.contact_tag.add_tag_mem(params,self.token).json() #{'errcode': 0, 'errmsg': 'ok', 'invalidparty': []} assert res["errmsg"] == "ok"

[ "tanya_li_931117@163.com" ]

tanya_li_931117@163.com

bee4f557d4eaf73b50b39fe6da8aff6cd3065efd

fc8ef4d310eaf76384cd1f29a45e65ffd1849a6b

/back-end/api/migrations/0004_article_source_name.py

371ef4c62f6d991ee5521f8b6c4f6db3a7a673c5

[]

no_license

mykola829/webl_lab_3_4

70c6c52e23962741971efc65a5a15aed5822059f

c47f09a03157e71687294b7a61863d775c6e95e2

refs/heads/master

2022-09-13T02:27:17.381772

2020-06-04T11:57:55

268,151,334

0

null

UTF-8

Python

false

434

py

# Generated by Django 3.0.6 on 2020-06-03 08:03 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('api', '0003_auto_20200603_1059'), ] operations = [ migrations.AddField( model_name='article', name='source_name', field=models.CharField(default=0, max_length=512), preserve_default=False, ), ]

[ "mykola829@gmail.com" ]

mykola829@gmail.com

394178ecf0b8ba5aa5f8ffac26bfc54459935fb5

812f7c3982f2525bc7c3013938f70ffdda4abe1e

/vehicles/admin.py

875e37a21f750efb0d84da238affc5a7c39c522c

[]

no_license

roditashakya/ebooking

7393aa651d2ddc979016000d62d6f44a3caddf57

3cdfe3a9b911835b4fcc32ae63e1e28983a4d6d9

refs/heads/master

2020-05-01T09:42:29.961770

2019-03-24T19:54:56

177,406,292

0

null

UTF-8

Python

false

408

py

from django.contrib import admin # Register your models here. from .models import SeatTemplate, TravelDetail, Vehicle, Booking, BookingUser, Seat, Schedule, Search admin.site.register(SeatTemplate) admin.site.register(TravelDetail) admin.site.register(Vehicle) admin.site.register(Booking) admin.site.register(BookingUser) admin.site.register(Seat) admin.site.register(Schedule) admin.site.register(Search)

[ "rodishakya@gmail.com" ]

rodishakya@gmail.com

70b411ba66521bde662ff464e6ab782442fa0581

1508f7da93705839660e4fdfb87df7a9664bf087

/a10API/a10API/flask/bin/migrate

bff34539b04e8d820b8b866d8ef3ee3bbc9995fb

[]

no_license

Younglu125/A10_Networks

1a1ecebb28dd225f6a1f901a7c28350300df356d

78a177ae4c8638d58dc873e4b1c589a1d5aaa717

refs/heads/master

2020-06-17T00:35:30.325740

2016-03-21T18:17:30

null

0

null

UTF-8

Python

false

354

#!/home/echou/a10API/flask/bin/python # EASY-INSTALL-ENTRY-SCRIPT: 'sqlalchemy-migrate==0.7.2','console_scripts','migrate' __requires__ = 'sqlalchemy-migrate==0.7.2' import sys from pkg_resources import load_entry_point if __name__ == '__main__': sys.exit( load_entry_point('sqlalchemy-migrate==0.7.2', 'console_scripts', 'migrate')() )

[ "info@pythonicneteng.com" ]

info@pythonicneteng.com

5c578a84b20bd789b433432dfab0e9c7bdd67379

b08a6adc56016a706d84752bcfb6d5bdf014f9fd

/easyocr/DBNet/assets/ops/dcn/functions/deform_pool.py

b4c9943cbc10212f1db23910dcafbd2a2d1b7435

[ "Apache-2.0" ]

permissive

JaidedAI/EasyOCR

c83903d2f0ac2adfda89b35274e71a410f7d12e8

f947eaa36a55adb306feac58966378e01cc67f85

refs/heads/master

2023-08-08T08:34:28.434530

2023-07-04T12:44:09

247,266,215

20,057

2,937

Apache-2.0

2023-09-12T22:16:00

2020-03-14T11:46:39

Python

UTF-8

Python

false

5,953

py

''' Modified by Jaided AI Released Date: 31/08/2022 Description: - Add support for Deformable convolution operator on CPU for forward propagation. - Change to Just-in-Time loading approach ''' import os import warnings import torch from torch.autograd import Function from torch.utils import cpp_extension # TODO - Jaided AI: # 1. Find a better way to handle and support both Ahead-of-Time (AoT) and Just-in-Time (JiT) compilation. # 2. Find a better way to report error to help pinpointing issues if there is any. # Note on JiT and AoT compilation: # This module supports both AoT and JiT compilation approaches. JiT is hardcoded as the default. If AoT compiled objects are present, it will supercede JiT compilation. def custom_formatwarning(msg, *args, **kwargs): # ignore everything except the message return str(msg) + '\n' warnings.formatwarning = custom_formatwarning dcn_dir = os.path.dirname(os.path.dirname(__file__)) try: from .. import deform_pool_cpu warnings.warn("Using precompiled deform_pool_cpu from {}".format(deform_pool_cpu.__file__)) dcn_cpu_ready = True except: try: warnings.warn("Compiling deform_pool_cpu ...") warnings.warn("(This may take a while if this module is loaded for the first time.)") deform_pool_cpu = cpp_extension.load( name="deform_pool_cpu", sources=[os.path.join(dcn_dir, 'src', "deform_pool_cpu.cpp"), os.path.join(dcn_dir, 'src', "deform_pool_cpu_kernel.cpp")]) warnings.warn("Done.") dcn_cpu_ready = True except Exception as error: warnings.warn(' '.join([ "Failed to import or compile 'deform_pool_cpu' with the following error", "{}".format(error), "Deformable convulution and DBNet will not be able to run on CPU." ])) dcn_cpu_ready = False if torch.cuda.is_available(): try: from .. import deform_pool_cuda warnings.warn("Using precompiled deform_pool_cuda from {}".format(deform_pool_cuda.__file__)) dcn_cuda_ready = True except: try: warnings.warn("Compiling deform_pool_cuda ...") warnings.warn("(This may take a while if this module is loaded for the first time.)") deform_pool_cuda = cpp_extension.load( name="deform_pool_cuda", sources=[os.path.join(dcn_dir, 'src', "deform_pool_cuda.cpp"), os.path.join(dcn_dir, 'src', "deform_pool_cuda_kernel.cu")]) warnings.warn("Done.") dcn_cuda_ready = True except Exception as error: warnings.warn(' '.join([ "Failed to import or compile 'deform_pool_cuda' with the following error", "{}".format(error), "Deformable convulution and DBNet will not be able to run on GPU." ])) dcn_cuda_ready = False class DeformRoIPoolingFunction(Function): @staticmethod def forward(ctx, data, rois, offset, spatial_scale, out_size, out_channels, no_trans, group_size=1, part_size=None, sample_per_part=4, trans_std=.0): ctx.spatial_scale = spatial_scale ctx.out_size = out_size ctx.out_channels = out_channels ctx.no_trans = no_trans ctx.group_size = group_size ctx.part_size = out_size if part_size is None else part_size ctx.sample_per_part = sample_per_part ctx.trans_std = trans_std assert 0.0 <= ctx.trans_std <= 1.0 n = rois.shape[0] output = data.new_empty(n, out_channels, out_size, out_size) output_count = data.new_empty(n, out_channels, out_size, out_size) if not data.is_cuda and dcn_cpu_ready: deform_pool_cpu.deform_psroi_pooling_cpu_forward( data, rois, offset, output, output_count, ctx.no_trans, ctx.spatial_scale, ctx.out_channels, ctx.group_size, ctx.out_size, ctx.part_size, ctx.sample_per_part, ctx.trans_std) elif data.is_cuda and dcn_cuda_ready: deform_pool_cuda.deform_psroi_pooling_cuda_forward( data, rois, offset, output, output_count, ctx.no_trans, ctx.spatial_scale, ctx.out_channels, ctx.group_size, ctx.out_size, ctx.part_size, ctx.sample_per_part, ctx.trans_std) else: device_ = input.device.type raise RuntimeError( "Input type is {}, but 'deform_conv_{}.*.so' is not imported successfully.".format(device_, device_), ) if data.requires_grad or rois.requires_grad or offset.requires_grad: ctx.save_for_backward(data, rois, offset) ctx.output_count = output_count return output @staticmethod def backward(ctx, grad_output): if not grad_output.is_cuda: raise NotImplementedError("DCN operator for cpu for backward propagation is not implemented.") data, rois, offset = ctx.saved_tensors output_count = ctx.output_count grad_input = torch.zeros_like(data) grad_rois = None grad_offset = torch.zeros_like(offset) deform_pool_cuda.deform_psroi_pooling_cuda_backward( grad_output, data, rois, offset, output_count, grad_input, grad_offset, ctx.no_trans, ctx.spatial_scale, ctx.out_channels, ctx.group_size, ctx.out_size, ctx.part_size, ctx.sample_per_part, ctx.trans_std) return (grad_input, grad_rois, grad_offset, None, None, None, None, None, None, None, None) deform_roi_pooling = DeformRoIPoolingFunction.apply

[ "rkcosmos@gmail.com" ]

rkcosmos@gmail.com

9f3846001c1c354cfeae9bb360ec909db95dbc28

3105edcc2326ed9d49c408833268453a942ba474

/web/modules/api/__init__.py

a164dbb5f0124fc34c059789ae5b31e2ac14489d

[]

no_license

cgle/sumopromo

641e56a14654fbd9368f1653a0d5282726d3d533

1e395eaeeb44acaa23f2ffb63ad68b7ded0799cf

refs/heads/master

2019-08-01T02:54:44.736669

2017-03-31T00:32:26

75,031,942

0

null

UTF-8

Python

false

98

py

from flask import Blueprint bp = Blueprint('api', __name__) from web.modules.api.views import *

[ "cglehh@gmail.com" ]

cglehh@gmail.com

6e8d64feec1287a4b57e616953041d7efd2c6bc7

245a9680c18bb08b338b024e8cb61da899097cec

/gamestore/store/urls.py

391ff5e89cf9119bd07a47ae7fdfcfa0e21e395f

[]

no_license

arnold1000/onlinestore

c5f2c003076d248cc18a3e2698c0e09cb4c0a18c

fe8a393a270dfb6cd32c0628385a0777d815f8e9

refs/heads/master

2021-09-22T23:19:15.736468

2020-02-20T10:04:50

240,704,666

0

null

2020-02-15T12:58:46

2020-02-15T12:17:51

JavaScript

UTF-8

Python

false

955

py

from django.urls import include, path from . import views urlpatterns = [ path('', views.games, name='store-home'), path(r'^activate/(?P<uidb64>[0-9A-Za-z_\-]+)/(?P<token>[0-9A-Za-z]{1,13}-[0-9A-Za-z]{1,20})/$', views.activate, name='activate'), path('games/', views.games, name='games'), path('games/<int:game_id>/', views.game, name='game'), path('games/<int:game_id>/score', views.save_score, name='save_score'), path('games/<int:game_id>/save', views.save_game, name='save_game'), path('games/<int:game_id>/load', views.load_game, name='load_game'), path('games/new/', views.add_new, name='add_game'), path('games/<int:game_id>/modify', views.modify, name='modify'), path('games/<int:game_id>/delete', views.delete, name='delete'), path('shop/', views.shop, name='shop'), path('shop/<int:game_id>/', views.buy, name="buy"), path('shop/payment/', views.buy_response, name="buy_response") ]

[ "arttu.e.koponen@aalto.fi" ]

arttu.e.koponen@aalto.fi

f6f2eef9a2b17f09fa5e8751ab81ae99d47ae64e

e85a47a94e59f4c2feaec8aa635aa9d42e0edc00

/django_project/urls.py

f03e6a43c2f71e2fc1f25d65ab2be1a55421f207

[]

no_license

afAditya/Django_Blog

1bf0e2949db03a6813db380c49cdca324cd7173b

7662d4765a03b25814481edc5a189b97d6899b41

refs/heads/master

2023-02-17T03:58:49.091498

2021-01-20T18:18:51

330,613,546

0

null

UTF-8

Python

false

1,393

py

"""django_project URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/2.2/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.contrib.auth import views as auth_views from django.urls import path,include from django.conf import settings from django.conf.urls.static import static from users import views as users_views urlpatterns = [ path('admin/', admin.site.urls), path('register/', users_views.register, name='register'), path('profile/', users_views.profile, name='profile'), path('login/', auth_views.LoginView.as_view(template_name='users/login.html'), name='login'), path('logout/', auth_views.LogoutView.as_view(template_name='users/logout.html'), name='logout'), path('', include('blog.urls')), ] if settings.DEBUG: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

[ "adityasinghrajput971@gmail.com" ]

adityasinghrajput971@gmail.com

a7072cf5db1b5527272336c6191bab4e1770b928

c840f190b3540bf212de2c70563e57da278fa9cb

/hyacinth.py

055e735da50162825883a5c29dfd69fcd0f7242d

[]

no_license

edelooff/hyacinth

b768a871d476dd120f7d2d1acb039a6a9ebf2e19

0a6dd15fa1b1357afa566f924ad27b744582464b

refs/heads/master

2022-04-16T13:24:18.986246

2020-04-01T08:15:36

251,756,604

0

null

UTF-8

Python

false

6,538

py

from collections import ( Counter, defaultdict) import random import re import sys DESIGN = re.compile(r''' (?P<design>[A-Z]) (?P<size>[SL]) (?P<flowers>(:?\d+[a-z])*) # The specification is fuzzy on 1+ or 0+ (?P<total>\d+)''', re.VERBOSE) DESIGN_FLOWER = re.compile(r''' (?P<count>\d+) (?P<species>[a-z])''', re.VERBOSE) class Pool: def __init__(self): self.common_species = set() self.designers = [] self.flowers = Counter() def add_designer(self, designer): """Adds a BouquetDesigner for the pool size. It also updates the set of known required species, allowing better picking of 'filler' flowers for requested bouquets. """ self.designers.append(designer) self.common_species |= designer.required_flowers.keys() def add_flower(self, species): """Adds a flower of given species to the pool of available flowers.""" self.flowers[species] += 1 for designer in self.designers: if designer.add(species): print(self.create_bouquet(designer)) def create_bouquet(self, designer): """Creates a bouquet according to the given designers design. After creating the bouquet, other designers are informed of the removal of flower species from the shared pool. """ bouquet = designer.create(self.flowers, self.common_species) bouquet_string = designer.stringify_bouquet(bouquet) for bundle in bouquet.items(): for designer in self.designers: designer.remove(*bundle) return bouquet_string class BouquetDesigner: def __init__(self, design, flower_size, required_flowers, bouquet_size): self.design = design self.flower_size = flower_size self.bouquet_size = bouquet_size self.required_flowers = required_flowers self.filler_quantity = bouquet_size - sum(required_flowers.values()) self.available_filler = 0 self.available_flowers = Counter() def add(self, species): """Adds a species of flower to the local availability cache. In addition. this will check whether a bouquet can be created based on the recently seen flowers. If one can be created, this returns True. """ if species in self.required_flowers: self.available_flowers[species] += 1 else: self.available_filler += 1 return self.can_create() def can_create(self): """Checks whether there are enough flowers to create a bouquet. This will check if there is enough quantity of the required flowers and if so, will check if there is enough filler to create a full bouquet. """ for flower, quantity in self.required_flowers.items(): if self.available_flowers[flower] < quantity: return False available = sum(self.available_flowers.values(), self.available_filler) if available >= self.bouquet_size: return True return False def create(self, pool, common_species): """Returns a bouquet (species listing) assembled from the given pool. After picking the required flowers, if additional flowers are needed as filler, this method selects a sample of flowers from the rest of the pool in two steps: 1. Species of flowers used by other BouquetDesigners are avoided so that selection for this bouquet causes the least conflict. 2. A random sample of flowers is picked, to avoid consistently stealing from the same other designers. Randomly selecting also hopefully generates nice and pleasing outcomes for the recipient, though this hypothesis has not been tested in the least ;-) In all cases we bias to picking filler flowers that we have a surplus of. In an ideal world we would have a function that determines the correct bias to introduce here. """ bouquet = Counter() for species, quantity in self.required_flowers.items(): pool[species] -= quantity bouquet[species] += quantity # Pick the remaining flowers if self.filler_quantity: remaining = self.filler_quantity for do_not_pick in (common_species, set()): population = [] for species in pool.keys() ^ do_not_pick: population.extend([species] * pool[species]) sample_size = min(len(population), remaining) for species in random.sample(population, sample_size): pool[species] -= 1 bouquet[species] += 1 remaining -= sample_size if not remaining: break return bouquet def remove(self, species, quantity): """Proceses removal of flowers from the flower pool. This will update either the cache for available required flowers, or if it's a species not -required- for this design, the filler count. """ if species in self.required_flowers: self.available_flowers[species] -= quantity else: self.available_filler -= quantity def stringify_bouquet(self, bouquet): """Returns the formatted bouquet string for this designer.""" flowers = sorted(bouquet.items()) flowerstring = (f'{count}{species}' for species, count in flowers) return f'{self.design}{self.flower_size}{"".join(flowerstring)}' @classmethod def from_specification(cls, design): """Creates a BouquetDesigner instance from a string specification.""" spec = DESIGN.match(design).groupdict() spec_flowers = DESIGN_FLOWER.findall(spec['flowers']) flowers = {species: int(count) for count, species in spec_flowers} return cls(spec['design'], spec['size'], flowers, int(spec['total'])) def read_until_empty(fp): """Yields lines from the given filepointer until an empty line is hit.""" while (line := fp.readline().strip()): yield line def main(): pools = defaultdict(Pool) for design in read_until_empty(sys.stdin): designer = BouquetDesigner.from_specification(design) pools[designer.flower_size].add_designer(designer) for species, size in read_until_empty(sys.stdin): pools[size].add_flower(species) if __name__ == '__main__': main()

[ "elmer.delooff@gmail.com" ]

elmer.delooff@gmail.com

3ad99e3d7e9841da8f65b2003210f661dc96df4a

0296bc69a0d9608ed826ad7a719395f019df098f

/Tools/Compare_images.py

f4ba586d2dfa3fcae52e277676f2b4a82ffdf59a

[]

no_license

jcn16/Blender_HDRmap_render

c0486a77e04c5b41a6f75f123dbdb3d10c682367

50e6cdb79fef83081de9830e7105dd425a235a9e

refs/heads/main

2023-07-19T22:22:53.622052

2021-08-20T06:29:10

377,757,283

2

0

null

UTF-8

Python

false

1,771

py

import cv2 import numpy as np def tianchong(img): m = img.shape[0] n = img.shape[1] append = int(np.ceil(abs(m - n) / 2)) if m > n: constant = cv2.copyMakeBorder(img, 0, 0, append, append, cv2.BORDER_CONSTANT, value=(0, 0, 0)) else: constant = cv2.copyMakeBorder(img, append, append, 0, 0, cv2.BORDER_CONSTANT, value=(0, 0, 0)) constant = cv2.resize(constant, (512, 512)) return constant def compare(): image_1=cv2.imread('/media/jcn/新加卷/JCN/JCN_test_datset/RayTracing/Train_HDR_512/126111539900259-h/0_-32_1_dikhololo_sunset_8k_324/raytracing.png') mask_1=cv2.imread('/media/jcn/新加卷/JCN/JCN_test_datset/RayTracing/Train_HDR_512/126111539900259-h/0_-32_1_dikhololo_sunset_8k_324/alpha.png') image_1=tianchong(image_1) mask_1=tianchong(mask_1) image_2=cv2.imread('/media/jcn/新加卷/JCN/JCN_test_datset/RayTracing/Train_HDR_512/126111539900259-h/0_-32_1_dikhololo_sunset_8k_324/shading.png') image_1=image_1/255.0*mask_1/255.0 image_2=image_2/255.0*mask_1/255.0 cv2.imshow('image_1',np.asarray(image_1*255,dtype=np.uint8)) cv2.imshow('image_2',np.asarray(image_2*255,dtype=np.uint8)) res=np.asarray(np.clip((image_1-image_2)*255,0,255),dtype=np.uint8) cv2.imshow('res',res) cv2.waitKey(0) def composite(): shading=cv2.imread('/media/jcn/新加卷/JCN/RelightHDR/TEST/images_high_res/10/raytracing.png') albedo=cv2.imread('/home/jcn/桌面/Oppo/Results_albedo/10/p_albedo.png') mask=cv2.imread('/home/jcn/桌面/Oppo/Results_albedo/10/gt_mask.png') relight=albedo/255.0*shading/255.0*mask/255.0 relight=np.asarray(relight*255,dtype=np.uint8) cv2.imshow('relight',relight) cv2.waitKey(0) if __name__=='__main__': compare()

[ "591599635@qq.com" ]

591599635@qq.com

70c1632fe562644b920d482abf735a3bc08211cc

673d7a7b8c43523c459c661c2e360d4398a53b28

/pip_upgrade-runner.py

c2d4d9070ba92561c8da342417040194fe860ecc

[ "MIT" ]

permissive

addisonElliott/pip_upgrade_outdated

19e3c16c5f8910cb20c142842dc2a992fd8801b7

2cf809ff9be2ab4070b75f5959ebcf21d9d34d82

refs/heads/master

2020-04-09T19:03:26.602029

2019-01-15T16:29:57

160,532,458

0

MIT

2018-12-05T14:43:44

2018-12-05T14:43:43

null

UTF-8

Python

false

229

py

#!/usr/bin/env python # -*- coding: utf-8 -*- """Convenience wrapper for running pushover directly from source tree.""" from pip_upgrade_outdated.upgrade_pip_packages import main if __name__ == '__main__': main()

[ "a.h.jaffe@gmail.com" ]

a.h.jaffe@gmail.com

f0ebbd9f94e46663f17baf0ce5d22f3445f7b76f

b1a584df32c2d11a0648dec27e2f9cacd540a7f2

/realtors/migrations/0001_initial.py

22c019188655b19dcb1f7eae14c3d94742f64f7b

[]

no_license

sree61/Django_project_realestate

b822f65dff1ea03e3739208c66b8a5f559bce1c0

8da46343a0275f8cd13bd71ed74eee6e4efb003a

refs/heads/master

2020-04-26T04:02:40.594223

2019-03-12T18:01:51

173,288,055

0

null

UTF-8

Python

false

922

py

# Generated by Django 2.1.7 on 2019-02-27 03:20 import datetime from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Realtor', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=200)), ('photo', models.ImageField(upload_to='photos/%Y/%m/%d/')), ('description', models.TextField(blank=True)), ('phone', models.CharField(max_length=20)), ('email', models.CharField(max_length=50)), ('is_mvp', models.BooleanField(default=False)), ('hire_date', models.DateTimeField(blank=True, default=datetime.datetime.now)), ], ), ]

[ "sreeamaravila@gmmail.com" ]

sreeamaravila@gmmail.com

94d24bbab5fe5d3c8c83cd1748d41d53ea82f907

1f40d003bdba15086e0c2e7828398e3e8e6041e3

/robotics/fileread.py

a9bd74f6e7dc443010797d5ad2675de000633796

[]

no_license

qwertpas/pythontests

0bb4982479f998625c0fd9d852df1ef66e3ada71

37fc2b253bf24d210364bacaf53f27347e9d29c1

refs/heads/master

2023-08-09T03:20:35.853236

2023-08-05T16:43:44

177,456,276

0

null

UTF-8

Python

false

1,817

py

import numpy as np import matplotlib.pyplot as plt from matplotlib import collections as mc import re def extract_nums(text): # text.replace('[', ' ') # text.replace(']', ' ') p = re.compile(r'\d+\.\d+') # Compile a pattern to capture float values floats = [float(i) for i in p.findall(text)] # Convert strings to float return np.array(floats) with open('ece470/data.txt') as f: lines = f.readlines() trials = [] for line in lines: if line == '\n': continue if 'start kill' in line: trials.append({}) continue if 'actual pos' in line: nums = list(extract_nums(line)) trials[-1]['actual'] = nums if 'detect pos' in line: nums = list(extract_nums(line)) trials[-1]['detect'] = nums if 'camera err' in line: nums = list(extract_nums(line)) trials[-1]['camera'] = nums actuals = [] detects = [] cameras = [] lines = [] for trial in trials: actuals.append(trial['actual']) detects.append(trial['detect']) cameras.append(trial['camera']) lines.append((trial['actual'], trial['detect'])) actuals = np.array(actuals) detects = np.array(detects) cameras = np.array(cameras) fig, ax = plt.subplots() ax.scatter(x=actuals[:,0], y=actuals[:,1], label='Actual position') ax.scatter(x=detects[:,0], y=detects[:,1], label='Detected position') ax.scatter(x=0, y=0, label='Robot base') # lines = [[(0, 1), (1, 1)], [(2, 3), (3, 3)], [(1, 2), (1, 3)]] lc = mc.LineCollection(lines, color='black', linewidths=1) ax.add_collection(lc) print(len(actuals)) ax.autoscale() accuracy = np.mean(cameras) ax.set_title(f"Cockroach detection accuracy with average error: {np.round(accuracy, 3)} m") ax.set_xlabel("Global X axis (m)") ax.set_ylabel("Global Y axis (m)") ax.legend() plt.show()

[ "cyx3@illinois.edu" ]

cyx3@illinois.edu

db365ccaef28c337a5d9c69e8c10f082020063ee

c940bcb25e1ed315263b25cbdac49cc4bf92cac1

/env/vkviewer/python/georef/georeferenceutils.py

92de981594a95d6365cfb3fdb3f7e7f015ad83b1

[]

no_license

kwaltr/vkviewer

281a3f1b5b08a18a89f232ecd096cea44faca58b

01d64df0a9266c65e0c3fb223e073ef384281bdc

refs/heads/master

2021-01-16T22:09:41.821531

2014-02-07T17:19:04

null

0

null

UTF-8

Python

false

4,844

py

''' Created on Oct 15, 2013 @author: mendt ''' import subprocess """ function: parseYSize @param - imageFile {String} - path to a image file @return - {Integer} - value which represents the y size of the file This function parse the x,y size of a given image file """ def parseXYSize(imageFile): # run gdalinfo command on imageFile and catch the response via Popen response = subprocess.Popen("gdalinfo %s"%imageFile, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True) # read the console output line by line for line in response.stdout: if 'Size is ' in line: x,y = line[8:].split(', ') #print "X: %s, Y: %s"%(x,y) return float(x),float(y) """ Functions for getting the gcps. """ def getGCPsAsString(unorderedPixels, verzeichnispfad, georefCoords): pure_gcps = getGCPs(unorderedPixels, verzeichnispfad, georefCoords) str_gcps = [] for tuple in pure_gcps: string = " ".join(str(i) for i in tuple[0])+", "+" ".join(str(i) for i in tuple[1]) str_gcps.append(string) return str_gcps def getGCPs(unorderedPixels, verzeichnispfad, georefCoords): # transformed the pixel coordinates to the georef coordinates by recalculating the y values, # because of a different coordinate origin transformedUnorderedPixels = [] xSize, ySize = parseXYSize(verzeichnispfad) for tuple in unorderedPixels: transformedUnorderedPixels.append((tuple[0],ySize-tuple[1])) # now order the pixel coords so that there sorting represents the order llc, ulc, urc, lrc transformedOrderedPixels = orderPixels(transformedUnorderedPixels) # now create the gcp list try: gcpPoints = [] for i in range(0,len(transformedOrderedPixels)): pixelPoints = (transformedOrderedPixels[i][0],transformedOrderedPixels[i][1]) georefPoints = (georefCoords[i][0],georefCoords[i][1]) gcpPoints.append((pixelPoints,georefPoints)) return gcpPoints except: raise def orderPixels(unorderdPixels): """ Function brings a list of tuples which are representing the clipping parameter from the client in the order llc ulc urc lrc and gives them back at a list. Only valide for pixel coords @param clippingParameterList: list whichcomprises 4 tuples of x,y coordinates """ xList = [] yList = [] for tuple in unorderdPixels: xList.append(tuple[0]) yList.append(tuple[1]) orderedList = [0, 0, 0, 0] xList.sort() yList.sort() for tuple in unorderdPixels: if (tuple[0] == xList[0] or tuple[0] == xList[1]) and \ (tuple[1] == yList[2] or tuple[1] == yList[3]): orderedList[0] = tuple elif (tuple[0] == xList[0] or tuple[0] == xList[1]) and \ (tuple[1] == yList[0] or tuple[1] == yList[1]): orderedList[1] = tuple elif (tuple[0] == xList[2] or tuple[0] == xList[3]) and \ (tuple[1] == yList[0] or tuple[1] == yList[1]): orderedList[2] = tuple elif (tuple[0] == xList[2] or tuple[0] == xList[3]) and \ (tuple[1] == yList[2] or tuple[1] == yList[3]): orderedList[3] = tuple return orderedList """ Functions for creating the commands for command line """ """ function: addGCPToTiff @param - gcPoints {list of gcp} - list of ground control points @param - srid {Integer} - epsg code of coordiante system @param - srcPath {String} @param - destPath {String} @return - command {String} Add the ground control points via gdal_translate to the src tiff file """ def addGCPToTiff(gcPoints,srs,srcPath,destPath): def addGCPToCommandStr(command,gcPoints): for string in gcPoints: command = command+"-gcp "+str(string)+" " return command command = "gdal_translate --config GDAL_CACHEMAX 500 -a_srs epsg:%s "%srs command = addGCPToCommandStr(command,gcPoints) command = command+str(srcPath)+" "+str(destPath) return command """ function: georeferenceTiff @param - shapefilePath {String} @param - srid {Integer} - epsg code of coordiante system @param - srcPath {String} @param - destPath {String} @param - tyoe {String} - if 'fast' there is less compression @return - command {String} Georeferencing via gdalwarp """ def georeferenceTiff(shapefilePath, srid, srcPath, destPath, type=None): if type == 'fast': command = "gdalwarp --config GDAL_CACHEMAX 500 -wm 500 -overwrite -co TILED=YES -cutline %s \ -crop_to_cutline -t_srs epsg:%s %s %s"%(shapefilePath,srid,srcPath,destPath) return command

[ "jacobmendt@googlemail.com" ]

jacobmendt@googlemail.com

0a8927cc6f6bdd664bb45f44bde260086ecb6f86

14dd1fd527bb7e30abd2e4ee64ffb34fe84f1e06

/jzc/postgresInsert.py

ff33ab9255a1b1887bfe3ed360a277bce6e8efcf

[]

no_license

wdwoodee/luozt

7a78e7e66f9bc51159f6f03ca4702f4db17dc580

6a4bc86969f6f2db24d9d7d1446e4a4f97846165

refs/heads/master

2021-05-04T04:46:30.812814

2016-10-14T08:30:19

70,889,537

0

null

UTF-8

Python

false

2,093

py

#_DEBUG = True import psycopg2 import pdb try: conn = psycopg2.connect(database="workspace2", user="postgres", password="postgres", host="127.0.0.1", port="54321") except Exception: print('Get a exception: Connect failed') print("successfully") cur = conn.cursor() try: errLine = 0 with open("test1ip.csv") as f: i = 0 while True: ln = f.readline() if not ln: break items = ln.split(',') if(items[0]=='LAN Segment'): continue if len(items) != 13: errLine += 1 continue #pdb.set_trace() if items[10] == "Device Interface": items[10]=9 elif items[10] == "ARP Table": items[10]=7 elif items[10] == "CDP/LLDP Table": items[10]=8 elif items[10] == "MAC Table": items[10]=6 elif items[10] == "Manual": items[10]=1 else : items[10]=0 #if ( not items[8].isnumeric()) or ( not items[10].isnumeric()) or ( not items[11].isnumeric()) : # pdb.set_trace() # errLine += 1 # continue try: sqlinsert = "select saveoneiprecode_ip2mac_x64 ( false, '%s', '%s', '', '%s', '%s', '%s', '%s', '%s', '%s', %s, %s, %s)" % (items[9], items[0], items[1], items[2], items[4], items[5], items[6], items[7], items[8], items[10], items[11]) cur.execute(sqlinsert) except Exception: print("Insert Err:%s",sqlinsert) errLine += 1 continue i += 1 if ( (i%5)==0 ): #pdb.set_trace() conn.commit() conn.commit() print ("Complete: insert %d , err %d" %( i, errLine) ); conn.close() except Exception: print('Get a exception')

[ "18511246771@163.com" ]

18511246771@163.com

1ea1be419f42ba190fe16b9772f1ad7bd9ddae47

afcb1837c0c50fd823964594780111d530a73f8e

/qtjsonschema/__main__.py

d267aee40ac8028b7f4edc49b45fb37004ea312c

[]

no_license

ArtemioGiovanni/pyqtschema

332a60462db5ac2e113256c940b557d77e16c0cf

7d84d8754d039504a5905289a33574abe5318e89

refs/heads/master

2020-05-04T20:38:22.850664

2014-08-15T22:07:40

null

0

null

UTF-8

Python

false

2,848

py

#!/usr/bin/env python """ pyqtschema - Python Qt JSON Schema Tool Generate a dynamic Qt form representing a JSON Schema. Filling the form will generate JSON. """ from PyQt4 import QtCore, QtGui from qtjsonschema.widgets import create_widget class MainWindow(QtGui.QWidget): def __init__(self, parent=None): QtGui.QWidget.__init__(self, parent) self.setWindowTitle("PyQtSchema") # Menu bar # File # Open # Save # -- # Close self.menu = QtGui.QMenuBar(self) self.file_menu = self.menu.addMenu("&File") _action_open = QtGui.QAction("&Open Schema", self) _action_open.triggered.connect(self._handle_open) _action_save = QtGui.QAction("&Save", self) _action_save.triggered.connect(self._handle_save) _action_quit = QtGui.QAction("&Close", self) _action_quit.triggered.connect(self._handle_quit) self.file_menu.addAction(_action_open) self.file_menu.addAction(_action_save) self.file_menu.addSeparator() self.file_menu.addAction(_action_quit) # Scrollable region for schema form self.content_region = QtGui.QScrollArea(self) vbox = QtGui.QVBoxLayout() vbox.addWidget(self.menu) vbox.addWidget(self.content_region) vbox.setContentsMargins(0,0,0,0) hbox = QtGui.QHBoxLayout() hbox.setContentsMargins(0,0,0,0) hbox.addLayout(vbox) self.setLayout(hbox) def process_schema(self, schema): """ Load a schema and create the root element. """ import json import collections with open(schema) as f: _schema = json.loads(f.read(), object_pairs_hook=collections.OrderedDict) if "title" in _schema: self.setWindowTitle("%s - PyQtSchema" % _schema["title"]) self.content_region.setWidget(create_widget(_schema.get("title", "(root)"), _schema)) self.content_region.setWidgetResizable(True) def _handle_open(self): # Open JSON Schema schema = QtGui.QFileDialog.getOpenFileName(self, 'Open Schema', filter="JSON Schema (*.schema *.json)") if schema: self.process_schema(schema) def _handle_save(self): # Save JSON output import json obj = self.content_region.widget().to_json_object() outfile = QtGui.QFileDialog.getSaveFileName(self, 'Save JSON', filter="JSON (*.json)") if outfile: with open(outfile, 'w') as f: f.write(json.dumps(obj)) def _handle_quit(self): # TODO: Check if saved? self.close() if __name__ == "__main__": import sys app = QtGui.QApplication(sys.argv) main_window = MainWindow() main_window.show() sys.exit(app.exec_())

[ "klange@yelp.com" ]

klange@yelp.com

9b577e0397ab602bffa52d7290910ae2afb30a2d

19872c0f261100d3a7a3c770aa16ef719b7f397b

/PythonProjects/crawl_work/crawl_190605_51jop/nationwide_make_urls.py

b5e328efff01c1510da69677c7ba2fb1cb81e680

[]

no_license

enjoqy/PythonProjects

b7951bd13c32ec40842e8c7f7a4b2a32929d3d8b

ae1a4b1a55a7906bb4dd78e8bd43d19decec48ba

refs/heads/master

2020-06-20T03:50:32.814009

2019-07-15T09:17:50

184,964,749

0

null

UTF-8

Python

false

2,367

py

#!/usr/bin/env python # -*- coding:utf-8 -*- # @Time: 2019/5/16 001612:11 # @Author: junhi # java # url = 'https://search.51job.com/list/010000,000000,0000,00,9,99,java,2,1.html?lang=c&stype=&postchannel=0000&workyear=99&cotype=99&degreefrom=99&jobterm=99&companysize=99&providesalary=99&lonlat=0%2C0&radius=-1&ord_field=0&confirmdate=9&fromType=&dibiaoid=0&address=&line=&specialarea=00&from=&welfare=' # 平面设计 # url = 'https://search.51job.com/list/010000,000000,0000,00,9,99,%25E5%25B9%25B3%25E9%259D%25A2,2,1.html?lang=c&stype=&postchannel=0000&workyear=99&cotype=99&degreefrom=99&jobterm=99&companysize=99&providesalary=99&lonlat=0%2C0&radius=-1&ord_field=0&confirmdate=9&fromType=&dibiaoid=0&address=&line=&specialarea=00&from=&welfare=' # 大数据 # url = 'https://search.51job.com/list/010000,000000,0000,00,9,99,%25E5%25A4%25A7%25E6%2595%25B0%25E6%258D%25AE,2,1.html?lang=c&stype=&postchannel=0000&workyear=99&cotype=99&degreefrom=99&jobterm=99&companysize=99&providesalary=99&lonlat=0%2C0&radius=-1&ord_field=0&confirmdate=9&fromType=&dibiaoid=0&address=&line=&specialarea=00&from=&welfare=' # 云计算 url = 'https://search.51job.com/list/010000,000000,0000,00,9,99,%25E4%25BA%2591%25E8%25AE%25A1%25E7%25AE%2597,2,1.html?lang=c&stype=&postchannel=0000&workyear=99&cotype=99&degreefrom=99&jobterm=99&companysize=99&providesalary=99&lonlat=0%2C0&radius=-1&ord_field=0&confirmdate=9&fromType=&dibiaoid=0&address=&line=&specialarea=00&from=&welfare=' provinces = [ '北京', '上海', '广东省', '深圳', '天津', '重庆', '江苏省', '浙江省', '四川省', '海南省', '福建省', '山东省', '江西省', '广西', '安徽省', '河北', '河南省', '湖北省', '湖南省', '陕西省', '山西省', '黑龙江省', '辽宁省', '吉林省', '云南省', '贵州省', '甘肃省', '内蒙古', '宁夏', '西藏', '新疆', '青海省', ] def get_nationwide_urls(): i = 1 nationwide_java_urls = {} for province in provinces: if i <= 9: province_url = url[0:31] + str(i) + url[32:] print(province_url) else: province_url = url[0:30] + str(i) + url[32:] print(province_url) nationwide_java_urls[province] = province_url i = int(i) if i == 32: break i += 1 return nationwide_java_urls

[ "gdlzhh321@163.com" ]

gdlzhh321@163.com

969e32c9641599d2ac6f429333a9a104f34dff93

6a33819de8b7aae1388f94dd0142819693da5cdf

/src/kitchen/auth_backend.py

73d1663bd8fa0f64f9a2fe2bf8ad9e972e0a97eb

[]

no_license

goudete/clustr

9ffa7deb9cec4492a7f65c888287976bdbd267f9

0a6904c7f29a3341fef55933cf7d73c8326fdb33

refs/heads/master

2023-04-06T06:39:52.048484

2020-09-19T14:26:27

289,341,808

0

null

UTF-8

Python

false

707

py

from django.contrib.auth.backends import ModelBackend from .models import Kitchen from django.contrib.auth.models import User from restaurant_admin.models import Restaurant class PasswordlessAuthBackend(ModelBackend): """Log in to Django without providing a password, just a cashier code/login number """ def authenticate(self, request, login_number=None): try: rest = Restaurant.objects.filter(kitchen_login_no=login_number).first() return rest except rest.DoesNotExist: return None def get_user(self, user_id): try: return User.objects.get(pk=user_id) except Kitchen.DoesNotExist: return None

[ "rfitch@oxy.edu" ]

rfitch@oxy.edu

6fa3e92bc057c995f58b43c06e0f64afa615f900

9a5c5ead8471c7bb71fe90429651b9d863ee2474

/bots/dayandtime.py

4d69b928ec7f213382d296b3b691500461877e14

[ "MIT", "LicenseRef-scancode-unknown-license-reference" ]

permissive

mwaiton/TwitterBots

12af71e19895a53791d12b7a788a508752b0f1d9

3c641690c5047a1bbbbf3c47bb90256b7cf4f271

refs/heads/master

2023-02-08T09:12:44.300477

2020-12-30T02:56:04

null

0

null

UTF-8

Python

false

474

py

import calendar from datetime import datetime """Python program to find day of the week for a given date. Also finds current date, which can be used to find the day. """ # To find a day of the week. def find_day(date): day = datetime.strptime(date, '%Y-%m-%d').weekday() return calendar.day_name[day] # To find today's date. def today(): return str(datetime.date(datetime.now())) if __name__ == '__main__': d = today() print("Today is", find_day(d))

[ "bexxmodd@seas.upenn.edu" ]

bexxmodd@seas.upenn.edu

97c5e4d3a1702140c12048536f8ec60595290914

b2be86ae60e9698a3daf78fdedacac631dd60cab

/django/user/tests/test_models.py

b0d94ce44fa3f235d6c64af4738666ba937c104d

[]

no_license

TigenTigen/do_you_know

351326388bb1ae9caffed246b8fcdcb8ba7af594

0c6a5b001243fafa1b8382f89ec8bf7aef640f2e

refs/heads/master

2020-06-13T13:26:29.402100

2019-08-07T06:27:37

194,670,788

0

null

UTF-8

Python

false

2,716

py

from django.test import TestCase from user.factories import AdvUserFactory from user.models import AdvUser, signer, dt_engine, mail from django.urls import reverse class TestAdvUserModel(TestCase): def test_str_for_user_created_by_factory(self): user = AdvUserFactory(username='some_user') self.assertEqual(str(user), 'some_user') def test_save_for_user_created_by_social_auth(self): user = AdvUser(username='id123456789', first_name='fn', last_name='ln', password='test_password') user.save() self.assertEqual(user.username, 'fn ln') def test_confirm_for_not_active_user(self): user = AdvUserFactory(is_active=False) self.assertFalse(user.is_active) user.confirm() self.assertTrue(user.is_active) def test_get_email_context(self): user = AdvUserFactory() link = reverse('user:registration_confirmed', kwargs={'sign': signer.sign(user.username)}) context = user.get_email_context() self.assertIsNotNone(context) self.assertIn('confirmation_link', str(context)) self.assertIn(link, str(context)) def test_send_confirmation_email(self): user = AdvUserFactory() link = reverse('user:registration_confirmed', kwargs={'sign': signer.sign(user.username)}) connection = mail.get_connection(backend='django.core.mail.backends.locmem.EmailBackend') outbox = user.send_confirmation_email(connection) self.assertEqual(len(outbox), 1) self.assertEqual(outbox[0].subject, 'Подтверждение регистрации') self.assertIn(link, outbox[0].body) def create_users_for_test(self, number): for i in range(number): user = AdvUserFactory() return AdvUser.objects.all() def test_social_count(self): users = self.create_users_for_test(10) for user in users: if user.social_auth.exists(): self.assertNotEqual(user.social_count(), 0) else: self.assertEqual(user.social_count(), 0) def test_total_points_count(self): users = self.create_users_for_test(10) for user in users: if user.replies.exists(): self.assertNotEqual(user.total_points_count(), 0) else: self.assertEqual(user.total_points_count(), 0) def test_get_points_rating_queryset_manager_with_users_and_no_replies(self): users = self.create_users_for_test(10) full_qs = AdvUser.objects.get_queryset() test_qs = AdvUser.objects.get_points_rating_queryset() self.assertEqual(full_qs.count(), 10) self.assertEqual(test_qs.count(), 0)

[ "Eleriya-25@yandex.ru" ]

Eleriya-25@yandex.ru

cc97266146a0e0a5a82b27d70bd9882600547a30

606afd1394624127e37bf82328e1d21f00f8a2ca

/Layer.py

0c21cbb41afc36e4c72c6f5a25825d5ff2ed8f09

[]

no_license

JoelGooch/Tensorflow-Final-Year-Project

b4d437a778f19e5cf7adc16afd82b5a0c7a93788

b72aeeed5ac9df13257c56fff5e71855709cb73c

refs/heads/master

2021-01-20T03:16:47.980594

2017-05-21T20:13:55

83,829,318

0

null

UTF-8

Python

false

2,299

py

# base Layer class that others will inherit from class Layer: def __init__(self, layer_name): self.layer_name = layer_name # contains all the parameters that a convolution layer will have class ConvLayer(Layer): def __init__(self, layer_name, kernel_size, stride, act_function, num_output_filters, weight_init, weight_val, bias_init, bias_val, padding, normalize, dropout , keep_rate): Layer.__init__(self, layer_name) self.layer_type = 'Convolution' self.kernel_size = int(kernel_size) self.stride = int(stride) self.act_function = act_function self.num_output_filters = int(num_output_filters) self.weight_init = weight_init self.weight_val = float(weight_val) self.bias_init = bias_init self.bias_val = float(bias_val) self.padding = padding self.normalize = normalize self.dropout = dropout self.keep_rate = float(keep_rate) # contains all the parameters that a max pooling layer will have class MaxPoolingLayer(Layer): def __init__(self, layer_name, kernel_size, stride, padding, normalize, dropout, keep_rate): Layer.__init__(self, layer_name) self.layer_type = 'Max Pool' self.kernel_size = int(kernel_size) self.stride = int(stride) self.padding = padding self.normalize = normalize self.dropout = dropout self.keep_rate = float(keep_rate) # contains all the parameters that a fully connected layer will have class FullyConnectedLayer(Layer): def __init__(self, layer_name, act_function, num_output_nodes, weight_init, weight_val, bias_init, bias_val, dropout, keep_rate): Layer.__init__(self, layer_name) self.layer_type = 'Fully Connected' self.act_function = act_function self.num_output_nodes = int(num_output_nodes) self.weight_init = weight_init self.weight_val = float(weight_val) self.bias_init = bias_init self.bias_val = float(bias_val) self.dropout = dropout self.keep_rate = float(keep_rate) # contains all the parameters that an output layer will have class OutputLayer(Layer): def __init__(self, layer_name, act_function, weight_init, weight_val, bias_init, bias_val): Layer.__init__(self, layer_name) self.layer_type = 'Output' self.act_function = act_function self.weight_init = weight_init self.weight_val = float(weight_val) self.bias_init = bias_init self.bias_val = float(bias_val)

[ "j_gooch808@hotmail.com" ]

j_gooch808@hotmail.com

f1b834746b4997f601868f58ed815391ad9e6bf7

730b85b3c23337fddca9f4a80d82f8ed2f2eb2a4

/BotBlocker.py

6f1b566e739ae14e718fb48d898640ff6245218d

[ "MIT" ]

permissive

sigmaister/Anonymous-Telegram-Bot

29db924b6a3b33fdae3aba045b68e3c0fb60992b

dee234dd9f931b438a9939310e6d54c0fea4999f

refs/heads/master

2023-05-25T01:08:30.300715

2020-04-12T10:55:33

2020-04-12T11:30:03

269,410,655

0

MIT

2023-05-22T23:29:49

2020-06-04T16:32:07

Python

UTF-8

Python

false

1,842

py

""" This software has been developed by github user fndh (http://github.com/fndh) You are free to use, modify and redistribute this software as you please, as long as you follow the conditions listed in the LICENSE file of the github repository indicated. I want to thank you for reading this small paragraph, and please consider sending me a message if you are using this software! It will surely make my day. """ class Blocker: def __init__(self, sql_wrapper): self.sql = sql_wrapper self.sql.execute_and_commit( "CREATE TABLE IF NOT EXISTS blocked_user_ids (user_id);") def block_user(self, user_id): """ Block a user. Updated the blocked table by adding the user ID if it is not already there.""" if not self.is_user_blocked(user_id): self.sql.execute_and_commit( "INSERT INTO blocked_user_ids (user_id) VALUES (?);", (user_id,)) def unblock_user(self, user_id): """ Unblock a user. Remove the blocked user ID from the block table if the ID exists.""" self.sql.execute_and_commit( "DELETE FROM blocked_user_ids WHERE user_id=?;", (user_id,)) def get_blocked_users(self): """Retrieve a list of the currently blocked user IDs.""" rows = self.sql.select_and_fetch( "SELECT user_id FROM blocked_user_ids;") user_ids = [str(user_id[0]) for user_id in rows] return user_ids def is_user_blocked(self, user_id): """Verify if a user ID is stored in the block table.""" matched_ids = self.sql.select_and_fetch( "SELECT COUNT(*) FROM blocked_user_ids WHERE user_id=?", (user_id,)) # Return format from query is [(count,)] return matched_ids[0][0]

[ "xavi_cat36@hotmail.com" ]

xavi_cat36@hotmail.com

7535a94b63e52647dad6aafa93a3c78cf10f5ec2

4833d5ebc9c84acd95059eb83524923dd9aebc83

/asyncio_helpers.py

d1cf4ebc364da783fd56b5ca077a0af4b7695b57

[]

no_license

bdutro/chromium-proxy

24738f5f7b088c8bae55ba398c71ac82b928b09f

334fb3bd006a3f26b553d354d2830ba3b0328b0b

refs/heads/main

2023-02-20T03:07:22.911243

2021-01-08T18:45:50

327,177,721

0

null

UTF-8

Python

false

223

py

import asyncio import sys if sys.version_info < (3, 7): def asyncio_run(p): loop = asyncio.get_event_loop() return loop.run_until_complete(p) else: def asyncio_run(p): return asyncio.run(p)

[ "brett.dutro@gmail.com" ]

brett.dutro@gmail.com

f8bc14a1c8b118e1a3d390327c9c1d7f9a1cbbd5

7a68632e1788079f40894501e8394d89ebf784df

/mysite/settings.py

d540fa83124150c965b10568958646da1b003d75

[]

no_license

Audywb/pythonanywhere

4f790dad374758f5419b59f4c59d9b22b4099881

4ec7494ad0e3fe478b9e6e6e56ed3ef8b1f29201

refs/heads/master

2023-01-02T14:56:31.593485

2020-10-25T13:38:30

285,757,171

0

null

UTF-8

Python

false

3,637

py

""" Django settings for mysite project. Generated by 'django-admin startproject' using Django 2.1. For more information on this file, see https://docs.djangoproject.com/en/2.1/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.1/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.1/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'l#d)=k3^2f9^39&__hb26y@cf+p95jv#g=p67-5yf9a1gi-$1+' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [u'audyyy.pythonanywhere.com',u'localhost',u'127.0.0.1'] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'myweb', ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'mysite.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'mysite.wsgi.application' # Database # https://docs.djangoproject.com/en/2.1/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/2.1/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.1/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.1/howto/static-files/ STATICFILES_DIRS = [ os.path.join(BASE_DIR, "static"), '/var/www/static/', ] STATIC_URL = '/static/' # default static files settings for PythonAnywhere. # see https://help.pythonanywhere.com/pages/DjangoStaticFiles for more info MEDIA_ROOT = u'/home/wichit2s/mysite/media' MEDIA_URL = '/media/' STATIC_ROOT = u'/home/wichit2s/mysite/static' STATIC_URL = '/static/'

[ "thesombats@gmail.com" ]

thesombats@gmail.com

49831033a0db7eb9b44e22f82a18daf733b0ede5

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p03698/s076680456.py

f88b228e0ad2e567dcb9e176f989690214f846c7

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

null

UTF-8

Python

false

100

py

S=input() for c in S: if S.count(c)>1: print("no") break else: print("yes")

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

f0b7898e2cc53710b09420d379c41c3e2ac4a97a

cbf70750d6c265e4043fd9d1d3bd835662cd680f

/customer/apps.py

845451d50116021235e04c440ee3b6c448bca321

[ "Apache-2.0" ]

permissive

xxcfun/DJANGO_CRM

c54e249a9a3da9edaeb5d9b49e852d351c7e359a

1f8d2d7a025f9dc54b5bf498e7a577469f74c612

refs/heads/master

2023-01-14T05:21:54.995601

2020-11-27T03:23:40

null

0

null

UTF-8

Python

false

131

py

from django.apps import AppConfig class CustomerConfig(AppConfig): name = 'customer' verbose_name = '客户管理'

[ "55070348+hhdMrLion@users.noreply.github.com" ]

55070348+hhdMrLion@users.noreply.github.com

3b42efb7734e3bf5050c3c3470912a7e738e57a2

456e964284c5e25bff5dd7df7361dd6e20b3ea96

/house_prices_competition.py

d3ec623731ca86a9398cbe1a73111ac24984088c

[]

no_license

huangshizhi/kaggle

069d310909f1e45bd420791ab00405fe2e49a621

d754fd0c152461bf96e8553a8e1fd58b65b82cd6

refs/heads/master

2021-01-16T17:16:36.212132

2017-08-11T07:39:17

100,005,336

0

null

UTF-8

Python

false

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# -*- coding: utf-8 -*- """ Created on Wed Aug 9 09:54:45 2017 @author: huangshizhi https://www.dataquest.io/blog/kaggle-getting-started/ """ import pandas as pd import numpy as np #1.加载数据 train = pd.read_csv(r'D:\kaggle\house_prices\data\train.csv') test = pd.read_csv(r'D:\kaggle\house_prices\data\test.csv') import matplotlib.pyplot as plt plt.style.use(style='ggplot') plt.rcParams['figure.figsize'] = (10, 6) #2.探究数据，查看数据的统计特征，skew为分布的不对称度 train.SalePrice.describe() print ("Skew is:", train.SalePrice.skew()) plt.hist(train.SalePrice, color='blue') plt.show() target = np.log(train.SalePrice) print ("Skew is:", target.skew()) plt.hist(target, color='blue') plt.show() #抽取数值型变量特征，Working with Numeric Features numeric_features = train.select_dtypes(include=[np.number]) numeric_features.dtypes #计算协方差矩阵 corr = numeric_features.corr() print (corr['SalePrice'].sort_values(ascending=False)[:5], '\n') print (corr['SalePrice'].sort_values(ascending=False)[-5:]) salePrice_top5 = corr['SalePrice'].sort_values(ascending=False)[:5] salePrice_bottom5 = corr['SalePrice'].sort_values(ascending=False)[-5:] #对房子的整体材料和成品率进行评估 train.OverallQual.unique() quality_pivot = train.pivot_table(index='OverallQual', values='SalePrice', aggfunc=np.median) quality_pivot.plot(kind='bar', color='blue') plt.xlabel('Overall Quality') plt.ylabel('Median Sale Price') plt.xticks(rotation=0) plt.show() #居住面积 plt.scatter(x=train['GrLivArea'], y=target) plt.ylabel('Sale Price') plt.xlabel('Above grade (ground) living area square feet') plt.show() #车库大小 plt.scatter(x=train['GarageArea'], y=target) plt.ylabel('Sale Price') plt.xlabel('Garage Area') plt.show() #去掉异常值之后 train = train[train['GarageArea'] < 1200] plt.scatter(x=train['GarageArea'], y=np.log(train.SalePrice)) plt.xlim(-200,1600) # This forces the same scale as before plt.ylabel('Sale Price') plt.xlabel('Garage Area') plt.show() #Handling Null Values nulls = pd.DataFrame(train.isnull().sum().sort_values(ascending=False)) nulls.columns = ['Null Count'] nulls.index.name = 'Feature' #不包括其他类别的杂项特性 print ("Unique values are:", train.MiscFeature.unique()) #抽取非数值型变量特征 categoricals = train.select_dtypes(exclude=[np.number]) cate_desc = categoricals.describe() print ("Original: \n") print (train.Street.value_counts(), "\n") #One-Hot Encoding train['enc_street'] = pd.get_dummies(train.Street, drop_first=True) test['enc_street'] = pd.get_dummies(train.Street, drop_first=True) print ('Encoded: \n') print (train.enc_street.value_counts()) condition_pivot = train.pivot_table(index='SaleCondition', values='SalePrice', aggfunc=np.median) condition_pivot.plot(kind='bar', color='blue') plt.xlabel('Sale Condition') plt.ylabel('Median Sale Price') plt.xticks(rotation=0) plt.show() def encode(x): return 1 if x == 'Partial' else 0 train['enc_condition'] = train.SaleCondition.apply(encode) test['enc_condition'] = test.SaleCondition.apply(encode) condition_pivot = train.pivot_table(index='enc_condition', values='SalePrice', aggfunc=np.median) condition_pivot.plot(kind='bar', color='blue') plt.xlabel('Encoded Sale Condition') plt.ylabel('Median Sale Price') plt.xticks(rotation=0) plt.show() #填充缺失值 data = train.select_dtypes(include=[np.number]).interpolate().dropna() #测试 sum(data.isnull().sum() != 0) #3.建立回归模型，训练数据 y = np.log(train.SalePrice) X = data.drop(['SalePrice', 'Id'], axis=1) from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split( X, y, random_state=42, test_size=.33) #建模 from sklearn import linear_model lr = linear_model.LinearRegression() model = lr.fit(X_train, y_train) print ("R^2 is: \n", model.score(X_test, y_test)) predictions = model.predict(X_test) from sklearn.metrics import mean_squared_error print ('RMSE is: \n', mean_squared_error(y_test, predictions)) actual_values = y_test plt.scatter(predictions, actual_values, alpha=.75,color='b') #plt.plot(X, y_rbf, color='black', lw=lw, label='RBF model') #alpha helps to show overlapping data plt.xlabel('Predicted Price') plt.ylabel('Actual Price') plt.title('Linear Regression Model') plt.show() for i in range (-2, 3): alpha = 10**i rm = linear_model.Ridge(alpha=alpha) ridge_model = rm.fit(X_train, y_train) preds_ridge = ridge_model.predict(X_test) plt.scatter(preds_ridge, actual_values, alpha=.75, color='b') plt.xlabel('Predicted Price') plt.ylabel('Actual Price') plt.title('Ridge Regularization with alpha = {}'.format(alpha)) overlay = 'R^2 is: {}\nRMSE is: {}'.format( ridge_model.score(X_test, y_test), mean_squared_error(y_test, preds_ridge)) plt.annotate(s=overlay,xy=(12.1,10.6),size='x-large') plt.show() #4.提交结果 submission = pd.DataFrame() submission['Id'] = test.Id feats = test.select_dtypes( include=[np.number]).drop(['Id'], axis=1).interpolate() predictions = model.predict(feats) final_predictions = np.exp(predictions) submission['SalePrice'] = final_predictions submission.head() submission.to_csv('D:\kaggle\house_prices\submission1.csv', index=False)

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# -*- coding: utf-8 -*- """ Created on Thu Feb 22 17:53:58 2018 @author: cq615 """ import numpy as np, cv2 def np_categorical_dice(pred, truth, k): # Dice overlap metric for label value k A = (pred == k).astype(np.float32) B = (truth == k).astype(np.float32) return 2 * np.sum(A * B) / (np.sum(A) + np.sum(B)) def distance_metric(seg_A, seg_B, dx, k): # Measure the distance errors between the contours of two segmentations # The manual contours are drawn on 2D slices. # We calculate contour to contour distance for each slice. table_md = [] table_hd = [] K, X, Y, Z = seg_A.shape for z in range(Z): # Binary mask at this slice slice_A = seg_A[k, :, :, z].astype(np.uint8) slice_B = seg_B[k, :, :, z].astype(np.uint8) # The distance is defined only when both contours exist on this slice if np.sum(slice_A) > 0 and np.sum(slice_B) > 0: # Find contours and retrieve all the points contours, _ = cv2.findContours(cv2.inRange(slice_A, 1, 1), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) pts_A = contours[0] for i in range(1, len(contours)): pts_A = np.vstack((pts_A, contours[i])) contours, _ = cv2.findContours(cv2.inRange(slice_B, 1, 1), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) pts_B = contours[0] for i in range(1, len(contours)): pts_B = np.vstack((pts_B, contours[i])) # Distance matrix between point sets M = np.zeros((len(pts_A), len(pts_B))) for i in range(len(pts_A)): for j in range(len(pts_B)): M[i, j] = np.linalg.norm(pts_A[i, 0] - pts_B[j, 0]) # Mean distance and hausdorff distance md = 0.5 * (np.mean(np.min(M, axis=0)) + np.mean(np.min(M, axis=1))) * dx hd = np.max([np.max(np.min(M, axis=0)), np.max(np.min(M, axis=1))]) * dx table_md += [md] table_hd += [hd] # Return the mean distance and Hausdorff distance across 2D slices mean_md = np.mean(table_md) if table_md else None mean_hd = np.mean(table_hd) if table_hd else None return mean_md, mean_hd

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/Repository/Labelling/Automatically Labelled News/generate_auto_label.py

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from collections import defaultdict from segmentation import SegmentCreator from segmentation import DataPoint import os, datetime, calendar from xml.etree import ElementTree from scipy.stats import pearsonr import pandas import matplotlib.pyplot as plot import matplotlib.ticker as ticker import numpy as np def _get_y_from_eqn(start_index_point:DataPoint, end_index_point:DataPoint, x_value): y = (((end_index_point.get_y() - start_index_point.get_y()) * (x_value - start_index_point.get_x())) / ( end_index_point.get_x() - start_index_point.get_x())) + start_index_point.get_y() return y def get_trend(start_point, end_point): y_difference = end_point.get_y() - start_point.get_y() if y_difference > 0: return "up" elif y_difference < 0: return "down" else: return "neutral" def get_news(): rel_path = "./" company_news_data = dict() for filename in os.listdir(rel_path): if ".xml" in filename and 'unsure' not in filename: company_news_data[filename.replace(".xml", '')] = ElementTree.parse(rel_path + filename).getroot() return company_news_data def get_data(path, draw=False): creator = SegmentCreator(draw=draw) return creator.create_segments(path, 2) def map_segments_to_company(): rel_path = "../../Stock Data/" company_data = dict() for filename in os.listdir(rel_path): if '.csv' in filename: company = filename.replace(".csv", '') company_data[company] = get_data(rel_path + filename) return company_data def get_segment_for_news_release(date, company_trends): for i in range(len(company_trends) - 1): start = company_trends[i] end = company_trends[i + 1] if datetime.datetime.strptime(start.get_date(), "%d/%m/%Y") <= datetime.datetime.strptime(date, "%d/%m/%Y") \ <= datetime.datetime.strptime(end.get_date(), "%d/%m/%Y"): return start, end else: return 0, 0 def auto_generate(news, company_trends, company_name, dates): progress_sentiment_from_number = dict(up='u', down='d', neutral='n') progress_sentiment_to_num = dict(up=1, down=-1, neutral=0) progress_sentiment_trend = defaultdict(int) for news_article in news: date_of_news_release = news_article.get('datetime') date_of_news_release = date_of_news_release.replace(' ET', '') date_of_news_release = datetime.datetime.strptime(date_of_news_release, '%b %d, %Y %I:%M %p').strftime( '%d/%m/%Y') if date_of_news_release in dates: start, end = get_segment_for_news_release(date_of_news_release, company_trends) trend = get_trend(start, end) news_article.attrib['progress_sentiment'] = progress_sentiment_from_number[trend] try: news_article.attrib.pop('feeling_sentiment') except: pass progress_sentiment_trend[date_of_news_release] += progress_sentiment_to_num[trend] # write to file ElementTree.ElementTree(news).write("{}.xml".format(company_name), xml_declaration=True) for day in dates: if not progress_sentiment_trend[str(day)] and not company_name == "ibm": progress_sentiment_trend[str(day)] = 1 elif not progress_sentiment_trend[str(day)] and company_name == "ibm": progress_sentiment_trend[str(day)] = -1 sorted_progress = sorted(progress_sentiment_trend) dateless_progress_trend = [] for day in sorted_progress: dateless_progress_trend.append(progress_sentiment_trend[day]) return dateless_progress_trend def get_projected_prices(segmented_price:list): prices = [] for i in range(len(segmented_price) - 1): start = segmented_price[i] end = segmented_price[i + 1] for x_value in range(start.get_x(), end.get_x()): prices.append(DataPoint(x_value, _get_y_from_eqn(start, end, x_value))) prices.append(segmented_price[-1]) prices.sort(key=lambda x: (x.get_x(), x.get_y())) return prices def aggregate_sentiment(trend): aggregate = [] for i in range(len(trend)): aggregate.append(sum(trend[:i + 1])) return aggregate if __name__ == '__main__': news = get_news() stock_price = map_segments_to_company() for company in stock_price.keys(): print("*******************{0}****************".format(company)) projected_prices = get_projected_prices(stock_price[company]) file_csv = pandas.read_csv("../../Stock Data/{0}.csv".format(company)) data = file_csv[file_csv.columns[2]].tolist() progress_trend = auto_generate(news[company], stock_price[company], company_name=company, dates=file_csv[file_csv.columns[0]].tolist()) correlation, pvalue = pearsonr([price.get_y() for price in projected_prices], aggregate_sentiment(progress_trend)) print("Projected correlation coefficient (progress)", correlation) correlation, pvalue = pearsonr(data, aggregate_sentiment(progress_trend)) print("Actual correlation coefficient (progress)", correlation) if company in []: dates = file_csv[file_csv.columns[0]].tolist() # next we'll write a custom formatter N = len(dates) ind = np.arange(N) # the evenly spaced plot indices def format_date(x, pos=None): thisind = np.clip(int(x + 0.5), 0, N - 1) return datetime.datetime.strptime(dates[thisind], '%d/%m/%Y').strftime( '%Y-%m-%d') fig, ax = plot.subplots() #ax.plot(ind, data, 'o-') ax.xaxis.set_major_formatter(ticker.FuncFormatter(format_date)) fig.autofmt_xdate() plot.plot(ind, [price.get_y() for price in projected_prices], linewidth=4) #plot.plot(ind, aggregate_sentiment(progress_trend)) plot.title(company) plot.show()

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# This is a sample Python script. # Press Shift+F10 to execute it or replace it with your code. # Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings. def print_hi(name): # Use a breakpoint in the code line below to debug your script. print(f'Hi, {name}') # Press Ctrl+F8 to toggle the breakpoint. print("{}, nice to meet you!".format(name)) # Press the green button in the gutter to run the script. if __name__ == '__main__': print_hi('PyCharm') # See PyCharm help at https://www.jetbrains.com/help/pycharm/

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for x in range(1,51): print(2*x)

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neurodata-cobalt/cobalt

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from ndreg import * import matplotlib #import ndio.remote.neurodata as neurodata from intern.remote.boss import BossRemote from intern.resource.boss.resource import * from NeuroDataResource import NeuroDataResource import pickle import numpy as np from requests import HTTPError import time import configparser startTime = time.time() matplotlib.rcParams['figure.figsize'] = (10.0, 8.0) # Assume a valid configuration file exists at .keys/intern.cfg. cfg_file = '.keys/intern.cfg' if cfg_file.startswith('~'): cfg_file = os.path.expanduser('~') + cfg_file[1:] config = configparser.ConfigParser() config.read_file(file(cfg_file)) TOKEN = config['Default']['token'] rmt = BossRemote(cfg_file_or_dict=cfg_file) REFERENCE_COLLECTION = 'ara_2016' REFERENCE_EXPERIMENT = 'sagittal_50um' REFERENCE_COORDINATE_FRAME = 'ara_2016' REFERENCE_CHANNEL = 'average_50um' # Set/Modify these parameters REFERENCE_RESOLUTION = 0 REFERENCE_ISOTROPIC = True # copied code from ndreg because for some reason it wasn't working def setup_experiment_boss(remote, collection, experiment): exp_setup = ExperimentResource(experiment, collection) try: exp_actual = remote.get_project(exp_setup) coord_setup = CoordinateFrameResource(exp_actual.coord_frame) coord_actual= remote.get_project(coord_setup) return (exp_setup, coord_actual) except HTTPError as e: print(e.message) def setup_channel_boss(remote, collection, experiment, channel, channel_type='image', datatype='uint16'): (exp_setup, coord_actual) = setup_experiment_boss(remote, collection, experiment) chan_setup = ChannelResource(channel, collection, experiment, channel_type, datatype=datatype) try: chan_actual = remote.get_project(chan_setup) return (exp_setup, coord_actual, chan_actual) except HTTPError as e: print(e.message) def imgDownload_boss(remote, channel_resource, coordinate_frame_resource, resolution=0, size=[], start=[], isotropic=False): """ Download image with given token from given server at given resolution. If channel isn't specified the first channel is downloaded. """ # TODO: Fix size and start parameters voxel_unit = coordinate_frame_resource.voxel_unit voxel_units = ('nanometers', 'micrometers', 'millimeters', 'centimeters') factor_divide = (1e-6, 1e-3, 1, 10) fact_div = factor_divide[voxel_units.index(voxel_unit)] spacingBoss = [coordinate_frame_resource.x_voxel_size, coordinate_frame_resource.y_voxel_size, coordinate_frame_resource.z_voxel_size] spacing = [x * fact_div for x in spacingBoss] # Convert spacing to mm if isotropic: spacing = [x * 2**resolution for x in spacing] else: spacing[0] = spacing[0] * 2**resolution spacing[1] = spacing[1] * 2**resolution # z spacing unchanged since not isotropic if size == []: size = get_image_size_boss(coordinate_frame_resource, resolution, isotropic) if start == []: start = get_offset_boss(coordinate_frame_resource, resolution, isotropic) #size[2] = 200 #dataType = metadata['channels'][channel]['datatype'] dataType = channel_resource.datatype # Download all image data from specified channel array = remote.get_cutout(channel_resource, resolution, [start[0], size[0]], [start[1], size[1]], [start[2], size[2]]) # Cast downloaded image to server's data type # img = sitk.Cast(sitk.GetImageFromArray(array),ndToSitkDataTypes[dataType]) # convert numpy array to sitk image img = sitk.Cast(sitk.GetImageFromArray(array),sitk.sitkUInt16) # convert numpy array to sitk image # Reverse axes order #img = sitk.PermuteAxesImageFilter().Execute(img,range(dimension-1,-1,-1)) img.SetDirection(identityDirection) img.SetSpacing(spacing) # Convert to 2D if only one slice img = imgCollaspeDimension(img) return img (ref_exp_resource, ref_coord_resource, ref_channel_resource) = setup_channel_boss(rmt, REFERENCE_COLLECTION, REFERENCE_EXPERIMENT, REFERENCE_CHANNEL) refImg = imgDownload_boss(rmt, ref_channel_resource, ref_coord_resource, resolution=REFERENCE_RESOLUTION, isotropic=REFERENCE_ISOTROPIC) refThreshold = imgPercentile(refImg, 0.99) REFERENCE_ANNOTATION_COLLECTION = 'ara_2016' REFERENCE_ANNOTATION_EXPERIMENT = 'sagittal_50um' REFERENCE_ANNOTATION_COORDINATE_FRAME = 'ara_2016' REFERENCE_ANNOTATION_CHANNEL = 'annotation_50um' REFERENCE_ANNOTATION_RESOLUTION = REFERENCE_RESOLUTION REFERENCE_ANNOTATION_ISOTROPIC = True (refAnnotation_exp_resource, refAnnotation_coord_resource, refAnnotation_channel_resource) = setup_channel_boss(rmt, REFERENCE_ANNOTATION_COLLECTION, REFERENCE_ANNOTATION_EXPERIMENT, REFERENCE_ANNOTATION_CHANNEL) refAnnotationImg = imgDownload_boss(rmt, refAnnotation_channel_resource, refAnnotation_coord_resource, resolution=REFERENCE_ANNOTATION_RESOLUTION, isotropic=REFERENCE_ANNOTATION_ISOTROPIC) randValues = np.random.rand(1000,3) randValues = np.concatenate(([[0,0,0]],randValues)) randCmap = matplotlib.colors.ListedColormap(randValues) # Remove missing parts of the brain remove_regions = [507, 212, 220, 228, 236, 244, 151, 188, 196, 204] refAnnoImg = sitk.GetArrayFromImage(refAnnotationImg) remove_indices = np.isin(refAnnoImg, remove_regions) refAnnoImg[remove_indices] = 0 # adjust annotations refAnnoImg_adj = sitk.GetImageFromArray(refAnnoImg) refAnnoImg_adj.SetSpacing(refAnnotationImg.GetSpacing()) refAnnotationImg = refAnnoImg_adj # adjust atlas with corresponding indices # refImg_adj = sitk.GetArrayFromImage(refImg) # refImg_adj[remove_indices] = 0 # refImg_adj = sitk.GetImageFromArray(refImg_adj) # refImg_adj.SetSpacing(refImg.GetSpacing()) # refImg = refImg_adj # Downloading input image # Modify these parameters for your specific experiment SAMPLE_COLLECTION = 'ailey-dev' SAMPLE_EXPERIMENT = 's3617' SAMPLE_COORDINATE_FRAME = 'aileydev_s3617' SAMPLE_CHANNEL = 'channel1' SAMPLE_RESOLUTION = 4 SAMPLE_ISOTROPIC = False sample_exp_resource, sample_coord_resource, sample_channel_resource = setup_channel_boss(rmt, SAMPLE_COLLECTION, SAMPLE_EXPERIMENT, SAMPLE_CHANNEL) sampleImg = imgDownload_boss(rmt, sample_channel_resource, sample_coord_resource, resolution=SAMPLE_RESOLUTION, isotropic=SAMPLE_ISOTROPIC) sampleThreshold = imgPercentile(sampleImg, .999) #Reorienting input image # modify sampleOrient based on your image orientation sampleOrient = "RPI" refOrient = "ASR" sampleImgReoriented = imgReorient(sampleImg, sampleOrient, refOrient) # Downsample images DOWNSAMPLE_SPACING = 0.010 # millimeters spacing = [DOWNSAMPLE_SPACING,DOWNSAMPLE_SPACING,DOWNSAMPLE_SPACING] refImg_ds = sitk.Clamp(imgResample(refImg, spacing), upperBound=refThreshold) sampleImg_ds = sitk.Clamp(imgResample(sampleImgReoriented, spacing), upperBound=sampleThreshold) sampleImgSize_reorient = sampleImgReoriented.GetSize() sampleImgSpacing_reorient= sampleImgReoriented.GetSpacing() # Affine Registration affine = imgAffineComposite(sampleImg_ds, refImg_ds, iterations=200, useMI=True, verbose=True) sampleImg_affine = imgApplyAffine(sampleImgReoriented, affine, size=refImg.GetSize(), spacing=refImg.GetSpacing()) sampleImg_affine_bounded = sitk.Clamp(sampleImg_affine,upperBound=sampleThreshold) refImg_bounded = sitk.Clamp(refImg, upperBound=refThreshold) # LDDMM Registration (field, invField) = imgMetamorphosisComposite(sampleImg_ds, refImg_ds, alphaList=[0.2, 0.1, 0.05], scaleList = 1.0, useMI=True, iterations=100, verbose=True) affineField = affineToField(affine, field.GetSize(), field.GetSpacing()) fieldComposite = fieldApplyField(field, affineField) invAffineField = affineToField(affineInverse(affine), invField.GetSize(), invField.GetSpacing()) invFieldComposite = fieldApplyField(invAffineField, invField) sampleImg_lddmm = imgApplyField(sampleImgReoriented, fieldComposite, size=refImg.GetSize(), spacing=refImg.GetSpacing())

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[]

no_license

LauraGwilliams/arab_pred

9d1dfb1285c769888905f09d30d0a14b5468fad0

f006a42a9979e7ca6c19634c5b90e51b8f8ba3f0

refs/heads/master

2016-09-08T05:04:18.583702

2015-11-02T16:30:41

18,057,133

5

0

null

UTF-8

Python

false

3,548

py

import sys import math from collections import Counter from collections import defaultdict #NOTE -- 'CV' -- corresponds to the element of interest, and # -- 'C' -- corresponds to the element of interest -1 #sets up the script arguments# phoneme_of_interest = sys.argv[1] #create empty dict that we'll fill after# MyDict = defaultdict(int) #figures out if it's a linear or mophemic analysis, reads the correct files and sets up the output file and folder# if '_' in phoneme_of_interest: C_in = open(phoneme_of_interest[:-2] + '_counts_final.txt','r').read().split('\n') folder_path = 'log2_surp_dicts/surp-dict-' print 'conducting morphemic analysis..' else: C_in = open(phoneme_of_interest[:-1] + '_counts_final.txt','r').read().split('\n') print 'conducting linear analysis..' folder_path = 'log2_surp_dicts/surp-dict-' #open and read the CV counts, then if the first element of CV is in C, print the frequency of both C and CV# with open(phoneme_of_interest + '_counts_final.txt','r') as CV_in: for CV in CV_in: for C in C_in: length = len(phoneme_of_interest) if '_' in phoneme_of_interest: if len(phoneme_of_interest) >=4: cv = ''.join(CV[0:int(length)-3]) if cv in C and ',' not in CV[0]: CV = CV.split(',') C = C.split(',') print CV print "CV" print float(CV[1]) print C print "C" print float(C[1]) print "cond_prob" cond_prob = float(CV[1])/float(C[1]) surp = math.log(float(cond_prob),2) print cond_prob MyDict[CV[0]] = surp print "---" else: cv = ''.join(CV[0:int(length)-2]) if cv in C and ',' not in CV[0]: CV = CV.split(',') C = C.split(',') print CV print "CV" print float(CV[1]) print C print "C" print float(C[1]) print "cond_prob" cond_prob = float(CV[1])/float(C[1]) surp = math.log(float(cond_prob),2) print cond_prob MyDict[CV[0]] = surp print "---" else: cv = ''.join(CV[0:int(length)-1]) #cv = ''.join(CV[0]) #cv = cv[:-1] #cv = ''.join(CV[0:2]) if cv in C and ',' not in CV[0]: #now, get the conditional probability of the second vowel, from that compute surprisal by making it log, then put it in the dict #(the key is the CV, and the number is the surprisal # #first, split the dict into its first and second elements i.e., 'ka' '34' CV = CV.split(',') C = C.split(',') #next, get the conditional probability from the second elements of the list (the number) and work out the surprisal print CV print "CV" print float(CV[1]) print C print "C" print float(C[1]) print "cond_prob" cond_prob = float(CV[1])/float(C[1]) surp = math.log(float(cond_prob),2) print cond_prob MyDict[CV[0]] = surp print "---" #now we just save the dict to file# file = open(folder_path + phoneme_of_interest + '.txt', 'w') for key in MyDict: file.write(key + ',' + str(MyDict[key]) + '\n') file.close() file = open(folder_path + phoneme_of_interest + '.txt', 'w') for key in MyDict: file.write(key + ',' + str(MyDict[key]) + '\n') file.close() #finally print out all words with a surprisal greater than 5: highest_surp = dict((k, v) for k, v in MyDict.items() if v <= -5) print "items with suprisal greater than 5:" print highest_surp #and less than 1: highest_surp = dict((k, v) for k, v in MyDict.items() if v >= -2) print "items with suprisal less than 2:" print highest_surp

[ "root@Lauras-MacBook-Pro.local" ]

root@Lauras-MacBook-Pro.local

ba33ce6940599e88acb5a239c6d0893a19068b6e

1b652b030a2742d8579474e155dcfdb65b34ac28

/print/name3.py

f3aa9cf3fac9d2fcf3ccdc2070123a4ca8d011b7

[]

no_license

RobinHou0516/Homework

065dc076a0d5b508433bf97c73a0f1f603447e34

dcb687da489f7c3a87476c07e5902f124edc5856

refs/heads/master

2020-04-09T23:57:08.793511

2018-12-06T12:28:51

160,671,520

3

0

null

UTF-8

Python

false

178

py

name='Robin Kawensanna Smartest Unrivalled' age='14' grade='9th' grade.title school='JXFLS' print('My name is '+name+'. I am a '+age+' year old '+grade+' grader at '+school+'.')

[ "Robinhou0516@gamil.com" ]

Robinhou0516@gamil.com

417047a76d6ad25de43fc2acde8e4c37efc3ab2e

62187abac35eec54f56d956ced4aae18be5c667d

/pilta.py

e9eff95395e2224f94d442902c52ef9d71ff2a61

[]

no_license

Gary345/Ivan_Arratia_1559

5aea66e102bcc49549f680413d5da00275079c72

fafcaa3c3c8e11f4264672dccee13a477a138bc0

refs/heads/main

2023-01-06T14:34:30.906982

2020-11-11T06:31:28

300,461,243

0

null

UTF-8

Python

false

228

py

pila =[3,4,5] # pila de inicio con un arreglo print (pila) #impresion de la pila #345 pila.append(7) pila.append(8) print (pila) #34578 print("saco este elemento",pila.pop()) #8 print("Se quedo asi la pila: ", pila) #3457

[ "ivanarratia314@aragon.unam.mx" ]

ivanarratia314@aragon.unam.mx

5da3583612010525fc95b1ad9c404287e473130d

00a3db4204f764b2d4e49867b198c0203b3e7732

/House_Price_Prediction.py

a7b87157d709fa31b37651b1176256246e5c8ce2

[]

no_license

Madhavraob/tensorflow

555397b7146753234299c26654156e2e99c7f47e

6b37014ceeb7e1bd025f2fa6c162b4dd9597e859

refs/heads/master

2020-03-20T05:55:16.610336

2018-06-24T04:15:36

137,231,285

0

null

UTF-8

Python

false

4,822

py

# # House_Price_Prediction.py # # This is a very simple prediction of house prices based on house size, implemented # in TensorFlow. This code is part of Pluralsight's course "TensorFlow: Getting Started" # import tensorflow as tf import numpy as np import math import matplotlib.pyplot as plt import matplotlib.animation as animation # import animation support # generation some house sizes between 1000 and 3500 (typical sq ft of house) num_house = 160 np.random.seed(42) house_size = np.random.randint(low=1000, high=3500, size=num_house ) # Generate house prices from house size with a random noise added. np.random.seed(42) house_price = house_size * 100.0 + np.random.randint(low=20000, high=70000, size=num_house) # Plot generated house and size # plt.plot(house_size, house_price, "bx") # bx = blue x # plt.ylabel("Price") # plt.xlabel("Size") # plt.show() # you need to normalize values to prevent under/overflows. def normalize(array): return (array - array.mean()) / array.std() # define number of training samples, 0.7 = 70%. We can take the first 70% since the values are randomized num_train_samples = math.floor(num_house * 0.7) # define training data train_house_size = np.asarray(house_size[:num_train_samples]) train_price = np.asanyarray(house_price[:num_train_samples:]) train_house_size_norm = normalize(train_house_size) train_price_norm = normalize(train_price) # define test data test_house_size = np.array(house_size[num_train_samples:]) test_house_price = np.array(house_price[num_train_samples:]) test_house_size_norm = normalize(test_house_size) test_house_price_norm = normalize(test_house_price) # Set up the TensorFlow placeholders that get updated as we descend down the gradient tf_house_size = tf.placeholder("float", name="house_size") tf_price = tf.placeholder("float", name="price") # Define the variables holding the size_factor and price we set during training. # We initialize them to some random values based on the normal distribution. tf_size_factor = tf.Variable(np.random.randn(), name="size_factor") tf_price_offset = tf.Variable(np.random.randn(), name="price_offset") # 2. Define the operations for the predicting values - predicted price = (size_factor * house_size ) + price_offset # Notice, the use of the tensorflow add and multiply functions. These add the operations to the computation graph, # AND the tensorflow methods understand how to deal with Tensors. Therefore do not try to use numpy or other library # methods. tf_price_pred = tf.add(tf.multiply(tf_size_factor, tf_house_size), tf_price_offset) # 3. Define the Loss Function (how much error) - Mean squared error tf_cost = tf.reduce_sum(tf.pow(tf_price_pred-tf_price, 2))/(2*num_train_samples) # Optimizer learning rate. The size of the steps down the gradient learning_rate = 0.1 # 4. define a Gradient descent optimizer that will minimize the loss defined in the operation "cost". optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(tf_cost) # Initializing the variables init = tf.global_variables_initializer() # Launch the graph in the session with tf.Session() as sess: sess.run(init) # set how often to display training progress and number of training iterations display_every = 2 num_training_iter = 50 # calculate the number of lines to animation fit_num_plots = math.floor(num_training_iter/display_every) # add storage of factor and offset values from each epoch fit_size_factor = np.zeros(fit_num_plots) fit_price_offsets = np.zeros(fit_num_plots) fit_plot_idx = 0 # keep iterating the training data for iteration in range(num_training_iter): # Fit all training data for (x, y) in zip(train_house_size_norm, train_price_norm): sess.run(optimizer, feed_dict={tf_house_size: x, tf_price: y}) # Display current status if (iteration + 1) % display_every == 0: c = sess.run(tf_cost, feed_dict={tf_house_size: train_house_size_norm, tf_price:train_price_norm}) print("iteration #:", '%04d' % (iteration + 1), "cost=", "{:.9f}".format(c), \ "size_factor=", sess.run(tf_size_factor), "price_offset=", sess.run(tf_price_offset)) # Save the fit size_factor and price_offset to allow animation of learning process fit_size_factor[fit_plot_idx] = sess.run(tf_size_factor) fit_price_offsets[fit_plot_idx] = sess.run(tf_price_offset) fit_plot_idx = fit_plot_idx + 1 print("Optimization Finished!") training_cost = sess.run(tf_cost, feed_dict={tf_house_size: train_house_size_norm, tf_price: train_price_norm}) print("Trained cost=", training_cost, "size_factor=", sess.run(tf_size_factor), "price_offset=", sess.run(tf_price_offset), '\n')

[ "madhavrao039@gmail.com" ]

madhavrao039@gmail.com

eb268714e1d62798cbe61cec0f6af724ee53d4f6

a163c2cec4d942212bd5bcd25a8759a7da570b7f

/ChatBot/main.py

f54e258b6b94e4253d6b6b77a9eb96e43cdb92e0

[]

no_license

cainanalves/computational_intelligence

1daa4c3f153563e11b0d8410d6429648b48b57f1

503dfeb9db3dc18725d30587f968ed86ece53d7d

refs/heads/master

2021-08-23T10:47:22.650121

2017-12-04T15:42:48

null

0

null

UTF-8

Python

false

674

py

#!/usr/bin/python3.5 # encoding: utf-8 from chatterbot.trainers import ListTrainer from chatterbot import ChatBot import os #Read_only=True --> Dizer ao bot que eu já o treinei e não precisa treinar novamente. bot = ChatBot("Teste")#read_only=True) bot.set_trainer(ListTrainer) for arq in os.listdir("arqs"): chats = open("arqs/"+arq,"rb").readlines() bot.train(chats) conversa = open("arqs/conversa", "a") while True: resq = input("Você: ") conversa.write(str(resq)+"\n") resp = bot.get_response(resq) conversa.write(str(resp)+"\n") print("Bot: "+ str(resp)) if (("chega de papo" in str(resq)) or ("chega de papo" in str(resp))): break conversa.close()

[ "cainan.teixeira10@hotmail.com" ]

cainan.teixeira10@hotmail.com

3d62fe89850d8886db18d58cd2b87b3b04745a1b

60ffc2a1264a7ac6e743b0c1da380d0daf9c849b

/src/core.py

d274ce41dd9a3d9ff816e8f776bf1ece3b235894

[]

no_license

pedromxavier/760D

d3622fb4487ece13c633a527e68526b1677d9da7

458ebbeb1aa8975628bd2caebdd919933ecf264a

refs/heads/master

2021-02-28T16:40:30.769008

2020-06-05T18:46:01

245,713,698

0

null

UTF-8

Python

false

2,725

py

import telebot as tb import re import html import urllib.request as req def STATUS_PONTE(): try: URL_PONTE = "https://www.ecoponte.com.br/condicoes-da-via" PATTERN = r'<tr class=.*?-row><td>.*?<td>(.*?)<td>\s*(\S*?)\s*' answer = req.urlopen(URL_PONTE) answer_bytes = answer.read() answer_html = answer_bytes.decode('utf8') matches = re.findall(PATTERN, answer_html, re.DOTALL) TEXT = "O tráfego na ponte está *{}* no sentido *{}* e *{}* no sentido *{}*." args = [] for name, status in matches: args.append(html.unescape(status)) args.append(html.unescape(name)) if not args: raise ValueError return TEXT.format(*args) except: return "Não tenho informações sobre a ponte agora, lamento." def NEXT_FRESCAO(): pass def FRESCAO_IMG(): return open(r'static/HORARIO_FRESCAO.jpg', 'rb') def START_TEXT(json): if tb.Tempo.morning: return "Bom dia, Niterói!" elif tb.Tempo.evening: return "Boa tarde, Niterói!" else: return "Boa Noite, Niterói!" def UNKNOWN_TEXT(json): return "Comando desconhecido `{text}`".format(json) bot = tb.Bot.load(debug=True, fname='LV760DBOT') bot.START_TEXT = START_TEXT bot.UNKNOWN_TEXT = UNKNOWN_TEXT with bot: @bot.cmd_handler('ponte') @bot.lock_start def ponte(self, update, context): self.debug[0]('[cmd :: ponte]') json = self.parse(update, context) self.debug[1]('[obj :: json]', json) kw = { 'chat_id' : json['chat_id'], 'text' : STATUS_PONTE(), 'parse_mode' : tb.telegram.ParseMode.MARKDOWN, } self.debug[1]('[obj :: kw]', kw) json['bot'].send_message(**kw) @bot.cmd_handler('frescao') @bot.lock_start def frescao(self, update, context): self.debug[0]('[cmd :: frescao]') json = self.parse(update, context) self.debug[1]('[obj :: json]', json) kw = { 'chat_id' : json['chat_id'], 'photo' : FRESCAO_IMG(), } self.debug[1]('[obj :: kw]', kw) json['bot'].send_photo(**kw) @bot.cmd_handler('lv') @bot.lock_start def lv(self, update, context): self.debug[0]('[cmd :: lv]') json = self.parse(update, context) self.debug[1]('[obj :: json]', json) kw = { 'chat_id' : json['chat_id'], 'text' : 'Não sei fazer isso ainda.' } self.debug[1]('[obj :: kw]', kw) json['bot'].send_message(**kw) if __name__ == '__main__': bot.run()

[ "pedromxavier@poli.ufrj.br" ]

pedromxavier@poli.ufrj.br

0330ab227a01ca6a6a99e83cd4578ca5f78b5586

b662dc0ac66c51a4ac8c707cb5222ede5f28bdea

/run.py

94883b1d621772024640541a86dda9af3048d101

[]

no_license

lukew3/ReCrypto

43bd033b6ea0050536f9f6d3e14d1e403470908a

6d6fe3e6e035d9dd74d9ab101b7c3ab4cfb8faf7

refs/heads/master

2023-02-21T11:32:54.709442

2021-09-08T15:43:03

231,695,238

0

null

2023-02-15T23:02:21

2020-01-04T02:04:08

HTML

UTF-8

Python

false

45

py

from recrypto import app app.run(debug=True)

[ "lukew25073@gmail.com" ]

lukew25073@gmail.com

da49a505c50819ea836f94a3f31c5cbacb368bcf

e6fb5885b04786ead91c5f98d5ce6134509e6482

/CompetitiveProgramming/week2/day4/prob2.py

66cbc1b25c74eef91f388156f2cded07d15ce8a9

[]

no_license

ShruthikaP/CompetitiveProgramming

82ff2cd05a8e96278a7787b8ebcd3dd103829c0a

fb3cda698a1d0a859c66b1f36a2edf85d8ca0804

refs/heads/master

2020-03-21T15:41:54.665575

2018-07-21T09:11:22

138,727,641

0

null

UTF-8

Python

false

291

py

import unittest def get(s): if len(s) <= 1: return set([s]) mid = s[:-1] end = s[-1] mid_perm = get(mid) p = set() for i in mid_perm: for j in range(len(mid) + 1): ans = (i[:j] + end + i[j:]) p.add(ans) return p

[ "noreply@github.com" ]

ShruthikaP.noreply@github.com

5ff698b54c085c2863d04a125320ecbaa0c0c1b0

470c42904eec5d46be4a12219d4dfa29e251d332

/spotcheck.py

76f8cb05049ea427ff66137e6312ef088aca5a0a

[]

no_license

warrendlee1/Python-Programs

c3f21f1875c7f5a27a8add5fe2caa2a5955dd5f8

97c84ba8a1fa8f5c5de77a69a534115838608c2a

refs/heads/master

2021-04-13T19:49:22.991286

2018-04-28T05:16:54

null

0

null

UTF-8

Python

false

122

py

# -*- coding: utf-8 -*- """ Created on Fri Nov 17 11:26:34 2017 @author: warrenl0134 """ listA = [1,4,3,0] listA

[ "warrenlee@Williams-MBP.attlocal.net" ]

warrenlee@Williams-MBP.attlocal.net

4ea07f0c63929fc01a0774b85c0d959f540d5aa4

10259763befc3aab2cb6f172a5f49a0fe6689b8a

/readingdb/test_lineroute.py

359d8377bee14d9b0b372b6df71c7e1243f4a485

[]

no_license

Lewington-pitsos/readingdb

4a8c473ffdef0f40978149f900d74051d1e8da85

a57b9dc1ecc8dd5c2aa1b35691fe0aa1bcaff733

refs/heads/master

2023-08-14T20:55:25.862149

2021-09-19T02:43:32

349,652,836

0

null

UTF-8

Python

false

4,263

py

import unittest from readingdb.lineroute import LinePoint, LineRoute, linear_interp class TestLineRoute(unittest.TestCase): def test_performs_lnear_interpolation_on_real_points(self): start_point = LinePoint.from_point({ "Timestamp": 1568113911576, "Latitude": -37.8714232, "Longitude": 145.2450816 }) end_point = LinePoint.from_point({ "Timestamp": 1618113911576, "Latitude": -37.8744232, "Longitude": 145.7450816 }) pnts = [ start_point, end_point ] r = LineRoute(pnts, interp_alg=linear_interp) interp = r.point_at(1568113911576) self.assertEqual(interp, start_point) r = LineRoute(pnts, interp_alg=linear_interp) interp = r.point_at(1617779685467) self.assertEqual(interp, LinePoint.from_point({ "Timestamp": 1617779685467, "Latitude": -37.874403146433465, "Longitude": 145.74173933891 })) def test_performs_lnear_interpolation_on_dummy_points(self): start_point = LinePoint.from_point({ "Timestamp": 10, "Latitude": 10, "Longitude": 20 }) middle_point = LinePoint.from_point({ "Timestamp": 20, "Latitude": 20, "Longitude": 40 }) end_point = LinePoint.from_point({ "Timestamp": 120, "Latitude": 21, "Longitude": 50 }) pnts = [ start_point, middle_point, end_point ] r = LineRoute(pnts, interp_alg=linear_interp) interp = r.point_at(10) self.assertEqual(interp, start_point) interp = r.point_at(20) self.assertEqual(interp, middle_point) interp = r.point_at(120) self.assertEqual(interp, end_point) interp = r.point_at(19) self.assertEqual(interp, LinePoint.from_point({ "Timestamp": 19, "Latitude": 19, "Longitude": 38 })) interp = r.point_at(11) self.assertEqual(interp, LinePoint.from_point({ "Timestamp": 11, "Latitude": 11, "Longitude": 22 })) interp = r.point_at(119) self.assertEqual(interp, LinePoint.from_point({ "Timestamp": 119, "Latitude": 20.99, "Longitude": 49.9 })) class TestInterpolation(unittest.TestCase): def test_linear_interpolation_returns_bookends(self): start_ts = 1568113911576 end_ts = 1618113911576 start_point = LinePoint.from_point({ "Timestamp": start_ts, "Latitude": -37.8714232, "Longitude": 145.2450816 }) end_point = LinePoint.from_point({ "Timestamp": end_ts, "Latitude": -37.8744232, "Longitude": 145.7450816 }) interp = linear_interp(start_point, end_point, start_ts) self.assertEqual(interp, start_point) interp = linear_interp(start_point, end_point, end_ts) self.assertEqual(interp, end_point) def test_linear_interpolation(self): start_point = LinePoint.from_point({ "Timestamp": 200, "Latitude": -10.0, "Longitude": 150.0 }) end_point = LinePoint.from_point({ "Timestamp": 300, "Latitude": -20.0, "Longitude": 100.0, }) interp = linear_interp(start_point, end_point, 250) self.assertEqual(interp, LinePoint.from_point({ "Timestamp": 250, "Latitude": -15.0, "Longitude": 125.0, })) start_point = LinePoint.from_point({ "Timestamp": 200, "Latitude": 20.0, "Longitude": 10.0 }) end_point = LinePoint.from_point({ "Timestamp": 300, "Latitude": -20.0, "Longitude": 110.0, }) interp = linear_interp(start_point, end_point, 210) self.assertEqual(interp, LinePoint.from_point({ "Timestamp": 210, "Latitude": 16.0, "Longitude": 20.0, }))

[ "lewingtonpitsos@gmail.com" ]

lewingtonpitsos@gmail.com

783fdd25c10199746426d1f7b3e87e009964b1e1

d4a5462b2cd2eff99da6ad5147b5423c819ae731

/1072.py

7cde2b4cbdcb7fcb593e7f072f7089b72b0530d7

[]

no_license

Rafesz/URI_solutions_py

3a61e6b0b571a03857f1c4efb54546edb2a0fb6a

62a9f8227523e409afa9d506df66516ef9b48079

refs/heads/main

2023-08-11T20:55:04.267913

2021-09-21T22:25:50

402,085,340

0

null

UTF-8

Python

false

816

py

# Leia um valor inteiro N. Este valor será a quantidade de valores inteiros X que serão lidos em seguida. # Mostre quantos destes valores X estão dentro do intervalo [10,20] e quantos estão fora do intervalo, mostrando essas informações. # Entrada # A primeira linha da entrada contém um valor inteiro N (N < 10000), que indica o número de casos de teste. # Cada caso de teste a seguir é um valor inteiro X (-107 < X <107). # Saída # Para cada caso, imprima quantos números estão dentro (in) e quantos valores estão fora (out) do intervalo. i = 0 contadorIn = 0 contaodorOut = 0 n = int(input()) while(i < n): valor = int(input()) if(10 <= valor <= 20): contadorIn += 1 else: contaodorOut += 1 i += 1 print("{} in\n{} out".format(contadorIn, contaodorOut))

[ "noreply@github.com" ]

Rafesz.noreply@github.com

af55f4e50ab0299aca371628784bd73425438b22

b5dcd0bad00891a07412123de90097d9459dffbe

/Characters/_data/noemye.py

0bd6ef0250c946bf262a6afe827db7e1ad7c3c0f

[]

no_license

Vgr255/Vgr255.github.io

c90f741f3c03449d884dda1d4672ee841307c304

4fc752f86678b7885ff84f392b23a1df2d39f582

refs/heads/master

2021-01-18T21:58:22.093346

2016-05-15T17:11:27

42,474,140

0

null

UTF-8

Python

false

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# Copyright (c) SenseTime. All Rights Reserved. from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals from pysot.models.sa.sa import sablock SABLOCKS = { 'sablock': sablock, } def get_sa(name, **kwargs): return SABLOCKS[name](**kwargs)

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#!/usr/bin/python import random from time import sleep from matplotlib import pyplot as plt from classes.Point import Point from classes.Vector2d import Vector2d, pi from divideAndRule2 import divide_and_rule, divide_and_rule from utils.binary import binary_test from utils.graph import draw_polygon def reflect(p, vector_coords): # Previous direction v = p.direction # Polygon side q = Vector2d(vector_coords[0], vector_coords[1]) scal = 2 * (Vector2d.scalar_product(v, q) / Vector2d.scalar_product(q, q)) prod = Vector2d.s_mult(q, scal) new_direction = Vector2d.s_minus(prod, v) return new_direction def plot_task(rectangle, points, points_y): MIN_DISTANSE = 0.5 plt.ion() s = 1 while s: plt.clf() draw_polygon(rectangle) clash_flag = divide_and_rule(points, points_y) if clash_flag[1] <= MIN_DISTANSE: clash_flag[0][0].reflect_direction() clash_flag[0][1].reflect_direction() for i in points: flag_binary = binary_test(rectangle, i.get_next_state_circle(MIN_DISTANSE / 2))['flag'] if not flag_binary: coords_binary = binary_test(rectangle, i.get_next_state_circle(MIN_DISTANSE / 2))['points'] new_direction = reflect(i, coords_binary) i.direction = new_direction for i in points: i.move() plt.scatter(i.x, i.y, s=MIN_DISTANSE / 2 * 750, marker='o', c='g') plt.draw() plt.gcf().canvas.flush_events() sleep(0.002) plt.show() plt.ioff() plt.show() if __name__ == '__main__': # Rectangle rectangle = [Point(1, 1), Point(1, 10), Point(15, 10), Point(15, 1)] # Our points points_set = [Point(2, 2), Point(2, 3), Point(4, 2), Point(4, 5), Point(4, 8), Point(6, 2), Point(6,9), Point(8, 5), Point(10,3), Point(11,9), Point(12, 5), Point(12,8)] points_set.sort(key=lambda point: (point.x, point.y)) points_set_y = points_set.copy() points_set_y.sort(key=lambda point: (point.y, point.x)) # min_dist = divide_and_rule(points_set) # print(min_dist) # Set points direction for point in points_set: point.set_direction(Vector2d.get_vector(random.uniform(0, 2 * pi), 0.09)) plot_task(rectangle, points_set, points_set_y)

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