def _showMollweide(self, param=None):
""" This plot script is based on two scripts by their respective authors:
- PlotOD.py from cryoEF package
- https://github.com/PirateFernandez/python3_rln_scripts/blob/main/rln_star_2_mollweide_any_star.py
"""
import numpy as np
from matplotlib import spines
from scipy.stats import gaussian_kde
views = []
xplotter = EmPlotter(
windowTitle="Mollweide projection plot of orientation distribution"
)
fn = np.genfromtxt(self.protocol._getFileName('anglesFn'),
delimiter=' ')
phi = fn[:, 0]
theta = fn[:, 1]
# Convert degrees to radians and obey angular range conventions
x = phi / 180 * np.pi # x is the phi angle (longitude)
y = theta / 180 * np.pi # y is the theta angle (latitude)
y = -1 * y + np.pi / 2 # The convention in RELION is [0, 180] for theta,
# whereas for the projection function it is [90, -90], so this conversion is required.
vertical_rad = np.vstack([y, x])
m = gaussian_kde(vertical_rad)(vertical_rad)
ax = xplotter.createSubPlot('', 'phi', 'theta', projection="mollweide")
# Plot your points on the projection
#ax.plot(x, y, ',', alpha=0.5, color='#64B5F6') # alpha - transparency (from 0 to 1), color - specify hex code
a = ax.scatter(x, y, cmap='plasma', c=m, s=2, alpha=0.4)
# Draw the horizontal and the vertical grid lines. Can add more grid lines if required.
major_ticks_x = [-np.pi, -np.pi / 2, 0, np.pi / 2, np.pi]
major_ticks_y = [-np.pi / 2, -np.pi / 4, 0, np.pi / 4, np.pi / 2]
ax.set_xticks(major_ticks_x)
ax.set_yticks(major_ticks_y)
ax.set_xticklabels([
'-180$^\circ$', '-90$^\circ$', '0$^\circ$', '90$^\circ$',
'180$^\circ$'
],
color='grey')
ax.set_yticklabels([
'-90$^\circ$', '-45$^\circ$', '0$^\circ$', '45$^\circ$',
'90$^\circ$'
],
color='grey')
# Set the color and the thickness of the grid lines
ax.grid(which='both', linestyle='--', linewidth=1, color='#555F61')
# Set the color and the thickness of the outlines
for child in ax.get_children():
if isinstance(child, spines.Spine):
child.set_color('#555F61')
xplotter.getColorBar(a)
xplotter.tightLayout()
xplotter.show()
return views.append(xplotter)
def _showVolumeColorSlices(self, param=None):
imageFile = self.protocol._getFileName(RESMAP_VOL)
imgData, _, _, _ = self.getImgData(imageFile)
xplotter = EmPlotter(x=2,
y=2,
mainTitle="Local Resolution Slices "
"along %s-axis." % self._getAxis())
# The slices to be shown are close to the center. Volume size is divided
# in segments, the fourth central ones are selected i.e. 3,4,5,6
for i in list(range(3, 7)):
sliceNumber = self.getSlice(i, imgData)
a = xplotter.createSubPlot("Slice %s" % (sliceNumber + 1), '', '')
matrix = self.getSliceImage(imgData, sliceNumber, self._getAxis())
plot = xplotter.plotMatrix(a,
matrix,
self.lowest.get(),
self.highest.get(),
cmap=self.getColorMap(),
interpolation="nearest")
xplotter.getColorBar(plot)
return [xplotter]
def _showOneColorslice(self, param=None):
imageFile = self.protocol._getFileName(RESMAP_VOL)
imgData, _, _, volDims = self.getImgData(imageFile)
print(volDims)
xplotter = EmPlotter(x=1,
y=1,
mainTitle="Local Resolution Slices "
"along %s-axis." % self._getAxis())
sliceNumber = self.sliceNumber.get()
if sliceNumber < 0:
sliceNumber = volDims[0] / 2
else:
sliceNumber -= 1
# sliceNumber has no sense to start in zero
a = xplotter.createSubPlot("Slice %s" % (sliceNumber + 1), '', '')
matrix = self.getSliceImage(imgData, sliceNumber, self._getAxis())
plot = xplotter.plotMatrix(a,
matrix,
self.lowest.get(),
self.highest.get(),
cmap=self.getColorMap(),
interpolation="nearest")
xplotter.getColorBar(plot)
return [xplotter]
