sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
dad14c5c229bed662cd9760245c9c499d3b424cedfde3fa6385bddaa81aee8aa | Python | 7,445 | 136 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import json
import types
import zipfile
from pathlib import Path
import torch
from ultralytics.nn.modules import Detect
from ultralytics.utils import LOGGER
from ultralytics.utils.export.engine import _NormalizeCo... |
c97dfaebffbc2b4ab4717e3d4874f8ffd4b69f054f1a3fc950de822904257b35 | Python | 7,447 | 211 | import copy
import numpy as np
from numpy import convolve
from scipy.interpolate import pchip
from scipy.signal.windows import gaussian
from mc_analysis.utils.absolute_paths import IRF_PATH
def interp_pchip(x, y, x_smooth):
"""1D PCHIP interpolation."""
func = pchip(x, y)
return func(x_smooth)
def con... |
187be4b0d6c63d8f95e54aba0ab3294a0b5b2cda18c5e6b843a7c9fa9c51845e | Python | 7,449 | 196 | # -*- coding: utf-8 -*-
"""
Created on Wed Nov 6 19:33:28 2019
@author: Yoshi
"""
import os
import numpy as np
import tifffile as tiff
import csv
import pandas
from roi_zip_reader import *
from key_reader import *
from cell_and_background_array import *
from data_sorter import *
from data_reader import *
from dfo... |
bfa8638be2ecc60d86c6fa49359caaf977b5a7c8947f3c1a65f120bb9a280f46 | Python | 7,449 | 202 | import fcn_megfmri
import numpy as np
import pandas as pd
import seaborn as sns
import scipy.stats as stats
import matplotlib.pyplot as plt
# get custom colormaps
cmap_seq, cmap_seq_r, megcmap, megcmap2, categ_cmap = fcn_megfmri.make_colormaps()
plt.rcParams['svg.fonttype'] = 'none'
plt.rcParams['font.sans-serif'] =... |
7c667f52bb452484e88ab77b7c02622f36d3079111a4a1bd6a739f00da7de4cf | Python | 7,455 | 353 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Segment, mask and bin 'MB-STn' files
"""
import os
import matplotlib.pyplot as plt
import numpy as np
import mbflim.utils as ut
import mbflim.visualization as vis
import mbflim.image.image_processing as pro
import mbflim.image.image_set_processing as setpro
import ... |
3d134b08ca2a14ad90dd083ef3acc7884ffd4cddc205d3955165bb8413a471fb | Python | 7,456 | 217 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from collections import OrderedDict
from datetime import datetime, timedelta, timezone
from typing import Any, Callable, TypeAlias, cast
import attrs
import cvat_sdk.auto_annotation as cvataa
import PIL.Image
from .agent_driver import (
AgentFu... |
5cee187d5e91c5541cd74c2f315648b79514a8363185926f060d93a240ba7d8d | Python | 7,456 | 176 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
import torch
from ultralytics.data import YOLODataset
from ultralytics.data.utils import get_split_fraction
from ultralytics.models.yolo.detect import DetectionValid... |
fd1c6130abfe33b752bb2096b533c6d21b5265e6261e0c650fb0b352e1e08081 | Python | 7,456 | 133 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'mosaic_dialog.ui'
#
# Created by: PyQt5 UI code generator 5.7
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Dialog(object):
def setupUi(self, Dialog):
Dialog.setObj... |
11b8c60a0afb19cb645e9dfad8d1cad7b27ef9bc9ee64c5b641ecc5aff79ebb3 | Python | 7,459 | 138 | """This scripts generates 3 examples where we regress HR real scans from multi-modal LR scans. Specifically we regress
HR T1 scans from LR T1 and T2 scans. We assume here that HR label maps are available with corresponding T1 scans. Thus
this script produces pairs of real HR T1 scans along with aligned HR synthetic sca... |
09a4ce05728ea66ae1eb248c21803de1aebdf3e4f7b0cd2ba77e465529ed988a | Python | 7,460 | 207 | from __future__ import print_function
import numpy as np
from PIL import Image
import cv2
import os.path as osp
import torch
from torch.autograd import Variable
import h5py
def srgb2rgb(srgb ):
ret = np.zeros_like(srgb )
idx0 = srgb <= 0.04045
idx1 = srgb > 0.04045
ret[idx0] = srgb[idx0] / 12.92
r... |
2bf4de8dccb99c412c9e5462ff3612d28dabed49d66d4bec2c8886cc857ae31d | Python | 7,460 | 229 | import os
import glob
import numpy as np
import h5py
from em_util.io.box import compute_bbox_all
from tqdm import tqdm
from nicety.conf import get_conf
from joblib import Parallel, delayed
from scipy.interpolate import splprep, splev, interp1d
from sklearn.decomposition import PCA
from cloudvolume import Skeleton
from ... |
d98db625c72294bfe490b62e92c52fa3a2095ab02c46c4937c8f3d8f4ba855cb | Python | 7,460 | 170 | from typing import Optional, Callable, List, Union
import numpy as np
import tensorflow as tf
import pickle
from ..config import TF_COMPLEX, NP_COMPLEX
from ..helpers import random_gaussian_batch
from ..tensorflow import MeshLayer, SVD
def complex_mse(y_true: tf.Tensor, y_pred: tf.Tensor):
"""
Args:
... |
5779f911ac9f252d832adc0bf492f53ec36cfa2aafba82f1aa069ad432a63ee7 | Python | 7,462 | 259 | from collections import deque
import numpy as np
import pandas as pd
import scipy.sparse
import scipy.spatial
import scipy.stats
import sklearn
from tqdm import tqdm
from nest import get_neighbor_adjacency
class GaussianExpressionModel:
def __init__(self, dim=16, pca=True):
self.dim = dim
self.u... |
c36c23d98969cd857f2113afae0cea07aa3085490a89aaaf1e80f5192f28a2ec | Python | 7,462 | 353 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Segment, mask and bin 'MB-Gn-cond' files
"""
import os
import matplotlib.pyplot as plt
import numpy as np
import mbflim.utils as ut
import mbflim.visualization as vis
import mbflim.image.image_processing as pro
import mbflim.image.image_set_processing as setpro
imp... |
320341fc59488de88b37d527945d0192d3f47b6e4b268cb20763fab971245f69 | Python | 7,463 | 195 | import numpy as np
class Stimulation:
def __init__(self, fname, depvar_sort=True):
self.load_data(fname)
self.fname = fname
# if depvar_full is None:
# depvar_full = []
# else:
# self.depvar_full = depvar_full
if depvar_sort:
self.depvar_sort()
... |
befa522511cd11114e42e26244e9409be9ffc6f8998eca09a6ab1229126c5c89 | Python | 7,463 | 353 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Segment, mask and bin 'MB-Gn-cond' files
"""
import os
import matplotlib.pyplot as plt
import numpy as np
import mbflim.utils as ut
import mbflim.visualization as vis
import mbflim.image.image_processing as pro
import mbflim.image.image_set_processing as setpro
imp... |
74f053e43fdeb153fa6a079e056882f84439b62174b300d9a7323c478964bc45 | Python | 7,464 | 211 | from __future__ import annotations
import json
from pathlib import Path
import numpy as np
import pytest
from PySide6.QtWidgets import QFileDialog
from pytestqt.qtbot import QtBot
from labelme._shape import Shape
from .conftest import MainWinFactory
@pytest.mark.gui
def test_actions_follow_image_and_shapes(
*... |
12bac0d00021f5aaa382b1fc774868d7031f623d8b735e22a57c970b612c3950 | Python | 7,466 | 238 | import re
from pathlib import Path
from typing import Literal, Optional
import numpy as np
import pandas as pd
import scipy as sp
import skimage
import tqdm
def apply_affine(T: np.ndarray, X: np.ndarray) -> np.ndarray:
"""Apply homogeneous-coordinate affine matrix T to each row of of matrix
X of shape (N, 3)... |
8e45b19b23b51d2834c0d6fb4f46248447ff7e0b7893971238431e2c252d9db9 | Python | 7,466 | 187 | import sys
sys.path.append('..')
import inspect
import torch
import torch.nn as nn
import torch.nn.functional as F
from copy import deepcopy
from typing import Dict, Any, List, Optional
from common.utils import get_regression_pred
from common.mapping_utils import CONV_MAP
from models.graph_models import GraphModel
def... |
b03377d7813cd1b23eff1ccde5f5fe7229d796a5d1544d21fcf059efe72c7c49 | Python | 7,466 | 354 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Segment, mask and bin 'MB-ABn-cond' files
"""
import os
import matplotlib.pyplot as plt
import numpy as np
import mbflim.utils as ut
import mbflim.visualization as vis
import mbflim.image.image_processing as pro
import mbflim.image.image_set_processing as setpro
im... |
436700ab8431f88eef9d770375127a50cb8753dec090c99c84ec9261ed25e043 | Python | 7,467 | 180 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
def nearest_neighbor(src, dst):
inner = -2 * torch.matmul(src.transpose(1, 0).contiguous(), dst) # src, dst (num_dims, num_points)
distances = -torch.sum(src ** 2, dim=0, keepdim=True... |
71de6a4cf397b5aa2bae4b0ceebe65704ee6b7d488ebbc94ceb7832436552f8c | Python | 7,467 | 213 | import torch
import torch.nn as nn
import torch.nn.functional as F
class TemporalSpatialBlock(nn.Module):
"""Temporal-spatial feature extraction block"""
def __init__(self, in_channels, out_channels, kernel_size=3, stride=1, padding=1):
super(TemporalSpatialBlock, self).__init__()
self.... |
7effe1c7e40bdbd0e2017320cccec74c6ad91c4cdbdc1ed5d0c9ad632c78d849 | Python | 7,469 | 298 | # -*- coding: utf-8 -*-
import json
import os
import sys
from dataclasses import asdict, dataclass, field
from multiprocessing import cpu_count
from torch.utils.data import Dataset
# ====================
# 工具函数
# ====================
def get_default_process_count():
"""
获取默认进程数
Returns:
int: 默... |
dde78f1e1674e245b9d91f39d7cb7994d406cede5f7f89e07eafd7620804a112 | Python | 7,471 | 182 | import torch
from torch import nn
from torch.nn import functional as F
#from models.networks_other import init_weights
#### From Attention UNet Otkay et al. 2018
class GridAttentionBlock2D(nn.Module):
def __init__(self, in_channels, gating_channels, inter_channels=None, dimension=2, mode='concatenation',
... |
87be4f4cb21e48b1b6b0246c1b00327c62fe34c0c3b9eb8b1860ac9f72478e46 | Python | 7,472 | 162 | import numpy as np
import tensorflow as tf
from src import TGCNN_layer
class TGCNN_Model(tf.keras.Model):
def __init__(self, num_filters=2, num_nodes=97, num_time_steps=100,
filter_size=3, variable_gamma=True, exponential_scaling=True, dropout_rate = 0.2,
lstm_units=16, fcl1... |
a014b04ab515ba672f8b4854439d1891faeb50757808ab77cb8c2c30230444af | Python | 7,472 | 130 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'focuslock.ui'
#
# Created by: PyQt5 UI code generator 5.8.2
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Dialog(object):
def setupUi(self, Dialog):
Dialog.setObjec... |
a19ef5b8ad3bb0657e47e5e22d2229e108ad53c32924f88adf12a9e85a54d76d | Python | 7,472 | 218 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from enum import Enum
from django.db import models
from drf_spectacular.utils import extend_schema_serializer
from rest_framework import serializers
from cvat.apps.engine.models import Project
from cvat.apps.engine.serializers import BasicUserSeria... |
dd4a30a64ed144e287b03051f75ba9fb8c0164e2ee36fa089b513018a6dde6c1 | Python | 7,475 | 188 | import glob
import logging
import os
import warnings
import h5py
import numpy as np
import pandas as pd
import plotly.express as px
import torch
from sklearn.metrics import accuracy_score, auc, f1_score, precision_score, recall_score, roc_curve
from sklearn.model_selection import train_test_split
from deeprank2.datas... |
e4e672fece747eb69eae453bacf6211f494668adca98f6d2b47f3805d627d307 | Python | 7,477 | 202 | import argparse
import glob
import os
import random
import sys
import csv
import tqdm
import numpy as np
import torch
from torch.utils.data import Dataset, DataLoader
import pytorch_lightning as L
from pytorch_lightning.callbacks import ModelCheckpoint
from pytorch_lightning.strategies import DDPStrategy
from lightnin... |
b5ddb636106bef1b7d0a87b795746bf0f9dd94a8fec26856e2a1f40546b105a0 | Python | 7,483 | 162 | import argparse
import utils
import plotting
import keras
from keras.models import Model
import tensorflow as tf
from os.path import join
import numpy as np
import gc
import yaml
from model_zoo import MPRAnn_heteroscedastic
'''
get the average of the predictions from all MPRAnn models trained with heteroscedastic in ... |
74b87cd5122ef77e53c86886a46de701db0b66ec00e74cef3d330ad4663ecba8 | Python | 7,484 | 226 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from enum import StrEnum
from typing import cast
from django.conf import settings
from rest_framework.exceptions import PermissionDenied, ValidationError
from cvat.apps.engine.models import Job, Project, Task
from cvat.apps.engine.permissions impor... |
79380ff54d9364331387f5d392845ae6affd19621bda640d53ed9bef624243a5 | Python | 7,485 | 188 | """Is a matched pair really the same cell? Ask its activity.
ROICaT matches on ROI footprint and position, so a spatial control cannot
distinguish "the same cell" from "a different cell in the same place". This
validates matches with signals the matcher never saw, after UnitMatch (van
Beest, Bimbard et al.), which val... |
7a5bdac6ca7101ccb410326e0756c2d05eeac6b7e03be3d07fa30e6dc6a0c26f | Python | 7,486 | 249 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
"""
import os
import open_clip
import torch
import numpy as np
from tqdm import tqdm
from PIL import Image
import cv2
from ..utils.io_helpers import check_outputfile
def extract_clip_features(
vr: object,
params: dict,
output_dir: str,
... |
ebe84d076c67df316541fd1879f1989eacde30e16ff1af298730c7f966b5964a | Python | 7,486 | 197 | """Prepare the NSD-core betas in fsaverage space.
Parameters
----------
subject : int
Number of the used NSD subject.
train_test_session_control : int
If '1', use the train and test splits consist of image conditions from
non-overlapping fMRI scan sessions.
zscore : int
Whether to z-score [1] or not [0] the fMRI r... |
428a5f6e76934a14ba9c80e40a752fe0faf82c06f0eb034117df96b5bdc98437 | Python | 7,487 | 164 | """
Interfacing between causallib and sklearn to take advantage of sklearn's
hyperparameter search machinery (e.g., GridSearchCV).
Wraps causallib's models and scorers to look like sklearn's,
and wraps sklearn's hyperparameter search models to look like causallib models.
"""
from typing import Type
from sklearn.model_... |
295b91d4dbe38b61bd0691c256c024749715df8de74cafe470a09feec551d061 | Python | 7,488 | 192 | # -*- coding: utf-8 -*-
"""
Contrast-to-noise ratio of functional time series (task-based activation)
This scripts calculates the contrast-to-noise ratio (CNR) in percent from
functional time series containing task-based activation following a block
design. The input can be a list of several runs. From the condition f... |
fdd6329be73f15252fb5c8d6722df413b1cf3839e6f16dd9ac4698e59ba614a8 | Python | 7,488 | 245 | """Multi-layer perceptron."""
from typing import Any
import torch
from torch import nn
import numpy as np
from modules.linear import SpikingLinear, SpikingEiLinear
from modules.norm1d import SpikingBatchNorm1d, SpikingEiNorm1d
from modules.activation import LIF
from utils.dim import AddTemporalDim, MergeTemporalDim,... |
843a7909b540709fd1220a1b4a67b4d90d287a26f8ed6a2b200911eddd4a7391 | Python | 7,491 | 185 | from pydantic import BaseModel, Field, model_validator
from typing import Union, Optional, Any, List, Type
from chemgraph.models.atomsdata import AtomsData
from chemgraph.models.calculators.tblite_calc import TBLiteCalc
from chemgraph.models.calculators.emt_calc import EMTCalc
from chemgraph.models.calculators.nwchem_c... |
2a28ac9144ab47c1b8a5b88510bc369ba90ee0f2352e3f90e01ab15665323337 | Python | 7,493 | 180 | # Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs (https://arxiv.org/abs/2203.06717)
# Github source: https://github.com/DingXiaoH/RepLKNet-pytorch
# Licensed under The MIT License [see LICENSE for details]
# Based on ConvNeXt, timm, DINO and DeiT code bases
# https://github.com/facebookresearc... |
8c3179dc147026b8727ea082851a9bbedf80a504b54a9e65f6b326ab7dab9b8c | Python | 7,493 | 204 | # %%
# imports per usual
from typing import Any, Callable, List, Optional, Tuple
import torch
import torchvision
from torch import nn
from torchvision.datasets import VisionDataset
# %%
# Helper function so the Dataset returns the supa raw emo class label
# Now must feed in the class list as an arg, in the event tha... |
2d3ff28a2a456d133ffae85dbe6d8cfe3bfefc1c8f3f6980bedd15376d79c1b9 | Python | 7,494 | 236 | """Strategy
1. Align code with destvi, make notebook run
2. Remove all duplicate code
3. Push
"""
import logging
from typing import Optional, OrderedDict
import numpy as np
import torch
from anndata import AnnData
from scvi.data import register_tensor_from_anndata
from scvi.dataloaders import DataSplitter
from scvi... |
7e3fbc9e10a274a0fc21e02519e28bbeae7120341842b1004279f7061569b5d0 | Python | 7,494 | 133 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
import plotting_related_functions
import KC_population_calcium_rate_model_functions as mdl
import os
from sympy import nsolve
from sympy.abc import x,y,z
rng = np.random.default_rng(666) # Set random seed
# Get the MBON ... |
a5101d50d5a3463acd6a2a38db957a8a1ffdb19ca1546b0796f6ba80befea759 | Python | 7,496 | 206 | import numpy as np
import pandas as pd
from obspy import UTCDateTime
from obspy.clients.fdsn import Client
import seisbench
import seisbench.util
from .base import WaveformBenchmarkDataset
class DummyDataset(WaveformBenchmarkDataset):
"""
A dummy dataset visualizing the implementation of custom datasets
... |
cc97058a4a6cf44fffbebbde793fd969aa0aa4ef7715a39ca0ee7e2cbb0d5ec7 | Python | 7,496 | 148 | """Export fixed paper membership from Excel without accessing any image files."""
from __future__ import annotations
import argparse
from collections import Counter, defaultdict
import csv
import gzip
import hashlib
import io
import json
import os
from pathlib import Path, PurePosixPath
FIELDS = ["sample_id", "source... |
b51c64785372c7043fe11d0c98ce4241c453e8ebc108989aae16819a15c44728 | Python | 7,497 | 249 | """LangGraph workflow for the RAG (Retrieval-Augmented Generation) agent.
This graph combines document retrieval tools (load_document,
query_knowledge_base) with the standard chemistry tools so the agent
can answer questions grounded in user-provided text documents *and*
run molecular simulations when needed.
Graph s... |
2635ec0afe534ecc12f0ac5c9e4d8070c5fa1ebb9efeb4b3858b58f6b4f04d57 | Python | 7,500 | 213 | """
Evaluate Classifier Predictions
Modified from PDX PPTC Machine Learning Analysis
https://github.com/marislab/pdx-classification
Rokita et al. Cell Reports. 2019.
https://doi.org/10.1016/j.celrep.2019.09.071
Gregory Way, 2018
Modified by Krutika Gaonkar for OpenPBTA, 2020
This script evaluates the predictions made... |
a68e214c4f8d2de1d707d784821b567781a22253794a01164b2bce1e93a051ef | Python | 7,500 | 180 | import logging
import unittest
import numpy as np
import pandas as pd
import scipy.stats as stats
import diffxpy.api as de
class TestVsRest(unittest.TestCase):
def test_null_distribution_wald(self, n_cells: int = 2000, n_genes: int = 100, n_groups: int = 2):
"""
Test if de.test_wald_loc() genera... |
5524c1eb99589974eb38865b50e02b606aa76c3eebde9866e7c811d4808e45b8 | Python | 7,501 | 250 | """
Unit Tests for H-FNO Models
Run with: pytest tests/test_models.py -v
"""
import pytest
import torch
import sys
from pathlib import Path
# Add parent directory
sys.path.insert(0, str(Path(__file__).parent.parent))
from hfno import HFNO, HFNOConfig, FNO, FNOConfig
from hfno.models import SpectralConv2d, SpectralC... |
6c81890c88c9f9686ab87b21981b3b99ff17484b72cc126f1ad2913788d89359 | Python | 7,503 | 180 | from PUMI._version import get_versions
import argparse
import ast
class BidsApp:
def __init__(self, pipeline, name, bids_dir=None, output_dir=None, analysis_level=None, participant_label=None,
working_dir='.', run_args=None, description=None, **kwargs):
if description is None:
... |
586cd7d72c399151f208eb7270e8069d0ab4bace700ea7bed9bc4f781c908d1d | Python | 7,505 | 200 | #!/usr/bin/env python
"""Agent + MCP + Globus Transfer + Globus Compute demo.
LLM agent on the laptop drives a local ``mace_mcp_hpc`` subprocess.
With both Compute and Transfer env vars set, the MCP server
auto-registers the transfer tools (``mace_mcp_hpc.py:310-313``). The
agent is told to (a) stage the demo's struct... |
0399c0cb0f45768b778c33bcb8bba2f363f2f96cd329d9873eae52fc5690a4e5 | Python | 7,506 | 213 | """
Generate observer-ignoring behavior from single player dataset and
compare with social condition data.
"""
# import sys
# import os
# sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
... |
7ab0af8539ac8c2c3334c8885c96126f081e7ad948c821e4995c79a42ad00bc4 | Python | 7,507 | 247 | import logging
import numpy as np
import pyfocus
__all__ = ["train_model", "METHODS"]
LASSO = "LASSO"
GBLUP = "GBLUP"
ENET = "ENET"
METHODS = [LASSO, GBLUP, ENET]
def _lrt_pvalue(logl_H0, logl_H1, dof=1):
from scipy.stats import chi2
from numpy import clip, inf
epsilon = np.finfo(float).tiny
lrs... |
5290dddeb562f31047ae28d116148c591cc6579cfd2e277f61c156b99b4bba14 | Python | 7,509 | 231 | # Copyright 2024 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, ... |
7e341151456e9f7f6f30102ba77420abaf1e3ea7adb08098eda6a842d9687ea5 | Python | 7,510 | 212 | from collections.abc import Callable
from dataclasses import dataclass
from functools import partial, update_wrapper
from pathlib import Path
from typing import Any
import numpy as np
import polars as pl
import torch
from PIL.Image import Image
from eir.data_load.data_preparation_modules.input_preparation_wrappers im... |
78ded533acbff72a00def70aaebfc1b904375176ad507fff97e830f3cad4d9be | Python | 7,514 | 182 | # Copyright 2016 Numenta Inc.
#
# Copyright may exist in Contributors' modifications
# and/or contributions to the work.
#
# Use of this source code is governed by the MIT
# license that can be found in the LICENSE file or at
# https://opensource.org/licenses/MIT.
import numpy
from scipy import stats
from nab.detecto... |
8c83ae59e7c3ef72a26b9ca28ffd99995d1c5610f5f09efc7d043a2423cc8604 | Python | 7,514 | 203 | # coding: utf-8
"""Compatibility library."""
import inspect
from typing import TYPE_CHECKING, Any, List
# scikit-learn is intentionally imported first here,
# see https://github.com/lightgbm-org/LightGBM/issues/6509
"""sklearn"""
try:
from sklearn import __version__ as _sklearn_version
from sklearn.base impor... |
f2f6c5e69e4de6e806a73d5525595413af93bae6f3a3627efd92f51f6e2c89d9 | Python | 7,515 | 230 | # Copyright 2024 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, ... |
b6215c34933917a630a13018ecfa999d7feb45e6465b660f00f8513661fe2998 | Python | 7,518 | 197 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from pathlib import Path
from ultralytics.utils import LOGGER, SETTINGS, TESTS_RUNNING, checks
try:
assert not TESTS_RUNNING # do not log pytest
assert SETTINGS["dvc"] is True # verify integration is enabled
import dvclive
assert ... |
7d4a2535431023edd659c5c937f261993a741e84163f7b75bdee2b429347eda5 | Python | 7,521 | 197 | from joblib import Parallel, delayed
import numpy as np
from nilearn import image
import nibabel as nib
import seaborn as sns
import matplotlib.pyplot as plt
from connattractor import network
def get_attractors_per_timesample(timeseries, hopnet, threshold=0):
def workhorse(ts_i):
activity = timeseries.loc[... |
decf9686cf54f7108ff5c7e3407937fbb83096e50366f6ad874e8581232a14ec | Python | 7,521 | 236 | """Per-exchange artifact attribution for the ChemGraph Streamlit UI.
All queries in a chat share one log directory, so "newest file in the
directory" heuristics attribute artifacts from later queries (or stale
files from unrelated runs) to earlier exchanges. Instead, the UI
snapshots the log directory before each age... |
425dcb036ef1c154515bfab6d1dde325babbd39cf7efbb988fbee732734639d0 | Python | 7,525 | 176 | """Pydantic schemas for MACE Parsl simulations.
These schemas define the API contract for MACE single and ensemble
calculations dispatched via Parsl.
"""
from __future__ import annotations
from pydantic import BaseModel, Field
class mace_input_schema(BaseModel):
input_structure_file: str = Field(
descr... |
71c34b42aa5bb0c31ffc8c77eea53e6666966fc5e74871121c8a51157365b45e | Python | 7,525 | 224 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from abc import ABCMeta, abstractmethod
from collections.abc import Callable
from typing import Any, ClassVar
import django_rq
from django.db.models import Model
from django_rq.queues import DjangoRQ
from rest_framework import status
from rest_frame... |
540793a525fa10a84621e2b4e1a2ac37767ec9cef04e226431ffe6edabebfe5f | Python | 7,526 | 158 | """Tests for the activation-cache stimulus-identifier contract.
Regression guard for the Zerbe rdm/cka family, which lost caching entirely
because the benchmark synthesised an identifier that no registered plugin
matched. See :mod:`brainscore_vision.benchmark_helpers.cache_contract`.
"""
from __future__ import annotat... |
bdbac4a7db753b03a2455c8e355b82748432a980fb8d65388a7c034ed57552d5 | Python | 7,528 | 230 | import torch
import numpy as np
import pandas as pd
from tqdm import tqdm
from datetime import datetime as dt
from dataset_tool import fast_merge,df_to_mask
import os
print('loading raw data')
node=pd.read_json("../datasets/Twibot-20/node.json")
edge=pd.read_csv("../datasets/Twibot-20/edge.csv")
label=pd.read_csv("../... |
2f664c7a6310ba7fc40319e8be31f19ab3d962b835276a4fc0c777651b73d89c | Python | 7,530 | 180 | import pandas
import json
import torch
import os.path as osp
from tqdm import tqdm
from torch_geometric.data import Data
from torch_geometric.loader import NeighborLoader
from model import BotGAT, BotRGCN
import torch.nn as nn
from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score
... |
ca47acb54bdb2ea79d912fb91dd888d70434264078c20808b9f73d12097c4eb9 | Python | 7,530 | 173 | # -*- coding: utf-8 -*-
"""
Created on Sat Oct 16 15:48:15 2021
@author: Yoshi
"""
import os
import shutil
import math
import statistics
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from numpy.polynomial import Polynomial
def bandwidth_analysis(path,key,cell_flags,correlation_coefficients... |
3c9ebb1b11a29c09cb73a914d18778e3c4620452532a77fc135c7c459017e744 | Python | 7,531 | 178 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch import nn
from torch.nn import functional as F
from typing import Any, Dict, List, Tuple
from .i... |
00b585796a8bf9cf4af809ada920ba80b2bfbd3f4c352ec9247490d1dff40ace | Python | 7,532 | 227 | # -*- coding: utf-8 -*-
import unittest
import arbor as A
from arbor import units as U
import numpy as np
"""
tests for cable probe wrappers
"""
# Test recipe cc comprises one simple cable cell and mechanisms on it
# sufficient to test cable cell probe wrappers wrap correctly.
class cc_recipe(A.recipe):
def __... |
1a39d1a61f55e3c3fb8a32365f701becbe69f2d8db65fba61ed2c3212350fc54 | Python | 7,534 | 209 | """Test network constructor and BaseModel and KANModel integration."""
import copy
from collections.abc import Generator
from itertools import product
import pytest
import torch
from omegaconf import OmegaConf
from mcmlnet.training.models.base_model import BaseModel
from mcmlnet.training.models.kan_model import KANM... |
dc9d4310be238718f7f2faa062183fa962a3dac7507df484a7af016c2992506d | Python | 7,537 | 249 | from __future__ import annotations
import json
import numpy as np
import osam
import pytest
from numpy.typing import NDArray
from labelme._automation._text_detection import MaskOutputUnavailableError
from labelme._automation._text_detection import get_bboxes_from_texts
from labelme._automation._text_detection import... |
0117eacdbcf98de64f031ff43b96ad23a0d735b529511cfa0aab22c919f6d4dc | Python | 7,540 | 177 | """Test node cartography / modularity-dependent metrics parity with MATLAB.
Run from the repo root::
uv run python python/test_pipeline_cartography.py
Modularity (community detection via Louvain + consensus clustering,
``modularity.py``) is inherently stochastic — MATLAB's own runs aren't
bit-reproducible across... |
1ad39c06096eaf4ee94a5c98127fb24e5db60c6c966423ae7425443c2a8311c1 | Python | 7,542 | 209 |
# Brandon Amos, J. Zico Kolter
# A PyTorch Implementation of DenseNet
# https://github.com/bamos/densenet.pytorch.
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.autograd import Variable
import torchvision.datasets as dset
import torchvision.transforms as ... |
f05e54a37c43f836271750a54794e6cc6a9a5c23d388001a96ac3f97759f7b5b | Python | 7,543 | 298 | # -*- coding: utf-8 -*-
"""
Spyder 编辑器
这是一个临时脚本文件。
"""
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
############ data prepare
res18fp_x = np.load('S-ResNet18_FP_x.npy')
res18fp_y = np.load('S-ResNet18_FP_y.npy')
res18fp_x = np.delete(res18fp_x, 1... |
30c0074b9947fdf91df02ea3b71a92d956410d3ddd0029f2fc61f0bb9d35b095 | Python | 7,544 | 178 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
import numpy as np
import sys
import os
from datetime import datetime
from tf_agents.environments import utils
from tf_agents.distributions.utils import SquashToSpecNormal
f... |
5c76e4944413f5db9424ed6e3a7b35571614eb9d9591341110136c03e02bff9e | Python | 7,544 | 195 | """Fast regression tests. None of these need the models or the reference database.
Each test corresponds to a defect that reached a release or a release candidate,
so a failure here means a bug we have already shipped once is back.
"""
import subprocess
import sys
import textwrap
import numpy as np
import pandas as p... |
8a78e2ac31be11033dcc6b63b50a03f5c57c76db0f99d52b84942a8d2fb1e0d0 | Python | 7,547 | 214 | import json
from pathlib import Path
# Define notebook categories. Note the order is retained in the website.
MODELS_NOTEBOOKS = [
'ipw.ipynb',
'standardization.ipynb',
'doubly_robust.ipynb',
'TMLE.ipynb',
'rlearner.ipynb',
'xlearner.ipynb',
'causal_survival_analysis.ipynb',
'matching... |
283f60bdb72e97efd7fb191284b25fcf33c8ce86390803ce40a00a040ce55c2c | Python | 7,548 | 198 | import numpy as np
from mat73 import loadmat
import os
import pandas as pd
def save_datastructure(
path="datasets/DataFromVahid",
expert=True,
save_video=True,
save_clusters_info=True,
):
"""Transforms the matlab file with the data in a folder structure that can be loaded easily to a pytorch datas... |
68873d86773d553465cfbb17e2741fb709a758d6887ce2ecd30c9650ce8681ea | Python | 7,549 | 127 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'galvo.ui'
#
# Created by: PyQt5 UI code generator 5.7
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Dialog(object):
def setupUi(self, Dialog):
Dialog.setObjectName(... |
885b8fd2ccfb8ee27c02d3a382e2951622fdcbc2af2bbca375aaf71d40f5f246 | Python | 7,549 | 200 | '''
Modified from https://raw.githubusercontent.com/pytorch/vision/v0.9.1/torchvision/models/resnet.py
BSD 3-Clause License
Copyright (c) Soumith Chintala 2016,
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions a... |
165a25cb0fa0f8348d6def9c378974701cde6c4b21bd0c2956279235ce9620ff | Python | 7,550 | 200 |
from brainscore_vision.model_helpers.check_submission import check_models
import functools
import numpy as np
import torch
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from PIL import Image
from torch import nn
import pytorch_lightning as pl
import torchvision.models as models
import ... |
4862490ad2992edcb4d9ec356b58e79852c64d7a81415cd50f71c894343cd03a | Python | 7,550 | 147 | """Acquire public audit inputs without overwriting or silently refreshing them."""
import hashlib
import json
from datetime import datetime, timezone
from pathlib import Path
from urllib.request import Request, urlopen
from urllib.error import HTTPError
ROOT = Path(__file__).resolve().parents[2]
MANIFEST = ROOT / 'me... |
4a8f3b9f51abab8607f4f158909f2084cb01486316c5fd5455884a9b9d57b7fd | Python | 7,550 | 200 |
from brainscore_vision.model_helpers.check_submission import check_models
import functools
import numpy as np
import torch
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from PIL import Image
from torch import nn
import pytorch_lightning as pl
import torchvision.models as models
import ... |
8a1650f96627733ea0a4a926bb549b67cae8529d8246c4503860d89c87166405 | Python | 7,550 | 200 |
from brainscore_vision.model_helpers.check_submission import check_models
import functools
import numpy as np
import torch
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from PIL import Image
from torch import nn
import pytorch_lightning as pl
import torchvision.models as models
import ... |
c32bf3cff372b265da0dc0ef836c5d72092cacdc892a775ca87dc94f3e8fbf97 | Python | 7,550 | 200 |
from brainscore_vision.model_helpers.check_submission import check_models
import functools
import numpy as np
import torch
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from PIL import Image
from torch import nn
import pytorch_lightning as pl
import torchvision.models as models
import ... |
2c9f40998b02bd14932321b56bac5054ead486b143462453bf1c259fd09d5786 | Python | 7,553 | 279 | # -*- coding: utf-8 -*-
"""
Interface to tif image files and stacks.
The interface makes use of the tifffile library.
Example:
>>> import os, numpy
>>> import ClearMap.IO.TIF as tif
>>> from ClearMap.Settings import ClearMapPath
>>> filename = os.path.join(ClearMapPath,'Test/Data/Tif/composite.tif')
... |
5a31741dc8304337f1bcb9b543ad58928b067a2d8ec5a6d437d423689bf45f27 | Python | 7,553 | 235 | #!/usr/bin/env python
# author: Jannes Spangenberg
# e-mail: jannes.spangenberg@uni-jena.de
# github: https://github.com/JannesSP
# website: https://jannessp.github.io
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, Namespace
import pysam
from pathlib import Path
from statistics import median
impor... |
ece9dc0a3bf2c17465700121a86a3504d38e8b6cd737499b86d29e0b20f0cc1f | Python | 7,553 | 77 | import utime
# Segment 1: The ECG Signal Data
# We use a tuple of tuples for better memory efficiency on the Pico
# Fixed Segment 1: All inner braces replaced with parentheses
ECG_SIGNAL1 = (
(53,79),(52,78),(50,76),(47,74),(44,72),(41,70),(37,68),(34,67),(31,66),(28,65),(26,64),(24,62),(22,60),(21,58),(20,5... |
1a7884aba847c0891707dbf796a5032af97ca5e87a5eed2ffe00f8fec7303fc2 | Python | 7,556 | 227 | from pathlib import Path
import json
import pytest
from chemgraph.tools.ase_tools import (
run_ase,
get_symmetry_number,
is_linear_molecule,
)
from chemgraph.tools.cheminformatics_tools import (
smiles_to_atomsdata,
molecule_name_to_smiles,
)
from chemgraph.schemas.atomsdata import AtomsData
from ch... |
7523b0882d931a8cebdfe6c6ade2858bc3ba1b03ab8c1d8a4ffee820db3b1774 | Python | 7,557 | 141 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 5 16:05:31 2024
@author: Amit Jaiswal, Megin Oy, Espoo, Finland <amit.jaiswal@megin.fi>
USAGE:
* This script is meant to check the quality of ICA applied through MEGnet and
override the ICA application with user's own selections.
... |
c75a09b488c6b2c2dd7561ab08b39676bd6ce3ad1efe7726c96e084229c2097f | Python | 7,557 | 235 | #!/usr/bin/env python
# author: Jannes Spangenberg
# github: https://github.com/JannesSP
# website: https://jannessp.github.io
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, Namespace
import pysam
from pathlib import Path
from statistics import median
import numpy as np
import json
import sys
from... |
68f7bf27d7708858064ea26f0000b822907cdd9bcff213fb4fd4b891577669f5 | Python | 7,558 | 188 | """Custom state initializers with permanent properties between trials"""
import numpy as np
import collections
from moog import sprite
from . import poll_generator
from moog.state_initialization import distributions as distribs
class ParentStateInitializer():
def __init__(self, agent_0_factors, agent_1_factors,
... |
0dfd4e3c72a88dc081892218c677104e705d556af32c31e30f1af366e601fccb | Python | 7,561 | 207 | #!/usr/bin/env python
"""
This script is used to extract sequences from bed file.
USAGE
getseqfrombed.py {OPTIONS} <.bed file|-> <reference .fasta file>
OPTIONS
-b/--seqerror [error file]\tSpecify the positional error profile to be used. The file should include at least 100 lines, each containing a positive numb... |
18f8d151c8767bc28be9d2ca4eb055557d14b40fd9c13f956caab67022569859 | Python | 7,561 | 184 | import torch
import torch.nn as nn
from torch_geometric.nn import GATConv, global_mean_pool
from torch_geometric.utils import add_self_loops
class GSR(nn.Module):
"""
Graph Structure-Recognition (GSR) model for molecular property prediction
using Graph Attention Networks (GAT) - TChemGNN from the paper.
... |
739c7eef0b514b345406aac6766b79b01c89091486cd4ca987ee91302e68257a | Python | 7,561 | 196 | import copy
import io
import socket
import subprocess
from concurrent.futures import ThreadPoolExecutor
from pathlib import Path
from typing import Any, Dict, Generator, List
import numpy as np
import pytest
from sklearn.datasets import make_blobs, make_regression
from sklearn.metrics import accuracy_score
TESTS_DIR ... |
7d75c41bd2193d50ead5e3cb7fd3dd45bd2595b3ec0a707fcd61dfc2a2c62955 | Python | 7,561 | 189 | # /------------------------------------------------------------------------------+
# | 19-JUL-2022 |
# | Copyright (c) Bone Imaging Laboratory |
# | All rights reserved ... |
b56cf00a37d3f5c15d41493b5405fb2940ca2ae2261cacc4b153e16a134b1f60 | Python | 7,561 | 190 | from bread.data import Features, Segmentation, Lineage
import networkx as nx
import pandas as pd
import numpy as np
from numpy.linalg import norm
import cv2
__all__ = ['build_cellgraph']
def build_cellgraph(feat: Features, time_id: int, cell_features, edge_features, return_df: bool = False, seg: Segmentation = None)... |
039151bc3d576269e21dfa6b9c4827df5a18d2de3cefc74933e5129b0f3bcb90 | Python | 7,562 | 221 | import json
from collections.abc import Callable
from pathlib import Path
from typing import TYPE_CHECKING, Any
import numpy as np
from aislib.misc_utils import ensure_path_exists
from sklearn.preprocessing import KBinsDiscretizer, LabelEncoder, StandardScaler
from eir.target_setup.target_setup_utils import IdentityT... |
24af09b73fe808d3f029caf22f2d8c884487ee1865f997f9e4db3c4f16eaa3b7 | Python | 7,565 | 262 | from dataclasses import dataclass
from functools import partial
from typing import (
TYPE_CHECKING,
Literal,
Protocol,
TypeGuard,
Union,
)
import torch
from torch import Tensor, nn
from eir.models.input.array.models_cnn import CNNModel, CNNModelConfig
from eir.models.input.array.models_locally_con... |
cd63a0c3bb8f9ba3020584123c9cde8a3a130d36ba82464bf66cdf1d80d9c5da | Python | 7,567 | 208 | import pandas as pd
import numpy as np
from sys import argv
import pickle as pk
import os
import random
import xgboost as xgb
from sklearn.preprocessing import MinMaxScaler
def add_into_single_df(list_of_dfs):
df = pd.concat(list_of_dfs)
df = df.reset_index(drop=True)
df["locus"] = pd.factorize(df["filenam... |
e0e8e8fc8700b54951c9d7c1baa50517e3a63ac76b8ee72e8670ee95dd683fc2 | Python | 7,567 | 211 | #!/usr/bin/env python3
"""Audit cached pretraining clips using canonical kinescope kinematics modules."""
from __future__ import annotations
import argparse
import pathlib
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from kinescope.kinematics import (
angle_features,
corr_lr,
g... |
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