Processing data and making figures

This notebook opens a Nanosurf image file, levels it, masks the features so they do not disturb the leveling, and makes figures for a report. Run it from this folder, next to MoS2.nid.

from NSFopen.process import process

import matplotlib.pyplot as plt

Open the file

afm.channels lists what the file holds. Every processing and plot function works on one channel, by default the forward height. afm.array() gives a channel as a plain array in SI units, for your own calculations.

afm = process("MoS2.nid")
print(afm.channels)

z = afm.array()  # the forward height, in m
width, height = afm.size()  # in m
print(f"{z.shape[1]} x {z.shape[0]} pixels, {width * 1e6:.2f} x {height * 1e6:.2f} um, unit {afm.unit()}")

{'Forward': ['Z-Axis', 'Amplitude', 'Phase', 'Z-Axis Sensor'], 'Backward': ['Z-Axis', 'Amplitude', 'Phase', 'Z-Axis Sensor']}
512 x 256 pixels, 3.97 x 3.97 um, unit m

Level the lines

flatten subtracts a straight line from every scan line. The unit, labels and color bar come from the file. color_range='p1' leaves the top and bottom 1 % of the pixels out of the color scale, so a few spikes cannot wash out the picture.

afm.flatten(order=1)

fig = afm.image(color_range="p1")
plt.show()

The bright islands pull the fit of every line they cross, which leaves dark bands beside them. To fix that, mask everything higher than 2 nm and fit the lines only to the rest. Heights are in m, so 2 nm is 2e-9.

afm.set_mask(afm.array() > 2e-9)
afm.flatten(order=1, fit_on="exclude")

fig = afm.image(color_range="p1", show_mask=True)
plt.show()

Figures for a report

The same call with a scale bar and without a title, and a dark version. To keep a figure, use fig.savefig("MoS2.png").

fig = afm.image(color_range="p1", scalebar=True, title=None, figsize=(5, 4))
plt.show()

fig = afm.image(color_range="p1", scalebar=True, title=None, figsize=(5, 4), theme="dark", cmap="Gold")
plt.show()

Pass ax= to put several plots into one figure. layout='constrained' keeps their labels apart.

fig, axes = plt.subplots(1, 2, figsize=(10, 4), layout="constrained", dpi=150)
afm.image(ax=axes[0], color_range="p1")
afm.hist(ax=axes[1], color_range="p1", bins=500)
axes[1].set_xlim(-2, 4)  # in nm; the few high spikes would otherwise stretch the axis to 25 nm
plt.show()

3D

z_scale sets how tall the height range looks. plot3d colors by height, or draws a material under a light; rotation, tilt and light change the view, see help(afm.plot3d).

fig = afm.plot3d(color_range="p1", z_scale=0.15)
plt.show()

fig = afm.plot3d(material="Gold", z_scale=0.15, rotation=-40, tilt=60)
plt.show()