sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
38a59ea5ca76a7402319f114c48fdb3ce6e2ce3f933dfc387bebbcee05d01aed | Python | 5,405 | 185 | import argparse
import json
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import os
from pathlib import Path
import random
import sys
import tensorflow as tf
from tensorflow.keras.models import load_model
import transistor_extract as... |
e6d240a7f137033c16185cf2396015e572d5a71ff2780cb6e0518b76fd7538a4 | Python | 5,405 | 141 | #
# Copyright 2017-2023 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with
# Sandia Corporation, the U.S. Government retains certain rights in this software.
#
# See LICENSE for full license details
#
from .idevice import IDevice
from .generic_device import (
UniformIndependentDevice,
... |
6f45abb0281e1c37748be26d63a1d4dae1f7ec0329cf19f7bf09ac7924d2b55f | Python | 5,406 | 132 | from __future__ import annotations
import torch
import torch.nn.functional as F
from torch.distributions import Distribution, constraints
from torch.distributions.utils import broadcast_all
from scvi.distributions._negative_binomial import _gamma, _lgamma_fn
from scvi.distributions._utils import _needs_cpu_detour
c... |
915e8fa846edb0529aa0668e22b6be38535b5fc11df6dddc60a4228013371cc6 | Python | 5,406 | 134 | import datetime
import logging
from copy import deepcopy
from functools import partial
from os import makedirs
from os.path import join, exists
from posixpath import abspath
import numpy as np
import pandas as pd
import yaml
from sklearn.model_selection import LeaveOneOut
from data.data_access import Data
from model.... |
70813e3011a3652e527aafb531d20a227678ecebab785a59b72e44951d957282 | Python | 5,407 | 126 | import os
import pandas as pd
import numpy as np
from BLRun.runner import Runner
class SCODERunner(Runner):
"""Concrete runner for the SCODE GRN inference algorithm."""
def generateInputs(self):
'''
Function to generate desired inputs for SCODE.
If the folder/files under self.input_d... |
f632715fac78d0c236cb68cdf047ffc5069d14b9da63b8a158c7e901dca895d3 | Python | 5,407 | 152 | #!/usr/bin/env python
#
# Kui Xu, xukui.cs@gmail.com
# 2019-02-25
# ref smoothGrad
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import grad,Variable
import numpy as np
class SmoothGrad(object):
def __init__(self, model, device='cpu', only_seq=False, train=False,
... |
d340e7eb5a129926782ad62a5a9aee580eb526e47cb75dfca06295444adf6f17 | Python | 5,411 | 152 | """Console logging for the entry points.
The library installs nothing on import: deciding where anyone else's records go
is the same first-writer-wins hazard `runtime.configure` exists for.
`configure` puts one handler on the `d3text` logger, and on `brenda_references`
(the dependency `d3text.datasets` imports for the... |
9d93f44d3b6bceeb44c6093ac36ca17e7ff296a179ddc124357f2e72b34bba4e | Python | 5,412 | 154 | """A dataclass that represents metadata
associated with a dimensionality reduction dataset,
as generated by
:func:`vak.core.prep.frame_classification.prep_dimensionality_reduction_dataset`"""
from __future__ import annotations
import json
import pathlib
from typing import ClassVar
import attr
def is_valid_dataset_... |
8aec12562d29ce9324ea45f539137e7e4c05d408484c1d0c7e752939272864ad | Python | 5,413 | 159 | import logging
import pickle
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Tuple, Union
import numpy as np
import torch
from spacestream.core.constants import (IT_SIZE, RETINA_SIZE, V1_SIZE, V2_SIZE,
V4_SIZE)
from spacestream.util... |
a4db99b13b20cd817a5b1af163ddb4b32d073f57dbd6ea3db561f12da1e34b22 | Python | 5,413 | 157 | from typing import List, Tuple
import pytest
from pymatgen.core import Element, Structure
from mattergen.evaluation.utils.structure_matcher import (
DefaultDisorderedStructureMatcher,
DefaultOrderedStructureMatcher,
check_is_disordered,
)
@pytest.fixture
def test_structures_for_matcher() -> List[Structu... |
2bfbf4ca3fbe24f0b45f82ab84e3fb620b7e3aa55ac7c437ba3972d6ab3b8f9b | Python | 5,414 | 150 | import asyncio
import itertools
import logging
import math
from collections.abc import Callable, Mapping
from aiotinydb import AIOTinyDB
from aiotinydb.storage import AIOJSONStorage
from tinydb import where
from tqdm import tqdm
from apiadapters.straininfo import (
AsyncStrainInfoAdapter,
normalize_strain_nam... |
d9d9d64bdf6380ed5e2bd7cff31d6bb8c0078c22d17a5163ceb52df1e23cc1ce | Python | 5,414 | 119 | import torch.nn as nn
import torch
import torch.nn.functional as F
#from dcn_v2 import DCNv2
from modelR.layers.deform_conv_v2 import DeformConv2d, DeformConv2d_offset
class hsigmoid(nn.Module):
def forward(self, x):
out = F.relu6(x + 3, inplace=True) / 6
return out
class MTR_Head1(nn.Module):
... |
7caebc175b44b3c727fc50420ada1a6a9500f3e4ce9e2839f69205437aa85e7a | Python | 5,415 | 177 | #!/usr/bin/env python
#
# Copyright 2006, Google Inc.
# 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 copyright
# notice, this list... |
0e0ea17c6fd1082b37189e27a302b3f70d2b0227e2c4ff0da35c31c0e2b4ef9c | Python | 5,419 | 200 | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
from poetry.repositories.pypi_repository import PyPiRepository
if TYPE_CHECKING:
from cleo.testers.command_tester import CommandTester
from poetry.config.source import Source
from poetry.poetry import Poetry
from tes... |
fa3ef7573df06cd6f5f8999ead6d9d998883bb32c5c33ae8614e62d8fcde3a0d | Python | 5,420 | 161 | """Training losses follow the loss-weight ramp; selection does not."""
import pytest
import torch
from torch.utils.data import DataLoader
from d3text.models.config import ModelConfig
from d3text.models.entity_linking import BrendaClassificationModel
from d3text.models.ete import ETEBrendaModel
from d3text.models.mode... |
74efa8ff153df4f4e1394c43590f30c3e5e74d32d478d6a58e1f98ccdcfff90a | Python | 5,422 | 170 | #
# Copyright 2017-2023 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with
# Sandia Corporation, the U.S. Government retains certain rights in this software.
#
# See LICENSE for full license details
#
import numpy as np
from scipy.optimize import minimize
import time
import os
# Use th... |
5a69bef73c416af236538beb311a8256760ba29556a46b71cab66ba16ec90f25 | Python | 5,423 | 156 | """Controller for graph helper operations used by plot orchestration."""
from __future__ import annotations
import pandas as pd
from src.gui.framework.graph_plotter import (
convert_time_data,
draw_behaviour_boxes,
retrieve_behaviour_records,
set_ax_tick_spacing,
)
from src.gui.framework.graph_plotte... |
a0cab4ded09f5882109e54563b88814e31a4c725f2ea88b5f3bbf77925d87941 | Python | 5,423 | 196 | import os
import nipype.pipeline.engine as pe
from fetpype.pipelines.full_pipeline import (
create_rec_pipeline,
)
from fetpype.utils.utils_bids import (
create_datasource,
create_bids_datasink,
create_description_file,
)
from fetpype.workflows.utils import (
init_and_load_cfg,
check_and_updat... |
938dfcda6350537f84d69d0b5f8050cb881cfef136d672e89298c9ad5a4dabd8 | Python | 5,427 | 114 | import pandas as pd
import networkx as nx
def get_segment_iax(segment, df):
"""
Returns a DataFrame containing the axial current values for a specific segment.
This function extracts the axial currents associated with a
specified segment. It handles both cases where the segment is a reference (ref)
... |
439fa45bf67ae5834115e4468bc90481c23da272ce40192a0d9cc37a2d9bf1c5 | Python | 5,428 | 171 | # %%
"""Generate Lorenz and Rossler signal datasets.
The training and analysis scripts expect paired files named
``Chaos_Signals/data1_<id>.npy`` and ``Chaos_Signals/data2_<id>.npy``.
Here ``data1`` is the normalized Lorenz trajectory and ``data2`` is the
normalized Rossler trajectory. Each output has shape
``(data_s... |
7da30e07edc611e69304430b7ead813c461ddf238cff4f2b26de24ac96978a57 | Python | 5,428 | 147 | import unittest
from unittest.mock import MagicMock
from simulation_encoder.runner import Runner
from simulation_encoder.dataclass.param_sets import ModelParams, DatasetParams
def _make_model_params(name="test_model", model_type="AE"):
"""Minimal ModelParams for tests that don't need a real model instance."""
... |
5144bae6053bc6e7db2399e924e022311ca62516361d819779c30defa07a7225 | Python | 5,429 | 151 | from abc import ABC, abstractmethod
import numpy as np
import pandas as pd
import rich
from scvi._types import AnnOrMuData
from scvi.data import _constants
from scvi.data._utils import get_anndata_attribute
class BaseAnnDataField(ABC):
"""Abstract class for a single AnnData/MuData field.
A Field class defi... |
7a1b39615dec7d3516ea5f3fd0390317792c3ff35005a1b7df90bf52b844eb54 | Python | 5,430 | 125 | # coding=utf-8
# Copyright 2019 Facebook AI Research and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 Licens... |
b43a89121d9c262a0550d663251e557bb3ce67c1675f2c520d31a2505af2ad7d | Python | 5,431 | 126 | # coding=utf-8
# Copyright 2019 Facebook AI Research and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 Licens... |
7fc606d63593fa0b5551e9857d0c5f05e468d075a323ebc713292beb7ee5f4c9 | Python | 5,432 | 156 | """Whether a pass actually waited on prefetched layer-boundary reads.
`_resolve_layer_boundary_cached` (`src/d3text/models/base.py`) blocks each
batch item's `store.get` future on `.result()`; nothing recorded how long
that took, so a run could not say whether the reads keep ahead of the GPU.
This pins `log_pass_stats... |
b271e7eb0f4db0f750828e97ca10998e559d20242d5a947307933c2f76a05ac1 | Python | 5,432 | 114 | import pandas as pd
import networkx as nx
def get_segment_iax(segment, df):
"""
Returns a DataFrame containing the axial current values for a specific segment.
This function extracts the axial currents associated with a
specified segment. It handles both cases where the segment is a reference (ref)
... |
d824e9244568b7f677289844c20a2ac5758ebd98c2ab9be1fceb4ad75fecb760 | Python | 5,433 | 130 | import torch
import numpy as np
import math
import copy
from scipy.interpolate import interp1d
from Survival_CostFunc_CIndex import neg_par_log_likelihood
def dropout_mask(n_node, drop_p):
'''Construct a binary matrix to randomly drop nodes in a layer.
Input:
n_node: number of nodes in the ... |
613ad01787617de9c6e6a6eb67628c55e723294f44ffbb8fd92ea0234cd3d856 | Python | 5,434 | 143 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial import distance_matrix
"""
This function computes nearest-neighbor distances (NND) and furthest-neighbor
distances between chromatophores based on epicenter coordinates stored in a CSV
file. The CSV must include `chrom_id`, `epic... |
970db41335c60141a7bc1757d75d94d67cbd581fb82b8e277d6faf2a561bf701 | Python | 5,434 | 90 | import importlib.util
import json
import os
from pathlib import Path
import subprocess
import shutil
import sys
import tempfile
import unittest
import zipfile
ROOT = Path(__file__).resolve().parents[1]
spec = importlib.util.spec_from_file_location("prepare_release", ROOT / "tools/prepare_windows_release.py")
prepare_r... |
e27b652d91e60a00d4b022c9e21495d6401b956e974adce6c56930a64e54adc8 | Python | 5,435 | 139 | import os
import re
import argparse
from bs4 import BeautifulSoup
import warnings
import logging
logging.basicConfig(filename='../monq/logging/annotation.log', filemode='w',
level=logging.DEBUG, format='%(asctime)s %(levelname)-8s %(message)s', datefmt='%Y-%m-%d %H:%M:%S')
def format_input(input... |
dde7bb355e86949c03e77bc185cd2f11cd09e0e80ed517a2efc8dbd63402a674 | Python | 5,442 | 66 | #!/usr/bin/env python
import logging
import sys
import argparse
from version import VERSION as __version__, MASTHEAD
import gsa_mixer.cli
import mixer_dev.cli
import bivar_mixer.figures
import common.utils_cli
if __name__ == "__main__":
logging.getLogger().setLevel(logging.INFO)
parser = argparse.ArgumentPa... |
85424efdbb8994793c032dc97fa88af56e2cf0e44262251d7f5a1722dd27c1e0 | Python | 5,443 | 123 |
from PyQt5.QtWidgets import *
import os
from PyQt5.QtGui import *
from PyQt5.QtCore import *
import cv2 as cv
import numpy as np
import sys
from scipy import stats
class tTestMap(QWidget):
def __init__(self):
super(tTestMap, self).__init__()
self.setFixedSize(400,240)
self.... |
9b39cc6e4968de563f065bd9ca0b3fba9065f5b8ed384ae636eca7ea0aa9ecfb | Python | 5,443 | 128 | # %%
"""Formal statistics for the selective-ablation effect (Reviewer 1, point 5).
For each output (Lorenz, Rossler) and each training condition (MI+L2, L2-only),
ablation is evaluated on the same models for both the primary and the
non-primary subgroup. This script quantifies the selective-damage signature:
1. gap(k... |
10c8eae0fbbd6638080ea2ec5088ca7030b2c56895531dbdaf238ba85dd0effb | Python | 5,449 | 172 | #!/usr/bin/env fbpython
# (c) Meta Platforms, Inc. and affiliates. Confidential and proprietary.
import contextlib
import logging
import unittest
from io import StringIO
from unittest.mock import MagicMock, patch
import torch
from fairseq import checkpoint_utils, data
from omegaconf import OmegaConf
def mock_traine... |
bfffa671f3361f50c3f201cdcae409b5819bb6411dd4146175eaccf0d12421bb | Python | 5,450 | 153 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import sys
import torch
from fairseq import utils
class SequenceScorer(object):
"""Scores the target for a given source sentence."""
... |
4d8b418698cbb4fb6cb0ee92526af7e0b866fcfd067c7f1115b853cd32f1d402 | Python | 5,451 | 144 | """File discovery, filename parsing, and CSV loading helpers.
Experiment files follow the naming convention
`DATE-YYYY-MM-DD_TIME-HH-MM-SS_..._fish-N_Ddpa_<genotype>_..._tracking-data.csv`.
"""
import os
from datetime import datetime
from pathlib import Path
import numpy as np
import pandas as pd
def find_files(fo... |
27e55ed9d74b0f59269a805302549e8693955bb69f27b2ed3786b71465849e3c | Python | 5,452 | 197 | # %%
from pathlib import Path
import pickle
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import t
# %%
# ================================
# Settings
# ================================
INPUT_DIR = Path(".")
OUTPUT_PATH = Path("Fig/dropout_robustness_primary_nonprimary.pdf")
OUTPUT_PATH_RIGHT_LE... |
73eb177e66ea6fa555fc8395b0e81c07937ed1bdcb57900e9e6bae44f3a8e1ba | Python | 5,461 | 143 | import math
import warnings
from typing import Optional, cast, List
from torch import Tensor
from torch.optim import Optimizer
from torch.optim.lr_scheduler import _LRScheduler, CosineAnnealingLR, _enable_get_lr_call
class Lin_incr_LRScheduler(_LRScheduler):
def __init__(self, optimizer, max_lr: float, max_steps... |
ba43c13819b95251576330b266605c85eb3c3066d6785a3f430036dd821add4e | Python | 5,461 | 146 | """Function that evaluates trained models in the parametric UMAP family."""
from __future__ import annotations
import logging
import pathlib
from collections import OrderedDict
from datetime import datetime
import lightning
import pandas as pd
import torch.utils.data
from .. import models
from ..common import valid... |
349ed8f6e0e699a254e332e88977bd87b737ae407b2c60a591d36ccaf54bafbb | Python | 5,465 | 138 | import unittest
from unittest.mock import patch
from pyecharts import options as opts
from pyecharts.charts import BMap
from pyecharts.globals import BMapType, ChartType
BAIDU_MAP_API_PREFIX = "https://api.map.baidu.com/api?v=2.0"
FAKE_API_KEY = "fake_application_key"
TEST_LOCATION = ["London"]
TEST_VALUE = [1]
cl... |
1fa0d55a7dc143cf30c91c50f6e3246c7d21ef36c04a3d3b93e72996d1133a3b | Python | 5,467 | 142 | import numpy as np
import cv2
def rotate_2d_vector_array(va,angle,axis=0,rad=True):#len along 'axis' should =2, transform vector to a newcorr system rotated with angle
assert va.shape[axis]==2
#va_r=np.copy(va)
X=np.take(va,0,axis=axis)
#print (X)
Y=np.take(va,1,axis=axis)
#print (Y)
... |
1ff28f88dd9d3e82ea328456a8e8db889818fabb0b81aa9bc75be1b3ff287581 | Python | 5,469 | 136 | """High-level function that evaluates trained models."""
from __future__ import annotations
import logging
import pathlib
from .. import models
from ..common import validators
from .frame_classification import eval_frame_classification_model
from .parametric_umap import eval_parametric_umap_model
logger = logging.g... |
6d57039517f07d942862e3150440946780176abf2ea2cd9e578e0c5726884dfa | Python | 5,469 | 139 | import torch
import numpy as np
import os
from networks.cnn import BINND, BINNDLite
from utils.paths import ROOT_DIR
MODEL_PATH = f"{ROOT_DIR}/inference_demo/BINND.pt" # Path to the pre-trained model file. Choose between BINND.pt or BINNDLite.pt
MAX_SEQUENCE_LENGTH = 20 # The current implementation only supports sequen... |
d84f8e9e5b520b8ee476b4b796452e7039b7594cf54134ae258e24f7f5a2462d | Python | 5,475 | 158 | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
from poetry.factory import Factory
from poetry.puzzle.provider import IncompatibleConstraintsError
from tests.mixology.helpers import add_to_repo
from tests.mixology.helpers import check_solver_result
if TYPE_CHECKING:
from poetr... |
5c6063ce3170d2df52c0a11f651a6166bd7e0d27040deafd4b97212578c2560c | Python | 5,476 | 153 | import argparse
import subprocess
import torch
import numpy as np
import biotite.structure.io as bsio
from Bio import SeqIO
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
from transformers import (
AutoConfig,
AutoModelForCausalLM,
AutoTokenizer,
EsmForProteinFolding,
set_seed
)
from e... |
dd80aac1304af2f2fa41da5340d7d9dc3f75017b75deec620306dc9aa2442868 | Python | 5,476 | 141 | import logging
import tempfile
import unittest
from pathlib import Path
from GMXMMPBSA.fake_mpi import MPI as FakeMPI
from GMXMMPBSA.exceptions import GMXMMPBSA_ERROR, MMPBSA_Error
from GMXMMPBSA.logging_utils import (
enable_file_logging,
format_command_line,
setup_logging as _setup_logging,
)
from GMXMMP... |
1cd05ec2c8cbef2d02b2b0a05f8e7eb8df335bd2a870870d5c4f2e8b94cb7a0b | Python | 5,481 | 150 | import asyncio
import itertools
import logging
import math
from collections.abc import Callable, Mapping
from aiotinydb import AIOTinyDB
from aiotinydb.storage import AIOJSONStorage
from tinydb import where
from tqdm import tqdm
from apiadapters.straininfo import (
AsyncStrainInfoAdapter,
normalize_strain_nam... |
9d7281d6753c89f7b0a20b49b1b3b05983c7299856370f1a499a3c8f5093b9a4 | Python | 5,482 | 125 | from pathlib import Path
import numpy as np
import pandas as pd
import thermodynamic_consistency_diagnostic as diag
def test_partition_helpers_use_gas_to_water_direction():
x = diag.aqueous_mole_fraction_from_molality(1.0)
assert np.isclose(x, 1.0 / (55.508 + 1.0))
lower_solubility_index = diag.gas_to_... |
3e7c4d86fb7dff29b9a95088dec74f931430b39a26c1234e603086fc6de2554b | Python | 5,484 | 162 | import os
import numpy as np
import pandas as pd
import pytest
from scipy import stats
from pgmpy.ci_tests import FisherZ, Pearsonr
from pgmpy.factors.continuous import LinearGaussianCPD
from pgmpy.models import LinearGaussianBayesianNetwork
@pytest.fixture
def fisher_data():
rng = np.random.default_rng(seed=42... |
c30a9f9d175088c5228de36a29c8cc5770fd1f045d458d579f1196e53791d8ab | Python | 5,484 | 113 | import matplotlib.pyplot as plt
import numpy as np
import igraph as ig
import networkx as nx
import os
import sys
import pandas as pd
sys.path.append('..\\src\\')
from read_graph import read_graph, k_core_weights, display_graph, display_graph_3d
from utils import get_category_indices
labels = ["G1", "G2", "G3", "G4", ... |
acc3217248e60d1a7ef18cd5935eda2bdd6dd61d22b3763ead8340d90a7bfe82 | Python | 5,486 | 128 | import pytest
import vak.config
class TestConfig:
@pytest.mark.parametrize(
'tables_to_parse',
[
None,
'prep',
['prep'],
]
)
def test_init_with_real_config(
self, a_generated_config_dict, tables_to_parse
):
... |
4f3905a7b7abf0ccae64cc54abe05eaa4a86e60158aae0acf0bf084e4808aab4 | Python | 5,487 | 140 | """Check that the shipped datasets match the cached benchmark predictions.
Why this exists
---------------
The training scripts locate their inputs with ``find_dataset_file``, which
searches a fallback chain::
$HIPPIE_DATA_ROOT/<dataset>/<file>
./datasets/<dataset>/<file>
./datasets_hippie/<dataset>/<file... |
083210554c63316c039a11379c5975107fe1b73fc3a8d370803ac1b8d6c4ebd2 | Python | 5,495 | 103 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'optimization_extra_data_add_protocol_map_dialog.ui'
#
# Created by: PyQt5 UI code generator 5.10.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_AddProtocolMapDialog(object):
... |
c545fc5acebc19c63de4118bc493be80f0d11cc447c2396dde428fe1170fc75f | Python | 5,496 | 158 | import networkx as nx
import pytest
from pgmpy.base import SimpleCausalModel
def test_simple_string_variables():
model = SimpleCausalModel(exposures="X", outcomes="Y", confounders="Z", mediators="M", instruments="I")
assert set(model.nodes()) == {"X", "Y", "Z", "M", "I"}
expected_edges = {("Z", "X"), ("Z... |
395abd4479239407308c3f383814861679d475ef672c671a03d612e051ba7004 | Python | 5,500 | 100 | #!/usr/bin/env python3
"""Reviewer point 2: add an explicit methylation-compartment flag to Supplementary Table S2 and
run the promoter-only sensitivity analysis.
Each of the 82 inverse-concordant genes is classified by the source of its methylation call:
- mCSEA promoter-region enrichment (promoter-anchored, consis... |
172d77f55d805a704af558bb7f38205f728728d2e5a4c91e1472c4f3128815ad | Python | 5,501 | 11 | import numpy as np
import pandas as pd
cn = {'P':0,'M':1,'A':2,'B':3}
cn_ = {0:'P',1:'M',2:'A',3:'B'}
chain_1_hot = np.eye(4)
b50 = {'A': np.array((5,-2,-1,-2,-1,-1,-1,0,-2,-1,-2,-1,-1,-3,-1,1,0,-3,-2,0)),'R': np.array((-2,7,-1,-2,-4,1,0,-3,0,-4,-3,3,-2,-3,-3,-1,-1,-3,-1,-3)),'N': np.array((-1,-1,7,2,-2,0,0,0,1,-3,-4,... |
420dfc8260aa27f54fe1336b1a82bec9178eadaa08d647a404b3df12d239b9c7 | Python | 5,504 | 152 | # -*- coding: utf-8 -*-
"""
Created on Thu Feb 6 14:42:30 2025
@author: hanna
"""
from tqdm import tqdm
import numpy as np
from sklearn.decomposition import FactorAnalysis
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import KFold
def perform_cv(data, n_components, n_splits, n_... |
d1d4caed52fe9fe061d015ef3c2b29521b716894b07e28dac3c7d27e6d42c7fe | Python | 5,504 | 155 | # Copyright 2021 DeepMind Technologies Limited
#
# 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 agr... |
ea931678459153c39161931b9ea8cb8edf537c2b028868a3e402c1adda863990 | Python | 5,504 | 162 | """Training UX callbacks: ETA in hours, val loss history for two-phase schedule."""
from __future__ import annotations
import time
from typing import Any, List, Optional
import pytorch_lightning as pl
from omegaconf import DictConfig
import torch
from pytorch_lightning.callbacks import TQDMProgressBar
from pytorch_l... |
b7c2ee4a7d6cc3af891ab4e6aa79374eb1aef51ed05da46ce11400476cdbfa50 | Python | 5,505 | 144 | import os
import sys
import warnings
from typing import Any
import pandas as pd
from scvi import settings
from scvi.utils import dependencies
@dependencies("mlflow")
def mlflow_log_artifact(
local_path: str,
artifact_path: str | None = None,
run_id: str | None = None,
max_size_mb: float = 5.0,
) -> ... |
cedba9505139462384e939b2ea6a11ee74c91f15a9cd739b7e1df0b745447d2e | Python | 5,506 | 151 | """Signal-processing utilities shared across the OMR analyses."""
import numpy as np
def interpolate_nans(data: np.ndarray) -> np.ndarray:
"""Linearly interpolate NaN values, extrapolating the edges with 0."""
out = data.copy()
if np.isnan(out[0]):
out[0] = 0.0
if np.isnan(out[-1]):
o... |
c5b2d9b204af2e64778ca284c2bb9fe6062b9f772b96732e5aeda1653f385524 | Python | 5,507 | 143 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from fairseq.modules.quantization import pq, quantization_options, scalar
from omegaconf import DictConfig
logger = logging.... |
54421dc81d692751abf5dee9a5567473d287481ceacc5a3266b1811e3a2fee33 | Python | 5,514 | 163 | import torch
import numpy as np
import utils.Geometry as Geometry
def meshgirdFromXY(x,y):
X,Y = torch.meshgrid(x, y)
X=X.reshape(-1)
Y=Y.reshape(-1)
return X,Y
def genMeshNodes2D(xstart,xend,xnum,ystart,yend,ynum):
'''生成规则网格排列的二维点'''
x = torch.linspace(xstart,xend,xnum)
y = torc... |
612b6b41090657327e9ef8aee333ace94bba05fd0d6a3dcd6fb4a34228b3d873 | Python | 5,514 | 161 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from dataclasses import dataclass
from functools import partial
from typing import Callable, Dict, Optional
import torch.nn as nn... |
f13ac3ee767960439055727b7aa170f264f05f8af5bddebfbac457eb5f770ab6 | Python | 5,514 | 139 | """Active learning iteration 3 — 50 picks, non-strain only, train on n=193.
Same protocol as iter 2 but with the n=193 SIESTA pool (initial 93 + AL1 50
+ AL2 50). Confines selection to non-strain candidates.
"""
from __future__ import annotations
import json
import re
from collections import defaultdict
from pathlib... |
73fb69ae0c8cf4b239cbab8e0b88af82178f412d66c8cbfbfcedc72f7444bec6 | Python | 5,515 | 169 | from __future__ import annotations
from PySide6.QtCore import QPoint, Qt, Signal
from PySide6.QtWidgets import (
QFrame,
QListWidget,
QListWidgetItem,
QPushButton,
QVBoxLayout,
QWidget,
)
from src.gui.framework.qt_view_styles import PALETTE, apply_button_role
_POPUP_STYLESHEET = f"""
QFrame#c... |
2ca88d4dfcd8465df352d5a3ee8de3c06cece42d6b25e3b8c14b685b32badb9b | Python | 5,518 | 197 | import gzip
import io
from skbase.base import BaseObject
from skbase.lookup import all_objects
from pgmpy.base import DAG
from pgmpy.readwrite import BIFReader
from pgmpy.utils.hf_hub import read_hf_file
class BaseExampleModel(BaseObject):
"""
Base class for all models in pgmpy.
Inherits from `skbase.b... |
244c21845493d4461ddb496a7b0be4867f94eaccd266e7fe4d7219edd5678ae8 | Python | 5,520 | 178 | #
# Copyright 2017-2023 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with
# Sandia Corporation, the U.S. Government retains certain rights in this software.
#
# See LICENSE for full license details
#
import numpy as np
from scipy.optimize import minimize
import time
import os
# Use ... |
4ebecd3344b79fcb49844cac1a7a0293bcf7b78fd301afd210f16d5d52c9f162 | Python | 5,522 | 143 | #!/usr/bin/env python
# ENCODE DCC Naive overlap wrapper
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_common import *
from encode_common_genomic import peak_to_bigbed, peak_to_hammock
from encode_blacklist_filter import blacklist_filter
from encode_frip import frip, frip_shif... |
2fc25827fc37425bdb750728857f58db2824feb3470a3150804d504c3df0c986 | Python | 5,525 | 109 | #!/usr/bin/env python3
"""Controles do resultado positivo da rodada 2. Quatro perguntas:
C1. Baseline constante: prever a mediana para todos. Se o erro do OCE nao for
bem menor, nao ha resolucao nenhuma.
C2. Baseline de volume: B correlaciona com 1/V0 por argumento fisico trivial
(celula menor, mais rigida... |
5800c4f2ba0ffa908779e9b85fe31bc14adac2b6598624c262fd3d95c870b4e2 | Python | 5,525 | 160 | import random
from typing import Optional, Sequence, Tuple, Any, List
from pathlib import Path
import numpy as np
from omegaconf import DictConfig
import torch
from torch.utils.data import Dataset, DistributedSampler
from torch.utils.data.distributed import DistributedSampler
from torch_geometric.loader import DataLo... |
0ca0a97ddbdef37d4d7217c25c45530383864472eed5e4a0870c06b281bd6024 | Python | 5,526 | 147 | from copy import deepcopy
import numpy as np
from batchgenerators.utilities.file_and_folder_operations import *
import shutil
from nnunetv2.dataset_conversion.generate_dataset_json import generate_dataset_json
from nnunetv2.paths import nnUNet_raw
import SimpleITK as sitk
if __name__ == '__main__':
"""
Downlo... |
d011dc77d391965b74d9d4c4bab62c0367fb5e7e2bc655fda4d11eeba396114f | Python | 5,526 | 138 | from copy import deepcopy
from mdt.component_templates.base import ComponentBuilder, ComponentTemplate
from mot.lib.cl_function import SimpleCLFunction, SimpleCLCodeObject
from mdt.model_building.parameters import LibraryParameter
from mdt.lib.components import get_component
from mot.library_functions.base import CLLib... |
5c41b2940a349741fca4bf1f0566dc7f7f3d9550aaee569b902df1a145c80428 | Python | 5,527 | 109 | import sys
sys.path.append("../utils")
import torch
import torch.nn as nn
import torch.nn.functional as F
from utils import utils_basic
import config.cfg_lodet as cfg
class FocalLoss(nn.Module):
def __init__(self, gamma=2.0, alpha=1.0, reduction="mean"):
super(FocalLoss, self).__init__()
self.__gam... |
4c8d8da55f432be3915d7c8b9834b90a17f927acdbbabca9c9b859347d80d4e6 | Python | 5,529 | 157 | # Copyright Howto100M authors.
# Copyright (c) Facebook, Inc. All Rights Reserved
import torch as th
import torch.nn.functional as F
import math
import numpy as np
import argparse
from torch.utils.data import DataLoader
from model import get_model
from preprocessing import Preprocessing
from random_sequence_shuffler ... |
6787c53a0252be8a3f3d0b77a7c9da4f82d8f411b33921fbceb73530269a540b | Python | 5,529 | 154 | import pytest
import torch
import scvi.distributions._gamma as gamma_module
from scvi.distributions import ZeroInflatedGamma
def test_zero_inflated_gamma_distribution():
"""Test ZeroInflatedGamma distribution."""
concentration = torch.tensor([2.0, 3.0])
rate = torch.tensor([1.0, 2.0])
zi_logits = tor... |
d317dd4112accbd5b0f2f52e8e64ce5c27ed06a87e3ef9f61703844ae76e0963 | Python | 5,532 | 152 | import os
from pathlib import Path
import pandas as pd
os.environ['WANDB_DIR'] = 'ADD YOUR DIRECTORY'
import wandb
import numpy as np
import torch, torchvision
from baseModels.utils import get_model
from training.training_utils import test_one_epoch
from analysis.metrics import dPrime_model
def getPerformance(mode... |
a1bde584f69856218ce7d42b04e614333d38e9e78f8ae3d64e66907a3d010283 | Python | 5,533 | 125 | import numpy as np
import collections
from mdt.lib.components import get_model
from mdt.lib.nifti import get_all_nifti_data
from mdt.utils import create_roi, restore_volumes
from mdt.lib.input_data import MockMRIInputData
from mot.lib.cl_function import SimpleCLFunction
from mot.lib.kernel_data import Array, Zeros
__a... |
c2579f3f02876db70948d51bcba11a1c11a02cfed72cc4278834f458c6027f49 | Python | 5,537 | 145 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
3b507c9a875222999a229526275b3c9efeaca16f376e9e66e49d15d58d86dda9 | Python | 5,538 | 144 | """Hybrid CE + Dice and metrics for dynamic segmentation."""
from __future__ import annotations
import torch
import torch.nn as nn
import torch.nn.functional as F
def compute_class_weight_from_loader(loader, num_classes, device="cuda"):
counts = torch.zeros(num_classes).to(device)
max_batches = 5... |
ee1d91105f482d20b279a8831008135ab501ae03e679f4b41ee94daf704b1cbe | Python | 5,538 | 143 | from ... import options as opts
from ... import types
from ...charts.chart import Chart
from ...commons.utils import JsCode
from ...globals import ChartType
class Polar(Chart):
"""
<<< Polar >>>
Polar coordinates can be used for scatter and polyline graphs.
"""
def __init__(
... |
7cc743035ce01b6bf6327133b6c3dd73e0f086ab27dd5f8a8b2275efa0d6ad12 | Python | 5,539 | 157 | """
Copy part of code from https://github.com/MIC-DKFZ/batchgenerators needed for inference so we do not
need this dependency during inference. This way we can become windows compatible.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from builtins impo... |
34cd6f18b824ae4a917ef069fc0e03d506ab0fe09c4836aa5980df2c97609786 | Python | 5,540 | 155 | """Measurement: is an LMDB get + blosc2 decompress cheaper than the forward?
Sources token ids from the precomputed encodings HDF5 rather than the corpus
text, so the input is byte-identical to what the training path feeds the base
model. Also sizes the store: the 112 GiB train figure below is
*uncompressed*, and the ... |
e6a754e6b68203e5b9033fe11632a3f9b193cc29defda368a5351b3cc4c5c6aa | Python | 5,541 | 142 | # Version information START --------------------------------------------------
VERSION_INFO = \
"""
Author: ZHANG YUBO
Version-01:
2019-11-04 calculate mean absolute error between prediction and true value
Version-02:
2021-09-23 calculate scaled Euclidean distance between prediction an... |
1ce325019f1ca9df925745a1a0ce0b1246b3de0223be5c05ee1659df9b223a24 | Python | 5,544 | 176 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Saves results of analysis"""
import os
import csv
from typing import Optional
from utils.models import Cell
class SaveCounts(object):
"""saves cell counts"""
fname = "counts"
extension = "csv"
encoding = "utf-8"
delimiter = ","
lineterminato... |
c1d3501ea6a05b17cfde1666e714cd0dbbcec7710ceac43430474cc666170f42 | Python | 5,545 | 123 | from multiprocessing import Pool
from typing import Union, Tuple
import numpy as np
from batchgenerators.utilities.file_and_folder_operations import *
from nnunetv2.configuration import default_num_processes
from nnunetv2.paths import nnUNet_results
from nnunetv2.utilities.dataset_name_id_conversion import maybe_conve... |
194f789eb1ca3bddb2bbb085c00c1cfd2199d51b0d7a102cd6780b374551197c | Python | 5,547 | 143 | #!/usr/bin/env python
# ENCODE DCC Naive overlap wrapper
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_common import *
from encode_common_genomic import peak_to_bigbed, peak_to_hammock
from encode_blacklist_filter import blacklist_filter
from encode_frip import frip, frip_shif... |
8ed7b53042678fec9ffb6d04ce97566bef1dfd66805429aba35af3fd2438fe22 | Python | 5,547 | 158 | import torch
import neurovfm.systems.classification as cls_mod
import neurovfm.models.mil as mil_mod
class _LinearDense(torch.nn.Module):
"""CPU-friendly stand-in for flash_attn FusedDense used in MIL modules."""
def __init__(self, in_features: int, out_features: int, bias: bool = True, **_):
super(... |
fe510581560a8e7130f645d868551d078d475b9ea2a2b32cc0c6dc70f6b5a06a | Python | 5,548 | 176 | import torch
import numpy as np
import unittest
from fairseq.modules import (
ESPNETMultiHeadedAttention,
RelPositionMultiHeadedAttention,
RotaryPositionMultiHeadedAttention,
)
torch.use_deterministic_algorithms(True)
class TestESPNETMultiHeadedAttention(unittest.TestCase):
def setUp(self) -> None:
... |
3ed6c7957b9200b1191d12d8f3480456fba7b797180c4581f7ac127942f5eb28 | Python | 5,555 | 172 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
from fairseq.models.transformer import (
TransformerDecoder,
TransformerEncoder,
TransformerModel,
)
fro... |
4128e3e707cb17e5dcc7b030fe0fd09002c4af02b73973f5b0a39d3db40ecf37 | Python | 5,556 | 128 | # RNAlysis-owned PyInstaller hook for the pure-Python ``graphviz`` package.
#
# RNAlysis depends on ``graphviz`` (NOT ``pygraphviz``); it shells out to the ``dot`` executable to
# render ontology DAGs. To keep the frozen app self-contained we bundle the graphviz program
# executables and their plugins/shared libraries.... |
f20eeb79c735f2ae82b295b27ffa65d4f3c19e62c12107895efaadcf61a830c1 | Python | 5,556 | 98 | import re
import slicer
from DICOMLib import DICOMUtils
import numpy as np
import StereotacticPlan
from .importerBase import ImporterDialogBase
class ImporterDialog(ImporterDialogBase):
def __init__(self):
ImporterDialogBase.__init__(self)
self.importerName = 'ROSA'
self.fileSelectTitle = ... |
71046c33fa9dbc80375921c12c36e812251e1c3c7da883c4e1f9c5640a83ce38 | Python | 5,557 | 159 | """A bounded Python implementation of the ``msbackadj`` baseline estimator.
The DFer option uses the documented quantile-window model with a pchip fit,
10% quantile, and equal window/step sizes. MATLAB is not available in the
application test environment, so this module is intentionally described as a
compatible esti... |
d232079375568cc268c58fbf0fbfc9ba79576769109807faab9e3303937ac956 | Python | 5,564 | 136 | """ Utility functions to plot data. """
import matplotlib.pyplot as plt
import numpy as np
def plot_queenframe(queenframe: np.ndarray) -> None:
"""
Plot the queenframe image.
Args:
queenframe (np.ndarray): The queenframe image to be plotted.
Returns:
None
This function displays ... |
604fa0a00777d13ed362aa7ef2051e6658737db107ab71cb65cd55b97b7c7c31 | Python | 5,566 | 164 | import pytest
from rnalysis.exceptions import (
ExternalServiceError,
IDMappingJobFailedError,
IDMappingTimeoutError,
InternalError,
InvalidTypeError,
InvalidValueError,
RNAlysisError,
RNAlysisInputError,
)
BUG_REPORT_SUFFIX = (
'This is likely a bug in RNAlysis - please report it ... |
d39b495853b2fb4199c6dfb64b1d41b50dc23a826c4c600aa394e333c90e6d72 | Python | 5,572 | 165 | import csv
import os
from collections import defaultdict
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
CSV_FILE = os.path.join(SCRIPT_DIR, "raw_readme.csv")
metadata = {}
panels = []
with open(CSV_FILE, newline="", encoding="utf-8-sig") as f:
reader = csv.reader(f)
rows = list(reader)
# Metadata r... |
4675d52ea8f2e6c67a33c80bade6699d52ca1d6dfd2658c9e49d794509ae843c | Python | 5,573 | 167 | """SIESTA isolated-atom references for the 9 perovskite elements.
Each atom is placed alone in a 20-A cubic vacuum box, spin-polarised, with
the same SZP basis and MeshCutoff 250 Ry used in the perovskite production
run. The unpaired-electron count comes from the GROUND_STATE_UHF dict in
oce.atomic_table (xtb-derived... |
897a1d01d32ec19b856705e60f2ab8121cdf7c6cc4ecf2b9247e9e9d8712a1a6 | Python | 5,573 | 150 | import torch
from torch import nn
from torch.nn import functional as F
from rinalmo.model.attention import MultiHeadSelfAttention, FlashMultiHeadSelfAttention
import torch.utils.checkpoint as checkpoint
class TokenDropout(nn.Module):
def __init__(
self,
active: bool,
mask_ratio: float,
... |
af56600ca644007acf2b4468ebc01063fdf56eaefecbcd53f66f8c0a2087f20c | Python | 5,578 | 161 | import scanpy as sc
import sys
sys.path.append('./scctools_0.4')
from scctools import *
# # load data
ad = sc.read('./FM27_cell_133454_wk.h5')
glut = FM27_cell[FM27_cell.obs['class']=='Exc',:]
# # violin plot
key = glut
matplotlib.rcParams.update({'font.size': 14})
basic_gene = ['SLC17A7','HPCAL1','NPY']
L23NPY_sp... |
ea3208d08f637569596b995e99f4d897a40d99b740ee9e5e00ccfcbdeb722b30 | Python | 5,578 | 145 | import h5py
import numpy as np
import tensortools as tt
import matplotlib.pyplot as plt
from scipy.stats import sem, t
from collections import defaultdict
import os
import pickle
num_animals = 12
replicates = 30
num_components = 31
output_dir = "performance_metrics"
os.makedirs(output_dir, exist_ok=True)
def compute... |
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