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#! /usr/bin/env python3
###########################################################
# The example shows how to get mapping data #
# The peak ratio at 1315 cm^-1 and 1380 cm^-1 are plotted #
# Details see Small 14, 1804006 (2018). #
###########################################################
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" / "streamline.wdf"
reader = WDFReader(filename)
print("Measurement: ", reader.measurement_type)
print("Scan: ", reader.scan_type)
assert reader.measurement_type == 3
assert reader.scan_type == 6
wn = reader.xdata
spectra = reader.spectra
print(wn.shape, spectra.shape)
x = reader.xpos
y = reader.ypos
print(len(x), len(y))
w, h = reader.map_shape
print("The size of mapping is {0:d} * {1:d}".format(w, h))
# 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
ratio_fl = ratio.flatten()
if plot is True:
plt.figure(figsize=(10, 5))
# Left plot histogram of Peak A/B ratio
plt.subplot(121)
img = mpimg.imread(reader.img, format="jpg")
img_x0, img_y0 = reader.img_origins
img_w, img_h = reader.img_dimensions
plt.imshow(img, extent=(img_x0, img_x0 + img_w, img_y0 + img_h, img_y0))
plt.scatter(x, y, s=0.4, alpha=0.8)
# plt.hist(ratio_fl, bins=50, range=(0.1, 2))
# plt.xlabel("Ratio peak A / peak B")
# plt.ylabel("Counts")
# Right plot histogram of Peak A/B mapping
plt.subplot(122)
plt.imshow(
peaks_b,
interpolation="bicubic",
extent=[0, x.max() - x.min(), y.max() - y.min(), 0],
)
# vmin=0.5, vmax=1.5)
plt.xlabel("Mapping x [μm]")
plt.ylabel("Mapping y [μm]")
cb = plt.colorbar()
cb.ax.set_title("Signal")
plt.tight_layout()
plt.show(block=False)
plt.pause(3)
plt.savefig(imgdir / "mapping_streamline.png", dpi=100)
plt.close()
else:
pass
return
if __name__ == "__main__":
main()
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