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b5842703ca8bb1831f5d523d7e7e968c1ba5293a | tombch/swell | swell/swell.py | [
"MIT"
] | Python | swell_from_fasta | <not_specific> | def swell_from_fasta(fasta_path):
'''
Calculate fasta statistics given the path to a fasta/multifasta.
'''
if fasta_path == "-":
fastas = readfq.readfq(sys.stdin)
else:
fastas = readfq.readfq(open(fasta_path))
rows = []
for name, seq, qual in fastas:
rows.app... |
Calculate fasta statistics given the path to a fasta/multifasta.
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if fasta_path == "-":
fastas = readfq.readfq(sys.stdin)
else:
fastas = readfq.readfq(open(fasta_path))
rows = []
for name, seq, qual in fastas:
rows.append([fasta_path, name] + calculate_fasta_stats(seq))
if fasta_path != "-":
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b5842703ca8bb1831f5d523d7e7e968c1ba5293a | tombch/swell | swell/swell.py | [
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] | Python | swell_from_fasta_seq | <not_specific> | def swell_from_fasta_seq(seq, fasta_path="", header=""):
'''
Calculate fasta statistics directly from a sequence.
'''
rows = [[fasta_path, header] + calculate_fasta_stats(seq)]
return ["fasta_path", "header", "num_seqs", "num_bases", "pc_acgt", "pc_masked", "pc_invalid", "pc_ambiguous", "longest_gap... |
Calculate fasta statistics directly from a sequence.
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rows = [[fasta_path, header] + calculate_fasta_stats(seq)]
return ["fasta_path", "header", "num_seqs", "num_bases", "pc_acgt", "pc_masked", "pc_invalid", "pc_ambiguous", "longest_gap", "longest_ungap"], rows | [
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93f081e2ae6f8c8a487b20db6ef00a1232381cea | tiny-mouse/prove-it | calc/calculator.py | [
"MIT"
] | Python | add | <not_specific> | def add(numbers):
"""Sums all the numbers in the specified iterable"""
the_sum = 0
for number in numbers:
the_sum += int(number)
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93f081e2ae6f8c8a487b20db6ef00a1232381cea | tiny-mouse/prove-it | calc/calculator.py | [
"MIT"
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93f081e2ae6f8c8a487b20db6ef00a1232381cea | tiny-mouse/prove-it | calc/calculator.py | [
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"""Raises the 0th number to the 1..Nth numbers as powers"""
result = numbers[0]
for number in numbers[1:]:
result *= number
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71b8a28e225dcde9e93ae68c8399184302be65cd | tiny-mouse/prove-it | calc/views.py | [
"MIT"
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"""Takes numbers params and sums them together"""
if not request.args.getlist('numbers'):
return "You need to give numbers to add", 400
numbers = request.args.get('numbers')
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71b8a28e225dcde9e93ae68c8399184302be65cd | tiny-mouse/prove-it | calc/views.py | [
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"""Takes numbers params and subtracts them from the first"""
if not request.args.get('numbers'):
return "You need to give numbers to subtract", 400
numbers = request.args.getlist('numbers')
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71b8a28e225dcde9e93ae68c8399184302be65cd | tiny-mouse/prove-it | calc/views.py | [
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"""Takes numbers params and multiplies them together"""
if not request.args.get('numbers'):
return "You need to give numbers to multiply", 400
numbers = request.args['numbers']
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71b8a28e225dcde9e93ae68c8399184302be65cd | tiny-mouse/prove-it | calc/views.py | [
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"""Takes numbers params and divides them."""
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71b8a28e225dcde9e93ae68c8399184302be65cd | tiny-mouse/prove-it | calc/views.py | [
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71b8a28e225dcde9e93ae68c8399184302be65cd | tiny-mouse/prove-it | calc/views.py | [
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e492972045a63af8bc0242e8f05dbd97d64bc41d | lab-a1/captcha-recognition | src/lib/metrics.py | [
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"""Mean between the predictions for the five characters."""
accuracy_result = 0
for y, t in zip(output, target):
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8f16b8482680785e92b1e9ccf9bc06e257c8b43f | roman-baldaev/test-task-weather | frontend/database.py | [
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Accepts the name of the city (city).
The temperature is extracted directly from the HTML page.
Return a list with two values.
In case of success - value of temperature and URL, otherwise - error and URL.
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Accepts the name of the city (city).
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] | [
"\"\"\"Function for obtaining temperature from Yandex.\n\n Accepts the name of the city (city).\n The temperature is extracted directly from the HTML page.\n Return a list with two values.\n In case of success - value of temperature and URL, otherwise - error and URL.\n\n \"\"\"",
"... | [
{
"param": "city",
"type": null
}
] | {
"returns": [],
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{
"identifier": "city",
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"docstring_tokens": [],
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"is_optional": null
}
],
"outlier_params": [],
"others": []
} |
8f16b8482680785e92b1e9ccf9bc06e257c8b43f | roman-baldaev/test-task-weather | frontend/database.py | [
"MIT"
] | Python | open_weather_map | <not_specific> | def open_weather_map(city):
"""Function for obtaining temperature from Yandex.
Accepts the name of the city (city)
The temperature is extracted from the JSON file obtained with OpenWeatherMap API.
Return a list with two values.
In case of success - value of temperature and URL, oth... | Function for obtaining temperature from Yandex.
Accepts the name of the city (city)
The temperature is extracted from the JSON file obtained with OpenWeatherMap API.
Return a list with two values.
In case of success - value of temperature and URL, otherwise - error and URL.
| Function for obtaining temperature from Yandex.
Accepts the name of the city (city)
The temperature is extracted from the JSON file obtained with OpenWeatherMap API.
Return a list with two values.
In case of success - value of temperature and URL, otherwise - error and URL. | [
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"... | def open_weather_map(city):
try:
url = 'http://api.openweathermap.org/data/2.5/weather?q={}&appid=c7365fbce4cdaa0eed49c8adb6828336'.format(city)
req = requests.get(url)
temperature = float(req.json()['main']['temp']) - 273.15
return [round(temperature, 1), url]
except Exception a... | [
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} |
8f16b8482680785e92b1e9ccf9bc06e257c8b43f | roman-baldaev/test-task-weather | frontend/database.py | [
"MIT"
] | Python | auto_update_function | <not_specific> | def auto_update_function(cities):
"""Auto-update weather function
The function takes a list of the cities to update.
If the error connecting to sources - an error with
a status of 500 and JSON with the cause of the error and URL.
If the connection is successful, it enters the
... | Auto-update weather function
The function takes a list of the cities to update.
If the error connecting to sources - an error with
a status of 500 and JSON with the cause of the error and URL.
If the connection is successful, it enters the
data into the database and returns an ... | Auto-update weather function
The function takes a list of the cities to update.
If the error connecting to sources - an error with
a status of 500 and JSON with the cause of the error and URL.
If the connection is successful, it enters the
data into the database and returns an empty response with code 200. | [
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try:
connect = psycopg2.connect(database = 'django_test', user = 'roman',
host = 'localhost', password = 'admin')
cursor = connect.cursor()
cursor.execute(
'SELECT city_name FROM frontend_cit... | [
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{
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],
"outlier_params": [],
"others": []
} |
3f7d19ea1361b53c9bad3edb8a7b61141a83f49a | roman-baldaev/test-task-weather | frontend/last_update.py | [
"MIT"
] | Python | last_update_temperature | <not_specific> | def last_update_temperature(city):
"""A script to retrieve data from the last update.
First check the availability of the city in the database - if not,
then the error 404 and JSON with error and reason.
If the city is in the database - sort by the time of the addition and select the last ent... | A script to retrieve data from the last update.
First check the availability of the city in the database - if not,
then the error 404 and JSON with error and reason.
If the city is in the database - sort by the time of the addition and select the last entry.
Return JSON with the results, c... | A script to retrieve data from the last update.
First check the availability of the city in the database - if not,
then the error 404 and JSON with error and reason.
If the city is in the database - sort by the time of the addition and select the last entry.
Return JSON with the results, code 200.
If the error connec... | [
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try:
utc_timezone = pytz.timezone('UTC')
connect = psycopg2.connect(database='django_test', user='roman',
host='localhost', password='admin')
cursor = connect.cursor()
cursor.execute("SELECT id FROM frontend_city W... | [
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],
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} |
306796f94a06d9a56bad1aded06bdccd3be77267 | possoj/Mobile-URSONet | src/my_mobile_ursonet.py | [
"MIT"
] | Python | copy_state_dict | <not_specific> | def copy_state_dict(state_dict_1, state_dict_2):
"""Manual copy of state dict.
Why ? Because when copying a state dict to another with load_state_dict, the values of weight are copied only
when keys are the same in both state_dict, even if strict=False.
"""
state1_keys = list(state_dict_1.keys())
... | Manual copy of state dict.
Why ? Because when copying a state dict to another with load_state_dict, the values of weight are copied only
when keys are the same in both state_dict, even if strict=False.
| Manual copy of state dict.
Why . Because when copying a state dict to another with load_state_dict, the values of weight are copied only
when keys are the same in both state_dict, even if strict=False. | [
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state1_keys = list(state_dict_1.keys())
state2_keys = list(state_dict_2.keys())
for x in range(len(state1_keys)):
state_dict_2[state2_keys[x]] = state_dict_1[state1_keys[x]]
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6a722055313c732c10b3d4f42d8740e1030f0cea | possoj/Mobile-URSONet | src/utils.py | [
"MIT"
] | Python | build_histogram | <not_specific> | def build_histogram(n_bins_per_dim, min_lim, max_lim):
"""Building the histogram of all possible orientation bins, given the number of bins per dimension and
min/max limits on Z, Y and X axis (rotation). See https://arxiv.org/pdf/1906.09868.pdf
The histogram is built only once to save time during execution
... | Building the histogram of all possible orientation bins, given the number of bins per dimension and
min/max limits on Z, Y and X axis (rotation). See https://arxiv.org/pdf/1906.09868.pdf
The histogram is built only once to save time during execution
| Building the histogram of all possible orientation bins, given the number of bins per dimension and
min/max limits on Z, Y and X axis (rotation). | [
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] | def build_histogram(n_bins_per_dim, min_lim, max_lim):
d = 3
n_bins = n_bins_per_dim ** d
bins_per_dim = torch.linspace(0.0, 1.0, n_bins_per_dim)
bins_all_dims = torch.cartesian_prod(bins_per_dim, bins_per_dim, bins_per_dim)
euler_bins = bins_all_dims * (max_lim - min_lim) + min_lim
quaternions_... | [
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6a722055313c732c10b3d4f42d8740e1030f0cea | possoj/Mobile-URSONet | src/utils.py | [
"MIT"
] | Python | decode_ori_batch | <not_specific> | def decode_ori_batch(ori, b):
"""Decode a batch of orientation (ori) using the pre-computed orientation decode variable (b) based on the histogram
(see pre_compute_ori_decode)
"""
ori = ori.cpu()
batch_size = ori.size(0)
ori_avg = torch.zeros((batch_size, 4), dtype=torch.float32)
h_avg = t... | Decode a batch of orientation (ori) using the pre-computed orientation decode variable (b) based on the histogram
(see pre_compute_ori_decode)
| Decode a batch of orientation (ori) using the pre-computed orientation decode variable (b) based on the histogram | [
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ori = ori.cpu()
batch_size = ori.size(0)
ori_avg = torch.zeros((batch_size, 4), dtype=torch.float32)
h_avg = torch.zeros((batch_size, 4, 4), dtype=torch.float32)
for i in range(batch_size):
ori_avg[i], h_avg[i] = decode_ori(ori[i], b)
return ori_avg, h_avg | [
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... |
b92b611f413dd6eec68bab2a417c805eb92b5a92 | possoj/Mobile-URSONet | src/data.py | [
"MIT"
] | Python | copy_speed_dataset_resize | null | def copy_speed_dataset_resize(old_path, new_path, new_size=(224, 224), split='train'):
"""copy and resize Speed images to a new directory. The new (empty) folders must be created before calling
this function"""
if split not in {'train', 'test', 'real_test'}:
raise ValueError('Invalid split, has to ... | copy and resize Speed images to a new directory. The new (empty) folders must be created before calling
this function | copy and resize Speed images to a new directory. The new (empty) folders must be created before calling
this function | [
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if split not in {'train', 'test', 'real_test'}:
raise ValueError('Invalid split, has to be either \'train\', \'test\' or \'real_test\'')
with open(os.path.join(old_path, split + '.json'), 'r') as f:
target_lis... | [
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8cd96511c23ec58df9bfdfb466a9a888c10dea24 | possoj/Mobile-URSONet | src/pose_net.py | [
"MIT"
] | Python | import_dataset | <not_specific> | def import_dataset(self):
"""Import the dataset. May take some seconds as we pre-compute the histogram to save time later"""
print('Import dataset...')
if self.config.DATASET == 'SPEED':
dataloader = prepare_speed_dataset(self.config)
else:
raise ValueError('Datas... | Import the dataset. May take some seconds as we pre-compute the histogram to save time later | Import the dataset. May take some seconds as we pre-compute the histogram to save time later | [
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print('Import dataset...')
if self.config.DATASET == 'SPEED':
dataloader = prepare_speed_dataset(self.config)
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raise ValueError('Dataset must be \'SPEED\' (URSO dataset not implemented)')
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"outlier_params": [],
"others": []
} |
8cd96511c23ec58df9bfdfb466a9a888c10dea24 | possoj/Mobile-URSONet | src/pose_net.py | [
"MIT"
] | Python | evaluate_submit | null | def evaluate_submit(self, sub):
"""Evaluation on test set for submission on ESA website"""
for phase in ['test', 'real_test']:
loop = tqdm(self.dataloader[phase], desc="Evaluation for submission",
bar_format='{l_bar}{bar:10}{r_bar}{bar:-10b}', file=sys.stdout)
... | Evaluation on test set for submission on ESA website | Evaluation on test set for submission on ESA website | [
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"ESA",
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] | def evaluate_submit(self, sub):
for phase in ['test', 'real_test']:
loop = tqdm(self.dataloader[phase], desc="Evaluation for submission",
bar_format='{l_bar}{bar:10}{r_bar}{bar:-10b}', file=sys.stdout)
for inputs, filenames in loop:
inputs = inputs... | [
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8cd96511c23ec58df9bfdfb466a9a888c10dea24 | possoj/Mobile-URSONet | src/pose_net.py | [
"MIT"
] | Python | eval_error_distance | <not_specific> | def eval_error_distance(self):
"""Evaluation on validation set. Distance with the target spacecraft is also returned for each prediction"""
phase = 'valid'
loop = tqdm(self.dataloader[phase], desc="Evaluation by distance", file=sys.stdout,
bar_format='{l_bar}{bar:10}{r_bar}{... | Evaluation on validation set. Distance with the target spacecraft is also returned for each prediction | Evaluation on validation set. Distance with the target spacecraft is also returned for each prediction | [
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] | def eval_error_distance(self):
phase = 'valid'
loop = tqdm(self.dataloader[phase], desc="Evaluation by distance", file=sys.stdout,
bar_format='{l_bar}{bar:10}{r_bar}{bar:-10b}')
ori_error = []
pos_error = []
distance = []
for inputs, targets in loop:
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8cd96511c23ec58df9bfdfb466a9a888c10dea24 | possoj/Mobile-URSONet | src/pose_net.py | [
"MIT"
] | Python | objective | <not_specific> | def objective(self, trial):
"""This is an objective function for hyperparameter tuning with Optuna"""
self.hparam_step += 1
# Uncomment the following to add hyperparameters:
# lr = trial.suggest_uniform("lr", 1e-5, 1e-1)
# self.config.ROT_PROBABILITY = trial.suggest_float("ROT_P... | This is an objective function for hyperparameter tuning with Optuna | This is an objective function for hyperparameter tuning with Optuna | [
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] | def objective(self, trial):
self.hparam_step += 1
self.config.WEIGHT_DECAY = trial.suggest_float("WEIGHT_DECAY", 0, 1e-2, step=1e-5)
self.model = self.import_model()
self.dataloader = self.import_dataset()
self.ori_criterion, self.pos_criterion = self.set_loss()
self.opti... | [
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8d68d32606b5ec842e383048c2b8a235a4f7a412 | kwarodom/mib_ui_data_analytics | energygame/views.py | [
"Unlicense"
] | Python | smap_plot_thermostat | <not_specific> | def smap_plot_thermostat(request, mac):
"""Page load definition for thermostat statistics."""
print "inside smap view method"
context = RequestContext(request)
if request.method == 'GET':
mac = '18b4302964f1'
device_metadata = [ob.device_control_page_info() for ob in DeviceMetadata.obje... | Page load definition for thermostat statistics. | Page load definition for thermostat statistics. | [
"Page",
"load",
"definition",
"for",
"thermostat",
"statistics",
"."
] | def smap_plot_thermostat(request, mac):
print "inside smap view method"
context = RequestContext(request)
if request.method == 'GET':
mac = '18b4302964f1'
device_metadata = [ob.device_control_page_info() for ob in DeviceMetadata.objects.filter(mac_address=mac)]
print device_metadata
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8d68d32606b5ec842e383048c2b8a235a4f7a412 | kwarodom/mib_ui_data_analytics | energygame/views.py | [
"Unlicense"
] | Python | smap_plot_vav | <not_specific> | def smap_plot_vav(request, mac):
"""Page load definition for VAV statistics."""
print "inside smap view method"
context = RequestContext(request)
if request.method == 'GET':
device_metadata = [ob.device_control_page_info() for ob in DeviceMetadata.objects.filter(mac_address=mac)]
print ... | Page load definition for VAV statistics. | Page load definition for VAV statistics. | [
"Page",
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"definition",
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"statistics",
"."
] | def smap_plot_vav(request, mac):
print "inside smap view method"
context = RequestContext(request)
if request.method == 'GET':
device_metadata = [ob.device_control_page_info() for ob in DeviceMetadata.objects.filter(mac_address=mac)]
print device_metadata
device_id = device_metadata[... | [
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8d68d32606b5ec842e383048c2b8a235a4f7a412 | kwarodom/mib_ui_data_analytics | energygame/views.py | [
"Unlicense"
] | Python | smap_plot_rtu | <not_specific> | def smap_plot_rtu(request, mac):
"""Page load definition for RTU statistics."""
print "inside smap view method"
context = RequestContext(request)
if request.method == 'GET':
device_metadata = [ob.device_control_page_info() for ob in DeviceMetadata.objects.filter(mac_address=mac)]
print ... | Page load definition for RTU statistics. | Page load definition for RTU statistics. | [
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"definition",
"for",
"RTU",
"statistics",
"."
] | def smap_plot_rtu(request, mac):
print "inside smap view method"
context = RequestContext(request)
if request.method == 'GET':
device_metadata = [ob.device_control_page_info() for ob in DeviceMetadata.objects.filter(mac_address=mac)]
print device_metadata
device_id = device_metadata[... | [
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afbfe2075bc7282dde472eed9fb933923c108afe | kwarodom/mib_ui_data_analytics | dashboard/views.py | [
"Unlicense"
] | Python | smap_plot_thermostat | <not_specific> | def smap_plot_thermostat(request, mac):
"""Page load definition for thermostat statistics."""
print "inside smap view method"
context = RequestContext(request)
if request.method == 'GET':
device_metadata = [ob.device_control_page_info() for ob in DeviceMetadata.objects.filter(mac_address=mac)]
... | Page load definition for thermostat statistics. | Page load definition for thermostat statistics. | [
"Page",
"load",
"definition",
"for",
"thermostat",
"statistics",
"."
] | def smap_plot_thermostat(request, mac):
print "inside smap view method"
context = RequestContext(request)
if request.method == 'GET':
device_metadata = [ob.device_control_page_info() for ob in DeviceMetadata.objects.filter(mac_address=mac)]
print device_metadata
device_id = device_me... | [
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65f423e476999d2a0ff3d5806c533bff23d4a718 | kwarodom/mib_ui_data_analytics | IEBSubscriber/iebsubscriber/agent.py | [
"Unlicense"
] | Python | on_match_device_status_update | null | def on_match_device_status_update(self, topic, headers, message, match):
'''Handle message and send to browser.'''
print os.path.basename(__file__)+"@on_match_device_status_update"
print "message:"+str(message)
device_info = topic.split('/')
device_id = device_info[6]
dev... | Handle message and send to browser. | Handle message and send to browser. | [
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"."
] | def on_match_device_status_update(self, topic, headers, message, match):
print os.path.basename(__file__)+"@on_match_device_status_update"
print "message:"+str(message)
device_info = topic.split('/')
device_id = device_info[6]
device_type = device_info[5]
page_load_helper... | [
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65f423e476999d2a0ff3d5806c533bff23d4a718 | kwarodom/mib_ui_data_analytics | IEBSubscriber/iebsubscriber/agent.py | [
"Unlicense"
] | Python | on_match_device_status_update_rtu | null | def on_match_device_status_update_rtu(self, topic, headers, message, match):
'''Handle message and send to browser.'''
print os.path.basename(__file__)+"@on_match_device_status_update"
print "message:"+str(message)
device_info = topic.split('/')
device_id = device_info[6]
... | Handle message and send to browser. | Handle message and send to browser. | [
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"."
] | def on_match_device_status_update_rtu(self, topic, headers, message, match):
print os.path.basename(__file__)+"@on_match_device_status_update"
print "message:"+str(message)
device_info = topic.split('/')
device_id = device_info[6]
device_type = device_info[5]
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65f423e476999d2a0ff3d5806c533bff23d4a718 | kwarodom/mib_ui_data_analytics | IEBSubscriber/iebsubscriber/agent.py | [
"Unlicense"
] | Python | on_match_device_status_update_vav | null | def on_match_device_status_update_vav(self, topic, headers, message, match):
'''Handle message and send to browser.'''
print os.path.basename(__file__)+"@on_match_device_status_update"
print "message:"+str(message)
device_info = topic.split('/')
device_id = device_info[6]
... | Handle message and send to browser. | Handle message and send to browser. | [
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"."
] | def on_match_device_status_update_vav(self, topic, headers, message, match):
print os.path.basename(__file__)+"@on_match_device_status_update"
print "message:"+str(message)
device_info = topic.split('/')
device_id = device_info[6]
device_type = device_info[5]
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a69cd36c5cfd1a8e127ddda094eff02a64fe0827 | kwarodom/mib_ui_data_analytics | AgentSimulator/agentsimulator/agent.py | [
"Unlicense"
] | Python | main | null | def main(argv=sys.argv):
'''Main method called by the eggsecutable.'''
try:
utils.default_main(ListenerAgent,
description='Example VOLTTRON heartbeat agent',
argv=argv)
except Exception as e:
_log.exception('unhandled exception') | Main method called by the eggsecutable. | Main method called by the eggsecutable. | [
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] | def main(argv=sys.argv):
try:
utils.default_main(ListenerAgent,
description='Example VOLTTRON heartbeat agent',
argv=argv)
except Exception as e:
_log.exception('unhandled exception') | [
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408b16062fad3e601e7f59efd3e1c2d4e1fa724b | newolfsociety/team7- | bot/exts/filter.py | [
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"""Try to find matches between registered filter patterns with a message."""
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408b16062fad3e601e7f59efd3e1c2d4e1fa724b | newolfsociety/team7- | bot/exts/filter.py | [
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408b16062fad3e601e7f59efd3e1c2d4e1fa724b | newolfsociety/team7- | bot/exts/filter.py | [
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b965245c3e51900afe12f0fbc12a04daad0cd5bc | newolfsociety/team7- | postgres/utils.py | [
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e70c26d3cbee96bc2abf80bac522ce8574987171 | newolfsociety/team7- | bot/bot.py | [
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f63b992b4fb8d96d9db06be7eff2b8259ba7f4b5 | bm371613/slice-aggregator | slice_aggregator/by_ixs.py | [
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e69f552f47f52ec56dcc3bd56f464d73fb522147 | reductionista/ipython-sql | src/sql/parse.py | [
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e5cea2450a709096167662e80075bd3aae416602 | reductionista/ipython-sql | src/sql/magic.py | [
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raise ImportError("Must `pip install pandas` to use DataFrames")
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frame_name = raw.strip(";")
if not frame_name:
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9fc7916ae7c211eb296824ffb80ae54fe9d0c34c | reductionista/ipython-sql | src/tests/test_magic.py | [
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runsql(
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b62b550f4c146dcd37173a98c5a0cfaf7027b6b3 | insaneyilin/face_off | capture_manager.py | [
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"""
Capture the next fame, if any
"""
assert not self._is_entered_frame, \
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if self._capture is not None:
self._is_entered_frame = self._capture.grab() |
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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] | Python | login | <not_specific> | def login(self, user_id, password):
"""Authenticate to ownCloud.
This will create a session on the server.
:param user_id: user id
:param password: password
:raises: ResponseError in case an HTTP error status was returned
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:param password: password
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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] | Python | logout | <not_specific> | def logout(self):
"""Log out the authenticated user and close the session.
:returns: True if the operation succeeded, False otherwise
:raises: ResponseError in case an HTTP error status was returned
"""
# TODO actual logout ?
self.__session.close()
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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] | Python | file_info | <not_specific> | def file_info(self, path):
"""Returns the file info for the given remote file
:param path: path to the remote file
:returns: file info
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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:param data: data to write into the remote file
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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:param local_directory: path to the local directory to upload
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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] | Python | delete | <not_specific> | def delete(self, path):
"""Deletes a remote file or directory
:param path: path to the file or directory to delete
:returns: True if the operation succeeded, False otherwise
:raises: ResponseError in case an HTTP error status was returned
"""
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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] | Python | share_file_with_link | <not_specific> | def share_file_with_link(self, path):
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:returns: instance of :class:`PublicShare` with the share info
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post_data = {'shareType': self.OCS_SHARE_TYPE_LINK, 'path': path}
res = self.__make_ocs_request(
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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] | Python | is_shared | <not_specific> | def is_shared(self, path):
"""Checks whether a path is already shared
:param path: path to the share to be checked
:returns: True if the path is already shared, else False
:raises: ResponseError in case an HTTP error status was returned
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# make sure that the path exis... | Checks whether a path is already shared
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result = self.get_shares(path)
if result:
return (len(result) > 0)
except ResponseError as e:
if e.status_code != 404:
raise e
return False
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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] | Python | share_file_with_user | <not_specific> | def share_file_with_user(self, path, user, **kwargs):
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:param path: path to the remote file to share
:param user: name of the user whom we want to share a file/folder
:param perms (optional): permissions of the shared object
default... | Shares a remote file with specified user
:param path: path to the remote file to share
:param user: name of the user whom we want to share a file/folder
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perms = kwargs.get('perms', self.OCS_PERMISSION_READ)
if (((not isinstance(perms, int)) or (perms > self.OCS_PERMISSION_ALL))
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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a6f1d549e1c1ea1762ac2b6c71a5fe07f9a1a848 | cernbox/pyocclient | owncloud/owncloud.py | [
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] | Python | __strip_dav_path | <not_specific> | def __strip_dav_path(self, path):
"""Removes the leading "remote.php/webdav" path from the given path
:param path: path containing the remote DAV path "remote.php/webdav"
:returns: path stripped of the remote DAV path
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053d673585ceceaf4a3ed61c2cf79c3c180c8aa3 | signalfx/python-tornado | tornado_opentracing/initialization.py | [
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"""
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This happens dynamically every time a request handler instace
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13f35a16943bc06f8ca55c6bb9bd7dd143aa14b7 | signalfx/python-tornado | tornado_opentracing/_tracing.py | [
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"""
Function decorator that traces functions
NOTE: Must be placed before the Tornado decorators
@param attributes any number of request attributes
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"""
@wrapt.decorator
def wrapp... |
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13f35a16943bc06f8ca55c6bb9bd7dd143aa14b7 | signalfx/python-tornado | tornado_opentracing/_tracing.py | [
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Helper function to avoid rewriting for middleware and decorator.
Returns a new span from the request with logged attributes and
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"""
operation_name = self._get_operation_name(handler)
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00db83ccd16877e1361e50b2360168acdb6a870f | BozianuLeon/graphnet | src/graphnet/models/utils.py | [
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] | Python | calculate_xyzt_homophily | <not_specific> | def calculate_xyzt_homophily(x, edge_index, batch):
"""Calculates xyzt homophily from a batch of graphs.
Homophily is a graph scalar quantity that measures the likeness of variables
in nodes. Notice that this calculator assumes a special order of input
features in x.
Returns:
tuple : tuple... | Calculates xyzt homophily from a batch of graphs.
Homophily is a graph scalar quantity that measures the likeness of variables
in nodes. Notice that this calculator assumes a special order of input
features in x.
Returns:
tuple : tuple of torch.tensor each with shape [batch_size,1]
| Calculates xyzt homophily from a batch of graphs.
Homophily is a graph scalar quantity that measures the likeness of variables
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00db83ccd16877e1361e50b2360168acdb6a870f | BozianuLeon/graphnet | src/graphnet/models/utils.py | [
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"""
Calculate the matrix of pairwise distances between pulses in (x,y,z)-coordinates.
Args:
xyz_coords: (x,y,z)-coordinates of pulses, of shape [nb_doms, 3].
Returns:
Matrix of pairwise distances, of shape [nb_doms, nb_doms]
... |
Calculate the matrix of pairwise distances between pulses in (x,y,z)-coordinates.
Args:
xyz_coords: (x,y,z)-coordinates of pulses, of shape [nb_doms, 3].
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Matrix of pairwise distances, of shape [nb_doms, nb_doms]
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4ee64c31ec5738b0e02d72aafa90b5dab0f9fa89 | BozianuLeon/graphnet | src/graphnet/models/detector/icecube.py | [
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Args:
data (Data): Input graph data.
Returns:
Data: Connected and preprocessed graph data.
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4ee64c31ec5738b0e02d72aafa90b5dab0f9fa89 | BozianuLeon/graphnet | src/graphnet/models/detector/icecube.py | [
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"""Ingests data, builds graph (connectivity/adjacency), and preprocesses features.
Args:
data (Data): Input graph data.
Returns:
Data: Connected and preprocessed graph data.
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# Check(s)
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4ee64c31ec5738b0e02d72aafa90b5dab0f9fa89 | BozianuLeon/graphnet | src/graphnet/models/detector/icecube.py | [
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Args:
data (Data): Input graph data.
Returns:
Data: Connected and preprocessed graph data.
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# Check(s)
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Args:
data (Data): Input graph data.
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e9669c4c0d3eb68438594c7c905f70a6d887a566 | BozianuLeon/graphnet | src/graphnet/models/coarsening.py | [
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"""Additional poolings of feature tensor `x` on `data`.
By default the nominal `pooling_method` is used for features as well.
This method can be overwritten for bespoke coarsening operations.
"""
return N... | Additional poolings of feature tensor `x` on `data`.
By default the nominal `pooling_method` is used for features as well.
This method can be overwritten for bespoke coarsening operations.
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e9669c4c0d3eb68438594c7c905f70a6d887a566 | BozianuLeon/graphnet | src/graphnet/models/coarsening.py | [
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"""Perform clustering of nodes in `data` by assigning unique cluster indices to each."""
# dom_index = group_pulses_to_dom(data)
dom_index = group_by(
data, ["dom_x", "dom_y", "dom_z", "rde", "pmt_area"]
)
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f339545d5b709f8bf3fc969d7ac24774f0deeb04 | BozianuLeon/graphnet | src/graphnet/pisa/plotting.py | [
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] | Python | plot_2D_contour | <not_specific> | def plot_2D_contour(
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xlim=(0.4, 0.6),
ylim=(2.38 * 1e-3, 2.55 * 1e-3),
chi2_critical_value=4.605,
width=3.176,
height=2.388,
):
"""Plots 2D contours from GraphNeT PISA fits.
Args:
contour_data (list): list of dictionaries with plotting information. Format is for e... | Plots 2D contours from GraphNeT PISA fits.
Args:
contour_data (list): list of dictionaries with plotting information. Format is for each dictionary is: {'path':path_to_pisa_fit_result, 'model': 'name_of_my_model_in_fit'}. One can specify optional fields in the dictionary: "label" - the legend label, "colo... | Plots 2D contours from GraphNeT PISA fits. | [
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xlim=(0.4, 0.6),
ylim=(2.38 * 1e-3, 2.55 * 1e-3),
chi2_critical_value=4.605,
width=3.176,
height=2.388,
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fig, ax = plt.subplots(figsize=(width, height), constrained_layout=True)
proxy = []
labels = []
for entry in contour_data:
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f339545d5b709f8bf3fc969d7ac24774f0deeb04 | BozianuLeon/graphnet | src/graphnet/pisa/plotting.py | [
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):
"""Plots 1D contours from GraphNeT PISA fits.
Args:
contour_data (list): list of dictionaries with plotting information. Format is for each dictionary is: {'path':path_to_pisa_fit_result, 'model': 'name_... | Plots 1D contours from GraphNeT PISA fits.
Args:
contour_data (list): list of dictionaries with plotting information. Format is for each dictionary is: {'path':path_to_pisa_fit_result, 'model': 'name_of_my_model_in_fit'}. One can specify optional fields in the dictionary: "label" - the legend label, "colo... | Plots 1D contours from GraphNeT PISA fits. | [
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variables = ["theta23_fixed", "dm31_fixed"]
fig, ax = plt.subplots(
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ls = 0
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... | Plots 1D contours from GraphNeT PISA fits. | [
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] | [
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{
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{
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] | {
"returns": [
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"type": "matplotlib.pyplot.figure"
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],
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... |
bbac19d83c2856e3f4287b2a5a741e0a5df2e691 | BozianuLeon/graphnet | studies/upgrade_noise/deployment/process_i3_file.py | [
"Apache-2.0"
] | Python | main | null | def main(input_files, output_file, key, pulsemaps, gcd_file, events_max):
"""Run minimal icetray chain with GraphNeT module."""
# Make sure output directory exists
makedirs(dirname(output_file), exist_ok=True)
# Get GCD file
if gcd_file is None:
gcd_candidates = [p for p in input_files if ... | Run minimal icetray chain with GraphNeT module. | Run minimal icetray chain with GraphNeT module. | [
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] | def main(input_files, output_file, key, pulsemaps, gcd_file, events_max):
makedirs(dirname(output_file), exist_ok=True)
if gcd_file is None:
gcd_candidates = [p for p in input_files if is_gcd_file(p)]
assert (
len(gcd_candidates) == 1
), f"Did not get exactly one GCD-file can... | [
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45b07f7057b6dcc347b9dde6b6c7219bf7595351 | BozianuLeon/graphnet | src/graphnet/plots/utils.py | [
"Apache-2.0"
] | Python | add_pid_and_interaction | <not_specific> | def add_pid_and_interaction(db, df):
"""Adds particle and interaction ID from database `db` to dataframe `df`."""
events = df["event_no"]
with sqlite3.connect(db) as con:
query = (
"select event_no, pid, interaction_type from truth where event_no in %s"
% str(tuple(events))
... | Adds particle and interaction ID from database `db` to dataframe `df`. | Adds particle and interaction ID from database `db` to dataframe `df`. | [
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] | def add_pid_and_interaction(db, df):
events = df["event_no"]
with sqlite3.connect(db) as con:
query = (
"select event_no, pid, interaction_type from truth where event_no in %s"
% str(tuple(events))
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data = (
pd.read_sql(query, con)
.sort_v... | [
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... |
45b07f7057b6dcc347b9dde6b6c7219bf7595351 | BozianuLeon/graphnet | src/graphnet/plots/utils.py | [
"Apache-2.0"
] | Python | calculate_width_error | <not_specific> | def calculate_width_error(diff):
"""Calculate the uncertainty on the estimated width from the 68-interpercentile range."""
N = len(diff)
x_16 = abs(
diff - np.percentile(diff, 16, interpolation="nearest")
).argmin()
x_84 = abs(
diff - np.percentile(diff, 84, interpolation="nearest")
... | Calculate the uncertainty on the estimated width from the 68-interpercentile range. | Calculate the uncertainty on the estimated width from the 68-interpercentile range. | [
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] | def calculate_width_error(diff):
N = len(diff)
x_16 = abs(
diff - np.percentile(diff, 16, interpolation="nearest")
).argmin()
x_84 = abs(
diff - np.percentile(diff, 84, interpolation="nearest")
).argmin()
if len(diff) > 0:
error_width = np.sqrt(
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} |
45b07f7057b6dcc347b9dde6b6c7219bf7595351 | BozianuLeon/graphnet | src/graphnet/plots/utils.py | [
"Apache-2.0"
] | Python | check_for_retro | bool | def check_for_retro(data: pd.DataFrame) -> bool:
"""Check whether `data` contains a column with a name containing "retro"."""
columns = data.columns
is_retro = False
for column in columns:
if "retro" in column:
is_retro = True
break
return is_retro | Check whether `data` contains a column with a name containing "retro". | Check whether `data` contains a column with a name containing "retro". | [
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] | def check_for_retro(data: pd.DataFrame) -> bool:
columns = data.columns
is_retro = False
for column in columns:
if "retro" in column:
is_retro = True
break
return is_retro | [
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45b07f7057b6dcc347b9dde6b6c7219bf7595351 | BozianuLeon/graphnet | src/graphnet/plots/utils.py | [
"Apache-2.0"
] | Python | PlotWidth | <not_specific> | def PlotWidth(key_limits, biases):
"""Plot reconstruction resoltion (width) for DynEdge vs. RetroReco."""
key_limits = key_limits["width"]
if "retro" in biases.keys():
contains_retro = True
else:
contains_retro = False
for key in biases["dynedge"].keys():
fig, ax = plt.subpl... | Plot reconstruction resoltion (width) for DynEdge vs. RetroReco. | Plot reconstruction resoltion (width) for DynEdge vs. | [
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] | def PlotWidth(key_limits, biases):
key_limits = key_limits["width"]
if "retro" in biases.keys():
contains_retro = True
else:
contains_retro = False
for key in biases["dynedge"].keys():
fig, ax = plt.subplots(2, 3, figsize=(11.69, 8.27))
fig.suptitle("dynedge: %s" % key, s... | [
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45b07f7057b6dcc347b9dde6b6c7219bf7595351 | BozianuLeon/graphnet | src/graphnet/plots/utils.py | [
"Apache-2.0"
] | Python | PlotRelativeImprovement | <not_specific> | def PlotRelativeImprovement(key_limits, biases):
"""Plot relative improvement of DynEdge vs. RetroReco."""
key_limits = key_limits["rel_imp"]
for key in biases["dynedge"].keys():
fig, ax = plt.subplots(2, 3, figsize=(11.69, 8.27))
fig.suptitle("dynedge: %s" % key, size=30)
pid_count ... | Plot relative improvement of DynEdge vs. RetroReco. | Plot relative improvement of DynEdge vs. | [
"Plot",
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"improvement",
"of",
"DynEdge",
"vs",
"."
] | def PlotRelativeImprovement(key_limits, biases):
key_limits = key_limits["rel_imp"]
for key in biases["dynedge"].keys():
fig, ax = plt.subplots(2, 3, figsize=(11.69, 8.27))
fig.suptitle("dynedge: %s" % key, size=30)
pid_count = 0
for pid in biases["dynedge"][key].keys():
... | [
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697ae1677de1f3bb5d2f53076b6bdc9f4d464681 | BozianuLeon/graphnet | src/graphnet/models/task/task.py | [
"Apache-2.0"
] | Python | _validate_and_set_transforms | null | def _validate_and_set_transforms(
self,
transform_prediction_and_target: Union[Callable, None],
transform_target: Union[Callable, None],
transform_inference: Union[Callable, None],
transform_support: Union[Callable, None],
):
"""Assert that a valid combination of tran... | Assert that a valid combination of transformation arguments are passed and update the corresponding functions | Assert that a valid combination of transformation arguments are passed and update the corresponding functions | [
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self,
transform_prediction_and_target: Union[Callable, None],
transform_target: Union[Callable, None],
transform_inference: Union[Callable, None],
transform_support: Union[Callable, None],
):
assert not (
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42ba5a8cff373f7c504fa163f58cf6739216c839 | BozianuLeon/graphnet | src/graphnet/data/i3extractor.py | [
"Apache-2.0"
] | Python | muon_stopped | <not_specific> | def muon_stopped(truth, borders, horizontal_pad=100.0, vertical_pad=100.0):
"""
Calculates where a simulated muon stops and if this is inside the detectors fiducial volume.
IMPORTANT: The final position of the muon is saved in truth extractor/databases as position_x,position_y and position_z.
... |
Calculates where a simulated muon stops and if this is inside the detectors fiducial volume.
IMPORTANT: The final position of the muon is saved in truth extractor/databases as position_x,position_y and position_z.
This is analogoues to the neutrinos whose interaction vertex is saved under the sa... | Calculates where a simulated muon stops and if this is inside the detectors fiducial volume.
IMPORTANT: The final position of the muon is saved in truth extractor/databases as position_x,position_y and position_z.
This is analogoues to the neutrinos whose interaction vertex is saved under the same name. | [
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... | def muon_stopped(truth, borders, horizontal_pad=100.0, vertical_pad=100.0):
border = mpath.Path(borders[0])
start_pos = np.array(
[truth["position_x"], truth["position_y"], truth["position_z"]]
)
travel_vec = -1 * np.array(
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truth["track_length"]
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a16a8546c30fc22f2c06edff19769d5c5095d634 | BozianuLeon/graphnet | src/graphnet/components/pool.py | [
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] | Python | sum_pool_and_distribute | Tensor | def sum_pool_and_distribute(
tensor: Tensor,
cluster_index: LongTensor,
batch: Optional[LongTensor] = None,
) -> Tensor:
"""Sum-pool values across the cluster, and distribute the individual nodes."""
if batch is None:
batch = torch.zeros(tensor.size(dim=0)).long()
tensor_pooled, _ = sum_... | Sum-pool values across the cluster, and distribute the individual nodes. | Sum-pool values across the cluster, and distribute the individual nodes. | [
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tensor: Tensor,
cluster_index: LongTensor,
batch: Optional[LongTensor] = None,
) -> Tensor:
if batch is None:
batch = torch.zeros(tensor.size(dim=0)).long()
tensor_pooled, _ = sum_pool_x(cluster_index, tensor, batch)
inv, _ = consecutive_cluster(cluster_index... | [
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a16a8546c30fc22f2c06edff19769d5c5095d634 | BozianuLeon/graphnet | src/graphnet/components/pool.py | [
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tensor: Tensor, batch: Optional[LongTensor] = None
) -> LongTensor:
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Args:
tensor (Tensor): Tensor of shape [N, F]
batch (Optional[LongTensor], optional): Batch indices, to only group
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batch (Optional[LongTensor], optional): Batch indices, to only group
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tensor = tensor.cat((tensor, batch.unsqueeze(dim=1)), dim=1)
return torch.unique(tensor, return_inverse=True, dim=0)[1] | [
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a16a8546c30fc22f2c06edff19769d5c5095d634 | BozianuLeon/graphnet | src/graphnet/components/pool.py | [
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a16a8546c30fc22f2c06edff19769d5c5095d634 | BozianuLeon/graphnet | src/graphnet/components/pool.py | [
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a16a8546c30fc22f2c06edff19769d5c5095d634 | BozianuLeon/graphnet | src/graphnet/components/pool.py | [
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r"""Pools and coarsens a graph given by the
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All nodes within the same cluster will be represented as one node.
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5980dee5fda952de5079f94ab087ebef4d2059c6 | BozianuLeon/graphnet | src/graphnet/utilities/imports.py | [
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"""Decorator for only exposing function if `icecube` module is present."""
def wrapper(*args, **kwargs):
if has_icecube_package():
return test_function(*args, **kwargs)
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71a00d6533f8202e1f3b01bfd85c232391d42fd2 | mosaicrown/freya-fs | mixslice.py | [
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"""Creates a MixSlice from plaintext data.
Args:
data (bytestr): The data to encrypt (multiple of MACRO_SIZE).
key (bytestr): The key used for AES encryption (16 bytes long).
iv (bytestr): The iv used for A... | Creates a MixSlice from plaintext data.
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data (bytestr): The data to encrypt (multiple of MACRO_SIZE).
key (bytestr): The key used for AES encryption (16 bytes long).
iv (bytestr): The iv used for AES encryption (16 bytes long).
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padded_data = padder.pad(data)
fragments = _mix_and_slice(data=padded_data, key=key,
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9a10c9b55327ba51836cef874e8ba9fb270e4770 | fir3storm/Dagon | thirdparty/blake/blake_wrapper.py | [
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9a10c9b55327ba51836cef874e8ba9fb270e4770 | fir3storm/Dagon | thirdparty/blake/blake_wrapper.py | [
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9a10c9b55327ba51836cef874e8ba9fb270e4770 | fir3storm/Dagon | thirdparty/blake/blake_wrapper.py | [
"MIT"
] | Python | final | <not_specific> | def final(self, data=b''):
""" finalize the hash -- pad and hash remaining data
returns hashval, the digest
"""
if data:
self.update(data)
hashval = c_buffer(int(self. hashbitlen /8))
ret = LIB.Final(self.state, hashval)
if ret:
raise ... | finalize the hash -- pad and hash remaining data
returns hashval, the digest
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self.update(data)
hashval = c_buffer(int(self. hashbitlen /8))
ret = LIB.Final(self.state, hashval)
if ret:
raise Exception('Final() ret = %d', ret)
return hashval.raw | [
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9a10c9b55327ba51836cef874e8ba9fb270e4770 | fir3storm/Dagon | thirdparty/blake/blake_wrapper.py | [
"MIT"
] | Python | BLAKE_func | <not_specific> | def BLAKE_func(hashbitlen, data, databitlen):
""" all-in-one function
hashbitlen must be one of 224, 256, 384, 512
data data to be hashed (bytestring)
databitlen length of data to be hashed in *bits*
returns digest value (bytestring)
"""
return BLAKE(hashbitlen).... | all-in-one function
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data data to be hashed (bytestring)
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returns digest value (bytestring)
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00075e486092ce9ed384f993921fe787a4c6d311 | fir3storm/Dagon | bin/attacks/bruteforce/bf_attack.py | [
"MIT"
] | Python | bruteforce_main | null | def bruteforce_main(verf_hash, algorithm=None, wordlist=None, salt=None, placement=None, all_algs=False, posx="",
use_hex=False, verbose=False, batch=False, rounds=10):
"""
Main function to be used for bruteforcing a hash
"""
wordlist_created = False
if wordlist is None:
... |
Main function to be used for bruteforcing a hash
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use_hex=False, verbose=False, batch=False, rounds=10):
wordlist_created = False
if wordlist is None:
create_dir("bf-dicts", verbose=verbose)
for item in os.listdi... | [
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2ac02f7405766168b23b070ef427cc733875bfb8 | fir3storm/Dagon | thirdparty/blake/blake.py | [
"MIT"
] | Python | addsalt | null | def addsalt(self, salt):
""" adds a salt to the hash function (OPTIONAL)
should be called AFTER Init, and BEFORE update
salt: a bytestring, length determined by hashbitlen.
if not of sufficient length, the bytestring
will be assumed to be a big endi... | adds a salt to the hash function (OPTIONAL)
should be called AFTER Init, and BEFORE update
salt: a bytestring, length determined by hashbitlen.
if not of sufficient length, the bytestring
will be assumed to be a big endian number and
pre... | adds a salt to the hash function (OPTIONAL)
should be called AFTER Init, and BEFORE update
salt: a bytestring, length determined by hashbitlen.
if not of sufficient length, the bytestring
will be assumed to be a big endian number and
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if self.state != 1:
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saltsize = self.WORDBYTES * 4
if len(salt) < saltsize:
salt = (chr(0) * (saltsize - len(salt)) + salt)
else:
salt = salt[-saltsize:]
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2ac02f7405766168b23b070ef427cc733875bfb8 | fir3storm/Dagon | thirdparty/blake/blake.py | [
"MIT"
] | Python | update | <not_specific> | def update(self, data):
""" update the state with new data, storing excess data
as necessary. may be called multiple times and if a
call sends less than a full block in size, the leftover
is cached and will be consumed in the next call
data: data to be hashed (b... | update the state with new data, storing excess data
as necessary. may be called multiple times and if a
call sends less than a full block in size, the leftover
is cached and will be consumed in the next call
data: data to be hashed (bytestring)
| update the state with new data, storing excess data
as necessary. may be called multiple times and if a
call sends less than a full block in size, the leftover
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self.state = 2
BLKBYTES = self.BLKBYTES
BLKBITS = self.BLKBITS
datalen = len(data)
if not datalen: return
if type(data) == type(u''):
data = data.encode('UTF-8')
left = len(self.cache)
fill = BLKBYTES - left
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2ac02f7405766168b23b070ef427cc733875bfb8 | fir3storm/Dagon | thirdparty/blake/blake.py | [
"MIT"
] | Python | final | <not_specific> | def final(self, data=''):
""" finalize the hash -- pad and hash remaining data
returns hashval, the digest
"""
if self.state == 3:
# we have already finalized so simply return the
# previously calculated/stored hash value
return self.hash
... | finalize the hash -- pad and hash remaining data
returns hashval, the digest
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if self.state == 3:
return self.hash
if data:
self.update(data)
ZZ = b'\x00'
ZO = b'\x01'
OZ = b'\x80'
OO = b'\x81'
PADDING = OZ + ZZ * 128
tt = self.t + (len(self.cache) << 3)
if self.BLKBYTES ==... | [
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2ac02f7405766168b23b070ef427cc733875bfb8 | fir3storm/Dagon | thirdparty/blake/blake.py | [
"MIT"
] | Python | _int2fourByte | <not_specific> | def _int2fourByte(self, x): # see also long2byt() below
""" convert a number to a 4-byte string, high order
truncation possible (in Python x could be a BIGNUM)
"""
return struct.pack('!L', x) | convert a number to a 4-byte string, high order
truncation possible (in Python x could be a BIGNUM)
| convert a number to a 4-byte string, high order
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2778bcd051477f2564b5c398a0a39cb418cbb99e | fir3storm/Dagon | bin/generators/__init__.py | [
"MIT"
] | Python | hash_file_generator | <not_specific> | def hash_file_generator(self):
"""
Parse a given file for anything that matches the hashes in the
hash type regex dict. Possible that this will pull random bytes
of data from the files.
"""
matched_hashes = set()
keys = [k for k in bin.verify_hashes.verify.H... |
Parse a given file for anything that matches the hashes in the
hash type regex dict. Possible that this will pull random bytes
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matched_hashes = set()
keys = [k for k in bin.verify_hashes.verify.HASH_TYPE_REGEX.iterkeys()]
with open(self.words) as wordlist:
for item in wordlist.readlines():
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} |
3fc45551ccbedd19219046b0736995d0d5f7661a | fir3storm/Dagon | lib/algorithms/hashing_algs.py | [
"MIT"
] | Python | blowfish | <not_specific> | def blowfish(string, **placeholder):
"""
Create a blowfish hash using bcrypt
> :param string: string to generate a Blowfish hash from
> :return: Blowfish hash
Example:
>>> blowfish("test")
$2b$12$fSX/dvlx3dJGkGYKSbBbLOTOhzqj8xQ2krOtu2QkHNeJiYTC0B/ji
"""
if type(stri... |
Create a blowfish hash using bcrypt
> :param string: string to generate a Blowfish hash from
> :return: Blowfish hash
Example:
>>> blowfish("test")
$2b$12$fSX/dvlx3dJGkGYKSbBbLOTOhzqj8xQ2krOtu2QkHNeJiYTC0B/ji
| Create a blowfish hash using bcrypt
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> :return: Blowfish hash | [
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] | def blowfish(string, **placeholder):
if type(string) is unicode:
string = lib.settings.force_encoding(string)
return bcrypt.hashpw(str(string), bcrypt.gensalt()) | [
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> :param string: string to generate a Blowfish hash from
> :return: Blowfish hash | [
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"\"\"\"\n Create a blowfish hash using bcrypt\n\n > :param string: string to generate a Blowfish hash from\n > :return: Blowfish hash\n\n Example:\n >>> blowfish(\"test\")\n $2b$12$fSX/dvlx3dJGkGYKSbBbLOTOhzqj8xQ2krOtu2QkHNeJiYTC0B/ji\n \"\"\""
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3fc45551ccbedd19219046b0736995d0d5f7661a | fir3storm/Dagon | lib/algorithms/hashing_algs.py | [
"MIT"
] | Python | postgres | <not_specific> | def postgres(string, salt=None, **placeholder):
"""
Create a PostgreSQL hash, if no salt is provided, salt will be created
> :param string: string to be hashed
> :return: a PostgreSQL hash
Example:
>>> postrges("test", "testing")
md55d6685f9c56cdd04d635c7cbed612db3
"""
... |
Create a PostgreSQL hash, if no salt is provided, salt will be created
> :param string: string to be hashed
> :return: a PostgreSQL hash
Example:
>>> postrges("test", "testing")
md55d6685f9c56cdd04d635c7cbed612db3
| Create a PostgreSQL hash, if no salt is provided, salt will be created
> :param string: string to be hashed
> :return: a PostgreSQL hash | [
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] | def postgres(string, salt=None, **placeholder):
if type(string) is unicode:
string = lib.settings.force_encoding(string)
if salt is None:
salt = lib.settings.random_salt_generator(use_string=True)[0]
obj = hashlib.md5()
obj.update(string + salt)
data = obj.hexdigest()
return "md5... | [
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3fc45551ccbedd19219046b0736995d0d5f7661a | fir3storm/Dagon | lib/algorithms/hashing_algs.py | [
"MIT"
] | Python | mssql_2000 | <not_specific> | def mssql_2000(string, salt=None, **placeholder):
"""
Create a MsSQL 2000 hash from a given string, if no salt is given, random salt will be generated
> :param string: the string to hash
> :return: a MsSQL 2000 hash
Example
>>> mssql_2000("testpass", salt="testsalt")
0x0100... |
Create a MsSQL 2000 hash from a given string, if no salt is given, random salt will be generated
> :param string: the string to hash
> :return: a MsSQL 2000 hash
Example
>>> mssql_2000("testpass", salt="testsalt")
0x01007465737473616C74C74B43A2862ECC89C7F94E02583583377F03977A1... | Create a MsSQL 2000 hash from a given string, if no salt is given, random salt will be generated
> :param string: the string to hash
> :return: a MsSQL 2000 hash
| [
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if type(string) is unicode:
string = lib.settings.force_encoding(string)
obj1 = hashlib.sha1()
obj2 = hashlib.sha1()
if salt is None:
salt = lib.settings.random_salt_generator(use_string=True)[0]
crypt_salt = salt.encode("hex")
da... | [
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3fc45551ccbedd19219046b0736995d0d5f7661a | fir3storm/Dagon | lib/algorithms/hashing_algs.py | [
"MIT"
] | Python | mssql_2005 | <not_specific> | def mssql_2005(string, salt=None, **placeholder):
"""
Create an MsSQL 2005 hash, if not salt is given, salt will be created
> :param string: string to be hashed
> :return: a MsSQL 2005 hash
Example:
>>> mssql_2005("test", salt="testing")
0x010074657374696e673f0414438c1b692d... |
Create an MsSQL 2005 hash, if not salt is given, salt will be created
> :param string: string to be hashed
> :return: a MsSQL 2005 hash
Example:
>>> mssql_2005("test", salt="testing")
0x010074657374696e673f0414438c1b692da8be7a1211a76d314ea0210f
| Create an MsSQL 2005 hash, if not salt is given, salt will be created
> :param string: string to be hashed
> :return: a MsSQL 2005 hash | [
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] | def mssql_2005(string, salt=None, **placeholder):
if type(string) is unicode:
string = lib.settings.force_encoding(string)
if salt is None:
salt = lib.settings.random_salt_generator(use_string=True)[0]
data_string = "".join(map(lambda s: ("%s\0" if ord(s) < 256 else "%s") % s.encode("utf8"),... | [
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"docstring_tokens":... |
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