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id: org.psychopy.PsychoPy | |
runtime: org.freedesktop.Platform | |
runtime-version: '22.08' | |
sdk: org.freedesktop.Sdk | |
command: psychopy | |
finish-args: | |
- --device=dri | |
- --device=input | |
- --filesystem=home | |
- --filesystem=host-os |
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pkgbase = rstudio-desktop-bin | |
pkgdesc = An integrated development environment (IDE) for R (binary from RStudio official repository) | |
pkgver = 2024.12.1.563 | |
pkgrel = 1 | |
url = https://posit.co/products/open-source/rstudio/ | |
arch = x86_64 | |
license = AGPL | |
depends = r>=3.3.0 | |
depends = ttf-dejavu | |
provides = rstudio-desktop=2024.12.1.563 |
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import numpy as np | |
import pandas as pd | |
import mne | |
files = ["data/black-white_gaming1.bdf", "data/black-white_standard3.bdf"] | |
rows = [] | |
n = 100 # expected number of events | |
mne.set_log_level("ERROR") |
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from pathlib import Path | |
import mne | |
fpath = Path(mne.datasets.sample.data_path()) / "MEG" / "sample" | |
raw = mne.io.read_raw_fif(fpath / "sample_audvis_filt-0-40_raw.fif") |
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import matplotlib.pyplot as plt | |
from matplotlib.animation import FuncAnimation | |
import numpy as np | |
from scipy.stats import norm | |
fps = 25 | |
fig, ax = plt.subplots(figsize=(8, 6)) | |
x = np.linspace(0, 20, 1000) |
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package_versions <- function(packages=NULL, base=FALSE, sort=FALSE) { | |
#' Determine package versions. | |
#' | |
#' @param packages Packages to query; if not specified (or \code{NULL}), | |
#' all currently attached packages are queried. | |
#' @param base If \code{TRUE}, include the base package (R version). | |
#' @param sort If \code{TRUE}, sort package names alphabetically. | |
#' @return Data frame with package names and corresponding versions. | |
if (is.null(packages)) | |
packages <- names(sessionInfo()$otherPkgs) |
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import numpy as np | |
def dependence_factor(a, b, norm=True): | |
"""Compute measure of dependence between a and b. | |
Independent means that Pab(i,j) - Pa(i) * Pa(j) == 0 for all i and j, where | |
i and j are the individual values that the variables a and b can take. | |
If norm=True, this function returns a value between 0 and 1, where 1 means |