sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
304fde18c356a4afa5cf89347b46ccd199b1d787576d67eb526b3349addd79a9 | Python | 2,991 | 88 | """Custom scoring functions"""
import numpy as np
from skorch.dataset import unpack_data
def loss_scoring(net, X, y=None, sample_weight=None):
"""Calculate score using the criterion of the net
Use the exact same logic as during model training to calculate the score.
This function can be used to implem... |
3747171c03694dd1376951d54ad762d5f08daa3a09450db4bc137364f1238778 | Python | 2,993 | 77 | #! /usr/bin/env python3
# ReScience yaml to README converter
# Released under the BSD two-clauses licence
def generate_README(article):
content = (
"**{_.title}**, {_.authors_abbrv}, "
"ReScience {_.journal_volume}(#{_.article_number}), {_.date_published.year}.\n"
"\n"
"**Abstract.... |
9652d81ef18fab48f515eb3c9432872e7d2fe0930058366375d0a9d3a756afee | Python | 2,993 | 79 | import os
from typing import List, Union
import torch
import ray
from ray.air._internal.device_manager.torch_device_manager import TorchDeviceManager
class CUDATorchDeviceManager(TorchDeviceManager):
"""CUDA device manager"""
def is_available(self) -> bool():
return torch.cuda.is_available()
d... |
67cf00527b4d7a2cbbb5315ce499a861174c95207124ad3cd361a89323a2c39a | Python | 2,994 | 93 | #data utils
import argparse
import rasterio as rio
import json
import os
import numpy as np
from torchvision import transforms
from sklearn import preprocessing
import torch
import yaml
import warnings
import pandas as pd
from torch.utils.data.dataloader import default_collate
def read_config(config_path):
"""Read... |
8fc22b0e87288e9d8efc4a2c6be8f599578100bd1d43df99f59a2473644d2b48 | Python | 2,994 | 101 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import os
import warnings
warnings.filterwarnings("ignore")
# load in directories
from language.constants import DATA_DIR
from language.preprocess import Participants
def load_dataframe(
bad_subjs=['p06', 'p08', 'p11', ... |
5b0bf094eba7e5698943534fbdb8349f9888effe8e6711a0dfe54c38641064f0 | Python | 2,995 | 90 | """
ICA and related signal decomposition methods for tedana
"""
import logging
import warnings
import numpy as np
from scipy import stats
from sklearn.decomposition import FastICA
LGR = logging.getLogger("GENERAL")
RepLGR = logging.getLogger("REPORT")
def tedica(data, n_components, fixed_seed, maxit=500, maxrestart... |
5a0a441267624d1d7c319eb714f818dc615920c52390dac11b3b25ce18454e61 | Python | 2,996 | 81 | import pathlib
path = pathlib.Path.cwd()
if path.stem == 'tmb_survival':
cwd = path
else:
cwd = list(path.parents)[::-1][path.parts.index('tmb_survival')]
import sys
sys.path.append(str(cwd))
from model import utils
from matplotlib import pyplot as plt
import seaborn as sns
import numpy as np
import pickle
t =... |
71c950d90880ff3b69bcef14d2d45ff25ae0b2df6f8f7fffa9a385cb606bdf1b | Python | 2,997 | 87 | # 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... |
d2fce6d4ce69b53d6cef1daf60051bee03e533b4a66c840034738d84b6657bc2 | Python | 2,997 | 89 | import os
from typing import List, Optional
from ci.ray_ci.configs import DEFAULT_ARCHITECTURE, PYTHON_VERSIONS
from ci.ray_ci.container import _DOCKER_ECR_REPO
from ci.ray_ci.docker_container import RAY_REPO_MAP, DockerContainer, RayType
from ci.ray_ci.utils import RAY_VERSION, docker_pull
from ray_release.configs.g... |
c3ae10eddbd0f2e3d396a6816825631cf9107dac0d2176d83b17e6407d09f01b | Python | 2,998 | 82 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Runner that executes Experiments locally."""
from typing import Dict, Optional
from torch import device as torch_device
from torchvision.datasets import Fas... |
f7e6528e1a11b3b0262aef1f34fce096c6e54f345771e3bce1d8b38aefd170f7 | Python | 2,998 | 104 | import cv2
from albumentations import Compose, PadIfNeeded
from transforms.albu import IsotropicResize
import numpy as np
import os
import cv2
import torch
from statistics import mean
approaches = {1: "FaceShifter", 2: "FS-GAN", 3: "DeepFakes", 4: "BlendFace", 5: "MMReplacement", 6: "DeepFakes-StarGAN-Stack", 7: "Talk... |
a17b8a161117d32a1adc7e5c9f540033780204c4e4e9e3046e82e7ccf3b0668b | Python | 2,999 | 87 | # -*- coding: utf-8 -*-
import socket
import struct
import time
import numpy as np
import pdb
from power_readout import *
def dB2inten(dB):
inten = 1000 * (10 ** (dB / 10))
return inten
class VoltageOperator(object):
def __init__(self):
self._addr = ("XXX", 7)
self._sock =... |
1bbd95a93eeb185a90007703c4bb604a15d9117cbb53924d22d7f5814754e5e5 | Python | 3,000 | 78 | import tensorflow as tf
# from tensorflow.keras import backend as K
import os, sys
import h5py
import matplotlib.pyplot as plt
from utils import *
import gc
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib.pyplot as plt; plt.rcdefaults()
from tqdm import tqdm
import warni... |
f4ca0025fab13ac5a1ca14aa08dc991acdc2311fcd23773fb235193df3406cb7 | Python | 3,000 | 93 | # Copyright 2023 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
7b4e5007926936cc3ed65c03cae49568604b34c3ea1d05cb67fb52f18a3dfe26 | Python | 3,001 | 80 | import seaborn as sns
import matplotlib.pyplot as plt
from Bio import SeqIO
import sys, os
import pandas as pd
import numpy as np
type = sys.argv[1]
target = "pos_MANE"
project_root = "../../train/src/INPUTS/800bp/"
output_dir = f"../../results/mutation/{target}/scores/"
def plot_violin(df, target):
plt.figure(fi... |
b9715d258509b1db75426acbb10655213519752ae4120cd873a79b6283b5edbd | Python | 3,001 | 93 | import torch
from torch import nn
from torchvision import models
class ResNetFeatures(nn.Module):
def __init__(self, resnet=50):
super().__init__()
if resnet == 18:
self.r = models.resnet18(pretrained=False)
elif resnet == 34:
self.r = models.resnet34(pretrained=Fal... |
40ffc4539eaea88dd453465c259ddd59e251a063fc213640154856f31eeb4abf | Python | 3,002 | 115 | """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
"""
import os
import sys
import mock
# -- Path setup --------------------------------------... |
58f98aedd0fb912fd1b20b348e173f9ba6069aa9a89a55cdb8f8887e75c9c748 | Python | 3,004 | 100 | import importlib
import ray
import yaml
import pdb
import numpy as np
from matplotlib import pyplot as plt
from data_assimilation.utils import create_directory
TEST_CASE = 'multi_phase_pipeflow_with_leak'
TRUE_SOLUTION_PATH = f'data/{TEST_CASE}/test'
DISTRIBUTED = True
NUM_WORKERS = 25
BATCH_SIZE = 25
PDEForwardMod... |
9793784185c5badfa2f5c976eb8c90aa3dc382d03754b15ae5e410e7720df849 | Python | 3,006 | 94 | """Script to train an ensemble of models."""
import argparse
import logging
from importlib import resources
from typing import List
from flyvis.utils.compute_cloud_utils import launch_range
from flyvis.utils.config_utils import HybridArgumentParser
logging.basicConfig(
format="[%(asctime)s] [%(filename)s:%(linen... |
7a4dacf85f5b1ea37c12a5a73db3c55932de23da344d3a8c18bd2c2726d85ffa | Python | 3,007 | 91 | import os
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
import math
import numpy as np
import tensorflow as tf
from tensorflow.keras import layers
import logging
tf.get_logger().setLevel(logging.ERROR)
class Envelope(layers.Layer):
"""
Envelope function that ensures a smooth cutoff
"""
def __init__(self... |
65c03214b3ec32aeb0e597efd2cda5bec94ab4bfaf48480d24a0a55361fb730c | Python | 3,008 | 91 | '''
Calculate the datasets on the selected combinations
'''
import time
import moabbpatch
import moabbpatch.datasets
import moabbpatch.baseparadigm
moabbpatch.baseparadigm.physionet_rm_rest = True
import moabbpatch.mne_estim_output
SEED = moabbpatch.set_random_seed(1023)
import config
import numpy as np
import pandas... |
a051d0074298efc82d900f461b26ea11c65e329d904a76cde28be94489f9a614 | Python | 3,008 | 78 | """ Contains the code for the Perstruc-Denoiser algorithm """
# Imports
import numpy as np
import copy
from tqdm import tqdm
from scipy.fftpack import fft, ifft
from scipy.ndimage import gaussian_filter1d
def perstruc_denoiser(img_stack, FREQ_POS=72, use_gaussian=False):
# Output image stack
modified_img_... |
f13dfe164ad2f14bf8af709dd96fb64a0b64cad47871cf5b0aa41647d3e2ca2f | Python | 3,008 | 100 | # stdlib dependencies
from typing import List, Union, Any
# 3rd party dependencies
from numpy.typing import NDArray
# project dependencies
from deepface.models.facial_recognition.tf import VGGFace
from deepface.commons import package_utils, weight_utils
from deepface.models.Demography import Demography
from deepface... |
59749d13c05e985d5957b2a011b34e85b553365746fc1c4e113af42662a0b7cc | Python | 3,009 | 87 | # 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... |
71e130c48dda800a635b324c727c9846dca40fc3352b672001abcb87a2a7e2b8 | Python | 3,009 | 107 | _base_ = [
'../_base_/datasets/rtts_coco.py', '../_base_/schedules/schedule_1x.py',
'../_base_/default_runtime.py'
]
# model settings
model = dict(
type='PAA',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
... |
fe78c4c6bd2a18d9d09629a0ec05bd154b262804ed739d6b006e321136ce72e5 | Python | 3,011 | 97 | import json
from collections import defaultdict
import tables as tb
def rapppid_to_pipr(
dataset_path, c_type, seq_path, train_path, test_path, val_path, metadata_path
):
rapppid_dataset = tb.open_file(dataset_path)
metadata = rapppid_dataset.root.metadata
cols = metadata.colnames
rows = [row[:]... |
031ea44c271e1630a018ee0e5f16de0eaae97a3a4ecab30000a29670d63ae2cc | Python | 3,013 | 96 |
import os
import pdb
import numpy as np
from tqdm import tqdm
import torch
import matplotlib.pyplot as plt
import yaml
from latent_time_stepping.AE_models.VAE_encoder import VAEEncoder
from latent_time_stepping.AE_models.autoencoder import Autoencoder
from latent_time_stepping.AE_models.encoder_decoder import Decoder,... |
a75833543c6fd098d40ce71baecdb0f1a8c0ba06e696e93714e7352bc4e5e29e | Python | 3,013 | 82 | """
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 pytest
from fairchem.applications.cattsunami.core import Reaction
from fairchem.applications.cat... |
89a3a5084efe4568fb5ce8a01c145efd1744025f4d2375b19a6758b44d25e1e2 | Python | 3,015 | 97 | # 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... |
cacbe43928bba1efc5c710cf7096d8eb46d15f51c40e173190863b56359ea2ac | Python | 3,015 | 86 | #!/usr/bin/env python3
"""Utility scripts for pruning graphs and adjacency matrices."""
import logging
import numpy as np
from scipy import sparse
def prune_graph_degree(graph, degree=0):
"""Prune igraph graph nodes by degree."""
logging.info("Removing igraph nodes with degree <= " + str(degree))
import i... |
3499aad16f1255fd6653014f9e67ef45a729f4de1762fa251f03a98890c885cf | Python | 3,016 | 74 | """Register each run to one reference run."""
import os
import subprocess
DATADIR = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti/derivatives'
SUBS = ['sub-06']
BBOX = {'sub-05': {'RH': {'xlower': 435, 'xrange': 162, 'ylower': 55, 'yrange': 162, 'zlower': 95, 'zrange': 158},
'LH': ... |
55d326af60771f46784d8a9f9a61c3de8d978cadce1d8a4f52e9592752fa3e64 | Python | 3,016 | 114 | import os
import tempfile
from ray.dag import DAGNode
from ray.dag.utils import _DAGNodeNameGenerator
from ray.util.annotations import DeveloperAPI
@DeveloperAPI
def plot(dag: DAGNode, to_file=None):
if to_file is None:
tmp_file = tempfile.NamedTemporaryFile(suffix=".png")
to_file = tmp_file.name... |
a3d4f2feaf2d5de1171e68d62e3b6e9e581a0dcb5b89514eaeae2a771bfe94af | Python | 3,016 | 99 | import argparse
import hashlib
import importlib
import os
from typing import Optional
import requests
import torch
from ldctbench.hub import load_model
torch.serialization.add_safe_globals([argparse.Namespace])
import torch.nn as nn
import tqdm
from ldctbench.utils import load_json
from platformdirs import user_cache... |
afd25836ab2b77a363043e54e8ec07cdfee7e583508f8f55c0d9fcca8d9b50db | Python | 3,016 | 107 | _base_ = [
'../_base_/datasets/duo_coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='PAA',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375... |
510f100bc59fa544fdf08b09fdfd6bc053ecd4e951ed3174b52382a2621d2181 | Python | 3,017 | 87 | from __future__ import annotations
from typing import Any, Optional
def _normalize_session_id(value: Any) -> str:
if value is None:
return ""
session_id = str(value).strip()
return session_id
def resolve_bridge_session_id(session: Any, *, create: bool = True) -> str:
"""Return the active ag... |
74a46509bee7ef56527c37865f90a79db78a26a1d3a5ed833c91b850e5fcb150 | Python | 3,017 | 92 | #!/usr/bin/env python
"""
Collect medcov metrics. Writes stats to stdout.
Metrics:
medcov_mean : mean median coverage
medcov_mean_err : mean absolute deviation from baseline profile (if --baseline specified)
medcov_max_err : max absolute deviation from baseline profile (if --baseline specified)
"""
impor... |
99128c2c424a0e25d4641a402d53ac3773a7bce9802c77e721de3d0391ba9e1f | Python | 3,018 | 123 | import numpy as np
from spinnaker2 import snn, hardware
from spinnaker2.mla import conv2d, mla_helpers
import matplotlib.pyplot as plt
#create input signal for rf neurons
dt = 0.01
timesteps = 512
t = np.linspace(0,(timesteps-1)*dt, timesteps)
w = np.array([0.2, 3, 4])
n_targets = len(w)
signal = np.exp(1j*2*np.pi... |
3060c2f8db4d46c98a81d2c47423e10e04248ea60d44e893652b13dfb28c6995 | Python | 3,019 | 96 | import os
class Parameters():
def __init__(
self,
dim_hidden = 16,
dim_context = 128,
ctx_wt = .5,
stickiness = 1,
concentration = 1,
gen_grad = 5,
lik_softmax_beta=.33,
try_reset_h=False,
use_shortcut=False,
pe_tracker_size =... |
d201b696c58f46119d32e08a3a225e4af4f8c7e6c28a2045aeb38da9c8a7b6e2 | Python | 3,020 | 107 | _base_ = [
'../_base_/datasets/ruod_coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='PAA',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.37... |
57e73b3b46ecb0f21c87687277ec9bf7ef508d7dd34e860f9fce0e2f0737ccfb | Python | 3,021 | 120 | import tempfile
import pytest
from pfrl.collections.persistent_collections import PersistentRandomAccessQueue
def check_basic(tmpd):
rb = PersistentRandomAccessQueue(tmpd, 16)
assert 16 == rb.maxlen
data = {0x42: "pocketburger"}
rb.append(data)
x = rb.sample(1)
assert [data] == x
assert... |
67396dd5577ad3dba6f0809f864f333085c0f59389b59991ba709afa6807c77a | Python | 3,021 | 96 | import numpy as np
from matplotlib.pyplot import imread
import h5py
import os
import argparse
import multiprocessing as mp
from typing import List
import functools
from lib.data_utils.sta_metadata import RGB_CONVERSION
CROP_HEIGHT = 160
CROP_WIDTH = 256
MAX_IM_PER_CLASS = 500
HALF_CROP_HEIGHT = CROP_HEIGHT // 2
H... |
7214d31ebc1a1e802184c028e796857c2dc49b40cecc910aa2bcc7e43071170b | Python | 3,021 | 118 | from typing import Union, Sequence, List, Dict, Callable, Tuple, Iterable
import collections
import numpy as np
from shapely.geometry.polygon import Polygon, LinearRing
from shapely.geometry import LineString
NicePathType = Sequence[Sequence[float]] # [[x, y], [x, y]]
PathType = Union[
str, # "x,y,x,y"
Nice... |
4a3c9efa81dffbbf65eb77d5de6ad87f1b104e6550e5cad5ab6ee98d6eefb870 | Python | 3,022 | 93 | #!/usr/bin/env python
# coding: utf-8
import sys
import numpy as np
import pandas as pd
import tensorflow as tf
import logging
tf.get_logger().setLevel(logging.ERROR)
sys.path.append('../DROID')
from data_descriptions.echo import LmdbEchoStudyVideoDataDescription
from model_descriptions.echo import create_movinet_cl... |
78804357ec34fa79e517097b4ba184af81a1eea620f686e92e0072362cfd63c6 | Python | 3,022 | 93 | """Script to run a notebook for each model of an ensemble."""
import argparse
import logging
from importlib import resources
from typing import List
from flyvis.utils.compute_cloud_utils import launch_range
from flyvis.utils.config_utils import HybridArgumentParser
logging.basicConfig(
format="[%(asctime)s] [%(f... |
c476483c86ad644325559a861bd084a7356a03a47d6f83ac2ff7419852d4e2b5 | Python | 3,022 | 67 | import numpy as np
import pandas as pd
from sklearn.datasets import make_classification
from siapy.entities import Pixels, Signatures, SpectralImage
from siapy.features import AutoSpectralIndicesClassification
from siapy.features.helpers import FeatureSelectorConfig
from siapy.features.spectral_indices import compute_... |
4a22a78bb619fa9999aeeac7537fa585b0c628e182095c522b71896eb011aa05 | Python | 3,023 | 92 | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class OnnxStableDiffusionImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers", "onnx"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["... |
77b6a1156782ddcc325f536c12481c05b3544400c05631a9d8e0a1395b520cc3 | Python | 3,024 | 83 | import numpy as np
from spinnaker2.neuron_models.application import BaseApplication
from spinnaker2 import mapper
from spinnaker2.mapper import SynapseWordSpec, SynapseWordSize
from spinnaker2.configuration import PEConfig, MemoryRegion
from spinnaker2.neuron_models.common import (add_log_memory_region,
N_WORD... |
aab61c497f3cab5a1fc30539f2aeef8286ec1b4354d053ba816941ccb51451e5 | Python | 3,024 | 55 | import tensorflow as tf
from mol_graph import max_nb
from utils.nn import *
def gated_convnet(graph_inputs, batch_size=64, hidden_size=300, depth=3, res_block=2):
input_atom, input_bond, atom_graph, bond_graph, num_nbs, node_mask = graph_inputs
layers = [input_atom]
atom_features = input_atom
for i in ... |
8bcbfb43a0dd949a506aa1c90883a76816bf1b64280ce36775a99c37c69ed73c | Python | 3,026 | 112 | from typing import Optional
import matplotlib.pyplot as plt
import numpy as np
from numbers import Number
class DataTracer:
def __init__(self):
self._data_list = []
self._data_array = np.array([])
self._time_list = []
self._time_array = np.array([])
self._ax = None
@pr... |
b9c7e770526af52878beb8316c15eb1b31584abf574cf080b590e5482ca69392 | Python | 3,026 | 98 | from spinnaker2 import snn, hardware
import json
from spinnaker2.helpers import read_log
import matplotlib.pyplot as plt
from numpy.polynomial import Polynomial
# enable profiling for LIFApplication class
import spinnaker2.neuron_models.lif_neuron
spinnaker2.neuron_models.lif_neuron.LIFApplication.profiling = True
d... |
d1250f16605933ef41eba49115590ac9100ace2764515b9a237c207d90d2b692 | Python | 3,026 | 75 | # 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 in writing, software
# distributed under th... |
eefed0fe24f7096a41d587b6b6f3ec3742b4860e6201039a44ec0240cc347cd5 | Python | 3,026 | 77 | import pathlib
path = pathlib.Path.cwd()
if path.stem == 'tmb_survival':
cwd = path
else:
cwd = list(path.parents)[::-1][path.parts.index('tmb_survival')]
import sys
sys.path.append(str(cwd))
import numpy as np
from lifelines import CoxPHFitter
from lifelines.utils import concordance_index
import pandas as pd
i... |
3d9ceeadaeb438002c166009e2d92847e349c6be51f3cd8325f7572ebbfa4a6f | Python | 3,027 | 87 | import numpy as np
import mne
from audio_utils import WaveProcessor
from tqdm import tqdm
def create(wav_dir: str, out_dir: str, config: dict) -> None:
""" Create feature from audio snips.
This function creates a feature from audio snips. The feature is an acoustic array of the shape
(samples, segments, ... |
1e7bd83c50f82f18fd9cca5e936c8117ad31d54565b4a03c5e562520c113359b | Python | 3,028 | 61 | from argparse import ArgumentParser
from sys import stdin as std_in
from sys import stdout as std_out
import logging
import pysam
from deltasplice.pred_utils import get_delta_prediction, Annotator
from tqdm import tqdm
def get_options():
parser=ArgumentParser(description="Version: 1.0.0")
parser.add_argument('-... |
224d826ff7bf8ecdb524d593f45080b16f87246458bc5ddc95afb0f3d7cb0945 | Python | 3,029 | 83 | #
# CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
# © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
# Source code:
# https://github.com/AdaptiveMotorControlLab/CEBRA
#
# Please see LICENSE.md for the full license document:
# https://github.com/AdaptiveMotorControlLab/CEBRA/bl... |
4f00de320e11ee401bc362b625dce73b01a56b430312de64786bb0c0b5a8289c | Python | 3,029 | 84 | import pathlib
path = pathlib.Path.cwd()
if path.stem == 'tmb_survival':
cwd = path
else:
cwd = list(path.parents)[::-1][path.parts.index('tmb_survival')]
import sys
sys.path.append(str(cwd))
from model import utils
from matplotlib import pyplot as plt
import seaborn as sns
import numpy as np
import pickle
t =... |
84146cbdbe47b1e9a8187687f0879019c0ad6399539ff2d87df1817a099ace45 | Python | 3,029 | 103 | """
Structured event reporting for OmicVerse Agent (P1-1).
Replaces hard-coded ``print()`` calls with a pluggable Reporter interface.
Three built-in implementations:
* **PrintReporter** – reproduces current emoji-rich terminal output (default).
* **SilentReporter** – logs to ``logging`` only (tests / batch pipelines)... |
ad669c304a1071683d4fa5700bb39b77acf0a4d216d9bf9d7fa4ba6434a43ea3 | Python | 3,029 | 105 | _base_ = [
'../_base_/datasets/rtts_coco.py', '../_base_/schedules/schedule_1x.py',
'../_base_/default_runtime.py'
]
# model settings
model = dict(
type='RetinaNet',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
... |
42f9b587a94aa44586f526c4ec2f690be7b9a7c083bee988db9c716f3d7b0bfd | Python | 3,030 | 87 | # 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... |
6146cf7d1566c7f3cc044a8cc1c05ba90e5a64ac74469f902cc117e3d82f5a43 | Python | 3,030 | 92 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for Bio-Diffusion (https://github.com/BioinfoMachineLearning/bio-diffusion):
# --------------------------------------------------------------------------------... |
762c2c4c99a8f9a0f1d588ff969222c394e3aad742c9ee3aaea7e2197dfeba3c | Python | 3,031 | 67 | ####################################################################################################
# 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... |
b0b26e3b18f3ecad70a091622e996f751c43ca16a5ece9ed9303cad0877f9dfa | Python | 3,031 | 80 | from typing import Optional, Sequence
from mmeval.metrics import MeanSquaredError as MMEVAL_MSE
from lqit.registry import METRICS
@METRICS.register_module()
class MeanSquaredError(MMEVAL_MSE):
"""Mean Squared Error metric for image.
mean((a - b) ^ 2)
Args:
gt_key (str): Key of ground-truth. De... |
3e827af6df218c2056a8c4f30bafa78767341add4919ae9245978081a19b026d | Python | 3,035 | 81 | from typing import Optional, Sequence
from mmeval.metrics import MeanAbsoluteError as MMEVAL_MAE
from lqit.registry import METRICS
@METRICS.register_module()
class MeanAbsoluteError(MMEVAL_MAE):
"""Mean Absolute Error metric for image.
mean(abs(a - b))
Args:
gt_key (str): Key of ground-truth. ... |
a92c0d410bb93cedced8bba23be0671a69a5c324e0087ac7cabe4812013c5676 | Python | 3,036 | 105 | _base_ = [
'../_base_/datasets/duo_coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='RetinaNet',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, ... |
b3641b6114eb197d7e21d6d0c7dc7c17a2f9415ab4c317624ebe282424ca543e | Python | 3,036 | 85 | import math
import torch
import torch.nn.functional as F
from ..distances import CosineSimilarity
from ..utils import common_functions as c_f
from ..utils import loss_and_miner_utils as lmu
from ..losses.base_metric_loss_function import BaseMetricLossFunction
from ..losses.mixins import WeightRegularizerMixin
#####... |
eb5ba364899d9bce25e491487bce9bd6e2828111b05699336ab0875c25b34bf0 | Python | 3,036 | 75 | import sys
import scipy.io as sio
import os
import numpy as np
from scipy import special
import h5py
if __name__ == "__main__":
list_Exp_ID = [ 'Mouse_1K', 'Mouse_2K', 'Mouse_3K', 'Mouse_4K', \
'Mouse_1M', 'Mouse_2M', 'Mouse_3M', 'Mouse_4M']
num_Exp = len(list_Exp_ID)
r_bg_ratio = 3
... |
0d8f6574c5600edf55cf21fa3c5bd5354b6b991457b1c92a87616f55ecc87698 | Python | 3,038 | 106 | import sys
from unittest.mock import Mock
import pandas as pd
import pytest
from data_profiling import ProfileReport
@pytest.fixture
def df():
return pd.DataFrame({"num": [1, 2, 3, 4, 5]})
@pytest.fixture(scope="function")
def mod():
mod = Mock()
sys.modules["great_expectations"] = mo... |
2b37fffb436ca4412c1cdedc2895a003b4b5f8627f36ac25879cc590123bef96 | Python | 3,038 | 105 | _base_ = [
'../../_base_/datasets/rtts_coco.py',
'../../_base_/schedules/schedule_1x.py', '../../_base_/default_runtime.py'
]
# model settings
model = dict(
type='RetinaNet',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, ... |
ba434a31adfe982fa797fb5924082596c086529a902c0c1fbb094301305a973d | Python | 3,038 | 80 | import torch
from ..utils import common_functions as c_f
from ..utils import loss_and_miner_utils as lmu
from ..losses.generic_pair_loss import GenericPairLoss
class LiftedStructureLoss(GenericPairLoss):
def __init__(self, neg_margin=1, pos_margin=0, **kwargs):
super().__init__(mat_based_loss=False, **kw... |
bc6f1e215269bdf473ec443f57c934e232d0d3f3c7a9b557d44da6063d7f0d11 | Python | 3,038 | 77 | # Copyright 2023 The HuggingFace Team, the AllenNLP library authors. All rights reserved.
#
# 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
#
... |
26a5529e21295d2921714213c0c06ab30c4722346de9e2d626e7036cd0fb65dd | Python | 3,040 | 94 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Tests for optimizers."""
from torch import Tensor, manual_seed
from torch.nn import Linear
from torch.optim import SGD, AdamW
from torch.nn.functional import... |
71cc536333053b0bcfd20d732d44020ea1ed84265d27792e9752179655e3dbfd | Python | 3,040 | 105 | _base_ = [
'../_base_/datasets/ruod_coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='RetinaNet',
data_preprocessor=dict(
type='DetDataPreprocessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12,... |
dca498edadb17048401c0b54606d78ef65179ecf7f179e4d7f2b6f1c9c075e8a | Python | 3,040 | 78 | from .swin_transformer import SwinTransformer, PatchMerging
from torch import nn
class Build_Merging(nn.Module):
def __init__(self, body_psg, body_hyp, head) -> None:
super().__init__()
self.body_eeg = body_psg
self.body_hyp = body_hyp
self.head = head
def forward(sel... |
54477151ca705a0a1be0dcc8d6299eb7a92ee8229bcd7f61db401164292aa26f | Python | 3,041 | 83 | # 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... |
5a121d2a770778fce5ebda3826d542f5efa6e9936ffd00a8aeaa9a5a049e42c9 | Python | 3,041 | 84 | import gym
import numpy as np
import pytest
import pfrl
@pytest.mark.parametrize("num_envs", [1, 2, 3])
@pytest.mark.parametrize("env_id", ["CartPole-v0", "Pendulum-v0"])
@pytest.mark.parametrize("random_seed_offset", [0, 100])
@pytest.mark.parametrize(
"vector_env_to_test", ["SerialVectorEnv", "MultiprocessVect... |
5e8d0a2b05523bc8bcb1dd56c707e35cc80902348bc0c2f0c0a429afe632b8c2 | Python | 3,041 | 121 | from argschema.schemas import ArgSchema, DefaultSchema
from argschema.fields import (
InputFile, OutputFile, String, Nested, Dict, List, Int, Field, Float, Boolean)
from marshmallow import ValidationError
class PathResolution(DefaultSchema):
path = String(
description="Fixed value boundary condition",... |
0a3905479a2c73e0a1c95e8c0a5740c9bbace196e277b62e8a189dfc5f53060c | Python | 3,044 | 92 | import os
import pickle
import numpy as np
import pandas as pd
from utils import to_pth, list_fnames, pickle_load
from utils.PCATransformer import PCATransformer
from sklearn.preprocessing import StandardScaler
DATA_ROOT = '../data/input_scene_vecs/'
scene_vec_fpattern = '*_kinect_sep_09.pkl'
FPS = 25
pcat = PCATransf... |
8cef85c73536f053c5310c70d8b2b40afbba9f474663da3b8bcac7cca763a8f1 | Python | 3,044 | 88 | import functools
import torch.nn as nn
# Isolated baseline implementation provided by @warvito and should be used as minimum performance
# for any further improvement. This implementation is 3D only. It was extracted from his codebase
# at commit https://github.com/Warvito/Dan_Data/blob/97ccba41d8ee1e811b66e79254fcce... |
a4fe830717996fea95e3cc9bc40d5a23553021a62a02bd096b9d176878b121d8 | Python | 3,044 | 78 | import numpy as np
import pandas as pd
def in_silico_fold_change(concentration, fold_change_limit=9):
''' Take a series of known concentration, and a fold change limit, and relabel
the concentrations such that new labels are within the fold change limit.
Returns the given concentrations, the replaced conc... |
f0c7e4f98434a5f23453dc21fdc0d261f720749fcd1e10496e61928dc4edd94d | Python | 3,045 | 99 | import numpy as np
import pandas as pd
import pytest
from matplotlib.legend import Legend
from matplotlib.pyplot import Axes, close, rcParams
from data_profiling.visualisation.plot import (
_create_timeseries_heatmap,
_plot_pie_chart,
_plot_stacked_barh,
_prepare_heatmap_data,
)
# Generating dummy dat... |
4c9ea6c8662df3079f0d387b440f8df6e715f4c76a66b3b6874f2135be1d12d4 | Python | 3,048 | 89 | """Reduce bounding box to decrease filesize."""
import os
import subprocess
import glob
# =============================================================================
# Define data dir
DATADIR = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti'
# Set subs to work on
SUBS = ['sub-07']
# ===============... |
fb77e7bad95440d57228d07783ef7151e58d349d2a5355ab92bdf04510128326 | Python | 3,048 | 88 | import functools
import torch.nn as nn
# Isolated baseline implementation provided by @warvito and should be used as minimum performance
# for any further improvement. This implementation is 2D only. It was extracted from his codebase
# at commit https://github.com/Warvito/Dan_Data/blob/97ccba41d8ee1e811b66e79254fcce... |
1dd1fbe115d43112188879e7f4d7c4102b3c19ef38a1c7790fc3b01a1248aba1 | Python | 3,049 | 94 | import torch
import torch.nn as nn
from torch.nn.functional import binary_cross_entropy_with_logits
from torchvision.transforms.functional import to_pil_image
import matplotlib.pyplot as plt
def convert_cell_to_img(t, padding=16):
"""Converts pytorch tensor into a Pillow Image. The padding will be removed
fro... |
1b888cef4ee821cf1abcd141f228d5f47ea990cfd70cdb87b73f1aad28782eef | Python | 3,051 | 83 | #
# Copyright (c) 2021, NVIDIA CORPORATION.
#
# 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 ... |
726bcd834eac43c4dd0da2350537b53eabfb78bc57141ef20ae365adcef33609 | Python | 3,051 | 77 | import unittest
import numpy as np
from reval.relative_validation import RelativeValidation
from reval.utils import kuhn_munkres_algorithm
from sklearn.neighbors import KNeighborsClassifier
from sklearn.cluster import AgglomerativeClustering
from hdbscan import HDBSCAN
from sklearn.datasets import make_blobs
# Modify... |
2a5b74e118bbda929b22c51a9b34db89710723a5d4699b77fd3dcbb9098285b4 | Python | 3,052 | 80 | import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import pandas as pd
from metabolite_learner.agilent import EXPECTED_SHAPE, TIME_GRID, convert_agilent_to_csv
from metabolite_learner.cli import build_parser
from metabolite_learner.pls import MetaboLiteLearner
class ... |
3f203177060b2f2dd6c019d20d09ae5a0b25954940825405b04fe3b22cb803e3 | Python | 3,053 | 96 | import numpy as np
from scipy.stats import sem
# from scipy.special import kl_div
from sklearn.metrics import accuracy_score
from sklearn import metrics
def compute_stats(arr, axis=0, n_se=2, use_se=True):
"""compute mean and errorbar w.r.t to SE
Parameters
----------
arr : nd array
data
ax... |
6092e4e65770a39e464a05380f1f9b7edbfa484d352eebe179afdf65d76bffec | Python | 3,053 | 82 | # built-in dependencies
import os
# 3rd party dependencies
import pytest
# project dependencies
from deepface.models.face_detection import OpenCv
from deepface.commons.logger import Logger
logger = Logger()
BUNDLED_PATH = os.path.join(os.path.dirname(OpenCv.cv2.__file__), "data")
def test_haarcascade_files_are_do... |
5b22a546a2e300c1f59e63854b9d99ffb37e245622d96394d63a421488b7b808 | Python | 3,057 | 137 | # flake8: noqa
# __tasks_start__
import ray
import time
# A regular Python function.
def normal_function():
return 1
# By adding the `@ray.remote` decorator, a regular Python function
# becomes a Ray remote function.
@ray.remote
def my_function():
return 1
# To invoke this remote function, use the `remot... |
cf59489dbe4f9c5c8fbc599127281cb87d79cd1580b4e5bc15f05ba4677ad333 | Python | 3,057 | 83 | 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_triplets_4_constants i... |
5225940063cf3fd67fa57387d75bbe3f53a272b6446614d5c220a8bfae4ae954 | Python | 3,058 | 79 | import io
import unittest
from unittest import mock
from container_resource_utils import (
get_container_cpu_limit,
get_container_mem_limit_mb,
get_system_ram_mb,
main,
)
class TestResourceUtils(unittest.TestCase):
def test_get_system_ram_mb_calculates_correctly(self):
with mock.patch("os... |
90c55df508fec9f658bc34ef2e81a4cc5f207c6eb5b9057a0e4fc7bf4e7fac56 | Python | 3,059 | 136 | import os
import pickle
import numpy as np
import matplotlib.pyplot as plt
from utils.grid_funcs import (
meanfr_repsupp
)
import settings
from joblib import Parallel, delayed
from tqdm import tqdm
###############################################################################
# Parameters ... |
57d5271e84ce1100d0e8205dae6800ae7285bc9d20490b7c03c25b4c0bb6458e | Python | 3,061 | 82 | #!/usr/bin/env python3
import argparse
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
def calculate_median_mad(group):
median = np.median(group)
mad = np.median(np.abs(group - median))
return median, mad
def main():
parser... |
f3bf9d252e763e7676e71a216dbd3911d932d09700beaba3f19cd49ac957f1e7 | Python | 3,062 | 81 | import optuna
import sys
import os
import datetime
import os.path as osp
from math import isfinite
sys.path.insert(0, "/srv/home/zgaleday/torch_pgn")
from torch_pgn.args import HyperoptArgs
from torch_pgn.train.run_training import run_training
DEVICE = 'cuda:' + sys.argv[1]
ENCODER = 'dimenet++'
DATA_PATH = sys.arg... |
3480fbbebe9870f090b8617b74a97a907b6b5bea5454d00a2fdf830a25a6f238 | Python | 3,063 | 74 | #!/usr/bin/env python
import numpy.testing as npt
import numpy as np
from scipy.ndimage.filters import gaussian_filter
import caiman.source_extraction.cnmf.params
from caiman.source_extraction import cnmf as cnmf
#%%
def gen_data(D=3, noise=.5, T=300, framerate=30, firerate=2.):
N = 4 ... |
c228e5a26c90fb4f6078a3dc1d01edc85585a5e0ab09ae7b02fe4c0aa617fabe | Python | 3,063 | 81 | import torch
import soft_rank_numpy
def wrap_class(cls, **kwargs):
"""Wraps the given NumpyOp in a torch Function."""
class NumpyOpWrapper(torch.autograd.Function):
"""A torch Function wrapping a NumpyOp."""
@staticmethod
def forward(ctx, values):
obj = cls(values.detach()... |
680b13badbe43cc0f33cd4e4d953ee9e616e60830f3149ea1a5c7d90894cc52e | Python | 3,064 | 46 | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: common.proto
"""Generated protocol buffer code."""
from google.protobuf.internal import builder as _builder
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
f... |
ef7fa57de01e6b7881c2e44a5dba705f430614e49e076e1db04c2a5582bd52b3 | Python | 3,064 | 83 | import torch
# mypy somehow complains about `torch.optim.RMSprop` as of torch==1.5.0.
class RMSpropEpsInsideSqrt(torch.optim.RMSprop): # type: ignore
"""torch.optim.RMSprop with eps inside sqrt."""
def step(self, closure=None):
"""Performs a single optimization step.
Arguments:
c... |
ea2090be6d29566c0a0cf83b2b22ddfe03cbb46237481afe8d7f862328bde49f | Python | 3,067 | 94 | from typing import Annotated, Literal
from mlxtend.feature_selection import SequentialFeatureSelector
from pydantic import BaseModel, ConfigDict
from sklearn.linear_model import Ridge, RidgeClassifier
from sklearn.pipeline import Pipeline, make_pipeline
from sklearn.preprocessing import RobustScaler
from siapy.core.e... |
0bb0b4671b7bcd80ebdb828bd967ca47b46c42c44370f3f1cdb0fe712940908d | Python | 3,068 | 87 | from pathos.pools import ParallelPool as Pool
from itertools import product
import numpy as np
from lgca import get_lgca
from tqdm import tqdm
INPUT = '.\\data\\gog\\nonlocaldensity_10reps\\'
OUTPUT = '.\\data\\gog\\nonlocaldensity_recurrence\\'
def iteration(args):
from pickle import dump, load
index, kwargs... |
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