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#! /usr/bin/env python3
########################################################
# The example shows on top of example 5 how to extract #
# the white-light image #
########################################################
import numpy as np
from renishawWiRE import WDFReader
from _path import curdir, imgdir
try:
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
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)
# Test newer API
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
if plot is True:
# Must provide the format to read the optical image
img = mpimg.imread(reader.img, format="jpg")
img_x0, img_y0 = reader.img_origins
img_w, img_h = reader.img_dimensions
print(reader.img_dimensions)
plt.figure(figsize=(10, 5))
# Left, plot the white light image and rectangle area
plt.subplot(121)
# Show the image with upper origin extent See
# https://matplotlib.org/3.1.1/gallery/text_labels_and_annotations/text_alignment.html
plt.imshow(img, extent=(img_x0, img_x0 + img_w, img_y0 + img_h, img_y0))
# Add rectangle for marking
r = plt.Rectangle(
xy=(map_x.min(), map_y.min()), width=map_w, height=map_h, fill=False
)
plt.gca().add_patch(r)
plt.xlabel("Stage X [μm]")
plt.ylabel("Stage Y [μm]")
# Right plot histogram of Peak A/B mapping
plt.subplot(122)
plt.imshow(
ratio,
interpolation="bicubic",
extent=[0, map_w, map_h, 0],
vmin=0.5,
vmax=1.5,
)
plt.xlabel("Mapping x [μm]")
plt.ylabel("Mapping y [μm]")
cb = plt.colorbar()
cb.ax.set_title("Ratio")
plt.tight_layout()
plt.show(block=False)
plt.pause(3)
plt.savefig(imgdir / "map-optical.png", dpi=100)
plt.close()
else:
pass
return
if __name__ == "__main__":
main()
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