Spaces:
Running
Running
File size: 2,204 Bytes
bdf9096 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 |
import numpy as np
def split_list_in_half(array):
"""
https://stackoverflow.com/questions/752308/split-list-into-smaller-lists-split-in-half
:param array: array (list, ndarray)
:return: tuple with the first and the second half of the list
"""
half = len(array) // 2
return array[:half], array[half:]
def rescale_center(symmetrical_array, stat_func: callable = np.median):
"""
Rescales the data in the array center, and eliminates all the other values on the sides (setting to 0)
:param symmetrical_array: (nd)array symmetrical
:param stat_func: Some statistical function of an array: np.median (default), np.mean, ...
:return:
"""
symmetrical_array = rescale_array(symmetrical_array, stat_func)
return extinct_side_values(symmetrical_array)
def rescale_array(array, stat_func: callable = np.median, interp_range=None, lower_bound=None):
"""
Rescale an array from a range, of its statistical value (mean, median, min, ...) to the maximum,
into a new range `interp_range` (default: 0-1)
:param array:
:param stat_func: Some statistical function of an array: np.median (default), np.mean, ...
:param interp_range: the new range for the interpolation
:param lower_bound:
:return: the new interpolated array
"""
if interp_range is None:
interp_range = [0, 1]
if lower_bound is None:
lower_bound = stat_func(array)
return np.interp(array, [lower_bound, array.max()], interp_range)
def extinct_side_values(symmetrical_array, smaller_than=0):
"""
Takes an array and searches the first value from the center smaller than the given value.
All the border values from that criteria are zeroed
:param symmetrical_array: symmetrical (nd)array
:param smaller_than: int
Sets the criteria to find the index between the center and the border.
:return:
"""
right_i = np.argmax(split_list_in_half(symmetrical_array)[1] <= smaller_than)
center_i = len(symmetrical_array) // 2
new_y = np.zeros_like(symmetrical_array)
new_y[center_i - right_i:center_i + right_i] = symmetrical_array[center_i - right_i:center_i + right_i]
return new_y
|