sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
435333b3115e2ff41813e6422662fd3ce9b682b279fc49bbb7e73062fa7240d3 | Python | 1,559 | 40 | """PEP 517 build backend wrapping scikit-build-core.
The shared tree headers are symlinks into the sibling shap/cext/ dir (the
CPU and GPU extensions compile against the same headers). scikit-build-core's
sdist packaging preserves symlinks as-is, which produces a tarball that's
broken once extracted outside this monor... |
33cb77bb4dba8f03da8bef13921e5d7f734ae450abe5c39bfede34f0ac38eed9 | Python | 1,560 | 69 | import pytest
import rpy2.rinterface as ri
ri.initr()
def test_init_from_seqr():
seq = [1+2j, 5+7j, 0+1j]
v = ri.ComplexSexpVector(seq)
assert len(v) == 3
for x, y in zip(seq, v):
assert x == y
def test_init_from_seq_invalid_item():
seq = [1+2j, 'a', 0+1j]
with pytest.raises(TypeErr... |
7213da7bf2f6ae792f7c9c952dc3669dd46ef835a282c0991152bc13c68465a8 | Python | 1,560 | 61 | """add user defined object stores
Revision ID: c14a3c93d66a
Revises: 5924fbf10430
Create Date: 2023-04-01 17:25:37.553039
"""
from sqlalchemy import (
Boolean,
Column,
DateTime,
ForeignKey,
Integer,
String,
Text,
)
from galaxy.model.custom_types import (
JSONType,
UUIDType,
)
fro... |
c562a0f40a5bbafc4479c54f8fb8a691e0dba0dff8a161c0dd8d2aa14ae4e1c9 | Python | 1,560 | 70 | """
mua_thresh.py
Modules for preprocessing tools (e.g. thresholds for mua
spike detections)
"""
import numpy as np
################################################################
################################################################
def find_mua_thresh(voltage_set=None, thresh_detect_mode='donoho', u... |
c91f5c46c2636597474792ec0fc9d5b1dce5382f56660a002641d692c715f736 | Python | 1,560 | 46 | """add metadata in run table
Revision ID: edcd10edf11d
Revises: f12747ed7e9c
Create Date: 2021-09-16 11:37:16.502609
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "edcd10edf11d"
down_revision = "f12747ed7e9c"
branch_labels = None
depends_on = None
def upgra... |
7b0c5f2167d52aab03aa14feb7c35800101b73909f01bea940ea8ac266368681 | Python | 1,561 | 48 | """Storage intent resolution tests for fastlog."""
from __future__ import annotations
from pathlib import Path
import torchlens as tl
from torchlens.capture.projections import _resolve_storage_intent
from torchlens.fastlog.options import RecordingOptions
def test_streaming_none_is_ram_only_intent() -> None:
""... |
a7614ca11df3a43b85b6a883eb2578b0067e645c32c5f4497b5fcca82341ddab | Python | 1,561 | 39 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
from scilpy.io.streamlines import load_tractogram_with_reference
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_te... |
873fb3e4f8aab7d73f905eb9e4e8d0350a8d8721b05c7c61777478b3a391d4c5 | Python | 1,562 | 53 | import kerastuner
import tensorflow as tf
from codecarbon import EmissionsTracker
class RandomSearchTuner(kerastuner.tuners.RandomSearch):
def run_trial(self, trial, *args, **kwargs):
# You can add additional HyperParameters for preprocessing and custom training loops
# via overriding `run_trial`... |
06745820ca63648c16a58388575cb0324e0bff969a3c6240f9df9a29680e4c55 | Python | 1,563 | 38 | from mudcod.network_simulations import MuSDynamicDCBM
def print_shape(adj, z):
print(
f"Shape of the time series of multi-subject adjacency matrices is: {adj.shape}",
)
print("(number of subjects, time-horizon, n, n)")
print(
f"Shape of the time series of multi-subject community labels... |
a382d39a62e260cdb80f727f3226b0b79ba80f60eadd8144b9e96f631f19dc78 | Python | 1,563 | 41 | import sqlite3
from .db import DB
class DistrictHospitalBedDetailsTable(DB):
def __init__(self):
self.table_name = "TN_district_hospital_bed_details"
self.table_desc = "Tamil Nadu hospital bed district wise details, table on pages 7, 8 and 9"
self.cols = self.getcolumns()
def getcolumn... |
40580548a46d4f1cbc82aa2553727793da4b6f8064577e33c848265617839bd6 | Python | 1,564 | 47 | import argparse
import logging
import time
import google.cloud.logging
from codecarbon import EmissionsTracker
from codecarbon.output import GoogleCloudLoggerOutput, LoggerOutput
def train_model(epochs: int):
"""
This function will do nothing during (occurrence * delay) seconds.
The Code Carbon API will... |
a72bad7bfce9c1067fcf31f75ccfdf5dcffee9a29404e2aa9fce5f286dcfe6fa | Python | 1,564 | 54 | import threading
from collections.abc import Iterator
from contextlib import contextmanager
from typing import (
NamedTuple,
)
from pyftpdlib.authorizers import DummyAuthorizer
from pyftpdlib.handlers import FTPHandler
from pyftpdlib.servers import FTPServer
class FtpServerAddress(NamedTuple):
host: str
... |
018862ddb82f1ee92652f69e559fe8df63fdad3ade810bdabbe5827e77a5e601 | Python | 1,565 | 58 | import torch
import torch.nn as nn
class LSTMLongRangeFinalLayer(nn.Module):
"""
Run an LSTM over the input, and return the output.
Potentially produces extra channels, which it then clips.
Shape: (batch_size, seq_len, num_channels) -> (batch_size, seq_len, num_channels)
Parameters
--------... |
0764f995a1e73785fa3daf17669f719abfc0abc366bc36e73147877374bfc54b | Python | 1,565 | 54 | """
Import initial data used for develop e2e api tests
The most important is the main user with a known id
We can then forge an access token and use the API for testing
"""
import logging
from carbonserver.api.infra.database.database_manager import Database
from carbonserver.api.infra.database.sql_models import User ... |
daa6d8658ac5a43ad726340b9d3dd7edb2a497a60e88e1115cb17a902cb57ff3 | Python | 1,565 | 43 | import os
import numpy as np
import itertools
from analysis.test_ensembling_model import TestEnsemblingModel
class LimitEnsembling:
def __init__(self):
dico_res = dict()
for k in range(1, 6):
moyenne, var = self.get_mean_var_for_one_nb_model(k)
dico_res[k] = [moyenne, var]
... |
9345fcc29e14ee96ecf5d341b9cea43664ecf5f77c068a2c9b4f88a35441d823 | Python | 1,566 | 55 | import os
import shutil
import numpy as np
import json
import copy
from tools.hash_value.make_hash import *
"""
Meta.json is the core of each model within Snudda.
See README.md for an example.
"""
def add_feature_to_meta(directory, additional_feature_json):
"""
:param directory: the m... |
9a3ed4002ac11e4b309202ae7b3c8f4bc3e02aab8e14a2bfa41be8857c7d8a38 | Python | 1,566 | 63 | import os.path as osp
import numpy as np
def save_split(path: str,
ndata: int,
ntrain: int,
nval: int,
ntest: int,
save_split: bool,
shuffle: bool = False,
seed: int = 42,
print_nsample: bool = Fa... |
6777a631614078d7545f164aa50c9f1a37f9b14dee974fdeb80e2f0fd3c77ab3 | Python | 1,567 | 48 | import numpy as np
import torch
from torch import nn
from modular_splicing.utils.construct import construct
from modular_splicing.models.motif_models.types import motif_model_types
class RobustlyAdjustedMotifs(nn.Module):
motif_model_dict = True
def __init__(self, adjusted_model_spec, randomize_after_spars... |
c9381732537a6af9dea2a344751b6ea0274c01b20976c512b663153df9b27b79 | Python | 1,567 | 52 | import time
from abc import ABC, abstractmethod
class OMOPDatasetBackend(ABC):
@abstractmethod
def __init__(self, config, connect_args):
pass
@abstractmethod
def execute_query(self, sql):
pass
@abstractmethod
def execute_queries(self, *sqls):
pass
@abstractm... |
faa6fb5add285e16ee56dcdc17d880fe2f1187a4d338b8b6c5c6b72326667320 | Python | 1,567 | 30 | """The lightly.loss package provides loss functions for self-supervised learning."""
# Copyright (c) 2020. Lightly AG and its affiliates.
# All Rights Reserved
from lightly.loss.barlow_twins_loss import BarlowTwinsLoss
from lightly.loss.capi_loss import CAPILoss
from lightly.loss.dcl_loss import DCLLoss, DCLWLoss
from... |
3d22cf3851489a9fc04beee7fd3d9840904084e168163629873c7db9c88a6b7b | Python | 1,568 | 55 | # coding=utf-8
# Copyright 2025 The Google Research Authors.
#
# 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 applicab... |
c164b9040f4dc35fafb612b65cf471ae4ff0e7ec54fd51d41444023feb2e9623 | Python | 1,568 | 44 | import os
data_dir = '../../data'
mass_shift_annotation_url = ('https://docs.google.com/spreadsheets/d/'
'1-xh2XpSqdsa4yU-ATpDRxmpZEH6ht982jCCATFOpkyM/'
'export?format=csv&gid=566878567')
# Living data analysis performed on 2020-11-18.
living_data_base_url = ... |
11a102b7a0b79697a816a6fe93263dfdf94fd32f530e69c4d3925347bb8e1ea3 | Python | 1,569 | 41 | """
With this script you can train one of the 24 included models
load one of the pre-processed datasets that comes with MoleculeACE
"""
from MoleculeACE.models import RF, SVM, GBM, KNN, MLP, GCN, MPNN, AFP, GAT, CNN, LSTM, Transformer
from MoleculeACE.benchmark.const import Descriptors, CONFIG_PATH, datasets, WORKING... |
1220d437b9ebf33c4a57b61cbe0fbbcef474a809edef4378e319b00c3a84f9dc | Python | 1,569 | 39 | """Prepare ILSVRC 2015 VId dataset
=========================================
`ILSVRC dataset <http://image-net.org/>`is Object detection from video
There are a total of 3862 snippets for training.
The number of snippets for each synest(category)ranges from 56 to 458
There are 555 validation snippets and 937 test snip... |
982a71268191cd3bd74a6c7534a0cc956ae18459837db7655fd56a629a6804b6 | Python | 1,569 | 38 | """
This module define a converter factory
"""
import logging
from converter.converter_proba_to_pred import ConverterProbaToPred
from converter.convert_inverse_weight_to_pred import ConverterInverseWeightToPred
from converter.converter_proba_to_pred_instance_weight import (
ConverterProbaToPredInstanceWeight,
)
fro... |
cfa4520ec7d375bbeaf165840b9f6198a3965601aacb62e59cc953b5c61894a4 | Python | 1,569 | 61 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.batch_size = 2 * msp.batch_size // 3
msp.lr = float(msp.lr) * 2 / 3
msp.architecture["num_motifs"] = 4 + 2
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_s... |
40dafead5050a5ae45023807122dc5ab8d62f8250a533d0e484c203e1042c78b | Python | 1,570 | 50 | # -*- coding: utf-8 -*-
"""
Created on Mon Dec 5 23:42:59 2022
@author: lijinp
"""
import numpy as np
import pandas as pd
from scipy.spatial import distance
# load in data
InputPath = "./../../Data/Main_Figure/"
InputFiles = ["SVG", "NULL"]
for InputFile in InputFiles:
InputExp = pd.read_csv... |
935239eae5af311fca840e3441719a40e2f4412f70cdc4e58aa394708e90d7c8 | Python | 1,570 | 50 | # Copyright 2023 Blue Brain Project, EPFL.
# See the top-level LICENSE file for details.
#
# SPDX-License-Identifier: Apache-2.0
from nmodl.dsl import ast
import nmodl.dsl as nmodl
import pytest
class TestAst(object):
def test_empty_program(self):
pnode = ast.Program()
assert str(pnode) == ""
... |
d3e3d4a2d251fde407c4081d94f6eee531638c61c74c4f1616bcc4d7a5118e8a | Python | 1,570 | 45 | import pytest
from kombu.utils.encoding import ensure_bytes
from celery.exceptions import SecurityError
from celery.security.key import PrivateKey
from celery.security.utils import get_digest_algorithm
from . import CERT1, ENCKEY1, ENCKEY2, KEY1, KEY2, KEY_ECDSA, KEYPASSWORD
from .case import SecurityCase
class tes... |
6b77298a2115cb974c64d4ad2e69bdcb9c90f482b40a97ef74bbd6dcb65cecba | Python | 1,571 | 57 | from sqlalchemy import (
asc,
false,
func,
not_,
or_,
select,
true,
)
from galaxy.model import (
Library,
LibraryPermissions,
)
def get_library_ids(session, library_access_action):
stmt = select(LibraryPermissions.library_id).where(LibraryPermissions.action == library_access_a... |
2211cf0a1f56a11cafe0e149e2cd8682094c4ada896986ab7ef11d5dc611ee23 | Python | 1,572 | 56 | import json
from importlib import import_module
from uuid import UUID
from pydantic import BaseModel
SCHEMA_MODELS_PACKAGE_BASE = "galaxy.schema."
# https://stackoverflow.com/a/2020083
def fullname(o):
klass = o.__class__
module = klass.__module__
if module == "builtins":
return klass.__qualname... |
6255fe0980840a7fa9904e2a2620a443682e72715223626b92b664421b24e710 | Python | 1,572 | 44 | """The default loader used when no custom app has been initialized."""
import os
import warnings
from celery.exceptions import NotConfigured
from celery.utils.collections import DictAttribute
from celery.utils.serialization import strtobool
from .base import BaseLoader
__all__ = ('Loader', 'DEFAULT_CONFIG_MODULE')
... |
802f5efe4dbbccd2e2e94d82df375dbab50304fd8ce1100ba0aeaf2bdd713e49 | Python | 1,573 | 38 | import unittest
from CEST.src.WASSR import WASSR
import numpy as np
from test_support_function.src.CEST import generate_Z_3D
class TestWASSR(unittest.TestCase):
def test_OF_0(self):
# Test WASSR with a Lorentzian curve centered at 0 ppm
Z = generate_Z_3D(img_size=(2, 2), dyn=21, ppm=3, a=1, b=0, c... |
8087388468641b9ab791cc31a8aabcbb64af6d953bec0a2e2dfd5bd0710454ff | Python | 1,573 | 39 | from __future__ import print_function, division, absolute_import
from .fbresnet import pretrained_settings as fbresnet_settings
from .bninception import pretrained_settings as bninception_settings
from .resnext import pretrained_settings as resnext_settings
from .inceptionv4 import pretrained_settings as inceptionv4_se... |
4bbded92cfe253a3db9ea1e67a2e1f2646a36ea600f5ca6db26e1381687bdd76 | Python | 1,574 | 41 | #!/usr/bin/env python
# coding: utf-8
"""
Construct a model RDM
---------------------
This example shows how to create RDMs from arbitrary data. A common use case for this is
to construct a "model" RDM to RSA against the brain data. In this example, we will
create a RDM based on the length of the words shown during a... |
8e896153cf9c702b5d1e3c3a98fae7311424fda904678b6d4ac2a4dc095e9a8b | Python | 1,575 | 57 | #### Modified from TAURUS Lee et al., Nat Methods 2019 (https://github.com/dixonlab/Taurus-MH)
import pysam
import sys
fn=sys.argv[1]
rfh=open(sys.argv[1]+'_multi_split_aligned_temp.txt','w')
IDs=[]
align=[]
splits=['1','1-1','1-2','1-3','2-3','2-2','2-1','2']
count=0
rfh.write('temp_ID\tID\t'+'\t'.join(splits)+'\n'... |
b3d5969e52f15f773ebce3444ecbd240fd74c3eba8cbfd8389184502bac64068 | Python | 1,575 | 36 | import warnings
from typing import Union, Iterable, Tuple
from torch import Tensor
from .graph_inn import GraphINN
class ReversibleGraphNet(GraphINN):
def __init__(self, node_list, ind_in=None, ind_out=None, verbose=True,
force_tuple_output=False):
warnings.warn("ReversibleGraphNet is d... |
4fca3f83120acc4ec70cde87fad65a5a85c6ba606d378292d13d83d6218cfd31 | Python | 1,576 | 69 | import torch
from spliceai_torch import (
SpliceAI,
load_model,
save_model,
SpliceAIDataset,
evaluate_model,
)
def load_dataset(
data_dir,
organism,
window,
CL_max,
SL,
bs,
):
dtrain = SpliceAIDataset.of(
data_dir + "/" + organism + "_" + "dataset" + "... |
d9d6dabdda964c46c5649b7d1d0fd7deb066c65651d9034912ab084384a14140 | Python | 1,576 | 49 | """Stage 4b dual-projection parity tests."""
from __future__ import annotations
import torch
from torch import nn
import torchlens as tl
from torchlens.capture.projectors import RecordingProjector
class DualProjectionToy(nn.Module):
"""Small mixed-operation model for sealed-core projection parity."""
def ... |
5977612679a26621f8ed940a3fcdbaf7169ac862a2d85ed944e10e61e0d6bd3a | Python | 1,577 | 61 | #!/usr/bin/env python
#
# JSONGenerateSphinxFiltersDoc.py
#
# This scripts read in the SimpleITK JSON descriptions of filters, and
# the text output produces a reStructuredText file for Sphinx documentation.
#
# Usage: Utilities/JSON/JSONGenerateSphinxFiltersDoc.py Code/BasicFilters/json/*.json
#
import json
import sy... |
611a8ed814b3e491e1c7ccf28061abb54823fd28fc6e476c50464169a00205fd | Python | 1,577 | 46 | import unittest
from unittest.mock import patch, seal
from cellxgene_gateway.backend_cache import BackendCache
from cellxgene_gateway.cache_key import CacheKey
from cellxgene_gateway.items.file.fileitem import FileItem
from cellxgene_gateway.items.file.fileitem_source import FileItemSource
from cellxgene_gateway.items... |
732b2bd35465a41b3009637c855cec6e6abb961855aea3cf1ad337a3ecee24cb | Python | 1,577 | 41 | import numpy_ as np
from brian2 import second
def set_input_sequence(Net, sequence, params, offset=0*second):
t = np.arange(len(sequence)) * params['ISI'] + params['settling_period'] + offset
if hasattr(Net, 'input_sequence'):
sequence = np.concatenate([Net.input_sequence, sequence])
t = np.co... |
8728c69a81ce6aeaa8cc4c49e12643db871c5d6e8efdb7e0e90fb4777475b5bf | Python | 1,577 | 53 | from functools import partial
import numpy as np
from sklearn.metrics import (accuracy_score, auc, balanced_accuracy_score,
brier_score_loss, mean_squared_error,
precision_recall_curve, precision_score, r2_score,
recall_score, roc_a... |
0215afe88d055a8f357fd967dd1ec7abe378ca73009f51aa4ad82890e8a53c14 | Python | 1,578 | 63 | from matplotlib import pyplot as plt
from PIL import Image
import pandas as pd
import matplotlib
import numpy as np
from stlearn._compat import Literal
from typing import Optional, Union
from anndata import AnnData
import warnings
# from .utils import get_img_from_fig, checkType
import scanpy
def non_spatial_plot(
... |
0f397e8c15ad67e37e51b91189a29f5c06eb0a11e304265abdd98bb692dff159 | Python | 1,578 | 63 | """
Plot correlation of LCMV beamformer weights
"""
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from scipy import stats
matplotlib.rcParams["pdf.fonttype"] = 42
sns.set(
style="ticks",
font="Helvetica",
font_scale=1,
rc={
"axes.... |
8481c40d25a397704894945596a7a3dbe8ebfae3ba7d41d3623ebe11d7072a10 | Python | 1,578 | 58 | import torch
from torch import nn
from torch.nn import functional as F
class AE(nn.Module):
''' Autoencoder for dimensional reduction'''
def __init__(self, dim):
super(AE, self).__init__()
self.dim = dim
self.fc1 = nn.Linear(dim, 512)
self.fc2 = nn.Linear(512, 128)
sel... |
c545f0605b4755a47d011bd7165d696dc672730eeca3830e58bc4e497bc283a6 | Python | 1,578 | 43 | """Inverse-adapter identity proof: inserting the adapter changes nothing."""
from __future__ import annotations
import pytest
import torchlens as tl
from ._models import SmallCNN, _cnn_input
from ._oracle_adapter import op_event_from_record
def test_adapter_is_identity_on_op_events(monkeypatch: pytest.MonkeyPatch... |
e7c8109f0bf0497ec07fd8ef425a33529ca4b566ffe663636f36e28078cd84c8 | Python | 1,578 | 63 | """Compare multiple Traces with Bundle.
What this demonstrates
----------------------
Construct a ``Bundle``, access one node across members, compute per-member
metrics, and compare outs at a shared site.
How to run
----------
``python examples/intervention/07_bundle_comparison.py``
Runnable by default.
"""
from __... |
2d4ce1ecb72fcf3f0b2cef5ae473797691b2d3587c6cc55d5d7612ddc7efdf46 | Python | 1,579 | 50 | import numpy as np
from PyQt6 import QtCore, QtGui, QtWidgets
import pyqtgraph as pg
from .simple_plot_widget import SimpleViewBox
class SimpleImageView(pg.ImageView):
"""Custom class for data visualization in impose"""
def __init__(self, *args, **kwargs):
super(SimpleImageView, self).__init__(view=... |
3cf9d54f309a77b8c5b7b5d91f90f21fc41762a9462c8e82e94744c03462a7df | Python | 1,579 | 56 | import numpy as np
import matplotlib.pyplot as plt
from modular_splicing.evaluation import standard_e2e_eval
def plot_topline_results(all_accuracies, ax):
"""
Plot topline results as a bar chart with error bars.
"""
all_accuracies = {
k: [np.array(v) * 100 for v in vs] for k, vs in all_accura... |
5daf090ba43a59473167144e486f4051a1c2ff55d51d9719caf5500837f039e9 | Python | 1,579 | 63 | # pylint: disable=missing-function-docstring
from __future__ import annotations
import argparse
import sys
import sysconfig
from ._version import __version__
from .commands import get_cmake_dir, get_include, get_pkgconfig_dir
def print_includes() -> None:
dirs = [
sysconfig.get_path("include"),
... |
024a5959a74d833fe005988ebc05abaf187399dfc679d5cf85ef90b835ba3f09 | Python | 1,580 | 54 | import numpy as np
import pandas as pd
from anndata import AnnData
from natsort import natsorted
def labels(
adata: AnnData,
label_filepath: str,
index_col: int = 0,
use_label: str | None = None,
sep: str = "\t",
copy: bool = False,
) -> AnnData | None:
"""\
Add label transfer results ... |
038a6df011a4d41bcedf7465eb97f7473c6afcdc47e18007fbb0fc9f1973498a | Python | 1,580 | 37 | from os.path import abspath, join
def run(num_procs):
from spitfire.chemistry.mechanism import ChemicalMechanismSpec
from spitfire.chemistry.tabulation import build_nonadiabatic_defect_steady_slfm_library
import spitfire.chemistry.analysis as sca
import numpy as np
test_xml = abspath(join('tests'... |
2c589f87ac5dbf14cf75d231a6e1cec76a70075489357e657d5c40afeefcd344 | Python | 1,580 | 59 | import argparse
import json
import warnings
import numpy as np
import pandas as pd
from sklearn.preprocessing import LabelEncoder
def main(inputs, infile, outfile, outfile_encoding_vocabulary):
"""
Parameter
---------
input : str
File path to galaxy tool parameter
infile : str
Fi... |
92085cefaa266fce8e21513eecedf035edbd771d36a60b7495b2dda2277cf89c | Python | 1,580 | 43 | # -*- coding: utf-8 -*-
# Copyright (c) 2016-2018 Braintech Sp. z o.o. [Ltd.] <http://www.braintech.pl>
# All rights reserved.
"""
Module defines single :class 'DataRawWriteProxy'.
Author:
Mateusz Kruszyński <mateusz.kruszynski@gmail.com>
"""
import numpy
from .data_generic_write_proxy import DataGenericWritePro... |
1a185fa26f8288abadbdca47c0c67c0bda898e8a7db328b486f3339d92ee1d17 | Python | 1,581 | 63 | """Intervene on an exact site after discovery.
What this demonstrates
----------------------
Use ``find_sites`` to inspect labels, then convert a discovered label into an
exact ``tl.label(...)`` selector for a portable intervention target.
How to run
----------
``python examples/intervention/02_exact_site_after_disco... |
5025c63b478f97af196bd774c3b2b58fd7a0560746d3b54744dcce9054dc080b | Python | 1,581 | 57 | """
CREaTor
Copyright (C) 2023 Microsoft Research
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 3 of the License, or
(at your option) any later version.
This program is distributed... |
6c8dd6f524447736eebb917a745352bdd4fb47e2e65d7ce27ee4e33bdc48b1d0 | Python | 1,581 | 53 | import rpy2.rinterface as ri
ri.initr()
def test_init_from_r():
pairlist = ri.baseenv.find('pairlist')
pl = pairlist(a=ri.StrSexpVector(['1', ]),
b=ri.StrSexpVector(['3', ]))
assert pl.typeof == ri.RTYPES.LISTSXP
def test_names():
pairlist = ri.baseenv.find('pairlist')
pl = p... |
862df03306dff6b3850a0edbd6824c8d46bcddb6378efeebdb454dd78c9601a3 | Python | 1,581 | 42 | from setuptools import setup, find_packages
with open("requirements.txt", "r", encoding="utf8") as fh:
REQUIREMENTS = fh.read()
INSTALL_REQUIREMENTS = REQUIREMENTS
CLASSIFIERS = ["Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.9",
"Programming Language :: ... |
9238fefd9eb8abc79e845970f88d06dc7a346e866e115eeffa81ae38e99b7e3f | Python | 1,581 | 31 | """Python implementation of features"""
"""
Copyright (c) 2015, Blue Brain Project/EPFL
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyrigh... |
c531f59ef1e1f6681dbd09d9ac87dc9dfd96225daee29b889304b06efdc153db | Python | 1,581 | 57 | from unittest.mock import Mock, patch
import pytest
from celery import bootsteps
from celery.worker.loops import synloop
def test_synloop_perform_pending_operations_on_system_exit():
# Mock dependencies
obj = Mock()
connection = Mock()
consumer = Mock()
blueprint = Mock()
hub = Mock()
qo... |
1a3eb7b3d990084a043bfb75ad9e50fbdc0b2d650ee8934af78fa77fe7955802 | Python | 1,582 | 62 | """
Widget for editing an environment's wind field.
"""
from __future__ import annotations
import param
from .widget_base import classattr_section, parameterized_editor
__all__ = ["build_windscape_widget"]
def _ordered_names(instance: param.Parameterized, preferred: list[str]) -> list[str]:
"""Order a configu... |
c797e0472c04d9c529836ff256cff7d20fc39764e6108f588abcec7a2f47b49f | Python | 1,582 | 48 | lif_exc = '''
dV/dt = (gl_e*(E_E_rest - V) + (g_e + ext_drive * g_chr(t,i)*nS)*(E_E_e - V) + g_i*(E_E_i - V))/C_e + sigma_noise*sqrt(2/(C_e/gl_e))*xi : volt (unless refractory)
Vt : volt
Vr : volt
'''
lif_inh = '''
dV/dt = (gl_i*(E_I_rest - V) + g_e*(E_I_e - V) + g_i*(E_I_i - V))/C_i + sigma_nois... |
f95f6f24a0a55fe927e39060d26be711bfd7b637dcb40a8ef6e3ec61b7397f43 | Python | 1,582 | 54 | import os
import time
import h5py
import numpy as np
import scanpy as sc
from dca.api import dca
from memory_profiler import profile
from scbig import setup_seed
@profile
def run_dca(adata):
dca(adata, mode='latent', ae_type='zinb', threads=1)
from memory_profiler import memory_usage
mem_used = memory_u... |
9fce357e53b51866169ff889fec94e639c6aa21eb50a18d89375e30c8911e80a | Python | 1,583 | 46 | from typing import List, Optional
from uuid import UUID
from carbonserver.api.errors import NotAllowedError, NotAllowedErrorEnum, UserException
from carbonserver.api.infra.repositories.repository_emissions import (
SqlAlchemyRepository as EmissionSqlRepository,
)
from carbonserver.api.schemas import Emission, Emis... |
e971bbd723c4a49d3cd805b133d89d785c97ed52290cf881d0b37c0182802464 | Python | 1,583 | 53 | from utils import AttributeDict
class Channel(object):
def __init__(self, name, Gmax, E_r, gates=[], sp_gates=[]):
self.name = name
self.Gmax = Gmax
self.E_r = E_r
self.gates = gates
self.gate_vals = AttributeDict()
self.sp_gates = sp_gates
self.I = 0
d... |
42c4d575feada522df61056864e91c6ee020d2d4cdbc8dbefd90d4cb2234ba4e | Python | 1,585 | 32 | #### Modified from TAURUS Lee et al., Nat Methods 2019 (https://github.com/dixonlab/Taurus-MH)
import sys
ref=[sys.argv[1]]
rfh=open('summary.txt','w')
rfh.write('Sample\tSequenced_Read-pair\tMapped_Read-pair\tNonclonal_Read-pair\tIntra_less\tIntra_more\tInter\tCpG_met\tCHG_met\tCHH_met\n')
for fn in ref:
fn=f... |
6c6ca98f8cf41bc4ed021c634bd1fc55ea72f20d6a7a6ce4bc2af4e46d04b605 | Python | 1,585 | 39 | # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
0c213907ab455cdde734c5752fa0296953d003935c921699afb9bcc71140331f | Python | 1,586 | 40 | # requires: mayavi
# dataset: mne_sample
"""Create a HTML report file for a permutation test of source space data"""
import eelbrain as e
# settings
n_samples = 1000
# Load data
ds = e.datasets.get_mne_sample(tmin=-0.1, tmax=0.2, src='ico', sub="modality=='A'")
# compute distribution of max t values through permu... |
0c34f03d50556fe31d9e17ce671a8e619255c8f5af2145c1e65452219cd613d0 | Python | 1,586 | 59 | import pytest
import torch
from lightly.loss.wmse_loss import WMSELoss
if not hasattr(torch.linalg, "solve_triangular"):
# torch.linalg.solve_triangular is only available in PyTorch >=1.11.
pytest.skip("torch.linalg.solve_triangular not available", allow_module_level=True)
class TestWMSELoss:
def test_f... |
0f9025a1da96154a6d3ad7fb192eb91d8d34713e2f7985fae245c67d3e8ca865 | Python | 1,586 | 63 | from __future__ import annotations
import dataclasses
from typing import Final
@dataclasses.dataclass(frozen=True)
class _AiAssistModelOption:
model_name: str
display_name: str
AI_ASSIST_MODEL_OPTIONS: Final[tuple[_AiAssistModelOption, ...]] = (
_AiAssistModelOption(
model_name="efficientsam:10... |
c07d6fa3c66a74658d5d0813150ed2c63fe7dc7d787f95d70ec9cfabc4788c82 | Python | 1,586 | 54 | from __future__ import division
from unittest import TestCase
import libmushu
# what should I do?
# enable to run a couple of tests --
# first test = just to see if amp works
# you start the amplifier thus-ly:
amp=AmpDecorator(BPAmplifier(Amplifier))
# second test =
class TestReplayAmp(TestCase):
... |
e17e11fefd33dac9cca90cb0631ae9dcc78e24f64877e74b2432cfdb52a539fc | Python | 1,586 | 89 | # %%
import torch
import torchmetrics
def get_Accuracy(num_class):
accuracy = torchmetrics.classification.BinaryAccuracy(
threshold=0.5
)
return accuracy
def get_Precision(num_class):
precision = torchmetrics.classification.BinaryPrecision(
)
return precision
def get_Dice():
... |
2043c9cd6a646940a9af6e18bd641bd4b72f7a83ab25530cb657f2298ce8d6ec | Python | 1,587 | 43 | from io import open
from os import path
from setuptools import find_packages, setup
import versioneer
here = path.abspath(path.dirname(__file__))
# Get the long description from the README file
with open(path.join(here, "README.md"), encoding="utf-8") as f:
long_description = f.read()
# Arguments marked as "Re... |
4e09db8d109fba60687cced11088dfad5451b8c8689c331ba4b083dde1e577c4 | Python | 1,587 | 50 | import ipyleaflet as L
def get_ndvi(nir, red, epsilon=1e-8):
nir = nir.astype(float)
red = red.astype(float)
return (nir - red) / (nir + red + epsilon)
def get_evi(nir, red, blue, G=2.5, C1=6, C2=7.5, L=1, norm=1/10000, epsilon=1e-8):
"""
Calculates the EVI (Enhanced Vegetation Index) of given... |
85560c7652a17bb2991453795dbecf7579666c5ead3419eff6b17ea753bfe58d | Python | 1,587 | 55 | """Miscellaneous utilities."""
import contextlib
import os
__all__ = ["CloudpickleWrapper", "clear_mpi_env_vars"]
class CloudpickleWrapper:
"""Wrapper that uses cloudpickle to pickle and unpickle the result."""
def __init__(self, fn: callable):
"""Cloudpickle wrapper for a function."""
self.... |
8d570a25eeb559d579db9e34faf32da0c906a2363a8be2fe43fca0b2161cc8d2 | Python | 1,588 | 40 | from packaging import version
import torch
from torch import nn
class PatchNCELoss(nn.Module):
def __init__(self, opt):
super().__init__()
self.opt = opt
self.cross_entropy_loss = torch.nn.CrossEntropyLoss(reduction='none')
self.mask_dtype = torch.uint8 if version.parse(torch.__ver... |
3f5250f79047fba36004552437ef9b908c9b1d2d7a3827c92f5ff0d813051a3b | Python | 1,590 | 50 | from imodelsx import AugGAMClassifier
import numpy as np
from auggam import data
import pickle as pkl
dsets = {
'financial_phrasebank': 'ahmedrachid/FinancialBERT-Sentiment-Analysis',
'sst2': 'textattack/bert-base-uncased-SST-2',
'emotion': 'nateraw/bert-base-uncased-emotion',
'rotten_tomatoes': 'text... |
cf70df0b96a52cbffd6306cca66a9692baf4ceabb1ab8beaa18679aa6211c3ba | Python | 1,590 | 51 | import numpy as np
import pickle
from pyrates import CircuitTemplate, NodeTemplate, grid_search
# define nodes
VPO = NodeTemplate.from_yaml("model_definitions/vdp_pop")
KO = NodeTemplate.from_yaml("model_definitions/sin_pop")
# define network
net = CircuitTemplate(
name="VPO_forced", nodes={'VPO': VPO, 'KO': KO},... |
1a569223d575a1cf5ab227b8eb1347861a7a6b22eebedb8a1b169ca6a7d4139f | Python | 1,591 | 45 | from carbontracker.components.handler import Handler
from typing import List
class SimulatedGPUHandler(Handler):
def __init__(self, name: str, watts: float, utilization: float = 0.5):
super().__init__(pids=[], devices_by_pid=False)
if not isinstance(name, str) or not name.strip():
raise... |
3a21440d3edfcd006640a185480f528720bffc68dff27dce779c1867c07f7b4f | Python | 1,591 | 50 | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bowen Cheng (bcheng9@illinois.edu)
# ------------------------------------------------------------------------------
from __future__ import absolute_import
from __fut... |
c70c232a1ebb066c2e2c894b3e8da25a2982da5ee034056181f3f4907068a893 | Python | 1,591 | 55 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
type="ResidualStack",
depth=3,
)
msp.arch... |
0b5f56e9660f9784862d6e42b7cb983ac8a573c381d16f3ebce0015ccd2ba9e7 | Python | 1,592 | 51 | # coding=utf-8
# Copyright 2022 The Google Research Authors.
#
# 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 applicab... |
87cbc42a4ae886710ffbf49afe705a7b6c898e88566efa1cd9d1de04f1f52509 | Python | 1,592 | 53 | import numpy as np
from numpy import ndarray as arr
def increment_mean_var(old_mean: arr, old_var: arr, new_mean: arr, new_var: arr, n: int, other_n: int = 1):
"""Incremental update of mean and variance.
Variance based on parallel algorithm at https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance... |
d30969545feac7a2988089d87904b88b57894a2ed9586418fa80a4414ea5c29c | Python | 1,592 | 61 | """Append compatible reruns for memory-constrained evaluation.
What this demonstrates
----------------------
Capture one small batch, then append another compatible batch with
``rerun(..., append=True)``. Append requires the same graph shape and
batch-independent helpers.
How to run
----------
``python examples/inter... |
dd792d1ac76f439dba2dedd952a85f986bfc3bdddaeeef78ca071a906bbf47df | Python | 1,592 | 56 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature... |
ddc32a9ce66b23772e79f7a03c5afc3fc6df3def891bc359146b36bd454408a9 | Python | 1,592 | 61 | import torch
import matplotlib.pyplot as plt
from rdkit.Chem import AllChem, Draw
from rdkit.Chem.Draw import rdMolDraw2D
plt.ioff() # prevent figures from popping up
cpu = torch.device("cpu")
atom_names_dict = {1: "H", 6: "C", 7: "N", 8: "O", 9: "F", 16: "S"}
atom_colors_dict = {1: "green", 6: "black", 7: "blue", 8... |
f2f6305f6d39fd9cb5d116c825e22a00896ecfb01b4b59cc24c607114d1790e9 | Python | 1,592 | 45 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
import sys
import os
sys.path.insert(0,os.path.abspath('..'))
import STalign # noqa: E402 (this checkout's package,... |
19e937a4929ddc66fbe4f8a1e53c5b5d87e1bd52e1e41d9ac32b9c7b887da952 | Python | 1,595 | 52 | # coding=utf-8
# Copyright 2022 The Google Research Authors.
#
# 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 applicab... |
d3ef73bcb2a08c7e2f7666b4d01382b60d6f4c27d4c062f079ee95627f13badb | Python | 1,595 | 34 | from os import PathLike
import scanpy as sc
from anndata import AnnData
def read_10x_h5(filename: PathLike, prot_only: bool = True, *args, **kwargs) -> AnnData:
"""Read a 10x Genomics ``.h5`` file, keeping only the protein (Antibody Capture) features by default.
Args:
filename: Path to the 10x Genom... |
0c29a215b3197b770076509e61d1edfb80ca95e925865473a82f95a420e40c51 | Python | 1,596 | 56 | import numpy as np
from gym import utils
from gym.envs.mujoco import MuJocoPyEnv
from gym.spaces import Box
class InvertedPendulumEnv(MuJocoPyEnv, utils.EzPickle):
metadata = {
"render_modes": [
"human",
"rgb_array",
"depth_array",
],
"render_fps": 25,
... |
e7b3c8748422aace4dbbcbb2fb625646510cc71f0e00dfcfe80a2c5ac9b5d831 | Python | 1,596 | 42 | import pickle
from os.path import abspath, join
def run():
from spitfire.chemistry.mechanism import ChemicalMechanismSpec
from spitfire.chemistry.reactors import HomogeneousReactor
from numpy import sin as sin, pi as pi, array
from os.path import abspath, join
xml = abspath(join('tests', 'test_me... |
07237b0e80950eb359b547f459f3ccc345f66e4ca5298d304833b0c656941659 | Python | 1,597 | 63 | """Tests for Phase 7 temporal visualization helpers."""
from __future__ import annotations
import pytest
import torch
from torch import nn
import torchlens as tl
class RecurrentLinear(nn.Module):
"""Small repeated-module model for animation tests."""
def __init__(self) -> None:
"""Initialize the r... |
6de755c19c3ca0f029f4f9061e9ff941ce54ff87a411d7fb4f7e4c55d39cba2f | Python | 1,597 | 56 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature... |
b750a84064a9075fe0afbdc4bd6eea8f767d365c06091026cc3474ce73e8f35d | Python | 1,597 | 56 | """Smoke tests for fastlog Trace preview rendering."""
from __future__ import annotations
from pathlib import Path
import torch
from torch import nn
import torchlens as tl
from torchlens.fastlog.exceptions import RecordContextFieldError
from torchlens.fastlog.types import RecordContext
def _mlp() -> nn.Module:
... |
d5cf74a56b4a3bfe119a14ca7d224a52f483bdc6e33b7bd3be85c5b357faed0c | Python | 1,597 | 55 | import pandas as pd
import numpy as np
from tqdm import tqdm
from rdkit import Chem
from utils.pretreat_molecule import wash_smiles
def BC(x):
try:
count = x.shape[0]
g = x.skew()
k = x.kurt()
bc = (g ** 2 + 1 ) / (k + (3 * (count - 1) ** 2) / ((co... |
30ff0a75c705aeaecef16d588b672e9a17931a8a75764487d3df59bf4e90d924 | Python | 1,598 | 49 | # -*- coding: utf-8 -*-
# @Author: gviejo
# @Date: 2022-11-30 09:29:21
# @Last Modified by: Guillaume Viejo
# @Last Modified time: 2023-09-21 15:59:54
"""Tests of time units for `pynapple` package."""
import warnings
import numpy as np
import pandas as pd
import pytest
import pynapple as nap
# from pynapple.cor... |
d39a38ed12f6162f3e1815c9bdd3fcef84d8b4afc8658e7ed5a9329460970bc2 | Python | 1,598 | 43 | """Widget containing force-distance plot"""
from PyQt6 import QtWidgets
from .mpl_indent import MPLIndentation
class WidgetPlotFD(QtWidgets.QWidget):
def __init__(self, *args, **kwargs):
"""Display force-indentation graph with navigation"""
super(WidgetPlotFD, self).__init__(*args, **kwargs)
... |
cf9b99b2869c53cbd2c80b00ab4312c46d0546cc40d686a6e514ea2960b2ea09 | Python | 1,599 | 58 | #!/usr/bin/env python
"""Recommendation."""
import argparse
import sys
from data import PredictDataset
from rbpfeatures import RBPVectorizer
from recommend import Predictor
__author__ = "Gianluca Corrado"
__copyright__ = "Copyright 2016, Gianluca Corrado"
__license__ = "MIT"
__maintainer__ = "Gianluca Corrado"
__ema... |
2290cd289e1ba87981ae51c35886c4ef3c1dfa7e636357b017e9a22ebe6cb0f0 | Python | 1,601 | 42 | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.