sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
d76058f782d57f1fd25189056721bba11ad81274bbdf2484d2f9940715912766 | Python | 4,229 | 125 | import os
import redis
import time
from param_default import redis_databases
def _get_redis_connection(db_name: str):
if "REDIS_SERVER" not in os.environ:
return None
redis_host = os.environ["REDIS_SERVER"]
db_number = redis_databases[db_name]
return redis.Redis(host=redis_host, db=db_number,... |
4a23776f0cd1326b66a3a50e649fce9f270df90f8efb7d3ba927524c406bfb65 | Python | 4,261 | 177 | # -*- coding: utf-8 -*-
"""Functions for simulations.
"""
import numpy as np
__all__ = ["shepp_logan"]
def shepp_logan(shape, dtype=complex):
"""Generates a Shepp Logan phantom with a given shape and dtype.
Args:
shape (tuple of ints): shape, can be of length 2 or 3.
dtype (Dtype): data typ... |
66504672c28c4d9eeccf2ed57cd14868edb0d1a9d97de05741d07c393045f2a2 | Python | 4,325 | 113 | from common import ZonalComputeUrl, GenerateBootDisk, GenerateNetworkInterface, GenerateAirflowVar
from common import INSTALL_DOCKER_CMD, INSTALL_NVIDIA_DOCKER_CMD, INSTALL_OPS_AGENT
from workers import GenerateCeleryWorkerCommand, GenerateEnvironVar, GenerateDockerCommand
def GenerateEasysegWorker(context, hostnam... |
781b8c1a8f65ead001abf585a1625978deef9997a865f732dfbad1217cc93a74 | Python | 4,335 | 162 | # -*- coding: utf-8 -*-
"""
Created on Mon Jul 7 19:32:53 2025
@author: Usuario
"""
#Run after main script
#im = 4
import matplotlib.pyplot as plt
masks_Tc2 = masks_Tc.copy()
masks_Nuc2 =masks_Nuc.copy()
image = imgs[im]
name = fields[im]
masks_Tc = masks_Tc[im]
masks_Nuc = masks_Nuc[im]
dummy... |
bdd3e575307365f738bf422bbb20c9b9b7c7f744cbc99477691af1f3a4e0a1e4 | Python | 4,357 | 134 | import unittest
import numpy as np
import numpy.testing as npt
from sigpy import util
from sigpy.mri import epi
if __name__ == '__main__':
unittest.main()
class TestEpi(unittest.TestCase):
def test_get_B(self):
b_0 = np.zeros((1, 1))
b_1 = np.ones((6, 1))
b = np.concatenate((b_0, b... |
03be0e0565c2ab4027424ba326b7d9f57c4b16ab60a798fe58b21cb4b6a6251a | Python | 4,394 | 135 | from __future__ import print_function
from intern.remote.boss import BossRemote
from intern.resource.boss.resource import (
ChannelResource, ExperimentResource, CoordinateFrameResource
)
from .. import autocropfn, readonlyguard, ImageSourceInterface
from ... import exceptions
from ...lib import (
colorize, red... |
f995e6febe6175905eeaa3eb22d9ea7b740b14117ffeb4b9bf4831d1835fa3f6 | Python | 4,405 | 113 | import unittest
import numpy as np
from sigpy import config, interp
if config.cupy_enabled:
import cupy as cp
if __name__ == "__main__":
unittest.main()
class TestInterp(unittest.TestCase):
def test_interpolate_spline(self):
xps = [np]
if config.cupy_enabled:
xps.append(cp)... |
3e7061dda053de9e5dd987bee50dc80e4f6220df6cb9bb622c3c1018a0da98b6 | Python | 4,419 | 211 | # -*- coding: utf-8 -*-
"""Thresholding functions.
"""
import numba as nb
import numpy as np
from sigpy import backend, config, util
__all__ = [
"soft_thresh",
"hard_thresh",
"l1_proj",
"l2_proj",
"linf_proj",
"psd_proj",
]
def soft_thresh(lamda, input):
r"""Soft threshold.
Performs... |
23c8ad0f7132028cb75b6d4f5c14fda02cb8aa0a52e3dc4c67b038165d7cf3db | Python | 4,515 | 121 | import asyncio
import functools
import logging
import base64
import fasteners
from slack_down import slack_md
import markdown
from bs4 import BeautifulSoup
import contextvars
from IPython.core.magic import (Magics, magics_class, line_cell_magic)
from IPython.display import display, HTML, Image, IFrame
from kombu_help... |
e7c943d6e9f53c2f16eb086639d7dd0a243095002adcb14255fa579e8b1b3954 | Python | 4,516 | 107 | import numpy as np
import quantities as pq
import neo
from elephant.conversion import BinnedSpikeTrain
def concatenate_spiketrains(spiketrains, interval):
st = list(spiketrains.values())[0][0]
trial_duration = (st.t_stop - st.t_start).rescale('s').magnitude + interval
concat_spiketrains = []
for sts ... |
8374415cecbd62c428c368e1930b26b54d22ec424beecef82dd17fefcd2884dc | Python | 4,532 | 115 | import argparse
import os
import sys
import pathlib
import radiomics
import SimpleITK as sitk
import csv
import pandas as pd
LABELS_FS = ['Left-Lateral-Ventricle', 'Left-Inf-Lat-Vent', 'Left-Thalamus-Proper', 'Left-Caudate', 'Left-Putamen', 'Left-Pallidum', '3rd-Ventricle',
'4th-Ventricle', 'Brain-Stem',... |
55eba56eb398e3aa1535cafba1e9ab380d2650c266c8f9cea852fb8df6a6a2c5 | Python | 4,600 | 132 | from lightparam.gui.precisionslider import PrecisionSingleSlider
import qdarkstyle
from PyQt5.QtWidgets import (
QApplication,
QWidget,
QHBoxLayout,
QGridLayout,
QDoubleSpinBox,
QLabel,
)
from PyQt5.QtGui import QColor
from PyQt5.QtCore import Qt, pyqtSignal, QPointF, QTimer
class MotionContr... |
ade5de04f03de8c47dae923ac4776e0e601bde949b85a3fd8cdaaef44af59414 | Python | 4,616 | 127 | def health_check_info(image_name):
from slack_message import slack_message
image = pull_image(image_name)
try:
if 'Healthcheck' in image.attrs['Config']:
slack_message(f':cool:Image `{image_name}` has builtin health check!')
return True
except:
pass
slack_me... |
e50daf20955733a4463583ef70c663efc75641bb6e72be3da5179a1b0de6106b | Python | 4,647 | 191 | from collections import defaultdict
from copy import deepcopy
import time
import re
import json
import socket
from operator import mul
from functools import reduce
import numpy as np
from cloudvolume import CloudVolume
N = 3
CHUNK_SIZES = (
(128,128,1),
(128,128,2),
(128,128,4),
(128,128,8),
(128,128,16),
(12... |
7ff477e11d9c747a62dd5f2d0ff85e9fd86e9390cbf11a15c9da8f973f19eabf | Python | 4,672 | 134 | # -*- coding: utf-8 -*-
"""MRI pulse-design-specific linear operators.
"""
import sigpy as sp
from sigpy import backend
def PtxSpatialExplicit(sens, coord, dt, img_shape, b0=None, ret_array=False):
"""Explicit spatial-domain pulse design linear operator.
Linear operator relates rf pulses to desired magnetizat... |
aefc4e487e27892cf34392295b4cc6868da6b9760532f10d6dbd788423eccbff | Python | 4,678 | 169 | # -*- coding: utf-8 -*-
"""MRI preconditioners.
"""
import sigpy as sp
__all__ = ["kspace_precond", "circulant_precond"]
def kspace_precond(
mps, weights=None, coord=None, lamda=0, device=sp.cpu_device, oversamp=1.25
):
r"""Compute a diagonal preconditioner in k-space.
Considers the optimization problem... |
27bb34ca7caf67358b5804a4a494135b4aa2c3b55a2fc7d431b98e275fb42383 | Python | 4,702 | 152 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 1 16:07:14 2025
@author: camille
"""
# Packages ####################################################################
from brian2 import *
matplotlib.rcParams.update({'font.size': 12})
# %matplotlib qt
# Parameters ###############################... |
5de55a3c305d8a45bb222d815ab8e1dff8ccc26920a929d236a1f34166c57c93 | Python | 4,754 | 149 | # -*- coding: utf-8 -*-
"""Functions for GRAPPA.
This implementation makes use of the function "sp.array_to_blocks" to slide through calibration as well as undersampled k-space data to perform GRAPPA kernel fitting and reconstruction.
Alternatively, one can also use other functions, e.g. "view_as_windows" in skimage.... |
7162c43f6ef58073b538148dc38af5a23d4bc4d8dfa6265f524d18350f883950 | Python | 4,758 | 141 | import warnings
warnings.filterwarnings("ignore")
# GENERAL IMPORTS
import os
import sys
# this is needed to limit the number of scipy threads
# and let spikeinterface handle parallelization
os.environ["OPENBLAS_NUM_THREADS"] = "1"
import argparse
import numpy as np
from pathlib import Path
import json
import pickl... |
01edfd086006e489b0a3ae3c8a210cd0f2b7a9066c83bfa360a7a4d60dc005ae | Python | 4,762 | 140 | #!/usr/bin/env python
"""
Utilities to convert sleepsign output files.
"""
import numpy as np
from somnotate._utils import convert_state_vector_to_state_intervals
from example_pipeline.data_io import (
ArgumentParser,
load_dataframe,
check_dataframe,
export_hypnogram,
)
SLEEPSIGN_KEY = dict([
... |
693e5c2bed85cdec87cf608d850fb27eb09c314ac35c9232f81cc28ad7bd8d3e | Python | 4,770 | 142 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Module to resample image into atlas space
@authors: Jorn Diedrichsen
"""
import nibabel as nib
import numpy as np
from numpy.linalg import inv
import nitools.volume as ntv
def reslice_image(
source_image,
deformation,
ma... |
c188f4dd149acf1ad5985c86de1ce6494bd181efb3d75fcde0bae29090cb2172 | Python | 4,785 | 123 | """Brain atlas tests"""
import unittest
from aind_data_schema_models.brain_atlas import CCFv3
class TestCCFStructure(unittest.TestCase):
"""CCFStructure tests"""
def test_from_id_valid(self):
"""Test from_id method with valid IDs."""
# Test with a few known IDs
structure = CCFv3.from... |
4661ec0fe730f141f09b74ef4488aaed73512b7f94325c7cf6968f00a714fc9e | Python | 4,823 | 142 | #! /usr/bin/env python3
import pathlib
import shutil
import unittest
from tetra.regression_manager import RegressionManager, TestFile, TestResult
class TestRegressionManager(unittest.TestCase):
KEEP_OUTPUT_DATA = False # Set to True to keep file for debugging
def setUp(self):
self.data_dir = path... |
f21cadfe8b3e7c3ded00cc2cba5e11270e2261528947b41da32ba68a6616e5b8 | Python | 4,838 | 110 | import pandas as pd
import numpy as np
import scipy.stats as stats
import nibabel as nib
import os
import sys
import csv
import skimage.segmentation as segmentation
import scipy.spatial as spatial
import argparse
# get cortical labels
def get_labels(offset):
lut = pd.read_csv('{}/fs_lut.csv'.format(os.path.dirnam... |
813ca4caec56b857d8bf91d5e94277c584bb85ecdded1a214b225e04eac29d22 | Python | 4,841 | 152 | """
losses.py
Loss functions used in RESURF/MISRGRU training.
Notes
-----
- All losses assume spatial dimensions are the last two dims (..., H, W).
This works for shapes like:
(H, W)
(C, H, W)
(B, C, H, W)
(B, T, H, W)
because rfft2 operates on the last two dimensions by default.
- `fourier_space... |
55aaf34a77eaf5f54b16bebe9bb64df4770266bfce90c489ce7c8183a745dc90 | Python | 4,876 | 158 | from typing import Optional
import numpy as np
import numpy.typing as npt
from ..sharding import ShardingSpecification, ShardReader, synthesize_shard_files
from ....skeleton import Skeleton
from ..spatial_index import CachedSpatialIndex
from ....exceptions import EmptyFileException
from cloudfiles import CloudFiles
... |
98b31a157bf21d479e10b76f4cf9f324bc4c2bc4e7ac437f53e30c368bd3399c | Python | 4,913 | 129 | import torch
from torch import nn
from torch.nn import functional as F
class _NonLocalBlockND(nn.Module):
def __init__(self, in_channels, inter_channels=None, dimension=3, sub_sample=True, bn_layer=True):
super(_NonLocalBlockND, self).__init__()
assert dimension in [1, 2, 3]
self.dimensi... |
fab7759c20ce6d76b0a84f05fcea08acdd79e931380537b1335cfe42ac00ce08 | Python | 4,941 | 125 | from airflow.utils import db as db_utils
from airflow.models import Variable
from airflow import models
from common.google_api import get_project_data, get_instance_data, get_instance_metadata, set_instance_metadata
from param_default import param_default, inference_param_default, synaptor_param_default
import os
impor... |
5090773a1cd9ebfd1022af5729aa922571f3a1b0bbd2e0532b86605af1e56fe9 | Python | 4,971 | 159 | # -*- coding: utf-8 -*-
"""Methods for Echo-Planar Imaging (EPI) acquisition:
* retrospectively undersampling phase-encoding direction
* split shots within one diffusion encoding
* find non-zero ky lines from Cartesian k-space data
Author:
Zhengguo Tan <zhengguo.tan@gmail.com>
"""
import numpy as np
from .dims i... |
43174c976dc45a85258b77e07b179404962cf3c07a2df925c1775033613b9812 | Python | 5,005 | 141 | # -*- coding: utf-8 -*-
"""
Created on Sun Sep 10 07:49:50 2023
@author: CAG329
"""
# Original code from
# https://brian2.readthedocs.io/en/stable/examples/IF_curve_Hodgkin_Huxley.html
# Packages ####################################################################
from brian2 import *
# %matplotlib qt
matplotlib.rc... |
11b98669868e6c3924007cdd1836292233150c1242f3bbf058a76a7ed2627f14 | Python | 5,028 | 144 | """
This dag autoscales your cluster. This only works with docker-compose (local)
and Infrakit (swarm).
For Infrakit, the following environment variables must be set:
- INFRAKIT_IMAGE - what docker image to use for infrakit
i.e.infrakit/devbundle:latest
- INFRAKIT_GROUPS_URL - the location of the groups js... |
f5d92ceec53225b25099473b5d5d09fd9dcdca6cd86208a04b1dad122c1ebd12 | Python | 5,042 | 140 | import numpy
import pandas
def pretty_print_diffs(exp, act, tolerance=0):
# First we check which rows/columns fail to match
pretty_diffs = []
r_match, r_exp, r_act = row_match(exp, act)
if r_exp:
pretty_diffs.append(
"SizeError({} Rows only in expected: {})".format(
... |
7af7e794e6e7a25c8025b8a18a84d8bf7940f0b8a868796564f8790e4e131b54 | Python | 5,048 | 176 | # %% [markdown]
# # Notebook 01: Mesh generation from TIFF mask
#
# **Paper section:** Methods — Neural tube segmentation
# **Paper figures:** Fig. 1c–d (segmented lumen meshes)
#
# This script converts two binary 3D TIFF segmentation masks (inner lumen and
# outer basal surface) into smoothed, decimated triangulated s... |
291cd60ba529e6f4d29e4d3c9375224639a2452f0d8cbb68105bd36f3c369474 | Python | 5,050 | 130 | from googleapiclient import discovery
import requests
import json
def get_project_data(key):
apiurl = f"http://metadata/computeMetadata/v1/project/{key}"
response = requests.get(apiurl, headers={"Metadata-Flavor": "Google"})
response.raise_for_status()
return response.text
def get_instance_data(key):
... |
55f7e356c01ec6d846981c552cf5c30bac2ba1c3f01a5cc62bbfc4070558df7a | Python | 5,050 | 149 | import os.path
from .. import exceptions, paths
from ..lib import yellow, Bbox, Vec, toabs, xyzrange, min2
from ..secrets import CLOUD_VOLUME_CACHE_DIR, CLOUD_VOLUME_DIR
import numpy as np
NON_ALIGNED_WRITE = yellow(
"""
Non-Aligned writes are disabled by default. There are several good reasons
not to use the... |
fb0f563c3b6fc17651bc9a39700c1337a3f053966e4b49d4ccc552e7c3e386b0 | Python | 5,056 | 164 | import time
import json
import functools
import concurrent.futures
from airflow import settings
from airflow.models import DagBag, DagModel, Variable, Connection
from airflow.models.dagrun import DagRun
from airflow.api.common.mark_tasks import set_dag_run_state_to_success
from airflow.api.common.trigger_dag import tr... |
620cde5cee462fd4316bea5a5c7707cac5556d70572be311a3edb1b64b34e224 | Python | 5,060 | 136 | """Local OnsagerNet variant with optional regularization on the potential V.
Hooks into the ``regu`` / ``regularization(x)`` interface that
``UIDD._losses.MLELoss`` already checks: when ``model.regu`` is truthy,
``MLELoss`` adds ``model.regularization(x)`` to the per-sample loss. We support
two families that act on th... |
7362e7e342a2c690b99b2a06a9a3e1a90a7c0f2b50aaa4bf6720e6522c901475 | Python | 5,085 | 167 | # -*- coding: utf-8 -*-
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup ------------------------------------------------------------... |
9a0e9993044a0164e045edc97b3aed3fb711c1baa3aaed8d7e07af4bec079e71 | Python | 5,085 | 134 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Cobra Compartment Duplicator
This script takes a metabolic model and duplicates its reactions based on a set
of predefined compartment transport rules. It is designed to create a new model
where reactions are split to represent transport between different compartme... |
b74d502f91031a084be28fc841abeb4cdf7432c8895639b04374dcfe68edcf57 | Python | 5,114 | 153 | #!/usr/bin/env python3
"""
This script creates a 3-minute synthetic recording and saves it to NWB for testing the pipeline.
Each ElectricalSeries gets its own Device / ElectrodeGroup with an externally given name, so that
the pipeline can be tested on the multi-probe NWB scenario (see issues #116 and #121): the NWB
re... |
34c793dd93d3f2497306d67d728efbe1befec1b6eefa8cab90ea542b7d8bade8 | Python | 5,178 | 155 | import unittest
import numpy as np
import numpy.testing as npt
from sigpy import backend, config, nlop, util, linop
import torch
from torch.autograd import Variable
if __name__ == '__main__':
unittest.main()
devices = [backend.cpu_device]
if config.cupy_enabled:
devices.append(backend.Device(0))
class Test... |
7cef84d961990be24136cbcf794efe509269ec8cf467da618621a41c19302baa | Python | 5,183 | 168 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from ._utils import (
robust_normalize,
truncate_signals,
pad_along_axis,
remove_padding_along_axis,
)
def plot_signals(signals,
sampling_frequency = 1,
remove_outliers = True,
... |
f3c81f656981ea6d609d077800e9438b98ed1c26b67c265d03ceb56a5cf2c820 | Python | 5,203 | 160 | from __future__ import division
import numpy as np
from numpy import random
from scipy.spatial.distance import pdist, cdist
from scipy.stats import kstwobign, pearsonr
from scipy.stats import genextreme
__all__ = ['ks2d2s', 'estat', 'estat2d']
def ks2d2s(x1, y1, x2, y2, nboot=None, extra=False):
'''Two-dimension... |
9f898089c28fdd19e7d3a0e93795f462b9e404edfa949993dbce2b67dbfb74ef | Python | 5,237 | 184 | from typing import Optional, Iterator
import datetime
import os
import posixpath
import numpy as np
import numpy.typing as npt
from cloudfiles import CloudFiles
from cloudvolume import lib
from cloudvolume.exceptions import (
SkeletonDecodeError, SkeletonEncodeError,
SkeletonUnassignedEdgeError
)
from cloudvol... |
fc018cb60e9c7f84c08302abcae50c9734a8e2764f8888f8d42b4cd1ee7df5ea | Python | 5,242 | 136 | """
Inference script to test the newest model on misclassified images.
Shows the image and the model's classification.
Example:
python inference_on_disagreements.py \
--model-path ./outputs/20260127_120000_binary_batch4_div5_tuned.keras \
--disagreement-dir /dls/science/groups/i23/scripts/chris/GoniOwl_metri... |
70979381634a78465e2bbf6e25834753ed9e07ff5d770c520a26ee53dabc1070 | Python | 5,289 | 139 | # -*- coding: utf-8 -*-
"""
MUSSELS Diffusion MRI Reconstruction.
Author: Zhengguo Tan <zhengguo.tan@gmail.com>
"""
import numpy as np
import sigpy as sp
from sigpy import backend
from sigpy.mri import app, sms
def MusselsRecon(y, coils, MB=1,
lamda=0.05, max_iter=50, rho=0.1,
reg... |
2ae5bc8fed826b57bbd08111d0905921538bc665d43bd5375623557d8b1af1df | Python | 5,325 | 179 | #!/usr/bin/env python3
#
# Test model downloads and smoke them.
#
import subprocess
import sys
from typing import Dict, List, Optional, Tuple
from argparse import ArgumentParser
from pathlib import Path
from tempfile import TemporaryDirectory
from fnmatch import fnmatch
import json
Job = Tuple[str, str, Optional[str... |
7167ed4cb67fa7f18b1d7fce0f448c19848bbfb96231708c6793a71bf0f73564 | Python | 5,335 | 138 | import unittest
import numpy as np
import numpy.testing as npt
from sigpy import backend, config, linop, pytorch
if config.pytorch_enabled:
import torch
if __name__ == "__main__":
unittest.main()
devices = [backend.cpu_device]
if config.cupy_enabled:
devices.append(backend.Device(0)... |
cb1caaeadad59c44290e6a0d7c1d9abe1c98b03ac921d6f1148a1078a15c056f | Python | 5,353 | 173 | """Coil compression functions.
Author: Zhengguo Tan <zhengguo.tan@gmail.com>
"""
import numpy as np
import sigpy as sp
from scipy.linalg import eig
__all__ = ['scc', 'gcc', 'rovir']
# %%
def scc(kdat, P=10, coil_dim=-2, device=sp.cpu_device):
r"""Coil compression based on SVD.
Args:
kdat (array): ... |
ff49beb2ed9ff8d80970b3c49e62e2d53f34d29a2246a4d77b75fe33a466eb74 | Python | 5,374 | 160 | # %% [markdown]
# # Notebook 02: Surface curvature mapping
#
# **Paper section:** Results — Surface curvature mapping
# **Paper figures:** Figs. 3 (Gaussian curvature), 4 (Mean curvature)
#
# This script computes the local Gaussian and Mean curvature at every vertex
# of the basal surface mesh.
#
# **Method:** For each... |
561a93581053f0dca74238210ae153edd7949c871807cc7b8da071f1b2c447cf | Python | 5,393 | 159 | import unittest
import numpy as np
import numpy.testing as npt
from sigpy import app, linop, util, prox, nlop
if __name__ == "__main__":
unittest.main()
class TestApp(unittest.TestCase):
def test_MaxEig(self):
n = 5
mat = util.randn([n, n])
A = linop.MatMul([n, 1], mat)
s =... |
4a33e9eb5101ef5f17e221d3ddbb0eef1c668a6955efcaa0a7e9413c20a5a1b9 | Python | 5,458 | 147 | """
samplers.py
Batch samplers that use Dataset grouping information.
This module expects a dataset that exposes:
dataset.pattern_to_indices : Dict[str, List[int]]
In this repo, GroupedPatternDataset builds that mapping so we can sample batches
that contain multiple pattern IDs (diversity per batch)
and the # d... |
7d23961db3794325fcf30dd6b6b7f9c64911d4eebf5fafd2c49c044ab1e2a388 | Python | 5,460 | 145 | """Tests classes in data_name_patterns module"""
import unittest
from datetime import datetime, timezone
from aind_data_schema_models.data_name_patterns import (
DataRegex,
DataRegexLegacy,
RegexParts,
build_data_name,
datetime_from_name_string,
datetime_to_name_string,
)
class TestRegexPart... |
327d5c23f7a44f481fdf023eb5cb03315eb41f573b1560051b7977bda8b54016 | Python | 5,535 | 196 | import os
import json
import subprocess
from collections import OrderedDict
from bot_info import workerid
fernet_key = os.environ["FERNET_KEY"]
#airflow_cmd = "sudo docker run -e FERNET_KEY={fernet_key} \
# -it --rm {docker_image} airflow".format(
# fernet_key=fernet_key,
# docker_image="ranlu/air-tas... |
50b3fc73550326471f495126a957fc9dec042d35f5874fba47e8d2ac1f6a7236 | Python | 5,580 | 150 | #!/usr/bin/env python
"""
Using a pre-trained model, and given the preprocessed signal arrays,
annotate the state for each sample in the signal array, and save out a
1) a hypnogram, and
2) the likelihood of the predicted state for each sample.
The latter can then be used to manually refine annotation.
"""
import nump... |
5b4e22e18522c60ade0906cadab84c1bce033b3a05dc5b16eec4e722e09c3fe0 | Python | 5,593 | 143 | """Tests classes with fixed Literal values match defaults"""
import unittest
from pydantic import BaseModel
from aind_data_schema_models.harp_types import HarpDeviceType
from aind_data_schema_models.organizations import Organization
from aind_data_schema_models.species import Species
from aind_data_schema_models.mou... |
5b47c39b6a20b182febfd858d01ab01b49206f2aa77a0485603b0d8ec7e8a01b | Python | 5,609 | 174 | import unittest
import numpy as np
import numpy.testing as npt
import sigpy as sp
from sigpy.mri import linop, precond
if __name__ == "__main__":
unittest.main()
class TestPrecond(unittest.TestCase):
def test_kspace_precond_cart(self):
nc = 4
n = 10
shape = (nc, n)
mps = sp.... |
1117f72658164d0f9314fc84103b98e590f1cda442da1477cbea317418d71b77 | Python | 5,644 | 177 | from typing import Dict, Tuple, Sequence, Union, Optional
import re
import os
import numpy as np
from cloudfiles import CloudFiles
from .. import autocropfn, readonlyguard, ImageSourceInterface
from ... import compression
from ... import chunks
from ... import exceptions
from ...lib import (
colorize, red, mkdi... |
d2dc88d06565c20b4ecefce2eb96a0a1f612072daaa58d50e1a894cdd2a406eb | Python | 5,684 | 231 | """Modalities"""
from typing import Literal, Union
from pydantic import ConfigDict, Field
from typing_extensions import Annotated
from aind_data_schema_models.pid_names import BaseName
class ModalityModel(BaseName):
"""Base model for modality"""
model_config = ConfigDict(frozen=True)
name: str
abb... |
673a0617b3c989469eb13bf8bf41830491a27138fce076164e979582cdd78970 | Python | 5,699 | 196 | # -*- coding: utf-8 -*-
"""Adiabatic Pulse Design functions.
"""
import numpy as np
__all__ = ["bir4", "hypsec", "wurst", "goia_wurst", "bloch_siegert_fm"]
def bir4(n, beta, kappa, theta, dw0):
r"""Design a BIR-4 adiabatic pulse.
BIR-4 is equivalent to two BIR-1 pulses back-to-back.
Args:
n (i... |
8dec963c423136fb811ffd9cc5c240d8f2532883d65579e60bfb57cd36073659 | Python | 5,727 | 155 | """Utilties for translating to/from dask arrays.
NOTE: Using the thread-based dask scheduler is very inefficient with
CloudVolume because CV is pure python and will cause substantial
GIL contention between the dask worker threads. It is HIGHLY
ADVISABLE to use a distributed process scheduler with on... |
4ae878a7dd5d3fe5023c21dd70879945a04865ee848093ff25840ec1f9c3772a | Python | 5,737 | 246 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Oct 21 18:22:23 2021.
@author: spiros
"""
import numpy as np
from pathlib import Path
from scipy.signal import find_peaks
from scipy.ndimage import gaussian_filter1d
import pickle
def my_style():
"""
Create custom plotting style.
Returns... |
990d969444e4aba80c100898e99cb7bba63f991448e449e94d16005d8ebbdf57 | Python | 5,754 | 218 | from typing import Optional
import copy
import re
import weakref
from ....lib import jsonify
from ..sharding import ShardingSpecification, compute_shard_params_for_hashed
import numpy as np
SKEL_MIP_REGEXP = re.compile(r'skeletons_mip_(\d+)')
class PrecomputedSkeletonMetadata(object):
def __init__(self, meta, ca... |
6b0c01c7285e3c98e5c0bd9abe93768af792e011920d39b8da8e5ebc24e639a3 | Python | 5,862 | 207 | import cloudfiles.paths
from collections import namedtuple
from functools import lru_cache
import os
import posixpath
import re
import sys
from .exceptions import UnsupportedProtocolError
from .lib import yellow, toabs
ExtractedPath = namedtuple('ExtractedPath',
('format', 'protocol', 'bucket', 'basepath', 'no_bu... |
6b5ae304fff29c1b922c17a953590c051ea75c788673ac85fdd337df4975259f | Python | 5,871 | 169 | """Utility functions for inspecting and exporting CaImAn CNMF results."""
from __future__ import annotations
from pathlib import Path
import cv2
import h5py
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.sparse import csc_matrix
def load_sparse_component(group: h5py.Group) -> csc... |
8bed8d926d2f64165afa1f10395b8c8099ccce6c84eb7326c6c52d1b6b4e62ad | Python | 5,885 | 180 | import numpy as np
import matplotlib.pyplot as plt
from scipy.io import loadmat
from sklearn import preprocessing
eeg = loadmat(r"./temp/trajectories.mat")
Y1 = eeg['x']
min_max_scaler = preprocessing.MinMaxScaler()
Y = min_max_scaler.fit_transform(Y1)
X1 = Y.copy()
X = X1
memory_factor = 0.5
m = X.shape[0]
n = X.s... |
e8ea5c784aa6dba502ec800c0d4b58731c96957d1a1ff54ec59126e11c935f15 | Python | 5,891 | 160 | import warnings
warnings.simplefilter(action='ignore')
import pycisTopic
pycisTopic.__version__
import pandas as pd
import scanpy as sc
import scipy
import pickle
import numpy as np
from scipy import sparse
import os
# Project directory
projDir = '/home3/ciervo/scMULTIOME/Analisi/'
# Output directory
outDir = projDir... |
3179a0a34eb6bbdb7f847b8a755d78987cf7be4c249bec3ea0eec33893b3b8d0 | Python | 5,940 | 161 | import os
import re
from cloudvolume import paths
from cloudvolume.paths import strict_extract, extract, ExtractedPath
from cloudvolume.exceptions import UnsupportedProtocolError
from cloudvolume import lib
def test_path_extraction():
def shoulderror(url):
try:
paths.strict_extract(url)
assert... |
88a6b73ac9a3a3e30f358b3043263083d39ccedf384696758e36ff37a3bba6bc | Python | 6,017 | 211 | # -*- coding: utf-8 -*-
"""MRI waveform import/export files.
"""
import struct
import numpy as np
__all__ = ["signa", "ge_rf_params", "philips_rf_params", "siemens_rf"]
def siemens_rf(
pulse, rfbw, rfdurms, pulsename, minslice=0.5, maxslice=320.0, comment=None
):
"""Write a .pta text file for Siemens Pulse... |
f496fba9ea63be02a3d6f0b5c969205e354942eb888c355cea45004aa07dbf2b | Python | 6,029 | 181 | """
# Dimensionality transformations
This module contains classes for dimensionality transformations, such as encoders and decoders.
These are to be used in the context where reduced dynamics is sought after,
but only microscopic data is available.
The main classes are `Encoder` and `Decoder`, which are abstract clas... |
b6e5b0b53386c50fe197f6a0b4be3580ddfffd90d4ee503c16a9228bd72bcb26 | Python | 6,114 | 207 | # -*- coding: utf-8 -*-
"""MRI simulation functions.
"""
import numpy as np
import math
from sigpy.mri import epi
__all__ = ['birdcage_maps', 'gradient_echoes', 'diffusion', 'get_subspace']
def birdcage_maps(shape, r=1.5, nzz=8, dtype=complex):
"""Simulates birdcage coil sensitivies.
Args:
shape (t... |
e3105069fe7ea5bfad37a65d5e3daa84a19948d0e2697996928729a2ac0bffef | Python | 6,125 | 193 | import unittest
import numpy as np
import numpy.testing as npt
import sigpy as sp
from sigpy.mri import linop, nlop
if __name__ == "__main__":
unittest.main()
def check_linop_adjoint(A, dtype=float, device=sp.cpu_device):
device = sp.Device(device)
x = sp.randn(A.ishape, dtype=dtype, device=device)
... |
23999bac6775b301b169eb4e02e0be6ecf426b519e806fc6f8fa44612872a39b | Python | 6,144 | 180 | import numpy as np
import matplotlib.pyplot as plt
from scipy.io import loadmat
from sklearn import preprocessing
eeg = loadmat(r"./temp/Bonn_eeg_E_100.mat")
Y1 = eeg['eeg_data']
min_max_scaler = preprocessing.MinMaxScaler()
Y = min_max_scaler.fit_transform(Y1)
# Y = mylorenz(30)
X1 = Y.copy()
X=X1
memory_factor=0.5
... |
3e4a6bbf270ae70fe48feb3439e8384662674689a415d770bb6a0f980aa68f62 | Python | 6,155 | 199 | import unittest
import numpy as np
import numpy.testing as npt
import sigpy as sp
from sigpy import util, linop, nlop
from sigpy.mri import app, sim
if __name__ == "__main__":
unittest.main()
class TestApp(unittest.TestCase):
def shepp_logan_setup(self):
img_shape = [6, 6]
mps_shape = [4, ... |
f3354218c4878638640485aa19bda669f14f1ff47fedc25b456d8cf8b6cccff4 | Python | 6,155 | 225 | from typing import Optional
import re
import weakref
from ....lib import jsonify
from ..sharding import ShardingSpecification, compute_shard_params_for_hashed
import numpy as np
MESH_MIP_REGEXP = re.compile(r'mesh_mip_(\d+)')
class PrecomputedMeshMetadata(object):
def __init__(self, meta, cache=None, config=None... |
1c0a09f4dc6692f85d4691b8f19de2493cd200bcc49b3f76bf1257efb072ac76 | Python | 6,197 | 167 | from airflow.operators.python_operator import PythonOperator
from airflow.utils.weight_rule import WeightRule
from slack_message import task_retry_alert
from igneous_and_cloudvolume import downsample, downsample_for_meshing, ingest_spatial_index, mesh, mesh_manifest, merge_mesh_fragments, create_skeleton_fragments, mer... |
461d45db8586629a5639c5674ff6ab5d758400e49b69fe81f2eceed35cda8b26 | Python | 6,265 | 227 | import copy
from functools import partial
import itertools
import json
import math
import multiprocessing as mp
import os
import platform
import posixpath
import signal
import traceback
import numpy as np
import concurrent.futures
from tqdm import tqdm
from ....lib import (
xyzrange, min2, max2, Vec, Bbox,
sip, ... |
6e50c2561faf0ea6da99691f6a6540cdd80e342742847395d7597df5181edf91 | Python | 6,292 | 233 | import unittest
import numpy as np
import numpy.testing as npt
from scipy.ndimage import gaussian_filter
import sigpy as sp
from sigpy.mri import linop, rf, sim
if __name__ == "__main__":
unittest.main()
class TestPtx(unittest.TestCase):
@staticmethod
def problem_2d(dim):
img_shape = [dim, dim]... |
dc817ad8e424d06e6f8f604c83b76ce8a51ea3172d35f8aafbd9e66b3a692fb2 | Python | 6,292 | 157 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Cobra Biolog ID Aligner (3)
This script aligns reaction IDs in an enzyme-constrained (ec) model with a
reference list of reaction IDs from a Biolog data CSV file. It is designed to
be run from the command line.
The primary use case is to rename exchange reactions ... |
378a7077bb52c9b242132015e43e8b98de0bbfec1d8f39d51ad7517498ea25a8 | Python | 6,307 | 185 | from __future__ import annotations
from seuronbot import SeuronBot
from airflow_api import get_variable, set_variable, run_dag
from bot_utils import replyto, download_json
from bot_utils import extract_bbox, extract_point, bbox_and_center
from nglinks import generate_link
@SeuronBot.on_message("update webknossos par... |
015361881c6338b250a9e0e414876dc46e7eccf7b7ae656f957562d89aa0a26a | Python | 6,343 | 193 | from airflow.operators.docker_plugin import DockerRemovableContainer
from airflow.operators.docker_plugin import DockerWithVariablesOperator
import unittest
from tests.utils.mock_helpers import patch_plugin_file
from datetime import datetime, timedelta
from docker.errors import NotFound, APIError
DAG_ARGS = {
'own... |
830063e7cc9f276483ef0b4ae48ed852deb17c30451a692ed4469855a2042dbf | Python | 6,345 | 188 | """
Find all instances where GoniOwl disagrees with the human decision,
run inference on those images, and save results with confidence-prefixed filenames.
Example:
python disagreement_inference.py \
--model-path ./outputs/checkpoints/20260219_094846_epoch99_binary_batch16.keras \
--img-height 152 --img-widt... |
1e7c4af50c847ea0f7c9dcd770ca5a57ae4c05d6cece4a0d42e0700f56c8ad65 | Python | 6,359 | 161 | # -*- coding: utf-8 -*-
"""
Created on Sun Oct 22 17:16:32 2023
@author: Camille Gontier
"""
# Packages ####################################################################
# Importation of all the required packages
import h5py
import matplotlib.pyplot as plt
import spikeinterface.extractors as se
from probeinterfac... |
c87bcf57bcf5514604adf1fd92e6e16aa3801dd0afb144e7a33cc246a056dfdd | Python | 6,360 | 226 | from typing import Optional, Union
from .annotation import PrecomputedAnnotationSource
from .image import PrecomputedImageSource
from .metadata import PrecomputedMetadata
from .mesh import PrecomputedMeshSource
from .skeleton import PrecomputedSkeletonSource
from .. import get_cache_path
from ...cloudvolume import (
... |
9b74672b26cf421b9537ee7f3d9745a3446c3981e2262d9cfe9eb61fde98ee34 | Python | 6,398 | 189 | import unittest
import numpy.testing as npt
from sigpy import backend, config, fourier, linop, util
from sigpy.mri import nlop
import sigpy as sp
if __name__ == '__main__':
unittest.main()
devices = [backend.cpu_device]
if config.cupy_enabled:
devices.append(backend.Device(0))
class TestNlop(unittest.Test... |
23efc9ceb0e4e4683544f6b587616c2afa9064a76ff552916e1ecebd59a3d2bf | Python | 6,407 | 199 | #! /usr/bin/env python3
import argparse
import pathlib
from dataclasses import asdict, dataclass
from utilities import run_dorado
DEBUG_PRINT = True
SPEED_LOG_STRING = "> Basecalled @ Samples/s:"
@dataclass(slots=True)
class Benchmarker(object):
input_file: str
output_file: str
device: str
iteratio... |
88d501ccbb3a47a6d878b02f8950832bb967cc9397ba39d5f918dbc2e0ffea26 | Python | 6,418 | 173 |
import numpy as np
class Graph_pool():
""" The Graph to model the skeletons of human body/hand
Args:
strategy (string): must be one of the follow candidates
- spatial: Clustered Configuration
layout (string): must be one of the follow candidates
- 'hm36_gt' same with ground t... |
e776c413a4e3855d8b45c2aed7d637fb6c524be8656fd00fc76195408aa7020c | Python | 6,520 | 227 | """Species"""
from typing import Literal, Optional, Union
from pydantic import BaseModel, ConfigDict, Field
from typing_extensions import Annotated
from aind_data_schema_models.registries import Registry
class StrainModel(BaseModel):
"""Base model for a strain"""
model_config = ConfigDict(frozen=True)
... |
2455274fbb9bc3cda450ec3b0b2cfecaefeabcc0ba148896cd2a69388d635833 | Python | 6,547 | 202 | # -*- coding: utf-8 -*-
"""
Created on Mon Jul 7 10:11:04 2025
@author: Usuario
"""
# Masks vs True positive
import os #For importing images and saving figures
import errno # for checking whether the montage direcotry already exists
import matplotlib.pyplot as plt
import numpy as np
from skimage import... |
745e99257d53307c610825261fbdedb4edac3e0b9b44c3404991f592ef7dbe61 | Python | 6,623 | 158 | """Test generator class"""
import unittest
from unittest.mock import patch, mock_open, MagicMock
from pathlib import Path
import pandas as pd
from aind_data_schema_models._generators.generator import generate_code, check_black_version, load_data
import os
TEST_DIR = Path(os.path.dirname(os.path.realpath(__file__)))
... |
637ea752230d9d7a9931026281d684dacf6f001e58ad1dbac1ce57b9d17cf513 | Python | 6,640 | 192 | """
This module implements non-linear least square (nlls) algorithms.
Author: Zhengguo Tan <zhengguo.tan@gmail.com>
"""
import numpy as np
import sigpy as sp
from sigpy import backend, alg, prox, util
class NonLinearLeastSquares(alg.Alg):
"""Abstraction for non-linear least square (nlls) algorithms.
Args:
... |
3860d74bc3d59e82f9e5f47a66f37881cfc6b5e0da7297e9ace0437f880988b4 | Python | 6,668 | 209 | from collections import defaultdict
import errno
import mmap
import os
import sys
import time
import multiprocessing as mp
import numpy as np
from .lib import Bbox, Vec, mkdir
SHM_DIRECTORY = '/dev/shm/'
EMULATED_SHM_DIRECTORY = '/tmp/cloudvolume-shm'
EMULATE_SHM = not os.path.isdir(SHM_DIRECTORY)
PLATFORM_SHM_DIR... |
6b74520bd7ef6ee88e6a5fccb9a520b2db47466eb5e703d23c93fc674fb8f817 | Python | 6,698 | 208 | # This script is part of mousebrains (http://www.github.com/schlegelp/navis-mousebrains).
# Copyright (C) 2020 Philipp Schlegel
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, e... |
27a53a4a652aba18163a61f54db5cc0b4cd3ae607e5bd263a51b4593ee8397c1 | Python | 6,702 | 226 | from typing import Optional, Union, Dict
from collections import defaultdict
import os
import json
from google.oauth2 import service_account
from .lib import mkdir, colorize
HOME = os.path.expanduser('~')
CLOUD_VOLUME_DIR = os.path.join(HOME, '.cloudvolume')
CLOUD_VOLUME_DIR = os.environ.get("CLOUD_VOLUME_DIR", CLO... |
36edc5a1a59030ef81b79890e443dba037d5f7a85252c9678ce050fabd5a6afe | Python | 6,727 | 170 | from __future__ import absolute_import, print_function
from setuptools import setup, find_packages, Extension
from setuptools.command.build_ext import build_ext
from numpy import get_include
from os import path
from glob import glob
def get_numpy_include_dirs():
return [get_include()]
class build_ext_openmp(bui... |
36e3478ba7956df9b3bfcb93c364399a4a8a5551bab8de37dc6011b8aa3fa49e | Python | 6,746 | 168 | import random
import base64
COMPUTE_URL_BASE = 'https://www.googleapis.com/compute/v1/'
INSTALL_DOCKER_CMD = '''
echo ##### Set up Docker #############################################################
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | apt-key add -
apt-key fingerprint 0EBFCD88
add-apt-repositor... |
fb5bfdef21a927a9e79d974073e8fe862431f9c1f0790f972a44e064112a1edb | Python | 6,754 | 176 | import copy
import pathlib
from ont_output_specification_validator import validate_file
from ont_output_specification_validator.errors import ErrorContainer
from ont_output_specification_validator.settings import ExperimentSettings
from ont_output_specification_validator.specification import (
SpecificationBundle,... |
c5e0ce8c4ca52ec67634078931596434888ae1501ce7ed393249545c8c1a3ea3 | Python | 6,756 | 191 | import pytest
import sys
import numpy as np
from cloudvolume.chunks import encode, decode
from cloudvolume import chunks
def encode_decode(data, format, shape=(64,64,64), num_chan=1, level=None):
compression_params = { "level": level }
encoded = encode(data, format, compression_params=compression_params)
resu... |
2654520dc26c736e4200a14765f0c397de0d5b1cf5eb58590d1643ad26e53fef | Python | 6,781 | 203 | from airflow.models import Variable
from airflow.configuration import conf
import os
import time
import traceback
import socket
import json
import base64
import requests
import shutil
from datetime import datetime
import redis
import multiprocessing
from concurrent.futures import ProcessPoolExecutor
from collections im... |
b93f7c759eb4582ef1fbd495c2b5e1c33b42110449b78d073ef8562f68b71458 | Python | 6,785 | 163 | import unittest
import numpy as np
from sigpy import block, config
if config.cupy_enabled:
import cupy as cp
if __name__ == "__main__":
unittest.main()
class TestInterp(unittest.TestCase):
def test_array_to_blocks(self):
xps = [np]
if config.cupy_enabled:
xps.append(cp)
... |
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