from spym.generic import Spm_image, load_from_gsf
import matplotlib.pyplot as plt
import numpy as np
file_name = 'wg_berk-0deg_n2_6um_000_TR.gsf'
#file_name = 'BMG8-zr60cu30al10_375c_10mN_6um_000_TR.gsf'
image =load_from_gsf(file_name)
image.change_xy_unit('um')
image.change_z_unit('nm')
image = image.crop(5,5,5,5)
image.center_min()
X, Y, Z = image.get_xyz()
r = 2.
mask = np.where(X[0]**2 > r**2, 0., np.nan )
image, residual = image.line_fit(mask = mask)
X, Y, Z = image.get_xyz()
xlabel, ylabel, zlabel = image.get_labels()
# Let's define some paths:
s = np.linspace(-5., 5., 100)
# A tilted line to produce a section
angle0 = 55.
xc = 0.
yc = 0.
x0 = np.cos(np.radians(angle0)) * s + xc
y0 = np.sin(np.radians(angle0)) * s + yc
X0, Y0, Z0 = image.interpolate(x0, y0)
x1 = np.cos(np.radians(angle0 + 120.)) * s + xc
y1 = np.sin(np.radians(angle0 + 120.)) * s + yc
X1, Y1, Z1 = image.interpolate(x1, y1)
x2 = np.cos(np.radians(angle0 - 120.)) * s + xc
y2 = np.sin(np.radians(angle0 - 120.)) * s + yc
from matplotlib import cm
import numpy as np
file_name = 'planilux_berk_10mN_6um.gsf'
# This script is intended to be used on "Gwyddion Simple File" (GSF) files. This choice is motivated by the fact that Gwyddion can open most of the proprietary files standards produced by AFM/SPM commercial devices and can then save them to the open format GSF.
name = 'planilux_berk_10mN_6um.gsf' # GSF File path
# GRAPHICAL SETTINGS
levels = 100 # Number of levels on the color maps
fs = 12. # Font size
alpha = 2.5 # Cross section tilt
med_filt_size = None # If the image is noisy, a median filter can be applied, put a number greater than 1 (eg. 3).
cmap = cm.jet
# IMAGE PREPROCESSING
image = load_from_gsf(file_name) # Image loading
image = image.crop(
cx0=10, cx1=10, cy0=10, cy1=10
) # Light crop in order to remove artifacts on the extremities of the scans
image.change_xy_unit('um') # Setting xy units
image.change_z_unit('nm') # Setting z unit
xlabel, ylabel, zlabel = image.get_labels(
) # Getting labels for ploting purpose
X0, Y0, Z0 = image.get_xyz() # Getting raw image data
image.center_min() # Offseting to center the bottom of the indent
X1, Y1, Z1 = image.get_xyz() # Getting centered image data for masking purpose
R2 = X1**2 + Y1**2 # Building a mask
r = min(X1.max(), -X1.min(), Y1.max(), -Y1.min())
k = .8
mask = np.where(R2 > r**2 * k**2, 1.,
np.nan) # Circular mask filled with 1 and NaN
from spym.generic import Spm_image, load_from_gsf
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
matplotlib.rcParams['contour.negative_linestyle'] = 'solid'
#file_name = 'wg_berk-0deg_n2_6um_000_TR.gsf'
file_name = 'BMG8-zr60cu30al10_375c_10mN_6um_000_TR.gsf'
image = load_from_gsf(file_name)
image.change_xy_unit('um')
image.change_z_unit('nm')
X, Y, Z = image.get_xyz()
xlabel, ylabel, zlabel = image.get_labels()
# Translation
image = image.translate(nx=30, ny=-50)
levels = 10
Xr, Yr, Zr = image.get_xyz()
fig = plt.figure(0)
plt.clf()
ax = fig.add_subplot(121)
ax.set_aspect('equal')
plt.title('Original')
grad = plt.contourf(X, Y, Z, levels)
plt.contour(X, Y, Z, levels, colors='black')
cbar = plt.colorbar(grad)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
cbar.set_label(zlabel)
ax = fig.add_subplot(122)
ax.set_aspect('equal')
plt.title('Translate')
file_name = 'planilux_berk_10mN_6um.gsf'
# This script is intended to be used on "Gwyddion Simple File" (GSF) files. This choice is motivated by the fact that Gwyddion can open most of the proprietary files standards produced by AFM/SPM commercial devices and can then save them to the open format GSF.
name = 'planilux_berk_10mN_6um.gsf' # GSF File path
# GRAPHICAL SETTINGS
levels = 100 # Number of levels on the color maps
fs = 12. # Font size
alpha = 2.5 # Cross section tilt
med_filt_size = None # If the image is noisy, a median filter can be applied, put a number greater than 1 (eg. 3).
cmap = cm.jet
# IMAGE PREPROCESSING
image = load_from_gsf(file_name) # Image loading
image = image.crop(cx0 = 10, cx1= 10, cy0 = 10, cy1= 10) # Light crop in order to remove artifacts on the extremities of the scans
image.change_xy_unit('um') # Setting xy units
image.change_z_unit('nm') # Setting z unit
xlabel, ylabel, zlabel = image.get_labels() # Getting labels for ploting purpose
X0, Y0, Z0 = image.get_xyz() # Getting raw image data
image.center_min() # Offseting to center the bottom of the indent
X1, Y1, Z1 = image.get_xyz() # Getting centered image data for masking purpose
R2 = X1**2 + Y1**2 # Building a mask
r = min( X1.max(), -X1.min(), Y1.max(), -Y1.min())
k = .8
mask = np.where(R2 > r**2 * k**2, 1., np.nan ) # Circular mask filled with 1 and NaN
image, trash = image.line_fit(mask = mask)
image = image.crop(cx0 = 40, cx1= 40, cy0 = 40, cy1= 40) # Cropping to keep only the indent
X, Y, Z = image.get_xyz() # Final image data
contour, area = Watershed(image, angle = 2.5)
from spym.generic import load_from_gsf
import numpy as np
file_name = 'WG-air_10mN_001_TF.gsf'
file_name = 'BMG8-zr60cu30al10_375c_10mN_6um_000_TR.gsf'
image = load_from_gsf(file_name) # Load the image
# Perform some operations
image.change_xy_unit('um')
image.change_z_unit('nm')
image = image.crop(5,5,5,5)
X, Y, Z = image.get_xyz()
xi = X[image.get_min_position()]
yi = Y[image.get_min_position()]
r = 2.
mask = np.where((X-xi)**2 + (Y-yi)**2 > r**2, 0., np.nan )
image, residual = image.line_fit(mask = mask)
image.center_min()
# Save it again
image.dump2gsf(file_name.replace('.', '_linefit.'))
from spym.generic import Spm_image, load_from_gsf
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
matplotlib.rcParams['contour.negative_linestyle'] = 'solid'
#file_name = 'wg_berk-0deg_n2_6um_000_TR.gsf'
file_name = 'BMG8-zr60cu30al10_375c_10mN_6um_000_TR.gsf'
image = load_from_gsf(file_name) # Load the image
image.change_xy_unit('um')
image.change_z_unit('nm')
xlabel, ylabel, zlabel = image.get_labels()
X, Y, Z = image.get_xyz()
loc = image.get_min_position()
xc, yc = X[loc], Y[loc]
image.set_center(xc=xc, yc=yc)
X, Y, Z = image.get_xyz()
image = image.rotate(angle=30., tx=0., ty=0.)
levels = 10
Xr, Yr, Zr = image.get_xyz()
fig = plt.figure(0)
plt.clf()
ax = fig.add_subplot(121)
ax.set_aspect('equal')
plt.title('Original')
grad = plt.contourf(X, Y, Z, levels)
plt.contour(X, Y, Z, levels, colors='black')
cbar = plt.colorbar(grad)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
cbar.set_label(zlabel)
from spym.generic import load_from_gsf
import matplotlib.pyplot as plt
file_name = 'WG-air_10mN_001_TF.gsf'
im = load_from_gsf(file_name)
im.change_xy_unit('um')
im.change_z_unit('nm')
plt.figure()
plt.clf()
X,Y,Z = im.get_xyz()
xlabel, ylabel, zlabel = im.get_labels()
plt.xlabel(xlabel)
plt.ylabel(ylabel)
grad = plt.contourf(X,Y,Z, 100)
cbar = plt.colorbar(grad)
cbar.set_label(zlabel)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.gca().set_aspect('equal')
plt.grid()
plt.show()
from spym.generic import load_from_gsf
import matplotlib.pyplot as plt
file_name = 'WG-air_10mN_001_TF.gsf'
im = load_from_gsf(file_name)
im.change_xy_unit('um')
im.change_z_unit('nm')
plt.figure()
plt.clf()
X, Y, Z = im.get_xyz()
xlabel, ylabel, zlabel = im.get_labels()
plt.xlabel(xlabel)
plt.ylabel(ylabel)
grad = plt.contourf(X, Y, Z, 100)
cbar = plt.colorbar(grad)
cbar.set_label(zlabel)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.gca().set_aspect('equal')
plt.grid()
plt.show()
