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#! /usr/bin/env python3
########################################################
# The example shows on top of example 6 how to overlay #
# the cropped image with mapping #
########################################################
import numpy as np
from renishawWiRE import WDFReader
from _path import curdir, imgdir
try:
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import PIL
plot = True
except ImportError:
plot = False
def peak_in_range(spectra, wn, range, method="max", **params):
"""Find the max intensity of peak within range
method can be max, min, or mean
"""
cond = np.where((wn >= range[0]) & (wn <= range[1]))[0]
spectra_cut = spectra[:, :, cond]
return getattr(np, method)(spectra_cut, axis=2, **params)
def main():
filename = curdir / "spectra_files" / "mapping.wdf"
reader = WDFReader(filename)
assert reader.measurement_type == 3
wn = reader.xdata
spectra = reader.spectra
print(wn.shape, spectra.shape)
map_x = reader.xpos
map_y = reader.ypos
map_w = reader.map_info["x_span"]
map_h = reader.map_info["y_span"]
# w and h are the measure in xy coordinates
# Level the spectra
spectra = spectra - np.min(spectra, axis=2, keepdims=True)
peaks_a = peak_in_range(spectra, wn, [1295, 1340])
peaks_b = peak_in_range(spectra, wn, [1350, 1400])
ratio = peaks_a / peaks_b
extent = [0, map_w, map_h, 0]
if plot is True:
# Must provide the format to read the optical image
# img = mpimg.imread(reader.img, format="jpg")
img = PIL.Image.open(reader.img)
print(reader.img_cropbox)
# Desaturate the whitelight image
img1 = img.crop(box=reader.img_cropbox).convert("L")
plt.figure(figsize=(6, 6))
# Left, plot the white light image and rectangle area
# Show the image with upper origin extent See
# https://matplotlib.org/3.1.1/gallery/text_labels_and_annotations/text_alignment.html
plt.imshow(img1, alpha=0.5, cmap="hot", extent=extent)
# Right plot histogram of Peak A/B mapping
cm = plt.imshow(
ratio,
interpolation="bicubic",
alpha=0.5,
cmap="viridis_r",
extent=extent,
vmin=0.5,
vmax=1.5,
)
plt.xlabel("Mapping x [μm]")
plt.ylabel("Mapping y [μm]")
cb = plt.colorbar(cm)
cb.ax.set_title("Ratio")
plt.title("50% Optical + 50% Raman")
plt.tight_layout()
plt.show(block=False)
plt.pause(3)
plt.savefig(imgdir / "map-overlay.png", dpi=100)
plt.close()
else:
pass
return
if __name__ == "__main__":
main()
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