sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
37ddc24920dee6d4a19339fe26ef2644e0906653042687a7aace2e992fda7bc1 | Python | 21,899 | 558 | """CSPNeXt (RTMDet / OpenMMLab)
CSPNeXt backbone from RTMDet (OpenMMLab), ImageNet-1k classification models.
Papers:
* `RTMDet: An Empirical Study of Designing Real-Time Object Detectors` - https://arxiv.org/abs/2212.07784
The paper describes this backbone (CSP blocks with 5x5 depthwise convs) without naming... |
e988ae1438d08a13980ff7d8dd7ee3b819a25a2235b262a6dcc7698e4c4afa94 | Python | 21,942 | 451 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import re
import os
import warnings
from matplotlib.ticker import FormatStrFormatter
from activation_utils import compute_mean_digit_separations_domainIL, compute_mean_digit_separation_classIL, get_distances
def preprocess_performance_data(results,... |
580583f42b6d85e4ddc2368f5a13f523ae2025d19eedbcff9b37413e0dd7637c | Python | 21,956 | 568 | """Base classes for PTSA readers."""
from __future__ import annotations
import sys
import os
from os.path import join
import re
import json
import unicodedata
from collections import defaultdict
import warnings
from abc import abstractmethod
from typing import Any, Dict, List, Optional, Sequence, Tuple, Union, cast
... |
be9b7613d1fef4449bb059eb2645a6ffb21fba72eb61bde3a5367b8a381d7d99 | Python | 22,009 | 441 | # Fundamental libraries
import os
import sys
import time
import glob
import copy
import random
import datetime
import warnings
import itertools
import numpy as np
import pandas as pd
import pickle as cp
import seaborn as sns
import multiprocessing
from scipy import stats
from pathlib import Path
from ast import literal... |
3ee1977e11953ae299621691a72d3c95e132b98bc4eae3cd9d5697fac0e4b36c | Python | 22,017 | 692 | import io
import os.path
import h5py
import numpy
import numpy.random
import numpy.testing
import pytest
import skimage.data
import skimage.util
import cellprofiler_core.image
import cellprofiler.modules.saveimages
import cellprofiler_core.pipeline
import cellprofiler_core.setting
import cellprofiler_core.preferences... |
945743224ded3de55a1a2976866c1ab0e19b30adb9427acff9e1bd131fd5d51f | Python | 22,047 | 699 | """Plot figures for report."""
import matplotlib as mpl
import matplotlib.colors as mcolors
import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import plotly.express as px
from nilearn import datasets
from nilearn.plotting import (
plot_glass_brain,
plot... |
36e387c20f5e95e88a7d1d4234c12d741127a406ed04f910808f82122ac838a5 | Python | 22,064 | 514 | import pyb
from array import array
from . import framework as fw
from .utility import randint
# Ring buffer -----------------------------------------------------------------
class Ring_buffer():
# Ring buffer for storing data from interrupt service routines.
def __init__(self, buffer_length=20):
... |
62884d23e351f61ec163b971375b463c4b0360b2e743abbcf3c4bdf3b1803ce3 | Python | 22,130 | 526 | import csv
import os
import sys
import tempfile
import click
import matplotlib.pyplot as plt
import pandas as pd
from sklearn import preprocessing
from sklearn.metrics import silhouette_score
from sklearn.mixture import GaussianMixture
from nidm.experiment.Query import GetProjectsUUID
from nidm.experiment.tools.click_b... |
f8318a694f09f753ab42f8e83dd2ea1cf866b57ce7228c4ada8c503c1f2ad5bf | Python | 22,168 | 521 | import io
import logging
import sys
import time
import traceback
import zmq
from ._pipeline_event_listener import PipelineEventListener
from ..analysis.reply import ImageSetSuccess, ServerExited
from ..analysis.reply import ImageSetSuccessWithDictionary
from ..analysis.reply import NoWork
from ..analysis.request impo... |
1a27f45fbbec7c88a14d6bf3afdf34c4ff3391f564d20e0737116621567cdf1c | Python | 22,198 | 419 | import numpy as np
import time
import nengo
import sys, os
import argparse
sys.path.insert(1, os.path.dirname(os.getcwd()))
#os.chdir("..")
import sspslam
from sspslam.networks import get_slam_input_functions, get_slam_input_functions2
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.animation import ... |
5d5a97498180f2a48b9b1ebb69069e15848b8429deaf7ba4dcbdabc5d112b6c7 | Python | 22,300 | 583 | """
RDNet
Papers:
* `DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs` - https://arxiv.org/abs/2403.19588
Copyright (c) 2024-present NAVER Cloud Corp.
Apache-2.0
"""
from functools import partial
from typing import List, Optional, Tuple, Union, Callable, Type
import torch
import torch.nn as nn
import torc... |
79453f1767ddb347a230e331e699b81638fe3a4a6997d0c2f4986879da3cf101 | Python | 22,329 | 709 | """ RepViT
Papers:
* `RepViT: Revisiting Mobile CNN From ViT Perspective` - https://arxiv.org/abs/2307.09283
@misc{wang2023repvit,
title={RepViT: Revisiting Mobile CNN From ViT Perspective},
author={Ao Wang and Hui Chen and Zijia Lin and Hengjun Pu and Guiguang Ding},
year={2023},
eprint={2307... |
cd3d871cfe57962e9ce30e134ccd60d217ad8d6460f09f534992c920cd492281 | Python | 22,341 | 651 | """
pysteps.nowcasts.utils
======================
Module with common utilities used by nowcasts methods.
.. autosummary::
:toctree: ../generated/
binned_timesteps
compute_dilated_mask
compute_percentile_mask
nowcast_main_loop
print_ar_params
print_corrcoefs
stack_cascades
"""
import ... |
a31f6e89b2e6cff16ab0cb54f854110372060c54725240cb8f4733e0c6bde028 | Python | 22,347 | 487 | """
Author: Mingjian He <mh1@stanford.edu>
arn module contains autoregressive model of order n methods used in SOMATA
"""
from somata.basic_models import StateSpaceModel as Ssm
from somata.exact_inference import inverse
import numpy as np
import numbers
from scipy.linalg import block_diag
class AutoRegModel(Ssm):
... |
ebb20eb53fcaf00a388595fc22afae003dcabd1df6042ca85a4ffe850bc83e6c | Python | 22,367 | 706 | from base64 import b64decode
from collections import namedtuple
from io import BytesIO
from typing import (
TYPE_CHECKING,
Any,
Callable,
Hashable,
Iterable,
Literal,
Mapping,
Optional,
Sequence,
Type,
Union,
)
import json
import time
import warnings
import numpy.typing as n... |
5d83c8b4317d89946866ae7d5ef4f61075f1ca9ef74cd4cb441a513706429c62 | Python | 22,377 | 651 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
a7cef90a7deffff8d544d149698ec4022f848a2377bf7928e6287e9beaf760ba | Python | 22,391 | 636 | import io
import os
import numpy
import skimage.io
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler_core.modules.injectimage
import cellprofiler.modules.measureobjectsizeshape
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspace
fro... |
e2685250d33ff5ed82eb96f755b6e84298498f31fe1789987baee6c9baea6cbf | Python | 22,419 | 627 | """
ImageMath
=========
**ImageMath** performs simple mathematical operations on image
intensities.
This module can perform addition, subtraction, multiplication, division,
or averaging of two or more image intensities, as well as inversion, log
transform, or scaling by a constant for individual image intensities.
K... |
4106afee1154ac6d683a426063d0b6f61d19fe38994d38dcf8af0f8b9c37ebb9 | Python | 22,422 | 638 | # pylint: disable=too-many-locals, too-many-arguments
# pylint: disable=too-many-branches, too-many-statements
"""Training Library containing training routines."""
import copy
import os
import weakref
from typing import (
TYPE_CHECKING,
Any,
Dict,
Iterable,
List,
Optional,
Sequence,
Tup... |
8d69a41cdbe8c8865b804ba11823639b46973f22538feb9329aa51c6b675297e | Python | 22,462 | 624 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 26 11:56:59 2019
@author: Nikolai M Chapochnikov
This plots the plots related to the simulation of the model on
artificial datasets, to understand its functioning
the external files are that used are:
data_i = 3
f'dataset{data_i}/dataset_{D}D_{n_c... |
9e949dc4a4972a0a2a76eb459d51775f4701a3cc67215ab9147a4b1d4ab0fb84 | Python | 22,464 | 524 | import os
import pathlib
from typing import Optional, Tuple, Union
import numpy as np
import pandas as pd
import SimpleITK as sitk
import torch
from torch.utils.data import DataLoader
import torchio
from GANDLF.compute.loss_and_metric import get_loss_and_metrics
from GANDLF.compute.step import step
from GANDLF.data.po... |
52809e20524abb0558bfd8810a7b1f3404cd7dd8ea113ccdab78be593e7a8975 | Python | 22,499 | 588 | import random
import re
import numpy as np
import pandas as pd
import torch
from torch.utils.data import Dataset
from sklearn.model_selection import KFold, train_test_split
import scanpy as sc
import scipy
import anndata as annd
from tqdm.auto import tqdm
from scipy.stats import pearsonr, spearmanr
def get_expression... |
343a04ae678c7480585770f0fbb9ded0b7ab0347aed6f682aa08a10a4d7e4699 | Python | 22,524 | 659 | """ Sequencer
Papers:
* `Sequencer: Deep LSTM for Image Classification` - https://arxiv.org/abs/2205.01972
"""
# Copyright (c) 2022. Yuki Tatsunami
# Licensed under the Apache License, Version 2.0 (the "License");
import math
from functools import partial
from itertools import accumulate
from typing import List, O... |
79ac4ddee086eec6f4b9f1e7d5b9640f4c16f0d4cb27294c17a63058e9c2c633 | Python | 22,550 | 530 | """ Loader Factory, Fast Collate, CUDA Prefetcher
Prefetcher and Fast Collate inspired by NVIDIA APEX example at
https://github.com/NVIDIA/apex/commit/d5e2bb4bdeedd27b1dfaf5bb2b24d6c000dee9be#diff-cf86c282ff7fba81fad27a559379d5bf
Hacked together by / Copyright 2019, Ross Wightman
"""
import logging
import random
from... |
70401b022e197c46bad1050e12bc20f4f8089185a313f26a62f60d1b719a2b15 | Python | 22,552 | 553 | import os
import sys
import matplotlib.cm
import wx
import wx.lib.scrolledpanel
from cellprofiler_core.preferences import ALWAYS_CONTINUE_HELP
from cellprofiler_core.preferences import export_to_json
from cellprofiler_core.preferences import CONSERVE_MEMORY_HELP
from cellprofiler_core.preferences import DEFAULT_COLORM... |
571f21cd2c2df48e690e4f5c92796aa5d77755c2de1f0270c12ee9eac9905845 | Python | 22,573 | 504 | """
Name:
shub_s1_s2_download_workflow.py
Description - short:
This Python workflow prepares Sentinel-1 and Sentinel-2 layer stacks described in the article "Machine
learning-ready remote sensing data for Maya archaeology" by Kokalj et al. (2023).
Sentinel Hub is used as a source for Sentinel-1 an... |
bfafb4987f885c23f08819057ec9570ef0475d36f50c2c617a21442115369998 | Python | 22,578 | 502 | """
Relief Visualization Toolbox – Visualization Functions
Contains functions to save visualizations tile by tile.
Credits:
Žiga Kokalj (ziga.kokalj@zrc-sazu.si)
Krištof Oštir (kristof.ostir@fgg.uni-lj.si)
Klemen Zakšek
Peter Pehani
Klemen Čotar
Maja Somrak
Žiga Maroh
Nejc Čož
Copyrig... |
b86aa336ac92743c4ae9f88aac587861ce7c9cdfb0e93c2c2e669b52609744b6 | Python | 22,591 | 693 | """Tests for dask shared by different test modules."""
from __future__ import annotations
import json
from collections.abc import Generator
from contextlib import contextmanager
from typing import TYPE_CHECKING, Any, List, Literal, Tuple, Type, Union, cast, overload
from unittest.mock import patch
import numpy as np... |
4bd55e55a4cc7980d4566ed3f549a3ad2481401bcd2c84de765393b7447774ea | Python | 22,623 | 604 | import torch
from torch.autograd import Variable
import torch.nn.functional as F
from torch.utils import data
from torch.utils.data import SequentialSampler
from torch import nn
from tqdm import tqdm
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from time import time
from sklearn.metrics impo... |
9ed115423749d1e980f59e720b7f1f115f46486db0a000464e77e4fee2896200 | Python | 22,648 | 622 | """Pytorch impl of Aligned Xception 41, 65, 71
This is a correct, from scratch impl of Aligned Xception (Deeplab) models compatible with TF weights at
https://github.com/tensorflow/models/blob/master/research/deeplab/g3doc/model_zoo.md
Papers:
* `Xception: Deep Learning with Depthwise Separable Convolutions` - https:... |
b6b205801f61e9cef884767b789472a8ae2c6627f1a0f2700c532c55fc6c13c9 | Python | 22,662 | 699 | import numpy as np
from numpy import linalg as LA
import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd
import os, re
import tensorflow as tf
import logomaker
from joblib import dump, load
from sklearn.cluster import KMeans, DBSCAN
# from sklearn.mixture import GaussianMixture
from sklearn.ens... |
a085c5dc557f90716ab0cfa8644c866e9cd033698a0ae342c7c159d56e75596a | Python | 22,676 | 595 | """ Transformer in Transformer (TNT) in PyTorch
A PyTorch implement of TNT as described in:
* `Transformer in Transformer` - https://arxiv.org/abs/2103.00112
The official mindspore code is released and available at
https://gitee.com/mindspore/mindspore/tree/master/model_zoo/research/cv/TNT
The official pytorch code ... |
2bb7820f6412a533235b4e52ed47a4c61bbe24d39d6e42b4b1be9518ccccd067 | Python | 22,685 | 713 | """empty message
Revision ID: 11230bf660dc
Revises: d0a243e71ea2
Create Date: 2021-07-21 15:27:03.443079
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "11230bf660dc"
down_revision = "d0a243e71ea2"
branch_labels = None... |
5f8895eb41a5a53112e83ccdf0e2b153bd0e6f8bd0e6680991779f5f98c66b34 | Python | 22,685 | 531 | from cellprofiler_core.constants.module import HELP_ON_MEASURING_DISTANCES
from cellprofiler_core.setting.choice import Choice
from cellprofiler_core.setting.subscriber import LabelSubscriber, GridSubscriber
from cellprofiler_core.setting.text import LabelName, Integer
from cellprofiler_core.utilities.core.module.ident... |
97709000c2c1b05a6af4bdbe8093e5d04126916f1c0b36aecd09dc3081092cd6 | Python | 22,687 | 658 | # -*- coding: utf-8 -*-
"""
@author: Nikolai M Chapochnikov
"""
# #############################################################################
# ################################# IMPORTS ###################################
# #############################################################################
import numpy a... |
f1659a12788f6edf59f333ffbf33f20875e37fd4cc90f172777bf7020ca972be | Python | 22,720 | 602 | """
DisplayDataOnImage
==================
**DisplayDataOnImage** produces an image with measured data on top of
identified objects.
This module displays either a single image measurement on an image of
your choosing, or one object measurement per object on top of every
object in an image. The display itself is an ima... |
f27f4cd5deaa5aa464c2d814dde68a7b96691a7a5edb93cca2bf022f8df86bf7 | Python | 22,756 | 577 | """
pnasnet5large implementation grabbed from Cadene's pretrained models
Additional credit to https://github.com/creafz
https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/pnasnet.py
Papers:
* `Progressive Neural Architecture Search` - https://arxiv.org/abs/1712.00559
"""
f... |
46608083cc87e8324a4f187919d1ce18d044ba9cbadabdea7d656daeafb4b1f5 | Python | 22,768 | 537 | """ Transforms Factory
Factory methods for building image transforms for use with TIMM (PyTorch Image Models)
Hacked together by / Copyright 2019, Ross Wightman
"""
import math
from typing import Optional, Tuple, Union
import torch
from torchvision import transforms
from timm.data.constants import IMAGENET_DEFAULT_M... |
ef472122d8e86b7b2ad6ba6b5016f614fb66acb7c221d244a642101c48dc7a9a | Python | 22,798 | 614 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
8fb0ebfc4bba80a58986cbf5dbadfd462e4dde46bd27a920418f87d375396dd3 | Python | 22,840 | 631 | import skimage
import cellprofiler_core.object
from cellprofiler_core.module.image_segmentation import ImageSegmentation
from cellprofiler_core.setting import Binary, StructuringElement
from cellprofiler_core.setting.choice import Choice
from cellprofiler_core.setting.subscriber import ImageSubscriber
from cellprofile... |
80ae9c019c77218ece12d4a89d6e78ea5262efdbb5e45094d7126c5cb5978021 | Python | 22,852 | 405 | #####################
# https://github.com/deepmind/surface-distance
#######################
# Copyright 2018 Google Inc. 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 a... |
c142dbaa1a99694ee6f3d048440d265ed0067497565e8e654833a73a1df69fba | Python | 22,904 | 592 | """
Morph
=====
**Morph** performs low-level morphological operations on binary or
grayscale images.
This module performs a series of morphological operations on a binary
image or grayscale image, resulting in an image of the same type. Many
require some image processing knowledge to understand how best to use
these ... |
41509634e1ecbd5210f149fa54aef71541d21bc501baff33a5208a40c348ce85 | Python | 22,970 | 508 | # -*- coding: utf-8 -*-
import torch
import torch.nn as nn
from torch.nn.parameter import Parameter
import function
import numpy as np
from module import FA_wrapper, TrainingHook
spike_args = {}
class NetworkBuilder(nn.Module):
def __init__(self, topology, input_size, input_channels, label_featur... |
20780e630aaaa1a8ea7db6ba4466dd2d68370fbefa8bb9fd15ee25e02656e609 | Python | 22,976 | 576 | """ ADOPT PyTorch Optimizer
ADOPT: Modified Adam Can Converge with Any β2 with the Optimal Rate: https://arxiv.org/abs/2411.02853
Modified for reduced dependencies on PyTorch internals from original at: https://github.com/iShohei220/adopt
@inproceedings{taniguchi2024adopt,
author={Taniguchi, Shohei and Harada, Keno... |
2d47b1039c7d21a536c435700fc7aafc834dc4935d73457ff56a4cb40e12e740 | Python | 23,113 | 485 | """
Conditional Wasserstein Generative Adversarial Network with Gradient Penalty
(C-WGAN-GP)
Author: Niklas Fehlemann, IMS IEHK
"""
import sys
import torch
import torch.autograd as autograd
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from geomloss import SamplesLoss
from tqdm import tqdm
im... |
8a9212d5dfa544b58eafdba88dda95328b72a809c4ee6e90db0b0dc45a124f94 | Python | 23,123 | 548 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Aug 24 11:51:41 2021
@author: filtsem
"""
import numpy as np
import matplotlib.pyplot as plt
import mne
import os
from mne.minimum_norm import read_inverse_operator, apply_inverse, apply_inverse_raw, make_inverse_operator,apply_inverse, write_inverse_op... |
9453ca9b74e03a6edb7c5a4236bbfa6a4192d099c878313885b702bd13232442 | Python | 23,138 | 563 | import numpy
from cellprofiler.modules import _help
from cellprofiler_core.constants.measurement import (
C_PARENT,
FF_CHILDREN_COUNT,
FF_PARENT,
COLTYPE_INTEGER,
)
from cellprofiler_core.module import Module
from cellprofiler_core.object import Objects
from cellprofiler_core.setting import Binary
from ... |
35e9e7a05559e4019820bfca241d7edd6567f2bd37d356e49c353c7ab29b7967 | Python | 23,187 | 964 | """
Module for generating rdkit molobj/smiles/molecular graph from free atoms
Implementation by Jan H. Jensen, based on the paper
Yeonjoon Kim and Woo Youn Kim
"Universal Structure Conversion Method for Organic Molecules: From Atomic Connectivity
to Three-Dimensional Geometry"
Bull. Korean Chem. Soc. ... |
451f290c6980680181956e794e2f132b82662c04eac2f6ffe523f8658b421221 | Python | 23,202 | 591 | import numpy
import six.moves
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler_core.measurement
import cellprofiler_core.modules
from cellprofiler_core.constants.measurement import FF_COUNT, COLTYPE_INTEGER, M_LOCATION_CENTER_X, COLTYPE_FLOAT, \
M_LOCATION_CENTER_Y, M_NUMBER_... |
9803a0e585690eaa88c98ac19ebc58d4fe092602d50c51844c04f1dba03a3447 | Python | 23,211 | 402 | import numpy as np
from numpy.typing import NDArray
from typing import List, Tuple, Annotated, Optional, Union
from pydantic import validate_call, ConfigDict, BeforeValidator, Field, BaseModel
from cellprofiler_library.functions.measurement import measure_correlation_and_slope_from_objects, measure_manders_coefficient_... |
440e31aadc05a307a0844c8a7b8369234411dfdcf0ce742ea0eab1685ff48b68 | Python | 23,274 | 647 | # -*- coding: utf-8 -*-
"""
pysteps.blending.utils
======================
Module with common utilities used by the blending methods.
.. autosummary::
:toctree: ../generated/
stack_cascades
blend_cascades
recompose_cascade
blend_optical_flows
decompose_NWP
compute_store_nwp_motion
load... |
8484cea78a2e46f8037a131c844662ecde1e39ab4015f2ecbd1c563fc3b374d3 | Python | 23,276 | 700 | import numpy
import pytest
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler_core.module
from cellprofiler_core.constants.measurement import (
C_PARENT,
GROUP_NUMBER,
GROUP_INDEX,
COLTYPE_FLOAT,
COLTYPE_INTEGER,
M_LOCATION_CENTER_X,
M_LOCATION_CENTER_Y,... |
2f87ff72340ea0a164b6f1213cfe1d7e8284e3a7587db655a608aec600beaf5d | Python | 23,308 | 497 | import numpy as np
import nengo
from .pathintegration import PathIntegration
from .associativememory import AssociativeMemory
from .binding import CircularConvolution, Product
class SLAMNetwork(nengo.network.Network):
r""" Nengo network that performs simultaneous localization and mapping (SLAM)
Paramete... |
79c3221de1560093046b2674aeda79af34881cf5443f58abb8d094169526c7ff | Python | 23,316 | 547 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Aug 24 11:51:41 2021
@author: filtsem
"""
import numpy as np
import matplotlib.pyplot as plt
import mne
import os
from mne.minimum_norm import read_inverse_operator, apply_inverse, apply_inverse_raw, make_inverse_operator,apply_inverse, write_inverse_op... |
e7f34e19c1b0225e04b42d71a46851629fb8b877d0bec8a6bc460bb8d81160fb | Python | 23,326 | 389 |
#! /usr/bin/env python
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function ##
import sys, os, glob, gzip, time
from functools import partial
from importlib import import_module
## Math
import numpy as np
## tensorflow imports
import tensorflow.compat.v1 as tf... |
d05d9a5797204dc54536169ec2c9735e4e4159c93671d104cfcb04f075ddc7a1 | Python | 23,328 | 616 | import atexit
import hashlib
import logging
import os
import tempfile
import urllib.parse
import urllib.request
import weakref
import numpy
from skimage.exposure import rescale_intensity
from skimage.util import img_as_float32
import cellprofiler_core.preferences
from .._abstract_image import AbstractImage
from ..._i... |
6801f1e03a891441d525b0790cc683f5154c871cc541e5d73c82249679f4770f | Python | 23,333 | 526 | from . GenomeTrack import GenomeTrack
from pygenometracks.utilities import InputError
from intervaltree import IntervalTree, Interval
import matplotlib
import numpy as np
from matplotlib.patches import Arc, Polygon
from .. utilities import opener, to_string, change_chrom_names, temp_file_from_intersect, get_region
from... |
c6002fdac368e2aff88bc58a369595e16a0e48f0c15d4973fd66a4396efa9c6d | Python | 23,398 | 605 | """ Inception-V3
Papers:
* `Rethinking the Inception Architecture for Computer Vision` - https://arxiv.org/abs/1512.00567
* `Adversarial Machine Learning at Scale` - https://arxiv.org/abs/1611.01236 (adversarially trained weights)
Originally from torchvision Inception3 model
Licensed BSD-Clause 3 https://github.com/p... |
64ca513623be1a00c9847d423cb93d0c5443da88c50fe9cbd03416a89fc9449e | Python | 23,407 | 576 | """ PyTorch Implementation of the Kron (PSGD) optimizer
This is a PSGD optimizer using a Kronecker-factored preconditioner.
This impl was adapted from https://github.com/evanatyourservice/kron_torch
by Evan Walters, licensed CC-BY-4.0.
Contributions to above also made by
* Lucas Nestler, added to his https://github.... |
f5152ef6cc0582cf9c86da983869370fb367c1ef6c9b594708f3299907bd65af | Python | 23,432 | 502 | from . GenomeTrack import GenomeTrack
from .. utilities import file_to_intervaltree, plot_coverage, InputError, transform, change_chrom_names
import numpy as np
import pyBigWig
import tempfile
import os
import pysam
DEFAULT_BEDGRAPH_COLOR = '#a6cee3'
class BedGraphTrack(GenomeTrack):
SUPPORTED_ENDINGS = ['.bg', ... |
d60667ec8e28f3314690988dba57458441bb93e9b93334c7d6ab6e803317d789 | Python | 23,563 | 606 | import sys
import unittest
import numpy as np
from numpy.testing import *
from ptsa.data.events import Events
from ptsa.data.readers import BaseEventReader
from ptsa.data.readers import PTSAEventReader
from ptsa.data.readers.EEGReader import EEGReader
from ptsa.data.readers.tal import TalReader
from ptsa.data.filters.... |
f2c3268c50c001b5f9af7befc178cf05a075cd19821450ef77cd2e492c955693 | Python | 23,569 | 746 | ''' adapted from https://github.com/all-umass/ManifoldWarping '''
import numpy as np
import scipy as sp
import sys
import time
import scipy.spatial.distance as sd
from sklearn.metrics.pairwise import euclidean_distances, pairwise_distances
from sklearn.manifold import Isomap,LocallyLinearEmbedding
import pandas as pd
... |
67ac79fb19cbd155932e3b869015c29aa385a0c75182c649a155c78138b2f1f3 | Python | 23,589 | 494 | from PIL import Image
import matplotlib
# matplotlib.use('Qt5Agg')
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from matplotlib import gridspec
import os.path as op
import os
import glob
import numpy as np
from tqdm import tqdm
from src.utils import utils
from src.utils import color_maps_utils as cmu
PICS... |
98e24830e78eb61789ee4389c7bb5a7f40c45eb2a48fc22ef17491966dd99796 | Python | 23,602 | 487 | # TODO shift map first using mask!
"""
Author: "Keitaro Yamashita, Garib N. Murshudov"
MRC Laboratory of Molecular Biology
This software is released under the
Mozilla Public License, version 2.0; see LICENSE.
"""
from __future__ import absolute_import, division, print_function, generators
import gemmi
import numpy... |
eca2580b959d2fb418df48d80a3a1306a04c02b2ce929fdb8a966daceb11aae9 | Python | 23,650 | 597 | #!/usr/bin/env python
"""
"""
from PIL import Image
import pandas as pd
import glob
import gc
import os
import numpy as np
import h5py
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils import data
from torchvision import models, transforms
import imgaug
from imgaug import augmenters as ... |
a0216cffee6cc824d78563e53685584c6bbea218659fb42d51a51243137f0576 | Python | 23,732 | 644 | """ Class-Attention in Image Transformers (CaiT)
Papers:
* `Going deeper with Image Transformers` - https://arxiv.org/abs/2103.17239
Original code and weights from https://github.com/facebookresearch/deit, copyright below
Modifications and additions for timm hacked together by / Copyright 2021, Ross Wightman
"""
# C... |
7d7d304b554c701bc807907b9ebed8e7b2769ef1cfb5161f9356733161574e0b | Python | 23,760 | 631 | """
SEResNet implementation from Cadene's pretrained models
https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/senet.py
Additional credit to https://github.com/creafz
Original model: https://github.com/hujie-frank/SENet
Papers:
* `Squeeze-and-Excitation Networks` - https://arxiv.o... |
72ed6bdd4440ef3f001d2a028bba94803931ac07d091bc58425839bd9e8c3fa5 | Python | 23,821 | 638 | """Generate the website's dataset catalog from a pinned registry snapshot."""
from __future__ import annotations
import argparse
import hashlib
import html
import json
import re
import sys
from collections.abc import Mapping, Sequence
from pathlib import Path
from typing import Any, Literal, TypedDict, cast
from urll... |
305d0f202a371ed2aa699f262490988c100af893a73ef5e4dfebcd8d2c396d43 | Python | 23,851 | 570 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
guideseq.py
===========
serves as the wrapper for all guideseq pipeline
"""
import os
import sys
import yaml
import argparse
import traceback
# Set up logger
import log
logger = log.createCustomLogger('root')
from alignReads import alignReads
from filterBackgroundS... |
b9355ede57508ff7b9f21e5e9d89e3ffec62264ac78a4a1c8acaec26f66f6d82 | Python | 23,858 | 596 | """
MeasureObjectNeighbors
======================
**MeasureObjectNeighbors** calculates how many neighbors each object
has and records various properties about the neighbors’ relationships,
including the percentage of an object’s edge pixels that touch a
neighbor. Please note that the distances reported for object
me... |
b829956fc0cc81906402eaf7e7b0c06474b01481b7a6ad6a29460fef662c8baf | Python | 23,860 | 667 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
3209ac0f2d6bf56a3a5fff436878c00a84542d26f418b855e2d301878ebd5299 | Python | 24,087 | 690 | """ Deep Layer Aggregation and DLA w/ Res2Net
Papers:
* `Deep Layer Aggregation` - https://arxiv.org/abs/1707.06484
* `Res2Net: A New Multi-scale Backbone Architecture` - https://arxiv.org/abs/1904.01169
DLA original adapted from Official Pytorch impl at: https://github.com/ucbdrive/dla
Res2Net additions from: https... |
46514698dc5a8bfeefaadc69ac871e6f45c82df7699bcf5cf83541a6e5f60afe | Python | 24,129 | 685 | """
ColorToGray
===========
**ColorToGray** converts an image with multiple color channels to one or more
grayscale images.
This module converts color and channel-stacked
images to grayscale. All channels can be merged into one grayscale image
(*Combine*), or each channel can be extracted into a separate grayscale im... |
e514af401848d5a4cc5d3512bd93d2c317f92272c6d30f218e0f00b7b4110534 | Python | 24,143 | 534 | __author__ = 'tsungyi'
import numpy as np
import datetime
import time
from collections import defaultdict
from . import mask as maskUtils
import copy
class COCOeval:
# Interface for evaluating detection on the Microsoft COCO dataset.
#
# The usage for CocoEval is as follows:
# cocoGt=..., cocoDt=... ... |
94bc8a6f3eb995882ac0d7d79b820f001d262883b9b505a0ebeeeed794f99689 | Python | 24,163 | 571 | import pandas as pd
import numpy as np
import wget
from zipfile import ZipFile
from DeepPurpose.utils import *
import json
import os
import requests
import re
'''
Acknowledgement:
The BindingDB dataset is hosted in https://www.bindingdb.org/bind/index.jsp.
The Davis Dataset can be found in http://staff.cs.utu.fi/~aat... |
ea99fd72cb69d6f27f660b09ad526cd43c27a70d907fcfb3be812e4b7f84e031 | Python | 24,177 | 744 | from .modelBase import ModelBase
from GANDLF.models.seg_modules.out_conv import out_conv
import torch
import torch.nn as nn
from torch.nn import ModuleList
import numpy as np
import math
class _DeconvConvBlock(nn.Sequential):
"""
A block consisting of a transposed convolutional layer, followed by a convolutio... |
fb0ea4e612f08533d8c4e3b6a5e281292b71a08ffb90018f21fbb9cb885ec5dd | Python | 24,328 | 507 | import numpy as np
import nengo
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import sys, os
sys.path.insert(1, os.path.dirname(os.getcwd()))
os.chdir("..")
import sspslam
import nengo_ocl
from sspslam.networks import get_slam_input_functions
import sspslam.utils as utils
import matplotlib.gr... |
4223cd2a27cbc6ddf7220f93b03a74481f93d9c5d811b848403bb3f21a49e55d | Python | 24,367 | 585 | """ EfficientNet, MobileNetV3, etc Builder
Assembles EfficieNet and related network feature blocks from string definitions.
Handles stride, dilation calculations, and selects feature extraction points.
Hacked together by / Copyright 2019, Ross Wightman
"""
from typing import Callable, Optional
import logging
import ... |
b64a5cd60b47222fac6f9cc3d704280b2a896dcc8f476150c9be7f671ca88362 | Python | 24,368 | 699 | import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import torch.nn as nn
import torch
import copy
import math
from sklearn.metrics import roc_curve
from scipy.optimize import curve_fit
from torchsummary import summary
from sklearn import tree
#from sklearn.externals... |
2dcd24b2baa1c34def9eec3d2741ae37a91deb9b2f4e5f6c85526c74f6a48a19 | Python | 24,370 | 580 | #!/usr/bin/env python3
"""
Makes temporary seed corr maps using a chosen roi for each network and
correlation maps
Usage:
cifti_vis_PINT snaps [options] <func.dtseries.nii> <subject> <PINT_summary.csv>
cifti_vis_PINT subject [options] <func.dtseries.nii> <subject> <PINT_summary.csv>
cifti_vis_PINT index [o... |
01713cac26c3ffcc1f032039136e098ad9586f71de687cd08c8712a1321e7705 | Python | 24,384 | 466 | #!/usr/bin/env python3
# MYC blacklist region chr8:129571461-129571635 (b37)
# MYC blacklist region chr8:128559215-128559389 (b38)
#################################################################
# Configure the enviroment
import pandas as pd
import argparse
from multiprocessing import Pool
########################... |
cc56b3c545397970a07516a266f8ac14c5ebb99a82ba6983e7d4b95c829635e1 | Python | 24,437 | 780 | """
Performs various operations.
@author: JingyiGF
"""
import scipy
import scipy.io
import sys
import os
import time
import copy
import warnings
import random
import pickle
from copy import deepcopy
from scipy.optimize import minimize
from scipy.stats import wilcoxon
from typing import Any, Optional
from collections.a... |
46e5f26f3d5afe695f7b0694541dabc10ccfb32cb1515186cf7fe12e7353ae81 | Python | 24,465 | 489 | # Analysis Imports
import math
import numpy as np
from scipy.signal.windows import dpss
from scipy.signal import detrend
# Logistical Imports
import warnings
import timeit
from joblib import Parallel, delayed, cpu_count
# Visualization imports
import colorcet # this import is necessary to add rainbow colormap to matpl... |
af3af33de5424dec6ce0ed8de7d850628c5da98eab85fc09056ab346e0d77cc8 | Python | 24,510 | 691 | import sys
from copy import copy
from typing import Any, Dict, Type
import numpy as np
import pytest
from hypothesis import assume, given, settings, strategies
from hypothesis.extra.pandas import column, data_frames, range_indexes
import xgboost as xgb
from xgboost import testing as tm
from xgboost.compat import impo... |
93d013dac47b61908a9354223a3a43407715d9d9f0c8cf55963bf3874dc40201 | Python | 24,519 | 597 | import numpy as np
import os
from matplotlib import pyplot as plt
from matplotlib.patches import Rectangle
from tensorflow.keras import callbacks
from tensorflow.python.keras.callbacks import Callback
from tensorflow.keras.callbacks import LearningRateScheduler
import math
from lib.pinn import PINN
from lib.network im... |
cd918891ada156b6f2d15af4a1d12913008031117e79d6bd90cecd4b68700d3e | Python | 24,536 | 531 | #!/usr/bin/env python3
"""
Runs a combination of fmriprep and ciftify pipelines from BIDS specification
Usage:
fmriprep_ciftify.py <bids_dir> <output_dir> <analysis_level> [options]
Arguments:
<bids_dir> The directory with the input dataset formatted
according to the B... |
fe2df30cf49a9312bf7f2366e3a79e105ff727a573f30f4a72ccc8d114ece7d0 | Python | 24,585 | 892 | from ptsa.data.readers import TalReader
from ptsa.data.readers.index import JsonIndexReader
import numpy as np
import os.path as osp
from tests import utils
@utils.skip_without_rhino
def test_talreader_on_database():
old_reader = TalReader(filename=osp.join(utils.get_rhino_root(), 'data/eeg/R1234D/tal/R1234D_talL... |
c470e282251958677f0a982baec18c6891d1c188acfa0b4e8c52a067fbe036d0 | Python | 24,628 | 559 | """ Dynamic Sequence Length Datasets for Variable Resolution Image Processing
Implements two dataset wrappers:
1. NaFlexMapDatasetWrapper - Map-style dataset that returns batches with variable sequence lengths
TODO: 2. NaFlexIterableDatasetWrapper - Iterable dataset that yields batches with variable sequence lengths
... |
0c3a954214a50c4b36719ecf7764c8875c0755a39660c399477d1b0f6419f0ab | Python | 24,696 | 614 | import csv
import os
import sys
import tempfile
import warnings
import click
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklearn import preprocessing
from sklearn.cluster import KMeans
from sklearn.decomposition import PCA
from sklearn.metrics import (
calinski_harabaz_score,
dav... |
7f2a238804408bd1d3e06c60bf89d7cf6415492aea93defcf60aaea1ee9b996d | Python | 24,703 | 602 | import numpy as np
import os
from matplotlib import pyplot as plt
from matplotlib.patches import Rectangle
from tensorflow.keras import callbacks
from tensorflow.python.keras.callbacks import Callback
from tensorflow.keras.callbacks import LearningRateScheduler
import math
from lib.pinn import PINN
from lib.network im... |
7c00b551b3d4762f467685698395e1069cb89987d623d33c9384c5fd94978e66 | Python | 24,711 | 368 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 4 12:16:50 2018
@author: saskiad
"""
import pandas as pd
cres
areas = ['VISp','VISl','VISal','VISpm','VISam','VISrl']
depths = [100,200,300,500]
table = pd.DataFrame(columns=('area','cre','depth','number_experiments','number_cells_dg','responsive... |
5c9c568c4c1922603a640f014cb632dd345a0122f816964d4c344aa7e7c59bef | Python | 24,751 | 577 | #!/usr/bin/env python3
# Copyright 2021 Alexander Meulemans, Matilde Tristany, Maria Cervera
#
# 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
... |
be250a49a4085ac838fdb7025f0c0f4c530e498bfcc5972154a3e237e0a2810b | Python | 24,779 | 711 | import torch
from torch import nn
from torch.nn import functional as F
import dgl
from layers import GATLayer, CapsuleLayer, squash, GAT_adj, WeightedSumAndMax, ConditionEmbedding
class DeepReac(nn.Module):
def __init__(self,
in_feats_0,
g_num,
c_num=0,
... |
0e40fe23eba24bde9d45a1a50d31c82c39f28706dc1af1a814e1d9f1628e51a0 | Python | 24,811 | 585 | import tensorflow as tf
import numpy as np
import settings
import pandas as pd
from pathlib import Path
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.collections import LineCollection
from matplotlib.colors import ListedColormap, BoundaryNorm
import os
os.environ['MNE_USE_NUMBA']='f... |
b6418389165390e67265892e21a37592795d1d595f95a70b4abbae9ab42c45c2 | Python | 24,821 | 821 | import numpy as np
import matplotlib.pyplot as plt
from scipy import io
import numpy as np
import sys
import cv2
import matplotlib
import skimage.transform as st
import pywt
import skimage.filters
from matplotlib import rc
import matplotlib.ticker
rc("font", family="serif", serif="cm10")
matplotlib.rcParams["text.use... |
e44e4a77837a5b0617e04c25290334a5cd09205d80866c80eaceb22553d5cdb1 | Python | 24,829 | 505 | """
Author: Mingjian He <mh1@stanford.edu>
vb module contains variational bayesian methods for switching inference
"""
from somata.basic_models import StateSpaceModel as Ssm
from somata.exact_inference import forward_backward, viterbi, run_em, logdet, inverse
from somata.switching import switching
import numpy as np
... |
950d6629b55bf3c1357a33559c57d982cfb21d3c9f01e6c8171713174465c9d2 | Python | 24,856 | 671 | # coding=utf-8
# Copyright 2020 The SimCLR 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 applicable law or... |
5db56f3d0c17b072984086568728ffcdfae7dcdb18a8d100eb2d08b617a1224e | Python | 24,858 | 661 | """SwiftFormer
SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications
Code: https://github.com/Amshaker/SwiftFormer
Paper:
* `SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications` - https://arxiv.org/abs/2303.15446
@InProceed... |
4c8d1a0e8bf52b63a36e60752f10d5b6e6736c1f7dff02224eedb6b6c1f8192d | Python | 24,871 | 672 | import os, time, psutil
from typing import Tuple, Union
import pandas as pd
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
import numpy as np
import torchio
from medcam import medcam
from GANDLF.data import get_testing_loader
from GANDLF.grad_clipping.grad_scaler import GradScaler, model_pa... |
83b83f507b5c7bcdf26fb52a1f53c8137bba5f54909f0130466ac57bb14eb8e0 | Python | 24,871 | 765 | # -*- coding: utf-8 -*-
"""
This test file will check each part of the
configuration file checker
which can raise an InputError
"""
import unittest
import pygenometracks.plotTracks
import os
from pygenometracks.utilities import InputError
ROOT = os.path.join(os.path.dirname(os.path.abspath(__file__)),
... |
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