sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
99ba21fc6acd40c1527470b6a0b8ce29551608c18d8b2253ed7aea070d577cdb | Python | 3,755 | 128 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import os
import pickle
import random
import ase
import numpy as np
import pytest
from fairchem.data.o... |
b53c8a0697c6a8a18f5565038846995ff9592a04f702ba096dabf481650deab9 | Python | 3,755 | 106 | import enum
import logging
import os
from typing import TYPE_CHECKING
from .base_autoscaling_coordinator import (
AutoscalingCoordinator,
ResourceDict,
ResourceRequestPriority,
)
from .base_cluster_autoscaler import ClusterAutoscaler
from .default_autoscaling_coordinator import (
DefaultAutoscalingCoor... |
88788f3ed3da7ab5304f1b11a387648e3ae836d743e301e755124000260e97ed | Python | 3,756 | 121 | r"""
Temporary compatibility helpers for loading datastores pickled with older Neo.
TODO: Remove this module once pre-neo==0.14.0 datastore pickles no longer need
to be supported. When bumping Neo for good, also update README.rst and the
GitHub Actions install command.
"""
from contextlib import contextmanager
from ... |
f420e98f68db7e9289463ac1d80c8c81c7ca8d2a8b1e15ce4597c1d62ce4eefc | Python | 3,757 | 83 | """Filtering primitives. PCA/tuning use correlation; final Gabor uses convolution."""
import math
import torch
from torch.nn import functional as F
from scipy.fft import next_fast_len
def correlate_valid(x, kernels, stride=1, backend="auto"):
"""x: [B,1,H,W], kernels: [K,1,h,w]. Real-valued valid correlation."""
... |
8ddebbc0f08404af2e157f2555bf7b4b04c768610cc2b19a69780a64fe86fba0 | Python | 3,758 | 96 | import collections
import inspect
from ray.dashboard.optional_deps import aiohttp
from ray.dashboard.routes import BaseRouteTable
from ray.dashboard.subprocesses.handle import SubprocessModuleHandle
from ray.dashboard.subprocesses.utils import ResponseType
class SubprocessRouteTable(BaseRouteTable):
"""
A ro... |
ca2a8a4350919c1854fe2a23e0f1933e17eca065502e70fec09f2f9ea9d01785 | Python | 3,758 | 116 | import sys
import networkx as nx
# Add package path
packagepath = '../kcorePercolation' # Manually specify the path to your script
sys.path.append(packagepath)
from utils import kcorePercolation as kp # Import custom utility functions
def GetfailedGCC(G, removed_node_set):
'''
Calculate the size of the large... |
93aafe139b451900cfdd3bcfa32dd639037c75caa0f0a8bc10c47c1589e3bb5e | Python | 3,759 | 123 | from pickle import FALSE
from datagenerator_pd import DataGenerator
from sklearn.metrics import confusion_matrix, accuracy_score, roc_curve, auc
from tensorflow.keras.utils import to_categorical
import matplotlib.pyplot as plt
import seaborn as sns
import SimpleITK as sitk
import pandas as pd
import numpy as np... |
9c276c2ab5119a87b2fe2a6b3d79614a749ef9eb13e6f3daa5100566b0dbb6a2 | Python | 3,759 | 143 | #!/usr/bin/env python3
import rospy
from std_msgs.msg import MultiArrayDimension,Int8MultiArray
import cv2
from cv_bridge import CvBridge
import ros_numpy
import numpy as np
import PIL.Image
import io
from torch2trt import torch2trt
from torch2trt import TRTModule
import torch
from torchvision import transforms
f... |
4204dadfdac17e5f9d061e23aefb977340033fc5b80c9c71f9162505fcbbb975 | Python | 3,760 | 99 | import numpy as np
import pickle as pkl
from multiprocessing import Pool
from utils import load_json_file, dump_as_pickle, load_pickle
from pathlib import Path
from torch import load
from glob import glob
import sys
import gc
import torch
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
from eval.eval_utils impor... |
71462a25020084ab88120883b4a27dc30fe2503e24d416a27e800f6928a5fe83 | Python | 3,761 | 118 | import os
os.environ["TESTING"] = "true"
from pathlib import Path
import nbformat
import papermill as pm
import pytest
import torch
pytestmark = pytest.mark.slow
examples_path = Path(__file__).parent.parent / "examples"
# List of notebook names
notebooks = [
pytest.param("01_flyvision_connectome.ipynb", marks=[]... |
4373e4dac866ab6a1a9ea793f2ce8c72959de5be90df5bddd8733c98bdc3da57 | Python | 3,762 | 130 | from scipy.io import loadmat
from scipy.special import erfcinv
import numpy as np
import pandas as pd
from scipy.stats import kstest, chi2_contingency
from itertools import combinations
def star(p_val):
assert 0 <= p_val <= 1
if p_val >= 0.05:
return 'ns'
if p_val >= 0.01:
return '*'
... |
38ffa28249b92f0153969bce1bfd6dcb6b97d1ce2188505c5879bcf92ab1a247 | Python | 3,763 | 90 | import sys
sys.path.insert(0, "/srv/home/zgaleday/torch_pgn")
from torch_pgn.args import TrainArgs, HyperoptArgs, DataArgs
from torch_pgn.load_data import process_raw
from scripts.generate_final_correlations import generate_final_correlations
import os
import os.path as osp
def generate_datasets(raw_path_1, raw_path... |
b8776fa53534647aec58f821bb1fcf7c23fcfd87e12beb1d2d34b67c4e1fbe69 | Python | 3,763 | 146 | # POINT METRICS
from scipy.spatial.distance import directed_hausdorff
import numpy as np
import persim
import cv2
import alphashape
from skimage.metrics import mean_squared_error
from skimage.metrics import structural_similarity as ssim
def hausdorff(set1, set2):
"""
Given two sets of points, compute their ha... |
cff06282a60cb950bb127cabd033db6284e33171adabc1db34ea3379d4b1cc3b | Python | 3,763 | 107 | import os
import pandas as pd
from src.commons.process_dataframe import keep_valid_columns, change_col_value_type, insert_new_col_from_two_cols, \
get_sub_df_according2col_value, get_mean, get_std
from src.commons.process_number import get_deviation, get_percent_change
from src.constants.ms2_uniform_prolific_1_con... |
a6e4a4495474a97b58c44453d18288c3dc6957ae6cf63613a4180cd5b7b819f6 | Python | 3,764 | 116 | from os.path import splitext
from os import listdir
import numpy as np
from glob import glob
import torch
from torch.utils.data import Dataset
import logging
from PIL import Image
import os
class BasicDataset(Dataset):
def __init__(self, root, scale=1, direction='AtoB',norm='std'):
# self.imgs_dir = imgs... |
30398e419fc0909d716295e76889aebe2758a6bca0a4c54c174e8759805ed308 | Python | 3,768 | 91 | import numpy as np
import os
import json
import math
from scipy.stats import chi2_contingency, wilcoxon, mannwhitneyu, shapiro, linregress
from ..io import SAVED_DIR, RESULTS_DIR, load_network, load_params, load_responsiveness, load_activity
from ..analysis import find_response_range, parse_activity, find_stimulus_rang... |
67404973a3a6e3d2cc10b75d6f695b6922999f5c1021960d805907b2b0158c1e | Python | 3,768 | 91 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
78ede641509982184fd569c60dfd909fe161eb2fe9f633b75546d317295e9294 | Python | 3,768 | 112 |
import numpy
import random
import sys
sys.path.insert(0, "..")
from scipy import stats, special
from sklearn.preprocessing import PolynomialFeatures
from matplotlib import pyplot
import matplotlib; matplotlib.use("MacOSX")
from banditopt import algorithms
# numpy.random.seed(42)
# random.seed(42)
class Sampler:
... |
60d2865ce54f1250b24bff8fc27ca02ee7fbc81e4850804ad2732e27b6e3574b | Python | 3,770 | 107 | import sys
import os
sys.path.insert(0, "/srv/home/zgaleday/torch_pgn")
from torch_pgn.train.Trainer import Trainer
from torch_pgn.train.train_utils import load_args
from torch_pgn.train.run_training import run_training
import numpy as np
import pandas as pd
import os.path as osp
import os
def generate_final_corre... |
cb15a62a094bf4d480ee4ad7bc62de7d997b6363bb5787b62c32663ddbd3ecda | Python | 3,770 | 124 |
from numpy import inf
def parse_deseq_file(path, lfc_cutoff = 1.5, pval_cutoff = 0.05, sep = '\t'):
up_genes, down_genes = [],[]
with open(path, 'r') as f:
skipped_header = False
for i, line in enumerate(f):
if i > 0 and not (line == '' or line == '\n'):
... |
295a0b56cc313bd0c6dcd146ffc267b29bce0df685191c6b5ee53ea6ef0dac59 | Python | 3,771 | 110 | # Copyright (c) DP Technology.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
from functools import lru_cache
from unicore.data import BaseWrapperDataset
class TTADataset(BaseWrapperDataset):
def __init__(self, datase... |
b60b7a95a4aaac1f9d64ad4f2c91b08e0d565be2993a776eb5a1388e1fe6049f | Python | 3,771 | 95 | import unittest
from copy import deepcopy
import torch
from rising.transforms.functional import box_to_seg, filter_keys, instance_to_semantic, pop_keys, seg_to_box
class TestSegBox(unittest.TestCase):
def setUp(self) -> None:
self.seg = torch.zeros(10, 10, 10, dtype=torch.long)
self.seg[1:3, 1:3... |
e7f425f209caa7d489f982ffd5c92818042f4744563171a399b7f05e9935f90c | Python | 3,773 | 133 | import time
import numpy as np
from discontinuous_galerkin.base.base_model import BaseModel
from discontinuous_galerkin.start_up_routines.start_up_1D import StartUp1D
import matplotlib.pyplot as plt
import pdb
import oci
import scipy.stats
import yaml
from matplotlib.animation import FuncAnimation
import ray
from gene... |
556b0c27e057c761aa31188d093ecde81c0eedf29b17ffdaebec5432f420dea6 | Python | 3,774 | 107 | # -*- coding: utf-8 -*-
"""Common tools for interactive 3D/4D visualization on Jupyter Notebook and Jupyter Lab."""
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
from ipywidgets import interact, IntSlider
from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar
def volume(v,... |
116f60291bc4743438ba0331212459df2a0a389dd03f6f9d1ea5d081052ff5a0 | Python | 3,775 | 96 | import json
import os
import subprocess
import boto3
DOCKER_USER = None
DOCKER_PASS = None
def _get_curr_dir():
return os.path.dirname(os.path.realpath(__file__))
def get_secrets():
global DOCKER_PASS, DOCKER_USER
secret_name = "dockerRetagLatestCredentials"
region_name = "us-west-2"
session ... |
12be228b98bf29752a7d3e4a017d3b8e0d09a3ada8d6791888e1ef8a00f788d4 | Python | 3,775 | 125 | """Hermetic test for the in-repo ``myst_eval_rst_doctree`` Sphinx extension.
Builds a tiny Sphinx project in a temp dir (in-process, no network, no Ray
import) with a Markdown page whose ``{eval-rst}`` block holds a bullet list and
a Python domain signature, then loads the pickled doctree and checks the
following:
* ... |
2c181aef0df53a938133762388cf7077418200fa97ee1c03a0c052182a5b7643 | Python | 3,776 | 97 | import numpy as np
import pickle as pkl
from multiprocessing import Pool
from utils import load_json_file, dump_as_pickle, load_pickle
from pathlib import Path
from keras.models import load_model
from glob import glob
import sys
import gc
from eval.eval_utils import calculate_metrics
def main():
config = l... |
df1f87c3f7b91fd13dce2899eeaf0d5467185d7e052c5f0da0206011bc18b3a4 | Python | 3,776 | 100 | import torch
import torch.nn as nn
import torch.nn.functional as F
class SACNN(nn.Module):
def __init__(self, input_channels=3):
super(SACNN, self).__init__()
# Block 1
self.block1_conv1 = nn.Conv2d(input_channels, 64, kernel_size=3, padding=1)
self.block1_conv2 = nn.Conv2d... |
40cd5242e49ae2c3166d24edd7e8e2221d490d355b9f2cfc4412ae50f701a671 | Python | 3,777 | 119 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
Run before 04_integrate_batches
"""
import argparse
import firecloud.api as fapi
from firecloud import fccore
from firecloud import errors as ferrors
from google.cloud import storage
fcconfig = fccore.config_parse()
def get_bucket_name(namespace, workspace):
... |
503e6c0f4ec3a4e77abc29dc3130950c3ea5383fe9789ef5b335aa6e17b33b71 | Python | 3,778 | 128 | # %%
#
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import seaborn as sns
import create_new_target_data as cnd
import SSN_model_funcs as ssn
from cycler import cycler
import pickle
from tqdm import tqdm
tqdm.pandas()
from pandarallel import pandarallel
pandarallel.... |
e20a018cae90bd13f5658a7e54bc2466267eff7ef61697c2e2219d771a846773 | Python | 3,779 | 100 | import torch
import torch.nn as nn
import torch.nn.functional as F
class PLReMixModel(nn.Module):
def __init__(self, backbone, dataset, n_clusters, n_heads=2):
super(PLReMixModel, self).__init__()
self.backbone_dim = backbone['dim']
self.n_heads = n_heads # 不是class numer
self.data... |
f756b5e0a3c09f28d298d78335feae559bf4455c3816fab8733056a94925f7e0 | Python | 3,781 | 99 | """Shared adapter for the optional :mod:`pymclustR` backend.
This replaces the ``rpy2`` bridge the spatial wrappers used to embed, so an R
installation is no longer required. For the ``EEE`` model those wrappers all
default to, the substitution is numerically transparent: on a real 700-cell
PCA embedding, ``pymclustR`... |
826b9b56ad1865bc50d508be1a221b2473410f0e43d7a6d7a45b81b91d726448 | Python | 3,783 | 105 | """
Pyspark counts
"""
from typing import Tuple
import pandas as pd
from pyspark.sql import DataFrame
from pyspark.sql import functions as F
from pyspark.sql import types as T
from data_profiling.config import Settings
from data_profiling.model.summary_algorithms import describe_counts
@describe_counts.register... |
d5bbbd4ea409e7d40b016bd459c0bc91581b5056095874214a82bb168496d8c0 | Python | 3,783 | 104 | import unittest
import io
import numpy as np
import vamb
import testtools
from vamb.parsecontigs import CompositionMetaData
class TestParseBam(unittest.TestCase):
@classmethod
def setUpClass(cls):
minlen = 3000
mask = np.array(
list(map(lambda x: x >= minlen, testtools.BAM_SEQ_LEN... |
aa2c7d435661c4f0752bbb8af8f8f3b090eeed61c629beb2dcaf72d652b487c0 | Python | 3,786 | 124 | # myhist.py
# Copyright (c) 2010 Jes Frellsen
#
# This file is part of Muninn.
#
# Muninn is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 3 as
# published by the Free Software Foundation.
#
# Muninn is distributed in the hope that it will be useful,... |
ecc07802e740ccbae745e5abaf946e161d32cdfa44f82c91e92e6e278bbba78c | Python | 3,787 | 104 | import os
import sys
import json
import logging
import neuron_morphology.swc_io as swc
import neuron_morphology.validation as validation
from neuron_morphology.validation.result import *
import neuron_morphology.marker as marker
from neuron_morphology.validation.report import Report
import argparse
import glob
import n... |
d4b45a8c2170ec66359293f5fcd45f80afc23e4bc59c165bc03678ecc815bfcc | Python | 3,788 | 115 | from typing import Any, Dict, List, Optional, Union
import torch
from ray.air._internal.device_manager import get_torch_device_manager_by_context
def get_devices() -> List[torch.device]:
"""Gets the correct torch device list configured for this process.
Returns a list of torch accelerator (GPU, HPU, NPU...... |
60b3b4e2e23b86fb71610c27d2690bd9b1a5c0787f61fae6902d6935011246af | Python | 3,789 | 138 | """Plotting functions for the missing values diagrams"""
from typing import Any, List
from matplotlib import pyplot as plt
from data_profiling.config import Settings
from data_profiling.visualisation.context import manage_matplotlib_context
from data_profiling.visualisation.plot import (
missing_bar,
missing_... |
618aa563531fed43f98a79c92d19f38a818c8a879059092840151fbbdb33d1eb | Python | 3,789 | 137 | """Scaling stimulus responses across durations"""
import os
import glob
import nibabel as nb
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
ROOT = '/Users/sebastiandresbach/github/neurovascularCouplingVASO/results'
SUBS = ['sub-05', 'sub-06', 'sub-07', 'sub-08', 'sub-09'... |
69b2e4bf9f98f50f7f54cd6a8d36c79a114f198760f7b8ad9343f6df6afbb2da | Python | 3,789 | 118 | from __future__ import annotations
from dataclasses import MISSING, dataclass, field, fields, is_dataclass
from typing import Literal
@dataclass
class GlobalConfigs:
regress_forces: bool
direct_forces: bool
hidden_size: int # divisible by 2 and num_heads
num_layers: int
activation: Literal[
... |
83814f4d163ac2bb7f7c8e039e4d0cb9b660456f6ba0b7f0a3cb2d7a8d93dc17 | Python | 3,789 | 130 | from pathlib import Path
from typing import Any, Dict
from ray.autoscaler._private.cli_logger import cli_logger
try: # py3
from shlex import quote
except ImportError: # py2
from pipes import quote
def _check_docker_file_mounts(file_mounts: Dict[str, str]) -> None:
"""Checks if files are passed as file... |
e85f2adabdd8f27b82b8eb0267d28ad1ea673faf29190dc6e94f216a3f712ba8 | Python | 3,789 | 119 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
author: Pengcheng Zhou
email: zhoupc1988@gmail.com
created: 6/16/17
last edited:
"""
import os
from collections import OrderedDict
from PyQt5.QtWidgets import QFileDialog, QWidget, QLabel, QPushButton, \
QLineEdit, QGridLayout, QApplication
# --------------------... |
522a4533370ec97f69105f8d881067fe8b163900f0e0aa8992d1ea7fa89343db | Python | 3,791 | 117 | from typing import List, Literal
import torch
import pandas as pd
import numpy as np
from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn.gaussian_process.kernels import DotProduct, WhiteKernel
from timm.models.vision_transformer import Block as AttentionBlock
import torch.nn as nn
import torch.nn... |
82d10c27672189487cf92e8a38c81c832bfb5b45ac7ff93513e479a076157ea2 | Python | 3,791 | 79 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
b87cd46896b24e2bd2153b6b6be294cad423c62a40bb11b878f5c077b86b927c | Python | 3,791 | 129 | import inspect
import multiprocessing
import random
import re
import types
from functools import partial
from pathlib import Path
from typing import Any, Callable, Generator, Iterable, Optional
import numpy as np
from siapy.core import logger
from siapy.core.exceptions import InvalidInputError
__all__ = [
"initi... |
1726dc1e158d09af472307cd08efd06c0cabf319ffe3abc4c1af40b5bf347064 | Python | 3,793 | 114 | import hashlib
import multiprocessing as mp
import nibabel as nib
import pandas as pd
from os import path
from joblib import Parallel, delayed
from nipype.interfaces import ants, fsl
def measure_sim(image_path, reference,
substitutions=False,
mask='',
metric='MI',
radius_or_number_of_bins=8,
sampling_strategy='N... |
2fb512c971471d2192d8189f578f3e0544f21fe7fb01e550488e38da20a00994 | Python | 3,793 | 95 | import os
import numpy as np
from transformers import AutoTokenizer
import random
import argparse
def parse_arguments():
parser = argparse.ArgumentParser(description='Process the text data for tokenization.')
parser.add_argument("--data_dir", type=str, required=True, help="Directory of the raw data.")
pars... |
8d049ce951fa7f3317b7c05179a972aa9da84a4d277058576411fedf6c4c70c1 | Python | 3,794 | 100 | import numpy as np
import math
class Box:
# def __init__(self,a1,a2,a3,b1,b2,b3,c1,c2,c3):
def __init__(self, *args, **kwargs):
self.mTrans = np.zeros((3,3))
# This will read the different cp2k options how to define a cell
if 'cellfn' in kwargs:
with open(kwargs['cellfn'], '... |
41c58ebb073a76b30d2c7dee89748b1bd4d003b75ddd4c966c5d99bcaf0ffbb9 | Python | 3,795 | 121 | from typing import List
from ipywidgets import widgets
from data_profiling.report.presentation.core.container import Container
from data_profiling.report.presentation.core.renderable import Renderable
def get_name(item: Renderable) -> str:
if hasattr(item, "name"):
return item.name
else:
ret... |
608d77449679d457556bb48dd9f071367b9a3ba7db659b97fa291d43ad86c9ea | Python | 3,796 | 101 | '''
MBEANN settings for solving the OpenAI Gym problem.
'''
class SettingsEA:
# --- Evolutionary algorithm settings. --- #
popSize = 200
maxGeneration = 100 # 0 to (max_generation - 1)
isMaximizingFit = True
eliteSize = 0
tournamentSize = 20
tournamentBestN = 1 # Select best N individua... |
1312319dbe5abd43afb712aec73b163afb8ece3bd1c426c1e7eae16cf3a46f99 | Python | 3,797 | 129 | import torch
import torch.nn as nn
import torch.nn.functional as F
from pfrl import action_value
from pfrl.initializers import init_chainer_default
from pfrl.nn.mlp import MLP
from pfrl.q_function import StateQFunction
def constant_bias_initializer(bias=0.0):
@torch.no_grad()
def init_bias(m):
if isi... |
a5ff8f332cc4ee30c48ffa3d6e90e0c3736c73f013dd917c3064072ef9de1ae8 | Python | 3,799 | 136 | """Prompt templates used by domain research helpers.
The utilities here centralise textual templates for the research pipeline.
Each function returns a formatted prompt string and accepts ``**kwargs`` to
allow model specific customisation without modifying the base templates.
Defaults include a brief description of Om... |
10c4c73bf41b3932613b794ea5cf95967e0d35f12f3cc00e4999d8d4cd450d44 | Python | 3,804 | 91 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
4ba78cca556d55b302350681b34b8dac37e94405397b9af758fefeaa3e1a95b9 | Python | 3,807 | 100 | import torch
import logging
import pandas as pd
from torch.utils.data import TensorDataset, random_split
from sklearn.model_selection import train_test_split
from agent.data.entities.config import FD_CLASS_VALUES, ITEMS_TABLE, CTT3_TEST_ITEM_FILTER, CTT3SIM_LABEL, CTT3_LABEL
from agent.classifiers.utils.class_mgmt im... |
6d66aa05ec5161d4d5be6980ecba2ac0bb70d4d4a5714aaaf159cc4ba86fb99c | Python | 3,807 | 154 | from typing import (
NamedTuple, Set, Dict, Any, Sequence, Type, List, TypeVar, Optional)
import abc
import copy as cp
from neuron_morphology.constants import (
AXON,
APICAL_DENDRITE,
BASAL_DENDRITE,
SOMA
)
from neuron_morphology.feature_extractor.mark import (
Mark,
RequiresAxon,
Req... |
6e77125c8d5bc32232119d7c34a51d895fc063a8824483b208d433be78b12ee7 | Python | 3,807 | 102 | #Include functions to graph different metrics
#Imports
import matplotlib.pyplot as plt
from sklearn.metrics import confusion_matrix
import seaborn as sns
import pandas as pd
colors = plt.rcParams['axes.prop_cycle'].by_key()['color']
#Create precision-recall curve plot
def plot_prc(name, labels, predictions, **kwargs... |
4306a94c1d044fea1094bde42b3740e9611c5cf69aca83a25803858ffad37748 | Python | 3,809 | 128 | # flake8: noqa
# isort: skip_file
# __lightgbm_start__
import pandas as pd
import lightgbm as lgb
# 1. Load your data as a `lightgbm.Dataset`.
train_df = pd.read_csv("s3://ray-example-data/iris/train/1.csv")
eval_df = pd.read_csv("s3://ray-example-data/iris/val/1.csv")
train_X = train_df.drop("target", axis=1)
train... |
1d0f4b1fa63d92f11b67c30e7eeddd0e09926bf6558c39fd74301601dd053d12 | Python | 3,810 | 86 |
import numpy
import gym
import gym.spaces
class GymnasiumWrapper(gym.Wrapper):
def __init__(self, env: gym.Env):
super().__init__(env)
def reset(self, *args, **kwargs):
"""Steps through the environment and if the number of steps elapsed exceeds ``max_episode_steps`` then truncate.
Arg... |
d970a9f175f00e04a39ac7ee125d803f88fce321f5dc115104d9a8204c891582 | Python | 3,810 | 91 | import tensorflow as tf
from models.deep_learning.deep_learning_models import DLRegressor
from utils.constants import is_spline
class BiGRURegressor(DLRegressor):
"""
This is a class implementing the BiGRU model for time series regression.
! Remember to use regularization techniques such as dropout, weigh... |
3fb711de73ca0f4950a99fa82f924c88e46ffe6629f23beda9dab36deef91245 | Python | 3,811 | 105 | import os
import sys
sys.path.append('.')
import cv2
import math
import torch
import argparse
import numpy as np
from torch.nn import functional as F
from model.pytorch_msssim import ssim_matlab
from model.RIFE import Model
from skimage.color import rgb2yuv, yuv2rgb
from yuv_frame_io import YUV_Read,YUV_Write
device = ... |
e7e1d4bf7093fd4f667103cbe25a0b31b5be2acf05bdb67c0f7a10b8defd9a4d | Python | 3,812 | 89 | import os
import numpy as np
import torch
from torch_geometric.data import InMemoryDataset
from torch_geometric.data import Data
from tqdm import tqdm
from torch_pgn.data.data_utils import LigandOnlyPretransform, RemoveProximityEdgesPretransform
"""
Code to load in the processed InteractionGraphs to pytorch geometr... |
71b94711be9327931948fae435ec254dab6a0cb013185bafec1b803bfa00e18e | Python | 3,813 | 98 | import torch
import torch.nn as nn
import numpy as np
from typing import Optional, Tuple, Union
from convex_optim_base.optim_base import BatchParallelDirectSolveProblem
from denoise_inverse_alg.hqs_alg import BatchParallel_HQS_X_Problem
class BatchNoiselessLinear_HQS_XProb(BatchParallelDirectSolveProblem,
... |
adc33ad60f7ae1cf2e202c61b515c72435d6a7dfdbce4d63824c0fe1edf8bdc0 | Python | 3,813 | 98 | import sys
sys.path.insert(0, '..')
import matplotlib.pyplot as plt
import numpy as np
import time
from glmhmm import glm, glm_hmm
from glmhmm.utils import permute_states, find_best_fit, compare_top_weights
from glmhmm.visualize import plot_model_params, plot_loglikelihoods, plot_weights
import matplotlib as mpl
mpl.... |
88913c2179ad617604eb3088171c7e32ca5f82dc942bec49b6258184b32adeaf | Python | 3,814 | 130 | import math
from dataclasses import dataclass
import torch
@dataclass
class Heaviside:
"""Heaviside surrogate gradient with optional shift.
Args:
window: Distance between step of Heaviside surrogate gradient and
threshold, relative to threshold.
"""
window: float = 1.0
def ... |
bbfde36dd966dae68a9d0dfc14eb724f7211a036f0cccedc541c836759a02e8c | Python | 3,815 | 82 | from sklearn.model_selection import GridSearchCV, StratifiedGroupKFold, LeaveOneGroupOut, cross_val_predict
from sklearn.ensemble import AdaBoostClassifier
from sklearn.preprocessing import StandardScaler
from email.message import EmailMessage
import smtplib, ssl
import numpy as np
import datetime
import pickle
# This... |
9bea7b7b7c43fe829e95b2214a6cdfdbcbe62f537abb6d7e92ff63ac5567a100 | Python | 3,816 | 132 | # Before using polynomials to solve for the inflection points of the injury degree-injury
# threshold curve, it is necessary to determine an appropriate fitting range.
# The impact cases of two types form two composite injury degree-injury threshold curves.
# 50 Head-concrete impacts form the first injury degree curve... |
db641aff5fda82618b7a2fa43916bf00b01c3d27860e1844658203e0b9ab52d4 | Python | 3,816 | 119 | """Base collector with common functionality."""
import logging
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional
import hashlib
import json
from sqlalchemy.orm import Session
from src.models.base import get_db
from config import settings
logger = logging.getLogger(__name__)
class B... |
00251007334609006ea0079c9097f52c66309bc1ed3db442c76cd50a87466f8b | Python | 3,818 | 102 | import torch
def print_model(model):
blank = ' '
print('-'*90)
print('|'+' '*11+'weight name'+' '*10+'|' \
+' '*15+'weight shape'+' '*15+'|' \
+' '*3+'number'+' '*3+'|')
print('-'*90)
num_para = 0
type_size = 1 ##如果是浮点数就是4
for index, (key, w_variabl... |
930d0177e3ebf9a1027b2ad3f2efdc4ad488cefc0c1dda6506a850364eb7754d | Python | 3,818 | 87 | import os
import argparse
import numpy as np
from ont_fast5_api.fast5_interface import get_fast5_file
def read_fast5(file_dir, min_length, size, ids=None):
file_count, reads_count, total_len = 0, 0, 0
accepted_reads, rejected_reads, short_reads = 0, 0, 0
reads_array = []
for root, _, files in os.walk(... |
ca0a4cb5bada6af0b484dedfb8c85bea053ef751649c993b8bc3ed0b2a7cf35d | Python | 3,820 | 114 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import random
import numpy as np
import pytest
from ase import Atoms
from ase.data import covalent_rad... |
5ecfdbace40610484101c3710d6adcab6c8f0de394f350e720e9d7fb8ccc5660 | Python | 3,822 | 116 | import logging
import os
import stat
from ray.autoscaler._private.aliyun.utils import AcsClient
# instance status
PENDING = "Pending"
RUNNING = "Running"
STARTING = "Starting"
STOPPING = "Stopping"
STOPPED = "Stopped"
logger = logging.getLogger(__name__)
def bootstrap_aliyun(config):
# print(config["provider"]... |
4859497d6a03aa0af91901fe8e9c41b63bc92b98a5319ccd0a7e6d85c8cf47bb | Python | 3,824 | 102 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import os
import hydra
import pytest
import torch
from omegaconf import OmegaConf
from fairchem.core.... |
de4144d058dc95492213378eb8ddfd1760b06fc164ad893fa01aed7ffe4cc819 | Python | 3,825 | 129 | import contextlib
import itertools
import json
import os
import subprocess
import sys
import tempfile
import pytest
import pfrl
@contextlib.contextmanager
def work_dir(dirname):
orig_dir = os.getcwd()
os.chdir(dirname)
yield
os.chdir(orig_dir)
def test_is_under_git_control():
with tempfile.Te... |
612921d1db6bbd046ce73950101e043e1532de830c484bf6c926e9e26d24b7a7 | Python | 3,826 | 88 | import pandas as pd
from src.commons.process_dataframe import rename_df_col, insert_new_col, insert_new_col_from_two_cols
from src.commons.process_number import cal_SEM
from src.ms2_uniform_prolific_1_main import get_percent_triplets
def get_samplesize(winsize):
if winsize == 0.4:
return 29
else:
... |
c5d01bf088440c27571b1a5325032d75a711fef65b591d05a1cfec7b76025115 | Python | 3,827 | 121 | import sys
import os
import logging
import copy as cp
from typing import List, Tuple, Optional
import numpy as np
from scipy.interpolate import griddata
import xarray as xr
from argschema import ArgSchemaParser
from neuron_morphology.transforms.pia_wm_streamlines._schemas import (
PiaWmStreamlineSchema, OutputP... |
db2d97dda8a71aa52076628c82c96ffd3f68e09cd3ea91fc36586e1b7f886bb8 | Python | 3,828 | 106 | from enum import Enum, auto
from typing import Any, Callable, Dict, List, Optional, Union
from ray.autoscaler._private.cli_logger import cli_logger
class CreateClusterEvent(Enum):
"""Events to track in ray.autoscaler.sdk.create_or_update_cluster.
Attributes:
up_started : Invoked at the beginning of ... |
a957fab4a9a97822d485d0986339d23c5d93e2af2dd7b59d82daffabc2619fe5 | Python | 3,829 | 123 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import time
import torch
from pyJoules.energy_meter import EnergyContext
from pyJoules.device.rapl_device import RaplPackageDomain, RaplDramDomain
from pyJoules.device.nvidia_device import NvidiaGPUDomain
from pyJoules.handler.pandas_handler impor... |
3efa4e8354f84d5ae05873e6ab74ce93ecebac22865c199128465568526eff2f | Python | 3,830 | 108 | import torch
from torch import nn
from torch.distributions import Normal
from lop.utils.miscellaneous import net_init, fc_body, register_hook, kaiming_init, xavier_init, lecun_init, gaussian_init
class Policy(object):
def action(self, x, to_log_features=False):
"""
:param x: tensor of shape [N, 1... |
c04c3d672e24b2527c9a590b137c9f6f7c53fadfddee55697c5c31f4984ab57c | Python | 3,830 | 75 | import torch
from torch._dynamo import OptimizedModule
from torch.nn.parallel import DistributedDataParallel as DDP
import torch.distributed as dist
from nnunetv2.utilities.checkpoints import load_network_weights
from nnunetv2.utilities.ddp import get_ddp_topology
def load_pretrained_weights(network, fname, verbose=... |
7dc6d84c7a4f5939fda5ebc2d7a12ef313002ef9c01539706b98d80681d7b638 | Python | 3,831 | 128 | # -*- coding: utf-8 -*-
#
"""
std_manta.py
Standardize a Manta record.
"""
from collections import deque
from svtk.utils import is_smaller_chrom, parse_bnd_pos, parse_bnd_strands
from .standardize import VCFStandardizer
@VCFStandardizer.register('manta')
class MantaStandardizer(VCFStandardizer):
def standardiz... |
aa18daf3cc613e5281803581c0e067180a5ce0f4289354d68214e2b9831d96c6 | Python | 3,832 | 96 | from itertools import groupby
import numpy as np
import pandas as pd
def fasta_iter(fasta_name):
with open(fasta_name) as fh:
faiter = (x[1] for x in groupby(fh, lambda line: line[0] == ">"))
for header in faiter:
headerStr = header.__next__()[1:].strip().split()[0]#Entire line, add .spl... |
b98a22909395b8bb503850d2c8489d28681a9a0c2e54ca4d56a06c5aedf434e1 | Python | 3,833 | 112 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import logging
import os
from typing import TYPE_CHECKING
import torch
from torch.profiler import Prof... |
83cc2fc295e3a0b4ac82eb216beadee5007065fe11be004aad4e4fdb584201f6 | Python | 3,835 | 113 | r"""Layer B — ESM-2 protein embeddings for downstream ML.
Turn a list of protein sequences into fixed-length vectors (mean-pooled
per-residue representations from an ESM-2 layer). These feed any downstream
model — enzyme property regressors, clustering, function transfer.
"""
from __future__ import annotations
from ... |
db43cace88cbdcea840052759d3cf24057f64eab0c3cff2753ee3e1c4e20bdcf | Python | 3,836 | 71 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'scripts/GUI/ui/ordering_form.ui'
#
# Created by: PyQt5 UI code generator 5.15.6
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt... |
1b28e62bf2f0558e0241f9211919a727709c4b78b139d1899cbc48fcb060a354 | Python | 3,837 | 149 | #!/usr/bin/env python3
import rospy
from std_msgs.msg import MultiArrayDimension,Int8MultiArray
import os
import cv2
from cv_bridge import CvBridge
import ros_numpy
import numpy as np
import PIL.Image
from torch2trt import torch2trt
from torch2trt import TRTModule
import torch
from torchvision import transforms
fro... |
ac82b84bdc31cfa686813165d8a997fee4a1dc4af9f04dc20f2c4861d74c0813 | Python | 3,837 | 115 | #!/bin/env python
import argparse
import pysam
import sys
from typing import Optional, List, Text, Set
def read_variant_ids(path: Text) -> Set[Text]:
"""
Reads a list of variant IDs from a file (one per line).
Parameters
----------
path: Text
path to file containing variant IDs
Retu... |
b3342ddac2d68acc58328cc530ff27e7f7bb5da9b3a1087e0cdcb697ad4e8f3b | Python | 3,837 | 117 |
#!/usr/bin/env python
# encoding: utf-8
import numpy as np
def mw2d(dim,missingAngle=[30,30]):
mw=np.zeros((dim,dim),dtype=np.double)
missingAngle = np.array(missingAngle)
missing=np.pi/180*(90-missingAngle)
for i in range(dim):
for j in range(dim):
y=(i-dim/2)
x=(j-di... |
87f1caf1be9899f2f2b5e1ecfeb00fcd66e59a5b5cb75100da9b0592490ba06d | Python | 3,839 | 108 | #!/usr/bin/env python
#!/usr/local/bin/python
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
import speech_data
sess = tf.InteractiveSession()
batch_size=100
width=height=64
dim=width*height
# # Create the classifier model
x2 = tf.placeholder("float", [batch_size, width, height], name='im... |
3fcbf4285f253ab7236f743d464745b57e6ab59bf49e08348b0411da9a001636 | Python | 3,840 | 111 | from dDR.dDR import dDR
from dDR.PCA import PCA
from dDR.utils.decoding import compute_dprime
import numpy as np
def get_noise_axis(X, stims):
"""
center X then compute first PC
"""
nc = X[stims[0]].shape[0]
Xa = (X[stims[0]] - X[stims[0]].mean(axis=1, keepdims=True)).reshape(nc, -1)
for s in s... |
6e79a9bacf442386b1bc5e310089cbfe1767f4d8497690d3fde371f24c9d010d | Python | 3,840 | 99 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
b08f0a3a0a000709030b46b4de08942663804ee60baf8ff54d3900b27cacca4c | Python | 3,840 | 102 | import logging
import json
from agent.data.entities.config import BACKUPS_PATH
from agent.data.sql.sql_mgmt import execute_query, execute_read_query, select_fields_where, get_connection
logging.basicConfig(format='%(levelname)s : %(message)s', level=logging.INFO)
logger = logging.getLogger(__name__)
logger.setLevel(... |
495ad023f3dc385982257dc0631dc2dfb216e64db6e80bddccefdea4c11160ce | Python | 3,841 | 96 | import os
import torch
def train_one_fold(fold, args, model, logger, train_loader, val_loader, optimizer, loss_fn, scheduler):
# check if model path exists
os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
path='./checkpoints/stage_{}/classes_{}/fold_{}'.format(args.stage, args.num_classes, fold)
if not o... |
baab340fd9c8af985d441545b9d794852077e468a151009d537a59c2e1723e2f | Python | 3,841 | 117 | import numpy as np
import pandas as pd
from tqdm import tqdm
import scipy.sparse as sp
from .Model import Model
from .utils import Transfer_pytorch_Data
import torch
import torch.nn.functional as F
def train_BINARY(adata,
pos_weight=10.0,
hidden_dims=[512, 30],
... |
bee5387f51f44dc4cbb29b7f9c0b943cb2501ee16de5e9ba64d77dc977a36bc3 | Python | 3,841 | 123 | from dataclasses import dataclass
from typing import Callable, List, Optional, Union
import torch
class BackwardClass:
@staticmethod
def backward(ctx, grad_output: torch.tensor):
""""""
(v_mem,) = ctx.saved_tensors
grad = ctx.surrogate_grad_fn(v_mem, ctx.spike_threshold)
grad_... |
f702a45a560fb7c87bbfeea0896ef79b04b8eb57ca060281bc42bebe24bd4d70 | Python | 3,846 | 99 | # coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# 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 ag... |
d6667a3594fc1c0acfc0d551774461f1ac1613dabee9af3fea631d73f4b21f8d | Python | 3,847 | 125 | from modulefinder import Module
import torch
import nni
import sys
import torch.nn.functional as F
import nni.retiarii.nn.pytorch as nn
from nni.retiarii import model_wrapper
from nni.retiarii.evaluator import FunctionalEvaluator
import nni.retiarii.strategy as strategy
from architecture import gnn_list, gnn_list_prot... |
09864529e475355b90a2ede4b6986a01fb17cbc63cec646fb8aef7f367222afc | Python | 3,849 | 119 | """Tests for scoring.py"""
import pytest
import numpy as np
import torch
class TestLossScoring:
@pytest.fixture(scope="module")
def data(self, classifier_data):
return classifier_data
@pytest.fixture(scope="module", params=["mean", "sum"])
def reduction(self, request):
return request... |
28a554d4b9b914b00ceaaca52357f64306de0d7e74d58f2fe6dd7e1601c8ed50 | Python | 3,850 | 70 | # Copyright 2021 Division of Medical Image Computing, German Cancer Research Center (DKFZ)
# and Applied Computer Vision Lab, Helmholtz Imaging Platform
#
# 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 L... |
2dda4369e1e1876712fb76922cec9a935461e2b74457e17bc1d1ffba877390ea | Python | 3,850 | 126 | # -*- coding: utf-8 -*-
"""
Created on Fri Jul 12 15:57:00 2019
@author: ju-bar
Peak functions and functions calculating their jacobians
This code is part of the 'emilys' repository
https://github.com/ju-bar/emilys
published under the GNU General Publishing License, version 3
"""
import numpy as np
# %%
def gauss_2d... |
3b319660f1751d966498d4ce4180cff4dad071ab4677880b86bae384fd701a00 | Python | 3,850 | 117 | import argparse
import pickle
import numpy as np
import pandas as pd
import os
from collections import defaultdict
from queue import PriorityQueue
from pathlib import Path
MAX_DIST = 40000
MAX_PARTNERS = 8
def parse_argument():
parser = argparse.ArgumentParser()
parser.add_argument('--ensg2tss', required=Tr... |
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