sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
91604ee4c85dd6cf213fbde5e6b7c86809bec264186576eecb5934757040988d | Python | 4,014 | 134 | from __future__ import division, print_function
import numpy as np
from numpy import inf, ndarray
import pandas as pd
import torch
import torch.nn as nn
from torch.functional import F
import os
import random
import sklearn
from sklearn.model_selection import KFold, StratifiedKFold
from sklearn import metrics
import re
... |
56ff48b89d643bede7c1c9113177c7068b3e0ac7bd249c194c2165e5d9c64155 | Python | 4,015 | 145 | from abc import ABC, abstractmethod
from dataclasses import KW_ONLY
from typing import Callable, Optional, Union
import equinox as eqx
import jax
import jax.numpy as jnp
import jax.scipy.special as jsp
class CardiacDriverBase(ABC, eqx.Module):
_: KW_ONLY
dynamic: bool = False
class FixedCardiacDriver(Cardi... |
7ebc7563c21385bc5634df3c55e6233ffd5475f0573132c6de289f4d360dface | Python | 4,015 | 118 | # --- 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 Gradient(_BaseTraceHierarchyType):
_parent_path_str = "scatterternary.marker"... |
814d819fcad59a5446318d4bba7404e6d4bf7a04d016f63876110d6b46077025 | Python | 4,015 | 115 | # SOURCE: vendored from HazeDT/WaveletKernelNet @ cd6091bf543bb03b65fb989f9dc28aeb3d4be3de
# https://github.com/HazeDT/WaveletKernelNet/blob/master/models/Morlet_LeNet.py
# The `Morlet_fast` (learnable-Morlet-wavelet CWConv layer, replaces the first conv
# layer with a bank of trainable-scale/translation wavelet filter... |
c5ea9a4ca0cfd1c7ad63f5f2c42c0e0dc7d5a159916ef6ff78218dfe92887cc1 | Python | 4,015 | 112 | # Copyright (c) 2024 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... |
6b017aa34adb1922cfc271a580095589072f949e3cba6174d694f8fc6adcb46b | Python | 4,016 | 127 | 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,
... |
b8fd3a023b44f1ea41c1753cc3b7162533e6845ede003b85af1cf3f3764b5150 | Python | 4,016 | 92 | import glob
import argparse
import json
import os
import tqdm
import numpy as np
import pandas as pd
from mp_dip.utils.db_atoms_utils import read_db_atoms
from mp_dip.utils.utils import read_raw, preanalyse_raw, get_rms_percentile, filter_selected_atoms, \
svarog_tags_writer, get_mp_to_raw_channel_map, get_mp_bo... |
3ded4f34faafcdfca48a7e0989b5d9fdbcd6485bca0817ac84b7fe920dc5585a | Python | 4,017 | 89 | import sys
import json
from collections import defaultdict
import numpy as np
import matplotlib
matplotlib.use("Agg")
from matplotlib import patheffects
import matplotlib.pyplot as plt
import aquarel
theme = (
aquarel.load_theme("arctic_light")
.set_grid(draw=True, width=0.5)
.set_font(family="sans-serif"... |
4d40266650d2b658ec34e29389d5c0010caf2a9bcc395916885ad1b53a0d940d | Python | 4,019 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "scatter3d.line.colorbar"
... |
59d04dda8b7fcedcecb86457307fd4bc2c9d49da52506afc48e679cf24204d63 | Python | 4,019 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "treemap.marker.colorbar"
... |
8550f25783cb32763edcb2ae4d51b34dc7c4e2a60f03f1a2e3e312139c306c47 | Python | 4,019 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "scatter.marker.colorbar"
... |
8e01dae88a9f5a4b4b582b1400e2be02ec4991a61b68f6073fe95c75a8a3f568 | Python | 4,019 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "parcoords.line.colorbar"
... |
f12c5ef5031035f651414014cc693f3dea9e05e947368bf71bda2f49f01c474c | Python | 4,019 | 106 | """Harvestability spike (row 0.9): count taught paths + claim strings NOW.
The taught-path and prose-claim universes stay OPEN until their parsers
exist; this spike proves the harvest is feasible and pins TODAY's counts so
the sweeps written against them at wave A start from a measured baseline,
never a guess. Fallbac... |
2a30cd68bb0ce171eee7dcc01be21faf33613a92b3d14beba691db7d2c7ce246 | Python | 4,020 | 114 | """
Figure about FSM models.
"""
import os
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import figutils
from PyPDF2 import PdfReader, PdfWriter, Transformation
# If you change figutils often, and want changes reloaded, uncomment lines below:
#from importlib import reload
#r... |
91759f37cf5e7a51dbd855236ebb7946c6b741089703e8b69816965a5521076b | Python | 4,021 | 134 | from __future__ import division, print_function
import numpy as np
from numpy import inf, ndarray
import pandas as pd
import torch
import torch.nn as nn
from torch.functional import F
import os
import random
import sklearn
from sklearn.model_selection import KFold, StratifiedKFold
from sklearn import metrics
import re
... |
a3e9f5da828a90a21034797a027444d46957272b9c31ff735e2a1e8e9b610604 | Python | 4,021 | 135 | import numpy as np
import tensorflow as tf
import random as python_random
import os
import tensorflow_datasets as tfds
from tensorflow.keras.models import load_model
from gradient_accumulator import GradientAccumulateOptimizer
def normalize_img(image, label):
"""Normalizes images: `uint8` -> `float32`."""
ret... |
2265f622c41d802098906a0947dd822f4d2b024b54e88de9d18f82f28d92d3ab | Python | 4,022 | 133 | # --- 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 Marker(_BaseTraceHierarchyType):
_parent_path_str = "box.selected"
_path_... |
15f8550a477d4f09d96b6f309774381b410493ac5550f924483497645dcfd0f8 | Python | 4,024 | 84 | import glob
import os
import SimpleITK as sitk
import cv2
import numpy as np
from natsort import natsorted
def subsample_segmentation(in_data, dim_size=None):
"""Takes an input image (no color channel) and resamples it to a desired size. It can be expanded to work with
any number of dimensions. """
dims ... |
aa822dc224cfaf91820d2b9f8faab26e1400cbbbdc3689b8001d032b5a98c9b3 | Python | 4,024 | 100 | """Lane A08 row gate: the harvested genuine-release corpus still round-trips.
The persistence-honesty fixes (WT1 A-IV items 17-22 + W3) must not change how
LAWFUL existing artifacts load: every in-window genuine artifact (writers
v2.31.0 through unreleased main) loads, and the below-floor v2.16.0 ModelLog
bundle keeps... |
1c7b9b34c46f6de6f1422b959af6c46d6f32756c0ea51ddff99af2b52297353d | Python | 4,026 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "sunburst.marker.colorbar"... |
624f4c053f6cc68e70431f33d9ab5e4e7a5c4c5ed9cb7c10e8968173bc435e37 | Python | 4,026 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "barpolar.marker.colorbar"... |
3e0b365db79bcb9533951977fbfa02f38d1389e4d5e132a8dcf364ab662044f4 | Python | 4,028 | 120 | import os
import argparse
import json
import gzip
from rdkit import Chem
class ModificationConstants:
DNA_SMILES_BACKBONE = "O=P(O)(O)OCC1OC*CC1(O)"
DNA_NAME_MAPPING = {
0: "OP1",
1: "P",
2: "OP2",
3: "OP3",
4: "O5'",
5: "C5'",
6: "C4'",
7: "O4'",
8: "C1'",
-1: "O3'",
-2: "C3'",
-3: "C2'",
}... |
c3b95bd5a19c02c2ed16aa809c40a65bd20c0110fde26ad8bf85ee1afaa4ab71 | Python | 4,028 | 124 | from __future__ import annotations
import pytest
from pybind11_tests import custom_type_casters as m
def test_noconvert_args(msg):
a = m.ArgInspector()
assert (
msg(a.f("hi"))
== """
loading ArgInspector1 argument WITH conversion allowed. Argument value = hi
"""
)
assert... |
aac0daf18e050bd0ff819a5acf3208a9c7bd4818aff1fdc70521d9092b4c0ca5 | Python | 4,029 | 114 | """A06 capture-options truth: the ``module_filter`` third save gate is DISCLOSED.
WALKTHROUGH list-A row 10 (second clause): ``module_filter`` was a
doc-invisible third save gate whose argument is an op-record namespace, so
the natural nn.Module-shaped filter (``lambda m: isinstance(m, nn.Linear)``)
silently saved ZER... |
da0d7873e1937a6a2e2b811f650315defff399cab0c26bb971c7ff0f7b9574a1 | Python | 4,029 | 109 | """
Predict tool usage to weigh the predicted tools
"""
import os
import numpy as np
import warnings
import csv
import collections
from sklearn.svm import SVR
from sklearn.model_selection import GridSearchCV
from sklearn.pipeline import Pipeline
from scripts import utils
warnings.filterwarnings("ignore")
main_path... |
285c72a31f1f69ffd46db489305b9f7c03f64290f1edb6d1421c23f7b1deddf5 | Python | 4,032 | 122 | """
OIDC-specific utility functions for token handling and verification.
This module contains helper functions that are specific to OpenID Connect (OIDC)
authentication. These should not be used with non-OIDC backends like OAuth2.
"""
import logging
from typing import TYPE_CHECKING
import jwt
from social_core.backen... |
c6bc5c032909e0a0dd4043333e03f34e1747dea3c7602c24133229cb071fc1b2 | Python | 4,032 | 133 | # --- 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 Marker(_BaseTraceHierarchyType):
_parent_path_str = "splom.selected"
_pat... |
01bd07fbefacd2d63b28333a076607fae1cd073ec26af0b2a97cb20d795c1f4d | Python | 4,033 | 121 | # --- 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 Z(_BaseTraceHierarchyType):
_parent_path_str = "volume.caps"
_path_str = ... |
2cfd65571560c6884abcd37a56906bf3d64d84ecf7dcb6ac4e65dfb88b792cec | Python | 4,033 | 121 | # --- 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 X(_BaseTraceHierarchyType):
_parent_path_str = "volume.caps"
_path_str = ... |
70cfaccb17ace97f7fbf683803c63ab7da0085fc376259015e6cc4368605b0a1 | Python | 4,033 | 121 | # --- 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 Y(_BaseTraceHierarchyType):
_parent_path_str = "volume.caps"
_path_str = ... |
ae2a5cc8839eaa56550178ba3020fc41463d06e585cd7a367a4d4d1239e78860 | Python | 4,033 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "scattergl.marker.colorbar... |
cd602e93cd3614144ba8ba78940822eff0df76eeea22cff0eb4a5de6fdcb50a4 | Python | 4,033 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "histogram.marker.colorbar... |
e5139df38e797455c6d38a0caa1910fa298f2a69b5a3d24395f6f3d7817c9b43 | Python | 4,033 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "scatter3d.marker.colorbar... |
23e97d2f5bc7371c61f375bab891140ddfb16db0340254876d00571c925a092f | Python | 4,034 | 134 | # --- 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 Marker(_BaseTraceHierarchyType):
_parent_path_str = "funnelarea"
_path_st... |
f99def2323b8264a81322a4ab0fbe1ce6c658ed05d221242b25fccfbf112a81a | Python | 4,034 | 162 | # Adapted from https://github.com/facebookresearch/xformers/blob/main/xformers/triton/k_activations.py
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import math
from e... |
2b744a4e7dc8e0d6c7d61d914216f9cf4aad691bcc6eab180233423c7b366288 | Python | 4,035 | 107 | # load environment gnnEnv2
from moviepy.editor import *
import pickle
import numpy as np
from pathlib import Path
import pandas as pd
arg = sys.argv[1]
if arg == "genset":
out_path = './genset_media_trimmed' #videos trimmed to motion stop
in_path = './original_dataset_files/test' #original v... |
5ed871761708e54fb38b670be081c207d692b717b825e746651b06fd9d5a2e24 | Python | 4,035 | 89 | # 结论：当模型进行ensemble的时候性能会明显提升。
import json
import numpy as np
import os, sys
from collections import Counter
from sklearn import preprocessing
from sklearn.metrics import f1_score
from sklearn.metrics import confusion_matrix
import torch
from random import choice
from sklearn.metrics import cohen_kappa_score
from statsm... |
886001d8e21d06b81b36302b8d30af148205baeff6a3d8836c5a1e1c970cd4e4 | Python | 4,036 | 136 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Title(_BaseLayoutHierarchyType):
_parent_path_str = "layout.coloraxis.color... |
a4d427d5d33a4b8950bb3ff6680e1f8ac0e60327bc561a4995b3877820b76287 | Python | 4,036 | 120 | from argparse import ArgumentParser
import torch
from pytorch_lightning import LightningModule, Trainer, seed_everything
from torch.nn import functional as F
from pl_bolts.models.vision.unet import UNet
class SemSegment(LightningModule):
def __init__(
self,
lr: float = 0.01,
num_classes:... |
b15231100ee032a67c9f86555943e304fb4d74c67f1744d0eb321869015fb04d | Python | 4,036 | 112 | import copy
from typing import List, Tuple
import torch
from pytorch_lightning import LightningModule
from torch import Tensor
from torch.nn import Identity
from torchvision.models import resnet50
from lightly.loss import BarlowTwinsLoss
from lightly.models.modules import BarlowTwinsProjectionHead
from lightly.models... |
042ea20273c39d558e59bab743716800831dc86376516ae977095ed9026841dc | Python | 4,037 | 142 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 12 11:38:07 2020
@author: KEPetousakis
"""
from numpy import exp as exp
import numpy as np
from matplotlib import pyplot as plt
from random import randint
import matplotlib as mpl
import warnings
import logging
logging.getLogger('matplotlib.font_manager... |
19f7525f65058bec89ff555d37c41c5de392d448e6354d8a0bba1a5d46f429e4 | Python | 4,037 | 133 | # --- 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 Marker(_BaseTraceHierarchyType):
_parent_path_str = "violin.selected"
_pa... |
9ce56b71890494b7844916895013a5d73ecce62ef19e68648a4c6b5b63ccdb49 | Python | 4,037 | 133 | import math
from typing import List, Sequence, Tuple, Union
import numpy as np
import torch
from torch import Tensor
from pl_bolts.utils import _SKLEARN_AVAILABLE
from pl_bolts.utils.warnings import warn_missing_pkg
if _SKLEARN_AVAILABLE:
from sklearn.utils import shuffle as sk_shuffle
else: # pragma: no cover
... |
1d62089a3012825b9d6bf04aca786fc24d1fe267bc4564592509bb984a9896fd | Python | 4,038 | 137 | """
This module includes auxiliary support methods and data structures.
"""
from collections import namedtuple
import numpy as np
from numba import njit
from numpy import array as array_t
# Add documentation to the NamedTuple.
__pdoc__ = {}
# Module level declaration.
MetalAtom = namedtuple("MetalAtom",
... |
afeb8246212773fb299271104aed114778cc54691cef815ff48b6b404dd72dd6 | Python | 4,038 | 105 | import torch
import torch.nn as nn
from collections import OrderedDict
from torchinfo import summary
import numpy as np
def Conv2D(
in_channels: int, out_channels: int,
kernel_size: int, stride: int, padding: int,
is_seperable: bool = False, has_relu: bool = False,
has_sigmo... |
24c19cd07014a72f0d33e30a1bc072f934d10a0f1bede95c0e4b8b28a12a842b | Python | 4,040 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "scattermap.marker.colorba... |
6c08c9384e399d5729e5a67bfed8a89aba70942797563d47992e1e67dc8c5c85 | Python | 4,040 | 92 | import torch
import numpy as np
from sklearn.model_selection import train_test_split
from scDGD.classes import scDataset
def prepate_data(adata, label_column, train_fraction=0.8, include_test=True, scaling_type='max', batch_size=256, num_w=0):
'''
Prepares the pytorch data sets and loaders for training and tes... |
886b80b9f54a56e66e51452cbef80903d122a85a8d3fb98608920c9042773b29 | Python | 4,040 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "scattergeo.marker.colorba... |
fe354cdfca0a97cf6d15b9934a0de84c4e791660973d15f5ad4a3be720c14d7d | Python | 4,040 | 143 | """Tests for the specparam.models.time, including the time model object and it's methods.
NOTES
-----
The tests here are not strong tests for accuracy.
They serve rather as 'smoke tests', for if anything fails completely.
"""
import numpy as np
from specparam.sim import sim_spectrogram
from specparam.models.utils im... |
879be9d4eba7e49d6df67b6f7ebf4522abe083c69b345bebb73f6a1ea553b70d | Python | 4,041 | 103 | import numpy as np
import pytest
from conftest import basis_raw, dataset_config_factory, mock_database
from coeffnet.predata.matrices import TaskdocsToData
def test_TaskdocToData_minimal_basis_input(
mock_database, dataset_config_factory, basis_raw
):
"""Test the input of the TaskdocToData class."""
db =... |
71c08ca07d22868e47113e29cef09cf083b95e603b449eb522a0bb17aeb73466 | Python | 4,042 | 133 | # --- 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 Marker(_BaseTraceHierarchyType):
_parent_path_str = "scatter.selected"
_p... |
b92b89f67d92de5618193f11e41202c3cd1d4dd0b2f5720f30a23bf1c55b5e0b | Python | 4,042 | 120 | from keras.src.api_export import keras_export
from keras.src.layers.preprocessing.image_preprocessing.base_image_preprocessing_layer import ( # noqa: E501
BaseImagePreprocessingLayer,
)
@keras_export("keras.layers.MaxNumBoundingBoxes")
class MaxNumBoundingBoxes(BaseImagePreprocessingLayer):
"""Ensure the max... |
ec10ada7e64e08b4da19067e894153230caf8b4202fe5f7d0102b756e1620d26 | Python | 4,042 | 125 | from typing import List, Any
from pathlib import Path
import os
import argparse
import numpy as np
from ase import build as ase_build
from ase import io as ase_io
from pymatgen.core.structure import Molecule
from pymatgen.io.ase import AseAtomsAdaptor
from pymatgen.core.operations import SymmOp
from minimal_basi... |
55b88dd169d9e9e903db007b4b207330e6f150fa111df250774d5436129a6aac | Python | 4,043 | 103 | """Registry of most widely used datasets"""
import os
import shutil
import tarfile
import zipfile
from ...data import VOCDetection, COCODetection
from ...utils import download as _download, makedirs
__all__ = ['get_dataset', 'list_dataset']
_DATASETS = {}
def list_dataset():
"""List available dataset registered... |
57cf6b5445e3b2466df35c79c26a70b4da6af9da855f38243ec5c64adfd1f4a1 | Python | 4,043 | 119 | import gzip
import os
from helixfold.data import mmcif_parsing
from helixfold.data import parsers
from helixfold.common.protein import PDB_CHAIN_IDS
def traverse_until_valid_res(info, res_index) -> int:
# NOTE: id of `info` starts from 0, while res_index
# starts from 1.
while res_index - 1 < len(info) a... |
5dc84e90d280c040658f28db857189ccbb9ee4b60018100e711201f706e14e2b | Python | 4,044 | 161 | """Credit-required lint (workstream D01 gate).
The acknowledgments page (docs/acknowledgments.md) is the assembled credit
roster from every design memo's CREDIT section. The convert-memo maintenance
rule: any change landing a borrowed idea adds or extends a row on that page
in the same change. This lint is the mechani... |
85fdfbb384e13c688d74afdeadbbf8a7bb7bd994e1cafb6e7290214db01f602b | Python | 4,045 | 107 | """grind-r3 T-CACHES: RF schema-operand-slot cache bounds and fail-closed lookup.
Round-2 F39-4a: the unbounded-negative-entry leak was fixed by NOT caching
``None``, which converted every unrecognized func name (loaded traces, custom
ops, non-aten labels) into an unbounded RE-computation -- torch does not
memoize a f... |
af9b4e72ffd4917e56a51f48bbeae9be40e7809ed9588646b0e435b95b043081 | Python | 4,045 | 136 | import numpy as np
import pytest
import gym
from gym import spaces
from gym.envs.registration import EnvSpec
from tests.envs.utils import all_testing_initialised_envs, mujoco_testing_env_specs
@pytest.mark.parametrize(
"env_spec",
mujoco_testing_env_specs,
ids=[env_spec.id for env_spec in mujoco_testing_... |
ba5b6ad22c505dee6b5e3c6190e9a3d82b3085b0833c293f07b7a87b2bb8c6d8 | Python | 4,046 | 95 | # SOURCE: vendored from PufferAI/PufferLib @ 4.0 (tests/test_nmmo3_encoder.py)
#
# `NMMO3EncoderRef` is the real PyTorch reference observation encoder for PufferLib's
# Neural MMO 3 baseline (`ocean/nmmo3`), used in `tests/test_nmmo3_encoder.py` as the
# ground-truth numerical reference that PufferLib's fused CUDA `oce... |
6eded46b7325bcb428264f522c7c622796aa86b26b4c3b1f720d702811c8da08 | Python | 4,047 | 75 | """General-purpose test script for image-to-image translation.
Once you have trained your model with train.py, you can use this script to test the model.
It will load a saved model from --checkpoints_dir and save the results to --results_dir.
It first creates model and dataset given the option. It will hard-code some... |
8ca3e80d0ca83a88e4d30c378615f65e91e60001a9460126f85f6dfcb9bb1586 | Python | 4,047 | 142 | import os
import sys
from pathlib import Path
import logging
import numpy as np
import tracemalloc
import argparse
import snapatac2 as sa2
import pyprojroot
code_root_dir = str(pyprojroot.here())
pack_dir = f"{code_root_dir}/package/python"
sys.path.insert(0, pack_dir)
import utils # type: ignore # noqa: E402
parser... |
d7995221c88cdd855d100a1288ce659f7f027e6e523ffeee332e165f07b8b2b3 | Python | 4,047 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "histogram2dcontour.colorb... |
fa4a71083d97d3c9b02b782c7cbe3288eb1f4a278288b1c7987d46481580242a | Python | 4,047 | 126 | from abc import ABC, abstractmethod
import os
import attr
from matplotlib import pyplot as plt
import numpy as np
class SLPD(ABC):
"""
Splicing length pattern distribution. Represents the distribution of
splicing length patterns (i.e. the lengths of the exons and introns
in a splicing pattern... |
4142d86746092754bce339ee343ede990e77965c9470af2197105b98c49bf17d | Python | 4,048 | 87 | import torch
from torch import nn
from torch import Tensor
from collections import OrderedDict
import numpy as np
class GetDensity(torch.nn.Module):
def __init__(self,rs,inta,cutoff,nipsin,norbit,ocmod_list):
super(GetDensity,self).__init__()
'''
rs: tensor[ntype,nwave] float
inta:... |
d419ad153cbd0f34c0cdb98557223a3d2dbb965818d274c32e3017fdc02a6040 | Python | 4,048 | 121 | from __future__ import print_function, division, absolute_import
import torch
import torch.nn as nn
from torch.autograd import Variable
#from torch.legacy import nn as nnl
import torch.utils.model_zoo as model_zoo
__all__ = ['vggm']
pretrained_settings = {
'vggm': {
'imagenet': {
'url': 'http:... |
d8026e3c8fc31cce53f480e0713c1fd04f2cbb21c01677ec7aca20af4001ed14 | Python | 4,048 | 110 | """Nicer log formatting with colours.
Code copied from Tornado, Apache licensed.
"""
# Copyright 2012 Facebook
#
# 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/licen... |
9a468494dc34dbe79b5aefd381f183785f547bcd4e3b3794cb12f3ecbdbddfe6 | Python | 4,049 | 75 | # !/usr/bin/env python
## created by Yun Hao @MooreLab 2021
## This script learns and evaluates DTox model
## Module
import sys
import torch
import numpy as np
import pandas as pd
sys.path.insert(0, 'code/')
import dtox_data
import dtox_learning
## This function implements DTox model training
def dtox(dtox_combin... |
42861fa47abf7375d8f7c088b45bf66be04b3616350fe02dd44dd312dcf046a2 | Python | 4,050 | 136 | """Adaptive input representations for neural language modeling.
Paper: "Adaptive Input Representations for Neural Language Modeling",
Baevski and Auli, ICLR 2019.
The architecture factorizes token input embeddings by frequency bucket: frequent
words receive full-width embeddings, while progressively rarer buckets use... |
465d947d9e86bbb60a8743d04d8d167d42d2c08df1bbc53796e6d4537d04b24d | Python | 4,051 | 84 | import os, argparse
import pandas as pd
import subprocess
import pickle
# Module rnaprot/rplib.py
from rnaprot.rplib import bed_overlap_with_genomic_features, gtf_extract_transcript_bed, gtf_get_transcript_ids, bed_get_transcript_annotations_from_gtf, bed_get_exon_intron_annotations_from_gtf, gtf_extract_most_prominen... |
83fcaa38d97145cb36c381039389846e64053011f0bf01ee3b4d0135ece7cc54 | Python | 4,051 | 103 |
import unittest
from command_utils import load_arguments
import os
import bleualign
import io
from bleualign.align import Aligner
from test.utils import Utils
class TestByEvalFilter(unittest.TestCase, Utils):
def setUp(self):
pass
def test_originalFileName(self):
self.main_test('fileNameOptions')
def test_fil... |
dc3146e2934f2d6d5acdbdda5f298cc5037dc293f8c2b4649d1bebe1fff4f02f | Python | 4,051 | 104 | """hd256 forward + backward on SM100/SM110 against FP64 eager, dense and varlen.
Shapes sit on the 128-row tile edges (127/128/129), a partial last tile (1000), a long
sequence (4096) and Q/K length mismatches in both directions, for MHA and 24/4 GQA, causal
and non-causal. The features the hd256 backward does not sup... |
70e05d7468fcebca52a94abcb5bec85efd6258ed3a40a05eaf93db75108babf6 | Python | 4,052 | 133 | # --- 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 Marker(_BaseTraceHierarchyType):
_parent_path_str = "scattergl.selected"
... |
b065c5de953db059fd91d925792b87feaa8e5b4c508b4197883b065c00e60893 | Python | 4,052 | 133 | """interactive plotting from https://stackoverflow.com/a/31417070/5407682"""
import colorsys
import math
from typing import List
import numpy
import numpy as np
from matplotlib import pyplot as plt, colors as mc
def make_interactive_legend(ax=None):
if ax is None:
ax = plt.gca()
if ax.legend_ is None... |
bf43400f0a648fb7ff23e631134bfdde8a666e489183714360e916574682e58f | Python | 4,053 | 102 | """
======================================================================
Classification accuracy vs class distinctiveness vs class separability
======================================================================
Generate several datasets containing data points from two-classes. Each class
is generated with a Riem... |
c6286711e514c3851333508c4541156862efefd10bd4975291e5d7f8c6a96d95 | Python | 4,054 | 109 | """
Manages active plugins. Load and access plugins.
SimplyFire - Customizable analysis of electrophysiology data
Copyright (C) 2022 Megumi Mori
This program comes with ABSOLUTELY NO WARRANTY
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as p... |
d3e79345b8263d35d7ed35870d720f72a3c337b2bf53311d22c9ce6064a02361 | Python | 4,054 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "scatterpolar.marker.color... |
e6a1cc934ad36067bc28df51d8fd1ebccf914887e8804feebc8c3e143e7b6cfd | Python | 4,054 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "scattersmith.marker.color... |
451396310a26d2471d951dd7f5299e23064e89034b4e6b7e260518015794285f | Python | 4,055 | 105 | """
#--------------------
Created on 2021.11.05
Version 1.0
__author__ = 'Xx'
#--------------------
"""
'''
Description:
Routine for determining the level of confidence of a particular clear sky test. Input two threshold values
('midpt') with associated confidence limits ('locut', 'hicut') whic... |
a945f7731a3e26173592d894bcacbd80f6f80c710eba43c9506737fb6ed90692 | Python | 4,055 | 123 | """
RSA statistics.
"""
import os
import mne
import numpy as np
from mne import spatial_src_adjacency
from mne.stats import (spatio_temporal_cluster_1samp_test)
import scipy.io
import argparse
import sys
from config import fname
from pathlib import Path
# Be verbose
mne.set_log_level('INFO')
# Handle command line a... |
cdf836be034661504a2435078815cee9c5731de72e3d642eafb36c05d33d0372 | Python | 4,055 | 159 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Pad(_BaseLayoutHierarchyType):
_parent_path_str = "layout.slider"
_path... |
77cd2b93334376ddaa5cbe58d1f85d91cebc3b3cd8d77c61ff11677df14ce1e8 | Python | 4,056 | 104 | #!/usr/bin/env python3
from htmd.ui import Molecule
from moleculekit.tools.atomtyper import prepareProteinForAtomtyping
from moleculekit.tools.voxeldescriptors import getVoxelDescriptors, getCenters
from argparse import ArgumentParser
def parse_cmd():
"""Parse command-line arguments.
Returns
-------
... |
af434fb7a6e3a73320cda876f398aa75cd825723743ae6d4f38502b42011e231 | Python | 4,056 | 128 | import os
import re
from matplotlib import pyplot as plt
import numpy as np
from permacache import permacache
from modular_splicing.models_for_testing.load_model_for_testing import step_for_density
from modular_splicing.utils.io import load_model, model_steps
from modular_splicing.motif_perturbations.summarize_effe... |
25c522f70c3233036844f63f8a112fbc8d6fd0be3e0bd5a2fd77bdb3db9f908c | Python | 4,057 | 118 | """
===============================================================================
Robust covariance estimation
===============================================================================
Comparison of robustness of different covariance estimators on a corrupted
low-dimensional dataset. See also [1]_.
"""
# Autho... |
676bf48dcb11a6e0003e606067174bd4ace292225f300b6f977be942dde8859f | Python | 4,057 | 119 | """
Module responsible for data augmentation constants and configuration.
"""
import torch as ch
from torchvision import transforms
from .audio_functions import audio_transforms
# lighting transform
# https://git.io/fhBOc
IMAGENET_PCA = {
'eigval':ch.Tensor([0.2175, 0.0188, 0.0045]),
'eigvec':ch.Tensor([
... |
a51b1c24aff1d05444a3a22afefed83dce0cc830aa6b2429a1255fc69ff29c3e | Python | 4,057 | 133 | # --- 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 Marker(_BaseTraceHierarchyType):
_parent_path_str = "scattermap.selected"
... |
d92ab717c7b07873b4b98c3593abbd19bdd9b5693ecbff27841b76db554bc17c | Python | 4,057 | 133 | # --- 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 Marker(_BaseTraceHierarchyType):
_parent_path_str = "scattergeo.selected"
... |
2f1365449c9578ebbb013df386b19914618cbd2a7f6720151c8ba439e69c680d | Python | 4,058 | 110 | """Accuracy metric for heatmap prediction."""
# pylint: disable=assignment-from-no-return
import numpy as np
try:
from mxnet.metric import EvalMetric, check_label_shapes
except ImportError:
from mxnet.gluon.metric import EvalMetric, check_label_shapes
class HeatmapAccuracy(EvalMetric):
"""Computes heatmap... |
037ab96f0d74a0075f2213f95330660403aca0dbfd61d3b090f37a4870c2222c | Python | 4,059 | 125 | """Visualize image."""
import numpy as np
try:
import mxnet as mx
except ImportError:
mx = None
def plot_image(img, ax=None, reverse_rgb=False):
"""Visualize image.
Parameters
----------
img : numpy.ndarray or mxnet.nd.NDArray
Image with shape `H, W, 3`.
ax : matplotlib axes, optio... |
0c8b2d3c718cc1750d0868de2614675b895dd642bfb58d592a68e4469916aa6b | Python | 4,059 | 127 | """Plenoxels radiance-field renderer in torch tensor form.
Fridovich-Keil et al. (CVPR 2022), "Plenoxels: Radiance Fields without Neural
Networks." Plenoxels represent a scene as an explicit sparse voxel grid of
density and spherical-harmonic color coefficients, then render rays by
trilinear interpolation and differe... |
c56fc59b02cab26cbc365245ec5dd4d7362a498606e8d329da2c62ad53bf8386 | Python | 4,059 | 197 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
# disable tensorflow warnings
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import tensorflow as tf
# constant values
from .constants import CRLF
from .constants import IMG_SIZE
from .constants import RESET_COLOR_CODE
from .constants import GREEN_COLOR_CODE
__autho... |
e7cdc0d2332d2abc973e68b4c8df4d38d559d739a59a35d119a3023c58266d5e | Python | 4,059 | 101 | # SOURCE: vendored from bigict/ProDESIGN-LE @ f9a9ba1 (main)
# File: pe/model/modules.py
# ProDESIGN-LE: local-environment-aware transformer for protein sequence design.
# `design.py` (repo root) constructs the real trainable network as
# `modules.Transformer(46, num_class, 256, nhead=16, nlayer=3, device=...)` -- a pl... |
6ed7c9e20ba89fe9e3fc8e8e17d81d013cf4b6e2982a7ffc11f66cc41560f01d | Python | 4,060 | 128 | from pathlib import Path
import pandas as pd
from anndata import AnnData
from pandas import DataFrame
def row_annotations(
adata: AnnData,
annotations: pd.DataFrame | str | Path,
join_column: str | None = None,
columns: list[str] | None = None,
copy: bool = False,
) -> AnnData | None:
"""\
... |
4b5f7356e3e386b10af367fe78f2164281810327093046dfdde87f0dd68f1941 | Python | 4,061 | 105 | from typing import Optional
import numpy as np
from brian2 import Quantity, meter
def generate_circle_locations(n, radius, rng):
if isinstance(radius, Quantity):
radius /= meter
loc = np.zeros((n, 2))
mask = np.ones(n, bool)
while mask.sum() > 0:
loc[mask] = rng.uniform(-radius, radius... |
914fdd2e3fba220e2fb3212aaefd312b304edf3029ccde17089a8fc6aadec108 | Python | 4,061 | 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 Title(_BaseTraceHierarchyType):
_parent_path_str = "scattercarpet.marker.colo... |
cc6b07819e50dff725701acb5acf49a8141922b537bf88df2c57a00fb64195b5 | Python | 4,061 | 186 | #!/usr/bin/env python
# coding: utf-8
# # General setup
# In[7]:
import os, sys, subprocess
import time
from glob import glob
import itertools
from functools import partial
import copy
import gc
import importlib
sys.path.insert(1, os.path.realpath('lib'))
if "utils" not in sys.modules: import utils
else: importlib... |
0b04809fdeb9072d4649dff306a2cdf16a0963ad214951f294a0338584569c85 | Python | 4,062 | 151 | import logomaker
import pandas as pd
import numpy as np
from tqdm.auto import tqdm
def plot_logo(
df,
threshold,
ax,
color_map={"A": "#00dc33", "C": "#1c1cd5", "G": "#f2a93c", "U": "#ff1525"},
nts=["A", "C", "G", "U"],
):
current_df = df.query(f"activation > {threshold}")
if len(current_d... |
32d9ccee301fbd1072c7d57f5aeaff03e6377043b7e18cf83be569f1aaca7a3f | Python | 4,062 | 111 | """Test cases for lane.py."""
import os
import unittest
import numpy as np
from scalabel.common.typing import NDArrayF64, NDArrayU8
from bdd100k.common.utils import list_files
from bdd100k.eval.lane import (
eval_lane_per_threshold,
evaluate_lane_marking,
get_foreground,
get_lane_class,
sub_task_f... |
bc178742c219099cdd62ca120d71d6dc099b722648dfbb57c3de3059e2358496 | Python | 4,062 | 122 | """Functions to analyze and investigate model fit results, in terms of model fit error."""
import numpy as np
from specparam.sim.gen import gen_model
from specparam.plts.error import plot_spectral_error
from specparam.modutils.errors import NoModelError, NoDataError
##################################################... |
0eb101bc65afdc38148f0c8ebab7aa54048b5c5350c01d92918bf148d25906d4 | Python | 4,064 | 130 | """
Functions written by other researchers.
"""
import numpy as np
import mne
from scipy.linalg import eig
def _get_global_reject_epochs(raw, decim):
"""
Author: Denis Engemann <denis.engemann@gmail.com>
Computes the threshold for global rejection of epochs based on the amplitude
Parameters
_____... |
2dc9d78d51b8317b1fc5fe743abc7e8065b73caae495187cd0a4f51162bbf7b4 | Python | 4,065 | 122 | # --- 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 Y(_BaseTraceHierarchyType):
_parent_path_str = "isosurface.caps"
_path_st... |
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