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c191f54e8df3fd4c02d34aac2777bc96d9a810d2 | shepherdpp/qteasy | qteasy/history.py | [
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""" read a csv file and convert its data to a HistoryPanel
:return:
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c191f54e8df3fd4c02d34aac2777bc96d9a810d2 | shepherdpp/qteasy | qteasy/history.py | [
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""" read a hdf file and convert its data to a HistoryPanel
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fb1eeb84ab109aaf28c8259643a8ed31d9d2a192 | shepherdpp/qteasy | qteasy/finance.py | [
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"""calculate the transaction fee given all parameters
"""
if fixed_fees: # 采用固定费用模式计算, 返回固定费用及滑点成本，返回的是费用而不是费率
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d7e279b24d45237786f5447972d84d66ddcc5b5f | shepherdpp/qteasy | qteasy/operator.py | [
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b5fed8122cc37bb057bb8480f1eb896cbb373499 | shepherdpp/qteasy | qteasy/space.py | [
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b5fed8122cc37bb057bb8480f1eb896cbb373499 | shepherdpp/qteasy | qteasy/space.py | [
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70896e94a95a7945c578c92437fa32bc85fc8530 | digs1998/Image-Classifier | predict.py | [
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width, height = im.size #original size
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70896e94a95a7945c578c92437fa32bc85fc8530 | digs1998/Image-Classifier | predict.py | [
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''' Predict the class (or classes) of an image using a trained deep learning model.
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model.to(device)
model.eval()
img = process_image(image_path)
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img = torch.from_numpy(np.array([img])).float()
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9b67aa75fec79a12034867928f4af5335f4151bf | niazwazir/WAZIR_ESPCN1 | source/models.py | [
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] | Python | _initialize_weights | null | def _initialize_weights(self):
""" Initialize weights
Private function to initialize weights. Executes once when ESPCN object is made.
:return: None
"""
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if isinstance(m, nn.Conv2d):
if m.in_channels == 32:
... | Initialize weights
Private function to initialize weights. Executes once when ESPCN object is made.
:return: None
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94ad1fd53ef54d7f2dda45fb49b7915f1c3f559c | niazwazir/WAZIR_ESPCN1 | source/utils.py | [
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""" Print configuration dictionary to console
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94ad1fd53ef54d7f2dda45fb49b7915f1c3f559c | niazwazir/WAZIR_ESPCN1 | source/utils.py | [
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] | Python | visualize_filters | null | def visualize_filters(dict_vis):
""" Visualize and save filters of all the convolutional layers
Plot filters of the conv layers using matplotlib. Weights are loaded, after which the function extracts the weights to 'model_weights'. Filters visuals are plotted for each layer and saved in data/visualize_filters.... | Visualize and save filters of all the convolutional layers
Plot filters of the conv layers using matplotlib. Weights are loaded, after which the function extracts the weights to 'model_weights'. Filters visuals are plotted for each layer and saved in data/visualize_filters. Command line arg is (-f, --filter-vis).... | Visualize and save filters of all the convolutional layers
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scale= dict_vis['scale']
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94ad1fd53ef54d7f2dda45fb49b7915f1c3f559c | niazwazir/WAZIR_ESPCN1 | source/utils.py | [
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] | Python | is_image_file | <not_specific> | def is_image_file(filename):
""" Check if file is an image
:param filename: file name string
:return: Boolean toggle
"""
return any(filename.endswith(extension) for extension in ['.bmp', '.png', '.jpg', '.jpeg', '.JPG', '.JPEG', '.PNG']) | Check if file is an image
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94ad1fd53ef54d7f2dda45fb49b7915f1c3f559c | niazwazir/WAZIR_ESPCN1 | source/utils.py | [
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] | Python | is_video_file | <not_specific> | def is_video_file(filename):
""" Check if file is a video
:param filename: file name string
:return: Boolean toggle
"""
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94ad1fd53ef54d7f2dda45fb49b7915f1c3f559c | niazwazir/WAZIR_ESPCN1 | source/utils.py | [
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] | Python | convert_rgb_to_y | <not_specific> | def convert_rgb_to_y(img, dim_order='hwc'):
""" Get Y(CbCr) value from RGB image (standard conversion)
:param img: input image array in RGB form
:return: array of Y values
"""
if dim_order == 'hwc':
return 16. + (64.738 * img[..., 0] + 129.057 * img[..., 1] + 25.064 * img[..., 2]) / 256.
... | Get Y(CbCr) value from RGB image (standard conversion)
:param img: input image array in RGB form
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return 16. + (64.738 * img[..., 0] + 129.057 * img[..., 1] + 25.064 * img[..., 2]) / 256.
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94ad1fd53ef54d7f2dda45fb49b7915f1c3f559c | niazwazir/WAZIR_ESPCN1 | source/utils.py | [
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] | Python | convert_rgb_to_ycbcr | <not_specific> | def convert_rgb_to_ycbcr(img, dim_order='hwc'):
""" Convert to YCbCr from RGB (standard conversion)
:param img: input image array in RGB form
:return: out image array in YCbCr form
"""
if dim_order == 'hwc':
y = 16. + (64.738 * img[..., 0] + 129.057 * img[..., 1] + 25.064 * img[..., 2]) /... | Convert to YCbCr from RGB (standard conversion)
:param img: input image array in RGB form
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cb = 128. + (-37.945 * img[..., 0] - 74.494 * img[..., 1] + 112.439 * img[..., 2]) / 256.
cr = 128. + (112.439 * img[..., 0] - 94.154 ... | [
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94ad1fd53ef54d7f2dda45fb49b7915f1c3f559c | niazwazir/WAZIR_ESPCN1 | source/utils.py | [
"MIT"
] | Python | convert_ycbcr_to_rgb | <not_specific> | def convert_ycbcr_to_rgb(img, dim_order='hwc'):
""" Convert to RGB from YCbCr (standard conversion)
:param img: input image array in YCbCr form
:return: out image array in RGB form
"""
if dim_order == 'hwc':
r = 298.082 * img[..., 0] / 256. + 408.583 * img[..., 2] / 256. - 222.921
... | Convert to RGB from YCbCr (standard conversion)
:param img: input image array in YCbCr form
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g = 298.082 * img[..., 0] / 256. - 100.291 * img[..., 1] / 256. - 208.120 * img[..., 2] / 256. + 135.576
b = 298.082 * img[..., 0] / 256. + 516.412... | [
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54aad5b0cc56d922848d44fd25423760969646ba | niazwazir/WAZIR_ESPCN1 | source/test_video.py | [
"MIT"
] | Python | testing_video | null | def testing_video(dict_video, batch_mode, psnr_plot):
""" Process video(s) through ESPCN
This function processes a video (file mode), or videos (batch mode) through ESPCN. Videos are processed frame by frame. These are first downscaled to lower resolution images. These are upscaled and saved using both (a) Bic... | Process video(s) through ESPCN
This function processes a video (file mode), or videos (batch mode) through ESPCN. Videos are processed frame by frame. These are first downscaled to lower resolution images. These are upscaled and saved using both (a) Bicubic interpolation and (b) ESPCN. The former is used for comp... | Process video(s) through ESPCN
This function processes a video (file mode), or videos (batch mode) through ESPCN. Videos are processed frame by frame. These are first downscaled to lower resolution images. These are upscaled and saved using both (a) Bicubic interpolation and (b) ESPCN. The former is used for comparison... | [
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video_dir= dict_video['video dir']
video_file= dict_video['video file'] if not batch_mode else None
cudnn.benchmark = True
device = torch.device('cpu')
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54937f14adbb4867ef81766e780ffcd1f7356edb | niazwazir/WAZIR_ESPCN1 | source/train.py | [
"MIT"
] | Python | training | null | def training(dict_train):
""" Train the model
Trains the model using training and eval datasets. Output directory contains all weights marked by epoch number. The weights corresponding to the smallest lost value are saved as 'best.pth'. The script displays a progressbar and psnr values for each epoch as its ru... | Train the model
Trains the model using training and eval datasets. Output directory contains all weights marked by epoch number. The weights corresponding to the smallest lost value are saved as 'best.pth'. The script displays a progressbar and psnr values for each epoch as its running.
:param dict_train: di... | Train the model
Trains the model using training and eval datasets. Output directory contains all weights marked by epoch number. The weights corresponding to the smallest lost value are saved as 'best.pth'. The script displays a progressbar and psnr values for each epoch as its running. | [
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scale= dict_train['scale']
lr= float(dict_train['lr'])
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
"MIT"
] | Python | valid_gameweek | <not_specific> | def valid_gameweek(gameweek):
"""Returns True if the gameweek is valid.
:param gameweek: The gameweek.
:type gameweek: int or string
:raises ValueError: if gameweek is not a number between 1 and 38
"""
gameweek = int(gameweek)
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:param gameweek: The gameweek.
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gameweek = int(gameweek)
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raise ValueError(f"Gameweek must be a number between {MIN_GAMEWEEK} and {MAX_GAMEWEEK}.")
return True | [
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
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] | Python | _ids_to_lineup | <not_specific> | def _ids_to_lineup(player_ids, user_team):
"""Helper for converting list of player IDs to usable lineup.
:param player_ids: List of player IDS.
:type player_ids: list
:param user_team: The user's current team.
:type user_team: list
:return: A usable lineup.
:rtype: list
"""
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:param player_ids: List of player IDS.
:type player_ids: list
:param user_team: The user's current team.
:type user_team: list
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
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"""Helper for converting a player's ID to their respective element type:
1, 2, 3 or 4.
:param player_id: A player's ID.
:type player_id: int
:param players: List of all players in the Fantasy Premier League.
:type players: list
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
"MIT"
] | Python | _set_element_type | null | def _set_element_type(lineup, players):
"""Helper for setting the players' element types.
:param lineup: The user's current lineup.
:type lineup: list
:param players: List of all players in the Fantasy Premier League.
:type players: list
"""
for player in lineup:
element_type = _id_... | Helper for setting the players' element types.
:param lineup: The user's current lineup.
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:param players: List of all players in the Fantasy Premier League.
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element_type = _id_to_element_type(player["element"], players)
player["element_type"] = element_type | [
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
"MIT"
] | Python | _set_captain | null | def _set_captain(lineup, captain, captain_type, player_ids):
"""Sets the given captain's captain_type to True.
:param lineup: List of players.
:type lineup: list
:param captain: ID of the captain.
:type captain: int or str
:param captain_type: The captain type: 'is_captain' or 'is_vice_captain'... | Sets the given captain's captain_type to True.
:param lineup: List of players.
:type lineup: list
:param captain: ID of the captain.
:type captain: int or str
:param captain_type: The captain type: 'is_captain' or 'is_vice_captain'.
:type captain_type: string
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if captain and captain not in player_ids:
raise ValueError(
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current_captain = next(player for player in lineup if player[captain_type])
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
"MIT"
] | Python | _get_transfer_payload | <not_specific> | def _get_transfer_payload(
self, players_out, players_in, user_team, players, wildcard,
free_hit):
"""Returns the payload needed to make the desired transfers."""
event = 0
if (self.current_event):
event = self.current_event
payload = {
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free_hit):
event = 0
if (self.current_event):
event = self.current_event
payload = {
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
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] | Python | transfer | <not_specific> | async def transfer(self, players_out, players_in, max_hit=60,
wildcard=False, free_hit=False):
"""Transfers given players out and transfers given players in.
:param players_out: List of IDs of players who will be transferred out.
:type players_out: list
:param pla... | Transfers given players out and transfers given players in.
:param players_out: List of IDs of players who will be transferred out.
:type players_out: list
:param players_in: List of IDs of players who will be transferred in.
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wildcard=False, free_hit=False):
if wildcard and free_hit:
raise Exception("Can only use 1 of wildcard and free hit.")
if not logged_in(self._session):
raise Exception("User must be logged in.")
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
"MIT"
] | Python | _create_new_lineup | <not_specific> | async def _create_new_lineup(self, players_in, players_out, lineup):
"""Helper for creating the new lineup of players.
:param players_in: List of IDs of players who will be substituted in.
:type players_in: list
:param players_out: List of IDs of players who will be substituted out.
... | Helper for creating the new lineup of players.
:param players_in: List of IDs of players who will be substituted in.
:type players_in: list
:param players_out: List of IDs of players who will be substituted out.
:type players_out: list
:param lineup: List containing the user's c... | Helper for creating the new lineup of players. | [
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players = await fetch(self._session, API_URLS["static"])
players = players["elements"]
_set_element_type(lineup, players)
subs_in = _ids_to_lineup(players_in, lineup)
subs_out = _ids_to_lineup(players_out, lineu... | [
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
"MIT"
] | Python | _post_substitutions | null | async def _post_substitutions(self, lineup):
"""Helper for sending the POST requests with the new lineup.
:param lineup: The new lineup.
:type lineup: list
"""
# Get CSRF token and create payload + headers
payload = json.dumps({"chip": None, "picks": lineup})
hea... | Helper for sending the POST requests with the new lineup.
:param lineup: The new lineup.
:type lineup: list
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payload = json.dumps({"chip": None, "picks": lineup})
headers = get_headers("https://fantasy.premierleague.com/a/team/my")
await post(
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
"MIT"
] | Python | _captain_helper | null | async def _captain_helper(self, captain, captain_type):
"""Helper for setting the (vice) captain of the user's team."""
if not logged_in(self._session):
raise Exception("User must be logged in.")
user_team = await self.get_team()
team_ids = [player["element"] for player in u... | Helper for setting the (vice) captain of the user's team. | Helper for setting the (vice) captain of the user's team. | [
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
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] | Python | captain | null | async def captain(self, captain):
"""Set the captain of the user's team.
:param captain: ID of the captain.
:type captain: int
"""
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
"MIT"
] | Python | vice_captain | null | async def vice_captain(self, vice_captain):
"""Set the vice captain of the user's team.
:param vice_captain: ID of the vice captain.
:type vice_captain: int
"""
await self._captain_helper(vice_captain, is_vc) | Set the vice captain of the user's team.
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946ea1a54722767d8191a3ba4eb80633c8abad1a | ido222/fpl | fpl/models/user.py | [
"MIT"
] | Python | substitute | null | async def substitute(self, players_in, players_out, captain=None,
vice_captain=None):
"""Substitute players on the bench for players in the starting eleven.
Also allows the user to simultaneously set the new (vice) captain(s).
A maximum of 4 substitutes is set to force p... | Substitute players on the bench for players in the starting eleven.
Also allows the user to simultaneously set the new (vice) captain(s).
A maximum of 4 substitutes is set to force proper usage.
:param players_in: List of IDs of players who will be substituted in.
:type players_in: list... | Substitute players on the bench for players in the starting eleven.
Also allows the user to simultaneously set the new (vice) captain(s).
A maximum of 4 substitutes is set to force proper usage. | [
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if not logged_in(self._session):
raise Exception("User must be logged in.")
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b873af6c401fb8df3cc7ef8c9b3956891642e663 | ido222/fpl | fpl/fpl.py | [
"MIT"
] | Python | login | null | async def login(self, email=None, password=None):
"""Returns a requests session with FPL login authentication.
:param string email: Email address for the user's Fantasy Premier
League account.
:param string password: Password for the user's Fantasy Premier League
account... | Returns a requests session with FPL login authentication.
:param string email: Email address for the user's Fantasy Premier
League account.
:param string password: Password for the user's Fantasy Premier League
account.
| Returns a requests session with FPL login authentication. | [
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] | async def login(self, email=None, password=None):
if not email and not password:
email = os.getenv("FPL_EMAIL", None)
password = os.getenv("FPL_PASSWORD", None)
if not email or not password:
raise ValueError("Email and password must be set")
payload = {
... | [
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b873af6c401fb8df3cc7ef8c9b3956891642e663 | ido222/fpl | fpl/fpl.py | [
"MIT"
] | Python | FDR | <not_specific> | async def FDR(self):
"""Creates a new Fixture Difficulty Ranking (FDR) based on the number
of points each team gives up to players in the Fantasy Premier League.
These numbers are also between 1.0 and 5.0 to give a similar ranking
system to the official FDR.
An example:
... | Creates a new Fixture Difficulty Ranking (FDR) based on the number
of points each team gives up to players in the Fantasy Premier League.
These numbers are also between 1.0 and 5.0 to give a similar ranking
system to the official FDR.
An example:
.. code-block:: javascript
... | Creates a new Fixture Difficulty Ranking (FDR) based on the number
of points each team gives up to players in the Fantasy Premier League.
These numbers are also between 1.0 and 5.0 to give a similar ranking
system to the official FDR.
An example.
code-block:: javascript
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def average_points_against(points_against):
for team, positions in points_against.items():
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position["H"] = average(position["H"])
position["A"] = average(position["A"])
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b873af6c401fb8df3cc7ef8c9b3956891642e663 | ido222/fpl | fpl/fpl.py | [
"MIT"
] | Python | average_points_against | <not_specific> | def average_points_against(points_against):
"""Returns a dict with the average points scored against all teams,
per position and location.
:param dict points_against: A dict containing the points scored
against each team in the Premier League.
:rtype: dic... | Returns a dict with the average points scored against all teams,
per position and location.
:param dict points_against: A dict containing the points scored
against each team in the Premier League.
:rtype: dict
| Returns a dict with the average points scored against all teams,
per position and location. | [
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] | def average_points_against(points_against):
for team, positions in points_against.items():
for position in positions.values():
position["H"] = average(position["H"])
position["A"] = average(position["A"])
points_against[team] = position... | [
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b873af6c401fb8df3cc7ef8c9b3956891642e663 | ido222/fpl | fpl/fpl.py | [
"MIT"
] | Python | calculate_fdr | <not_specific> | def calculate_fdr(average_points, extrema):
"""Returns a dict containing the FDR for each team, which is
calculated by scaling the average points conceded per position
between 1.0 and 5.0 using the given extrema.
:param dict points_against: A dict containing the points s... | Returns a dict containing the FDR for each team, which is
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:param dict points_against: A dict containing the points scored
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for position, locations in positions.items():
min_h, max_h = extrema[position]["H"]
min_a, max_a = extrema[position]["A"]
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5a5822084f5070af0705b91923d95d7c243837f0 | karaposu/dlcourse_ai | assignments/assignment1/knn.py | [
"MIT"
] | Python | compute_distances_two_loops | <not_specific> | def compute_distances_two_loops(self, X):
'''
Computes L1 distance from every sample of X to every training sample
Uses simplest implementation with 2 Python loops
Arguments:
X, np array (num_test_samples, num_features) - samples to run
Returns:
dists, n... |
Computes L1 distance from every sample of X to every training sample
Uses simplest implementation with 2 Python loops
Arguments:
X, np array (num_test_samples, num_features) - samples to run
Returns:
dists, np array (num_test_samples, num_train_samples) - array... | Computes L1 distance from every sample of X to every training sample
Uses simplest implementation with 2 Python loops
X, np array (num_test_samples, num_features) - samples to run
dists, np array (num_test_samples, num_train_samples) - array
with distances between each test and each train sample | [
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num_train = self.train_X.shape[0]
num_test = X.shape[0]
dists = np.zeros((num_test, num_train), np.float32)
for i_test in range(num_test):
for i_train in range(num_train):
dists[i_test,i_train]=np.sum(np.abs([ X[i_test... | [
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5a5822084f5070af0705b91923d95d7c243837f0 | karaposu/dlcourse_ai | assignments/assignment1/knn.py | [
"MIT"
] | Python | compute_distances_one_loop | <not_specific> | def compute_distances_one_loop(self, X):
'''
Computes L1 distance from every sample of X to every training sample
Vectorizes some of the calculations, so only 1 loop is used
Arguments:
X, np array (num_test_samples, num_features) - samples to run
Returns:
... |
Computes L1 distance from every sample of X to every training sample
Vectorizes some of the calculations, so only 1 loop is used
Arguments:
X, np array (num_test_samples, num_features) - samples to run
Returns:
dists, np array (num_test_samples, num_train_sampl... | Computes L1 distance from every sample of X to every training sample
Vectorizes some of the calculations, so only 1 loop is used
X, np array (num_test_samples, num_features) - samples to run
dists, np array (num_test_samples, num_train_samples) - array
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num_train = self.train_X.shape[0]
num_test = X.shape[0]
dists = np.zeros((num_test, num_train), np.float32)
for i_test in range(num_test):
distance = np.abs(X[i_test] - self.train_X)
distance = distance.sum(axis=1).reshape(... | [
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5a5822084f5070af0705b91923d95d7c243837f0 | karaposu/dlcourse_ai | assignments/assignment1/knn.py | [
"MIT"
] | Python | compute_distances_no_loops | <not_specific> | def compute_distances_no_loops(self, X):
'''
Computes L1 distance from every sample of X to every training sample
Fully vectorizes the calculations using numpy
Arguments:
X, np array (num_test_samples, num_features) - samples to run
Returns:
dists, np ar... |
Computes L1 distance from every sample of X to every training sample
Fully vectorizes the calculations using numpy
Arguments:
X, np array (num_test_samples, num_features) - samples to run
Returns:
dists, np array (num_test_samples, num_train_samples) - array
... | Computes L1 distance from every sample of X to every training sample
Fully vectorizes the calculations using numpy
X, np array (num_test_samples, num_features) - samples to run
dists, np array (num_test_samples, num_train_samples) - array
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num_train = self.train_X.shape[0]
num_test = X.shape[0]
print("train_X.shape:",self.train_X.shape)
Using float32 to to save memory - the default is float64
dists = np.zeros((num_test, num_train), np.float32)
TODO: Implement comp... | [
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5a5822084f5070af0705b91923d95d7c243837f0 | karaposu/dlcourse_ai | assignments/assignment1/knn.py | [
"MIT"
] | Python | predict_labels_binary | <not_specific> | def predict_labels_binary(self, dists):
'''
Returns model predictions for binary classification case
Arguments:
dists, np array (num_test_samples, num_train_samples) - array
with distances between each test and each train sample
Returns:
pred, np arra... |
Returns model predictions for binary classification case
Arguments:
dists, np array (num_test_samples, num_train_samples) - array
with distances between each test and each train sample
Returns:
pred, np array of bool (num_test_samples) - binary predictions
... | Returns model predictions for binary classification case
Arguments:
dists, np array (num_test_samples, num_train_samples) - array
with distances between each test and each train sample
pred, np array of bool (num_test_samples) - binary predictions
for every test sample | [
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num_test = dists.shape[0]
pred = np.zeros(num_test, np.bool)
for i in range(num_test):
indexes_of_k_smallest_values= np.argpartition(dists[i], self.k)[:self.k]
filter_indices = indexes_of_k_smallest_values
axis = 0
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5a5822084f5070af0705b91923d95d7c243837f0 | karaposu/dlcourse_ai | assignments/assignment1/knn.py | [
"MIT"
] | Python | predict_labels_multiclass | <not_specific> | def predict_labels_multiclass(self, dists):
'''
Returns model predictions for multi-class classification case
Arguments:
dists, np array (num_test_samples, num_train_samples) - array
with distances between each test and each train sample
Returns:
pred... |
Returns model predictions for multi-class classification case
Arguments:
dists, np array (num_test_samples, num_train_samples) - array
with distances between each test and each train sample
Returns:
pred, np array of int (num_test_samples) - predicted class ... | Returns model predictions for multi-class classification case
Arguments:
dists, np array (num_test_samples, num_train_samples) - array
with distances between each test and each train sample
pred, np array of int (num_test_samples) - predicted class index
for every test sample | [
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num_test = dists.shape[0]
num_test = dists.shape[0]
pred = np.zeros(num_test, np.int)
for i in range(num_test):
indexes_of_k_smallest_values = np.argpartition(dists[i], self.k)[:self.k]
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34ec6584dbe37b9e9fa39003d265ae473fd0a4e8 | karaposu/dlcourse_ai | assignments/assignment1/metrics.py | [
"MIT"
] | Python | multiclass_accuracy | <not_specific> | def multiclass_accuracy(prediction, ground_truth):
'''
Computes metrics for multiclass classification
Arguments:
prediction, np array of int (num_samples) - model predictions
ground_truth, np array of int (num_samples) - true labels
Returns:
accuracy - ratio of accurate predictions to tota... |
Computes metrics for multiclass classification
Arguments:
prediction, np array of int (num_samples) - model predictions
ground_truth, np array of int (num_samples) - true labels
Returns:
accuracy - ratio of accurate predictions to total samples
| Computes metrics for multiclass classification
Arguments:
prediction, np array of int (num_samples) - model predictions
ground_truth, np array of int (num_samples) - true labels
ratio of accurate predictions to total samples | [
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accuracy = 0
nTruePositives = 0
nFalsePositives = 0
for i in range(len(prediction)):
if prediction[i] == ground_truth[i]:
nTruePositives = nTruePositives + 1
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nFalsePositives = nFalsePositives + 1
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9368e9c4103bf9d8869b9bd4ca782ac8a80aafb4 | Zxynine/fusion360-thomasa88lib | timeline.py | [
"MIT"
] | Python | flatten_timeline | <not_specific> | def flatten_timeline(timeline_collection):
'''
A flat timeline representation, with all objects except any group objects.
(Groups disappear when expanded - The icon is no longer there in the timeline.)
'''
flat_collection = []
for obj in timeline_collection:
if obj.isGroup:
... |
A flat timeline representation, with all objects except any group objects.
(Groups disappear when expanded - The icon is no longer there in the timeline.)
| A flat timeline representation, with all objects except any group objects.
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DEBUG | <not_specific> | def LF_DEBUG(c):
"""
This label function is for debugging purposes. Feel free to ignore.
keyword arguments:
c - The candidate object to be labeled
"""
print(c)
print()
print("Left Tokens")
print(list(get_left_tokens(c[0], window=5)))
print()
print("Right Tokens")
print(li... |
This label function is for debugging purposes. Feel free to ignore.
keyword arguments:
c - The candidate object to be labeled
| This label function is for debugging purposes. Feel free to ignore.
keyword arguments:
c - The candidate object to be labeled | [
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_HETNET_DISEASES | <not_specific> | def LF_HETNET_DISEASES(c):
"""
This label function returns 1 if the given Disease Gene pair is
located in the Diseases database
"""
return 1 if (c.Gene_cid, c.Disease_cid, "DISEASES") in knowledge_base else 0 |
This label function returns 1 if the given Disease Gene pair is
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_HETNET_DOAF | <not_specific> | def LF_HETNET_DOAF(c):
"""
This label function returns 1 if the given Disease Gene pair is
located in the DOAF database
"""
return 1 if (c.Gene_cid, c.Disease_cid, "DOAF") in knowledge_base else 0 |
This label function returns 1 if the given Disease Gene pair is
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_HETNET_DisGeNET | <not_specific> | def LF_HETNET_DisGeNET(c):
"""
This label function returns 1 if the given Disease Gene pair is
located in the DisGeNET database
"""
return 1 if (c.Gene_cid, c.Disease_cid, "DisGeNET") in knowledge_base else 0 |
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_HETNET_GWAS | <not_specific> | def LF_HETNET_GWAS(c):
"""
This label function returns 1 if the given Disease Gene pair is
located in the GWAS database
"""
return 1 if (c.Gene_cid, c.Disease_cid, "GWAS Catalog") in knowledge_base else 0 |
This label function returns 1 if the given Disease Gene pair is
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_HETNET_DaG_ABSENT | <not_specific> | def LF_HETNET_DaG_ABSENT(c):
"""
This label function fires -1 if the given Disease Gene pair does not appear
in the databases above.
"""
return 0 if any([
LF_HETNET_DISEASES(c),
LF_HETNET_DOAF(c),
LF_HETNET_DisGeNET(c),
LF_HETNET_GWAS(c)
]) else -1 |
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return 0 if any([
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_HETNET_DuG_ABSENT | <not_specific> | def LF_HETNET_DuG_ABSENT(c):
"""
This label function fires -1 if the given Disease Gene pair does not appear
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"""
return 0 if LF_HETNET_STARGEO_UP(c) else -1 |
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_HETNET_DdG_ABSENT | <not_specific> | def LF_HETNET_DdG_ABSENT(c):
"""
This label function fires -1 if the given Disease Gene pair does not appear
in the databases above.
"""
return 0 if LF_HETNET_STARGEO_DOWN(c) else -1 |
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_DG_CHECK_GENE_TAG | <not_specific> | def LF_DG_CHECK_GENE_TAG(c):
"""
This label function is used for labeling each passed candidate as either pos or neg.
Keyword Args:
c- the candidate object to be passed in.
"""
sen = c[1].get_parent()
gene_name = re.sub("\)", "", c[1].get_span().lower())
gene_id = sen.entity_cids[c[1].ge... |
This label function is used for labeling each passed candidate as either pos or neg.
Keyword Args:
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sen = c[1].get_parent()
gene_name = re.sub("\)", "", c[1].get_span().lower())
gene_id = sen.entity_cids[c[1].get_word_start()]
gene_entry_df = gene_desc.query("GeneID == @gene_id")
if gene_entry_df.empty:
return -1
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_CHECK_DISEASE_TAG | <not_specific> | def LF_DG_CHECK_DISEASE_TAG(c):
"""
This label function is used for labeling each passed candidate as either pos or neg.
Keyword Args:
c- the candidate object to be passed in.
"""
sen = c[0].get_parent()
disease_name = re.sub("\) ?", "", c[0].get_span())
disease_name = re.sub(r"(\w)-(\w)... |
This label function is used for labeling each passed candidate as either pos or neg.
Keyword Args:
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disease_name = re.sub("\) ?", "", c[0].get_span())
disease_name = re.sub(r"(\w)-(\w)", r"\g<1> \g<2>", disease_name)
disease_name = " ".join([word for word in word_tokenize(disease_name) if word not in set(stop_word_list)])
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_IS_BIOMARKER | <not_specific> | def LF_DG_IS_BIOMARKER(c):
"""
This label function examines a sentences to determine of a sentence
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c - The candidate obejct being passed in
"""
if LF_DG_METHOD_DESC(c) or LF_DG_TITLE(c):
return 0
elif re.search(l... |
This label function examines a sentences to determine of a sentence
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c - The candidate obejct being passed in
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DaG_ASSOCIATION | <not_specific> | def LF_DaG_ASSOCIATION(c):
"""
This LF is designed to test if there is a key phrase that suggests
a d-g pair is an association.
"""
left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_tokens(c[0], window=10)) + "... |
This LF is designed to test if there is a key phrase that suggests
a d-g pair is an association.
| This LF is designed to test if there is a key phrase that suggests
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left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_tokens(c[0], window=10)) + " ".join(get_right_tokens(c[1], window=10))
found_negation = not re.search(r'\b(not|no)\b', left_window, flags=re.I)
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DaG_WEAK_ASSOCIATION | <not_specific> | def LF_DaG_WEAK_ASSOCIATION(c):
"""
This label function is design to search for phrases that indicate a
weak association between the disease and gene
"""
left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_token... |
This label function is design to search for phrases that indicate a
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left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_tokens(c[0], window=10)) + " ".join(get_right_tokens(c[1], window=10))
if LF_DG_METHOD_DESC(c) or LF_DG_TITLE(c):
return 0
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_DaG_NO_ASSOCIATION | <not_specific> | def LF_DaG_NO_ASSOCIATION(c):
"""
This LF is designed to test if there is a key phrase that suggests
a d-g pair is no an association.
"""
left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_tokens(c[0], window=10... |
This LF is designed to test if there is a key phrase that suggests
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] | def LF_DaG_NO_ASSOCIATION(c):
left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_tokens(c[0], window=10)) + " ".join(get_right_tokens(c[1], window=10))
if LF_DG_METHOD_DESC(c) or LF_DG_TITLE(c):
return 0
elif re... | [
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DaG_CELLULAR_ACTIVITY | <not_specific> | def LF_DaG_CELLULAR_ACTIVITY(c):
"""
This LF is designed to look for key phrases that indicate activity within a cell.
e.x. positive immunostating for an experiment
"""
left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(g... |
This LF is designed to look for key phrases that indicate activity within a cell.
e.x. positive immunostating for an experiment
| This LF is designed to look for key phrases that indicate activity within a cell. | [
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] | def LF_DaG_CELLULAR_ACTIVITY(c):
left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_tokens(c[0], window=10)) + " ".join(get_right_tokens(c[1], window=10))
if re.search(ltp(cellular_activity), get_tagged_text(c), flags=re.I)... | [
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} |
983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DaG_DISEASE_SAMPLE | <not_specific> | def LF_DaG_DISEASE_SAMPLE(c):
"""
This LF is designed to look for key phrases that indicate a sentence talking about tissue samples
ex. cell line etc
"""
left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_tokens... |
This LF is designed to look for key phrases that indicate a sentence talking about tissue samples
ex. cell line etc
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] | def LF_DaG_DISEASE_SAMPLE(c):
left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_tokens(c[0], window=10)) + " ".join(get_right_tokens(c[1], window=10))
if re.search(ltp(disease_sample_indicators), left_window, flags=re.I):
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_METHOD_DESC | <not_specific> | def LF_DG_METHOD_DESC(c):
"""
This label function is designed to look for phrases
that imply a sentence is description an experimental design
"""
sentence_tokens = " ".join(c.get_parent().words[0:20])
if re.search(ltp(method_indication), sentence_tokens, flags=re.I):
return -1
elif ... |
This label function is designed to look for phrases
that imply a sentence is description an experimental design
| This label function is designed to look for phrases
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] | def LF_DG_METHOD_DESC(c):
sentence_tokens = " ".join(c.get_parent().words[0:20])
if re.search(ltp(method_indication), sentence_tokens, flags=re.I):
return -1
elif re.search(ltp(method_indication), " ".join(get_between_tokens(c)), flags=re.I):
return -1
else:
return 0 | [
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_TITLE | <not_specific> | def LF_DG_TITLE(c):
"""
This label function is designed to look for phrases that inditcates
a paper title
"""
if re.search(r'^(\[|\[ )?'+ltp(title_indication), get_tagged_text(c), flags=re.I):
return -1
elif re.search(ltp(title_indication)+r'$', get_tagged_text(c), flags=re.I):
r... |
This label function is designed to look for phrases that inditcates
a paper title
| This label function is designed to look for phrases that inditcates
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] | def LF_DG_TITLE(c):
if re.search(r'^(\[|\[ )?'+ltp(title_indication), get_tagged_text(c), flags=re.I):
return -1
elif re.search(ltp(title_indication)+r'$', get_tagged_text(c), flags=re.I):
return -1
elif "(author's transl)" in get_tagged_text(c):
return -1
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} |
983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DuG_UPREGULATES | <not_specific> | def LF_DuG_UPREGULATES(c):
"""
This label function is designed to search for words that indicate
a sort of positive response or imply an upregulates association
"""
if LF_DG_METHOD_DESC(c) or LF_DG_TITLE(c):
return 0
else:
if rule_regex_search_btw_AB(c, r'.*'+ltp(upregulates)+r'.... |
This label function is designed to search for words that indicate
a sort of positive response or imply an upregulates association
| This label function is designed to search for words that indicate
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] | def LF_DuG_UPREGULATES(c):
if LF_DG_METHOD_DESC(c) or LF_DG_TITLE(c):
return 0
else:
if rule_regex_search_btw_AB(c, r'.*'+ltp(upregulates)+r'.*', 1):
return 1
elif rule_regex_search_btw_BA(c, r'.*'+ltp(upregulates)+r'.*', 1):
return 1
elif re.search(r'({{A... | [
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DdG_DOWNREGULATES | <not_specific> | def LF_DdG_DOWNREGULATES(c):
"""
This label function is designed to search for words that indicate
a sort of negative response or imply an downregulates association
"""
if LF_DG_METHOD_DESC(c) or LF_DG_TITLE(c):
return 0
else:
if rule_regex_search_btw_AB(c, r'.*'+ltp(downregulate... |
This label function is designed to search for words that indicate
a sort of negative response or imply an downregulates association
| This label function is designed to search for words that indicate
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] | def LF_DdG_DOWNREGULATES(c):
if LF_DG_METHOD_DESC(c) or LF_DG_TITLE(c):
return 0
else:
if rule_regex_search_btw_AB(c, r'.*'+ltp(downregulates)+r'.*', 1):
return 1
elif rule_regex_search_btw_BA(c, r'.*'+ltp(downregulates)+r'.*', 1):
return 1
elif re.search(... | [
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_GENETIC_ABNORMALITIES | <not_specific> | def LF_DG_GENETIC_ABNORMALITIES(c):
"""
This LF searches for key phraes that indicate a genetic abnormality
"""
left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_tokens(c[0], window=10)) + " ".join(get_right_tokens... |
This LF searches for key phraes that indicate a genetic abnormality
| This LF searches for key phraes that indicate a genetic abnormality | [
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] | def LF_DG_GENETIC_ABNORMALITIES(c):
left_window = " ".join(get_left_tokens(c[0], window=10)) + " ".join(get_left_tokens(c[1], window=10))
right_window = " ".join(get_right_tokens(c[0], window=10)) + " ".join(get_right_tokens(c[1], window=10))
if re.search(ltp(genetic_abnormalities), get_text_between(c), fla... | [
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],
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} |
983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_DIAGNOSIS | <not_specific> | def LF_DG_DIAGNOSIS(c):
"""
This label function is designed to search for words that imply a patient diagnosis
which will provide evidence for possible disease gene association.
"""
return 1 if any([rule_regex_search_btw_AB(c, r'.*'+ltp(diagnosis_indicators) + r".*", 1), rule_regex_search_btw_BA(c, ... |
This label function is designed to search for words that imply a patient diagnosis
which will provide evidence for possible disease gene association.
| This label function is designed to search for words that imply a patient diagnosis
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] | def LF_DG_DIAGNOSIS(c):
return 1 if any([rule_regex_search_btw_AB(c, r'.*'+ltp(diagnosis_indicators) + r".*", 1), rule_regex_search_btw_BA(c, r'.*'+ltp(diagnosis_indicators) + r".*", 1)]) or \
re.search(r'({{A}}|{{B}}).*({{A}}|{{B}}).*' + ltp(diagnosis_indicators), get_tagged_text(c)) else 0 | [
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_PATIENT_WITH | <not_specific> | def LF_DG_PATIENT_WITH(c):
"""
This label function looks for the phrase " with" disease.
"""
return 1 if re.search(r"patient(s)? with.{1,200}{{A}}", get_tagged_text(c), flags=re.I) else 0 |
This label function looks for the phrase " with" disease.
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return 1 if re.search(r"patient(s)? with.{1,200}{{A}}", get_tagged_text(c), flags=re.I) else 0 | [
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_CONCLUSION_TITLE | <not_specific> | def LF_DG_CONCLUSION_TITLE(c):
""""
This label function searches for the word conclusion at the beginning of the sentence.
Some abstracts are written in this format.
"""
return 1 if "CONCLUSION:" in get_tagged_text(c) or "concluded" in get_tagged_text(c) else 0 |
This label function searches for the word conclusion at the beginning of the sentence.
Some abstracts are written in this format.
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DaG_NO_CONCLUSION | <not_specific> | def LF_DaG_NO_CONCLUSION(c):
"""
This label function fires a -1 if the number of negative label functinos is greater than the number
of positive label functions.
The main idea behind this label function is add support to sentences that could
mention a possible disease gene association.
"""
p... |
This label function fires a -1 if the number of negative label functinos is greater than the number
of positive label functions.
The main idea behind this label function is add support to sentences that could
mention a possible disease gene association.
| This label function fires a -1 if the number of negative label functinos is greater than the number
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The main idea behind this label function is add support to sentences that could
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positive_num = np.sum([
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LF_DaG_CELLULAR_ACTIVITY(c),
np.abs(LF_DaG_WEAK_ASSOCIATION(c)), np.abs(LF_DaG_NO_ASSOCIATION(c))
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negative_num = np.abs(np.sum([
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DaG_CONCLUSION | <not_specific> | def LF_DaG_CONCLUSION(c):
"""
This label function fires a 1 if the number of positive label functions is greater than the number
of negative label functions.
The main idea behind this label function is add support to sentences that could
mention a possible disease gene association
"""
if LF_... |
This label function fires a 1 if the number of positive label functions is greater than the number
of negative label functions.
The main idea behind this label function is add support to sentences that could
mention a possible disease gene association
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The main idea behind this label function is add support to sentences that could
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_DuG_NO_CONCLUSION | <not_specific> | def LF_DuG_NO_CONCLUSION(c):
"""
This label function fires a -1 if the number of negative label functinos is greater than the number
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The main idea behind this label function is add support to sentences that could
mention a possible disease gene association.
"""
p... |
This label function fires a -1 if the number of negative label functinos is greater than the number
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The main idea behind this label function is add support to sentences that could
mention a possible disease gene association.
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positive_num = np.sum([
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negative_num = np.abs(np.sum(LF_DG_METHOD_DESC(c), LF_DG_TITLE(c)))
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_DuG_CONCLUSION | <not_specific> | def LF_DuG_CONCLUSION(c):
"""
This label function fires a 1 if the number of positive label functions is greater than the number
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The main idea behind this label function is add support to sentences that could
mention a possible disease gene association
"""
if not... |
This label function fires a 1 if the number of positive label functions is greater than the number
of negative label functions.
The main idea behind this label function is add support to sentences that could
mention a possible disease gene association
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_DdG_NO_CONCLUSION | <not_specific> | def LF_DdG_NO_CONCLUSION(c):
"""
This label function fires a -1 if the number of negative label functinos is greater than the number
of positive label functions.
The main idea behind this label function is add support to sentences that could
mention a possible disease gene association.
"""
p... |
This label function fires a -1 if the number of negative label functinos is greater than the number
of positive label functions.
The main idea behind this label function is add support to sentences that could
mention a possible disease gene association.
| This label function fires a -1 if the number of negative label functinos is greater than the number
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positive_num = np.sum([
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_DdG_CONCLUSION | <not_specific> | def LF_DdG_CONCLUSION(c):
"""
This label function fires a 1 if the number of positive label functions is greater than the number
of negative label functions.
The main idea behind this label function is add support to sentences that could
mention a possible disease gene association
"""
if not... |
This label function fires a 1 if the number of positive label functions is greater than the number
of negative label functions.
The main idea behind this label function is add support to sentences that could
mention a possible disease gene association
| This label function fires a 1 if the number of positive label functions is greater than the number
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_DG_DISTANCE_SHORT | <not_specific> | def LF_DG_DISTANCE_SHORT(c):
"""
This LF is designed to make sure that the disease mention
and the gene mention aren't right next to each other.
"""
return -1 if len(list(get_between_tokens(c))) <= 2 else 0 |
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| This LF is designed to make sure that the disease mention
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_DG_DISTANCE_LONG | <not_specific> | def LF_DG_DISTANCE_LONG(c):
"""
This LF is designed to make sure that the disease mention
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"""
return -1 if len(list(get_between_tokens(c))) > 50 else 0 |
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_DG_ALLOWED_DISTANCE | <not_specific> | def LF_DG_ALLOWED_DISTANCE(c):
"""
This LF is designed to make sure that the disease mention
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"""
return 0 if any([
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_DG_NO_VERB | <not_specific> | def LF_DG_NO_VERB(c):
"""
This label function is designed to fire if a given
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"""
if len([x for x in c.get_parent().pos_tags if "VB" in x and x != "VBG"]) == 0:
return -1
return 0 |
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_DG_BICLUSTER_CASUAL_MUTATIONS | <not_specific> | def LF_DG_BICLUSTER_CASUAL_MUTATIONS(c):
"""
This label function uses the bicluster data located in the
A global network of biomedical relationships
"""
sen_pos = c.get_parent().position
pubmed_id = int(c.get_parent().document.name)
if (pubmed_id, sen_pos) in causal_mutations_base:
... |
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] | def LF_DG_BICLUSTER_CASUAL_MUTATIONS(c):
sen_pos = c.get_parent().position
pubmed_id = int(c.get_parent().document.name)
if (pubmed_id, sen_pos) in causal_mutations_base:
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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] | Python | LF_DG_BICLUSTER_MUTATIONS | <not_specific> | def LF_DG_BICLUSTER_MUTATIONS(c):
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This label function uses the bicluster data located in the
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"""
sen_pos = c.get_parent().position
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_DG_BICLUSTER_DRUG_TARGETS | <not_specific> | def LF_DG_BICLUSTER_DRUG_TARGETS(c):
"""
This label function uses the bicluster data located in the
A global network of biomedical relationships
"""
sen_pos = c.get_parent().position
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sen_pos = c.get_parent().position
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_DG_BICLUSTER_PATHOGENESIS | <not_specific> | def LF_DG_BICLUSTER_PATHOGENESIS(c):
"""
This label function uses the bicluster data located in the
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"""
sen_pos = c.get_parent().position
pubmed_id = int(c.get_parent().document.name)
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sen_pos = c.get_parent().position
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_DG_BICLUSTER_THERAPEUTIC | <not_specific> | def LF_DG_BICLUSTER_THERAPEUTIC(c):
"""
This label function uses the bicluster data located in the
A global network of biomedical relationships
"""
sen_pos = c.get_parent().position
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] | def LF_DG_BICLUSTER_THERAPEUTIC(c):
sen_pos = c.get_parent().position
pubmed_id = int(c.get_parent().document.name)
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_DG_BICLUSTER_POLYMORPHISMS | <not_specific> | def LF_DG_BICLUSTER_POLYMORPHISMS(c):
"""
This label function uses the bicluster data located in the
A global network of biomedical relationships
"""
sen_pos = c.get_parent().position
pubmed_id = int(c.get_parent().document.name)
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] | def LF_DG_BICLUSTER_POLYMORPHISMS(c):
sen_pos = c.get_parent().position
pubmed_id = int(c.get_parent().document.name)
if (pubmed_id, sen_pos) in polymorphisms_base:
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_BICLUSTER_PROGRESSION | <not_specific> | def LF_DG_BICLUSTER_PROGRESSION(c):
"""
This label function uses the bicluster data located in the
A global network of biomedical relationships
"""
sen_pos = c.get_parent().position
pubmed_id = int(c.get_parent().document.name)
if (pubmed_id, sen_pos) in progression_base:
return 1
... |
This label function uses the bicluster data located in the
A global network of biomedical relationships
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] | def LF_DG_BICLUSTER_PROGRESSION(c):
sen_pos = c.get_parent().position
pubmed_id = int(c.get_parent().document.name)
if (pubmed_id, sen_pos) in progression_base:
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return 0 | [
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_DG_BICLUSTER_BIOMARKERS | <not_specific> | def LF_DG_BICLUSTER_BIOMARKERS(c):
"""
This label function uses the bicluster data located in the
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"""
sen_pos = c.get_parent().position
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... |
This label function uses the bicluster data located in the
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sen_pos = c.get_parent().position
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_DG_BICLUSTER_OVEREXPRESSION | <not_specific> | def LF_DG_BICLUSTER_OVEREXPRESSION(c):
"""
This label function uses the bicluster data located in the
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"""
sen_pos = c.get_parent().position
pubmed_id = int(c.get_parent().document.name)
if (pubmed_id, sen_pos) in overexpression_base:
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This label function uses the bicluster data located in the
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sen_pos = c.get_parent().position
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983b2e6f7f22e3acf81091870788b531f6c94e5d | ajlee21/snorkeling | disease_gene/disease_associates_gene/data/label_functions/disease_gene_lfs.py | [
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"BSD-3-Clause"
] | Python | LF_DG_BICLUSTER_REGULATION | <not_specific> | def LF_DG_BICLUSTER_REGULATION(c):
"""
This label function uses the bicluster data located in the
A global network of biomedical relationships
"""
sen_pos = c.get_parent().position
pubmed_id = int(c.get_parent().document.name)
if (pubmed_id, sen_pos) in regulation_base:
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... |
This label function uses the bicluster data located in the
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sen_pos = c.get_parent().position
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054d5b905ca3e260f967b37f358e343af8588544 | ajlee21/snorkeling | gene_gene/gene_interacts_gene/datafile/gene_gene_datafile_generator.py | [
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"BSD-3-Clause"
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0,1 - not in hetionet and... |
This function creates a parition rank for the current dataset.
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1,1 -in hetionet and has sentences
1,0 - in hetionet and doesn't have sentences
0,1 - not in hetionet and does have sentences
... | This function creates a parition rank for the current dataset.
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_HETNET_DG_ABSENT | <not_specific> | def LF_HETNET_DG_ABSENT(c):
"""
This label function fires -1 if the given Disease Gene pair does not appear
in the databases above.
"""
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_IS_BIOMARKER | <not_specific> | def LF_DG_IS_BIOMARKER(c):
"""
This label function examines a sentences to determine of a sentence
is talking about a biomarker. (A biomarker leads towards D-G assocation
c - The candidate obejct being passed in
"""
if re.search(ltp(biomarker_indicators) + r".*{{B}}", get_tagged_text(c), flags=r... |
This label function examines a sentences to determine of a sentence
is talking about a biomarker. (A biomarker leads towards D-G assocation
c - The candidate obejct being passed in
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if re.search(ltp(biomarker_indicators) + r".*{{B}}", get_tagged_text(c), flags=re.I):
return 1
elif re.search(r"{{B}}.*" + ltp(biomarker_indicators), get_tagged_text(c), flags=re.I):
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_ASSOCIATION | <not_specific> | def LF_DG_ASSOCIATION(c):
"""
This LF is designed to test if there is a key phrase that suggests
a d-g pair is an association.
"""
if re.search(r'(?<!not )(?<!no )' + ltp(direct_association), get_text_between(c), flags=re.I):
return 1
elif re.search(r'(?<!not )(?<!no )' + ltp(direct_asso... |
This LF is designed to test if there is a key phrase that suggests
a d-g pair is an association.
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elif re.search(r'(?<!not )(?<!no )' + ltp(direct_association) + r".*({{B}}|{{A}})", get_tagged_text(c), flags=re.I):
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_WEAK_ASSOCIATION | <not_specific> | def LF_DG_WEAK_ASSOCIATION(c):
"""
This label function is design to search for phrases that indicate a
weak association between the disease and gene
"""
if re.search(ltp(weak_association), get_text_between(c), flags=re.I):
return -1
elif re.search(ltp(weak_association) + r".*({{B}}|{{A}... |
This label function is design to search for phrases that indicate a
weak association between the disease and gene
| This label function is design to search for phrases that indicate a
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] | def LF_DG_WEAK_ASSOCIATION(c):
if re.search(ltp(weak_association), get_text_between(c), flags=re.I):
return -1
elif re.search(ltp(weak_association) + r".*({{B}}|{{A}})", get_tagged_text(c), flags=re.I):
return -1
elif re.search(r"({{B}}|{{A}}).*" + ltp(weak_association), get_tagged_text(c), ... | [
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_NO_ASSOCIATION | <not_specific> | def LF_DG_NO_ASSOCIATION(c):
"""
This LF is designed to test if there is a key phrase that suggests
a d-g pair is no an association.
"""
if re.search(ltp(no_direct_association), get_text_between(c), flags=re.I):
return -1
elif re.search(ltp(no_direct_association) + r".*({{B}}|{{A}})", ge... |
This LF is designed to test if there is a key phrase that suggests
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if re.search(ltp(no_direct_association), get_text_between(c), flags=re.I):
return -1
elif re.search(ltp(no_direct_association) + r".*({{B}}|{{A}})", get_tagged_text(c), flags=re.I):
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_METHOD_DESC | <not_specific> | def LF_DG_METHOD_DESC(c):
"""
This label function is designed to look for phrases
that imply a sentence is description an experimental design
"""
if re.search(ltp(method_indication), get_tagged_text(c), flags=re.I):
return -1
else:
return 0 |
This label function is designed to look for phrases
that imply a sentence is description an experimental design
| This label function is designed to look for phrases
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] | def LF_DG_METHOD_DESC(c):
if re.search(ltp(method_indication), get_tagged_text(c), flags=re.I):
return -1
else:
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_TITLE | <not_specific> | def LF_DG_TITLE(c):
"""
This label function is designed to look for phrases that inditcates
a paper title
"""
if re.search(r'^'+ltp(title_indication), get_tagged_text(c), flags=re.I):
return -1
elif re.search(ltp(title_indication)+r'$', get_tagged_text(c), flags=re.I):
return -1
... |
This label function is designed to look for phrases that inditcates
a paper title
| This label function is designed to look for phrases that inditcates
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] | def LF_DG_TITLE(c):
if re.search(r'^'+ltp(title_indication), get_tagged_text(c), flags=re.I):
return -1
elif re.search(ltp(title_indication)+r'$', get_tagged_text(c), flags=re.I):
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
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] | Python | LF_DG_POSITIVE_DIRECTION | <not_specific> | def LF_DG_POSITIVE_DIRECTION(c):
"""
This label function is designed to search for words that indicate
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"""
return 1 if any([rule_regex_search_btw_AB(c, r'.*'+ltp(positive_direction)+r'.*', 1), rule_regex_search_btw_BA(c, r'.*'+ltp(posit... |
This label function is designed to search for words that indicate
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] | def LF_DG_POSITIVE_DIRECTION(c):
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_NEGATIVE_DIRECTION | <not_specific> | def LF_DG_NEGATIVE_DIRECTION(c):
"""
This label function is designed to search for words that indicate
a sort of negative response or imply an downregulates association
"""
return 1 if any([rule_regex_search_btw_AB(c, r'.*'+ltp(negative_direction)+r'.*', 1), rule_regex_search_btw_BA(c, r'.*'+ltp(neg... |
This label function is designed to search for words that indicate
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] | def LF_DG_NEGATIVE_DIRECTION(c):
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_RISK | <not_specific> | def LF_DG_RISK(c):
"""
This label function searched for sentences that mention a patient being at risk for disease or
a signal implying increased/decreased risk of disease.
"""
return 1 if re.search(r"risk (of|for)", get_tagged_text(c), flags=re.I) else 0 |
This label function searched for sentences that mention a patient being at risk for disease or
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
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] | Python | LF_DG_PATIENT_WITH | <not_specific> | def LF_DG_PATIENT_WITH(c):
"""
This label function looks for the phrase "patients with" disease.
"""
return 1 if re.search(r"patient(s)? with {{A}}", get_tagged_text(c), flags=re.I) else 0 |
This label function looks for the phrase "patients with" disease.
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_PURPOSE | <not_specific> | def LF_DG_PURPOSE(c):
""""
This label function searches for the word purpose at the beginning of the sentence.
Some abstracts are written in this format.
"""
return -1 if "PURPOSE:" in get_tagged_text(c) else 0 |
This label function searches for the word purpose at the beginning of the sentence.
Some abstracts are written in this format.
| This label function searches for the word purpose at the beginning of the sentence.
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34ffd5b620f09d787deb594a055410486a7745d2 | ajlee21/snorkeling | playground/compound_disease/transfer_learning_experiment/data/label_functions/disease_gene_lf.py | [
"CC0-1.0",
"BSD-3-Clause"
] | Python | LF_DG_CONCLUSION_TITLE | <not_specific> | def LF_DG_CONCLUSION_TITLE(c):
""""
This label function searches for the word conclusion at the beginning of the sentence.
Some abstracts are written in this format.
"""
return 1 if "CONCLUSION" in get_tagged_text(c) or "concluded" in get_tagged_text(c) else 0 |
This label function searches for the word conclusion at the beginning of the sentence.
Some abstracts are written in this format.
| This label function searches for the word conclusion at the beginning of the sentence.
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"in",
"this",
"format",
"."
] | def LF_DG_CONCLUSION_TITLE(c):
return 1 if "CONCLUSION" in get_tagged_text(c) or "concluded" in get_tagged_text(c) else 0 | [
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"LF_DG_CONCLUSION_TITLE",
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"c",
")",
"or",
"\"concluded\"",
"in",
"get_tagged_text",
"(",
"c",
")",
"else",
"0"
] | This label function searches for the word conclusion at the beginning of the sentence. | [
"This",
"label",
"function",
"searches",
"for",
"the",
"word",
"conclusion",
"at",
"the",
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"of",
"the",
"sentence",
"."
] | [
"\"\"\"\"\n This label function searches for the word conclusion at the beginning of the sentence.\n Some abstracts are written in this format.\n \"\"\""
] | [
{
"param": "c",
"type": null
}
] | {
"returns": [],
"raises": [],
"params": [
{
"identifier": "c",
"type": null,
"docstring": null,
"docstring_tokens": [],
"default": null,
"is_optional": null
}
],
"outlier_params": [],
"others": []
} |
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