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# copyright: sktime developers, BSD-3-Clause License (see LICENSE file) """Base class template for forecaster scitype. class name: BaseForecaster Scitype defining methods: fitting - fit(y, X=None, fh=None) forecasting - predict(fh=None, X=None) updating - update(y, X=None, ...
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# SPDX-License-Identifier: LGPL-3.0-or-later import json import warnings from collections.abc import ( Callable, ) from typing import ( TYPE_CHECKING, Any, Optional, ) import numpy as np import torch from deepmd.dpmodel.model.transform_output import ( communicate_extended_output, ) from deepmd.dpm...
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#!/usr/bin/env python __author__ = "pbmanis" """ model_run.py Run a model based on a hoc structure, decorating the structure with ion channels and synapses. Requires: Python 3.7 (anaconda distribution) Neuron7.7 (neuron.yale.edu) pyqtgraph (Campagnola, from github) neuronvis (Campagnola/Manis, from github) cnmodel ...
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Python
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# Copyright (c) ONNX Project Contributors # # SPDX-License-Identifier: Apache-2.0 from __future__ import annotations import ml_dtypes import numpy as np import onnx from onnx.backend.test.case.base import Base from onnx.backend.test.case.node import expect from onnx.reference.ops.op_attention import _compute_attentio...
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Python
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import itertools from functools import partial import warnings import numpy as np import pandas as pd import matplotlib as mpl import matplotlib.pyplot as plt from matplotlib.colors import same_color, to_rgb, to_rgba import pytest from pytest import approx from numpy.testing import ( assert_array_equal, asser...
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""" Functions to compute some results and plot the simulation results from model_run2. Reads the new format filenames. This is written as a class with a set of methods that can be called from elsewhere. Typically, these will be called from within DataTablesVCN.py, which provides graphical table-based access to the sim...
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Python
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# -*- coding: utf-8 -*- """logger class mainly to be used with `CMAEvolutionStrategy` """ from __future__ import absolute_import, division, print_function, unicode_literals __author__ = "Nikolaus Hansen" import os # path import sys # flush import warnings import time # from collections import defaultdict as _defau...
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import pdb import xarray as xr import numpy as np import pandas as pd import itertools from collections import defaultdict # import src.data.analyse_spikes as anaspikes import sklearn.metrics as sklmetrics import sklearn.linear_model as sklinear def align_single_event(binned_spike_ds, behave_df, event_name, time_...
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Python
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from collections import namedtuple from textwrap import dedent import warnings from colorsys import rgb_to_hls from functools import partial import numpy as np import pandas as pd import matplotlib as mpl from matplotlib.cbook import normalize_kwargs from matplotlib.collections import PatchCollection from matplotlib....
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Python
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import bisect import copy import logging import re import typing from abc import ABC, abstractmethod from collections import Counter, defaultdict from collections.abc import Iterable from operator import itemgetter from os import PathLike from pathlib import Path from typing import Any, NamedTuple, Optional, Union, cas...
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import numpy as np import pandas as pd import os from pandas.api.types import is_string_dtype,is_numeric_dtype import networkx as nx import seaborn as sns import pylab as plt import matplotlib as mpl import shapely.geometry as geom from copy import deepcopy import itertools from scipy.spatial import distance,cKDTree,KD...
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## For Calculating Chlorpromazine Concentration in the ECS from numba import jit import numpy as np #import matplotlib.pyplot as plt from scipy import interpolate import time begin = time.time() h=0.01 # In minutes -- time step size g=0.01 # In Centimeter -- spatial step size print("h=",h) print("g=",g) ...
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# SPDX-License-Identifier: LGPL-3.0-or-later import itertools import math import os import unittest from contextlib import ( nullcontext, ) from types import ( SimpleNamespace, ) from unittest import ( mock, ) import torch from deepmd.pt.model.descriptor.sezm import ( DescrptSeZM, ) from deepmd.pt.mod...
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Python
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import pandas as pd from copy import deepcopy from utils.swa_bn_update import update_bn from torch.optim.swa_utils import AveragedModel, SWALR from torch.optim.lr_scheduler import ExponentialLR, StepLR, CosineAnnealingWarmRestarts from tqdm import tqdm import logging import sys logging.getLogger('some_logger') from sp...
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import io import os import re import json import yaml import types import gzip import zipfile import tempfile import mimetypes import subprocess import idlib import rdflib from inspect import getsourcefile from pathlib import Path, PurePath from itertools import chain from collections import namedtuple from urllib.pars...
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# SPDX-License-Identifier: LGPL-3.0-or-later """ SO(2)-equivariant message-passing layers for DPA4/SeZM. This module defines the reduced-layout SO(2) linear operator and the edge convolution used inside SeZM interaction blocks. This module is the dpmodel (array-API) port of ``deepmd.pt.model.descriptor.sezm_nn.so2``....
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import pdb import numpy as np import pandas as pd from tqdm import tqdm from collections import defaultdict import scipy.ndimage as spimage import scipy.signal as spsignal import scipy.stats as sstats import xarray as xr import pickle as pkl from collections import defaultdict import itertools import os import src.da...
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# SPDX-License-Identifier: LGPL-3.0-or-later """ SO(2)-equivariant message-passing layers for SeZM. This module defines the reduced-layout SO(2) linear operator and the edge convolution used inside SeZM interaction blocks. """ from __future__ import ( annotations, ) import math from typing import ( TYPE_CHEC...
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# SPDX-License-Identifier: LGPL-3.0-or-later """ DPA4/SeZM descriptor: Smooth Equivariant Zone-bridging Model. dpmodel (array-API) backend This implementation is designed around two goals: 1) Conservative forces: the descriptor is computed from differentiable energy. 2) Efficient inference: edge geometry and Wigner-...
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# SPDX-License-Identifier: LGPL-3.0-or-later """ SeZM descriptor: Smooth Equivariant Zone-bridging Model. PyTorch backend This implementation is designed around two goals: 1) Conservative forces: the descriptor is computed from differentiable energy. 2) Efficient inference: edge geometry and Wigner-D rotation blocks...
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# SPDX-License-Identifier: LGPL-3.0-or-later """Unit tests for LmdbDataReader, LmdbTestData, LmdbBatchSampler, etc. Pure dpmodel (NumPy/lmdb) tests — no PyTorch dependency. """ import gc import os import signal import subprocess import sys import tempfile import textwrap import unittest from concurrent.futures import...
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# SPDX-License-Identifier: LGPL-3.0-or-later import contextlib import ctypes import dataclasses import json import logging import os from collections.abc import ( Iterator, ) from typing import ( Any, ) import numpy as np import torch from deepmd.dpmodel.utils.neighbor_graph import ( PME_MESH, flatten...
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from __future__ import division from textwrap import dedent import colorsys import numpy as np from scipy import stats import pandas as pd import matplotlib as mpl from matplotlib.collections import PatchCollection import matplotlib.patches as Patches import matplotlib.pyplot as plt import warnings from .external.six ...
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# SPDX-License-Identifier: LGPL-3.0-or-later import math import os import tempfile import unittest import warnings from pathlib import ( Path, ) from unittest import ( mock, ) import h5py import numpy as np import torch from packaging.version import parse as parse_version from deepmd.pt.loss import ( DeNS...
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#!/usr/bin/env python3 """WARNING: DO NOT MODIFY THIS FILE IT IS AUTOMATICALLY GENERATED BY scigraph.py AND WILL BE OVERWRITTEN Swagger Version: 2.0, API Version: 1.0.1 generated for http://localhost:9000/scigraph/swagger.json by scigraph.py """ import re import copy import inspect import builtins from urllib.parse imp...
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import numpy as np import scipy.stats as sstats import pandas as pd import xarray as xr import joblib import multiprocessing # from tqdm import tqdm from tqdm.notebook import tqdm from collections import defaultdict import itertools import pdb import src.data.process_ephys_data as pephys import src.data.analyse_spikes...
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Python
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# Copyright (c) ONNX Project Contributors # SPDX-License-Identifier: Apache-2.0 from __future__ import annotations import contextlib import os import struct import tempfile import numpy as np import pytest import onnx.version_converter from onnx import ( GraphProto, ModelProto, OperatorSetIdProto, T...
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import rdflib from rdflib import URIRef, Literal from pyontutils import combinators as cmb from pyontutils.core import OntId, OntTerm, qname from pyontutils.core import simpleOnt, displayGraph from pyontutils.namespaces import OntCuries, makeNamespaces from pyontutils.namespaces import partOf, hasRole, locatedIn from p...
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import rdflib from rdflib import URIRef, Literal from pyontutils import combinators as cmb from pyontutils.core import OntId, OntTerm, qname from pyontutils.core import simpleOnt, displayGraph from pyontutils.namespaces import OntCuries, makeNamespaces from pyontutils.namespaces import partOf, hasRole, locatedIn from p...
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# Copyright 2019 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 # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agr...
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# SPDX-License-Identifier: LGPL-3.0-or-later """SeZM: Smooth equivariant Zone-bridging Model. This module hosts the ``make_fx`` + Inductor pipeline that runs the SeZM energy (``ener``) path on the GPU. To the authors' knowledge this is the first public implementation of a compiled, dynamically shaped machine-learning...
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#!/usr/bin/env python3 import os import sys import atexit import inspect import tempfile from pprint import pformat from pathlib import Path, PurePath as PPath from importlib import import_module from collections import defaultdict from urllib.error import HTTPError import git import rdflib import requests import ontqu...
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import io import os import re import json import yaml import types import gzip import zipfile import tempfile import mimetypes import subprocess import idlib import rdflib from inspect import getsourcefile from pathlib import Path, PurePath from itertools import chain from collections import namedtuple, defaultdict fro...
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"""figures.py - generate figures for the paper This class generates final figures for the SBEM manuscript by reaching back to the original simulation data, including, in some cases, refitting. Both primary "examplar" figures, and supplemental figures, are generated. The figures are made consistent by using both sns.set...
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import matplotlib.pyplot as plt import numpy as np from src.visualization.useSansMaths import use_sans_maths from src.utils import get_project_root root = get_project_root() import os import glob import pickle as pkl import pandas as pd import src.data.process_ephys_data as pephys import src.data.stat as stat import d...
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# SPDX-License-Identifier: LGPL-3.0-or-later """Training loop for the pt_expt backend. Uses ``DeepmdDataSystem`` (numpy-based batch provider) instead of the pt backend's ``DpLoaderSet`` + ``DataLoader``. NumPy batches are converted to torch tensors at the boundary. """ import functools import logging import time fro...
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import pdb import pandas as pd import pickle as pkl import numpy as np import os import glob import matplotlib.pyplot as plt import matplotlib as mpl import sciplotlib.style as splstyle from tqdm import tqdm import time import src.data.analyse_spikes as anaspikes import src.data.process_ephys_data as pephys import...
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Important Details about EEG data:\n", "Sampple Frequency = 200 Hz\n", "\n", "Number of Samples = 621892\n", "\n", "Duration of trial = 0.85 seconds after onset, which is indicated by firs non-zero marker value f...
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regs_per_section ={ 1 : ['fiber tracts', 'OLF'], 2 : ['fiber tracts', 'OLF'], 3 : ['fiber tracts', 'OLF'], 4 : ['fiber tracts', 'OLF', 'MOB'], 5 : ['fiber tracts', 'OLF', 'MOB'], 6 : ['fiber tracts', 'OLF', 'MOB'], 7 : ['fiber tracts', 'OLF', 'MOB'], 8 : ['fiber tracts', 'OLF', 'MOB'], 9 : ['fiber tracts', 'OLF', 'MOB'...
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regs_per_section ={ 1 : ['fiber tracts', 'OLF'], 2 : ['fiber tracts', 'OLF'], 3 : ['fiber tracts', 'OLF'], 4 : ['fiber tracts', 'OLF', 'MOB'], 5 : ['fiber tracts', 'OLF', 'MOB'], 6 : ['fiber tracts', 'OLF', 'MOB'], 7 : ['fiber tracts', 'OLF', 'MOB'], 8 : ['fiber tracts', 'OLF', 'MOB'], 9 : ['fiber tracts', 'OLF', 'MOB'...
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#!/usr/bin/env python3 import os import sys import atexit import inspect import tempfile from pprint import pformat from pathlib import Path, PurePath as PPath from importlib import import_module, reload from collections import defaultdict from urllib.error import HTTPError import git import rdflib import requests impo...
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regs_per_section ={ 1: ['root', 'CTX', 'OLF', 'MOB', 'MOBgl', 'MOBgr', 'MOBipl', 'MOBmi', 'MOBopl', 'fiber tracts', 'VS'], 2: ['root', 'CTX', 'OLF', 'MOB', 'MOBgl', 'MOBgr', 'MOBipl', 'MOBmi', 'MOBopl', 'fiber tracts', 'VS'], 3: ['root', 'CTX', 'OLF', 'MOB', 'MOBgl', 'MOBgr', 'MOBipl', 'MOBmi', 'MOBopl', 'fiber tracts'...
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# SPDX-License-Identifier: LGPL-3.0-or-later """Framework-agnostic LMDB data utilities for DeePMD-kit. All code here is pure Python/NumPy/lmdb/msgpack — no framework dependency. Backend-specific wrappers (PyTorch Dataset, JAX, etc.) import from here. """ import copy import dataclasses import hashlib import logging im...
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# -*- coding: utf-8 -*- # Resource object code # # Created by: The Resource Compiler for PyQt5 (Qt v5.15.2) # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore qt_resource_data = b"\ \x00\x00\x04\x5e\ \x00\ \x00\x0f\x81\x78\x9c\xe5\x57\xcb\x6e\x23\x37\x10\xbc\x07\xc8\x3f\ \x10\x93\x33\x...
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# SPDX-License-Identifier: LGPL-3.0-or-later """Parity tests: dpmodel ``dpa4_nn`` modules vs the reference pt ``sezm_nn`` modules. This file is extended task-by-task as the DPA4 port progresses. Index-table and numeric-helper parity is exact (``assert_array_equal`` / tight rtol). Module-level weight-copy parity tests ...
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# Copyright (c) ONNX Project Contributors # # SPDX-License-Identifier: Apache-2.0 # This file contains freeze NumPy array for ImageDecoder backend test's input/output # They were generated by image_decoder.py's generate_test_data with pillow # To make ONNX backend test generation simple, use freeze NumPy array directl...
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# SPDX-License-Identifier: LGPL-3.0-or-later # pyright: reportMissingImports=false # ruff: noqa: ANN001, ANN202, RUF005 """Fused Triton SO(2) value path for the SeZM/DPA4 descriptor. The SO(2) value path of :class:`SO2Convolution` -- rotate-to-local, radial degree mixing, the multi-layer gated SO(2) mixing stack, and ...
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Python
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import pandas as pd from sklearn.metrics.pairwise import euclidean_distances as euclidian_distance import random from io import StringIO import requests as r from matplotlib.collections import LineCollection import torch.nn from scipy import stats import matplotlib.pyplot as plt from sklearn.metrics import matthews_cor...
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# tifffile.py # Copyright (c) 2008-2022, Christoph Gohlke # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, # this l...
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from numpy import array#[discrete,41] index_cpd = array ([ 2.4061224878e-01, 2.4061224878e-01, 3.6224921707e-03, 1.7136941457e-02, 1.7136941457e-02, 1.8695002605e-02, 1.8695002605e-02, 1.8695002605e-02, 1.1793657306e-02, 1.1793657306e-02, 6.8502755171e-03, 6.8502755171e-03, 1.6318959354e-02, 1.6318959354e-0...
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# Copyright 2022 The TensorFlow Authors. 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 applica...
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# These medication codes were retrieved from https://biobank.ndph.ox.ac.uk/showcase/coding.cgi?id=4&nl=1 . MEDICATION_CODES = { 1185: 'vitamin e product [ctsu]', 1187: 'chondroitin product', 1189: 'co-enzyme q10/ubiquinone/bio-quinone/coenzyme q10', 1191: 'indigestion remedy (over the counter)', 11...
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# Copyright (c) ONNX Project Contributors # SPDX-License-Identifier: Apache-2.0 from __future__ import annotations import contextlib import gc from pathlib import Path from typing import TYPE_CHECKING, Any import numpy as np import pytest from google.protobuf import text_format from shape_inference_test_utils impor...
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# Copyright (c) ONNX Project Contributors # SPDX-License-Identifier: Apache-2.0 # mypy: ignore-errors from __future__ import annotations import importlib.util import math import warnings from os import getenv from textwrap import dedent from typing import TYPE_CHECKING import ml_dtypes import numpy as np import pyte...
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import datetime import os from pathlib import Path from medications import MEDICATION_CODES class Config: """ This class is used to encapsulate all data that can easily be manually adjusted by each of us. It is inherited by the Dataset class and there is no reason for it to ever be instantiated (if ...
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{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Important Details about EEG data:\n", "Sampple Frequency = 200 Hz\n", "\n", "Number of Samples = 621892\n", "\n", "Duration of trial = 0.85 seconds after onset, which is indicated by firs non-zero marker value f...
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import copy import gzip import json import logging import os import re import shutil import tarfile import tempfile import zipfile from collections import defaultdict from collections.abc import Iterable, Iterator from pathlib import Path from typing import ( Any, Optional, Union, cast, ) import reques...
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Python
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import inspect import json import logging import os import re import shutil import sys from abc import ABC, abstractmethod from collections import defaultdict, deque from collections.abc import Iterable from copy import copy from operator import attrgetter from pathlib import Path from tarfile import ( CompressionE...
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# test_tifffile.py # Copyright (c) 2008-2026, Christoph Gohlke # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, # t...
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Python
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import copy import torch from torch.autograd import Variable import torch.nn as nn import torch.nn.functional as F from torch.autograd import grad from torch.optim import Optimizer import sys import glob import os import numpy as np import matplotlib.pyplot as plt from scipy.special import logsumexp from scipy.spe...
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Python
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# tifffile.py # Copyright (c) 2008-2026, Christoph Gohlke # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, # this l...
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Python
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# SPDX-License-Identifier: LGPL-3.0-or-later import json import logging import warnings from collections.abc import ( Callable, ) from dataclasses import ( dataclass, ) from typing import ( Any, ) from dargs import ( Argument, ArgumentEncoder, Variant, dargs, ) from dargs.json_schema import...
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Python
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from abc import ABCMeta from abc import abstractmethod import numpy as np import pandas as pd from tqdm import tqdm import itertools from sklearn.metrics import mean_squared_error from sklearn.metrics import r2_score from tensorflow.keras.layers import Input from tensorflow.keras.layers import Conv2D from tensorflow....
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Python
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5,802
# test_tifffile.py # Copyright (c) 2008-2022, Christoph Gohlke # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, # t...
15539fc0d90f0d9bf926b83f32da9d90e51224bfefc021f5cba93cfae6ee23c5
Python
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import numpy as np import pandas as pd from pandas.api.types import ( is_string_dtype, is_numeric_dtype ) import anndata as ad import networkx as nx import re from statsmodels.nonparametric.smoothers_lowess import lowess from statsmodels.sandbox.stats.multicomp import multipletests import seaborn as sns import ...
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Python
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# -*- coding: utf-8 -*- """CMA-ES (evolution strategy), the main sub-module of `cma` implementing in particular `CMAEvolutionStrategy`, `fmin2` and further ``fmin_*`` functions. """ # TODO (complex): reconsider geno-pheno transformation. Can it be a # separate module that operates inbetween optimizer and objecti...
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R
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library(testthat) library(pubmedR) test_check("pubmedR")
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R
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library(testthat) library(tiltedCCA) test_check("tiltedCCA")
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R
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library(testthat) library(ggforestplot) test_check("ggforestplot")
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R
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# % of missing data a=ifelse((is.na(pilot_data)),1,0); 100*sum(a)/(dim(pilot_data)[1]*dim(pilot_data)[2])
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R
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# Create subfolder within the current working directory dir.create("R") dir.create("Output") dir.create("Output/Data") dir.create("Output/Data/csv") dir.create("Output/Plots")
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R
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inputs = list(1, 2, -5 , 4, 'oops', 0, 10) for(input in inputs) { print(paste("log of", input, "=", log(input))) } for(input in inputs) { try(print(paste("log of", input, "=", log(input)))) }
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R
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a=read.table('PDGFRA_TSS_hg19.1k.LOOP.tss.bed.demo.bed.signal',sep='\t') b=c(as.numeric(a[2,12]),mean(as.numeric(a[2,7:11]))) pdf('f00p04_demo_pdgfra.pdf',width=5,height=3) barplot(as.numeric(a[2,7:12]),col=c(rep('grey60',5),'red'),border=F) abline(h=1) dev.off()
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R
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gc_log=function(x,n){ row_i=as.numeric(as.character(x[7])) if(row_i < 100){ rows_k=row_i:(row_i+99) } else if(row_i > (nrow(counts_gc_2)-100)){ rows_k=(row_i-99):row_i } else { rows_k=(row_i-50):(row_i+49) } return(as.numeric(as.character(x[n]))/mean(counts_gc_2[rows_k,n])) }
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R
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withWarnings <- function(expr) { #https://stackoverflow.com/a/4947528/949513 myWarnings <- NULL wHandler <- function(w) { myWarnings <<- c(myWarnings, list(w)) invokeRestart("muffleWarning") } val <- withCallingHandlers(expr, warning = wHandler) list(value = val, warnings = myWar...
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R
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# Utilities/helper functions for preprocessing # Directories to save data to savedir_seurat <- "./data/seurat/" savedir_anndata <- "./data/anndata/" # Gene names in "Elfn1" format (mouse convention) recode_genes <- function(gene_names){ sapply(gene_names, function(name){ paste0(substr(name, 1, 1), tolower(subs...
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R
359
19
# sxtTools::setwd_project() # setwd("demo_data/") # minfrac.qc = 0 # minfrac.sample = 0 # normalization.method = "svr" # optimization = TRUE # begin = 0.5 # end = 12 # step = 0.2 # ##loess parameters # multiple = 5 # threads = 3 # ##svr parameters # rerun.loess = TRUE # rerun.svr = TRUE # peakplot = TRUE # datastyle = ...
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R
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set.seed(123) N=50 a=rep(1:N,each=N)/N b=rep(1:N,times=N)/N out=rbind(a,b) rownames(out)=c('a','b') colnames(out)=c(1:ncol(out)) write.table(out, file='mat.txt', row.names=T,col.names=T,quote=F,sep='\t') network=matrix(NA, nrow=1,ncol=2) network[1,1]='a' network[1,2]='b' write.table(network, file='net.txt', ro...
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R
370
12
# Function: Prediction Accuracy from logistic / probit regression predictionAccuracy <- function(x){ classify <- x$data |> mutate(predicted = if_else((fitted(x)) < 0.5, "0", "1"), predicted = factor(predicted, levels = (c("0", "1")))) class_table <- table(classify$predicted, classify$respon...
e1dd04e3e502f6f7f86adada7002e35367e7408fc5ce88e81d17a85c6195e4ee
R
373
14
# Function: Run permutation tests on glm-objects # Main function permutationTest_TP <- function(x) { model <- update(x, data = transform(x$data, TP = sample(TP))) } permutationTest_IF <- function(x) { model <- update(x, data = transform(x$data, IF = sample(IF))) } permutationTest_AF <- function(x) { model <- u...
cf7503cd6c3b37e80ad0822e516dd95fecd317e1ed9cc7bdede9952f541e7308
R
405
11
make_regression_table<-function(slouch.table){ saved.table<-NULL table.names<-c("Model Type","Predictors","t1/2","t1/2 min","t1/2 max","Vy","Vy min","Vy max","R2","logL","AICc","N=") for(i in 1:dim(slouch.table)[1]){ if(is.na(slouch.table[i,1])==FALSE){ saved.table<-rbind(saved.table,slouch.table[i,c(1,...
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R
407
14
rmMeanAdjust<-function(dataframe) { varNames<-names(dataframe) pMean<-(dataframe[,1] + dataframe[,2])/2 grandmean<-mean(c(dataframe[,1], dataframe[,2])) adj<-grandmean-pMean varA_adj<-dataframe[,1] + adj varB_adj<-dataframe[,2] + adj output<-data.frame(varA_adj, varB_adj) names(output)<-c(paste(va...
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R
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22
i=1 while(i<=10){ N=i*1000 set.seed(N) a=runif(N) b=runif(N) out=rbind(a,b) rownames(out)=c('a','b') colnames(out)=c(1:ncol(out)) write.table(out, file=paste0('./testN/mat',N,'.txt'), row.names=T,col.names=T,quote=F,sep='\t') network=matrix(NA, nrow=1,ncol=2) network[1,1]='a' network[1,2]='b' write.table(network, ...
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R
418
20
#!/usr/bin/env Rscript #args = commandArgs(trailingOnly=TRUE) #print(args) # THIS CHECKS THE VERSION OF R INSTALLED version # THIS CHECKS IF XGBOOST IS INSTALLED version print ("Attaching CBDA, xgboost,Superlearner, FNN and SMOTE package....") library(CBDA) library(smotefamily) library(SuperLearner) library(bartMachi...
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R
419
18
# Generating barplot using targets of regulons which are in the DEGs # Load pacckages library(ggplot2) # Load DEG table TF_gene <- read.csv2("DEGs_targeted_by_TFs.csv", sep = ",") head(TF_gene) p.adjust <- TF_gene$p_val_adj ########## ########## # Plot Figure 5C, Appiah et al. ggplot(data = TF_gene...
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R
430
18
risk_F <- function(SampleData){ risk_vector <- rep(NA, 43) for (i in 1:nrow(SampleData)) { if(SampleData[i,4] == "AF22" ){ risk_vector[i] <- "control" } if(SampleData[i,4] == "CTRL9II") { risk_vector[i] <- "control" } if(SampleData[i,4] == "ASD17AII" ){ risk_vector[i] <- "risk"...
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R
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16
#' ggforestplot: Forestplot Visualizations. #' #' ggforestplot is a package for plotting measures of effect, e.g. linear #' associations or log and hazard ratios, with their confidence interval in a #' forestplot layout. It's main plotting function is \code{forestplot()}. #' #' @keywords internal #' #' @importFrom magr...
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R
457
24
COR=c() i=1 while(i<=10){ N=i*1000 A=read.table(paste0('./testN/this.out.ori.',N),header=T,row.names=1,sep='\t') B=read.table(paste0('./testN/this.out.r100.',N),header=T,row.names=1,sep='\t') A=t(A)[,1] B=t(B)[,1] this_cor=cor(A,B) COR=c(COR,this_cor) i=i+1 } TIME=read.table('TIME.txt',sep='\t',header=F,row.names=N...
3caa9500c50a71be984cabb5c5d1b1ebb67c1af226a8e09f4a07e9f42de9e6b6
R
485
16
library(ggplot2) setwd(dirname(rstudioapi::getSourceEditorContext()$path)) summary<-read.csv("summary_bCalAnn1.txt", na.strings = c(".", "N"), sep="\t", header = TRUE) plot(summary$edit_fraction,summary$read_fraction) p = ggplot() + geom_line(data = summary, aes(x = edit_fraction, y = read_fraction), color = "b...
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R
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19
#!/usr/bin/env Rscript library( "ANTsR" ) library("extremevalues" ) args<-commandArgs(TRUE) aslImg <- args[1] outname <- args[2] pasl <- antsImageRead( aslImg, 4 ) pcasl.processing <- aslPerfusion(pasl, moreaccurate=FALSE) pcasl.parameters <- list( sequence="pcasl", m0=pcasl.processing$m0 ) cbf <- quantifyCBF( pcas...
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R
496
12
# ipak function: install and load multiple R packages. # check to see if packages are installed. Install them if they are not, then load them into the R session. ipak <- function(pkg){ new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])] if (length(new.pkg)) install.packages(new.pkg, dependencies = T...
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R
504
11
c.theme <- function(){ theme_tufte() + theme(text = element_text(family = 'sans', color = 'black'), plot.title = element_text(hjust = 0.5, size = 18), axis.text = element_text(size = 13, color = 'black'), axis.title = element_text(size = 16), legend.text = element_text(siz...
398d0511401309ba93181a22eb266f70c8868be042b5ce19f8f831ba3bfd2a84
R
525
36
#/home/toolkit/tools/R4.2.0/bin/Rscript #/home/toolkit/tools/R4.2.0/bin/R source('/home/disk/database/data/ICS_scHIC/src00_ics/ICS.R') source('https://gitee.com/jumphone/VISA/raw/master/VISA.R') set.seed(123) N=50 a=rep(1:N,each=N)/N b=rep(1:N,times=N)/N N=1000 a=rnorm(N) b=a*0.3 + rnorm(N)*0.5 CEX=1 PCH=1...
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R
535
11
install.packages("cli", repos='http://cran.rstudio.com/') install.packages("rlang", repos='http://cran.rstudio.com/') install.packages("devtools", repos='http://cran.rstudio.com/') library(devtools) install_version("gtools", version = "3.9.2") install_version("janitor", version = "2.1.0") install_version("tidyver...
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R
543
12
##This function is simplifying the selection of significant exons ##The user gives dxr result object as an input and chooses the thresholds ##and gives them as pval, log2fc and ebm parameters. The output is ##a dataframe with significant dxr results Sig_F <- function(data, pval, log2fc, ebm){ sig <- as.data.frame(d...
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R
552
17
# ipak function: install and load multiple R packages. # check to see if packages are installed. Install them if they are not, then load them into the R session. local({r <- getOption("repos") r["CRAN"] <- "<https://cran.mtu.edu/>" options(repos=r) }) ipak <- function(pkg){ new.pkg <- pkg[!(pkg %in% installed.pack...
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R
576
18
test_that("pacnet_load reads a data file under native R", { ig <- pacnet_load("liver_studies_iGenes.rds") expect_type(ig, "character") expect_gt(length(ig), 1000) }) test_that("pacnet_load names the missing file", { expect_error(pacnet_load("no_such_file.rds"), "no_such_file.rds") }) test_that("pacnet_data_ur...
03f20b05122222bca3883fc678f68a3c7925638c3fe1f62e28c9fb26f4676e10
R
599
23
#!/usr/bin/env Rscript args = commandArgs(trailingOnly=TRUE) print(args) arg_file = as.array(args[1]) print(arg_file) j_global=as.numeric(args[2]) alpha=as.numeric(args[3]) dataset_file = as.array(args[4]) workspace_directory=as.array(args[5]) label=as.array(args[6]) i_exp=as.numeric(args[7]) print(label) print(worksp...
b498cb54ce793145cda40cd01d7e0a4818662ff35efff67f269b8e0a0ebefe60
R
599
16
library(DirichletReg) dirichlet_model <- function(inputData_train, inputData_test, n_features) { if( ncol((inputData_train)) != ncol((inputData_test)) ) stop('Dataframes do not have the same shape.') data_train <- inputData_train[,1:n_features] data_train$Y <- DR_data (inputData_train[,(n_features+1):ncol(...
a0af724335267a148e1403e893ec6f572a1f4b1222a936b3241a3ae9829b1c00
R
607
18
if (!require("devtools")) install.packages("devtools") devtools::install_github("ck37/varImpact") library("varImpact") #################################### # Create test dataset. set.seed(1) N <- 200 num_normal <- 7 X <- as.data.frame(matrix(rnorm(N * num_normal), N, num_normal)) Y <- rbinom(N, 1, plogis(.2*X[, 1] + .1...