sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
517d44e8f6182d94147c329f33752daa0d63afebe339454a3adc7d8a637e7605 | Python | 4,247 | 126 | """Coverage of the input validators in pyrosm.utils (#272).
These assert the error branches (bad argument types / values) that the parsing
APIs rely on, so the validators are exercised directly rather than only through
the happy path.
"""
import pytest
from shapely.geometry import Polygon, MultiLineString, LineString... |
600d22ec66e434b99a8e7d5363cf66dd4baa263be6638c7122630ba18df9612f | Python | 4,247 | 151 | import torch.nn as nn
import torch
class TemporalTransLayer(nn.Module):
def __init__(
self,
dim,
depth,
heads,
mlp_dim,
dropout_rate=0.1,
attn_dropout_rate=0.1,
):
super().__init__()
layers = []
# print("trans depth:", depth)
... |
015be59fe4df1ad7b3ab78307b3e3ea0bc4a385918286dd3fb89ec5b27a5162f | Python | 4,248 | 145 | # coding=utf-8
import os
import datasets
import requests
from promptsource import DEFAULT_PROMPTSOURCE_CACHE_HOME
from promptsource.templates import INCLUDED_USERS
def removeHyphen(example):
example_clean = {}
for key in example.keys():
if "-" in key:
new_key = key.replace("-", "_")
... |
cc7cfcdf6b9fdfedcdbe01c647df53d90ea41f109ec45cb75c214c7343748dc2 | Python | 4,248 | 122 | """"Functions to compute measures across collections of recorded neurons."""
import numpy as np
from spiketools.utils.checks import check_time_bins
from spiketools.measures.spikes import compute_spike_presence
###################################################################################################
#######... |
3ff20a2748bcb4c5ad8013a22cdfebb9f5d0c4542a1c67be8821c4a8932fcd5d | Python | 4,249 | 121 | #!/usr/bin/env python
'''
Tool for building a combined SDB or CSV sample-set from other sets
Use 'python3 data_set_tool.py -h' for help
'''
import sys
import argparse
import progressbar
from pathlib import Path
from deepspeech_training.util.audio import (
AUDIO_TYPE_PCM,
AUDIO_TYPE_OPUS,
AUDIO_TYPE_WAV,
... |
01bb5a1bee8ac70a9b7623e8fee16f402d3f26eb62f29629b7dc031843898372 | Python | 4,250 | 118 | """Move-compat gates for the _io split (C01 item 3) + disposition labels (item 4).
The split sends the IO error vocabulary to ``format_errors`` (logical L0)
and the format contract to ``format_contract`` (L1) with ``_io/__init__``
a declared re-export facade. Two invariants gate it:
- ZERO SPELLING CHANGES: every his... |
1f8f64e0ffd6b088dad3ed97428285fb05e3dd915a6188a8f578af41d77254cf | Python | 4,250 | 146 | import numpy as np
import pandas as pd
import io
from PIL import Image
import matplotlib
import matplotlib.pyplot as plt
from anndata import AnnData
from scanpy.plotting import palettes
from stlearn.plotting import palettes_st
from typing import Optional, Union, Mapping # Special
from typing import Sequence, Iterab... |
7ce11c6b06467f8ec6ed6ab50c4278b35778c15b1c62fe158a2286478fa436a4 | Python | 4,251 | 130 | # This example requires the following dependencies to be installed:
# pip install lightly
# Note: The model and training settings do not follow the reference settings
# from the paper. The settings are chosen such that the example can easily be
# run on a small dataset with a single GPU.
import copy
import pytorch_li... |
cd6b8a7627d6d7b8490fcecbbd1b58cb39a4a71ab18a07736b98ee57cf938da2 | Python | 4,252 | 132 | #!/usr/bin/env python3
'''Takes a bunch of types training files. First argument is what index the receptor starts on
(ligands are assumed to be right after). Reads in the gninatypes files specified in these types
files and writes out two monolithic receptor and ligand cache files in version 2 format.
Version 2 is o... |
dc491c66bbb993d4fa1c3a0187350e35c1d693093d302fae14690f0b02e4ce77 | Python | 4,252 | 109 | """Packaging guards for ``pyproject.toml`` optional-dependency extras (r20a).
These tests assert the metadata-level contract of the advertised extras, catching
the two defects the r20a hardening pass fixed:
* ``all`` was an empty extra (``all = []``), so ``pip install torchlens[all]``
silently installed nothing whi... |
9a1b5fdd78da5a574c3656f44172e5a32bc107e1abd0484e66f92bb572ace79d | Python | 4,253 | 100 | from functools import partial
from transformers import BertModel, DistilBertModel
from transformers import pipeline
from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoModel, AutoModelForCausalLM
import numpy as np
import pickle as pkl
import os
import os.path
from os.path import join as oj
... |
fd5d4308460acad10c597536f0874ff50fe116c68eb4fc87f5dc4754b69e29bf | Python | 4,253 | 107 | """Memory-timeline parity oracle + frozen torch-2.13 golden (W0.7, DEADLINE).
Torch's still-alive PRIVATE categorizer (``prof._memory_profile()``) is the
one oracle the rebuilt categorized timeline (observe, W3.2) can ever be
checked against; after upstream deletes it the oracle can never be built
again. This suite is... |
4f7e3529044f433fc62b756b99a0ab7b5a21cc858c03df59bcad86d74629862f | Python | 4,256 | 156 | import numpy as np
from anndata import AnnData
from matplotlib import pyplot as plt
def qc_plot(
adata: AnnData,
name: str,
library_id: str | None = None,
data_alpha: float = 0.8,
tissue_alpha: float = 1.0,
cmap: str = "Spectral_r",
spot_size: tuple = (5, 40),
show_color_bar: bool = Tr... |
8ee24b5e52d30230921b5447eb74a6d6e4cf3cc594cdbedbd9fc5c754a73e721 | Python | 4,257 | 90 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import json
import os
import re
import shutil
import sysconfig
from pathlib import Path
from ultralytics.utils import LOGGER
from ultralytics.utils.checks import ONNXRUNTIME_BUILDS, check_requirements
def onnx2xi... |
4daabf9ededbfff96a6844075dff0eea746841b9bd6e93ba18dc7217089eecc3 | Python | 4,259 | 90 | """Prepare PASCAL VOC datasets"""
import os
import shutil
import argparse
import tarfile
from gluoncv.utils import download, makedirs
_TARGET_DIR = os.path.expanduser(os.environ.get('MXNET_HOME', os.path.join('~', '.mxnet', 'datasets', 'voc')))
def parse_args():
parser = argparse.ArgumentParser(
descript... |
b24dce1af3de17c56f01faca353de5395e5df7e6680e4be199225d71cd76f535 | Python | 4,259 | 119 | # %% [markdown]
# # Customizing the pyramid
# (advanced:pyramid)=
#
#
# Multi-resolution pyramids are an integral part of ome-zarr image data
# and enable fast rendering of large images.
# The entrypoints to writing ome-zarr images in ome-zarr-py ({py:func}`ome_zarr.classes.image.OMEZarrMultiscale`, {py:func}`ome_zarr.... |
55f1bf042808818b9beb490efaa793789732df43a7015083110e149b1ccf35f1 | Python | 4,261 | 96 | # -*- coding: utf-8 -*-
"""
Created on Fri Jun 10 09:56:26 2022
@author: 8
"""
import torch
import math
import random
import numpy as np
import torch.nn as nn
import torch.nn.init as init
import matplotlib.pyplot as plt
import torch.nn.functional as F
import torch.optim as optim
class MScnn(nn.Module):
def __init... |
6ebc1d62ee16b679b77538a364db410b2147693753645ad8e043cd71c5bf4b76 | Python | 4,261 | 102 | from typing import Any
from pathlib import Path
import os
import pandas as pd
from mirp._data_import.generic_file import MaskFile
def extract_mask_labels(
mask=None,
sample_name: None | str | list[str] = None,
mask_name: None | str | list[str] = None,
mask_file_type: None | str = Non... |
70b9dde9281b512ed2b92e13b060ccdfda00667e4f53a4a87acaf0dc355644c0 | Python | 4,261 | 129 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created in March 2020
@author: Nathan de Lara <nathan.delara@polytechnique.org>
"""
from functools import partial
from multiprocessing import Pool
from typing import Union, Optional
import numpy as np
from scipy import sparse
from sknetwork.classification.base import... |
51605dc1dafc2f1c52bca9a0f3b782483ae004f6cdb935a2c41e6e29b8dd4e2c | Python | 4,262 | 129 | import copy
from functools import lru_cache
import numpy as np
import pandas as pd
from permacache import permacache
import tqdm.auto as tqdm
from modular_splicing.models_for_testing.list import binarized_models
from modular_splicing.evaluation.run_evaluation import evaluate_model_on_data
from modular_splicing.legac... |
2db3a09c21a330532cf7c822672352fbe00405aa47560719289f0ae7fdbda5ca | Python | 4,265 | 112 | import logging
import os
import tempfile
import unittest
import arviz as az
from pathlib import Path
from sklearn.model_selection import train_test_split
from pmsurv.models.gaussian_process import GaussianProcessModel
import tests.syntheticdata
logger = logging.getLogger(__name__)
@unittest.skip("Not yet ready")
cla... |
7dbd44daae594a4b2beafbd6ce4923f46049ff332b7227603b6e3cee939434ac | Python | 4,265 | 121 | from bioseq2seq.utils.logging import logger
from bioseq2seq.transforms import register_transform
from .transform import Transform, ObservableStats
class FilterTooLongStats(ObservableStats):
"""Runing statistics for FilterTooLongTransform."""
__slots__ = ["filtered"]
def __init__(self):
self.filte... |
39d830d8524a89bbab7687215f7377777c8674457ca3f3032e33a677d5ec7ba8 | Python | 4,266 | 130 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
"""
Reuires https://github.com/maenu/scholar.py::
pip install https://github.com/maenu/scholar.py/archive/master.zip
!! Run from interpreter to retain data for debugging access
run find_publications.py, then copy-paste download function
"""
from argparse ... |
7cf885d704aba4bf44e15a339cb470eedbbc83ba8c81d49c6a2fba63df97403d | Python | 4,266 | 149 | """myapp.py
Usage::
(window1)$ python myapp.py worker -l INFO
(window2)$ celery shell
>>> from myapp import example
>>> example()
You can also specify the app to use with the `celery` command,
using the `-A` / `--app` option::
$ celery -A myapp worker -l INFO
With the `-A myproj` argument the pro... |
dc1e561660d90acb138b346d32d0bc9ebdd83aac717c4bac6666df986e371f73 | Python | 4,266 | 129 | # -*- coding: utf-8 -*-
"""Segment tree for Proirtized Replay Buffer."""
import operator
from typing import Callable
class SegmentTree:
"""Create SegmentTree.
Taken from OpenAI baselines github repository:
https://github.com/openai/baselines/blob/master/baselines/common/segment_tree.py
Attributes:
... |
b2a2b82dfb80b47b950fb393b0a6ca7ef0763a47ce0fe2b7eda73d8bf17c348b | Python | 4,267 | 157 | """The ``celery logtool`` command."""
import re
from collections import Counter
from fileinput import FileInput
import click
from celery.bin.base import CeleryCommand, handle_preload_options
__all__ = ('logtool',)
RE_LOG_START = re.compile(r'^\[\d\d\d\d\-\d\d-\d\d ')
RE_TASK_RECEIVED = re.compile(r'.+?\] Received')... |
ffb79dcd9a22be16340e3cfd17ea1a88b20d13f4993441d054198ebd579892d7 | Python | 4,267 | 165 | from datetime import datetime
import numpy as np
import torch
import os
import time
from constants import get_args
from motif_model import (
MotifModel,
load_model,
save_model,
MotifModelDataset,
evaluate_model,
)
from load_psam_motif import read_motifs
from map_protein_name import get_map_prote... |
18613eef6d11cc83d288a794b3065c704146c0b59ffffb97ef357f9b6bef2ec2 | Python | 4,269 | 111 | import os
import cv2
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
mpl.rcParams["pdf.fonttype"] = 42
def get_fb_dis(image_tif, labels_tif):
data = cv2.imread(image_tif, 2)
labels = cv2.imread(labels_tif, 2)
cell_sigs = np.bincount(data[labe... |
2aaa8a2bdf398f27be44e39ef73a8a00596fde3a28633c846a6f92aa42bc2a19 | Python | 4,269 | 104 | """Module which creates mesh lines from a line set
Open3D relies upon using glLineWidth to set line width on a LineSet
However, this method is now deprecated and not fully supporeted in newer OpenGL versions
See:
Open3D Github Pull Request - https://github.com/intel-isl/Open3D/pull/738
Other Framework Issues - ... |
dc777d864d62605ca15100e6595b531c42c80eb2032e0b3a09dbbfb7da43fbf2 | Python | 4,269 | 91 | """DO NOT EDIT.
This file was autogenerated. Do not edit it by hand,
since your modifications would be overwritten.
"""
from keras.src.legacy.losses import Reduction as Reduction
from keras.src.losses import deserialize as deserialize
from keras.src.losses import get as get
from keras.src.losses import serialize as s... |
e3161c9bd988203853d83e4d0bd82bffe64f67cc4f89e837670d35be7ca01bb8 | Python | 4,269 | 155 | VALIDATION_STATIONS = [
"fowd_cdip_163p1",
"fowd_cdip_168p1",
"fowd_cdip_181p1",
"fowd_cdip_185p1",
"fowd_cdip_187p1",
"fowd_cdip_188p1",
"fowd_cdip_189p1",
"fowd_cdip_194p1",
"fowd_cdip_196p1",
"fowd_cdip_197p1",
"fowd_cdip_198p1",
"fowd_cdip_200p1",
"fowd_cdip_201p1... |
7f0856d01fc003141d4c46250b9dd09d90d1a85be21a98e2c517431cb183e2d2 | Python | 4,270 | 127 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import pandas as pd
from sklearn.model_selection import train_test_split, TimeSeriesSplit
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_percentage_error
from sklearn import preprocessing
import ... |
a3557814063402a35203fde3d9917cc4ae126215366989c9e8e81da5e546623a | Python | 4,270 | 107 | import random
import unittest
import numpy as np
from angorapy.tasks.registration import make_task
from angorapy.common.senses import Sensation
from angorapy.common.postprocessors import RewardNormalizer, merge_postprocessors, \
StateNormalizer
from angorapy.utilities.core import env_extract_dims
def test_state... |
d5f5d54fc45d7a4177a730fcefa7fbdc315c4a8351b345e6bcf085a2db1871d3 | Python | 4,270 | 119 | import numpy as np
class EdgeIndex(object):
'''
find the index of the edge from node i to node j in edges
'''
def __init__(self, edge) -> None:
self.num_nodes = edge.max() + 1
self.index = {code:idx for idx, code in enumerate(self.encode(edge[0], edge[1]))}
def enco... |
1fa1fd16a1711415a913d8c4ba07ca40804446c13594ba94c70eb2c0d403c5d7 | Python | 4,271 | 169 | """Parameters for model and training
"""
from src.utils import DotDict
epochs = 3
experiment_name = 'test_loop_1'
id_vae_cmnist = 'test_vae_cmnist'
id_vae_oscn = 'test_vae_oscn'
id_mmvae_cmnist_oscn = 'test_mmvae_cmnist_oscn'
id_classifier_cmnist = 'test_classifier_cmnist'
id_classifier_oscn = 'test_classifier_oscn'
... |
c27144029158edcb85bd8b74b31d9ebdf424fb4c791ff42c00851c651d076a6d | Python | 4,271 | 126 | from typing import List, Tuple
import torch
from pytorch_lightning import LightningModule
from timm.models.vision_transformer import vit_small_patch16_224
from torch import Tensor
from torch.optim import AdamW
from lightly.loss import LeJEPALoss
from lightly.models.modules import LeJEPAProjectionHead
from lightly.tra... |
e47c187b7e7712059a2efbd3ededd4513d7f81f8ba88769969640315a26cba4c | Python | 4,271 | 117 | import torch
import torch.nn as nn
import numpy as np
from utils import fftshift_tensor,tensor_unsqueeze,ifftshift_tensor,get_mask_from_data
import torch.fft as tfft
def d_k_torch_batch(fov,mat_size,TAng, thre=0.2, device='cpu'):
''' get dipole kernel from fov,mat_size,TAng '''
batch_size = mat_size.... |
cd6dcb6112a6457e8c6a22d4afd0fbf6146a0d5b9ea07cfc2bf3842c96004d17 | Python | 4,272 | 129 | # This example requires the following dependencies to be installed:
# pip install lightly
# Note: The model and training settings do not follow the reference settings
# from the paper. The settings are chosen such that the example can easily be
# run on a small dataset with a single GPU.
import copy
import pytorch_li... |
402116f86dae7cd73528591581996c2784fcf9278e0b07643e653d2cff641d73 | Python | 4,274 | 125 | from functools import partial
import numpy as np
import pytest
from gym.spaces import Discrete, Tuple
from gym.vector.async_vector_env import AsyncVectorEnv
from gym.vector.sync_vector_env import SyncVectorEnv
from gym.vector.vector_env import VectorEnv
from tests.testing_env import GenericTestEnv
from tests.vector.u... |
25d39bdff884e6531f18d912c64cd0cff0052cc3f6fed679c2d20a5b91dd066a | Python | 4,275 | 106 | from typing import Optional, Union
import numpy as np
import pandas as pd
from anndata import AnnData
from numpy import ndarray
from scipy.sparse import issparse
from ...logging import logger_manager as lm
from .interpolation_deeplearn import DataSampler, DeepInterpolation, interpolation_nn
def deep_intepretation(
... |
00514d0d6e7d82972ff45160616d8fd21612e1a1d8151a3835e36b54668aeae1 | Python | 4,276 | 83 | import numpy as np
import tensorflow as tf
import os, argparse
import cv2
from data import (
process_image_file,
process_image_file_medusa,
)
# To remove TF Warnings
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
parser = argparse.ArgumentParser(descri... |
6eb09a98b14c2b10cb08ee2e68f36ca8523bb4198f3d2db61e2d64cfa78850c1 | Python | 4,276 | 111 | import numpy as np
import tensorflow as tf
from tensorflow.keras.layers import Embedding, Add, Dropout, Multiply, Conv2D, BatchNormalization, AveragePooling2D, \
Concatenate, Flatten, Dense, InputLayer, GRU, Bidirectional, GlobalMaxPool2D
class DeepSmilesConfig():
def __init__(self... |
b1f767573082fa6c9338a26814cfc0f4f6688daf39601483169d5ccff1323cbc | Python | 4,276 | 136 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Connector(_BaseTraceHierarchyType):
_parent_path_str = "funnel"
_path_str... |
1fb17a20daa4708c6df6914950b419dd97b262e5a6f6047fad7676e5ba3976b9 | Python | 4,277 | 117 | import argparse
import os
import sys
import json
from tqdm import tqdm
from bulletin_download import main as bulletin_downloader
from db.main import DBMain
from local_extractor import main as extractor_main
from local_extractor.utils import custom_exceptions
STATES = [
'DL', 'GA', 'HR',
'KA', 'KL', 'MH',
... |
d9310e8e8d0275d4d7986c87c224b788efdb1f80dadabea1a49f50179c4af0ea | Python | 4,277 | 121 | """The canonical weightsfree parity matrix (weightsfree memo sec 8.1 item 1).
Per parity fixture, the gate assertion uses ONLY shipped authorities:
``real digest == meta digest AND discharge_against(real).verdict is
CORROBORATED``. This is the metric that survived all four panel rounds
unchanged and caught every one o... |
a8dd94c982a9cf8b0f8643df2ce5b6f970bacce5b224a68313ef3d4da63dfbcf | Python | 4,279 | 75 | import time
import torch
from options.train_options import TrainOptions
from data import create_dataset
from models import create_model
from util.visualizer import Visualizer
if __name__ == '__main__':
opt = TrainOptions().parse() # get training options
dataset = create_dataset(opt) # create a dataset give... |
d79885e52a871fd7144b073c90250f0228a04b4d25b6fcc2777723b6d292686e | Python | 4,279 | 131 | """Tests for the xcp_d.utils.atlas module."""
import json
from pathlib import Path
import pytest
from xcp_d.utils import atlas
_XCPD_ATLASES = str(Path.home() / '.cache' / 'xcp_d' / 'XCPDAtlases')
def test_get_atlas_names():
"""Test xcp_d.utils.atlas.select_atlases."""
selected_atlases = atlas.select_atla... |
f79092a2274b4f7426f0def63bff5b83e1e566e1dd14c1c0b3dfc48d2c6b9b0a | Python | 4,279 | 79 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
3c7dbeb02e3242c9f1c763c232afa8cfa8b0a6086558c8cf2739bd256f5b41f7 | Python | 4,281 | 112 | #!/usr/bin/env python
"""Export Parquet as plain tabular or quoted TSV, without retaining its schema."""
import argparse
import base64
import csv
import json
import math
import sys
from collections.abc import Sequence
from datetime import (
date,
datetime,
time,
timedelta,
)
from decimal import Decimal... |
65686cd62a96c41639901305c21dca82d26f68d6f51a0402d53e993723b83d74 | Python | 4,281 | 132 | """Numbers-truth surface fixes: front door (A8), escape bytes (A11), memory footer (A7).
Lane A07 (2026-08-27). Spec: the summary design memo build items 1-3.
"""
from __future__ import annotations
import subprocess
import sys
import warnings
from collections.abc import Generator
import pytest
import torch
from tor... |
a7dd43adc152e1dd26cca498fcce50efb8928ba96dd61d52f113d4a56ec353bf | Python | 4,281 | 128 | import os
import pickle
from concurrent.futures import ThreadPoolExecutor
import numpy as np
from scipy.sparse._csr import csr_matrix
from tqdm import tqdm
def load_mimic_data_and_vocab(path: str):
with open(os.path.join(path, "mimiciv-2.2.pkl"), "rb") as f:
data = pickle.load(f)
vocab_path = os.pat... |
68471d8d50cae0d2f1bf6eabca28499c0a12d9122ef6a295a327ee6b1696982a | Python | 4,283 | 119 | #!/usr/bin/env python
# encoding: utf-8
from __future__ import (absolute_import, division,
print_function, unicode_literals)
import os, sys, re
import logging
import argparse
import collections
import numpy
import time
import hashlib
logger = logging.getLogger(__name__)
class Trinity_fasta_... |
d67e257649a73d483edb69dc0af9090ecb1dc4d1a6bcc5781e43815a50519c68 | Python | 4,283 | 114 | import torch
import torch.nn as nn
class SplicePointIdentifier(nn.Module):
"""
Represnts the core LSSI model. This is a convolutional neural network that takes in a sequence of RNA
and outputs a prediction of the splicing probability at each position in the sequence.
It only represents one of 3' or 5... |
f5b3dba0065b823c1db8f41d3e8bb591566cfadff5b3c8e711affa22c86a00ec | Python | 4,283 | 87 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
d952d22b8831fcee1234dc8ff520c3033028be076a1aaf7553a215b9d04b3654 | Python | 4,284 | 146 | # -*- coding: utf-8 -*-
"""
This code will search for the parents of a single cell, get the DI for all individual, pair, and triplet of parents.
It does so separately for different time intervals and types of restrictions on parent sets.
No need to parallelize -- statsmodel will do so while fitting, and getting m... |
00148af6dad00ee3315fa2d8087b764891194f7a981e639e05ae795430c8c00d | Python | 4,286 | 127 | import numpy as np
import torch
from torch import nn
from fit.basefit import BaseFit3DPlus
from models.densenet import DenseNet121
from models.efficientnet import EfficientNetBN
from models.module import SEModule
from models.resnet import resnet50, resnext50, wideresnet50
def get_optimizer(model, lr, weight_decay, o... |
720260e0041e8ec502f189347696cd12c0fa6fafb443a2146e9e037118d9ff8a | Python | 4,286 | 98 | ## Read write encoder
# This version works with "wheel_tracker\only_rotary_teensy_prtc/only_rotary_teensy_prtc.ino"
# on Teensy 3.5
# In addition to saving position / interrupt data, it also saves timestamps whenever a sync pulse is detected
# It writes two files
# - Position data csv
# - _sync Sync data csv
import ... |
c1d1c28325bc9e65f49350c6961ce4c5cb82e2d821a9098eb606e2bde880c38e | Python | 4,286 | 128 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 28 13:59:56 2017
@author: papoutsi
"""
import numpy as np
#from scipy.stats import norm
from scipy.optimize import curve_fit
def spike_count(data):
if data[0]>0:
data[0]=-1
# Find values above zero
id_zero=np.nonzero(da... |
c37c2d23365338e9f75fe73c61fc4b75b9590e9f72574f75f0ac201b72257a4d | Python | 4,286 | 111 | """siamRPN RPN
Code adapted from https://github.com/STVIR/pysot"""
# pylint: disable=arguments-differ
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from mxnet.gluon.block import HybridBlock
from mxnet.gluon import nn
... |
c669446d9b047bf1cd43df2abc7de86cadc9aed9c9f383ff59403314ec66a662 | Python | 4,287 | 132 | #!/usr/bin/env python
# test_triggerdelay.py
# Copyright (C) 2013 Bastian Venthur
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any l... |
d823857e5df61c0efe421a321e79a9582c16f798f3a60ea1f03fa842539a984b | Python | 4,288 | 130 | """A compatibility wrapper converting an old-style environment into a valid environment."""
import sys
from typing import Any, Dict, Optional, Tuple
import gym
from gym.core import ObsType
from gym.utils.step_api_compatibility import convert_to_terminated_truncated_step_api
if sys.version_info >= (3, 8):
from typ... |
df81400be5c5ef95082eb98b3298eda4cc69b64f16df098bad056a520005750f | Python | 4,288 | 126 | #!/usr/bin/env python
# coding: utf-8
# In[4]:
import pandas as pd
from sklearn.model_selection import train_test_split, TimeSeriesSplit
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_percentage_error
from sklearn import preprocessing
import... |
3c8ccce75a4dbdb5e6764244e72b7f1bdd9c617f829202fdbdc8dca2da25fa79 | Python | 4,291 | 109 | """Persistence honesty: structure-only saves never write a poison artifact.
WT1 A-IV item 22 + M(weightsfree) W3 (lane A08):
* Item 22 -- ``level="executable_with_callables"`` on a structure-only trace
used to WRITE an artifact whose load ALWAYS refused (forced saved-args
payloads under the marker fail the M-C2 c... |
8b1f678a5018d840f3dc78ef2264c5fd0f03a48dbcce6df25913bf59bf264b16 | Python | 4,291 | 80 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
869c9e1943774708d6bf055a694e3b3f0c15d8cab928eec8a10d3768abecf399 | Python | 4,292 | 137 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
import ConfigParser
import os
import shutil
import subprocess
import sys
import tempfile
def manage_loc_file(path, data):
"""
updates or inserts config lines like the following one:
chembl_2011 ChemBL 2011 (~1.0M compounds) schema database_name user l... |
298d8e69729a1d86b7a3a8bd1afd24ad099a76bebbeb07c6de69bd5fb3c5e9c3 | Python | 4,293 | 90 | # pylint: disable=wildcard-import, unused-wildcard-import
"""
GluonCV-PyTorch model zoo
"""
from .action_recognition import *
from .video_language.coot_model import MultiModalTransformer
from .pose.directpose_resnet_fpn import *
__all__ = ['get_model', 'get_model_list']
_models = {
'resnet18_v1b_kinetics400': r... |
7cc2af907b073740358197501bc01868e929e8070ac2040b9506c2db6d2f410a | Python | 4,293 | 123 | import tvm
from tvm import relay
from tvm.contrib import graph_executor
from PIL import Image
import numpy as np
import torch
import torchvision.transforms as T
import torchvision
from torchvision import transforms
from gluoncv.torch.engine.config import get_cfg_defaults
from gluoncv.torch import model_zoo
def _test_... |
cc39f4c4fa7e3f198202b30a354754ce27f6adec316f56173a48bc5e3f556419 | Python | 4,294 | 131 | import numpy as np
from numpy.random import default_rng
import pathlib
from mpi4py import MPI
from causal_optoconnectics.tools import conditional_probability, joint_probability, roll_pad
from causal_optoconnectics.generator import (
construct_connectivity_filters,
construct_connectivity_matrix,
simulate,
... |
d7975c6e850912773154edada564ede331f7a3f934a9ab002e9d78f1866dfd8c | Python | 4,294 | 103 | """``torch.overrides`` drift oracle (torchnative 8b / W2.8).
TorchLens is BUILT on the ``__torch_function__`` protocol, so torch's own
overridable-function registry is a free drift oracle: a torch upgrade
cannot silently add protocol-visible functions TorchLens does not see. The
frozen baseline (``tests/data/torchnati... |
f20f5f09a38c4f7bfee5915e7e31e0de12e78719dff7f64d36657c22f5953e66 | Python | 4,294 | 134 | #!/usr/bin/env python
# Created on: November 26, 2013
__author__ = "Sven Kreiss, Kyle Cranmer"
__version__ = "0.1"
__description__ = """
First stage of Decouple.
"""
import optparse
parser = optparse.OptionParser(version=__version__, description=__description__)
parser.add_option("-i", "--input", dest="input", defa... |
f834ccb692673af759e88da85af8d81323b73c404bcf4d5a15370c891b3cddf6 | Python | 4,294 | 157 | from matplotlib import pyplot as plt
import numpy as np
from typing import Optional, Union
from anndata import AnnData
def QC_plot(
adata: AnnData,
library_id: str = None,
name: str = None,
data_alpha: float = 0.8,
tissue_alpha: float = 1.0,
cmap: str = "Spectral_r",
spot_size: tuple = (5,... |
678197ad9a4f95c1e2a6bcbbb6e1ef0a724ddaa55f73dd579f70d67b6ae01793 | Python | 4,295 | 119 | from galaxy.exceptions import (
AuthenticationRequired,
MessageException,
)
from galaxy.files.models import (
AnyRemoteEntry,
FilesSourceRuntimeContext,
)
from galaxy.files.sources._defaults import DEFAULT_SCHEME
from galaxy.files.sources._fsspec import (
CacheOptionsDictType,
FsspecBaseFileSour... |
55197f5ce35cc27692fe96734ff34ec78e7e8ef8e96b31c20e86e0a5a4888f95 | Python | 4,298 | 141 | """
Segment text using DocLayout Yolo model
"""
import argparse
import json
import os
import cv2
from doclayout_yolo import YOLOv10
def _as_numpy(value):
if value is None:
return None
if hasattr(value, "cpu"):
value = value.cpu()
if hasattr(value, "numpy"):
value = value.numpy()
... |
92dfdf3c0a5403b400990e1bc74f257b3c9a7fb07f87df6d288a7d42a6329c0d | Python | 4,299 | 140 | from permacache import permacache, stable_hash, drop_if_equal
import tqdm.auto as tqdm
import numpy as np
from modular_splicing.evaluation.predict_motifs import predict_motifs
from modular_splicing.utils.run_batched import run_batched
def is_kaway(arr, k):
"""
Takes a boolean array (batch, sequence) and ret... |
cca5a6a3d70649d6967425cf909cf6243dae8e3927a06a3b7cf1efa06386c62c | Python | 4,299 | 135 | """A06 capture-options truth: ``save_grads`` predicates are honored.
WALKTHROUGH list-A row 10 (first clause): the trace path silently DISCARDED
selector/callable ``save_grads`` predicates -- ``callable -> "all"`` -- so a
narrowing predicate saved EVERY gradient (memory blowups on real models).
Predicates now ride the... |
dcfbf3964e5a86219f9a130f89413b573cf2839788429c68de3bf284e967655b | Python | 4,299 | 133 | __author__ = 'quentin'
class BaseIntVariable(int):
"""
Template class for defining arbitrary variable types.
Each class derived from this one should at least define the three following attributes:
* `sql_data_type`, The MySQL data type. This allows to use minimal space to save data points.
* `hea... |
2a2aa08ddfadb86c712a5f0101e7644840021bb24421803eb6da1d1df78f52f4 | Python | 4,300 | 79 | import argparse
class AcquisitionParameters:
# spot: str
# xOffset: int
# yOffset: int
# path: str
# name: str
# geometry: str
# laserOffsetX: int
# laserOffsetY: int
# acqtype: str
# ceTable: str
def __init__(self, args):
parser = argparse.Argument... |
bcbabb2e7f453d957786a4388470a54cb1dfe166f3d8b55c7fcab811da204003 | Python | 4,300 | 152 | import os
import numpy as np
import torch
from modular_splicing.utils.io import load_model, model_steps
from modular_splicing.utils.entropy_calculations import hbern
from permacache import permacache
@permacache(
"spliceai/statistics/model_sparsity_2",
key_function=dict(path=os.path.realpath, step=int),
)
... |
ea379d1ac0ab50e698c8b61b017d5e365409d2cce2189d36805ca5ffc6a56731 | Python | 4,301 | 87 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
946520d496a261408466cc4b0c6fa4f9222ea0309a2bbd2d02b39cc8d95ae09c | Python | 4,302 | 115 | # utils
from torch_geometric.data.data import Data
from sklearn.model_selection import KFold
from GNNSubNet import GNNSubNet
from GNNSubNet import GNNSubNet as gnn
import ensemble_gnn as egnn
import copy
import numpy as np
import random
def split(gnnsubnet: GNNSubNet, split: float = 0.8, random_seed: int = 42) -> tup... |
a275db8294616a94d7711b535ba8cd544da1684a7c7dd51f8eaeec2307899c86 | Python | 4,302 | 93 | # segment cells and save csv file of cells in organoids per well
#imports
from pathlib import Path
import zarr
import pandas as pd
from stardist.models import StarDist3D
from csbdeep.utils import normalize
from skimage import measure
import configparser
import argparse
import numpy as np
#function definitions
def loa... |
cac9074128f1048f1f33fefdb4f531fed029fdd1469bd2479e8314c13a229f60 | Python | 4,303 | 135 | """
Many models in Galaxy are not meant to be removed from the database but only
marked as deleted. These models have the boolean attribute 'deleted'.
Other models are deletable and also may be purged. Most often these are
models have some backing/supporting resources that can be removed as well
(e.g. Datasets have da... |
de7b83ffb7ce809e99e84f8a4fc10ae5215e99e0930de9dba5b61a7089d7ea00 | Python | 4,304 | 123 | # some of the code is from https://github.com/JinmiaoChenLab/SEDR
import os
import scanpy as sc
import pandas as pd
from pathlib import Path
from scanpy.readwrite import read_visium
from scanpy._utils import check_presence_download
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
def plot_clus... |
00eea84c08301bce3a5555d32afddb6bad04f0d2de2923f2744ab0376742b74f | Python | 4,305 | 142 | import os
import sys
import pandas as pd
import anndata as ad
from pyprojroot import here
proj_root = str(here())
sys.path.insert(0, os.path.join(proj_root, "package/python"))
from myanndata import grouped_obs_mean, get_barcode2group
from utils import set_file_logger
# * configs
resource_dir = f"{proj_root}/19.snap... |
1a55df502a9e1a0c25f6d0ff58f620c6b1c65db93264c7414ccae4df309cba02 | Python | 4,305 | 105 | """Shared-root corruption plant for the capture-oracle characterizer.
b9-sol R75-1: ``_characterize._snapshot_events`` derives ground-truth events
from the captured journal THROUGH the shared inverse oracle adapter
(``producer_parity._oracle_adapter.op_event_from_record``) — the same root the
production ingest migrati... |
949a6f440e0541f9337a19e47a896be6f28ae3d5abe3fe0ae14b24358f34773c | Python | 4,305 | 91 | import pylustrator
pylustrator.start()
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from copy import deepcopy
datasets = ["mnist", "fashion_mnist", "cifar10", "letter_mnist"]
experiment = "no_bias_gaussian_weights_128"
decays = [15, 30, 45, 60, 75, 90, 180, 285, 390, 480, 600] # ... |
0afbbeeb0548246571664d2cdc849858ab6d007ed994fdc24e479523eb595640 | Python | 4,307 | 152 | """Convert poly2d to mask/bitmask."""
import argparse
import os
from functools import partial
from multiprocessing import Pool
from typing import List
import numpy as np
from PIL import Image
from scalabel.common.parallel import NPROC
from tqdm import tqdm
from bdd100k.common.utils import group_and_sort_files, list_... |
5ecf60c6ef137cd43dacb89783b9446cfca64c03d249e4cbcdd0da6c91a647f8 | Python | 4,307 | 103 | import os
import glob
from PIL import Image
help_msg = """
The dataset can be downloaded from https://cityscapes-dataset.com.
Please download the datasets [gtFine_trainvaltest.zip] and [leftImg8bit_trainvaltest.zip] and unzip them.
gtFine contains the semantics segmentations. Use --gtFine_dir to specify the path to th... |
a364720d1d43f80a72a66daf910cf733bbb7875d3f7aa7595ff2a7e175bc3fb9 | Python | 4,307 | 117 | '''
@saulzhang
The implementation code of LoG filter algorithm by convolution filter approximately
data: Nov,16,2019
'''
import torch
import torch.nn.functional as F
import numpy as np
import torch.nn as nn
from torch.autograd import Variable
from math import exp
from PIL import Image
from torchvision.utils import sav... |
a9390b4889249b21cca94574b24993e20ecc8889bee477f6880e61ec9644f1c8 | Python | 4,307 | 122 | import sys
import argparse
import modeling
import data_prep
import os
import numpy as np
import scipy
import matplotlib.pyplot as plt
import pandas as pd
from tensorflow import keras
from sklearn.model_selection import train_test_split
parser = argparse.ArgumentParser()
parser.add_argument("library", help="name of lib... |
00224302665bc03ad902f3be2ec1e745a79ffbc297edeb0cd4bc55520957b4bc | Python | 4,308 | 133 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created in July 2020
@author: Pierre Pebereau <pierre.pebereau@telecom-paris.fr>
@author: Alexis Barreaux <alexis.barreaux@telecom-paris.fr>
"""
from typing import Union
import numpy as np
from scipy import sparse
from sknetwork.topology.weisfeiler_lehman_core import... |
049983295c92d860cd3fe8f61d2f6fc26f079f000780c4391d8d59792bf85546 | Python | 4,308 | 113 | import os
import logging
import tempfile
import unittest
import arviz as az
from pathlib import Path
from pmsurv.models.exponential_model import ExponentialModel
import tests.syntheticdata
logger = logging.getLogger(__name__)
class TestExponentialModel(unittest.TestCase):
def test_setup(self):
logger.in... |
68111a1cafe0f782ef96a849077b98b8e6042dafd40ff29d87d3f9df365452c0 | Python | 4,308 | 96 | import pandas as pd
import numpy as np
from nilearn import image
from nilearn.masking import apply_mask
# Set input and output paths
data_dir = './Pilot_N3'
ROIs_dir = f'{data_dir}/ROIs'
fmri_prep = f'{data_dir}/derivatives/fmri_prep'
fstlvl_dir = f'{data_dir}/derivatives/fmri_prep/firstlvl_out/contrast_files'
df_out... |
a7b3a97414c2695d7686ca8ace97c31b2ccc113c1cb83905330652197d7a2224 | Python | 4,308 | 173 | import numpy as np
import pandas as pd
import pytest
import pynapple as nap
from pynapple.core.base_class import _Base
from pynapple.core.time_index import TsIndex
from pynapple.core.time_series import _BaseTsd
class MyClass(_BaseTsd):
def __getitem__(self, key):
return key
def __setitem__(self, ke... |
ec1d003f654ad41d75098adb93045273a6a80bd33a3e8e9f22652855f9ce9681 | Python | 4,308 | 124 | """Worker Task Consumer Bootstep."""
from __future__ import annotations
from kombu.common import QoS, ignore_errors
from celery import bootsteps
from celery.utils.log import get_logger
from celery.utils.quorum_queues import detect_quorum_queues
from .mingle import Mingle
__all__ = ('Tasks',)
logger = get_logger(... |
ae717a01c20b66bc391ee0c3878409fe7c7d4f8abbd4d4526cbe80bea43cdecc | Python | 4,309 | 117 | import torch
import torchvision
import logging
import os
import pandas as pd
from pathlib import Path
import numpy as np
logging.getLogger(__name__)
def validate(
model,
loss_func,
validate_loader,
device,
epoch): # loader adapted from deep learning in pytorch book
for name, loader in [("Vali... |
aa5f99b25158d62956481dc04e40c3723b9719bae4df342bd0c9cd3affd13a79 | Python | 4,310 | 112 | #!/usr/bin/env python3
"""
File: prepare_bryois_genotype_dump.py
Created: 2022/01/26
Last Changed: 2022/02/10
Author: M.Vochteloo
Copyright (C) 2020 University Medical Center Groningen.
A copy of the BSD 3-Clause "New" or "Revised" License can be found in the
LICENSE file in the root directory of ... |
3c6873fd258aedebc1e592b8088027a58a8d22f54d0af8d0fabf5a4f9ae91ebe | Python | 4,311 | 129 |
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Test objects and function of the ``tfep`` library.
"""
# =============================================================================... |
41fe6245d2fd76a1126c1101e57da1a284930acd5a338675d32ab9a06459c0c8 | Python | 4,311 | 119 | import numpy as np
from mne.time_frequency import psd_array_multitaper
from meegkit.dss import dss_line
import matplotlib.pylab as plt
import numpy as np
import copy
def nan_basic_interp(array):
nans, ix = np.isnan(array), lambda x: x.nonzero()[0]
array[nans] = np.interp(ix(nans), ix(~nans), array[~nans])
... |
460a7755ed707c3ff1f786ec3f6c32d6fa6ceb71cc0a13feffe5d56e2e07a8a6 | Python | 4,311 | 146 | """
Methods for managing shapely-based metrics
"""
from __future__ import annotations
from typing import Any
from shapely import geometry
__all__: list[str] = [
"segments_intersection",
"detect_nearest_obstacle",
]
def segments_intersection(
segment_1: tuple[geometry.Point, geometry.Point],
segmen... |
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