sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
a69c46af7df65abb8cf12a3171ac1bef8fecc791bfb8f085bb57aacb248ae7ab | Python | 2,933 | 60 | # GoPro should be connected via wifi
# make sure the 2.4ghz connection is selected and connect via the computer's wifi
# need to cite this github repo https://github.com/KonradIT/gopro-py-api
from goprocam import GoProCamera, constants # imports GoPro capabilities
gpCam = GoProCamera.GoPro() # defines gpCam as variabl... |
56294e3264d0a04d43530a40f13f7189027c003f8e231ca317087b53533824d3 | Python | 2,934 | 104 | # %%
'''
Want to find how long occured between MRI and behavioural session
'''
import numpy as np
import pandas as pd
import datetime
import glob
from tqdm import tqdm
import sys
import pydicom as dicom
import nibabel.nicom.csareader as csareader
sys.path.insert(0, '..')
# import my own code
from functions.data_helpe... |
80e4085044101edb97455804e42bd46c4f0d5e5ff24219189a58009dc654492c | Python | 2,934 | 109 | """
Larvaworld : A Drosophila larva behavioral analysis and simulation platform
"""
from __future__ import annotations
import os
__author__ = "Panagiotis Sakagiannis"
__license__ = "MIT License"
__copyright__ = "2024, Panagiotis Sakagiannis"
# TODO : the automatic version naming requires the package itself to be in... |
f898fd71b9fa6bd9d7681638450182d9bef5a19525038cffc5abfe2be9b0af44 | Python | 2,936 | 70 | import pandas as pd
ARI1952 = r"./data/ari-1952.csv" # 1
ARI1953 = r"./data/ari-1953.csv" # 1
ARI2049 = r"./data/ari-2049.csv" # 2
ARI1885 = r"./data/ari-1885.csv" # 2
ARI1727 = r"./data/ari-1727.csv" # 1
ARPA = r"./data/arpa.csv" # GT
class DataCollection:
def __init__(self, drop_null:bool=True):
... |
2877602a98350cf041f5eb4fb69906d54d314d8a769eafbe7cfa68ddb616b0c3 | Python | 2,937 | 71 | """The smooth l1 loss layer for detection related targets"""
# pylint: disable=redefined-builtin
import torch
def smooth_l1_loss(input: torch.Tensor, target: torch.Tensor, beta: float, reduction: str = "none") -> torch.Tensor:
"""
Smooth L1 loss defined in the Fast R-CNN paper as:
| 0.5 * x... |
a75e045174b1fc971dbbb03afc82d332f9e91cbf0cb98d4ec1327c76fe7ca97a | Python | 2,937 | 114 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import tensorflow as tf
import tensorflow.keras as keras
from tensorflow.keras.layers import Reshape, Input, Flatten, concatenate, Dense, BatchNormalization ,Conv1D,Conv2D,Conv3D,MaxPool1D, MaxPool2D,MaxPool3D, GlobalMaxPool2D, Dropout
from tensorflow.keras.optimizers i... |
10d09c6c0bce19c9a92d0c006dc95fe181eff2dc2c3a96254a73b07e0127e5c9 | Python | 2,939 | 78 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import numpy as np
import pandas as pd
import argparse
import os
import sys
import pdb
import csv
def generate_data(input_csv, binarize=False, head_only=False, head_row... |
653213395139e9c75c32a5c456152f397a7df7156d0282e0a74a2e7373cd634d | Python | 2,939 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "surface"
_... |
7cb88db751738e09ce97c88b518ba74462e8dba8b0b2b55947f178fcdf97e5ef | Python | 2,939 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "heatmap"
_... |
862adb93c34b92ece02dc11b0e9ca0743c5bf1646434419222202112fd8d14b6 | Python | 2,939 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "scatter"
_... |
8f0434848bad090aaf4637f725853cfc81dbfeadd80e09a5c4a7bf09876c2679 | Python | 2,939 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "parcats"
_... |
b34a56ffa388acf20a57fd019d69315510506b595234bab0089b2adaa6c6d1c5 | Python | 2,939 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "contour"
_... |
d94f56a59f66d433385ec3a7dc40cbe6ff643d27904e7b675001e0f8a926f7af | Python | 2,939 | 71 | import sys
# setting path
sys.path.append('../TM2_segmentation')
import os
import numpy as np
import nibabel as nib
import itk
import pandas as pd
import tarfile
from scripts.preprocess_utils import find_file_in_path
# load metadata file
input_annotation_file = 'data/csv_files/NYU_2_phenotypic_data.csv'
df = p... |
f0d0edc10b00364e2d781dcaebc140822a693c02481bcaaeb51c8ffbf4855089 | Python | 2,939 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "treemap"
_... |
5edffb7e7effe3c1c9cec1d50168c88f76efaee1fa1c2d22d804bad2164bf15b | Python | 2,940 | 91 | '''Example for comparing two populations using
the violin plots from their morphometrics'''
import neurom as nm
import numpy as np
import pylab as plt
import pandas
import seaborn
feat_list = ['number_of_neurites',
'number_of_sections_per_neurite',
'number_of_terminations',
'n... |
baf287942fa1b3b2ada5b94663d5ef6678f77f23b5a2ad814b1f8c8baa0514a8 | Python | 2,940 | 91 | #!/usr/bin/env python
#=========================================================================
#
# Copyright NumFOCUS
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://... |
e5570e2b5f0a3426075962b84924bdfd6f33f4b09457dc2fbe4f24cbc054bfd9 | Python | 2,940 | 93 | import os
from scripts.constants import PARTICIPANT_IDS_FILE, OUTPUT_DIRS, MIN_MS, MAX_MS
from scripts.analysis_steps import Analysis, save_aggregated_spoc_patterns
from scripts.data_types import Epochs
def prepare_output_dirs():
for output_dir in OUTPUT_DIRS:
if not os.path.exists(output_dir):
... |
26a33b8ec4b36f4bb9857e0925a22ec6c8c147ec898fd1ce5b07871839991958 | Python | 2,942 | 98 | import collections.abc
import hashlib
import numbers
import pathlib
import numpy as np
def dict_update_nested(orig_dict, new_dict):
"""Update nested dictionaries (does not override subdicts)"""
for k, v in new_dict.items():
if isinstance(v, collections.abc.Mapping):
orig_dict[k] = dict_up... |
b76318b70ad0680009cf917f4ab45a011c32848ebf0e803680fe16ac8ee7e0ed | Python | 2,943 | 87 | import os
import subprocess
import pysam
from TestUtils import force_str
def build_fetch_with_samtoolsshell(fn):
retval = os.popen("samtools view {} 2> /dev/null | wc -l".format(fn)).read()
return int(retval.strip())
def build_fetch_with_samtoolspipe(fn):
FNULL = open(os.devnull, 'w')
with subproce... |
015b20ad93eefe8ba47efc845a4d86155d0b635b8c329fa4b45691761a8200dd | Python | 2,944 | 103 | from . import utils
from . import extract_signals
def fit_dim_reduce_model(trial_data, model, signal, train_trials=None, fit_kwargs=None):
"""
Fit a dimensionality reduction model to train_trials
Parameters
----------
trial_data : pd.DataFrame
data in trial_data format
model : ... |
9a2b4fdf111cb94470784a5778d593932d97e344d1c10c821eaf474037d5c9bd | Python | 2,944 | 99 | """
====================================================================
ERP EEG decoding in Tangent space.
====================================================================
Decoding applied to EEG data in sensor space decomposed using Xdawn.
After spatial filtering, covariances matrices are estimated, then project... |
aef9b651e6f627723ef77dda8746f544811b25ede9fc1bbab81b527fdf2d3241 | Python | 2,944 | 91 | import Code_General_utility_spikes_pickling as util
import numpy as np
import matplotlib.pyplot as plt
from copy import deepcopy as dcp
import matplotlib
import warnings
import logging
logging.getLogger('matplotlib.font_manager').disabled = True
warnings.filterwarnings("ignore")
font = {'family' : 'normal',
... |
fde848a07f27400c1b1dbf839a1cb187162f66c2a67745029735b3f11f9a7d2d | Python | 2,944 | 84 | import os
from math import sqrt
import h5py
import numpy as np
import pandas as pd
import scanpy as sc
from dca.api import dca
from scipy.stats import pearsonr,spearmanr
from sklearn.metrics import mean_squared_error
from scbig import setup_seed
for sparity in ['0.8', '0.85', '0.9', '0.95']:
print('-------------... |
09a4e7d70014aaa4befde3edb4f146509770a803e9e6ad87a02a681fc4f9ae2c | Python | 2,945 | 83 | import numpy as np
import nitorch as ni
import json
from metrics.labels import min_distance_boundary, hausdorff_boundary
LABELS_INFRA_MRI = [2]
LABELS_SUPRA_MRI = [3]
LABELS_INFRA_SPIM = [4, 5]
LABELS_SUPRA_SPIM = [1, 2, 3]
LABEL_INFRA = 1
LABEL_SUPRA = 2
ROOT = '.'
MRI_SEG = ROOT + '/warp2lsfm/slide_center_oct/inf... |
3c002903c07bc42ec881688e3c69a83bcce7b6d5bd81c20f308a400b0d5bd2c8 | Python | 2,945 | 79 | import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import kde
def find_closest(A, target):
idx = A.searchsorted(target)
idx = np.clip(idx, 1, len(A)-1)
left = A[idx-1]
right = A[idx]
idx -= target - left < right - target
return idx
def sinaplot(y, pos, ax=None, direction='le... |
485046c533cf1a9042452b5e537fe1b323c0a369d95b5d07e5d3fe07c79fc206 | Python | 2,946 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "sunburst"
... |
715bd83797f333305ff21712261f972440fd52599af7134ea03bc559c4bd412d | Python | 2,946 | 105 | """Permutation related functions."""
import numpy as np
from scipy.stats import zmap
from spiketools.plts.stats import plot_surrogates
###################################################################################################
##################################################################################... |
b1e787f249bb506415f996c014adca95f6668548b1fff14a1c60d3baab7e4921 | Python | 2,946 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "barpolar"
... |
e093fd9f7c214fc14928a642bd58de4b8cf17e5716b8390a50084753b11eef7f | Python | 2,946 | 85 | import numpy as np
import pandas as pd
from anndata import AnnData
from scipy.sparse import csr_matrix
from ._weighting_matrix import (
_PLATFORM,
_WEIGHTING_MATRIX,
impute_neighbour,
weight_matrix,
)
def sme_normalize(
adata: AnnData,
use_data: str = "raw",
weights: _WEIGHTING_MATRIX = "... |
f42ed2ae67db968e2be3bba8ce33a26b2b91b7ed01c66a473c47e1426543f250 | Python | 2,946 | 78 | import mxnet as mx
from mxnet.gluon import nn
from mxnet.gluon.nn import HybridBlock
# pylint: disable-all
__all__ = ['PAM_Module', 'CAM_Module']
class PAM_Module(HybridBlock):
r""" Position attention module
from the paper `"Dual Attention Network for Scene Segmentation"
<https://arxiv.org/abs/1809.02983... |
9d707693904879571eb24096781f00b0d5e04d0c40afb6a024df290a6fa02817 | Python | 2,947 | 68 | import json
import os
import time
import mne
import nibabel
import numpy as np
from mne.datasets import fetch_fsaverage
from atlasreader.atlasreader import read_atlas_peak
from mp_dip.utils.mne_freesurf_labels import read_freesurfer_lut
# multiprocessing not safe
# trying to make it safe
while True:
try:
... |
713bf3f3558b62baa1ad92c57da21dc94fdb6d53c462f829b2187a22adbedcb2 | Python | 2,948 | 74 | """03. Multiple object tracking with pre-trained SMOT models
=============================================================
In this tutorial, we present a method,
called `Single-Shot Multi Object Tracking (SMOT) <https://arxiv.org/abs/2010.16031>`_, to perform multi-object tracking.
SMOT is a new tracking framework tha... |
4be5fa41d76cdb66d4cc0874c1a91bf0ec3235eec2158ce2fe913473112309bf | Python | 2,949 | 108 | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao (leoxiaobin@gmail.com)
# Modified by Bowen Cheng (bcheng9@illinois.edu)
# ------------------------------------------------------------------------------
fro... |
7c8fd81c95ac2a019027cf09ff74389c9f2ac224177511bcd7b1fd50341aa169 | Python | 2,949 | 97 | import argparse
import numpy as np
from mordred import Calculator, descriptors
from rdkit import Chem
from rdkit.Chem.rdmolfiles import SDMolSupplier
def convert_errors_to_nan(el):
"""
Remove elements from the Mordred dataframe which are not
in float or int format
"""
if type(el) == bool:
... |
b672ee8ed01775c8c6df2c415f1ce9c4c3e71413a366f0d0bad3b86989991905 | Python | 2,949 | 64 | import torch
import torch.nn as nn
from torch_geometric.nn import GCNConv, GATConv, SAGEConv, global_max_pool as gmp, global_mean_pool as gep
class CPI_regression(torch.nn.Module):
def __init__(self, device,emb_size, max_length, n_output=1, hidden_size=128, num_features_mol=78,dropout=None):
super(CPI_re... |
c993b960a254c86b4451b2556e5047a5893dd1520d31c28f8488f092e4403b7d | Python | 2,949 | 77 | '''
utils
'''
from Bio import SeqIO
import torch
import numpy as np
import os
import re
from subprocess import call
import shlex
c_s = ['K', 'R']
def esm_feature(data_list, device):
import esm
model, alphabet = esm.pretrained.esm1_t12_85M_UR50S()
model = model.to(device)
batch_converter = alphabet.ge... |
d7400f93e46f6e83946cf46d22e0180c77ce8f7c73b328a41e6ad3ab8d772abd | Python | 2,951 | 99 | from __future__ import annotations
from pathlib import Path
import pytest
from larvaworld.portal import landing_app as landing_module
from larvaworld.portal import serve, workspace_ui
from larvaworld.portal.workspace import (
get_active_workspace_path,
initialize_workspace,
set_active_workspace_path,
)
... |
a24205d0654f35514e58149707ac62effcef86931e7e13238494f4e1da55c55f | Python | 2,952 | 81 | """01. Predict depth from a single image with pre-trained Monodepth2 models
===========================================================================
This is a quick demo of using GluonCV Monodepth2 model for KITTI on real-world images.
Please follow the `installation guide <../../index.html#installation>`__
to inst... |
4ae125f73fa59032c566341c3709c400e52f7999d98bd9ffbf8ec71aee74492e | Python | 2,953 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "scatter3d"
... |
4eab23e42f80bbc77e7eea968d9749168d07dd55a51edf8856d665527cbfe96e | Python | 2,953 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "histogram"
... |
66d18d5804cda35ff9536b4d7403a867946b76505a174d229237a689d326aafb | Python | 2,953 | 90 | #!/usr/bin/env python
#=========================================================================
#
# Copyright NumFOCUS
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://... |
8f7dc28bea75435acda0cd95d6595c717fedc9f05acfaeb816d3476c92f01bd7 | Python | 2,953 | 60 | # -*- coding: utf-8 -*-
"""
Created on Tue Feb 28 16:28:17 2023
@author: cbri3325
"""
import SimpleITK as sitk
import pandas as pd
import os
from ImageAnalysisFunctions import getMaxRoi,getMeanRoi
data_supradir = 'Path to data directory'
subjs_path = [ f.path for f in os.scandir(data_supradir) if f.is... |
942bd5b39056fce163567519b5296f0d05d6ac766d56d4ad90b83bac92b34e7c | Python | 2,953 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "indicator"
... |
ac558471cf7dc02ebdb800b2ed6f8b4294567b3b82c556a573aa878fe6dd00a2 | Python | 2,953 | 91 | import logging
import tarfile
from galaxy.datatypes.binary import CompressedArchive
from galaxy.datatypes.data import (
get_file_peek,
Text,
)
from galaxy.datatypes.protocols import DatasetProtocol
from galaxy.datatypes.sniff import (
build_sniff_from_prefix,
FilePrefix,
)
from galaxy.util import nice_... |
ad1e3ec403a9d7bc503394d82dfa0f960005ea25dcbb038722aea29e73858fdf | Python | 2,953 | 72 | """Default configs for image classification"""
# pylint: disable=bad-whitespace,missing-class-docstring
from typing import Union, Tuple
from autocfg import dataclass, field
@dataclass
class ImageClassification:
model : str = 'resnet50_v1'
use_pretrained : bool = True
use_gn : bool = False
batch_norm :... |
ef35276f94df63deb3c22b08f2caa7571754c8e60e1070d44e5a905554fc3878 | Python | 2,953 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "waterfall"
... |
fd864045b2c71090944506ca7ac34a35fd648949b27f5b2c87ed9a97633054dc | Python | 2,953 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "parcoords"
... |
fff15464a60f592ea451fc08d4af65b826f9a80ac6192d2e2dd2b704619d79a1 | Python | 2,953 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "scattergl"
... |
07eee56c4c830ac59397e84eb40c6e583c7da8ebe8abcff3ca9c6f48df2437d0 | Python | 2,954 | 83 | """1. Getting Started with FCN Pre-trained Models
==============================================
This is a quick demo of using GluonCV FCN model on PASCAL VOC dataset.
Please follow the `installation guide <../../index.html#installation>`__
to install MXNet and GluonCV if not yet.
"""
import mxnet as mx
from mxnet imp... |
dfdaafc6f593f3d99d77bb0a0ec93dc958b746c1eb8cd9181c60ffcc705e00c7 | Python | 2,954 | 92 | import matplotlib.pyplot as plt
import seaborn as sns
from geopandas import GeoDataFrame
from matplotlib import colors
def lisa_quantiles(df: GeoDataFrame):
"""Scatterplot of the gene expression and its spatial lag. Categorization into the four regions (HH, HL, LH, LL) is
also annotated. This function should ... |
eab543b60a5ddf73e0a8e48951667a3830c754ffbbfe9f660e9f1d36dcfb70d3 | Python | 2,956 | 102 | #Autors: Carlos Alberto Hernández Nava
#ASVspoof2017 Assembly for classification
import cv2, os, sys, csv
import numpy as np
import pandas as pd
import keras.models
import tensorflow
from keras.models import Sequential
from keras.layers import Activation, Dense
import matplotlib.pyplot as plt
import seaborn as sns
fro... |
64e58acab51328a4c763edf8ddd7857bc615992f7d49a74fa9c315401052ffdc | Python | 2,957 | 72 | #!/usr/bin/python3
# -*- coding: utf-8 -*-
"""Unified gridsearch and shuffled controls.
Run from the command line with a condition name argument. Optionally, pass the name of
the settings file to use as a second argument.
"""
import time
import sys
import os
import crf_util
import logging
from gridsearch_t... |
8c39f99b51e444521c228f1b122b935130c533b33cd9060454cfbf4bdc997e2f | Python | 2,958 | 87 | """Support functions for Bitmask."""
from typing import List, Tuple
import numpy as np
from scalabel.common.typing import NDArrayF64, NDArrayI32, NDArrayU8
MAX_DET = 100
def gen_blank_bitmask(shape: Tuple[int, ...]) -> NDArrayU8:
"""Generate blank bitmask given the shape."""
assert shape[-1] == 4
bitma... |
b2a840a196db0bd9c9a2fb06c713c546522b5eb8c32f125113a584d1a106ccfa | Python | 2,958 | 95 | import platform
import subprocess
import re
import time
from carbontracker.components.handler import Handler
from typing import Union, List, Pattern
class PowerMetricsUnified:
_output: Union[None, str] = None
_last_updated: Union[None, float] = None
@staticmethod
def get_output():
if (
... |
1eff407bcc7b9a6e01873cae069979be76d66739873de66cc432f2824e774498 | Python | 2,959 | 97 | import torch
import numpy as np
import pandas as pd
from tqdm.auto import tqdm
from .gia._perturb import perturb_seq_torch
from ._utils import _model_to_device
# Reference vs output difference methods
def delta(y, reference):
"""Difference between output and reference"""
return (y - reference).sum(axis=-1)
de... |
0eb1bbe175679e0ac8ea26244d1175e17ef2c3b52c907268638188f3456b8917 | Python | 2,960 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "choropleth"
... |
233ea772c6de73ab6b02e48e00cb2c63a30d04cfd6c6da978a4d9b53e110ff94 | Python | 2,960 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "scattergeo"
... |
29ea81dffe23c4090bd73ecdcec17e4b836f116f30d1bc53e3f012125a7a1aad | Python | 2,960 | 80 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import shutil
from functools import partial
from pathlib import Path
import torch
from ultralytics.nn.modules import Pose, Pose26
from ultralytics.utils import LOGGER, YAML
from ultralytics.utils.checks import che... |
2cf82226b0a63750415c314f862fdf119a243497504b30135f71716e796a13cf | Python | 2,960 | 86 | from typing import Dict, Tuple
import torch
from rbm.potts.grad import compute_gradient
from rbm.potts.sampling import sample_hiddens, sample_state
def update_parameters(
data : dict[str, torch.Tensor],
chains : dict[str, torch.Tensor],
params : dict[str, torch.Tensor],
lr : float,
centered : bo... |
34a2b5fea01e11bb29c777463c4958fd606284baf2956a9ea7f1af69bdc2157c | Python | 2,960 | 104 | import logging
import time
from ethoscope.hardware.interfaces.interfaces import BaseInterface
class WrongSerialPortError(Exception):
pass
class NoValidPortError(Exception):
pass
class OptoMotor(BaseInterface):
_baud = 115200
_n_channels = 24
def __init__(self, port=None, *args, **kwargs):
... |
3819deb222f4c5871fedeb19c7ae67ad65e71c552c20ba6a35302d0f6aa3ed71 | Python | 2,960 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "densitymap"
... |
611fbec604e1d877f20e441f4ebb0e6daa6b2a921a4432d2976ef014f3c86781 | Python | 2,960 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "streamtube"
... |
666c2f38d6617c6d24d74b11ee70a652cf2933ce739dffc25e709ab5d3f0e073 | Python | 2,960 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "funnelarea"
... |
9b8bbd6be5a51f22d729f700553d4a2dc45902be9808fdc6a9fa1351dd2d5fdf | Python | 2,960 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "scattermap"
... |
d4bb8aa95d1965da1b940b37d7aae656abd06f89d5509be649bf89de5e590ec0 | Python | 2,960 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "isosurface"
... |
9861bc086a7cf0887596a78c3f4bb12450c39ad60f3c7b1535aea61f0ed636cd | Python | 2,961 | 86 | """Tests for bdpy.dl.torch.domain.feature_domain."""
import unittest
import torch
from bdpy.dl.torch.domain import feature_domain as feature_domain_module
class TestMethods(unittest.TestCase):
def setUp(self):
self.lnd_tensor = torch.empty((12, 196, 768))
self.nld_tensor = torch.empty((196, 12, 7... |
cdd96377c3c096824616cff48c366f73013e27b7c67c93131d037dec5bbac0b2 | Python | 2,961 | 75 | from copy import deepcopy
import tensorflow as tf
import tensorflow.keras as keras
import tensorflow_addons as tfa
from sklearn.model_selection import StratifiedKFold
from tf_spiking.helper import TrainingHistory
from tf_spiking import DenseLIF, DenseLIFNoSpike, IntensityToPoissonSpiking
import numpy as np
from traini... |
18403c5daf1f859cb3d4a75474ff29ed1d0b191ae9c8b5b58fad80f0d2a9783c | Python | 2,962 | 93 | """
Unit tests for stimulators/optomotor_stimulators.py.
Tests OptoMidlineCrossStimulator class.
"""
import unittest
from unittest.mock import Mock
from ethoscope.hardware.interfaces.optomotor import OptoMotor
from ethoscope.stimulators.optomotor_stimulators import OptoMidlineCrossStimulator
from ethoscope.stimulato... |
293cd994b8bbc61b43eb29da4637ba7c50ccfd2a87dc2197159a3d6df40293fb | Python | 2,962 | 99 | """Regression tests for selective-save child-version snapshots."""
from __future__ import annotations
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens.backends.torch.aliasing import detect_torch_alias_contract
from torchlens.ir.intervention import FunctionEventInput
class FastP... |
cf5b66844fd79255fdaf7054430aacb93877c8a6cb22a35e83831bd6d2e6d17e | Python | 2,962 | 96 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
""" Chamfer distance in Pytorch.
Author: Charles R. Qi
"""
import torch
import torch.nn as nn
import numpy as np
def huber_loss(error, del... |
f8252d419d5b870ec8fea2a4ecaad16a32fc5c8f872d34a08f4d14ce38b44960 | Python | 2,962 | 84 | import tensorflow as tf
import tensorflow.keras as keras
import tensorflow_addons as tfa
import numpy as np
from copy import deepcopy
from sklearn.model_selection import StratifiedKFold
brightness_offset = 42 #90
# THIS OFFSET IS SUBTRACTED
def load_local_fashion_mnist(path, kind='train'):
import os
import g... |
87481f3c5e63ca50c44b1fc81e017a6d9304ed0004387cd01dd9fae463fe8eb1 | Python | 2,963 | 78 | from __future__ import absolute_import
from pip._vendor.packaging.utils import canonicalize_name
from pip._internal.cli.base_command import Command
from pip._internal.exceptions import InstallationError
from pip._internal.req import parse_requirements
from pip._internal.req.constructors import install_req_from_line
f... |
142357f7bbb4bad493126e15cba99a55a34fa4091d86e1ceeaf801b30f1570e3 | Python | 2,964 | 120 | import pytest
import rpy2.robjects as robjects
rinterface = robjects.rinterface
import array
def test_init_empty():
env = robjects.Environment()
assert env.typeof == rinterface.RTYPES.ENVSXP
def test_init_invalid():
with pytest.raises(ValueError):
robjects.Environment('a')
def test_get... |
20eaeeeba33a2a3b9bdf1bbee19e2129c7e8c2d58c9e016fd6e7df6434b0512a | Python | 2,965 | 100 | """
A script to exctract frames from a .db file and create a video.
There are to external deps: ffmpeg and imagemagick.
"""
import sqlite3
import io
import tempfile
import shutil
import os
from optparse import OptionParser
import datetime
import glob
from multiprocessing import Pool
def annotate_image(args):
inp... |
37ad768d3b31c23bf1ec70b184d17f57f96007e525e95c1aa578e4222b260fbe | Python | 2,965 | 76 | """Plain pickles of a Trace must not embed builtin facet recipe function identities.
FW2-B item 12-A. ``Trace.facet_registry_snapshot`` is session-time state
(``FieldPolicy.DROP``) whose ``_RegisteredRecipe.func`` entries pickle the
builtin recipe FUNCTIONS by import identity. Carrying it through
``Trace.__getstate__`... |
7278c8e342e64ce0e80225868d5c89ed7f5e0c944c548ea5d623005421abb413 | Python | 2,966 | 64 | import unittest
from os.path import join, abspath
from numpy.testing import assert_allclose
from tests.tabulation.nonadiabatic_defect_equilibrium.rebless import run
from spitfire.chemistry.library import Library
from spitfire.chemistry.ctversion import check as cantera_version_check
if cantera_version_check('atleas... |
d878e4664380b8a9a84c32f69fcb96d62279e0e4bd8fdba92b90b2a71cad155b | Python | 2,966 | 83 | import warnings
warnings.filterwarnings("ignore", category=RuntimeWarning)
import os, glob
import argparse
import numpy as np
import pandas as pd
import nibabel as nib
from fmri_encoder.logger import console
from fmri_encoder.lazy import default_process_multipleX_and_cv_encode
if __name__ == "__main__":
parser ... |
76f7d97929ac3db36b06d8ca68dc36ccaf3234e70b31f30b16101605e8ab7678 | Python | 2,967 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "candlestick"
... |
dc8561d8f52ef36ea022293cb5b5726d516222ecc57ef820f610176e46068213 | Python | 2,967 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "histogram2d"
... |
3178bd1131c4dcdf7052b2c9c01639cdfcbf343c261f759774c49ff535453d23 | Python | 2,968 | 93 | from setuptools import setup, find_packages
from setuptools.command.build_py import build_py
import os
import subprocess
import shutil
import platform
class BuildPyCommand(build_py):
"""Modified build command to compile C library."""
def __build_c_library(self):
this_dir = os.path.dirname(__file__)
... |
745754ca73f02c976b078ead85ea91f86733096a17631ceaf96acc7cf4e11ac7 | Python | 2,968 | 102 | """
====================================================================
One Way manova with Frequenty
====================================================================
One way manova to compare Left vs Right for each frequency.
"""
import numpy as np
import seaborn as sns
from time import time
from pylab import p... |
abd8ea3e8f369b653e4b45b978d3ec7556384a0d86a1837fcceefbd65d80d830 | Python | 2,968 | 87 | from abc import ABC, abstractmethod
import torch.nn as nn
import torch.nn.functional as F
class LinearEffects(nn.Module, ABC):
"""
Represents how to compute true motifs when effects are linear.
In effect, we set up the optimization problem (where m0 is the input and m is the true
motifs we output... |
b854300de869cc7b9c645bdce344de5ab3cd4b2ee188a8744d780c226a7e1db7 | Python | 2,968 | 76 | import json
import statistics
import time
import statsmodels.stats.api as sms
from angorapy.utilities.datatypes import mpi_condense_stats
from angorapy.agent.ppo_agent import PPOAgent
try:
from mpi4py import MPI
except ImportError:
MPI = None
def evaluate_agent(agent: PPOAgent, n_episodes: int, act_confide... |
8a16637672a096ae599e1a7910a7dc78764765c444da3413dd1d235f6c66a2e6 | Python | 2,969 | 98 | #!/usr/bin/env python3
"""
Analyze what domains powerstat reads by examining all RAPL domains
and comparing with powerstat output.
"""
import os
print("=" * 80)
print("All available RAPL domains on your system:")
print("=" * 80)
# Find all RAPL domain directories
rapl_dirs = []
for base in ["/sys/class/powercap", "/... |
c5e0bd34943c582b2c477ed608fd70f3f2713e6f742ce4d488fea419b8aa587d | Python | 2,970 | 119 | """Model configuration JSON export utilities."""
from __future__ import annotations
import json
from typing import Any
__all__ = ["export_model_config_to_json"]
def export_model_config_to_json(
model_id: str,
config: dict[str, Any],
compare_model_id: str | None = None,
compare_config: dict[str, Any... |
0b56ca2ccde54e22c0af3303bad9a978144edbd96c87cc3c4f9cd8763b8c1fe0 | Python | 2,971 | 84 | import os
import shutil
from qtpy import QtCore
from llspy.gui.mainwindow import main_GUI
from llspy.llsdir import LLSdir
from .conftest import requires_cuda
@requires_cuda
def test_basic_processing(qtbot):
testdata = os.path.join(os.path.dirname(__file__), "testdata", "sample")
deconFolder = os.path.join(... |
5fbbe4dc74d107211ba83dd521919462c06376ba4e2dd5bfea71de1cef609f07 | Python | 2,971 | 94 | # -*- coding: utf-8 -*-
"""
Tier 1: import every pyoperant/behavior/*.py module standalone, with
hardware modules stubbed out. Catches import-time bugs (missing
dependencies, broken imports) that Tier 0 (syntax) can't, without needing
real GPIO/serial/audio hardware.
Unlike py-behaviors' Tier 1 (which loads each file ... |
f01d2b0589061852c9eb9889cf5374874be2195652858d382472e73906479b9e | Python | 2,971 | 74 | import torch.nn as nn
import torchvision.models as models
import torch
from exceptions.exceptions import InvalidBackboneError
class ResNetSimCLR(nn.Module):
def __init__(self, base_model, out_dim):
super(ResNetSimCLR, self).__init__()
print("HEREEEEEE?")
self.resnet_dict = {"resnet18": m... |
5536b1d7fca609c21c6d09b333b0634aa9790ed08501413a948ab30d706e39db | Python | 2,972 | 104 | """
Tests to make sure the dataload module isn't busted
"""
import os
import torch
import numpy as np
import eugene as eu
import pytest
from pathlib import Path
from eugene.dataload import SeqData, SeqDataset
HERE = Path(__file__).parent
def check_random1000_load(sdata, has_target=False):
assert isinstance(sdat... |
9070cbdfd6077873cb6cf8a265bae5a1e0007e333d3d22293d5e12775f31bf95 | Python | 2,972 | 87 | from typing import Optional, Tuple
import numpy as np
import pytest
import gym
from gym import spaces
from gym.wrappers.filter_observation import FilterObservation
class FakeEnvironment(gym.Env):
def __init__(
self, render_mode=None, observation_keys: Tuple[str, ...] = ("state",)
):
self.obs... |
de2955f962c0d9067bdb6a5c8f47ff4781d455fc81ab48efd2e5494c9a501fd6 | Python | 2,972 | 101 | # !/usr/bin/env python
"""
Modified version of code examples from the chemfp project.
http://code.google.com/p/chem-fingerprints/
Thanks to Andrew Dalke of Andrew Dalke Scientific!
"""
import argparse
import chemfp
import matplotlib
matplotlib.use("Agg") # noqa
from matplotlib import rcParams # noqa
rcP... |
36c873b17c85046edd39634330dddeb5a69059e3c1faf5b5422d9a02d7a6ae8b | Python | 2,973 | 63 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'score_session_manager_control_ui.ui'
#
# Created by: PyQt5 UI code generator 5.6
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Form(object):
def setupUi(self, Form):
... |
6d1e763c05c62a18274b95bf1df08b04c867257882503a8f0488154f39a58f71 | Python | 2,973 | 82 | import sys
from ij import IJ
# Fiji Jython interpreter implements Python 2.5 which does not
# provide support for argparse.\
input_file = sys.argv[-7]
operation = sys.argv[-6]
expression = sys.argv[-5]
if sys.argv[-4] in [None, "None"]:
bin_constant = None
else:
bin_constant = int(sys.argv[-4])
if sys.argv[-3... |
a916863ed0721c3d0d87fe18cc0ea0c38999b9ed370683f72dde25aaa80d623e | Python | 2,973 | 64 | import unittest
from os.path import join, abspath
from numpy.testing import assert_allclose
from tests.tabulation.nonadiabatic_defect_burke_schumann.rebless import run
from spitfire.chemistry.library import Library
from spitfire.chemistry.ctversion import check as cantera_version_check
if cantera_version_check('atl... |
b1d42943ea0f03bc0043d2a1ef0693e55c512eff5d57a6704feca99aeee5a50a | Python | 2,973 | 87 | import numpy as np
import scipy.spatial.distance, scipy.cluster.hierarchy
from tqdm.auto import tqdm
import scipy.sparse
from . import xpu, stats, spatial
from .xpu import cupy_wrapper, iscupy, to_numpy
#TODO: remove this function and use spatial.pdist below
def pdist(X, Y, metric='euclidean'):
if iscupy(X):
... |
13c213d47d1090b6e1f693986df5ae8449ad629008b47314f756a7e164745cd7 | Python | 2,975 | 98 | """The ``celery events`` program."""
import sys
from functools import partial
import click
from celery.bin.base import (LOG_LEVEL, CeleryDaemonCommand, CeleryOption, handle_preload_options,
handle_remote_command_error)
from celery.platforms import detached, set_process_title, strargv
de... |
49d683e5fd0d6757ddf4febdcb959c9240b42418b88c36332d52f4f3077c7829 | Python | 2,975 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "scattersmith"
... |
8321500516297f04b6e75665b2f737aae412456e2e9cb78357e3553866329977 | Python | 2,975 | 104 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
_parent_path_str = "scatterpolar"
... |
8ce514d19cae32773a27e87481938399375686994893b0617dfd0f70efa50388 | Python | 2,975 | 87 | import torch.nn as nn
from .residual_unit import HalfResidualUnit, ResidualUnit
class ResidualStack(nn.Module):
"""
Represents a stack of ResidualUnits. The number of ResidualUnits is
determined by the `depth` parameter, which can be an integer or a
half integer. If it is a half integer, the ... |
b009f5433d847aec98c757b950f785dc0addff17f1dd749456e1df8f16ebde66 | Python | 2,975 | 78 | import numpy as np
from larvaworld.lib.util import fft_max, detect_strides
def test_fft_max_basic():
a = np.array([0, 1, 0, -1])
dt = 1.0
fr, yf = fft_max(a, dt, return_amps=True)
assert np.isclose(fr, 0.25), f"Expected dominant frequency to be 0.25, but got {fr}"
assert len(yf) == 2, f"Expected l... |
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