sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5c99a4bb902a438623d7402666ff7392961964b039f972a40bdc81bc337963e8 | Python | 3,588 | 64 | # Case 1: courtship vs defense — recursive A·D·C·Φ likelihood, parameter & model recovery
import numpy as np, json, sys
from scipy.optimize import minimize
from scipy.special import logsumexp
rng=np.random.default_rng(11)
NC=9; TAU_U=200.
def design(n_wt=275,n_lc=60,n_ph=0,n_p1=0):
n=n_wt+n_lc+n_ph+n_p1
g=np.r_... |
79f52c837633a9f08bc93438ff54c4d9da35b573dae392621e42a2e657ae2a79 | Python | 3,588 | 99 | from catboost import CatBoostRegressor
from lightgbm import LGBMRegressor
from pathlib import Path
from sklearn.ensemble import RandomForestRegressor
from sklearn.impute import SimpleImputer
from sklearn.metrics import roc_auc_score
from sklearn.model_selection import train_test_split
import numpy as np
import sys
de... |
3b086b74246d0896e3f5cbea5efff79973c06baebc2fcb99858bcdc17e70f1c6 | Python | 3,589 | 141 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
For every gene in the provided GTF, subtract UTR sequence from the exonic
features. Requires the input GTF be sorted by gene_id (`sort -k10,10`).
"""
import argparse
import sys
import re
import pybedtools as pbt
def parse_attribute(attribute):
"""
Convert ... |
120d711bfc65f13120926ba941441fac0be9df66dbd1aa962e3b74f511088d0a | Python | 3,591 | 99 | import os
def main():
SEQ_LEN = "800"
HALF_SEQ_LEN = int(SEQ_LEN) // 2
QUATER_SEQ_LEN = int(SEQ_LEN) // 4
print("QUATER_SEQ_LEN: ", QUATER_SEQ_LEN)
# output_files = ["./dataset/pos/", "./dataset/outlier_test/", "./dataset/neg_5/"]
output_dir = "./dataset/"
output_files = [output_dir+"pos... |
9105a6cb34d0b701a932cbe17017cf5702682e72418c4752a37704924979e53b | Python | 3,591 | 124 | from scipy.io import loadmat
from scipy.special import erfcinv
import numpy as np
import pandas as pd
from scipy.stats import kstest, kruskal
from itertools import combinations
from matplotlib import pyplot as plt
def star(p_val):
assert 0 <= p_val <= 1
if p_val >= 0.05:
return 'ns'
if p_val >=... |
c1eec5b5b85159a9fc2d85cb9a7083052b17c625f56efe11e8ab876ac7226635 | Python | 3,591 | 141 | import os
import subprocess
seed_list = [1111, 2222, 3333, 4444, 5555]
#snn_ratio = [0.05, 0.25, 0.5, 0.75, 0.95]
snn_ratio = [0.05, 0.15, 0.25, 0.35, 0.45, 0.5, 0.55, 0.65, 0.75, 0.85, 0.95]
log_folder_path = "./log/"
dataset = "mnist"
rnn_type = "rnn"
def extract_one_performance(model, seed, ratio=None):
if... |
2d0b3185b7b093119330567ec0556fbf798ac08128ffc3bc3e7133034b32c778 | Python | 3,592 | 105 | import torch
from loss import spearman_loss
from metrics import spearman_corr
class ProcessingData(torch.utils.data.Dataset):
def __init__(self, train_csv, train_pt, dataset_type):
self.train_csv = train_csv
self.train_pt = train_pt
self.dataset_type = dataset_type
def __len__(self)... |
aae6ed4caa3cf3e38b38386eff285f7ef4623fbd0efb7d20d7b4c08a18fccbb9 | Python | 3,592 | 99 | from abc import ABCMeta, abstractmethod
# Delay importing optuna since it is an optional dependency.
try:
import optuna
_optuna_available = True
except ImportError:
_optuna_available = False
class EvaluationHook(object, metaclass=ABCMeta):
"""Hook function that will be called after evaluation.
... |
37084e17ee2cbaeb72997560e6f6f60a86679a280da32eee09ef45ee9a93963c | Python | 3,593 | 116 | #Download deepforest before tests start
import comet_ml
from deepforest.main import deepforest
import geopandas as gpd
import os
import glob
import rasterio as rio
from src import data
from src.models import year
from src.models import dead, multi_stage
from src import utils
import tempfile
import torch
from pytorch_li... |
c4c64b72e50ed6a85af53e29a53ac2662b3a7fa0c484ae314eb287c79022e812 | Python | 3,593 | 110 | import unittest
from unittest.mock import Mock, call
import torch
from rising.transforms import AbstractTransform, BaseTransform, PerChannelTransform, PerSampleTransform
class AddTransform(AbstractTransform):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.grad_tensor... |
956ffd7a5eeec3d07ac8a186ceb10ff134f0b5c3a1a22d1dced5a729563420bd | Python | 3,594 | 99 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
b7f4eed3afb42180208d26414beb0ed7639808bd62c6a38c738275cf8e5c1db2 | Python | 3,594 | 105 | #
# CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
# © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
# Source code:
# https://github.com/AdaptiveMotorControlLab/CEBRA
#
# Please see LICENSE.md for the full license document:
# https://github.com/AdaptiveMotorControlLab/CEBRA/bl... |
e1ecb2bb1b9e03873c601803040878057c8d68ba6c135b98fa5dead534c4aac1 | Python | 3,595 | 124 | import sys
import getopt
import math
import numpy
import random
import logging
import numpy as np
from skimage.color import rgb2yuv, yuv2rgb
from PIL import Image
import os
from shutil import copyfile
class YUV_Read():
def __init__(self, filepath, h, w, format='yuv420', toRGB=True):
self.h = h
sel... |
0ae01550dbfbac0773f204e7e43b88745c49f77267d97843a0232d20f00f7a04 | Python | 3,597 | 89 | # Copyright 2023 Google LLC
# 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 to in writing, sof... |
324914702df29714362069a3f114878591e16e325d9cf5ad9736ddd5f9b6ac3e | Python | 3,598 | 96 | # import the main libraries required for the preprocessing
import mne
from pathlib import Path
import numpy as np
import matplotlib.pyplot as plt
import os
import pickle
from scipy.stats import zscore
# import homemade function
from technical_validation_utils import (parula_map, interp, subjects)
mne.set_log_level(v... |
ef982a90b04303795187abe4e908742d0a294baca0af598175e81b11caea2e06 | Python | 3,598 | 98 | import pytest
@pytest.mark.parametrize(
"in_channels,out_channels,kernel_size,padding,stride,input_shape",
[
(2, 2, (3, 3), (1, 1), (1, 1), (2, 8, 8)),
(2, 4, (7, 7), (3, 3), (1, 1), (4, 8, 8)),
],
)
def test_specksim_conv_layer_setup(
in_channels, out_channels, kernel_size, padding, s... |
8ee88ffacb964f21151752226b8b215319fd6224d0c8aedd36b7986df6e5d6a5 | Python | 3,599 | 90 | """
This Script checks the provided WDL files with miniwdl for
syntax, validation, and import errors. See the following
page on the checks. Note that this script does not
check for "warning" or "suggestions"; you may use
`$ miniwdl check WDL_FILENAME` to get warnings and suggestions.
https://miniwdl.readthedocs.io/en/... |
370e9096b5357ca567fb9b53684397ab2f692478e081349444a7caf1bcd43c3b | Python | 3,600 | 95 | import keras
from typing import List, Dict
from common import DataRecord, SEED
from innvestigate import create_analyzer
from innvestigate.utils import model_wo_softmax
# from scipy.ndimage import sobel, laplace
import numpy as np
from keras.layers import Conv2D
np.random.seed(SEED)
import os
os.environ['PYTHONHAS... |
d07246936e910aeef88af0ec1ff7a890404f16b0b377bed6c3788c5c155fad50 | Python | 3,600 | 98 | import json
import logging
import os
from typing import List
from ray._private.runtime_env.constants import (
RAY_RUNTIME_ENV_PLUGIN_SCHEMA_SUFFIX,
RAY_RUNTIME_ENV_PLUGIN_SCHEMAS_ENV_VAR,
)
logger = logging.getLogger(__name__)
class RuntimeEnvPluginSchemaManager:
"""This manager is used to load plugin j... |
fbe4accb46c7fe7f7d6d2bd39fc6fb88bb5949b3827027ca3032af4300cbe652 | Python | 3,600 | 76 | import numpy as np
from sklearn.metrics import pairwise_distances
import matplotlib.pyplot as plt
# Linearly scale isodepth range inside each domain s.t. isodepth approximately measures microns
# isodepth: N x 1 numpy array of isodepth values per spot
# num_domains: number of domains
# q_vals: num_domains x 1 array... |
50ba3f2784c85fe345b05739c3214fbdddf3e6ecf62e738c23a16edda390f583 | Python | 3,602 | 115 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
from collections.abc import Callable
from typing import TYPE_CHECKING, Any, ClassVar, Generic, Protocol, Self, TypeVar
import cvat_sdk.auto_annotation as cvataa
import cvat_sdk.datasets as cvatds
from cvat_sdk imp... |
9358b59eac00c9473e3eb7eeb11cb9bd942e09183d1b2a7e63a559ab13026bf4 | Python | 3,602 | 113 | import stereoEstimation
import readGPS
import os
import shutil
import argparse
if __name__=="__main__":
print "check"
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('img0_folder', type=str, default="/home/leo/Nvidia_SS/semantic-segmentation2/logs/eval_DM/dext... |
444fdceb43b27dd4e3cec45febacad7511910abf5d74129f147815b757c96960 | Python | 3,605 | 112 | import numpy as np
import pytest
from PIL import Image
from siapy.core.exceptions import InvalidInputError
from siapy.core.types import XarrayType
from siapy.entities.images.mock import MockImage
def test_initialization():
# Valid 3D array
valid_array = np.random.rand(100, 100, 3).astype(np.float32)
mock... |
9ab07b6e2318085d4928c6e7ee2db00e325e7056acf9585819637ed69cb5e7e2 | Python | 3,605 | 85 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
# mypy: disable-error-code=attr-defined
"""Tile with quantized periphery and outputs."""
from typing import TYPE_CHECKING, Optional, Tuple
from torch import T... |
d3319c1c75e7f9e3f7fdbf43d98e9009b4741e6b5e47a96666a475c696c0f3d1 | Python | 3,606 | 89 | # Copyright 2023 Google LLC
# 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 to in writing, sof... |
2f6dff997d91efc9f1d6ea422145df4d0ca373dac9fde34fb6777985952f7082 | Python | 3,607 | 116 | '''train a regular nn on two bandits -- see if ...
1. is there a development of certainty representation, which can be used to trigger CRP
2. is h_t different across bandits, which is needed for CRP to do the right splitting
'''
import numpy as np
import torch
import torch.nn as nn
import seaborn as sns
import matplotl... |
596b5d95ea95268ce1b74115c1eb6a01348988ad7f8881c9c4cbe2049df9f94f | Python | 3,608 | 109 | '''define prediction error in the case of 2 gaussians'''
import numpy as np
import scipy.stats as stats
import matplotlib.pyplot as plt
from scipy.stats import sem
import seaborn as sns
sns.set(style='white', palette='colorblind', context='talk')
cp = sns.color_palette(n_colors=2)
alpha = .7
np.random.seed(0)
'''help... |
84ccd6e2d1ca4b2724f245117f282fba2530d1b213729f624fd01ff72ee90264 | Python | 3,610 | 99 | import numpy as np
import scipy.sparse as sp
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..nn.gcn import sparse_or_dense_dropout
from ..utils import to_sparse_tensor
__all__ = [
'ImprovedGCN',
'ImpGraphConvolution',
]
class ImpGraphConvolution(nn.Module):
"""Graph convolution... |
2634faa39df312e1edb0566e00720bd5c80eaa8cd6dc9669f1c0ec5e9d041fb9 | Python | 3,611 | 112 | import tensorflow as tf
from tensorflow.keras import backend as K
import os, sys
import matplotlib.pyplot as plt
from utils import *
import gc
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib.pyplot as plt; plt.rcdefaults()
from keras.models import load_model
from pkg_re... |
86dc49b1e57c7d055a39f865ec7d4d2af3c3265cb1042b2fcdeb53a1dbf7ba15 | Python | 3,612 | 71 | """
This file will help to demonstrate pipeline for testing microscopy data using the DeepCAD-RT algorithm.
The demo shows how to construct the params and call the relevant functions for testing DeepCAD-RT network.
The demo will automatically download tif file and corresponding model file for demo testing.
See insi... |
567934773eb5951add329b19c5924d208ae82e4cd714e7872fb75a1b9575a4c7 | Python | 3,615 | 109 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Compare the metric values captured by two runs of ``run_examples.py``.
By default the two most recent runs under ``run_results/`` are c... |
e1fdb16b37960a5aca1bc45d27a3202be1acca6b01add44e26b7c1ab315760a1 | Python | 3,615 | 112 | import tensorflow as tf
from tensorflow.keras import backend as K
import os, sys
import matplotlib.pyplot as plt
from utils import *
import gc
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib.pyplot as plt; plt.rcdefaults()
from keras.models import load_model
from pkg_re... |
2db10dbe9fc6ae08778ae92209b2c5b4f0c540bffe7fe7a2eafdd87ba4b69739 | Python | 3,616 | 87 | import requests
from .__config import base_url
from .__aux_funcs import process_response
def fetch_status_display_patient_trts(study_ids, tier="Agent"):
"""
Check if patient level treatments should be displayed. \n
:param study_ids: List of Study IDs. \n
:type study_ids: list of str \n
:param tier:... |
12e463e41c5778275dc4a6fad39c7effe238accafb8d71e6a920d8c698254c38 | Python | 3,617 | 95 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from models.DeepLab.modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
class _ASPPModule(nn.Module):
def __init__(self, inplanes, planes, kernel_size, padding, dilation, BatchNorm):
super(_ASPPModule, self).__init_... |
261740eb12f60942f0dbf4e3b8f7d810c7259488ecb92bddfb83632f83161b6e | Python | 3,617 | 82 | #Imports relevant modules
import os
import csv
#Defines the path of the directory containing compiled data for all pipelines.
compiled_dir = '\\<directory root>\\Sustainability_Output\\Compiled'
#Defines the path of the directory that output data should be written into.
JASP_dir = '\\<directory root>\\JASP\\O... |
c276650e27d775f50be9d4cdfa03edc29cb3345c97ca05f915e7d093a3dfe202 | Python | 3,617 | 102 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Python version: 3.10.9
pandas version: 1.5.0
seaborn version: 0.11.0
matplotlib version: 3.6.3
pingouin version: 0.5.3
ptitprince version: 0.2.6
scipy version: 1.11.4
"""
#%% Import Modules
import pandas as pd
import glob
import seaborn as sns
import matplotlib.pylab... |
35f48b72776afa9b52a39c018815173e3d852d118448d3d54982d9f7ffd17b2e | Python | 3,618 | 99 | '''
MBEANN settings for solving XOR.
'''
class SettingsEA:
# --- Evolutionary algorithm settings. --- #
popSize = 100
maxGeneration = 100 # 0 to (max_generation - 1)
isMaximizingFit = False
eliteSize = 0
tournamentSize = 20
tournamentBestN = 1 # Select best N individuals from each tourn... |
49486d8566febbfa1e66eed97aa993634c335205547e1b6e2859b5c62c174792 | Python | 3,618 | 99 |
import torch
import os
from banditopt import algorithms, models
# import sys
# sys.path.insert(0, "..")
from .defaults import regressors_dict
class AlgorithmsConfigurator:
"""
Implements the configuration of the algorithms based on the given configuration file.
"""
def __init__(self, config, **kwarg... |
9de54a2ae611f2c47e4e08a169eae13a2190604888432837617e5d1e01fac822 | Python | 3,618 | 91 | """Qwen3 with the LM head replaced by a scalar reward head, as a vLLM plugin."""
import os
from collections.abc import Iterable
import torch
from vllm.config import VllmConfig
from vllm.logger import init_logger
from vllm.model_executor.layers.linear import ReplicatedLinear
from vllm.model_executor.layers.pooler imp... |
dd688023fee177f93d42c8c67ab4bddfa6b483aeb1fa8642ace4d0e0efd3b5ef | Python | 3,619 | 98 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
c73cdcc13d5a9f13fdcdf9b97f332fc575c4a77d97ae0172b8fd7e3c6afdf9e8 | Python | 3,620 | 119 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 21 23:29:28 2021
@author: Saad Idrees, Joel Zylberberg's Lab, York University
idrees.sa@gmail.com
"""
import numpy as np
import tensorflow as tf
import models
import prfr_params
from tensorflow.keras.layers import Input
# %%GENERATE RANDOM DATA
... |
306a799882b34f4043c18e1d95f28518db42e12f661cb1d854888f1257c88074 | Python | 3,621 | 132 | import os
import sys
import time
import errno
import time
import timeit
import numpy as np
from numba import jit
import warnings
warnings.simplefilter("ignore")
@jit(nopython=False)
def VEP2Dmodel_sensor(params, constants, init_conditions, SC, Gain, dt, ts):
nt=ts.shape[0]
nn=SC.shape[0]
ns=Gain.sha... |
3592dbce81518d0c48f7a0fe1921259289f6df75760720c0ffb9ffadde5d6fe3 | Python | 3,621 | 145 | """Benchmark to test time and memory performance of History.
Before #312, the timing would be roughly 5 sec and memory usage would
triple. After #312, the timing would be roughly 2 sec and memory usage
roughly constant.
For the reasons, see #306.
"""
from pprint import pprint
import time
import numpy as np
from sk... |
7126902acc162f97cc22abad696d8382a94cf8df07753b5046b3c7a837b674bb | Python | 3,624 | 98 | import logging
import threading
from typing import Optional
import ray
import ray._private.ray_constants as ray_constants
from ray.air._internal.device_manager.cpu import CPUTorchDeviceManager
from ray.air._internal.device_manager.hpu import HPUTorchDeviceManager
from ray.air._internal.device_manager.npu import NPUTor... |
cad11aca5ab770617a50d8c832f6908b1a50e7eb653631180f5174eae841b213 | Python | 3,626 | 41 | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: i_onnx_common.proto
"""Generated protocol buffer code."""
from google.protobuf.internal import builder as _builder
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor... |
dc0995a5182b48beafb3f38ffceb520ecb75230e399e94cfe40e1594be8736fd | Python | 3,627 | 94 | r"""Version shims for anndata and zarr.
omicverse supports a range of anndata versions rather than tracking the newest,
so the differences between them are collected here instead of being scattered
through the codebase.
What actually differs
---------------------
Measured on real installs (anndata 0.11.4 + zarr 2.18.... |
773baa42211d37cc804da55e6836da33d19c0ac2cc6f812522c37171ae5fde13 | Python | 3,628 | 132 | # -*- coding: utf-8 -*-
import numpy as np
from vtkplotlib._get_vtk import vtk
from vtkplotlib.plots.BasePlot import SourcedPlot, _iter_colors, _iter_points, _iter_scalar
class Sphere(SourcedPlot):
"""Plot an individual sphere."""
def __init__(self, point, color=None, opacity=None, radius=1., fig="gcf",
... |
26b8492244a6b97297e93d10b8b84f48389f4da6f4e14339fd1723d5caeae543 | Python | 3,629 | 105 | """ Calculate surprisal and frequency for each word in a sentence using the pre-trained German BERT model and DeReKo
1grams. """
import os
import json
import logging
import torch
import numpy as np
import pandas as pd
import tqdm
from pathlib import Path
from transformers import BertTokenizer, BertForMaskedLM
from ge... |
8a3d7bccf64b2179c2a4d107eed5b2db4b58407192d8c386bb78794e801cab31 | Python | 3,629 | 111 | import math
import torch
import torch.nn as nn
def batched_index_select(values, indices):
last_dim = values.shape[-1]
return values.gather(1, indices[:, :, None].expand(-1, -1, last_dim))
def default_conv(in_channels, out_channels, kernel_size, stride=(1, 1), bias=True):
return nn.Conv2d(
in_cha... |
c502da3736c2a704c14dd2a6caf5f3b7d19aca6275dfc48568c78133c34611e5 | Python | 3,629 | 120 | # __program_start__
import ray
from ray import DynamicObjectRefGenerator
# fmt: off
# __dynamic_generator_start__
import numpy as np
@ray.remote(num_returns="dynamic")
def split(array, chunk_size):
while len(array) > 0:
yield array[:chunk_size]
array = array[chunk_size:]
array_ref = ray.put(np.... |
c6e362d48993529f938815f844aca3abe013fe6b79be423257a3c398016b2d5b | Python | 3,629 | 110 | """Utils to detect runtime environment."""
import logging
import os
import sys
from typing import List
from ray._private.runtime_env.utils import check_output_cmd
_WIN32 = os.name == "nt"
def is_in_virtualenv() -> bool:
# virtualenv <= 16.7.9 sets the real_prefix,
# virtualenv > 16.7.9 & venv set the base_... |
de02875b66f129f30e31e92fa00dcf92242c87b2da1693df5f77652ab9aef9a5 | Python | 3,629 | 115 | from pathlib import Path
from typing import Literal
import math
import pickle
import json
import matplotlib.pyplot as plt
import argparse
import logging
import pandas as pd
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.utils import ModelEma
from timm.loss import Label... |
1bfb8dbe7dbe878906706b9d7f66dbbfe07a1cc54ede64f6a154663c709a048f | Python | 3,630 | 98 | from typing import Any, Dict, List, Optional, Tuple
from ray.util.annotations import DeveloperAPI
@DeveloperAPI
class CommandRunnerInterface:
"""Interface to run commands on a remote cluster node.
**Important**: This is an INTERNAL API that is only exposed for the purpose
of implementing custom node pro... |
8bf9e7c0f8d82fbf6b983db86f9041469e37cdf4f530b6276e86e1f276cf0f49 | Python | 3,630 | 58 | #Plot abundance distribution
from glob import glob
import os
import pandas as pd
import geopandas as gpd
from src import start_cluster
client = start_cluster.start(cpus=100,mem_size="5GB")
#Same data
#species_model_paths = #"/blue/ewhite/b.weinstein/DeepTreeAttention/snapshots/06ee8e987b014a4d9b6b824ad6d28d83.pt",
... |
73127aa4780a279724e1f56f9c937a78d7ea3c5ddacd7371057c58ecc5a04475 | Python | 3,634 | 99 | '''
MBEANN settings for the double pole balancing problem.
'''
class SettingsEA:
# --- Evolutionary algorithm settings. --- #
popSize = 1000
maxGeneration = 500 # 0 to (maxGeneration - 1)
isMaximizingFit = True
eliteSize = 0
tournamentSize = 20
tournamentBestN = 1 # Select best N indivi... |
af2bf69292d7cfc2ddde322756275d78f9fc0d8c2eeb182d4e3e1479ac9577f3 | Python | 3,634 | 102 | from pathlib import Path
import torch
from einops import rearrange
from structured_kernels import cauchy_mult_sym_fwd, cauchy_mult_sym_bwd
# try:
# from cauchy_mult import cauchy_mult_sym_fwd, cauchy_mult_sym_bwd
# except ImportError:
# from torch.utils.cpp_extension import load
# current_dir = Path(__fil... |
b8cfd44ac83f80b3c9f5a21407839f7a7dd3f6b6a931ae8c88bc27d76da569ff | Python | 3,636 | 109 | """Plotting helpers for ambient-RNA decontamination diagnostics.
A single light helper, :func:`plot_contamination`, draws the per-cell
contamination-fraction distribution. For embedding overlays or grouped
violins, prefer the general omicverse plotting surface
(``ov.pl.embedding(adata, color='ambient_contamination')`... |
22c650225a1e8f9cc083787a385ef7315b4815bdfeaec03921cff9d8ed55f855 | Python | 3,637 | 89 | import tensorflow as tf
from models.deep_learning.deep_learning_models import DLRegressor
from utils.constants import is_spline
class GRURegressor(DLRegressor):
"""
This is a class implementing the GRU model for time series regression.
! Remember to use regularization techniques such as dropout, weight d... |
be6ddd381340c344b62ca9f130539ebed4aa1d60b34d884aa5319ca061aa91e9 | Python | 3,637 | 88 | import copy
from typing import List, Tuple, Union
from mmdet.models.detectors import BaseDetector
from mmdet.structures import SampleList
from mmdet.utils import ConfigType, OptConfigType, OptMultiConfig
from mmengine.utils import is_list_of
from torch import Tensor
from lqit.registry import MODELS
@MODELS.register... |
cb88076e579991acaa27db4c8148f9632aa29121f9e693b2ed92783fea7af32e | Python | 3,637 | 94 | import torch
import torch.nn as nn
# derived from https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
def ohkm(loss, topk):
ohkm_loss = 0.
for i in range(loss.shape[0]):
sub_loss = loss[i]
topk_val, topk_idx = torch.topk(
sub_loss, k=topk, dim=0, sorted=False
)
... |
eb61b62aaf86fd6262772cf61d7a2a89f5c6ae4e6ba02ad7cb5947b88bd07bce | Python | 3,637 | 89 | import torch
import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
from torch.nn import functional as F
import torch
import torch.nn as nn
import torch.nn.functional as F
#from resnet50 import Resnet50 as backbone
from . import resnet_custom as resnet
from torchvision.models.segmentation.deepla... |
698854adc051bcbcaf6d1815b991c35705aad816f2a6e756ca80e3d005d9a727 | Python | 3,638 | 103 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
from ase.calculators.calculator import PropertyNotPresent
from pymatg... |
81d20b6271508ca94b713bfcfa533691034ca61abf34dcddaae283bafdb19533 | Python | 3,638 | 126 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
Annotate a VCF of structural variants with a list of genomic elements.
"""
import pandas as pd
def split_gencode_fields(field_str):
fields = field_str.strip(';').split('; ')
fields = [x.split(' ') for x in fields]
fields = dict(map(lambda s: s.strip('"... |
0810c29a12124a0fcc8933eac4e09970f0224f3abf27bc407460302f88c940fa | Python | 3,639 | 106 | """Used to check bazel output for team's test owner tags
The bazel output looks like
<?xml version="1.1" encoding="UTF-8" standalone="no"?>
<query version="2">
<rule class="cc_test"
location="/Users/simonmo/Desktop/ray/ray/streaming/BUILD.bazel:312:8"
name="//streaming:streaming_util_tests"
... |
72c67c96aaaf03a8586c0ebdbf3617dec6fb5f55f311f5ec61fe82774dbacb51 | Python | 3,639 | 104 | import logging
import os
from typing import Dict, List, Optional
from ray._common.utils import try_to_create_directory
from ray._private.runtime_env.context import RuntimeEnvContext
from ray._private.runtime_env.packaging import (
delete_package,
download_and_unpack_package,
get_local_dir_from_uri,
is_... |
eda1902f6babaf8fd9e976e4bc8477a96c92fe167256605a256dd3a29bca1426 | Python | 3,639 | 91 | import gzip
import re
from csv import DictReader
from pathlib import Path
from . import utils
def download(path: Path, version: str = "current"):
url = f"http://cbdm-01.zdv.uni-mainz.de/~mschaefer/hippie/HIPPIE-{current}.mitab.txt"
utils.download_file(url, path / "HIPPIE-current.mitab.txt", "Downloading HIPP... |
eec13d03d44ebe763e136cedba506b7981275b36afcd3433c5b304978e58d927 | Python | 3,639 | 99 | # --------------------------------------------------------
# SimMIM
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Zhenda Xie
# --------------------------------------------------------
import math
import random
import numpy as np
import torch
import torch.distri... |
10c0dc8ab1c3c4d6325f5040ac2d0915b39915205a0be56df96c8d91779dcad6 | Python | 3,641 | 89 | import pandas as pd
import os
import sys
project_root = '/ccb/cybertron/khchao/splam-analysis-results/'
output_dir = f'{project_root}train/results/ALL_RefSeq/BAM_REF_Intersection/'
def get_hg38_chrom_size():
f_chrs = open("../hg38_chrom_size.tsv", "r")
lines = f_chrs.read().splitlines()
chrs = {}
for... |
d7a6cdf39f6030299a347db7c6002aee8718bacd2e37377eb18e6ce0fda761ed | Python | 3,641 | 133 | """Get image metas on a specific dataset.
Examples:
python tools/misc/get_image_metas.py \
${ANNOTATIONS FILE} \
${PATH TO IMAGES} \
--out-dir ${OUTPUT FILE PATH} \
--img-suffix ${IMAGE SUFFIX}
"""
import argparse
import os.path as osp
from multiprocessing import Pool
from mmcv import imread
from ... |
2cee149e72b5ca7323aec52212694e94c83ed6c97801caed2c1e7271b1c998c5 | Python | 3,643 | 81 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
ab371cc3baff1d2ad47f8a10b3a7c02986e285caa6e338f9505a868bbfdb04b8 | Python | 3,643 | 96 | import os
import pandas as pd
import matplotlib.pyplot as plt
from adjustText import adjust_text
annotations = ["chess", "gencode", "refseq_ucsc"]
colors = ['blue', 'red', 'green', 'cyan', 'magenta', 'olive', 'black', 'gray', 'orange', 'purple']
os.makedirs("exon_intron", exist_ok=True)
for level in ["exons", "intr... |
b9b5dd0253b5460b79a0837ef7b29c4ef26fd0e5c8b7ee75e6499fb041658752 | Python | 3,643 | 121 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import argparse
import logging
from pathlib import Path
from fairchem.experimental.legacy.utils import... |
223f52a5df47d9b5adf2bc554c7d13d36acf1de01ffb12ceef848132d9cf086c | Python | 3,644 | 121 | import numpy as np
class ContextRep():
def __init__(self, context_dim, threshold=.3, n_contexts=100):
self.context_dim = context_dim
self.n_contexts = n_contexts
self.threshold = threshold
self.contexts = [
np.random.normal(size=(self.context_dim, ))
for _ i... |
87abe579d548519dede8ae985b379a005502a1460945356b98f15b2469b8a912 | Python | 3,644 | 98 | import argparse, os, sys, glob
from omegaconf import OmegaConf
from PIL import Image
from tqdm import tqdm
import numpy as np
import torch
from main import instantiate_from_config
from ldm.models.diffusion.ddim import DDIMSampler
def make_batch(image, mask, device):
image = np.array(Image.open(image).convert("RGB... |
9d64b10940f0402dc78da88370233050302e7bdcf669282cdc1f332639b0fd01 | Python | 3,645 | 123 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import random
from functools import partial
import numpy as np
import pytest
import torch
from ase imp... |
1d86975d2c653a6bcbb879b1c3f78ebe20020fc124f56313b3af204ddbb359b9 | Python | 3,646 | 71 | import logging
from os.path import exists
from sklearn.metrics import precision_score, recall_score, f1_score, accuracy_score
from sklearn.metrics import classification_report
from agent.data.entities.config import RESULTS_FILE_TSV, RESULTS_FILE_TXT
from agent.data.entities.config import CW_CLASS_VALUES, FC_CLASS_VAL... |
771bd22e254ca873d0b618f56e2fe4cf7ca5c13f7efd42335d9532029f21d797 | Python | 3,646 | 97 | # --------------------------------------------- #
# This script generates samples at the reference and/or target level of theory
# --------------------------------------------- #
# define equilibirum sampling control parameters
smiles = "Cn1cc(Cl)c(/C=N/O)n1" # SMILES of the molecule
run_id = 1
n_samples = 1_000 # how ... |
d1195ce45e691f64abcb436168f9f2f6d8e01e5cd966657989e5c7685ba68706 | Python | 3,646 | 86 | import pandas as pd
import os
def get_hg38_chrom_size():
f_chrs = open("./hg38_chrom_size.tsv", "r")
lines = f_chrs.read().splitlines()
chrs = {}
for line in lines:
eles = line.split("\t")
chrs[eles[0]] = int(eles[1])
return chrs
SEQ_LEN="800"
QUATER_SEQ_LEN = int(SEQ_LEN) // 4
p... |
28d640e8c6cd126b6d931762a242cc6886be15834053e33dfa10ee9c4db6b486 | Python | 3,647 | 119 | """
This file serves as a documentation example and CI test for data parallel + prefill-decode disaggregation.
Structure:
1. Monkeypatch setup: Ensures serve.run is non-blocking and removes accelerator requirements for CI testing.
2. Docs example (between __dp_pd_example_start/end__): Embedded in Sphinx docs via liter... |
c328a7b09e825b6e88abe962f248f3c375082d909e94bc4f20e5ede05f244b9c | Python | 3,648 | 122 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
c31373f1e20083dee0ee2f4a5a650ae5a6a68bd74e7ed8e977838087cb0debdb | Python | 3,651 | 104 | import torch
from sinabs.layers import ExpLeak, ExpLeakSqueeze
def test_leaky_basic():
time_steps = 100
tau_mem = torch.tensor(30.0)
input_current = torch.rand(time_steps, 2, 7, 7)
layer = ExpLeak(tau_mem=tau_mem)
membrane_output = layer(input_current)
assert not layer.does_spike
assert ... |
d456950ca4c825074106cd3c1df144f6475d21f155ac254e7095e6014fb178f6 | Python | 3,651 | 77 | """
This file will demonstrate pipeline for training microscopy data using the DeepCAD-RT algorithm.
The demo shows how to construct the params and call the relevant functions for training DeepCAD-RT network.
The demo will automatically download tif file for demo training.
See inside for details.
* This demo is ... |
a21ad8cf679a081f67e9216b30f39b34f18db225c1a423100dc44e8697e264d9 | Python | 3,652 | 116 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
ONLY for use in the NeurIPS 2021 Open Catalyst Challenge. For all other submissions
please use make_submission_file.py.
"""
from __future__ im... |
9caefb49c156993261264e89ac50b536086b2275c606a2e98e33cf85d2ccace7 | Python | 3,653 | 91 | # Imports
import sys,subprocess
try:
import scipy.io as sio
except ModuleNotFoundError:
subprocess.run([sys.executable, '-m', 'pip', 'install', 'scipy'])
import scipy.io as sio
try:
import numpy as np
except ModuleNotFoundError:
subprocess.run([sys.executable, '-m', 'pip', 'install', 'numpy'])
... |
adf72065febe722d9636c1a99f2a98ed582d6d762d8d047f25f8e8be926e87e1 | Python | 3,653 | 86 | import numpy as np
import pandas as pd
from autogluon.text import TextPredictor
from Bio import SeqIO
import argparse
import json
def Csv_to_json(input_path,result_path):
'''
This function takes two arguments input_path and result_path.
It loads the csv file from input_path,
it converts t... |
61c49d5eb7362b159b63adb13799eca4f08522fb0d8415ca4972a0608bb17da4 | Python | 3,654 | 87 | # Copyright 2026 Google LLC
#
# 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 to in writing, ... |
b17a8cda8b759c2ffb3d0883f2f72e7d804c1f813c254e523ca549009f51511b | Python | 3,656 | 108 | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... |
0dfcb3fc1616bfbf59c8781d6d36febae25f5e5cd3dedb8dca47fb656bad511b | Python | 3,657 | 113 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
from typing import TYPE_CHECKING, Iterable
if TYPE_CHECKING:
from fairchem.demo.ocpapi.client impor... |
d65dd6bc1abae1b069d6179b6f8d35179232bc21589caa76d56faa811a06ef51 | Python | 3,657 | 106 | # ruff: noqa: F401
import warnings
from pathlib import Path
warnings.filterwarnings("ignore", message=".*The 'nopython' keyword.*") # noqa # isort:skip
# Note: Geneformer dictionary files are not included in the package to reduce size.
# Users must provide their own paths to these files when initializing the tokeniz... |
e41590848fc8bb6e4161b05ee4ebd7aa6cd77c863f3200373fe82045cec4d9e6 | Python | 3,658 | 89 | import tensorflow as tf
from models.deep_learning.deep_learning_models import DLRegressor
from utils.constants import is_spline
class LSTMRegressor(DLRegressor):
"""
This is a class implementing the LSTM model for time series regression.
! Remember to use regularization techniques such as dropout, weight ... |
818e1ec8e485bd8ae9ee753ea0e80e27f1316b7ee69cce9309350b6fe2ae45ad | Python | 3,659 | 128 | import logging
import psycopg2
import yaml
from psycopg2 import OperationalError
from psycopg2.extras import RealDictCursor
from agent.data.entities.config import CONFIG_FILE_PATH
logging.basicConfig(format='%(levelname)s : %(message)s', level=logging.INFO)
logger = logging.getLogger(__name__)
logger.setLevel(loggin... |
ab241ff8923f494673678033033b984ead1e30ba684cd85a853b2fb177c2e2aa | Python | 3,659 | 105 | from typing import Dict, Callable
import torch
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
from src.handlers.general import TBSummaryTypes
from src.losses.adversarial.utils import AdversarialLosses
class AdversarialLoss(_Loss):
def __init__(
self,
criterion: str = Adv... |
b9cdf1531863ef5f9a8a7f9d00214e620928b656655b9cc0909d1a2a153815b0 | Python | 3,659 | 125 | # -*- coding: utf-8 -*-
### ---------------- IMPORTS ------------------ ###
import os
import tables
from pick import pick
import numpy as np
# User Defined
from helper.array_helper import find_szr_idx
### ------------------------------------------- ###
class UserVerify:
"""
Class for user verificat... |
7bbc191607affa13fb3d70fd991892e470babaacf60a69c2ac344befb73e2ead | Python | 3,660 | 126 | """
OmicVerse main CLI dispatcher.
Entry point: ``omicverse`` (registered via pyproject.toml scripts).
Sub-commands
------------
claw Start the Jarvis bot and/or generate code with -q.
jarvis Alias for ``claw`` (legacy name).
web Launch the OmicVerse web interface.
skill-seeker OmicVerse Sk... |
93572edd2ee38fae3fc1d538dbcd253570a5260f8cd3c419f743455d2ec4f3b6 | Python | 3,660 | 96 | import os
project_root = '/ccb/cybertron/khchao/splam-analysis-results/'
output_dir = f'{project_root}/train/results/tool_benchmark/splam/'
def main():
SEQ_LEN = "800"
HALF_SEQ_LEN = int(SEQ_LEN) // 2
QUATER_SEQ_LEN = int(SEQ_LEN) // 4
print("QUATER_SEQ_LEN: ", QUATER_SEQ_LEN)
output_files = [out... |
170d50ec08482ca99818046934c4568d34338d837b7c95361cd7805b2b507d3d | Python | 3,661 | 94 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 23 21:00:57 2021
@author: saad
"""
import os
import h5py
import tensorflow as tf
import tensorflow.keras.callbacks as cb
from tensorflow.keras.optimizers import Adam, SGD
import model_acnn.metrics as metrics
from model_acnn import customCallbacks
i... |
4eada1973613138fa7321615861da88748529d541735d4563dc3f908b5f9d4c7 | Python | 3,662 | 77 | ####################################################################################################
# Copyright (c) 2025, Open Brain Institute
# Author(s): Marwan Abdellah <marwan.abdellah@openbraininstitute.org>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is ... |
65a6e8874077cc35f8dde840d103ff232c526fdeb6f9505aebdc4921dd373730 | Python | 3,662 | 111 | from __future__ import division
import numpy as np
from ..utils import dotd
from .. import gpu_utils
# Import manually defined functions
from .variational_nodes import Constant_Variational_Node
class Y_Node(Constant_Variational_Node):
def __init__(self, dim, value, groups):
Constant_Variational_Node.__in... |
a73e76d4c3cf91ee321933791e7cb5076803047cb77548746e46270426e52a9c | Python | 3,662 | 86 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
a84b623b6f174d5bd594e228305bfb0a0a2c446edb0ea3281b5b27a08e3edeec | Python | 3,662 | 107 | #Metrics
import torch
import numpy as np
import pandas as pd
from torch.nn import functional as F
from src import data
def site_confusion(y_true, y_pred, site_lists):
"""What proportion of misidentified species come from the same site?
Args:
y_true: string values of true labels
y_pred: string ... |
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