jlln

def splitDataFrameList(df,target_column,separator):
    ''' df = dataframe to split,
    target_column = the column containing the values to split
    separator = the symbol used to perform the split

    returns: a dataframe with each entry for the target column separated, with each element moved into a new row. 
    The values in the other columns are duplicated across the newly divided rows.
    '''
    def splitListToRows(row,row_accumulator,target_column,separator):
        split_row = row[target_column].split(separator)

teoliphant

# The kernel function is 
#   roughtly equivalent to new[:] = np.interp(xnew, xvals, yvals)
#   But this is broadcast so that it can be run many, many times 
#   quickly.

# Call using ynew = interp1d(xnew, xdata, ydata)
#   ynew.shape will be xnew.shape
#   Also, ydata.shape[-1] must be xdata.shape[-1]
#   and if ydata or xdata have ndim greater than 1, the initial dimensions
#   must be xnew.shape:

devisperessutti

# generic imports
import os
import imageio
import datetime
import numpy as np

# sentinelhub-py and eo-learn imports
from sentinelhub.geometry import BBox
from sentinelhub.constants import CRS, DataSource
from eolearn.core import EOTask, FeatureType, LinearWorkflow