# Copyright CNRS/Inria/UCA
# Contributor(s): Eric Debreuve (since 2021)
#
# eric.debreuve@cnrs.fr
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import matplotlib.pyplot as pypl
import numpy as nmpy
from scipy.ndimage import gaussian_filter

import cell_tracking_BC.OLD.task.pattern as ptrn


signal = nmpy.zeros(100, dtype=nmpy.float64)
signal[(signal.size // 2) :] = 2.0
signal = gaussian_filter(signal, 2)
signal += 0.2 * nmpy.random.randn(signal.size)

pattern_abscissa = nmpy.linspace(-5.0, 5.0, num=20)
pattern = 1.0 / (1.0 + nmpy.exp(-pattern_abscissa))

matching = ptrn.match_template(signal, pattern, pad_input=True, mode="edge")

pypl.plot(signal, "g-", label="Signal")
pypl.plot(pattern, "r-", label="Pattern")
pypl.plot(matching, "b-", label="Matching")
pypl.show()
