sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
63c79b72ec965cc4eb0848dd63d0ebb65b1b5cd437dfd162519243ebe98ef851 | Python | 1,139 | 32 | from lips.benchmark.airfransBenchmark import AirfRANSBenchmark
from lips.dataset.airfransDataSet import AirfRANSDataSet, extract_dataset_by_simulations
import dill
import os
import numpy as np
import json
ROOT = "."
DIRECTORY_NAME = os.path.join(ROOT, 'Dataset')
BENCHMARK_NAME = "Case1"
LOG_PATH = os.path.join(ROOT,... |
a59f7d006174fb069705d51f17dd104e6ede95ed76efcfd4b9e1397aa56ab808 | Python | 1,139 | 44 | # For this you need matlab and the new requirements.txt
import argparse
import matlab
import matlab.engine
import scipy.io
from oset.ecg.peak_detection.peak_det_amp_threshold import (
peak_det_amp_threshold,
)
import unit_test as testing
mat = scipy.io.loadmat("../../../datasets/sample-data/SampleECG1.mat")["dat... |
651a5c04b8c09670cda894a86cb5fb053fd19ee56b557447f2c2855b7e4a97c6 | Python | 1,140 | 28 | """Custom auth so `langgraph dev` knows which user a run belongs to.
The handler maps the `x-user-id` header to a user identity. That identity is
what `graph_factory.make_graph` reads off `runtime.user` and mints an MCP token
for, so each run talks to the fleet as its own user. A real deployment
validates a credential... |
7303b03eeeee5e72ee0e1fce304ef97de3a62009e2fd8dc1d9f4a06360a4f6d6 | Python | 1,140 | 47 | import numpy as np
import nibabel as nib
from time import time
from dipy.data import get_sphere
from dipy.reconst.shm import real_sh_tournier
from dipy.reconst.shm import calculate_max_order
def main(sh_fname, sh_norm_fname):
sh_img = nib.load(sh_fname)
sh = sh_img.get_fdata()
affine = sh_img.affine
... |
7269c21cd649be96c544047e3b9bbd74d4c00132842b530ce9f230f3e69a361d | Python | 1,141 | 43 | # -*- coding:utf-8 -*-
import argparse
import csv
from rdkit import Chem
import preprocess_ea_data as ped
def process_reaction(line, ofile, flavor_db):
row = line.split(" ")
smiles = row[0].split(">")
flag = False
for s in smiles:
mols = []
try:
ped.get_mols_without_h(s, mol... |
75c212f6c97830e5751a8ea6db409cf0e23feeeab11ae1be328b32cca4a4d1a6 | Python | 1,141 | 50 | # Copyright (c) 2021, David Williams, Reza Sameni
# All rights reserved.
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import scipy.linalg as la
from SynchPhaseTimes2 import SynchPhaseTimes2
def PiCA(x,peaks,varar... |
6557bb81f8b7fea8eb4bab7c0783d73794ae2d89e3affe58fa6d55b1d6a41914 | Python | 1,142 | 45 | from langchain_core.runnables import __all__
EXPECTED_ALL = [
"chain",
"AddableDict",
"ConfigurableField",
"ConfigurableFieldSingleOption",
"ConfigurableFieldMultiOption",
"ConfigurableFieldSpec",
"ensure_config",
"run_in_executor",
"patch_config",
"RouterInput",
"RouterRunn... |
8f075a9c3ab38d6ed82c62adcb8de964043c4dc67d21702c2b473f7253560181 | Python | 1,142 | 34 | import argparse
import trimesh
def convert_stl_to_obj(input_stl_path, output_obj_path):
"""Convert STL file to OBJ format and check mesh validity."""
# 加载STL文件
mesh_data = trimesh.load_mesh(input_stl_path)
# 检查网格是否封闭（水密性）
if not mesh_data.is_watertight:
print("Warning: The mesh is not wate... |
2858a7f00e2c6b34bbe89800b2d91a50b76e4d0efbb3ef9fed625e1923fccf12 | Python | 1,143 | 49 | """
Usage: python merge_fc.py --fc_dir <fc_dir>
"""
import argparse
import os
from functools import reduce
import pandas as pd
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
'--fc_dir',
help='Path to the directory containing the feature count files',
required=Tru... |
83135cf5c7d780d4e8b77f5c94f529daf9941e71d1c643be490f510df6b22c68 | Python | 1,143 | 19 | """This package contains the classes and subclasses used to create the plants that a model will be trained to control.
Plants are implemented as subclasses of the :class:`motornet.plants.plants.Plant` object. They all contain a single
:class:`motornet.plants.skeletons.Skeleton` and :class:`motornet.plants.muscles.Muscl... |
c553ec1bd2451645b6f7ce49acdc63484a70e3ab865e7e2dfb186747a15b6808 | Python | 1,143 | 37 | """
scaden Main functionality
Contains code to
- process a training datasets
- train a model
- perform predictions
"""
# Imports
import tensorflow as tf
from anndata import read_h5ad
from scaden.model.functions import get_signature_genes, preprocess_h5ad_data
"""
PARAMETERS
"""
# ===================================... |
402648af94ff983022d0d8841ddb64b0793c1aa0390075261907c353f122f286 | Python | 1,144 | 40 | from .BIF import BIFReader, BIFWriter
from .LGBNJSON import LGBNJSONReader, LGBNJSONWriter
from .NET import NETReader, NETWriter
from .PomdpX import PomdpXReader, PomdpXWriter
from .UAI import UAIReader, UAIWriter
from .XDSL import XDSLReader, XDSLWriter
from .XMLBeliefNetwork import XBNReader, XBNWriter
from .XMLBIF i... |
8c4fa03ccee9202fc0021fd119dff8fb148607f01d847c31fbf15a6c8a1a86f4 | Python | 1,144 | 55 | import torch
from torch import nn
from neuralpredictors.old_constraints import positive
class GradientMixin:
"""
Test whether the constrain correctly switches off the gradient for tensors and parameters.
When subclassing, you need to implement a function
```
@staticmethod
def apply_constrai... |
46e0e77a2ef9cd86a94d3968f7d135e74b072e189b6fddefb84056bfeccbf807 | Python | 1,145 | 38 | from typing import TYPE_CHECKING, Any
from langchain_classic._api import create_importer
if TYPE_CHECKING:
from langchain_community.callbacks.mlflow_callback import (
MlflowCallbackHandler,
MlflowLogger,
analyze_text,
construct_html_from_prompt_and_generation,
)
# Create a way... |
66c89db0b517d1bcf10c342c33b1c7a33e583253943347938b1b16bf2172009d | Python | 1,145 | 36 | from typing import TYPE_CHECKING, Any
from langchain_classic._api import create_importer
if TYPE_CHECKING:
from langchain_community.chains.graph_qa.neptune_sparql import (
INTERMEDIATE_STEPS_KEY,
SPARQL_GENERATION_TEMPLATE,
NeptuneSparqlQAChain,
extract_sparql,
)
# Create a wa... |
f4ed686194f7ab73366804141764528bb67d8ec0ae7985debb3c31af8efc9b8a | Python | 1,146 | 35 | """ Package providing miscellaneous functionalities such as datsets, input-output, visualization, profiling methods ...
:Version:
1.1.0
:Date:
19.03.2017
:Author:
Jan Melchior
:Contact:
JanMelchior@gmx.de
:License:
Copyright (C) 2017 Jan Melchior
... |
78048ba347a278ab4460c4b35fe3475afecc0be60ff9fd94d1b9a264a08afaaf | Python | 1,147 | 23 | # MIT License
# Copyright (c) 2023 The embanded authors
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, ... |
82fe493fc7ec37db8de9fd7ceffdbb7755fe2da4883a20e591008dd61c2d0bba | Python | 1,147 | 40 | """This module provides dynamic access to deprecated Jira tools.
When attributes like `JiraAction` are accessed, they are redirected to their new
locations in `langchain_community.tools`. This ensures backward compatibility
while warning developers about deprecation.
Attributes:
JiraAction (deprecated): Dynamical... |
8e4817f26d61e9a7dc4d3529c31ed6bbc26bc7d37c62dba3ed4f81f0eee84d9c | Python | 1,147 | 30 | from data import generate_recog_data_batch, generate_recog_data
from networks import VanillaRNN
from plotting import plot_recog_generalization, plot_train_perf
#%%
d=25
N=625
R = [3,6]
gen_data = lambda: generate_recog_data_batch(T=500, d=d, R=R, P=0.5, batchSize=1, multiRep=False)
dims = [d,N,1]
net = Van... |
06cca965f76fdad26b1b7ddba614f55bd6e6fe1f333dc58e1653da22c9456188 | Python | 1,148 | 36 | from typing import TYPE_CHECKING, Any
from langchain_classic._api import create_importer
if TYPE_CHECKING:
from langchain_community.utils.ernie_functions import (
FunctionDescription,
ToolDescription,
convert_pydantic_to_ernie_function,
convert_pydantic_to_ernie_tool,
)
# Crea... |
4cbe5dba0bd1292c3a77816ef1a640934022c1448e4bc7aeb2ce439af6a5d610 | Python | 1,148 | 41 | from typing import Any
from typing import Dict
from typing import Optional
import torch
from neuralpredictors.layers.readouts import MultiReadoutBase
from torch import nn
from .core import Core2d
from .nonlinearity import NonLinearity
class Model(nn.Module):
def __init__(
self,
core: Core2d,
... |
f679538b2a58903c99c2a65306f21adbfa4e9e854286765fdb4322cafb17b278 | Python | 1,149 | 33 | #!/usr/bin/env python
import os
import gzip
import tempfile
class CombinedFragmentFiles:
def __init__(self, files, chromosomes, barcodes = None):
self.files = files
self.chromosomes = chromosomes
self.barcodes = barcodes
def __enter__(self):
self.tempfile = tempfile.Named... |
35297ff10f5a496a8676f17b7363724af3b1f82a76662a95f5ba71691d5d1a65 | Python | 1,152 | 30 | from langchain_core.prompts.prompt import PromptTemplate
_CREATE_DRAFT_ANSWER_TEMPLATE = """{question}\n\n"""
CREATE_DRAFT_ANSWER_PROMPT = PromptTemplate(
input_variables=["question"], template=_CREATE_DRAFT_ANSWER_TEMPLATE
)
_LIST_ASSERTIONS_TEMPLATE = """Here is a statement:
{statement}
Make a bullet point list... |
8c054335f299d748e4c681e3c5e0ecd1779506d6defed922e3aa45b662864699 | Python | 1,152 | 45 | # For this you need matlab and the new requirements.txt
import argparse
import matlab
import matlab.engine
import numpy as np
import scipy.io
from oset.ecg.peak_detection.peak_det_pan_tompkins import (
peak_det_pan_tompkins,
)
import unit_test as testing
mat = scipy.io.loadmat("../../../datasets/sample-data/Samp... |
6837b760313805e889b06dbf812f204c37d2e0ebe702523eaedd42fc318f6b7b | Python | 1,153 | 30 | import argparse
import cwas.factory
import pytest
from cwas.runnable import Runnable
def test_make_class_name():
assert cwas.factory.make_class_name("categorization") == "Categorization"
assert cwas.factory.make_class_name("annotation") == "Annotation"
assert cwas.factory.make_class_name("burden_test") =... |
f71436d78631e074cfaf33b6ae86514144fd8894a3335ee8e60091a87b2c554b | Python | 1,155 | 36 | import os
import csv
import torch
from validate import validate
from networks.resnet import resnet50
from options.test_options import TestOptions
from eval_config import *
# Running tests
opt = TestOptions().parse(print_options=False)
model_name = os.path.basename(model_path).replace('.pth', '')
rows = [["{} model t... |
14aacbce18abbb2ba201df720c36aa21f550b5189df7d348686ac9aa8e023409 | Python | 1,156 | 44 | from __future__ import annotations
import numpy as np
class Hebb:
def __init__(self, parameter: np.ndarray, lr: float) -> None:
self.parameter = parameter
self.mask = (self.parameter != 0) * 1
self.lr = lr
def fit(self, pre: np.ndarray, post: np.ndarray) -> None:
dw = np.dot... |
4fc51b22ec5b96723a072870f81300cf041c6c1e70c3737a06232a309c52e897 | Python | 1,156 | 32 | """Prompt for the router chain in the multi-prompt chain."""
MULTI_PROMPT_ROUTER_TEMPLATE = """\
Given a raw text input to a language model select the model prompt best suited for \
the input. You will be given the names of the available prompts and a description of \
what the prompt is best suited for. You may also r... |
c64e73b6aca464974d05fcb299d0620093cb61eb75307fa9c73f366396da9533 | Python | 1,156 | 24 | from langchain_core.prompts.prompt import PromptTemplate
_DEFAULT_ENTITY_SUMMARIZATION_TEMPLATE = """You are an AI assistant helping a human keep track of facts about relevant people, places, and concepts in their life. Update the summary of the provided entity in the "Entity" section based on the last line of your co... |
4a782fe5217037882033fd0446b501ea6a8ce0ce62a1f23de7ec4d47c1066e60 | Python | 1,157 | 42 | # import built-in modules
import argparse
import os
import glob
import shutil
from time import time
from pathlib import Path
from tqdm import tqdm
import pandas as pd
# import local modules
from sscd_libs.helpers import (
boolean_string,
clean_output_dir,
unpack_for_string,
query_yes_no
)
from s... |
c04002c15dc6ebc2c642f0804c3a7e1ae2f77dc0ba9e007844ec78259dc3b224 | Python | 1,157 | 42 | from langchain_core.callbacks import __all__
EXPECTED_ALL = [
"RetrieverManagerMixin",
"LLMManagerMixin",
"ChainManagerMixin",
"ToolManagerMixin",
"Callbacks",
"CallbackManagerMixin",
"RunManagerMixin",
"BaseCallbackHandler",
"AsyncCallbackHandler",
"BaseCallbackManager",
"B... |
d56cb14af5a824f589d13947ed07ee2e81f226297d4a8dac57747368616f2678 | Python | 1,158 | 39 | #! /usr/local/bin/python
#'#################################################################################
#'#################################################################################
#' Transform hdf5 data to list with input for biodnn model
#'#################################################################... |
d870aad36a110ead42cd3ed190e429b77d7b028a48be19cc083da35b72c75eee | Python | 1,158 | 41 | import numpy as np
import struct
def writemda(X, fname, dtype="int16"):
'''Python implementation of .mda file write function
About MDA files: http://magland.github.io//articles/mda-format/
Currently only supporsts <int16> format export
'''
# confirm number of dimensions of array
# TODO ha... |
4d7f2e4cc915d6a6fb1af8b72d10ad21d287aaa4add6a3899141c477f55b7ca3 | Python | 1,160 | 42 | #!/bin/env python3
import voxcell as vc
import numpy as np
import sys
hierarchy_json = sys.argv[1]
brain_regions_nrrd = sys.argv[2]
output = sys.argv[3]
include = []
if len(sys.argv) > 4:
include = sys.argv[4]
include = include.split(",")
exclude = []
if len(sys.argv) > 5:
exclude = sys.argv[5]
excl... |
4d5754b891497727dc72564fe89612e53d311f2be1521963f39a9870e001769d | Python | 1,162 | 28 | # Generated by Django 3.1.4 on 2022-05-11 19:55
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Analysis',
fields=[
('id', models.AutoField... |
d8ac97c5e8fcf16ed689781dcb0676b74a99029e4bd0dfd7eb53c62a42dbff2b | Python | 1,162 | 34 | #%%
dataset_dir = "spatial_prompt/"
import pandas as pd
import numpy as np
import scanpy as sc
import STAGATE
import time
import tensorflow as tf
tf.compat.v1.disable_eager_execution()
dt_dir = "benchmark/"
import stlearn as st
#%% import data
libd_data_dir = dataset_dir+"benchmark/spatiallibd/st_data/spatialLIBD/"
li... |
655da0be83d3a08e56e8a084b5ba48332d468153504911396d9367a647fbb15b | Python | 1,163 | 35 | #!/usr/bin/env python
import os
import tempfile
import unittest
import hashlib
from ldr.utilities.utilities import untar
class TestUntarOutput:
def __init__(self, tar):
self.tar = tar
def __enter__(self):
self.directory = tempfile.TemporaryDirectory()
untar(self.tar, self.direct... |
d14a9e854d67fe30d65904e3d5d0d9008bfb93b852b53edc07cb36c8d004b681 | Python | 1,164 | 39 | import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from statsmodels.tsa.seasonal import seasonal_decompose
# read data
df = pd.read_csv('o1_i900s_w1_s1_fmean.csv', index_col='dateTime',parse_dates=True)
def stl(data, freq):
decomposition = seasonal_decompose(data, model='additive', pe... |
180a4811c65e3c220fa4f9e23124575e20ff85e3d2f4060485551bdcfd2068bf | Python | 1,165 | 37 | #! /usr/local/bin/python
#'#################################################################################
#'#################################################################################
#' Extract features from network
#'#################################################################################
#'######... |
45785f8f87ad40d924225c2ab0282af9505508abbd59b8690cce5d13f584a113 | Python | 1,166 | 37 | from PIL import Image
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
import numpy as np
from tiatoolbox.tools.stainaugment import StainAugmentor
class StainAugment(object):
def __init__(self, p=0.5) -> None:
stain_matrix = np.array([[0.91633014, -0.20408072, -0.34451435],
... |
5dee11cc01dcc5e8eb84f31e9e10f911e68a7467523de9703943c4b1db15c5a3 | Python | 1,166 | 35 | from pycromanager import ZMQRemoteMMCoreJ
import numpy as np
import time
core = ZMQRemoteMMCoreJ()
camera_name = core.get_camera_device()
#trigger mode
core.set_trigger_mode(camera_name, 'FrameStart', True)
print(core.get_trigger_mode(camera_name, 'FrameStart'))
core.set_trigger_mode(camera_name, 'FrameStart', False... |
4e069c8c63d54aff1bad882ee0fcad6b73911d60b58fd04fe7d871abae9f59f1 | Python | 1,167 | 41 | import os
import json
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
class Params:
"""
Class that stores and loads hyper-parameters
"""
def __init__(self, params=None):
if params:
self.... |
37ca3c65b985e6e5abac72c4639fd879daf548162587641d576a75f88a9758ff | Python | 1,168 | 40 | import pytest
from langchain_core.tools import BaseTool, tool
from langchain_classic.tools.render import (
render_text_description,
render_text_description_and_args,
)
@tool
def search(query: str) -> str: # noqa: ARG001
"""Lookup things online."""
return "foo"
@tool
def calculator(expression: str)... |
ae043da3d9be1b56f14e6c0b29e6219bef7a55a1707333a2671850fc3c450ac9 | Python | 1,169 | 46 | import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
mean = 20.22
vari = 0.96
def target_distribution(x):
return np.exp(-(x - mean) ** 2.0 / (2.0 * vari ** 2.0)) / (np.sqrt(2.0 * np.pi) * vari)
def proposal_distribution(x, step):
return np.random.uniform(x - step, x + step)
... |
5c5383390342f04fd14a31c9015f56bc73909bb245dba663f0746c5f2c755c33 | Python | 1,170 | 39 | from datetime import datetime
import pytest
from langchain_core.exceptions import OutputParserException
from langchain_classic.output_parsers.datetime import DatetimeOutputParser
def test_datetime_output_parser_parse() -> None:
parser = DatetimeOutputParser()
# Test valid input
date = datetime.now() #... |
c4b9822916548b9d71e55d784c99eeb56c39ab4ae8b06344b75c93c1440173a7 | Python | 1,170 | 37 | import torch
import torch.nn as nn
class simpleECG(nn.Module):
def __init__(self,num_classes=5,num_channels=12,**kwargs):
super(simpleECG, self).__init__()
self.num_channels = num_channels
self.num_classes = num_classes
k = 64
M = 7
modules = []
#m... |
46d4e0d1257a7864bdd52d7a88c5e5c744d6068093310b88c0b7f68741bfa69b | Python | 1,172 | 26 | import mne
import os.path as op
from config_FaceName import MEG_data_path,group_name,Ids,conditions_encode,conditions_recall,eq_conditions_encode,eq_conditions_recall
from custom_functions import eq_cond_name
for subject_id in Ids:
subject = group_name+"%02d" % subject_id
print("processing subject: %s" %... |
f4a955a83abb806bd3f4dab2312645fa2f6b8799e8a520e38459aa6bea5f268e | Python | 1,172 | 46 | '''Trackers for analysing chromatin tracks.'''
import os
import sys
import re
import types
import itertools
import glob
from PeakcallingReport import *
from cgatReport.Tracker import *
class TrackerTracks(TrackerSQL):
mPattern = "_tracks$"
def getTracks(self, subset=None):
return [x for x in Tracke... |
f9c074ee6426ce1348daefa54166d0f6e789eae505594b8c34663d62e327fe3b | Python | 1,172 | 38 | import logging
import sys
import uuid
import pytest
from langchain_classic.callbacks.tracers import LoggingCallbackHandler
def test_logging(
caplog: pytest.LogCaptureFixture,
capsys: pytest.CaptureFixture[str],
) -> None:
# Set up a Logger and a handler so we can check the Logger's handlers work too
... |
d11a1d0ce8808b9dec897c88ebdffe9e4511bebe768e9d35343f920bc0ae5aa5 | Python | 1,173 | 32 | ##################################################################################
# DNN gene expression autoencoder pathways network 3
##################################################################################
##################################################################################
from tensorflow.k... |
abaf12d462179dface22b1d3780aea4faef91fac92bac079506593e3a8e35ff8 | Python | 1,174 | 48 | import sys
import numpy as np
import torch
import torch.nn as nn
import joblib
from dt_utils import Timer
from data_utils import generate_recognition_data
from plastic import PlasticNet
from neural_net_utils import random_weight_init
d = 50 #length of input vector
R = int(sys.argv[1]) ... |
b79dc60c5863aa34d20569bd15e9555b26f63e67b1ecd1bbfb45e55f1136b57f | Python | 1,175 | 42 | from typing import TYPE_CHECKING, Any
from langchain_classic._api import create_importer
if TYPE_CHECKING:
from langchain_community.tools import (
BaseRequestsTool,
RequestsDeleteTool,
RequestsGetTool,
RequestsPatchTool,
RequestsPostTool,
RequestsPutTool,
)
# C... |
5d62d20770a761f865eb6479271db5aaa1eadc25cdb604e48c3065cda8d1a397 | Python | 1,177 | 49 | import numpy as np
import scipy.sparse as sp
####################################################
# This tool is to collect neighbors, and reform them
# as numpy.array style for futher usage.
####################################################
# This is for DBLP
pa = np.genfromtxt("./dblp/pa.txt")
a_n = {}
for i in ... |
cdeade09fc884a78de833b257e90951ec35f3e540272bc1017325a203366f388 | Python | 1,178 | 42 | """Logic for selecting examples to include in prompts."""
from typing import TYPE_CHECKING, Any
from langchain_core.example_selectors.length_based import (
LengthBasedExampleSelector,
)
from langchain_core.example_selectors.semantic_similarity import (
MaxMarginalRelevanceExampleSelector,
SemanticSimilari... |
1ad553ca62874ae6512ac4820e3bb417ff6cc93a1a2846d11f586b7d8219c986 | Python | 1,180 | 36 | """ Package providing basic/fundamental functions/structures such as cost-functions, activation-functions, \
preprocessing ...
:Version:
1.1.0
:Date:
13.03.2017
:Author:
Jan Melchior
:Contact:
JanMelchior@gmx.de
:License:
Copyright (C) 2017 J... |
ecd9e6558aa4eb499f44bca65c98a75b6454d49bc675c28cc9f078fb3c7ee98f | Python | 1,180 | 36 | from langchain_core.prompts import PromptTemplate
from langchain_core.prompts.chat import (
ChatPromptTemplate,
HumanMessagePromptTemplate,
SystemMessagePromptTemplate,
)
from langchain_classic.chains.prompt_selector import (
ConditionalPromptSelector,
is_chat_model,
)
prompt_template = """Use the... |
28ea75039bc1d263eac4771854d659d4d9bef2579d18a13fb4923a39322ea354 | Python | 1,181 | 38 | import os
import pydicom
import numpy as np
from glob import glob,iglob
from tqdm import tqdm
import skimage.transform as sktf
from joblib import Parallel,delayed
from engine import utils
from constants import BASE_DATA_DIR,CXRAY_SZ,MIMIC_DIR
def resize_mimic_dcms():
dst_folder = utils.get_prepared_path('%sdcm3... |
76c654cd1bc5db379893c9b6ed534bfacbf3f105e4016ec3261aab6d3e6110b2 | Python | 1,181 | 29 | from pycromanager import Acquisition, multi_d_acquisition_events, AcqNotification
import time
import numpy as np
events = multi_d_acquisition_events(num_time_points=10, time_interval_s=0)
print_notification_fn = lambda x: print(x.to_json())
start = time.time()
with Acquisition(directory='C:\\Users\\henry\\Desktop\\d... |
51c2d3c097f46f71bdf1b173e592064512975d02f29d8a42617f34febf8b8b5f | Python | 1,182 | 38 | import os
__all__ = ["dynamic_metadata"]
def __dir__():
return __all__
KEYS = {"env-prefix"}
DEFAULT_EXTRA_PREFIX = "default-"
def dynamic_metadata(field, settings, project):
"""Return the list of package dependencies
This function reads dependencies from the project.optional-dependencies table
... |
ddc555ae9c65c7c695c30ebf50f01d3ef5eae6631f1442dcd8bd2fafbf3c2e50 | Python | 1,182 | 36 | from astrocast.autoencoders import CNN_Autoencoder, TimeSeriesRnnAE, PaddedDataLoader
from astrocast.helper import DummyGenerator
class TestAutoEncoders:
def setup_class(self):
pass
def teardown_class(self):
pass
def test_cnn(self, trace_length=16, num_rows=128):
DG = DummyGener... |
8de20dd0dffdac5fec4780ce190a3800c5d21a1b8e1c1c5ed31d278a1e0ff0db | Python | 1,183 | 33 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Dec 13 21:12:37 2020
@author: shni2598
"""
import numpy as np
#%%
class get_stim_scale:
def __init__(self):
self.seed = 10
self.stim_dura = 200 # ms
self.separate_dura = np.array([300,500]) # ms
self.dt_stim = 1... |
6f745f88814a7e9a3e53e1110e452c6ef58ed17ac7c06725b639f21199d1951f | Python | 1,184 | 41 | import numpy as np
from dival import TaskTable
from dival.measure import PSNR, SSIM
from dival.reconstructors.odl_reconstructors import FBPReconstructor
from dliplib.utils import Params
from dliplib.utils.helper import select_hyper_best_parameters, load_standard_dataset
from dliplib.utils.reports import save_results_... |
87da503ab9a83c5f464192666cb3bc3bef5c8834b2767a78e4b13e4f92a05e5c | Python | 1,184 | 34 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Apr 19 22:15:19 2021
@author: shni2598
"""
import numpy as np
#%%
class get_stim_scale:
def __init__(self):
self.seed = 10
self.stim_dura = 200 # ms
self.separate_dura = np.array([300,500]) # ms
self.dt_stim = ... |
d87da19061aa14fe400c1bcd07c82d07019ac29d319b81ecce9f2e2b26ff1523 | Python | 1,184 | 38 | import numpy as np
from dival import TaskTable
from dival.measure import PSNR, SSIM
from dival.reconstructors.odl_reconstructors import FBPReconstructor
from dliplib.utils import Params
from dliplib.utils.helper import select_hyper_best_parameters, load_standard_dataset
from dliplib.utils.reports import save_results_... |
e3a5ed99188c2e9d1185145c4ad53560a9ad34227b04d211c884e7f0d06bac2d | Python | 1,185 | 29 | SYSTEM_MESSAGE_PREFIX = """Answer the following questions as best you can. You have access to the following tools:""" # noqa: E501
FORMAT_INSTRUCTIONS = """The way you use the tools is by specifying a json blob.
Specifically, this json should have a `action` key (with the name of the tool to use) and a `action_input` ... |
fa0fbb6a4e232c64bd2f55c6b321e1f4e98940b07c294c219b1d763f84413235 | Python | 1,185 | 48 | from __future__ import print_function
import argparse
import sys # for commanad line
import os # for file paths
import re
import itertools
import cPickle as pickle
import numpy as np
def main():
'''Read reactions'''
global v
found_counts = []
times = []
candidate_counts = []
f = open(inf... |
9d3e84a6632a2108a56465be5ad5642a3103acfad378ec7d36a45026d8983358 | Python | 1,186 | 27 | import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="brainagemodel",
version="0.0.1",
author="Amir H. Ansari, Kirubin Pillay",
author_email="amirans65.ai@gmail.com",
description="This package provids the essential implimentations of a deep ... |
fb434d07e13fc36616abc7a1cace92aff6393ee55f14fae5bde98402f07e6424 | Python | 1,187 | 24 | import os
import setuptools
setuptools.setup(
name='nowcasting',
version="0.1.dev0",
author="Xingjian Shi, Zhihan Gao, Leonard Lausen, Hao Wang, Dit-Yan Yeung, Wang-chun Woo, Wai-kin Wong",
author_email="xshiab@cse.ust.hk, zhihan.gao@connect.ust.hk, lelausen@connect.ust.hk, hwangaz@cse.ust.hk, dyyeung... |
28c199d383521cb01aa323a4403808fd2ce7ebb9698f36c032e83e1151595b86 | Python | 1,188 | 45 | from typing import TYPE_CHECKING, Any
from langchain_classic._api import create_importer
if TYPE_CHECKING:
from langchain_community.utilities.clickup import (
ClickupAPIWrapper,
Component,
CUList,
Member,
Space,
Task,
Team,
)
# Create a way to dynamical... |
bb58e2d98e91d233ffeac6d9c62b256e51593319e3722620222de8b42abfb042 | Python | 1,188 | 40 | from torch.utils.data import DataLoader, Subset, TensorDataset
from vulcanai.models import ConvNet, DenseNet
import sys
sys.path.append('.')
from vulcanai.models.metrics import Metrics
import torch
def dataloader():
"""Create a dataset by importing from the test csv"""
test_input = torch.rand(size=[13, 15])
... |
2c4241a8c7eb5e2d2f183eeb987ba1522aeb7b9de805a3e54543ccfea1878a87 | Python | 1,189 | 42 | import torch
import torch.nn as nn
r'''
Minimal implementation to test: Fast parameter insert for PyTorch modules (Forecaster).
'''
def replace_params_with_custom_tensor(module, custom_tensor_func):
for name, param in list(module.named_parameters(recurse=False)):
# Delete the original parameter
de... |
f9c9ea514e14f960a5a73ee94cee4bfcda47afdc739e5bd47838cdfa9a036162 | Python | 1,190 | 40 | from __future__ import annotations
import re
from langchain_core.output_parsers import BaseOutputParser
from typing_extensions import override
class RegexParser(BaseOutputParser[dict[str, str]]):
"""Parse the output of an LLM call using a regex."""
@classmethod
@override
def is_lc_serializable(cls)... |
b2309df48d6074b4a80bc8a341db5abfa5207d5fc5730b8a1b4c59541ce019af | Python | 1,191 | 48 | from openff.toolkit import unit
from openff.toolkit.typing.engines.smirnoff import ParameterHandler, ParameterIOHandler
from openff.toolkit.typing.engines.smirnoff.parameters import (
ParameterAttribute,
ParameterType,
_NonbondedHandler,
)
class CustomHandler(ParameterHandler):
_TAGNAME = "CustomHandl... |
bcb041953d599d16ecf4cbaaffa1d2bdff6d5649471944b8e12e0e973c096690 | Python | 1,192 | 44 | """py.test configuration"""
import os
from pathlib import Path
import numpy
import pytest
from bids.layout import BIDSLayout
test_data_env = os.getenv('TEST_DATA_HOME', str(Path.home() / 'sdcflows-tests'))
test_output_dir = os.getenv('TEST_OUTPUT_DIR')
test_workdir = os.getenv('TEST_WORK_DIR')
layouts = {p.name: BIDS... |
9afe5307e0c1d105ebc0ce00018c040d7a6ff88311cd4bcb597b902a12294a89 | Python | 1,193 | 39 | #! /usr/local/bin/python
#'#################################################################################
#'#################################################################################
#' Combine methy from hdf5 data and labels
#'#################################################################################... |
9a73e14f7e98f79a0265c03b99669db56429cac6b73bbcfa6759511ade90ef51 | Python | 1,194 | 48 | from voxcell import VoxelData
import flatmap_util as fmutil
import numpy as np
import sys
flatmap_nrrd = sys.argv[1]
hemi_nrrd = sys.argv[2]
output_nrrd = sys.argv[3]
xmax = 1.0
if len(sys.argv) > 4:
xmax = float(sys.argv[4])
# load
fmap, _ = fmutil.load_flatmap(flatmap_nrrd)
hemi = VoxelData.load_nrrd(hemi_nrrd... |
8aad9d335dcf082167101f1af1f44af3e8a50c59083332cf03a23a0a9e3a376e | Python | 1,195 | 42 | #! /usr/local/bin/python
#'#################################################################################
#'#################################################################################
#' Train TCGA network
#'#################################################################################
#'#################... |
c636818b079868243514cd548d128004588379f3116a54d1adcc9241354164c5 | Python | 1,195 | 42 | from setuptools import setup, find_packages
setup(name='pensa',
version='0.2.7',
description='PENSA - protein ensemble analysis',
url='http://github.com/drorlab/pensa',
author='Martin Voegele, Neil Thomson, Sang Truong, Jasper McAvity',
author_email='mvoegele@stanford.edu',
license=... |
ed4c4fa991ca7cf6da1989e3ef9d84d920937e28fd4390a3ec0e2137111ee56c | Python | 1,195 | 1 | import os
import sys
from pathlib import Path
root_dir = Path(__file__).resolve().parent.parent
work_space = str(root_dir) + os.sep
sys.path.append(work_space)
import uvicorn as uvicorn
from fastapi import FastAPI, HTTPException, Form
from web.options.options import SERVER_PORT
from web.model.model import Adaptor
fr... |
648a88a29c338d040f6d89c877cffc39a0edc0597e5a16cd13498eb77852339b | Python | 1,196 | 41 | import numpy as np
from dival import TaskTable
from dival.measure import PSNR, SSIM
from dival.reconstructors.odl_reconstructors import FBPReconstructor
from dliplib.utils import Params
from dliplib.utils.helper import select_hyper_best_parameters, load_standard_dataset
from dliplib.utils.reports import save_results_... |
6d9408ee1928283673a9369bac538c76bd36993932045166d82d6f5f4f443bbd | Python | 1,196 | 39 | import torch
import numpy as np
def tv_loss(x):
"""
Isotropic TV loss similar to the one in (cf. [1])
References
----------
.. [1] https://en.wikipedia.org/wiki/Total_variation_denoising
"""
dh = torch.abs(x[..., :, 1:] - x[..., :, :-1])
dw = torch.abs(x[..., 1:, :] - x[..., :-1, :])
... |
eb300dcf54dba0ff1fdf8f45de2e98ff0a73b92d12a94f330931a7a4345e36f8 | Python | 1,196 | 29 | from cv2 import imread, imwrite, resize
import os
"""path = "Z:\Projets\I3DOPPORTUNITES\I3DOP049UNIVERCELL\Acquisitions\\2022-08-HCD-manip7-Harmine\\2022_08_12\sphero-redim-EdU"
res_path = os.path.join(path, "resultats")
if os.path.isdir(res_path) is False:
os.mkdir(res_path)
onlyfiles = [os.path.join(path, f) fo... |
3768463ccd00da6a0b2dcd9a24b120e355001183f5def35509d7a8f48b27285d | Python | 1,197 | 38 | txt_file = '../string/preprocessed/protein.sequences.corpus_partial.txt'
inp = txt_file
ofile = 'string_vec_partial.txt'
#train
import logging
import os.path
import sys
import multiprocessing
import time
from gensim.corpora import WikiCorpus
from gensim.models import Word2Vec
from gensim.models import P... |
fd7e7711f2402e916f0929d6d9bfc5609add31fe009fd146a4dd1d24662980d8 | Python | 1,197 | 33 | import os
d="/jukebox/griffiths/bert-brains/"
d="/jukebox/griffiths/bert-brains/"
#ds=['layer_'+str(i)+"_activations" for i in range(12)]
#ds+=['layer_'+str(i)+"_z_representations" for i in range(12)]
#ds+=['bert-base-uncased_syntactic_complexity_L-inf_T-128_D-concat']
#ds=['ling_features']
#ds=['bert-base-uncased_... |
17a047bd689626aacb7c45b777a524cf7f6dbd924ec3adc94fbdca748da96430 | Python | 1,198 | 32 | import numpy as np
from statsmodels.nonparametric.smoothers_lowess import lowess
from scipy.interpolate import interp1d
def loess_ci(x, y, percentile, frac, n_bootstrap=100):
n_points = y.shape[0]
# allow for multiple confidence interval percentiles
n_ci = len(percentile)
# one column for loess curve... |
f94cc9d6bd4e54f176bfa401f687d42fd01f588e5ea57858dcea8c23bd0da337 | Python | 1,199 | 44 | #!/usr/bin/env python
import argparse
import json
import re
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument("--delete_objects_from", nargs='+')
arg_parser.add_argument("--delete_object_keys", nargs='+')
arg_parser.add_argument("--merge_files", nargs=2)
ARGS = arg_parser.parse_args()
def loadFile(file_n... |
04063820387f74f5bd6811d22b5cc3733edfc36fbe5a04cbb16b1f7676eae350 | Python | 1,201 | 36 | import pandas as pd
df = pd.read_csv('genemap2.edited.collapsed.txt', sep='\t')
print(df.head())
print(df.shape)
#AD: autosomal dominant
#AR: autosomal recessive
# AD
print('\nAnnotation has AD:')
ad_df = df.loc[df.Annotation.str.contains('AD'), :]
pd.Series(ad_df['Approved_Symbol'].unique()).to_csv('AD_genes.txt', ... |
438895476dd4f6c5ba00b5b8e843dc273c0505d081cb5393aa76263cdf1d58aa | Python | 1,202 | 36 | #! /usr/local/bin/python
#'#################################################################################
#'#################################################################################
#' Reshape hdf5 data to add channel dimension
#'##############################################################################... |
869afcd8642d525177edb00f2fc990ab4a031bdcbecc227956a0b8bc399814e8 | Python | 1,202 | 36 | """
Make main plots for the given subject data file.
- Summary table
- Performance over sessions
- Learning rate around change points
- Learning rate modulation by variables
- Individual sequences
"""
import argparse
import data_analysis_utils as dana
import subject_summary_table
import performance_over_sessions_subj... |
ce8be16593a02e8722d775dece5ffd96961ca82dabe8c31b34222dc77146c24e | Python | 1,202 | 31 | # -*- coding: utf-8 -*-
####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2026 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See t... |
7ad5f94486d2126089ca22575d318db1809fa8e62d9a7f5782f90b2ef7d9cc6c | Python | 1,204 | 33 | # Copyright 2022 DeepMind Technologies Limited.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
67899c752f59233f0763eed71d14c665b7f54b0988d0128e8b19659d678bdd34 | Python | 1,205 | 45 | '''very basic utility functions. We avoid module level imports
in order to avoid dependencies if not required.
'''
def set_seeds(seed_val=42):
'''fix seeds for reproducibility.
'''
from numpy.random import seed
from tensorflow import set_random_seed
seed(seed_val)
set_random_seed(seed_val)
... |
8a07d1ddab6e7cd980b1dce3cb8fa8260ac88284fa4676f286788e069b13f6d5 | Python | 1,205 | 44 | # Copyright 2020 DeepMind Technologies Limited.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
daaa8ee644e95cb06fc33f7cef30ca6a50aa21bc941d38bbbdb0175ced61444f | Python | 1,205 | 44 | from skimage.io import imread, imsave
import os
import numpy as np
from PIL import ImageDraw, ImageFont, Image
line_nb = 8
col_nb = 8
path = "/home/clement/Bureau/res_cam_trous"
case = "im"
# im pour mosaique image ou cam pour l'autre
if case == "im":
keyword = "rgb"
elif case == "cam":
keyword = "visu"
on... |
1c504685c621c624681b40b540e4c13f43726effe08eb54f8b0796e69fe9c627 | Python | 1,207 | 28 | # This file is part of the markovmodel/deeptime repository.
# Copyright (C) 2017, 2018 Computational Molecular Biology Group,
# Freie Universitaet Berlin (GER)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by... |
8b8f8a3b990d6e2933b7f3968f5c9f2fc0afe9241000e469557aa0dd46ddd521 | Python | 1,207 | 46 | import numpy as np
from matplotlib.collections import LineCollection
import matplotlib.pyplot as plt
def tick_curves(
x0, y0, labels, idx=None,
ax=None, lw=3,
color='black', tick_len=0.2,
text_offset=0.5, skip=1,
skip_ticks=1,
fontsize="xx-small",
**text_kwargs
):
"""
create ticke... |
b4603e0620b536e4c7a2d3c248406a318dbd483764adc9626489a53dd08a8eca | Python | 1,207 | 35 | import os
import numpy as np
from re import VERBOSE
import tensorflow as tf
from tqdm import tqdm
from tensorflow.keras.utils import Sequence
from brainagemodel.core.ensemblemodels import EnsembleModels
class PretrainedSincModel(EnsembleModels):
'''
To load all ensembled trained Sinc models.
Note that it i... |
e34ff1419f1bab4afa76d45db7d90c62fbfb1e483513840c1491e4f586f5496a | Python | 1,208 | 44 | from typing import Tuple
import cv2
import numpy as np
from .annotations_io import AnnotationTable, WorldlineTable
from .transform import mip_threeview
def hex_to_rgb(value: bytes) -> Tuple[int, ...]:
value = value.lstrip(b'#')
lv = len(value)
return tuple(int(value[i:i + lv // 3], 16) for i in range(0,... |
bc690192ef3ec4bcf0651018364289799a3436e59721d0eea009f83a6d6a19ca | Python | 1,210 | 45 | from unittest import TestCase
import torch
from chroma.models.graph_classifier import GraphClassifier
class TestGraphClassifier(TestCase):
def test_graph_classifier(self):
class_config = {
"dummy_1": {
"tokens": ["a", "b", "c", "d"],
"loss": "bce",
... |
f94336bb263ae7d539e6bdf6f08369b834077b147edd3a3bf36fef4376598d69 | Python | 1,211 | 36 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import os.path as osp
from setuptools import find_packages, setup
with open("README.md", encoding="utf-8") as fh:
long_description = fh.read()
exec(open(osp.join(osp.dirname(__file__), "pdearena", "version.py")).read())
setup(
name="pd... |
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