sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
668eb5165ceb4c44c57a234ad5abd1a727092403486992faaf444ab35cc8a6b7 | Python | 2,431 | 70 | #!/usr/bin/env python3
"""
This script creates a 3-minute synthetic recording and saves it to SpikeInterface format for testing the pipeline.
Requirements:
- spikeinterface
"""
from argparse import ArgumentParser
import spikeinterface as si
from pathlib import Path
this_folder = Path(__file__).parent
si.set_global_... |
379899ce239ceac54c0c19f3b67fec74d2933bdf8a7accca697fcc91c1177f1c | Python | 2,442 | 104 | # -*- coding: utf-8 -*-
"""
Created on Sat Dec 23 18:42:59 2023
@author: CAG329
"""
# Packages ####################################################################
from brian2 import *
# %matplotlib qt
matplotlib.rcParams.update({'font.size': 13})
# Parameters #######################################################... |
8a95e72f3979db08356fc343e84cb188aa5595b596c14dd82df34abaa84355bf | Python | 2,462 | 81 | import pyvisa
from math import acos
class LaserPowerControl:
def __init__(
self,
port="COM4",
baudrate=921600,
parity=pyvisa.constants.Parity.none,
encoding="ascii",
device=1,
*args,
**kwargs
):
super().__init__(*args, **kwargs)
s... |
bd0c9dca9d211b850f0062360dc96a895649ae54dbaf4f8e405c7b30fde282e4 | Python | 2,464 | 64 | # test flatmap
"""
Unit test for flatmap unit
@author: jdiedrichsen
"""
import unittest
import SUITPy.flatmap as flatmap
import numpy as np
import plotly.graph_objs as go
import nibabel as nb
import matplotlib.pyplot as plt
def test_flatmap_plot(render='plotly'):
ax = flatmap.plot('docs/source/notebooks/MDTB08_Mat... |
a32477edf50c31822e403a5f1cd3d4b33e1c4830f3239cacec34ab7670090423 | Python | 2,483 | 79 | import unittest
import numpy as np
import numpy.testing as npt
from sigpy.mri import rf
if __name__ == "__main__":
unittest.main()
class TestAdiabatic(unittest.TestCase):
def test_bir4(self):
# test an excitation bir4 pulse
n = 1176
dt = 4e-6
dw0 = 100 * np.pi / dt / n
... |
b6b36b4d2ec50c47d8bde92449cd04c1626231d722ab31e616657f4679e7aa00 | Python | 2,500 | 66 | import json
from workers import GenerateWorkers
from manager import GenerateManager
from easyseg_worker import GenerateEasysegWorker
from nfs_server import GenerateNFSServer
from networks import GenerateNetworks
def GenerateConfig(context):
common_ext = f"{context.properties['zone']}.c.{context.env['project']}.in... |
8f6eb0a7088c344e51dcd309cb99d79df923add96393981db1b091c4f00af577 | Python | 2,623 | 92 | import torch
import numpy as np
import torch.nn as nn
import torch.optim as optim
from sigpy.mri import dce
# %%
class DCE(nn.Module):
def __init__(self,
ishape,
sample_time,
R1 = 1.,
M0 = 5.,
R1CA = 4.39,
FA = ... |
2909b2771a0217def75a4471f45b6d4de9c2a10a32966d3857e65e9ba1b40187 | Python | 2,641 | 79 | import time
from dags.google_api_helper import toggle_nfs_server
from seuronbot import SeuronBot
from bot_utils import replyto, extract_command, clear_queues
from airflow_api import get_variable, set_variable, \
check_running, mark_dags_success, run_dag
from bot_info import broker_url
from kombu_helper import drain... |
16015482b7a978555d5c538a6aa6e2fbdf3ff254f6cdf8e7d87df5ce8fbacfbc | Python | 2,669 | 67 | # -*- coding: utf-8 -*-
"""
Created on Sat Dec 9 19:49:52 2023
@author: CAG329
"""
# From https://brian2.readthedocs.io/en/stable/user/plotting_functions.html
# Packages ####################################################################
from brian2 import *
matplotlib.rcParams.update({'font.size': 14})
# Parame... |
f2c7676ec705c54b99e36ebaa1f50671d10b7f73e3308592f7223cd605e95382 | Python | 2,681 | 93 | # %% [markdown]
# # Notebook 03: Tissue thickness mapping
#
# **Paper section:** Results — The cranial neural tube maintains a
# dorso-ventral thickness gradient
# **Paper figures:** Fig. 5
#
# This script quantifies local tissue thickness by measuring the Euclidean
# distance from each vertex on the **basal (outer) su... |
4cc7e72b7d73a34042125fd94aba1b4106298ba48f1ae710d6404b28b5826627 | Python | 2,682 | 78 | import streamlit as st
import py3Dmol
import base64
from rdkit import Chem
from rdkit.Chem import AllChem, Draw
from rdkit.Chem.Draw import rdMolDraw2D
import streamlit_ketcher as sk
def generate_3d_view(smiles, style="stick"):
mol = Chem.MolFromSmiles(smiles)
if mol:
mol = Chem.AddHs(mol) # Add hydro... |
b316673b962aacc0ecc0025ef8d38cbf344052c03e85bab1fffc8f7810e80f62 | Python | 2,706 | 85 | # This script is part of mousebrains (http://www.github.com/schlegelp/navis-mousebrains).
# Copyright (C) 2024 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... |
7ad1e6194de4c254c0358417e6ef7a1652de14e74a0d746233b0a6abc7cdb5ac | Python | 2,722 | 68 | """Unit tests for the Gene model, focusing on GenBank accession ID retrieval."""
import unittest
from pathlib import Path
from unittest.mock import Mock, patch
from aind_data_schema_models.gene import Gene, NucleotideModel
class TestGene(unittest.TestCase):
"""Tests for Gene model"""
def setUp(self):
... |
837e48fc88539e8c4565c81245a0607d614e906768464dc95916e0e670998c7a | Python | 2,724 | 79 | import os
os.environ["JAX_PLATFORM_NAME"] = "cuda"
os.environ["XLA_PYTHON_CLIENT_MEM_FRACTION"] = "0.95"
import jax
jax.config.update("jax_enable_x64", True)
import equinox as eqx
import sys
sys.path.append('..')
sys.path.append('../..')
import hydra
import logging
from omegaconf import DictConfig
from UIDD.traine... |
4cee4d15b09cfe06c5f316e671974e82561edb689731777f5cb9a5b9e3fa22db | Python | 2,744 | 87 | # -*- coding: utf-8 -*-
"""Non-Linear MRI reconstruction applications.
"""
import numpy as np
import sigpy as sp
from sigpy import backend, nlls, fourier
from sigpy.mri import nlop, app, epi
class kinv(nlls.NonLinearLeastSquares):
r"""non-linear mri reconstruction.
Args:
"""
def __init__(self, y, im... |
0fb03f4a2c48285f0af3a2275b9417d6342e99b1133586b8bd6d7928ab30970d | Python | 2,782 | 79 | from airflow.plugins_manager import AirflowPlugin
from datetime import datetime
import logging
import types
import collections
from airflow.models import BaseOperator
from airflow.models import DagBag
from airflow.utils.state import State
from airflow import settings
class MultiTriggerDagRunOperator(BaseOperator):
... |
c57835199030c76a36f8f6ffe28221121b2874ddc8e2b89664bba5c26581ae21 | Python | 2,782 | 74 | from igneous_and_cloudvolume import submit_igneous_tasks, submit_custom_cpu_tasks, submit_custom_gpu_tasks
from airflow import DAG
from airflow.operators.python import PythonOperator
from airflow.utils.weight_rule import WeightRule
from datetime import datetime
from slack_message import task_failure_alert
from helper_o... |
d6987ee82b5fcd1ff1234fd3ed37c312d2df909a263a524a68e041d90ca62b7c | Python | 2,787 | 69 | #!/usr/bin/env python
"""
Convert hypnograms to matlab array.
"""
import numpy as np
from scipy.io import savemat
from example_pipeline.data_io import (
ArgumentParser,
load_dataframe,
check_dataframe,
load_state_vector,
)
def convert_hypnogram_to_mat(file_path_hyp, file_path_mat, mapping, time_res... |
15f15195820fc127b2b8d421f3d11819a45cf950f4dd0e71a6ee2b8a17afa91c | Python | 2,803 | 91 | def GenerateInternalFirewallRules(context, network, sourceRanges):
return [{
'name': f'{context.env["deployment"]}-firewall-internal',
'type': 'compute.v1.firewall',
'properties': {
'allowed': [
{
'IPProtocol': 'tcp',
},
... |
da3bb646b7701ce8ae0e16e7c87cc3d6242e84b386e1047d2e765adc79676086 | Python | 2,804 | 93 | #!/usr/bin/env python3
"""
Make a .keras model compatible with older Keras 3 versions by stripping
unsupported keys like 'quantization_config' from the saved config.
A .keras file is a zip archive containing config.json and weight files.
This script patches config.json in-place so the model loads on older Keras 3.
"""... |
1146b467a807013c39a14d0be62e7b0c835ce1717dc35d2fa3bc220d17ba6056 | Python | 2,815 | 77 | # %%
# Set vedo backend to VTK — required for Jupyter notebooks
from vedo import settings
settings.default_backend = "vtk"
# Import all spatchcocking utilities (includes getTightercmap, getAxis, etc.)
from spatchcocking import *
# %%
# Discover all VTK mesh files in the meshes folder.
# Files are sorted: 3 × HH17 (in... |
a34597e9a9521fa6b127dd56dba4166d081d44ff9958f3932dd88bebc047e12c | Python | 2,857 | 81 | import os
os.environ["JAX_PLATFORM_NAME"] = "cuda"
os.environ["XLA_PYTHON_CLIENT_MEM_FRACTION"] = "0.95"
import jax
jax.config.update("jax_enable_x64", True)
import equinox as eqx
import sys
sys.path.append('..')
sys.path.append('../..')
import hydra
import logging
from omegaconf import DictConfig
from UIDD.trainer... |
d24e78bf9f035f5434d3e238cf092dfd43cd24ee893182ab67a6e0fabb51d486 | Python | 2,860 | 173 | """Module for defining UnitWithValue classes"""
from enum import Enum
from typing import Union
class SizeUnit(str, Enum):
"""Enumeration of Length Measurements"""
M = "meter"
CM = "centimeter"
MM = "millimeter"
UM = "micrometer"
NM = "nanometer"
IN = "inch"
PX = "pixel"
class MassU... |
c9762ecacf2962ad094a4c4c23594b3a526de729bdb94660961ec593d07fa7db | Python | 2,864 | 87 | # -*- 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... |
0d4f5dcccb21d4766ab6e6c12236a770ad516884ffe34e98cecbf793994f02ac | Python | 2,874 | 72 | import sys
import torch
import torch.nn as nn
import torch.nn.functional as F
class ActionHeadClassification(nn.Module):
def __init__(self, dropout_ratio=0., dim_rep=512, num_classes=60, num_joints=17, hidden_dim=2048):
super(ActionHeadClassification, self).__init__()
self.dropout = nn.Dropout(... |
323e0408803b529ce25b6c4e841c15629f9b2120ab3e20471aca3fcc4481fb8f | Python | 2,877 | 97 | import mudata
import os
import scanpy as sc
import anndata
import matplotlib
import matplotlib.pyplot as plt
import adjustText
import numpy as np
import pandas as pd
import pickle
# Function to save an object
def save_object(obj, filename):
with open(filename, 'wb') as f:
pickle.dump(obj, f)
# Fun... |
fbc6f8119c7b28187bf190b32899aa86512d5929c5b6954838d7d065d896ee0a | Python | 2,933 | 92 | """Script to grab protocol information from protocols.IO using the official API.
Requires you set PROTOCOLS_CLIENT_TOKEN environment variable with your API token, from
protocols.io/developers
"""
import re
import requests
import pandas as pd
import os
OUTPUT_CSV = "src/aind_data_schema_models/_generators/models/pro... |
5b4c9128002e550efd6d9883a95028601e7d51321e46a6da4305fcbb39dd7691 | Python | 2,939 | 85 | # %% Imports
import sys
import numpy as np
import matplotlib.pyplot as plt
# %% Parse the command line arguments
args = sys.argv
if len(args) != 5:
raise ValueError("Following arguments need to be given: session, epoch, trial type, quality threshold")
session = args[1]
epoch = args[2]
trialtype = args[3]
quality_... |
a2a9ef9b499cb1d7c82a7c480f2874807efbccd7679d68309cdc4c047abd778f | Python | 2,981 | 72 | import pandas as pd
from rdkit import Chem
from rdkit.Chem import AllChem, Descriptors
import joblib
import tensorflow as tf
from keras.layers import TFSMLayer
class NeuralNetworkPredictor:
def __init__(self):
self.nn_model = TFSMLayer('multi_tasking_model_converted', call_endpoint='serving_defaul... |
f7f1fef2375448146fe2ad96f8a43d1b84e24d74b7dbaae791341b234eb86228 | Python | 2,988 | 79 | #! /usr/bin/env python
"""
Setup script for SUITPy, a python package for cerebellar neuroimaging.
"""
descr = """A python package for cerebellar neuroimaging."""
import sys
import os
from setuptools import setup, find_packages
_SUITPy_INSTALL_MSG = 'See %s for installation information.' % (
'https://suitpy.read... |
5f89dc1856529ce782e31095aa29a8f687e28653b1adb5ff2f75ed7d7b6a2b27 | Python | 3,020 | 80 | import unittest
from numpy import nan
from pandas import DataFrame
from pandas.testing import assert_frame_equal
from tetra.error_display import (
col_match,
find_value_differences,
pretty_print_diffs,
row_match,
)
class TestErrorDisplay(unittest.TestCase):
def setUp(self):
self.headers ... |
c42f12f5734096ec01ba22aa1466d926b0fc4723bc37f3126abe50398089eb1d | Python | 3,035 | 131 | """Diffusion Vector Sets (dvs)
for the use of customized diffusion directions on the scanner
Author: Zhengguo Tan <zhengguo.tan@gmail.com>
"""
import numpy as np
from pathlib import Path
list_CoordinateSystem = ['xyz', 'prs']
list_Normalisation = ['unity', 'maximum', 'none']
def _read_directions(line_str):
lin... |
972465a46fb0f0596c7c578348e319c979b656bb81bf06050e2957a9aed29d1a | Python | 3,041 | 62 | import streamlit as st
def weto_ai_slider(value):
weto_ai_slider = st.slider(label = "slider",
help = """
Set the confidence range for the A.I. Classifier\n\nThe
default confidence range is from 60 to 100.\n\n \n\nSamples will be classified a... |
c173b70337df25be102431e340710e03269b04c0d73c7d8560882cf5eb0425af | Python | 3,043 | 109 | from datetime import datetime, timedelta
def check_worker_image_labels(variable):
from airflow.models import Variable
from docker_helper import pull_image
if variable == "param":
image_name = "WORKER_IMAGE"
default_path = default_seg_workspace
elif variable == "inference_param":
... |
6021f0bf7a6f055ab562a574a38f98792062bbfc6274feb5e58c92e62e8db8cb | Python | 3,056 | 88 | """Module to publish models to docdb"""
import csv
import os
from typing import Iterator, List
from aind_data_access_api.document_db import Client as DocDBClient
from requests import HTTPError
DOCDB_HOST = os.getenv("DOCDB_HOST")
DOCDB_DATABASE = os.getenv("DOCDB_DATABASE")
DOCDB_COLLECTION = os.getenv("DOCDB_COLLEC... |
bceb1fcd01f2d8b8d052ad2cdd42bd78e3d899e0f18cbd6e3e8720351a655aec | Python | 3,064 | 117 | """Neuroglancer link functions."""
import json
import urllib
from typing import Optional, Union
from collections import OrderedDict
from dataclasses import dataclass
from enum import Enum
class LayerType(Enum):
Image = "image"
Segmentation = "segmentation"
@dataclass
class Layer:
name: str
cloudpath... |
197890fefcc3b0d114181a40611232124a3771f22c7e2623e34581e7f902236e | Python | 3,070 | 105 | from airflow.utils.db import provide_session
from cloudfiles.paths import to_https_protocol, ascloudpath, ExtractedPath
def resolve_url(url: str) -> str:
"""Resolves protocol aliases and returns a https url."""
if url.startswith("gs://"):
return url
result = to_https_protocol(url)
if isinstanc... |
c383c568757b53004cdf318dd080d32dd0a11452ac92a38212e1fba928bc043d | Python | 3,076 | 119 | """
# Custom activations
This module contains custom activation functions.
"""
import jax
import jax.numpy as jnp
# ------------------------- Typing imports ------------------------- #
from jax import Array
from jax.typing import ArrayLike
from typing import Callable
# --------------------------------------------... |
73f92fc79fa9580e8b7f52ce2d83b7cda6f8e8dcf2b2773a0b7e70786a275a97 | Python | 3,099 | 113 | import os
import sys
import numpy as np
import cloudvolume.sharedmemory as shm
def test_ndarray_fs():
location = 'cloudvolume-shm-test-ndarray'
array_like, array = shm.ndarray_fs(
shape=(2,2,2), dtype=np.uint8, location=location,
lock=None, emulate_shm=True
)
assert np.all(array == np.zeros(shape=(2,2,2), d... |
eb0fbc23f555a280d145a7f40e85e3b24d92a49445b12e3808baa283808bf7ba | Python | 3,103 | 98 | # -*- coding: utf-8 -*-
"""
Created on Sun Sep 10 07:50:08 2023
@author: CAG329
"""
# Original code from
# https://brian2.readthedocs.io/en/stable/examples/IF_curve_Hodgkin_Huxley.html
# Packages ####################################################################
from mpl_toolkits.axes_grid1.inset_locator import z... |
0bc64ab87a046719101e8b8b47fdb84eb2893cc9f601e30b6460da81ccefc052 | Python | 3,119 | 97 | from typing import Optional, Union
from .mesh import GrapheneMeshSource
from .metadata import GrapheneMetadata
from ..precomputed.image import PrecomputedImageSource
from ..precomputed.skeleton import PrecomputedSkeletonSource
from .. import get_cache_path
from ...cacheservice import CacheService
from ...cloudvolume ... |
a57d02f4419070eaf2924e450a1f6822eb0dceb8cc1e4f061a7e6783b83689a8 | Python | 3,128 | 93 | """Check that sorter params in default_params.json match SpikeInterface defaults.
For each sorter, the keys of its ``sorter`` block are compared (recursively)
against ``spikeinterface.sorters.get_default_sorter_params``:
- Keys present in the pipeline but unknown to SpikeInterface (typos, renamed or
removed params)... |
cc34ff45d70bf155cf626bd3966f2039d067f3c6bc185a1d0afdd5ac8535d322 | Python | 3,159 | 126 | from cloudfiles.exceptions import CompressionError, DecompressionError
from osteoid.exceptions import (
SkeletonUnassignedEdgeError,
SkeletonDecodeError,
SkeletonEncodeError,
SkeletonTransformError,
SkeletonAttributeMixingError,
)
class AuthenticationError(Exception):
"""Incorrect credentials."""
pass
... |
4d1431c8cef761a53940e2cef61c5a80205481ed7c18f154bea27091f7807621 | Python | 3,184 | 86 | import numpy as np
class RankItemEnv:
def __init__(self, n_items: int) -> None:
self.n_items = n_items
self.micro_time = 1
self.code_book = np.eye(n_items,n_items+1)
self.train_pairs = [(i,j) for i in range(n_items) for j in range(n_items) if i!=j]
self.train_label... |
6127568cf0a53028fe628180ec21c6c3355dd5b6dcf43726d9ea6164ce0bfcaa | Python | 3,193 | 81 | import numpy as np
import scipy.special as scipy_special
import nibabel as nib
import os
import sys
import argparse
import ants
def save_img(img, dst, name, ref_img):
fname = '{}/{}.nii.gz'.format(dst, name)
niftiImg = nib.Nifti1Image(img, ref_img.affine)
niftiImg.header['xyzt_units'] = 2 # mm
nib.sa... |
cfd2448887dd151e2d15e717ce6d3c971df6fc916533b601959a00015dcee11f | Python | 3,204 | 94 | import pytest
import os
import json
from layer_harness import delete_layer
from cloudvolume.provenance import DataLayerProvenance, DatasetProvenance
from cloudvolume.storage import Storage
def test_dataset_provenance():
fs = '/tmp/removeme/provenance/'
delete_layer(fs)
prov = DatasetProvenance()
prov.data... |
8e4a0d8bc1916fbb84195a64d62b926afcd689c82c29417def3cd9573653e942 | Python | 3,211 | 109 | """Code generator for data schema models."""
import argparse
from jinja2 import Environment
import pandas as pd
from aind_data_schema_models._generators.dev_utils import to_class_name, to_class_name_underscored
from pathlib import Path
import subprocess
SKIP_SORT = ["mouse_anatomy"]
def check_black_version():
... |
71fe94d8097d79476f8f686f5224246ba0d22b86bd5a227957f3d2868943d68a | Python | 3,228 | 106 | # -*- coding: utf-8 -*-
"""
Created on Sun Sep 10 07:50:01 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... |
2232874083be482d9f51135a5b54b5cdd4f7aa0e71d5352832fb73d8e402279b | Python | 3,240 | 97 | """
A "serverless" Python client for reading and writing arbitrarily large
Neuroglancer Precomputed volumes both locally and on cloud services.
Precomputed volumes consist of chunked numpy arrays, meshes, and
skeletons and can be visualized using Neuroglancer. Typically these
volumes represent one or three channel ... |
8648cf866137c54e79c1c06aff94cefa8d6e629debc5426584eda2bee5b2291b | Python | 3,242 | 114 | # -------------------------------------------------------------
# Subgrid Optimization
# Copyright (c) 2026
# Dirk Keller, Nick Ramsey's Lab, University Medical Center Utrecht, University Utrecht
# Licensed under the MIT License [see LICENSE for detail]
# ----------------------------------------------------------... |
d9b24d058e8a2d28ec90f5b7ab2bd43028744f6071b01d98e1530aa2ab51f424 | Python | 3,262 | 79 | import pandas as pd
import argparse
import sys
import glob
import os
import re
REGEX_SUBCORT = '^(?!lh-|rh-).*'
REGEX_LH = '(SUBJECT.*)|(^lh.*)'
REGEX_RH = '(SUBJECT.*)|(^rh.*)'
def collect_stats(directory, filename):
df = None
for f in sorted(glob.glob('{}/*/{}'.format(directory, filename))):
df_su... |
4adda0a71eb1fd0e13ebd6c78c70f7b279447c3adfb62a94499321301d63d377 | Python | 3,274 | 116 | """Module for defining our data naming conventions"""
from datetime import datetime
from enum import Enum
class RegexParts(str, Enum):
"""Regular expression components to be re-used elsewhere"""
DATE = r"\d{4}-\d{2}-\d{2}"
TIME = r"\d{2}-\d{2}-\d{2}"
DATETIME = r"\d{4}-\d{2}-\d{2}_\d{2}-\d{2}-\d{2}"... |
58bdefaa5ce48e5e5dc4ff4e30200d159d00f2170a853dee0780dcbf38e71fa5 | Python | 3,304 | 119 | import pyvisa
class MotorControl:
def __init__(
self,
port,
baudrate=921600,
parity=pyvisa.constants.Parity.none,
encoding="ascii",
axes=None,
):
self.baudrate = baudrate
self.parity = parity
self.encoding = encoding
self.port = p... |
84155ef30c0bbdae7540f6fa92c009745bdae6b7a09ce0c55708d6514ade7600 | Python | 3,402 | 85 | import os
import shutil
import zipfile
import gdown
# Configuration
# Example URL: https://drive.google.com/file/d/1XyZ.../view
# Extract the long string of letters and numbers; that is your FILE_ID.
FILE_ID = "1UTYNFWWDvkyErYEemTks-va95H3-LqKP"
ZIP_TMP_PATH = "temp_downloaded.zip"
TARGET_DIR = "./"
def download_and... |
43f3a813d75c1baf5b5aadf668dda916d9319c608db29cf94d6730ce734f9712 | Python | 3,425 | 94 | import os
os.environ["JAX_PLATFORM_NAME"] = "cuda"
os.environ["XLA_PYTHON_CLIENT_MEM_FRACTION"] = "0.48"
import jax
jax.config.update("jax_enable_x64", True)
import equinox as eqx
import sys
sys.path.append('..')
sys.path.append('../..')
from utils.data import shrink_trajectory_len
import hydra
import logging
from o... |
0ddaa6f16885a287f5f552b65c30ccb5067d6ed235c2a660ee3aaf028fd04165 | Python | 3,438 | 95 | import os
import pytest
import sys
import numpy as np
from cloudvolume import dask as dasklib
@pytest.mark.skipif(sys.version_info[0] < 3, reason="Python 2 not supported.")
def test_roundtrip_3d():
da = pytest.importorskip('dask.array')
du = pytest.importorskip('dask.utils')
a = da.random.randint(100, size=(3,... |
df9da3b883f3af47669508170e8cb81f33841428972f58b6c24fcd2013792fd8 | Python | 3,447 | 112 | import os
import json
import numpy as np
from tqdm import tqdm
from .lib import mkdir, save_images
class VolumeCutout(np.ndarray):
def __new__(cls, buf, path, cloudpath, resolution, mip, layer_type, bounds, handle, *args, **kwargs):
return super(VolumeCutout, cls).__new__(cls, shape=buf.shape, buffer=np.asfo... |
89ebe8f8ae179e103f52e08f2ad22fe0649c6be340114d37115fb192685192ad | Python | 3,464 | 114 | import os
from http.server import BaseHTTPRequestHandler, HTTPServer
import json
import re
import numpy as np
from tqdm import tqdm
from cloudfiles import CloudFiles
from cloudvolume.lib import Vec, Bbox, mkdir, save_images, yellow
from cloudvolume.paths import ExtractedPath
DEFAULT_PORT = 8080
RANGE_RE = re.com... |
c2b876b08c703e58cabdfe0353579022ca168557f3f35f97ed2617d6ccac3537 | Python | 3,510 | 122 | # -*- coding: utf-8 -*-
"""MRI RF shimming.
"""
import numpy as np
import sigpy as sp
from sigpy import backend
from sigpy.mri import rf as rf
__all__ = ["calc_shims", "init_optimal_spectral", "init_circ_polar"]
def calc_shims(shim_roi, sens, x0, dt, lamb=0, max_iter=50):
"""RF shim designer. Uses the Gerchber... |
f102f71d79576b5ab8f0924c9f958b3b59ec22320f9388913467bebc742c0b9d | Python | 3,510 | 135 | import queue as Queue
import threading
import time
from functools import partial
import boto3
from google.cloud.storage import Client
import tenacity
from .secrets import google_credentials, aws_credentials
from .exceptions import UnsupportedProtocolError
retry = tenacity.retry(
reraise=True,
stop=tenacity.sto... |
caa8589a4c576cf7546000f42b612210c5d63683e202cea6643c11b30e48c680 | Python | 3,524 | 125 | # -*- coding: utf-8 -*-
"""MRI utilities.
"""
import numpy as np
import sigpy as sp
__all__ = ["get_cov", "whiten", "tseg_off_res_b_ct", "apply_tseg"]
def get_cov(noise):
"""Get covariance matrix from noise measurements.
Args:
noise (array): Noise measurements of shape [num_coils, ...]
Returns... |
902bb974f9e2069aabe14c3379602f2639d6fdf07d3d2f1a5bcb1245d84031cb | Python | 3,530 | 119 | from typing import Optional, Union, Iterable
from dataclasses import dataclass
import os
import posixpath
from cloudfiles import CloudFiles
import numpy as np
import numpy.typing as npt
from .metadata import PrecomputedAnnotationMetadata
from ....cacheservice import CacheService
from ....paths import strict_extract... |
148dc42533b6be50c0f7036e6f98b18d3ed42275d8433f928585e3313af0de73 | Python | 3,545 | 92 | import pendulum
from airflow import DAG
from airflow.operators.python import PythonOperator
metrics_default_args = {
'owner': 'seuronbot',
'depends_on_past': False,
'start_date': pendulum.datetime(2019, 2, 8),
'catchup': False,
'retries': 3,
}
def format_uptime(dt):
for attr in ["weeks", "day... |
472138b842e5f2e489a0b46402288b6939b6cd1464f662fc580b662f05f9a035 | Python | 3,548 | 122 | # -------------------------------------------------------------
# Channel Elimination
# Copyright (c) 2024
# Dirk Keller, Nick Ramsey's Lab, University Medical Center Utrecht, University Utrecht
# Licensed under the MIT License [see LICENSE for detail]
# -----------------------------------------------------------... |
c5b1ca29696f43b6ec95590abddfe2d613a78d785fbacc84baae5e0bb2ac0f3e | Python | 3,550 | 122 | import unittest
import numpy as np
import numpy.testing as npt
from sigpy import linop, prox, util
if __name__ == "__main__":
unittest.main()
class TestProx(unittest.TestCase):
def test_L1Reg(self):
shape = [6]
lamda = 1.0
P = prox.L1Reg(shape, lamda)
phase = np.exp(1j * np.... |
9916f41523527af97444dbcd648c8c54af07a5bddefaa2d7cff5b0163a914e89 | Python | 3,554 | 131 | import pickle
import unittest
import numpy as np
import numpy.testing as npt
from sigpy import backend, util
if __name__ == "__main__":
unittest.main()
class TestUtil(unittest.TestCase):
def test_device(self):
device = backend.Device(-1)
pickle.dumps(device)
def test_dirac(self):
... |
8cd825a172dcd183285c342003cee0471597709638762c4d645f017fc9f2d2d5 | Python | 3,556 | 79 | import torch
import torch.nn as nn
class SimpleTemporalModel(nn.Module):
def __init__(self, num_joints_in, in_features, output_dim, filter_widths, dropout=0.25, channels=1024, task='classification'):
"""
A simplified temporal model with 1D convolutions and adaptive average pooling.
... |
a220ab1481b5dbd34b988cb6bbf6d4fba34941bd540aa55df5a3c62463618808 | Python | 3,580 | 87 | """Test mouse anatomy class methods"""
import unittest
from unittest.mock import patch
from aind_data_schema_models.mouse_anatomy import search_emapa_exact_match, get_emapa_id
from aind_data_schema_models.mouse_anatomy import MouseAnatomy, MouseAnatomyModel, Registry
class MouseAnatomyTests(unittest.TestCase):
... |
6c8f3c6c963e591c73ea972167c98350939d2256a9713e91956bef1dca99939f | Python | 3,590 | 120 | # -*- coding: utf-8 -*-
"""Optimal Control Pulse Design functions.
"""
from sigpy import backend
__all__ = ["blochsim", "deriv"]
def blochsim(rf, x, g):
r"""1D RF pulse simulation, with simultaneous RF + gradient rotations.
Assume x has inverse spatial units of g, and g has gamma*dt applied and
assume x ... |
b889e9f14d3a736d34fb0cd219a1944882494e6802aba14275c7098c5019b844 | Python | 3,635 | 127 | # -*- coding: utf-8 -*-
"""
Created on Mon May 27 14:28:36 2024
@author: CAG329
"""
# Packages ####################################################################
from brian2 import *
# %matplotlib qt
matplotlib.rcParams.update({'font.size': 13})
# Parameters #######################################################... |
8164ff72d879cad6601b74b0194c4d3c5df2be26c8afbc37bd8259bdfab6e2aa | Python | 3,665 | 165 | import sys
from tqdm import tqdm
from .lib import totalfn
from .threaded_queue import ThreadedQueue, DEFAULT_THREADS
def schedule_threaded_jobs(
fns, concurrency=DEFAULT_THREADS,
progress=None, total=None
):
if total is None:
try:
total = len(fns)
except TypeError: # generators don't have... |
0e876dbd4d041ae805e48470b9fecb200c593a12a6e63fe0bcb161765cfac296 | Python | 3,670 | 106 | #!/usr/bin/env python
"""
Using a pre-trained model, and given the preprocessed signal
arrays, compute the probability of each state for each sample in the
signal array.
"""
import numpy as np
import matplotlib.pyplot as plt
from somnotate._automated_state_annotation import StateAnnotator
from somnotate._utils impo... |
f47bb1013bef770b40153a8b4c463d953e90830f31d2058d92c9f04b6d632b80 | Python | 3,671 | 124 | import math
import numpy as np
from ...lib import Vec, Bbox
def content_type(encoding):
if encoding == 'jpeg':
return 'image/jpeg'
elif encoding == 'png':
return 'image/png'
elif encoding == 'jxl':
return 'image/jxl'
elif encoding in ('compresso', 'compressed_segmentation', 'fpzip', 'kempressed',... |
e6ae217be7bbfaebffa01b2334e53143874850eba855535dfb52394eb955f669 | Python | 3,705 | 92 | import nibabel as nib
import numpy as np
import os
import argparse
import torch
from HD_BET.run import run_hd_bet
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Brain extraction (skull-stripping) using HD-BET.')
parser.add_argument(
'--mp2rage-inv2',
type=str,
... |
fa60210e196ab02c57922a940b0f793ab2be86b8ce2e9e1cd2314fc84585934d | Python | 3,709 | 114 | # -*- 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... |
49624692cd607af574d8cfdf815ac9e8e9aa1d8e3df0b9b2538b25c38dd9b685 | Python | 3,720 | 138 | import os
import setuptools
import sys
def read(fname):
with open(os.path.join(os.path.dirname(__file__), fname), 'rt') as f:
return f.read()
def requirements():
with open(os.path.join(os.path.dirname(__file__), 'requirements.txt'), 'rt') as f:
return f.readlines()
EM_CODECS = [
"imagecodecs",
"simpl... |
a4b74ac94b7be58d5736f25048b0439594e49d0c1fa0dcc33e02110faad06bbc | Python | 3,720 | 132 | """
Methods for DICOM loading, extraction and saving.
Author: Zhengguo Tan <zhengguo.tan@gmail.com>
"""
# %%
import numpy as np
import os
import pydicom
import os.path
import sys
sys.path.insert(0, os.path.join(os.environ['BART_PATH'], 'python'))
import cfl
from optparse import OptionParser
# __all__ = ['extract_e... |
87fa3cbdb020e995c9ecf6c3a05f48c736be8d1d511b6f3855c0c43bd00c9806 | Python | 3,724 | 100 | import os
import subprocess
import sys
from datetime import datetime
psutil_available = True
try:
import psutil
except ImportError:
print("CPU monitoring unavailable")
psutil_available = False
VERBOSE = False
def get_process_priority(pid: int) -> str:
if psutil_available:
return str(psutil.P... |
f3c5b3237097eab9bb3f7b9d7a1906c9228e56b286e8f9efbf80cddb209be969 | Python | 3,729 | 127 | """SDE utilities"""
import jax
import jax.numpy as jnp
import equinox as eqx
from diffrax import (
diffeqsolve,
ControlTerm,
Euler,
ItoMilstein,
MultiTerm,
ODETerm,
SaveAt,
VirtualBrownianTree,
)
import sys
sys.path.append('../..')
from UIDD._utils import default_floating_dtype
# ----... |
5e29624d8076059fba92612075faeaaa115a26c106fc1f5021a950435b47072d | Python | 3,760 | 91 | from worker_op import worker_op
from airflow.utils.weight_rule import WeightRule
from datetime import timedelta
from param_default import default_args, cmd_proto, default_mount_path, default_seg_workspace
from slack_message import task_retry_alert
import os
def composite_chunks_wrap_op(img, dag, config_mounts, queue,... |
00c888080c72a46009cb7d9837e714da18b1172c91d47077f7b31aaf0a53d828 | Python | 3,775 | 109 | # %% [markdown]
# # Notebook 04: pHH3+ mitotic cell density mapping
#
# **Paper section:** Results — Spatial patterns of mitotic activity are
# preserved across global expansion
# **Paper figures:** Fig. 6
#
# This script maps the local density of pHH3+ mitotic cells onto the
# basal surface mesh.
#
# **Method:**
# 1. ... |
088e7b49f27f690829be70980e52eb5df13310241920b7ba7552fbbc9b78eb1c | Python | 3,782 | 181 | """Device enums for data schema"""
from enum import Enum
class ImagingDeviceType(str, Enum):
"""Imaginge device type name"""
BEAM_EXPANDER = "Beam expander"
SAMPLE_CHAMBER = "Sample Chamber"
DIFFUSER = "Diffuser"
GALVO = "Galvo"
LASER_COMBINER = "Laser combiner"
LASER_COUPLER = "Laser co... |
68117a4dd12bb0fbf62dafa79f852f7eacd61ee048b278489744c58c3b798139 | Python | 3,792 | 89 | import unittest
from data_paths import ROOT_DIR, REFERENCE_FOLDER
from tetra.compare_platforms import PlatformCompare, SpecialCase, compare_platforms
class TestCompareData(unittest.TestCase):
def test_compare_platforms(self):
"""
This compares test results from different platforms. As new tests a... |
fbf0a51cef48a006835993c60a34a9184b249e86bca1574c6acf9bd1d165a332 | Python | 3,815 | 105 | import pathlib
from dataclasses import dataclass
from tetra.data_frame_utils import load_sorted_data_frame
from tetra.error_display import pretty_print_diffs
@dataclass(slots=True)
class SpecialCase:
pattern: str
tolerance: float | None
@dataclass(slots=True)
class PlatformCompare:
reference_path: path... |
c5846b6520005ae58df06957076edd1d952d510d2c93a4b1caead86f9dcbfde8 | Python | 3,846 | 91 | """Test human developmental stage class methods"""
import unittest
from unittest.mock import patch
from aind_data_schema_models.human_developmental_stage import search_hsapdv_exact_match, get_hsapdv_id
from aind_data_schema_models.human_developmental_stage import (
HumanDevelopmentalStage,
HumanDevelopmentalS... |
c2404e598748bf50b23e3318b9c7ee9127483108b075522ef65d90a249bac7ba | Python | 3,856 | 159 | import python_jsonschema_objects as pjs
import orjson
import json5
dataset_provenance_schema = {
"$schema": "http://json-schema.org/draft-04/schema#",
"id": "DatasetProvenance",
"title": "Dataset Provenance",
"description": "Represents a dataset and its derived data layers.",
"required": [
"dataset_name"... |
92403efe0fc3eeff41b22799f09a2d4692132d232a2eca79669ca7ef257c534d | Python | 3,861 | 91 | """Test mouse developmental stage class methods"""
import unittest
from unittest.mock import patch
from aind_data_schema_models.mouse_developmental_stage import search_mmusdv_exact_match, get_mmusdv_id
from aind_data_schema_models.mouse_developmental_stage import (
MouseDevelopmentalStage,
MouseDevelopmentalS... |
860b065971540628976eb10d74edcfe7973bde43a0a583e12f9f0feacef122a8 | Python | 3,888 | 100 | # Compute a version number from a git repo or archive
# This file is released into the public dodls-python3-release. Generated by:
# versiongit-2.1 (https://github.com/dls-controls/versiongit)
import re
import sys
from pathlib import Path
from subprocess import STDOUT, CalledProcessError, check_output
# These will be... |
eed77f4f5fed76b36d7515a0be0c43be8d0dab230ee0fa7cba75709fe0dc1003 | Python | 3,896 | 91 | """Test C. elegans developmental stage class methods"""
import unittest
from unittest.mock import patch
from aind_data_schema_models.celegans_developmental_stage import search_wbls_exact_match, get_wbls_id
from aind_data_schema_models.celegans_developmental_stage import (
CElegansDevelopmentalStage,
CElegansD... |
718e6f1d30410bb39f05d67d8dd4164b80f4dbfbf44d4c7b749d44213a8a86da | Python | 3,907 | 101 | from cothread import catools
from softioc import builder
import tensorflow as tf
from tensorflow import keras
import cv2
from io import BytesIO
import urllib
from time import sleep
import numpy as np
import datetime
try:
import epicscorelibs.path.cothread
except ImportError:
pass
# 20250714-111015_epoch20_bi... |
79aac8a1cb1a17cf7a8e9ffdab068782bc043c0db6c6d4f88e1a5bddb013d34f | Python | 3,908 | 91 | """Test drosophila developmental stage class methods"""
import unittest
from unittest.mock import patch
from aind_data_schema_models.drosophila_developmental_stage import search_fbdv_exact_match, get_fbdv_id
from aind_data_schema_models.drosophila_developmental_stage import (
DrosophilaDevelopmentalStage,
Dro... |
6e3fb9b2b62d0f891ddecb2431453456bf905fcf4e7961f33c8ec1cce422aadf | Python | 3,940 | 108 | # -*- coding: utf-8 -*-
"""
Created on Wed Mar 18 15:25:03 2026
@author: simon
"""
import numpy as np
import matplotlib.pyplot as plt
from plotting_functions import my_style
from matplotlib.gridspec import GridSpec
import seaborn as sns; sns.set_theme()
import pickle
import pandas as pd
import pingouin ... |
55b647cae90855a481c5bb6662764b42907a28b8ae6e694fa4b0e333992cc660 | Python | 3,947 | 101 | #!/usr/bin/env python
"""
Truncate manual state annotations and preprocessed datasets to a given (start, stop) interval.
Truncated files will have the same name as the original apart from a suffix noting the start and stop time points.
"""
import numpy as np
import matplotlib.pyplot as plt
import pathlib
from somnot... |
c0c57881a6ed81205bf2d065f3c8b78687cbdee7f8123dce6d2dac2e00197e2f | Python | 3,999 | 135 | # -*- coding: utf-8 -*-
"""Functions for interoperability between sigpy and pytorch."""
import numpy as np
from sigpy import backend, config
__all__ = ["to_pytorch", "from_pytorch", "to_pytorch_function"]
def to_pytorch(array, requires_grad=True): # pragma: no cover
"""Zero-copy conversion from numpy/cupy arra... |
a6397a33e6460633b46dfaf5c229b4c4821e45c2641ebf3cdbda261ac56cd037 | Python | 4,016 | 135 | import unittest
import numpy as np
import numpy.testing as npt
import sigpy as sp
import sigpy.mri.rf as rf
if __name__ == "__main__":
unittest.main()
class TestSlr(unittest.TestCase):
def test_st(self):
# check to make sure profile roughly matches anticipated within d1, d2
N = 128
... |
7d2f0df3476b57a5788d7259354d517a00aae39d5aa3a396d6a255992ee41c29 | Python | 4,031 | 138 | from cloudfiles import CloudFiles
from cloudvolume.datasource.precomputed.metadata import PrecomputedMetadata
from cloudvolume.lib import jsonify, Vec, Bbox
from ...provenance import DataLayerProvenance
class N5Metadata(PrecomputedMetadata):
def __init__(self, cloudpath, config, cache, info=None):
# some ... |
5c3c6a04605f9cc9d4c1d7f333ab0e414a2ee69870178fc950242ad5be212e63 | Python | 4,058 | 126 | # -*- coding: utf-8 -*-
"""
Created on Fri Nov 4 16:15:55 2022
@author: spiros
"""
import os
import brian2
import numpy as np
import pathlib
# Get the path of the current script
base_path = pathlib.Path().resolve().parent
def theta_prob(spike, f_theta, phi_theta):
"""
Theta-like probab... |
68237220c449fa6512f92b828aa1dc500b9cb1f5b23d2bd893c1d4f4f33d51ec | Python | 4,096 | 126 | """
Generate a histogram of average image intensity for all images in a directory tree.
Also writes a CSV with per-image averages and summary statistics.
Useful for determining high/low values for over/under exposed images
Example:
python intensity_histogram.py \
--input-dir ./outputs/disagreements \
--outpu... |
86bf72c06841b7988daa4a751eb0a0392477ef86eabf4f0e6adea151f541c302 | Python | 4,197 | 109 | import sys
import re
import logging
import json
import shutil
import time
from pathlib import Path
import numpy as np
from aind_data_schema.core.quality_control import QualityControl
data_folder = Path("../data")
results_folder = Path("../results")
logging.basicConfig(level=logging.INFO, stream=sys.stdout, format... |
4c5a4896128a2cbefa36640f98a0e04886eb60733d26415cca6d7d423dc8ad07 | Python | 4,219 | 89 | import pandas as pd
import glob
import os
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
dodgy_data = []
dodgy_data.append("2024-08-01-09-02-27")
dir = "/dls_sw/i23/logs/GoniOwl"
start_date_cutoff = "2023-01-01" # Only process files from this date onwards (YYYY-MM-DD format)
csvs = glob.glob(os.pa... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.