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@numba.jit | |
def ucorrelate(t, u, maxlag=None): | |
"""Compute correlation of two signals defined at uniformly-spaced points. | |
The correlation is defined only for positive lags (including zero). | |
The input arrays represent signals defined at uniformily-spaced | |
points. This function is equivalent to :func:`numpy.correlate`, but can | |
efficiently compute correlations on a limited number of lags. | |
Note that binning point-processes with uniform bins, provides | |
signals that can be passed as argument to this function. | |
Arguments: |
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{ | |
"global": { | |
"check_for_updates_on_startup": true, | |
"show_in_menu_bar": true, | |
"show_profile_name_in_menu_bar": false | |
}, | |
"profiles": [ | |
{ | |
"complex_modifications": { | |
"parameters": { |
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function rest(dag) { | |
layering = d3.layeringSimplex() | |
decrossing = d3.decrossOpt() | |
coords = d3.coordQuad() |
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import pyranges as pr | |
gr = pr.PyRanges(chromosomes=["chr1"] * 2 + ["chr2"] * 2, starts=[0, 100, 200, 300], ends=[50, 150, 250, 350], strands=["+", "+", "-", "-"]) | |
gr.spliced_subsequence(0, -75, by="gene") | |
+--------------+-----------+-----------+--------------+------------+ | |
| Chromosome | Start | End | Strand | gene | | |
| (category) | (int64) | (int32) | (category) | (object) | | |
|--------------+-----------+-----------+--------------+------------| | |
| chr1 | 0 | 25 | + | 1 | |
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from typing import List | |
import polars as pl | |
import numpy as np | |
import bioframe.core.arrops as arrops | |
import pyoframe as pf | |
import polars as pl |
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