(numpy_arrays, gaussian_size, clip)
return ((min_value, max_value), heatmap)
Convert list of arrays into a heatmap.
    The stages and values are chosen with trial and error, 
    so this function is still open to improvement.
Convert list of arrays into a heatmap.
    The stages and values are chosen with trial and error, 
    so this function is still open to improvement.
Convert list of arrays into a heatmap . The stages and values are chosen with trial and error so this function is still open to improvement .
def arrays_to_heatmap(numpy_arrays, gaussian_size, clip):
    """Convert list of arrays into a heatmap.
    The stages and values are chosen with trial and error, 
    so this function is still open to improvement.
    """
    
    #Add all arrays together
    Message(LANGUAGE.strings['Generation']['ArrayMerge'])
    merged_arrays = numpy.merge(numpy_arrays, 'add', 'float64')
    
    #Set to constant values
    Message(LANGUAGE.strings['Generation']['ArrayRemap'])
    flattened = numpy.remap_to_range(merged_arrays)
    
    #Blur the array
    if gaussian_size:
        Message(LANGUAGE.strings['Generation']['ArrayBlur'])
        heatmap = blur(flattened, gaussian_size)
    else:
        heatmap = flattened
    
    Message(LANGUAGE.strings['Generation']['ArrayRange'])
    min_value = numpy.min(heatmap)
    
    #Lower the maximum value a little
    all_values = numpy.sort(heatmap.ravel(), unique=True)
    max_value = all_values[round_int(all_values.size * clip)]
    
    return ((min_value, max_value), heatmap)
def arrays_to_heatmap ( numpy_arrays , gaussian_size , clip ) : #Add all arrays together Message ( LANGUAGE . strings [ 'Generation' ] [ 'ArrayMerge' ] ) merged_arrays = numpy . merge ( numpy_arrays , 'add' , 'float64' ) #Set to constant values Message ( LANGUAGE . strings [ 'Generation' ] [ 'ArrayRemap' ] ) flattened = numpy . remap_to_range ( merged_arrays ) #Blur the array if gaussian_size : Message ( LANGUAGE . strings [ 'Generation' ] [ 'ArrayBlur' ] ) heatmap = blur ( flattened , gaussian_size ) else : heatmap = flattened Message ( LANGUAGE . strings [ 'Generation' ] [ 'ArrayRange' ] ) min_value = numpy . min ( heatmap ) #Lower the maximum value a little all_values = numpy . sort ( heatmap . ravel ( ) , unique = True ) max_value = all_values [ round_int ( all_values . size * clip ) ] return ( ( min_value , max_value ) , heatmap )