sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0ab5cb71712976520398d8d3b8bfe07bbb705251073ac546c6c5c7adaf48749d | Python | 3,530 | 94 | """
EEG speech envelope TRF
=======================
Analyze continuous speech data from the mTRF dataset [1]_: use the
boosting algorithm for estimating temporal response functions (TRFs) to the
acoustic envelope.
"""
# Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
# sphinx_gallery_thumbnail_number = 4
import... |
2393ce3e894759db7264bf8392572eaf5a3e670bd1a289678705801f04d4085d | Python | 3,530 | 109 | """
Convert gtex gene ids to genesymbols, normalize the expression, and write the resulting dataframe
to disk
"""
import argparse
import numpy as np
import pandas as pd
def parse_gtex_file(file_path: str) -> pd.DataFrame:
"""
Read the expression data from a GTEx file
Arguments
---------
file_pa... |
2e37f47f165b667e7ab115a9195ee7e1064d22209d3613a3c57c07e375a39964 | Python | 3,530 | 188 | # Generic
import yaml
import time
import torch
import pickle
import pprint
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# Libraries
from pathlib import Path
# Own
from ls2d.utils import _load_pickle
from ls2d.utils import _dump_pickle
# ------------------
# Load config
# ------------------
... |
d8baba34ed9b97ed8ca46a09d1502389d588507765e9de98ba656cbe67886961 | Python | 3,530 | 87 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
97f9a4053e614b1b46f7ae67e618579864e31f514203bb1c9572f70f1b81f4e8 | Python | 3,534 | 121 | # %% [markdown]
# ##
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
from scipy.integrate import tplquad
from scipy.stats import gaussian_kde
import pymaid
from src.data import load... |
9d382bd4451fbffbcc386a6b80f4fbe14203facd6f89c66ac3e94de3f8b27aa7 | Python | 3,534 | 125 | # %% [markdown]
# #
from src.graph import MetaGraph, preprocess
from src.data import load_metagraph
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import networkx as nx
def get_edges(adj):
edgemat = np.empty((len(adj), 2 * len(adj)))
for i in range(len(adj)):
... |
03936bf1d2f10792b04c9e5e1f2ac9b5e1fc9ba18a0423de2e96db5511bf353e | Python | 3,535 | 103 | # python 3.7
"""Contains the base class for generator in a GAN model.
This class is derived from the `BaseModule` class defined in `base_module.py`.
"""
import numpy as np
from .base_module import BaseModule
__all__ = ['BaseGenerator']
class BaseGenerator(BaseModule):
"""Base class for generator used in GAN var... |
76f21d6db976693156c207741da82812c7b57e4067b3c8b4c73481212d05a91f | Python | 3,536 | 105 | import json
from utils import full_target_file_pipeline
FASTA_PATH = "/mnt/datasets/DeepCT/male.hg19.fasta"
ALL_TARGETS_PATH = "/mnt/datasets/DeepCT/all_features/sorted_deepsea_data.bed"
def create_mini_fasta(fasta_path, mini_fasta_path, mini_fasta_counts_path):
"""
Sample some lines from `fasta_path` to cr... |
d273653d77f906422fb5669dc1d100b94a98ca8faacca3c18a310a5fa67d132b | Python | 3,536 | 103 | import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
# Device configuration
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
# Hyper-parameters
sequence_length = 28
input_size = 28
hidden_size = 128
num_layers = 2
num_classes = 10
batch_size = 100
nu... |
56c4fdf1b64ea5eb63e806f89da2301bc84cc4e8702455aaa01b52fb181fa494 | Python | 3,537 | 106 | import os
import time
import logging
import numpy as np
from siVAE import FeatureImportance as FI
def residual_analysis(self, y_reconstruct, y_test, min_PVE = 0, take_mean = False, verbose = False, save_PVE = False):
"""
Calculate PVE and RE of the true and reconstructed numpy array
Return [RE... |
6fdf586e8e00ec4277b5b6b7141d949457b875d5ab646676822deab0b2ff9e8a | Python | 3,537 | 139 | """The functions used in the program search.
This library implements the functions that will be used in the program search.
Having a shared library of functions will make it easier to share the discovered
algorithms between different tasks. For example, if we want to evaluate one
algorithm on both language and vision ... |
bb03b17f3f676d16e39077db9a7f5a72a5d3bae85d429ddd14708aaab5399ad4 | Python | 3,537 | 117 | import os
from skimage import io, transform
import torch
import torchvision
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms#, utils
# import torch.optim as optim
import numpy as np
from PIL imp... |
cb9fee74fd9918f6aea45f0d9997c24887b6a12ea01063fb01b667d32fd5c2a6 | Python | 3,538 | 99 | import logging
import os
import zipfile
import anndata
import numpy as np
import pandas as pd
from scvi.data import setup_anndata
from scvi.data._built_in_data._download import _download
logger = logging.getLogger(__name__)
def _load_seqfishplus(
save_path: str = "data/",
tissue_region: str = "subventricul... |
73737f3b921cc01a6e974aa44b2c211eb9cb079b54e23f6f0f3a7d5839d15eac | Python | 3,540 | 111 | # -*- coding: utf-8 -*-
import pathlib
import queue, subprocess, threading, io, os, sys
import time
class GpuThread:
def __init__(self, gpu, pool):
self.gpu = gpu
self.pool = pool
self.queue = queue.Queue()
self.thread = threading.Thread(target=self.run)
self.log = io.Strin... |
48564d8d2d3fda118a92bd98ebe0ca123160adcbe902079a57862186b504d98c | Python | 3,541 | 80 | # python 3.6
"""Revised from Inverts given images to latent codes with In-Domain GAN Inversion."""
import os
import argparse
from utils.inverter import StyleGANInverter
from utils.visualizer import save_image, load_image, resize_image
def parse_args():
"""Parses arguments."""
parser = argparse.ArgumentParser()
... |
82f533b90381d16d3dd2227067804bd4f3961cfaa27aa477ceb941f94145dd11 | Python | 3,541 | 84 | """Phase 3d regression tests: dual-DAN model and latent inhibition.
These tests pin down the headline behaviour:
- Dual model acquires CS+ on a control (un-pre-exposed) schedule
- Dual model shows latent inhibition: pre-exposed CS+ acquires slower
- Pure RPE does NOT show latent inhibition (the structural predic... |
2b6b8af61afb76e400b4f7c206075ff167bd64c55580e72d2624768a3d2401c8 | Python | 3,544 | 112 | '''
Figure 7.
Zoom on action potential.
Ionic current in the example, based on passive subtraction.
Estimation of calcium accumulation.
'''
from brian2 import *
from brian2.units.constants import faraday_constant as F
import yaml
from file_management import *
from pylab import *
import matplotlib.font_manager as fm
imp... |
baa3a8b32def2c8c7cbe2d481148043e6301bef4ba6ee344856a68505b3b723a | Python | 3,546 | 86 | import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import hilbert, welch
class WelchPSD():
def __init__(self, signal, fs=25000, nperseg=1024, scaling="density", unit="microV", tokens={}):
self.fs = fs
self.nperseg = nperseg
self.scaling = scaling
self.unit = unit
... |
aec106ad98ef74c0544865a5eb14a58d5822aacb41c934e965d5bb3e4c55709b | Python | 3,549 | 110 | """
Kuramoto-type model.
- Sinusoidal coupling
- accelerated with numba
"""
import numpy as np
import math
import numba
def njit_wrapper(use_numba, *args, **kwargs):
'''
Wrapper for numba njit decorator
If :param use_numba: is True -> will use @njit with given args and kwargs.
... |
dbc2400530fc60c1fe4c71f645e64169461822992b439aaea87a18b83df93b64 | Python | 3,549 | 80 | #!/usr/bin/env python
# Copyright 2014 Johns Hopkins University (Authors: Daniel Povey, Vijayaditya Peddinti). Apache 2.0.
# creates a segments file in the provided data directory
# into uniform segments with specified window and overlap
from __future__ import division
import imp, sys, argparse, os, math, subproces... |
069f52003a2ea9126fc859b9107b965ebe96eb913b50d7ad07fd47790bd45cd7 | Python | 3,550 | 94 | """This file is for back-of-the-envelope calculations / figures based on them."""
import numpy as np
def binary_svd_depth_size(n, k, interport_distance=25, device_length=200, loss_db: float = 0.3):
"""Binary SVD architecture depth and size.
Args:
n: Number of inputs.
k: Number of outputs (ge... |
5983df2676d1ca7612dbf08ac67de75cd2309df596e5823944415da12c7a5c6f | Python | 3,551 | 100 | r"""Modified from https://github.com/facebookresearch/detectron2/blob/master/detectron2/layers/wrappers.py # noqa: E501
Wrap some nn modules to support empty tensor input. Currently, these wrappers
are mainly used in mask heads like fcn_mask_head and maskiou_heads since mask
heads are trained on only positive RoIs.
"... |
89559f406de2847a1f447fb76bf2a27fe2ce4af8df3c61327d68d5101285f3ec | Python | 3,551 | 110 | import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
from torchvision import transforms
class ToOneHot(object):
""" Convert the input PIL image to a one-hot torch tensor """
def __init__(self, n_classes=None):
self.n_classes = n_classes
def onehot_initialization(self, a):
... |
fdc35a18af7d59039782b79422d8b8393dc3393c1b2c58a42914277f7abfddc8 | Python | 3,551 | 83 | #!/usr/bin/env python3
# Copyright 2020 Yuri Khokhlov, Ivan Medennikov (STC-innovations Ltd)
# Apache 2.0.
"""This script converts JSON to VAD alignment.
Single-speaker speech is treated as 1, whereas both silence and overlapped speech as 0.
This can be used for excluding overlapping regions from i-vectors estimati... |
07776f1b3f78f7b32ee36b2436df1cfc4c84707b69ab3e9c2d783e121ec2c4d5 | Python | 3,552 | 98 | import numpy as np
def linear_(x, params):
a, b = params
return a*x+b
def sigmoid(x, L, x0, k, b):
return L/(1+np.exp(-k*(x-x0)))+b
def sigmoid_fit(x, y):
from scipy.optimize import curve_fit
ymin = np.percentile(y, 5)
ymax = np.percentile(y, 95)
x0 = np.percentile(x, 70)
p0 = [yma... |
4e69a25f88c7830525e0ef7405fb8c3523df5f8ac5e4c9da1048e5a70e3335f0 | Python | 3,555 | 116 | ''' Define the Layers '''
import math
import torch
import torch.nn as nn
import numpy as np
def pad_mask(seq, pad_idx=0):
return seq == pad_idx
def tri_mask(seq, diag=1):
''' For masking out the subsequent info. '''
sz_b, len_s = seq.size()
masks = torch.ones((len_s, len_s)).triu(diagonal=diag)
m... |
050e3e81c4777caf05e1169b8e5536d50f251f46b9e10be528728e1c79908c89 | Python | 3,556 | 119 | from collections import namedtuple
import torch
from torch.nn import Conv2d, BatchNorm2d, PReLU, ReLU, Sigmoid, MaxPool2d, AdaptiveAvgPool2d, Sequential, Module
"""
ArcFace implementation from [TreB1eN](https://github.com/TreB1eN/InsightFace_Pytorch)
"""
class Flatten(Module):
def forward(self, input):
return inp... |
093bbc8a99817390baca9829fdca1d97bc68705cc777db5ccd1092b0dedb8cec | Python | 3,556 | 94 | import numpy as np
import torch
import functools
class CORE_Dataset(torch.utils.data.Dataset):
'Characterizes a dataset for PyTorch'
def __init__(self, data, tokenizer, use_ratio = 1, which_label = 'void_fraction'):
label_dict = {
'void_fraction':2,
'pld':3,
... |
bea66e23aefc7e62c2d06c40730efe0ab9bfe2c9653dc51ce61e57fb59a3c0ef | Python | 3,556 | 113 | import logging
from typing import Any, Dict, List, Optional, Tuple
import numpy as np
import pandas as pd
import pytorch_lightning as pl
import torch
import torch.nn as nn
from FrEIA.framework import ReversibleSequential
from FrEIA.modules import AllInOneBlock
from hydra.utils import instantiate
from src.util.util imp... |
8b009f53638c3daa05bde9a5ac08cc55d2dab4abe8b25caa7454abc3b186078a | Python | 3,557 | 89 | import torch
import torch.nn as nn
from .conv_ws import CONV_LAYERS,ConvAWS2d
#from mmcv.cnn.utils import constant_init
#from .registry import CONV_LAYERS
import torch.nn.functional as F
#from mmcv.utils import TORCH_VERSION
#from torch.autograd import Variable
class Attention(nn.Module):
def __init__(self,... |
3cb24c8db42a4855de305dd5e5a5b121193253b39e88990fef32861ae9471903 | Python | 3,560 | 63 | import os
# Heuristics created by Vincent for Abbas dataset sample6.
# 27th Nov. 2019
# updated 23th Jan. 2020
def create_key(template, outtype=('nii.gz',), annotation_classes=None):
if template is None or not template:
raise ValueError('Template must be a valid format string')
return template, outtype,... |
89871e1b20df677975fcde016a8e39b50d8d84f2061b582cfb2f5905648bdc36 | Python | 3,561 | 99 | import math
import unittest
from types import SimpleNamespace
import numpy as np
try:
import carla
except ImportError: # the wheel is optional for the pure-python tests
carla = None
from alpamayo_coordinates import (
alpamayo_points_to_carla_local,
carla_rotation_matrix,
history_to_alpamayo,
)
... |
8a3665bcb587c069899af9581b68cfb78ebea7c43bb2708cfdc6fcc79208dce1 | Python | 3,561 | 120 | from __future__ import print_function, absolute_import
import os
import os.path
import torch
import torch.utils.data as data
import torchvision
import torchvision.transforms.functional as TF
from dataloader.data_utils import *
def generate_pair_images(root, gap=6, win_gap = 7):
images = []
root = os.path... |
517ff6a8d69edd542bcfd8af798b8f52783435073e0eb7b249189203599cb612 | Python | 3,562 | 94 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
2c306433088756f3a314025f5f10047691459bd6c28c06b869fd2ec1e65e4e41 | Python | 3,564 | 80 | """Phase 3c regression tests: extinction behaviour.
Documents the complementary failure modes of RPE and the Bayesian-observer
AIF formulation:
- RPE extinguishes correctly under signed weights (allow_negative_weights=True).
- AIF (perceptual-Bayesian) cannot extinguish; this is informative, not a bug.
"""
import num... |
eea7b16712566225d4608b9c0f7ebbd4524e8012d1f1aa276aafb82122ea7707 | Python | 3,564 | 112 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
337f1ccbb7d63abab71eed8c4811fee97315bd3ba646885b6569cbb62b46f7d0 | Python | 3,566 | 101 | import torch.nn as nn
from mmcv.cnn import constant_init, normal_init
from mmdet.models.registry import BACKBONES
from .derive_blocks import derive_blocks
from .operations import Conv1_1, conv_dw
from tools.apis.param_remap import remap_for_paramadapt
@BACKBONES.register_module
class FNA_SSDLite(nn.Module):
ext... |
73863ef59efcf34ed50d8cd0224b4b68487946449722900ee3e5925e987567a3 | Python | 3,566 | 132 | import corticostriatal as cs
from matplotlib import pyplot as plt
from matplotlib import patches as mpatches
from matplotlib import lines as mlines
from matplotlib.legend_handler import HandlerLine2D, HandlerTuple
from jax.random import PRNGKey,split,uniform
from jax.ops import index,index_update
from jax import numpy ... |
9b752981195cbd0aa4802e1f6277727ea778a7b1e0905b941c3a0c7751ab7235 | Python | 3,566 | 99 | # Copyright 2020 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
b6e606e97d067ee2bfdc642500d73d37c1dfe6b6a6c981b73d99470d7b621ef3 | Python | 3,566 | 81 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
from collections import OrderedDict
import logging
import torch
from maskrcnn_benchmark.utils.imports import import_file
def align_and_update_state_dicts(model_state_dict, loaded_state_dict, silent=False):
"""
Strategy: suppose that the... |
37c8a0277bd2964ae71ebebfe2e8f9186a2bec1a68885f895f9dca9cb8f2ca04 | Python | 3,567 | 92 | '''
@author: Mahbub Ul Alam (mahbub@dsv.su.se)
@version: 1.0+
@copyright: Copyright (c) Mahbub Ul Alam (mahbub@dsv.su.se)
@license : MIT License
'''
'''@file early_sepsis_detector.py
run this file to go through the complete neural net training, testing and evaluating procedures,
look at the 'early_sepsis_detector_con... |
c01abbba0955c9c2074b0efc119e84f132969727fb6c21c07b649214d13dbd74 | Python | 3,567 | 92 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
1caba972be41cf5b282d7d7129b71a934cf6c3ebea885ebf946136ed58bb4a8e | Python | 3,568 | 116 | import numpy as np
import pandas as pd
def exp_smoother(
sequence,
da,
nsyllables=10,
baseline_temperature=0.1,
entropy_tau=10,
usage_tau=200.0,
entropy_scaling=0.3,
usage_scaling=0.3,
eps=1e-10,
log_variables=False,
):
from rl_analysis.photometry.decoding.util import stab... |
5011667a20ec260e614b7e566987b5912fc93db79b869ba096f3d2cf9aaae081 | Python | 3,568 | 92 | # python 3.7
"""Contains the base class for encoder in a GAN model.
In addition to the two-player game between generator and discriminator in GANs,
some work introduce an extra encoder to facilitate real image inference. The
encoder can be view as the reverse of the generator, which projects a given
image back to the ... |
7aa45607d50e25abf8dc011ecf7f75f36bb36c1cd40a5042d74ddc8acdf65f2c | Python | 3,569 | 86 | '''
@author: Mahbub Ul Alam (mahbub@dsv.su.se)
@version: 1.0+
@copyright: Copyright (c) Mahbub Ul Alam (mahbub@dsv.su.se)
@license : MIT License
'''
'''@file early_sepsis_detector.py
run this file to go through the complete neural net training, testing and evaluating procedures,
look at the 'early_sepsis_detector_con... |
309822655c099995026edfccd939c8857d7ddaa69a4fc1d0d2592aa9f92a18a5 | Python | 3,570 | 97 | """Tests for `navis.drop_internals` - the wrapper, not the repair.
The repair itself lives in navis-fastcore and is tested there. What navis adds
is the bookkeeping around it, and two pieces of that are easy to get wrong.
fastcore reports "I kept surface I could not vouch for" with `warnings.warn` and
a `stacklevel` ... |
4ecfda2a32b39c5f89f66c5d021deaa950d9e05631f418a0688b7ce431567daa | Python | 3,571 | 111 | # -*- coding: utf-8 -*-
# File : test_sync_batchnorm.py
# Author : Jiayuan Mao
# Email : maojiayuan@gmail.com
# Date : 27/01/2018
#
# This file is part of Synchronized-BatchNorm-PyTorch.
import unittest
import torch
import torch.nn as nn
from torch.autograd import Variable
from sync_batchnorm import Synchroniz... |
96017766629be45139d6dcb6e2765eed675bb16c2b08885b46d7b9331962b918 | Python | 3,571 | 99 | import gurobipy as gp
import numpy as np
from mip.mip_nn import MIP_NN
from globals import EPSILON, CONT, GUROBI_ENV, LOG
class MAX_M(MIP_NN):
def __init__(self, data, architecture, bound, reg, fair):
model = gp.Model("Gurobi_NN", env=GUROBI_ENV)
if not LOG:
model.setParam("OutputFlag", 0)
self.N... |
2d7d02e4e6db56a0155434b8b34ff2fc0c836e6697a52a70c6c21cc2a8994e70 | Python | 3,572 | 110 | #! /bin/env/python
from rdkit import Chem
##### Sanifix 4 by James Davidson ######
""" sanifix4.py
Contribution from James Davidson
"""
def _FragIndicesToMol(oMol, indices):
em = Chem.rdchem.EditableMol(Chem.rdchem.Mol())
newIndices = {}
for i, idx in enumerate(indices):
em.Add... |
fa31789edf85005c2767966af7fea37cf34906a74f2bb7af62fe6e338fa8f054 | Python | 3,573 | 124 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
9066e3cab2e00b7f68472dffde838abdfa02252210dad15a2ca1a3f9df62f75f | Python | 3,574 | 144 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
import os
def create_op(func, **placeholders):
op = func(**placeholders)
def f(**kwargs):
feed_dict = {}
for argname, argvalue in kwargs.items():
p... |
ac3c1c81d4d11e0d76c3d3fbecc4d3a07c6c5e19a5bd8c66a503526c1923a0fb | Python | 3,574 | 92 | #!/usr/bin/env python3
import argparse
import BTlib
import glob
import os
from collections import defaultdict
import pandas
from pathlib import Path
####################################
### Parse command-line arguments ###
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser... |
bbc3fdb17560b88d3b96890ee76375da78474158edbb83984c8c1463ca2bd36b | Python | 3,574 | 125 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
e57c9a1b4fbfa5795e8f057f9d09f17244cc187d7c77fc64c2ca1afa9dbe9924 | Python | 3,574 | 125 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
662fbb74549198330c0c530c0448bac524a19f90218c70131b72781f9d36aafa | Python | 3,575 | 90 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
abd5f4c88780cf0f4dc2a4e539715e27d9971bf5c37bad9062eaa3cf93a41f98 | Python | 3,577 | 104 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
c36993099b3f32446536a08517aead9e0f2d2a7fd525aec1859ccd000910e4a3 | Python | 3,577 | 120 | import argparse
import os.path as op
from glob import glob
import pandas as pd
def _get_parser():
parser = argparse.ArgumentParser(description="Get subjects to download")
parser.add_argument(
"--dset",
dest="dset",
required=True,
help="Path to BIDS directory",
)
parser... |
12275d4c8ec3fb09821e25b04feaac818b7f1f21288afde3ccdedc50fc29603e | Python | 3,580 | 97 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# Set up custom environment before nearly anything else is imported
# NOTE: this should be the first import (no not reorder)
from maskrcnn_benchmark.utils.env import setup_environment # noqa F401 isort:skip
import argparse
import os
import torch... |
1db617c824ed58548a172921f68751de5da8b484a98813578332fd15ff4a125e | Python | 3,582 | 99 | import argparse
import os
import pandas as pd
import numpy as np
from rdkit import Chem
from rdkit.Chem import MolFromSmiles, MolToSmiles, AllChem, Descriptors
from rdkit import DataStructs
from rdkit.Chem import Descriptors
import chemprop
from chemprop.args import TrainArgs, PredictArgs
from chemprop.train import cr... |
29374799b285b13b3ab8be2e800640df92b4c47c8f70e1f1a58feef848cc3ca5 | Python | 3,582 | 94 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
9b0eddfd204f157dead7d5ccf31306f2ba57c8c008a726e3b13523414ba844b4 | Python | 3,582 | 90 | # Code adapted from here:
# https://github.com/joe3141592/PyTorch-CAM
import numpy as np
import torch
import matplotlib.pyplot as plt
import skimage.transform
from aug_accuracy import InputError
class ActivationMap:
def __init__(self, model):
'''The initializer needs to find the final layer before avgpool... |
d2bd169f054189b37a5ff62fe27b6d675d30423ea0582bb257e047033af06932 | Python | 3,583 | 121 | import logging
from typing import Union
import numpy as np
import torch
from rich.console import Console
from rich.logging import RichHandler
from ._compat import Literal
logger = logging.getLogger(__name__)
scvi_logger = logging.getLogger("scvi")
class ScviConfig:
"""
Config manager for scvi-tools.
E... |
f3452f15848773c60b38034f77ad488c425802c75cdcdc2168e74eee477e6c02 | Python | 3,583 | 123 | from setuptools import setup, Extension
from setuptools.command.build_ext import build_ext
import sys
import setuptools
import os
__version__ = '1.3.1'
def read(fname):
return open(os.path.join(os.path.dirname(__file__), fname)).read()
class GetPybindInclude(object):
"""Helper class to determine the pybind... |
fb7da6534cf7c93344363e8bb29f2ac655d8ca32f5eed5c32f21481202ca08dd | Python | 3,583 | 108 | #!/usr/bin/env python
""" TL info printer
"""
# Copyright (c) 2026 Computer Vision Center (CVC) at the Universitat Autonoma de
# Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
# ====================================================... |
2687c335aea9e3bbc776cf747857cec6bdefa475b00753bd473d1e9f3e6f5c81 | Python | 3,588 | 109 | __author__ = "Jianfeng Sun"
__version__ = "v1.0"
__copyright__ = "Copyright 2023"
__license__ = "GPL v3.0"
__email__ = "jianfeng.sunmt@gmail.com"
__maintainer__ = "Jianfeng Sun"
import time
class Single:
"""It offers methods to perform a sliding window op for each of central
residue pairs for a given sequ... |
3326f5994e5486d3f21f5986c7579c818ddb6600e4323012d32bc6c426ba7e73 | Python | 3,590 | 124 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
500ebb1a27d06533940852f2779d5ffb72f8e8bd54c24917bb530d37948c822a | Python | 3,590 | 90 | import argparse
import gzip
parser = argparse.ArgumentParser(description='Merge MetaBrain with eQTLs from eqtlGen et al.')
parser.add_argument('eqtlGen_eqtls', help='eQTLs from eqtlGen')
parser.add_argument('name', help='name that is given in output columns')
parser.add_argument('MetaBrain_eqtls', help='eQTLs from Meta... |
9ab4f7714d18e4f5b15db6258fb554e03cd2d3bb4499d1ba0808902754c85d75 | Python | 3,591 | 125 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
e6d037a35223220fb4b1305c9e03a9e8bf150ddaed283768a7dfa7fab621d8a7 | Python | 3,591 | 104 | import torch
from sklearn import metrics
import numpy as np
def accuracy(output, target):
with torch.no_grad():
pred = torch.argmax(output, dim=1)
assert pred.shape[0] == len(target)
correct = 0
correct += torch.sum(pred == target).item()
return correct / len(target)
def prec... |
bdf7590f7d48b97836a9a985aa099dbb432a386a8d19a034bd1fa86958a18c21 | Python | 3,592 | 114 | """Tools for importing data through mne.
.. autosummary::
:toctree: generated
events
epochs
mne_epochs
add_epochs
add_mne_epochs
epochs_ndvar
evoked_ndvar
sensor_dim
stc_ndvar
forward_operator
inverse_operator
DatasetSTCLoader
.. currentmodule:: eelbrain
Managing events with ... |
8d1b465391630d294a164bd64bbf70a4430c79d9dab0c35d43eac19dbba8a228 | Python | 3,593 | 84 | import synapseclient
import getpass
import synapseutils
import glob
user = input("Synapse username:")
password = getpass.getpass('Synapse password:')
syn = synapseclient.Synapse()
syn.login(user,password)
samples_processed = {'featureCounts':set([]), 'kallisto':set([]), 'rMats':set([])}
studies = ['MayoTCX','MayoCBE'... |
a7f0d189b176d27cda89f5c38c7dcc4f6bb1901c940aa08223e72d09f5821487 | Python | 3,593 | 85 | import torch
import torch.nn as nn
import torchvision.models as models
from torch.nn.utils.rnn import pack_padded_sequence
from torch.autograd import Variable
from recurrent_rsa.rsa_utils.build_vocab import Vocabulary
import pickle
class EncoderCNN(nn.Module):
def __init__(self, embed_size):
"""Load the p... |
818150f2ea9741277684d6e6d374fc145381c9d865c84a3fc29de33e7e13a433 | Python | 3,595 | 125 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
8919f702e2a534621ea17efa117091f9029c20df5adb87c42e437211ba7fa2f1 | Python | 3,595 | 118 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from slideflow.clam.models.model_mil import MIL_fc, MIL_fc_mc
from slideflow.clam.models.model_clam import CLAM_SB, CLAM_MB
import pdb
import os
import pandas as pd
from slideflow.clam.utils import *
from slideflow.clam.utils.core_ut... |
bdc2128428522aacb40beeaeeb8499a1d4fedc8c5eba32a9f58ba00f9b1bd374 | Python | 3,595 | 125 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
d29fc3fd54602130e60d3ee3d7246a026a42b8f70a47a3b3cad9a6e15ff6cb89 | Python | 3,595 | 125 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
6c3d55b26e2f4c3445edb00f50540d606a8a83cf153098cfad359d3988152121 | Python | 3,596 | 145 | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 20 18:47:06 2021
@author: N.V
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib.animation import FuncAnimation
import os
# note that this must be executed before 'import numba'
os.environ['NUMBA_DISABLE_INTEL_... |
1ba37cf9a35b32b2fb77befb595d8e6031c651a1efc60f70463294e3fbd6471c | Python | 3,597 | 95 | #!/usr/bin/env python3
#
# Copyright (c) 2018 Institute for Basic Science
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to u... |
0e7070bbdeb8e3394e7505a58f4f6be8a3beffea854070e085ffeac1eaca7c9c | Python | 3,598 | 145 | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 20 18:47:06 2021
@author: N.V
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib.animation import FuncAnimation
import os
# note that this must be executed before 'import numba'
os.environ['NUMBA_DISABLE_INTEL_... |
d1fa01a10450f90515fceb7df4e4e8b98dc3ea4b503292b9868090077c400a0b | Python | 3,600 | 102 | import torch
import torch.nn as nn
import torchvision
import torchvision.transforms as transforms
# Device configuration
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
# Hyper-parameters
sequence_length = 28
input_size = 28
hidden_size = 128
num_layers = 2
num_classes = 10
batch_size = 100
nu... |
33d50323e463ba80d672496bfe7de5f25a2fc1042124f4981c1264d855a0f354 | Python | 3,601 | 125 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
7b6cfef99bc416539c17f464e324dcb47adda49618c02cbfd5a5860b8da56949 | Python | 3,601 | 125 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
b08d639048dd658a31f453d1b6338cdad7493ecd4dafeb61b606e6c4b6a8f9d7 | Python | 3,601 | 129 | # model settings
model = dict(
type='RetinaNet',
pretrained=dict(
use_load=True,
load_path='./seed_mbv2.pt',
seed_num_layers=[1, 1, 2, 3, 4, 3, 3, 1, 1] # mbv2
),
backbone=dict(
type='FNA_Retinanet',
net_config="""[[32, 16], ['k3_e1'], 1]|
[[16, 24], ['k3_e6',... |
e027177f48bd828ad6ebb5103a9c97db7b52e67f038adb8c0180d815d807dea6 | Python | 3,601 | 125 | import csv
import os
import sys
def feature_to_index(cases, column_nb, offset=0):
feature_set = set()
for case in cases:
if len(case) > column_nb:
feature_set.add(case[column_nb])
l = list(feature_set)
index = {}
i = 0
for f in l:
if f != '':
index[f] = i... |
7f81f4a522175382dcb21dbe69aab24f1c9d36e35a54ca026803e978e57a4e85 | Python | 3,603 | 84 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
d557caf0a727a24e9440345a1bc961628cc7b1f02f5342e27cd057485932c116 | Python | 3,603 | 101 | from dataclasses import dataclass
from typing import List
from lark import Lark, Transformer
from deprecated.classic import deprecated
from oaklib.datamodels.search_datamodel import SearchBaseConfiguration, SearchProperty, SearchTermSyntax
from oaklib.datamodels.vocabulary import LABEL_PREDICATE, SYNONYM_PREDICATES
f... |
e93b48fb1c951667ad7e9b1ab4a7f2e6edb96fa489516bf275159cb579f201c6 | Python | 3,603 | 96 | """ this code establishes the real-time port b/t FDTD and Python to enable state and reward passes
for optimization of photonic crystals by RL. NOEL, Renjie Li, December 2021
The simulation file used here is taken directly from Loncar's paper: Deterministic design of wavelength scale,
ultra-high Q photo... |
bbfaf2004c74c76a2ef0857bfd10a112934ee85fbdffe1ee824444a71551c9cd | Python | 3,604 | 101 | import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import mean_absolute_error, mean_squared_error, mean_absolute_error
from sklearn.model_selection import cross_val_score
from sklearn.model_selection impor... |
cb8853f8d0bb411de2b6730c710cc268562f21e81c0607eb5d56b291c574663c | Python | 3,604 | 110 | import torch
import torch.nn as nn
import torch.nn.functional as F
class TextEncoder(nn.Module):
def __init__(self, channels, kernel_size, depth, n_symbols):
super().__init__()
self.embedding = nn.Embedding(n_symbols, channels)
padding = (kernel_size - 1) // 2
self.cnn = list()
... |
dedd7f840228794b39789e9dee897013963a2591551d3b15c11f33c65134c215 | Python | 3,604 | 96 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
import os
import sys
sys.path.insert(0, os.path.abspath('../..'))
sys.path.insert(0, os.path.abspath('../../..'))
sy... |
53df5e41506c455697b6b532ef113ad3aaa6467bfde982721c19fde11dcdf58f | Python | 3,605 | 85 | import pandas as pd
import glob
import os
import numpy as np
import sys
from sklearn.metrics import roc_auc_score, precision_score, recall_score, accuracy_score
atac_data = ['BICCN2', 'GSE111586', 'GSE123576', 'GSE126074', 'GSE127257', 'GSE1303990']
rna_data = ['BICCN2', 'GSE126074', 'GSE1303990']
rna_data = ['BICCN2'... |
7fff9547160724ea5aa8c724dceba1a8b76fa106c4100113f8f686d09a5bc57c | Python | 3,607 | 144 | # encoding: utf-8
from __future__ import absolute_import, division, print_function
import argparse
import os.path as osp
import sys
import time
import numpy as np
import torch.utils.model_zoo as model_zoo
from easydict import EasyDict as edict
C = edict()
config = C
cfg = C
C.seed = 12345
"""please config ROOT_d... |
214664a078929896a996f8a15c497f042552edcf9c7f7631d2b7ccc349340199 | Python | 3,609 | 107 | import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, kaiming_init
from mmdet.core import auto_fp16, force_fp32
from mmdet.models.builder import HEADS
@HEADS.register_module()
class FusedSemanticHead(nn.Module):
r"""Multi-level fused semantic segmentation head.
.. code-block... |
4db15047c5801f2d96376bc91ae3737a17b87c43b2b3dea085e78762dfcb2eb5 | Python | 3,609 | 111 | from dolfin import Cell, Expression, UserExpression
import numpy as np
def cell_orientation(is_1d_in_3d):
'''A line mesh in 3d cannot be oriented - fall back to 0'''
return lambda cell: cell.orientation() if not is_1d_in_3d else 0
class DegreeOfFreedom(object):
'''Evaluator of dof of V on functions'''
... |
38a059a79a7a18202ec0073c05afb123f37069e40d31e65a2c52269d41f19347 | Python | 3,610 | 125 | # -*- coding: utf-8 -*-
"""
Created on Fri May 14 23:06:21 2021
@author: Sleepymouse
"""
import glob
import numpy as np
import pandas as pd
from scipy.stats import chi2
import sympy
import csv
import matplotlib.pyplot as plt
import sys
#wheel managerから排出されたファイルは.csv形式（名前は.xls）なので、.xlsに変換sにて保存しなおしてから使用すること
#mac
#path... |
eb75d9373ce5534721f468706e229713a92cf92ddde0d456da572e5d4672bcf2 | Python | 3,612 | 105 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
d3aa3a221a9f4f8c0988f239d3602c76300b0bda02853eff961a22111d4a079b | Python | 3,613 | 108 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# 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
#
# httpwww.apache.orglicensesLICENSE-2.0
#
# Unless required by applicable law or agreed to in wri... |
f09c357b2ddf9fc027d539dd533225bfdd5977bcfeebe264721c75b7c2e20fe7 | Python | 3,613 | 88 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to... |
e7ace105db659e9a9aec4c431323f9702f2eb4dd97d361d6464ff215b09e10b2 | Python | 3,615 | 127 | '''
To add/improve:
- objects are solid color or trimesh
- exclude large arrows in vicinity of singularity
'''
import numpy as np
import FBEM
import matplotlib.pyplot as plt
def _get_keys(projection):
if projection == 'xy':
keyX = 0
keyY = 1
keyZ = 2
elif projection == 'xz':
ke... |
79245ec8076e547ed005d8a44696a4687742f26826fd4a7ef8ccf91bfed0f334 | Python | 3,616 | 97 | # This script is part of navis (http://www.github.com/schlegelp/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of... |
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