sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b5c9e45058005dc86aa33151c1bf57f07a1fb805c1ef2b88a01acdc77328a078 | Python | 5,365 | 166 | # %%
from pathlib import Path
import h5py
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import torch
from fastai.learner import load_learner
from PIL import Image
from marugoto import mil
from marugoto.mil.data import get_target_enc
__all__ = ["plot_top_att_tiles_", "plot_top_att_from_df_"]
... |
d0ef00013dfb9bcb2fa07ede09db1f2b65a4479ba61066eba49bd6c5bb86be68 | Python | 5,368 | 154 | # Copyright (c) 2017-present, Facebook, 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 agreed... |
6da6a70ffba23824154eb6192d32d7b8fc4761e890059e054fe083e9a83184ed | Python | 5,369 | 140 | r"""``ov.epi.pp`` — epigenomics preprocessing (wraps :mod:`epione.pp`).
Quality control, fragment ingestion and feature-matrix construction for
single-cell ATAC-seq, delegating to `epione <https://github.com/aristoteleo/epione>`_.
Each function imports epione internally, so importing omicverse stays cheap.
Typical sc... |
86f5b4bc8185cdb3341355452d5c4fa74a0fb6be5c97470a8c99b9efb24e68e8 | Python | 5,369 | 210 |
import csv
#import itertools
#import operator
#import numpy as np
#import nltk
import os
#from rdkit import Chem
#from rdkit.Chem import Draw
#from IPython import display
#import matplotlib.pyplot as plt
#from rdkit.Chem import Descriptors
""" def zinc_data_with_bracket():
sen_space=[]
#f = open('/Users/yan... |
3a3994038396121256ecd0411db2f5c53d739a591cad3c78c60fe2cacd76770f | Python | 5,372 | 172 | # 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, ... |
f2b226af8634e25a7f9bcfea9699fca482b1eed3bb698dcb0600e1914f016821 | Python | 5,374 | 188 | import torch
import torch.nn.functional as F
from math import exp
def gaussian(window_size, sigma):
gauss = torch.Tensor(
[
exp(-((x - window_size // 2) ** 2) / float(2 * sigma**2))
for x in range(window_size)
]
)
return gauss / gauss.sum()
def crea... |
e9fad503a7bff6a700f9892ab3596c9470099fa8b54ee5b352fe319f97956ac3 | Python | 5,380 | 121 | ####################################################################################################
# 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... |
7b1bf39692b98876b8628ec572043686db320a1f693d679fa4f6f99ae89fe21d | Python | 5,381 | 160 | # Copyright 2023 The HuggingFace Team. 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
#
# Unless required by applicabl... |
1306123e714b4f3ca932cda3f7093eec117751ddf2aa4069ae6948d78fb0264c | Python | 5,383 | 134 | import math
import torch
from torchEnKF import nn_templates
from torchdiffeq import odeint_adjoint
from torchdiffeq import odeint
from tqdm import tqdm
import os
import sys
sys.path.append(os.getcwd()) # Fix Python path
def generate(ode_func, obs_func, t_obs, x0, model_Q_param, noise_R_param, device,
ode... |
fe21fab07090a8869d8385691d7ad0abe877b37e250d25dabcf3441eee6f1a84 | Python | 5,384 | 104 | import os
import torch
import random
import pandas as pd
from model import PretrainModel
from dms import ProcessingData, train_model, validation_model, test_model
#######################################################################
# predifined parameters
############################################################... |
0659c6a72a30cd63f4c2b2cfb28b855922f5564658ecf18f307c22e75e4d12df | Python | 5,385 | 194 | """
Implementing "a network with residual connections" example in https://github.com/synsense/sinabs/issues/181
"""
import torch.nn as nn
from sinabs.activation.surrogate_gradient_fn import PeriodicExponential
from sinabs.layers import IAFSqueeze
dcnnl_map_1 = {
0: {
"input_shape": (2, 34, 34),
"... |
47a074756e88b5f24e96b57e9827b5f35a11cd0088014ca2267d37c45054cdb1 | Python | 5,390 | 128 | import matplotlib.pyplot as plt
import pickle
import numpy as np
import sys
import os
# from Step_7_util import *
from sklearn.metrics import accuracy_score, confusion_matrix, roc_auc_score, roc_curve, precision_recall_curve
np.set_printoptions(threshold=sys.maxsize)
def main():
splam_v2_j_shuffle_pred_prob = []... |
4f588fcabbf2ed2ed0996a5934d2a0dd267617bf0d982673ace39bd450b1a4dd | Python | 5,390 | 165 | from array import array
import os
from pathlib import Path
import pdb
import pickle
import numpy as np
import oci
from multiprocessing import Process
from multiprocessing import Semaphore
import ocifs
import torch
import yaml
# Number of max processes allowed at a time
concurrency= 5
sema = Semaphore(concurrenc... |
d297839f8dc78a9e3d60da9fabef984b7e19f58927d63e306dabe886d8fe2cf0 | Python | 5,392 | 173 | """Database utilities and initialization."""
import logging
from typing import Optional
from sqlalchemy import create_engine, event, text
from sqlalchemy.orm import Session
from sqlalchemy.pool import Pool
from src.models.base import Base, init_db
from ..config import settings
logger = logging.getLogger(__name__)
... |
ef214b97f86434fd458b9a718774e84a8a46f1562c02932f2dd5caccdbab4ff3 | Python | 5,392 | 63 | """Merge event related average measurements into a single nifti."""
import os
import subprocess
import numpy as np
import nibabel as nb
import glob
# =============================================================================
FOLDER = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti/derivatives/sub-06... |
5a436de56ba636669eff4ec0ee6578ee7096d32103db587e5658c7b1e0c6db8d | Python | 5,393 | 191 | """ This module contains utilities for processing cortical surface drawings.
In general we take these as given (they even take precedence of e.g. the
upper and lower surfaces of layers 1 and 6b for instance), but some drawings
pose resolvable problems.
The main such problem occurs when cortical layer drawings exten... |
d70f400e32f0ee54e3ddc98628432727bd967b00e91fe4aef1856f32ee64ec4a | Python | 5,393 | 197 | # flake8: noqa
"""
Cross-node parallelism examples for Ray Serve LLM.
TP / PP / custom placement group strategies
for multi-node LLM deployments.
"""
# __cross_node_tp_example_start__
import vllm
from ray import serve
from ray.serve.llm import LLMConfig, build_openai_app
# Configure a model with tensor parallelism a... |
67af56eeec4d87fd79fc8c6a399112e9e9ac5cb4efe7ef219513fc4b088c4be6 | Python | 5,395 | 133 | """
Functions to identify TE-dependent and TE-independent components.
"""
import logging
import numpy as np
from tedana import utils
from tedana.metrics import collect
from tedana.selection.selection_utils import clean_dataframe, getelbow, getelbow_cons
from tedana.stats import getfbounds
LGR = logging.getLogger("GE... |
4a29923a91472e0aaa4e1ef4bd16fe92998f2be900d62ed9c13496b3f5eb7f24 | Python | 5,397 | 174 | from typing import List, Optional
from itertools import chain
import math
import torch
import numpy as np
from scipy.spatial import Delaunay
import scipy
from anndata import AnnData
def alpha_shape(points, alpha, only_outer=True)->List:
"""
Compute the alpha shape (concave hull) of a set of points.
P... |
5842df464032cd56c161c6ae1408d1ce7d4e5ea3af4dae6d269c6d0e2f70bf7d | Python | 5,398 | 162 | import collections
import numpy as np
from neuron_morphology.validation.result import NodeValidationError as ve
from neuron_morphology.constants import *
def validate_radius_threshold(morphology):
""" This function validates the radius for types 1, 3, and 4 """
result = []
soma_radius_threshold = 35
... |
fd6c674be39a763a86f6299682ff95e8e3ef1a2f6d34c281a780b6ed00c90a37 | Python | 5,398 | 143 | """Real scRNA-seq data for the ``ov.single`` metabolism tutorial.
Loaders download a dataset asset from the ``omicverse-data`` GitHub
release (``metabolism-v1``) on first use, cache it under ``dir``, and
return it ready for the single-cell metabolism workflow
(:class:`ov.single.Metabolism` — scMetabolism / Compass / s... |
85037b2c3ca9ca8c525ae1b365835e13a9bf9bfd46e240cfbf87e1a0deb72f55 | Python | 5,399 | 112 | # -*- coding: utf-8 -*-
"""Rolling shutter diffuserCam utility functions.
Heavily referenced from Nick Antipa's MATLAB code::
https://people.eecs.berkeley.edu/~nick.antipa/antipa_files/hsvideo_code_with_data.zip
"""
import numpy as np
from skimage import io as skimageio
import skimage.transform
from absl import ... |
0be9fc03028a604cd70de9d60c9102575b64e305379908be40b8cc4cd20b660b | Python | 5,400 | 131 | import numpy as np
import torch
import pickle
import lpips
from eval_fns.eval import Masked_MS_SSIM, compute_convolutional_max_metric, compute_convolutional_min_LPIPS
from lib.data_utils.matched_cells_struct import OrderedMatchedCellsStruct
import lib.dataset_config_parser.dataset_config_parser as dcp
from lib.datas... |
67d49fab06dc637d194c81a6691256aedf7a2acb9cfe0eff1a1a2896d001816c | Python | 5,400 | 107 | from loguru import logger
import os
import argparse
import random
import numpy as np
from deltasplice.utils import MutGenerator, GetSummaryStatisticsCallback
from deltasplice.models.model_utils import (
get_available_gpus,
)
import torch
from torch.utils.data import DataLoader
import copy
import deltasp... |
0b851b5f2898ea81fda91bfe4db63d5704ae38ffc733c11f3b9a9f4f3109cb87 | Python | 5,401 | 142 | import requests
from .__config import base_url
from .__aux_funcs import process_response
def get_all_sample_lists(projection="SUMMARY", direction="ASC", pageNumber=0, pageSize=10000000, sortBy=None):
"""
Get all sample lists. \n
:param projection: Level of detail of the response. \n
Possible values... |
339d502454f66875712c773d6dbe6a831ae5dffb3e3337ae67b8ebf0072e2376 | Python | 5,405 | 177 | """
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 numpy as np
import pytest
import torch
from ase.geometry.geometry import general_find_mic
from ... |
febe3598ca493739f6aeb14523eaabce945b064d5e8fe00871e660a97e168c83 | Python | 5,405 | 151 | import torch
import torch.nn.functional as F
import torch.nn as nn
import math
from models.DeepLab.modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
import torch.utils.model_zoo as model_zoo
def conv_bn(inp, oup, stride, BatchNorm):
return nn.Sequential(
nn.Conv2d(inp, oup, 3, stride, 1, bia... |
9171f0e1d09967cd37843acc4bba983d6a75d15bb9d33c22347c44351ee7c8a8 | Python | 5,408 | 134 | #!/usr/bin/env python
# import
## batteries
from __future__ import print_function
import argparse
import logging
## 3rd party
import networkx as nx
from networkx.algorithms.dag import descendants
from networkx.algorithms.lowest_common_ancestors import lowest_common_ancestor
from networkx.algorithms.shortest_paths.unwei... |
b82d7edb5e52a8ae57f015e31584d533ac3c16ec50aa285e07bb861fbaf07470 | Python | 5,408 | 160 | import torch
import torch.nn as nn
import torch.nn.functional as F
from .utils import preprocess_graph
class GraphAttentionLayer(nn.Module):
"""
Simple GAT layer, similar to https://arxiv.org/abs/1710.10903
"""
def __init__(self, in_features, out_features, dropout, alpha, concat=True):
super(... |
5e56df01fb32fbc8f020206a3ecb663242fae4918ee29a62f9ade3be659da166 | Python | 5,410 | 127 | ####################################################################################################
# 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... |
c643a69478a931b52fbb6519ade7b6a8470358de84004209be1ddcab926d4886 | Python | 5,411 | 171 | from imports import *
# Lazy import
from ngs_mapper.bqd import (
G, N, LC, LQ, LCQ
)
class Base(BaseTester):
modulepath = 'ngs_mapper.bqd'
def setUp(self):
pass
def _make_lineargs(self, regiontypes):
lineargs = {}
for r in regiontypes:
lineargs[r] = {'color':r,'li... |
cd0fad9d935b0cae6e4a2c55a15be1f68770efab182ce11f7cce63862cb4e323 | Python | 5,411 | 149 | import torch
import torch.utils.data as data
import os
import random
import glob
from PIL import Image
from utils import preprocess
import numpy as np
import cv2
class DMData(data.Dataset):
CLASSES = [
'BG','DM'
]
def __init__(self, root, train=True, test=False, inference=False,transform=None, tar... |
00b3af740da6417e13470b0faf5b017ba103528550316e862c2f844e65bfcd07 | Python | 5,413 | 86 | proj_dir = "/path/to/main_project_folder/" # edit this line
import numpy as np
import pandas as pd
import xarray as xr
import dask.array as da
import glob as glob
from functools import partial
import os
import sys
sys.path.append(proj_dir)
from project_fxns import load_region
from project_fxns import fxns
import impor... |
7a9cad2395ee3e7a62704022e61bdc2bc993232fec42e91fa8b6e364babbab39 | Python | 5,413 | 152 | import os
from concurrent import futures
from typing import Any, Optional, Sequence, Tuple
import grpc
from grpc import aio as aiogrpc
import ray
from ray._common.tls_utils import load_certs_from_env
from ray._private.authentication import authentication_utils
def init_grpc_channel(
address: str,
options: O... |
6804b3aa15e53e3c42bee2e59435f878734e9372888b82742aa0c8fce233ebb7 | Python | 5,414 | 132 | from loguru import logger
import os
import sys
import json
from deltasplice.constant import CL, EL, Fapath
from bisect import bisect_left
import numpy as np
from pyfasta import Fasta
from pyliftover import LiftOver
SavePath = "data/sQTLs"
def parse_line(line, i):
line = line.replace("\n", "").split("\t")
Na... |
8f1f681073d45a5a7a1c341602ef12f12846100d4f9cc5609fefc58a229295aa | Python | 5,414 | 224 | import time
from typing import Any, Type
import pytest
import ray
from ray.air.execution._internal import Barrier
from ray.air.execution._internal.event_manager import RayEventManager
from ray.exceptions import RayTaskError
@pytest.fixture(scope="module")
def ray_start_4_cpus():
address_info = ray.init(num_cpus... |
a8f753f94e4108c361c08e25508b826b91a82e28ab1a4b7efea924e6c58de2a0 | Python | 5,414 | 173 | # Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
import os
import json
import torch
import clip
from PIL import Image
import numpy as np
from torch.utils.data import dataset
import torchvision.transforms as transforms
from bert_embedding import BertEmbedding
from timm.data.constants import IMAGENET_D... |
ea63613af6ae7074c5a35604fc88068580df8ef909b79484b7d44c68e31c75f1 | Python | 5,414 | 120 | ####################################################################################################
# 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... |
ebf648470cef49ae678c0890410df25dd874bdfe0159f4e7d78e5b08ccb9bf0b | Python | 5,416 | 126 | import scipy.io as sio
import os
import numpy as np
import h5py
import sys
# from skimage import filters
from scipy.ndimage import gaussian_filter
import time
import multiprocessing as mp
sys.path.insert(1, '../SUNS2') # the path containing "suns" folder
from suns.PreProcessing.preprocessing_functions import preproces... |
8163ce294b949388dc2134dc1bf792b44fac7286db0ef812dc0c1ad1d7aa21b7 | Python | 5,418 | 152 | # 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... |
7691ce13feab9367b77364d4de6d296f7990a0097052f477c458f99fc1c4ae3e | Python | 5,419 | 197 | """
Utilities for the chord diagram.
"""
from collections import defaultdict
import numpy as np
def dist(points):
'''
Compute the distance between two points.
Parameters
----------
points : array of length 4
The coordinates of the two points, P1 = (x1, y1) and P2 = (x2, y2)
in th... |
ca8cea9a94f29eeeebec4e477c3e5807e52317d1f4dd07b6c76ac7600c13ff7f | Python | 5,419 | 129 | ####################################################################################################
# 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... |
eccdc3aebb44d3879a256b3c272b38a041b84b1aec08dc50101ce847d1870ff0 | Python | 5,419 | 122 | import torch
import numpy as np
import argparse
import pickle
from typing import List
from lib.data_utils.matched_cells_struct import OrderedMatchedCellsStruct
import lib.dataset_config_parser.dataset_config_parser as dcp
from lib.dataset_config_parser.dataset_config_parser import read_config_file
import lib.data_uti... |
efc98320783eecfae712d25a4154cb1850e3bb8411e0017dd38e1aa8d2e35064 | Python | 5,420 | 124 | import random
import numpy as np
from projectmetis.python.logging.metis_logger import MetisLogger
class DataPartitioning(object):
def __init__(self, x_train, y_train, partitions_num, seed=1990):
self.x_train = x_train
self.y_train = y_train
self.partitions_num = partitions_num
s... |
874dce25cd8c1907a2358d9fcf14a0a317e272653bd55a8f1dca1c3f161f11f1 | Python | 5,423 | 148 | import torch
import torch.nn as nn
from torch_geometric.nn import GCNConv, NNConv, GINConv, GATConv, Set2Set
class GNNm(nn.Module):
def __init__(self, n_features, hidden_dim, n_classes, n_conv_layers=3, dropout=0.1,
conv_type1="GIN",conv_type2="GIN",batch_norm=True, batch_size=128):
supe... |
ba6770ec40684c39634ecc51c436269a0da5849956f2f9a5c880382aa86a57c5 | Python | 5,423 | 179 | """
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 random
from functools import partial
import numpy as np
import pytest
import torch
f... |
e679d78f8a2eff05a1329d62ca3ffade1954bd41a311c51bc340f1342522b0fa | Python | 5,424 | 142 | r"""Convenience loaders for 10x Visium demo datasets used by HE-zoo.
Two adjacent sections from the same patient/block are pre-wired:
* **Section 1** (``load_breast(section=1)``, the default) — used as the
reference / training slide across all HE-zoo tutorials.
* **Section 2** (``load_breast(section=2)``) — the *he... |
ed3386f9b79d4513e49f06918f31e136d88f262e56d2f24592c820a2dbb17a09 | Python | 5,424 | 152 | """Runtime-specific data location constants and associated helper methods.
TODO(everyone):
* Add more datasets and data types as needed.
* Update logic to determine runtime as needed.
* Update Cloud Storage and persistent disk paths as needed.
"""
import collections
from enum import Enum, auto
import os
class Runti... |
f03f3a267da8de7e753dc42c79df25d8cc4a473ad0464878995245080f4876c5 | Python | 5,424 | 168 | from dataclasses import dataclass
from torch import nn
import torch
from tqdm import tqdm
import pdb
from latent_time_stepping.time_stepping_training.train_steppers import BaseTimeSteppingTrainStepper
@dataclass
class EarlyStopping:
num_non_improving_epochs: int = 0
best_loss: float = float('inf')
patien... |
299cb111afa7e91ce19dee85b138325e5ede439590276c16ffeadeff48c77605 | Python | 5,426 | 140 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 9 10:24:09 2023
@author: hansav
"""
import os
import pickle
import pandas as pd
import numpy as np
import pcntoolkit as ptk
from pcntoolkit.dataio.fileio import load as ptkload
from pcntoolkit.dataio.fileio import save as ptksave
from pcntoolkit.... |
96914017e251b521140306ddf5a997c210d305e6ac3c1ef0738088d0d05c1ff6 | Python | 5,427 | 134 | ####################################################################################################
# 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... |
9de154990cd71786a0ce7325e5f635e6574b23a95a23a06b2db156a932df7943 | Python | 5,431 | 140 | # -*- coding: utf-8 -*-
"""
Pairwise functional alignment.
==============================
In this tutorial, we show how to better predict new contrasts for a target
subject using source subject corresponding contrasts and data in common.
We mostly rely on python common packages and on nilearn to handle functional
da... |
1b0f8388a73a3699768ed254716556a0d5ee91f7eb1453f4a86a92caaed97b80 | Python | 5,432 | 165 | import unittest
import numpy as np
import neuron_morphology.features.layer.layer_histogram as layer
from neuron_morphology.feature_extractor.data import Data
from neuron_morphology.features.layer.reference_layer_depths import \
ReferenceLayerDepths
from neuron_morphology.features.layer.layered_point_depths import... |
9607f6c2cfdeb51813b4845013e5568b5ef5fac6fb00b5904a95b4bf19800fcc | Python | 5,432 | 98 | import os
from typing import Optional, Sequence, Tuple, Set
from sv_utils import pedigree_tools
class Default:
resources_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "resources")
ped_file = os.path.join(resources_dir, "1KGP_2504_and_698_with_GIAB.ped")
random_seed = 0
class SubsetData... |
cf93e1bb203d17fcd07bc761891245fc80ad3f9ab720a8cacec84c1c217dd489 | Python | 5,432 | 155 | from ray.dag import DAGNode
from ray.util.annotations import DeveloperAPI
@DeveloperAPI
def get_dag_node_str(
dag_node: DAGNode,
body_line,
):
indent = _get_indentation()
other_args_to_resolve_lines = _get_other_args_to_resolve_lines(
dag_node._bound_other_args_to_resolve
)
return (
... |
3c0f85854c912ef301e0fb2fb0151e0fcf968f9abba6b253a7c0fc12d863defa | Python | 5,433 | 159 | from numpy.random import seed
seed(1)
import tensorflow as tf
tf.random.set_seed(1)
import random
random.seed(1)
import tensorflow as tf
import csv
import numpy as np
import SimpleITK as sitk
import matplotlib.pyplot as plt
from numpy import argmax
import pandas as pd
import tensorflow.keras.backend as K
... |
50f5f6a1c8307be8481bd6459830ded848eab1bd6e9de60a18ee72bd07991a4e | Python | 5,433 | 136 | # -*- 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 quantized tile functionality."""
from typing import Union
from pytest import mark
import torch
from aihwkit.nn import AnalogLinear
from aihwkit.s... |
e4b2a1cd3219c8fd71d0216b1cd2186b4d3891117a6354e1363ef013c2e701ae | Python | 5,437 | 149 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on Wed Sep 20 17:52:23 2017
Basic demo for the OnACID algorithm using CNMF initialization. For a more
complete demo check the script demo_OnACID_mesoscope.py
@author: jfriedrich & epnev
"""
import os
import numpy as np
import pylab as pl
import caiman as cm
f... |
5ec45febe7020a8f733951b9da8c0950256511dced5f6e2d6c34d4a3a8de7de6 | Python | 5,438 | 133 | # -*- coding: utf-8 -*-
from __future__ import print_function, unicode_literals, absolute_import, division
from six.moves import zip
from tifffile import imread
from collections import namedtuple
from itertools import chain
from ..utils import _raise, consume, axes_check_and_normalize
from ..utils.six import Path, Fil... |
115e2a8c885c72638c631a30dcfc1481444ffb9acc8cef482e20e6260e7df2c7 | Python | 5,440 | 171 | '''
check if we can cluster the scene vectors
in particular, can we derive good clustering parameters from the training set
and generalize to the validation set
this is essential for the clustering based shortcut model to work
'''
import os
import pickle
import numpy as np
import pandas as pd
import seaborn as sns
imp... |
51307089f59e98f66988d038964982eb5bb59d9ee310b4773c581dfa6b284f54 | Python | 5,441 | 152 | import asyncio
import logging
import random
from typing import List, Optional
from packaging.version import Version
import ray.dashboard.optional_utils as dashboard_optional_utils
from ray._common.network_utils import build_address, get_localhost_ip, is_localhost
from ray._common.utils import get_or_create_event_loop... |
6bcbb68838c1804108245a10d5ad51fe2854d81a5b64c031129d298257d545d3 | Python | 5,442 | 192 | import os
import pdb
from matplotlib import pyplot as plt
import numpy as np
import yaml
from yaml.loader import SafeLoader
import torch
from latent_time_stepping.AE_models.ViT import SimpleViT, ViTEncoderLayer
from latent_time_stepping.oracle import ObjectStorageClientWrapper
from latent_time_stepping.utils import cr... |
49f2dd325eba8537209aec165e5a2a8fa247f1b87fc6c48920cfc8d80d55fe44 | Python | 5,444 | 139 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 9 10:24:09 2023
@author: hansav
"""
import os
import pickle
import pandas as pd
import numpy as np
import pcntoolkit as ptk
from pcntoolkit.dataio.fileio import load as ptkload
from pcntoolkit.dataio.fileio import save as ptksave
from pcntoolkit.... |
10a79eccc7afa8dfd95d5a0fc53c01ec96fbf15f6043a738f0b29ad1c754e384 | Python | 5,445 | 176 | import time
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from config import args
from dataloader import DataLoaderSubstructContext
from models import GNN
from torch_geometric.nn import global_mean_pool
from util import ExtractSubstructureContextPair, cycle_index
from datasets impo... |
98b09cef4df0382350b6665a1ccde6991a064d090951c5a95668222a9e887085 | Python | 5,445 | 219 | #!/usr/bin/env python
import os
import librosa #mfcc 1.st lib
from scikits.talkbox.features import mfcc # 2'nd lib
# import python_speech_features # 3rd lib
import os.path
import numpy as np
import subprocess
AUTOMATIC_ALL_VOICES=False
# list voices: `say -v ?`
# good_voices = [] #AUTOMATIC !!
good_voices = """
Agnes... |
54e6799efb02c5e2409e90334c9e694d87e39d732b1998cb2988152536ddd447 | Python | 5,446 | 115 | # 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, ... |
6dace6045ee3a4b29caf3e0928e558c40e03dbae7d1c49c0051ab50919645ab7 | Python | 5,447 | 109 | import os
import torch
import pandas as pd
from model import Model
from data_ddG_dTm import ProcessingData, train_model, validation_model, test_model, convert_batch_data
#######################################################################
# predifined parameters
#####################################################... |
24f9ead08358adfb4e2eb79a1dbbccb9c9fb765692bc50801ffbe893c85bf55d | Python | 5,448 | 112 | 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
def get_percent_triplets(percentpairs):
if percentpairs == 1:
return 0
elif percentpairs == 0.75:
return 0.25
elif perce... |
3b7c09782da5e4f368ac53e1273a35551c28db250105a8bf6993d1bdcb1c4ace | Python | 5,448 | 141 | import numpy as np
import matplotlib.pyplot as plt
import math
from matplotlib.ticker import FixedLocator,FuncFormatter
plt.rc('font',size=15)
ruptime=[]
rdowntime=[]
puptime=[]
pdowntime=[]
rupnumber=0
rdownnumber=0
pupnumber=0
pdownnumber=0
point=20
upstate=28
downstate=12
Exp=0
def Fsign(data)... |
df6d7a0615ab07b4e277f482785efc10ddacd8e7116ecb4e66b7648fbfb45d3e | Python | 5,449 | 122 | ####################################################################################################
# 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... |
fb72fe3f2dc72569b0d9e1ffe25b9517a98112392450d74618942e95274eeddd | Python | 5,449 | 209 | import gc
from typing import List
import torch
from rdkit import Chem
from utils.rerank import rerank_predictions
CUDA_OOM_ERROR = getattr(torch.cuda, 'OutOfMemoryError', None)
def check_valid(smi):
mol = Chem.MolFromSmiles(smi)
return mol is not None
def _strip_tokens(smi, begin_token, end_token, pad_t... |
50ad21f64f5b80b003fb67e2feac7b2eec5153198542acc8300e1ca6d8367195 | Python | 5,452 | 167 | '''
check if we can cluster the scene vectors
in particular, can we derive good clustering parameters from the training set
and generalize to the validation set
this is essential for the clustering based shortcut model to work
'''
import os
import pickle
import numpy as np
import pandas as pd
import seaborn as sns
imp... |
bdc0612410b2b6e9317802eb85e9a650a473c0875ba2d918d6792575d0ee0896 | Python | 5,452 | 136 | # import the main libraries required for the preprocessing
from pathlib import Path
import numpy as np
import matplotlib.pyplot as plt
import os
# import homemade function
from technical_validation_utils import subjects
# %%
# NB: run_emg.py must has been runned before running the average
emg_dir = [Path('./emg... |
8e80eaa4420c937b4e31f039a2bc52a846788c7f27d542178514a54cec821d07 | Python | 5,455 | 155 | # --- START OF FILE token_counter.py ---
import tiktoken
import logging
import json # Added to enable JSON conversion
from typing import Tuple
# Set up logging for the token counter
logger = logging.getLogger('token_counter')
logger.setLevel(logging.INFO)
handler = logging.FileHandler('logs/token_counter.log')
handle... |
acc896ee2312b4b8db42ec6c400423fd89d5f7a56d46ba3d9d8ebfecfef93208 | Python | 5,457 | 160 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
b9766c283946b10158faeb0412d24899b038a22aa0e9af94e2570d48895f4aec | Python | 5,458 | 142 | ####################################################################################################
# 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>
#
# The code in this fi... |
ff5740ca3ea1e32ca8f2f3b60d1546a3ef36624e813495e46842a0a42abd08ac | Python | 5,458 | 152 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modif... |
31a23e0a8ab5dd4a5c40858d6519b1260d06c9c8a526d0350e4be132838a76f1 | Python | 5,462 | 140 | import numpy as np
import argparse
import subprocess
import datetime
import time
import os
import pandas as pd
import glob as glob
def string(boolean):
if boolean == True:
return "true"
else:
return "false"
def loop(output_dir, params, param_names,
values = [], depth = 0, **kwargs):... |
5e78591522308baab1768974751fb1dbda54cadfaee7348e143612479ec9c0c1 | Python | 5,462 | 117 | # Copyright 2023 The HuggingFace Team. 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
#
# Unless required by applicabl... |
2bce98279d68798c18755b9ee4151928b975d2cdd1931ecd9176fd7588ebd7eb | Python | 5,464 | 166 | """Unit tests for PlatformEventsHead module.
Tests verify the core caching, deduplication, eviction, and REST API
logic inside the central PlatformEventsHead controller.
"""
import sys
from unittest.mock import MagicMock, patch
import pytest
from ray._private import ray_constants
from ray.core.generated.events_base... |
8494f90bfa7bedac8d0e015e29c21f1d031d502ccef50139acd8a78dfdd61562 | Python | 5,464 | 116 | ####################################################################################################
# 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... |
85e4a8788103df2f170ce3550550ccee27478704de1ac0df2a372540f7370542 | Python | 5,465 | 134 | # Ultralytics YOLO 🚀, GPL-3.0 license
import signal
import sys
from pathlib import Path
from time import sleep
import requests
from ultralytics.hub.utils import HUB_API_ROOT, check_dataset_disk_space, smart_request
from ultralytics.yolo.utils import LOGGER, PREFIX, __version__, checks, emojis, is_colab, threaded
AG... |
24412168e98f81cb304ddbed1d1cf5df2725f892923544d2836fc93672b40351 | Python | 5,470 | 122 | def predict_nmd(gencode, transcript):
'''
Aim: Predict nonsense-mediated decay for transcript using:
- ORF prediction from CPAT --> ORF length, start and end
- Blat analysis of Best ORF.fa from CPAT to mouse reference genome --> genomic coordinates of CDS
## Assuming if there is only one ... |
07f47d3886482fd5d6d15ed14c89930cd13399f2e22fa4ea3f3272eae29c8c07 | Python | 5,471 | 131 | r"""Vendored `PrimeDesign <https://github.com/pinellolab/PrimeDesign>`_ — the
Pinello-lab reference pegRNA/ngRNA designer (Hsu *et al.* 2021).
PrimeDesign is a pure-stdlib Python tool (no heavy deps). We clone it on first
use and drive its command-line script, converting an ``ov.synbio`` edit
(``target`` + ``edit_pos`... |
3a2c2334f56c6d4081580b0b862a0e2b5ae12efe47bb61d139f0f665d35c5077 | Python | 5,471 | 129 | from loguru import logger
import os
import sys
import json
from deltasplice.constant import CL, EL, Fapath
from bisect import bisect_left
import numpy as np
from pyfasta import Fasta
from pyliftover import LiftOver
SavePath = "data/sQTLs_neg"
def parse_line(line, i):
line = line.replace("\n", "").split("\t")
... |
43cd6ad60ef3e550f5398f41dd1e7fba03145398a0ea1d131923310c2d34b3ad | Python | 5,471 | 168 | # 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, ... |
0f4615f2028873a455402f48c5ac2249878b1707108ade8d5af2c9791dc328f8 | Python | 5,472 | 102 | import os
import argparse
import subprocess
import multiprocessing
from utils.generate_folds import generate_kfolds
from utils.tools import ROOT_PATH, absolute_path
"""
Train and test the SNN pipeline (CSNN + Readout) with K-fold cross-validation.
The input directory must contain the datasets to the format <X_{set}.... |
4e3611794a95cdfee91b6996c7d77b551d4fad467f52b503050e92759fbd5e8a | Python | 5,472 | 147 | # general imports
from openmm import LangevinIntegrator
from openmm.app import (
PME,
CharmmParameterSet,
CharmmPsfFile,
CharmmCrdFile,
PDBFile,
Simulation,
)
from endstate_correction.constant import zinc_systems, blacklist
from endstate_correction.analysis import plot_endstate_correction_result... |
7c6a6550b8f00ca04e46293b32d35bd26a701bbed173874438467cc9a887ccc2 | Python | 5,472 | 157 | import sys
import os
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
import numpy as np
import pandas as pd
from random import choices
from random import sample
from itertools import combinations
from scipy import stats
import itertools
import tensorflow as tf
from tensorflow import keras
from tensorflow.ke... |
27ee74d92e722f4f661ab0f3142a1d3ee75da57ddfb0ec9d375184d4676e8c6a | Python | 5,474 | 141 | import re
import torch
import numpy as np
import os
from batchgenerators.dataloading.data_loader import DataLoaderFromDataset
from batchgenerators.dataloading.multi_threaded_augmenter import MultiThreadedAugmenter
from batchgenerators.datasets.cifar import HighPerformanceCIFARLoader, CifarDataset
from batchgenerators.t... |
533c377a8c7d1ef4f1b9888e86ee51b20f645e7c7dbf3a456ed84b070ab0b732 | Python | 5,474 | 138 | import asyncio
import logging
import os
import time
from concurrent.futures import ThreadPoolExecutor
from typing import Union
import ray._private.ray_constants as ray_constants
import ray.dashboard.consts as dashboard_consts
import ray.dashboard.utils as dashboard_utils
from ray._private.authentication.http_token_aut... |
f7b13d6bd634f7ac44e70b721fda2af64f225cae37cd30018e5a8e5562cfa90c | Python | 5,474 | 161 | #!/usr/bin/env python3
"""Verify a soft-wrap pass changed nothing but whitespace.
For each target file, compares the current (transformed) content against a
reference -- either a git ref (the pre-transform state) or a reference
directory -- on three deterministic axes:
1. Content invariant non-whitespace bytes id... |
d44cacddd07c4044725935f09d0fd9719d34cce5ee90722d6fa8633516ac3836 | Python | 5,477 | 192 | #!/usr/bin/env python
from __future__ import print_function
import subprocess
import os
# BEDS = [
# # 'np_pb_intersect.bed',
# # 'np_pb_int_gte10.bed',
# # 'np_pb_int_gte5.bed',
# # 'np_pb_int_gte15.bed',
# 'int_gte5_2xmed.bed',
# 'pb_gte5_2xmed.bed',
# 'np_gte5_2xmed.bed',
# # 'gatk_... |
127c5aed3be5ab2fd0b0e19de53a05219acc13790c1942e459b94adcc60e4025 | Python | 5,478 | 147 | r"""Layer B — zero-shot variant-effect prediction (in-silico directed evolution).
Score amino-acid substitutions with an ESM language model, no labels required.
For a mutation ``p.A123V`` the effect is the log-likelihood ratio
.. math:: \text{score} = \log P(x_i = \text{mut}) - \log P(x_i = \text{wt})
positive ⇒ th... |
321236625ea38c7fe3fbb6b03b56dde5f5b93b3b7888a6588a8805d2ce6fa7d3 | Python | 5,479 | 160 | """Tests for the optional threemica bridge."""
import subprocess
import sys
import types
import numpy as np
import brainspace.plotting.threemica_report as threemica_report
from brainspace.plotting.threemica_report import (
available_threemica_surface_maps,
write_brainspace_threemica_report,
write_threemi... |
3ffa2f1df5ebee05e87b2e516529e08c44d9f863cb972d4cba6c5ca4d4980f1f | Python | 5,481 | 134 |
import torch.nn.functional as F
import torch
from torch import nn
class DecadeCELoss(nn.Module):
def __init__(self, sigma = 5) -> None:
super().__init__()
self.ce = nn.MultiLabelSoftMarginLoss()
self.sigma = sigma
def forward(self, input, target):
# input: B, 10
... |
5f8f15a7b6b2cf91efeda1b65b241f0e301109c068a2f575e4d88b706472fbd4 | Python | 5,481 | 169 | import logging
from typing import TYPE_CHECKING, List, Optional
from ray.data._internal.object_extensions.arrow import raise_on_pickle_object_columns
from ray.data._internal.util import _check_import
from ray.data.block import Block, BlockMetadata
from ray.data.datasource.datasource import Datasource, ReadTask
if TYP... |
caaca24156b59a2480715779fa1777c83eb9c62ffa03caa581f65ff38d576b29 | Python | 5,481 | 187 | #
# 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... |
6d8ed3746f5647502e52d7b89191595ccb0299484b4bb3b3f69e37ec1176704b | Python | 5,484 | 134 | """HTTP/TLS and IDNA compatibility; no external network, credentials or model files."""
import json
from pathlib import Path
import ssl
import subprocess
import tempfile
import threading
import unittest
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from urllib.parse import urlparse, parse_qs
impo... |
6f1f37083ba8393e320ddb9f5d0dc022df01e1400f65a9276a9806319146a324 | Python | 5,485 | 115 | #Plot abundance distribution
from glob import glob
import os
import pandas as pd
import geopandas as gpd
from src import start_cluster
client = start_cluster.start(cpus=75,mem_size="10GB")
##Same data
species_model_paths = ["/blue/ewhite/b.weinstein/DeepTreeAttention/snapshots/1ccdc11bdb9a4ae897377e3e97ce88b9.pt",
... |
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