goatpy.io

Functions

parmap(f, X[, nprocs])	Parallel map using joblib (more robust for Jupyter).
getimage(peak, path[, tol])
rd_peaks(fn)
rd_peaks_from_package()
glyco_spatialdata(imzml_path[, peaks_path, tol, ...])
centroids_to_pixel_squares(df[, x_col, y_col, pixel_size])

Module Contents

goatpy.io.parmap(f, X, nprocs=None)

Parallel map using joblib (more robust for Jupyter).

Parameters:

• f (callable) – Function to apply to each element

• X (iterable) – Input data

• nprocs (int, optional) – Number of processes (default: -1, all CPUs)

Returns:

Results in same order as input

Return type:

list

goatpy.io.getimage(peak, path, tol=0.1)

goatpy.io.rd_peaks(fn)

goatpy.io.rd_peaks_from_package()

goatpy.io.glyco_spatialdata(imzml_path, peaks_path=None, tol=0.1, pixel_size=20)

goatpy.io.centroids_to_pixel_squares(df, x_col='x', y_col='y', pixel_size=1.0)