# **************************************************************************
# *
# * Authors: J.M. De la Rosa Trevin (jmdelarosa@cnb.csic.es)
# * Slavica Jonic (slavica.jonic@upmc.fr)
# *
# * This program is free software; you can redistribute it and/or modify
# * it under the terms of the GNU General Public License as published by
# * the Free Software Foundation; either version 2 of the License, or
# * (at your option) any later version.
# *
# * This program is distributed in the hope that it will be useful,
# * but WITHOUT ANY WARRANTY; without even the implied warranty of
# * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# * GNU General Public License for more details.
# *
# * You should have received a copy of the GNU General Public License
# * along with this program; if not, write to the Free Software
# * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA
# * 02111-1307 USA
# *
# * All comments concerning this program package may be sent to the
# * e-mail address 'scipion@cnb.csic.es'
# *
# **************************************************************************
"""
This module implement the wrappers aroung Xmipp CL2D protocol
visualization program.
"""
from os.path import basename
from pyworkflow.protocol.params import StringParam, LEVEL_ADVANCED
from pyworkflow.viewer import (ProtocolViewer, DESKTOP_TKINTER, WEB_DJANGO)
from pyworkflow.protocol import params
from continuousflex.protocols.data import Point, Data
from continuousflex.viewers.nma_plotter import FlexNmaPlotter
from continuousflex.protocols import FlexProtAlignmentNMA
from pwem.emlib import MetaData, MDL_ORDER, MDL_ANGLE_ROT, MDL_ANGLE_TILT, MDL_ANGLE_PSI, MDL_SHIFT_X, MDL_SHIFT_Y, \
MDL_SHIFT_Z, MDL_NMA
from continuousflex.protocols.convert import l2
from xmippLib import SymList
import numpy as np
import tkinter.messagebox as mb
import matplotlib.pyplot as plt
from continuousflex.protocols.protocol_image_synthesize import FlexProtSynthesizeImages
FIGURE_LIMIT_NONE = 0
FIGURE_LIMITS = 1
X_LIMITS_NONE = 0
X_LIMITS = 1
Y_LIMITS_NONE = 0
Y_LIMITS = 1
Z_LIMITS_NONE = 0
Z_LIMITS = 1
METADATA_PROJECT = 0
METADATA_FILE = 1
[docs]class FlexAlignmentNMAViewer(ProtocolViewer):
""" Visualization of results from the NMA protocol
"""
_label = 'viewer nma alignment'
_targets = [FlexProtAlignmentNMA]
_environments = [DESKTOP_TKINTER, WEB_DJANGO]
def __init__(self, **kwargs):
ProtocolViewer.__init__(self, **kwargs)
self._data = None
[docs] def getData(self):
if self._data is None:
self._data = self.loadData()
return self._data
def _defineParams(self, form):
form.addSection(label='Visualization')
form.addParam('displayRawDeformation', StringParam, default='7 8',
label='Display the computed normal-mode amplitudes',
help='Type 7 to see the histogram of amplitudes along mode 7; \n'
'type 8 to see the histogram of amplitudes along mode 8, etc.\n'
'Type 7 8 to see the 2D plot of amplitudes along modes 7 and 8.\n'
'Type 7 8 9 to see the 3D plot of amplitudes along modes 7, 8 and 9; etc.'
)
form.addParam('limits_modes', params.EnumParam,
choices=['Automatic (Recommended)', 'Set manually Use upper and lower values'],
default=FIGURE_LIMIT_NONE,
label='Error limits', display=params.EnumParam.DISPLAY_COMBO,
help='If you want to use a range of Error in the color bar choose to set it manually.')
form.addParam('LimitLow', params.FloatParam, default=None,
condition='limits_modes==%d' % FIGURE_LIMITS,
label='Lower Error value',
help='The lower Error used in the graph')
form.addParam('LimitHigh', params.FloatParam, default=None,
condition='limits_modes==%d' % FIGURE_LIMITS,
label='Upper Error value',
help='The upper Error used in the graph')
form.addParam('xlimits_mode', params.EnumParam,
choices=['Automatic (Recommended)', 'Set manually x-axis limits'],
default=X_LIMITS_NONE,
label='x-axis limits', display=params.EnumParam.DISPLAY_COMBO,
help='This allows you to use a specific range of x-axis limits')
form.addParam('xlim_low', params.FloatParam, default=None,
condition='xlimits_mode==%d' % X_LIMITS,
label='Lower x-axis limit')
form.addParam('xlim_high', params.FloatParam, default=None,
condition='xlimits_mode==%d' % X_LIMITS,
label='Upper x-axis limit')
form.addParam('ylimits_mode', params.EnumParam,
choices=['Automatic (Recommended)', 'Set manually y-axis limits'],
default=Y_LIMITS_NONE,
label='y-axis limits', display=params.EnumParam.DISPLAY_COMBO,
help='This allows you to use a specific range of y-axis limits')
form.addParam('ylim_low', params.FloatParam, default=None,
condition='ylimits_mode==%d' % Y_LIMITS,
label='Lower y-axis limit')
form.addParam('ylim_high', params.FloatParam, default=None,
condition='ylimits_mode==%d' % Y_LIMITS,
label='Upper y-axis limit')
form.addParam('zlimits_mode', params.EnumParam,
choices=['Automatic (Recommended)', 'Set manually z-axis limits'],
default=Z_LIMITS_NONE,
label='z-axis limits', display=params.EnumParam.DISPLAY_COMBO,
help='This allows you to use a specific range of z-axis limits')
form.addParam('zlim_low', params.FloatParam, default=None,
condition='zlimits_mode==%d' % Z_LIMITS,
label='Lower z-axis limit')
form.addParam('zlim_high', params.FloatParam, default=None,
condition='zlimits_mode==%d' % Z_LIMITS,
label='Upper z-axis limit')
group = form.addGroup('Comparing with ground-truth', expertLevel=LEVEL_ADVANCED)
group.addParam('GroundTruth', params.EnumParam,
choices=['From volume synthesis protocol', 'From an external metadata file'],
default=METADATA_PROJECT,
label='Ground-Truth parameters', display=params.EnumParam.DISPLAY_COMBO,
help='Use this is only when testing the method with synthetic data')
group.addParam('SynthesisProject', params.PointerParam, pointerClass='FlexProtSynthesizeImages',
condition='GroundTruth==%d' % METADATA_PROJECT,
allowsNull=True,
label="Project for volume synthesize",
help='Select a previous run for subtomogram synthesize.')
group.addParam('MetadataFile', params.FileParam,
pointerClass='params.FileParam', allowsNull=True,
condition='GroundTruth==%d' % METADATA_FILE,
label="Metadata file (xmd)",
help='Choose a metadata file containing angles, shifts and NM amplitudes, typically a metadata'
' file from synthesizing volumes')
group.addParam('displayStatistics', params.LabelParam,
label="Display error statistics and plots?")
def _getVisualizeDict(self):
return {'displayRawDeformation': self._viewRawDeformation,
'displayStatistics': self._viewErrorStatistics,
}
def _viewRawDeformation(self, paramName):
components = self.displayRawDeformation.get()
return self._doViewRawDeformation(components)
def _doViewRawDeformation(self, components):
components = list(map(int, components.split()))
dim = len(components)
views = []
if dim > 0:
modeList = []
modeNameList = []
missingList = []
for modeNumber in components:
found = False
md = MetaData(self.protocol._getExtraPath('modes.xmd'))
for i, objId in enumerate(md):
modeId = md.getValue(MDL_ORDER, objId)
if modeNumber == modeId:
modeNameList.append('Mode %d' % modeNumber)
modeList.append(i)
found = True
break
if not found:
missingList.append(str(modeNumber))
if missingList:
return [self.errorMessage("Invalid mode(s) *%s*\n." % (', '.join(missingList)),
title="Invalid input")]
# Actually plot
if self.limits_modes == FIGURE_LIMIT_NONE:
plotter = FlexNmaPlotter(data=self.getData(),
xlim_low=self.xlim_low, xlim_high=self.xlim_high,
ylim_low=self.ylim_low, ylim_high=self.ylim_high,
zlim_low=self.zlim_low, zlim_high=self.zlim_high)
else:
plotter = FlexNmaPlotter(data=self.getData(),
LimitL=self.LimitLow, LimitH=self.LimitHigh,
xlim_low=self.xlim_low, xlim_high=self.xlim_high,
ylim_low=self.ylim_low, ylim_high=self.ylim_high,
zlim_low=self.zlim_low, zlim_high=self.zlim_high)
baseList = [basename(n) for n in modeNameList]
self.getData().XIND = modeList[0]
if dim == 1:
plotter.plotArray1D("Histogram of normal-mode amplitudes: %s" % baseList[0],
"Amplitude", "Number of images")
else:
self.getData().YIND = modeList[1]
if dim == 2:
plotter.plotArray2D("Normal-mode amplitudes: %s vs %s" % tuple(baseList), *baseList)
elif dim == 3:
self.getData().ZIND = modeList[2]
plotter.plotArray3D("Normal-mode amplitudes: %s %s %s" % tuple(baseList), *baseList)
views.append(plotter)
return views
def _viewErrorStatistics(self, paramName):
if self.GroundTruth.get() == METADATA_PROJECT:
metadata_file = self.SynthesisProject.get()._getExtraPath('GroundTruth.xmd')
else:
metadata_file = self.MetadataFile.get()
return self._doViewErrorStatistics(metadata_file)
def _doViewErrorStatistics(self, metadata_file):
md_gt = MetaData(metadata_file)
md_protocol = MetaData(self.protocol._getExtraPath('images.xmd'))
md_protocol.sort()
# Get the matching modes:
md_modes = MetaData(self.protocol._getExtraPath('modes.xmd'))
modeIds = []
for i, objId in enumerate(md_modes):
modeIds.append(md_modes.getValue(MDL_ORDER, objId))
# print(modeIds)
# Get the parameters from both lists:
rtp_protocol = []
xy_protocol = []
mode_ampl_protocol = []
rtp_gt = []
xy_gt = []
mode_ampl_gt = []
for objId in md_protocol:
rtp_protocol.append([md_protocol.getValue(MDL_ANGLE_ROT, objId),
md_protocol.getValue(MDL_ANGLE_TILT, objId),
md_protocol.getValue(MDL_ANGLE_PSI, objId)])
xy_protocol.append([md_protocol.getValue(MDL_SHIFT_X, objId),
md_protocol.getValue(MDL_SHIFT_Y, objId),])
mode_ampl_protocol.append(md_protocol.getValue(MDL_NMA, objId))
rtp_gt.append([md_gt.getValue(MDL_ANGLE_ROT, objId),
md_gt.getValue(MDL_ANGLE_TILT, objId),
md_gt.getValue(MDL_ANGLE_PSI, objId)])
xy_gt.append([md_gt.getValue(MDL_SHIFT_X, objId),
md_gt.getValue(MDL_SHIFT_Y, objId)])
mode_ampl_gt.append(md_gt.getValue(MDL_NMA, objId))
# Angular and shift distances
shift_distance = []
angular_distance = []
# The full description of computeDistanceAngles function is:
# A = SymList.computeDistanceAngles(SymList(), rot1, tilt1, psi1, rot2, tilt2, psi2, projdir_mode, check_mirrors, object_rotation)
# By default, they are all set to False. However, check_mirrors should be true in general.
for i in range(len(rtp_protocol)):
shift_distance.append(l2(xy_gt[i], xy_protocol[i]))
angular_distance.append(SymList.computeDistanceAngles(SymList(),
rtp_protocol[i][0], rtp_protocol[i][1], rtp_protocol[i][2],
rtp_gt[i][0], rtp_gt[i][1], rtp_gt[i][2],
False, True, False))
# Normal mode amplitudes distances: we need to find the subset of normal modes used in alignment in the groundtruth
mode_distances = []
counter = 0
plt.figure()
mean_amplitudes = []
std_amplitudes = []
label = []
dist = []
for i in modeIds:
# mode 7 corresponds to zero in the ground truth, so we need to subtract 7
A = np.array(mode_ampl_gt)[:,i - 7]
B = np.array(mode_ampl_protocol)[:, counter]
mean_amplitudes.append(np.mean(np.array(A - B)))
std_amplitudes.append(np.std(np.array(A - B)))
label.append('mode ' + str(i))
dist.append(np.array(A - B))
counter +=1
plt.title('histogram of normal mode amplitude distances')
plt.hist(dist, bins=100, label=label)
plt.legend(loc='upper right')
plt.figure()
plt.hist(np.array(angular_distance), bins=100)
plt.title('histogram of angular distance')
plt.figure()
plt.hist(np.array(shift_distance), bins=100)
plt.title('histogram of shift distance')
message = 'mean and standard deviation angular distance: ' + str(np.mean(np.array(angular_distance)))[:7]
message += ' and ' + str(np.std(np.array(angular_distance)))[:7]
message += '\nmean and standard deviation shift distance: ' + str(np.mean(np.array(shift_distance)))[:7]
message += ' and ' + str(np.std(np.array(shift_distance)))[:7]
counter = 0
for i in modeIds:
message += '\nmean and standard deviation for mode ' + str(i) + ': ' + str(mean_amplitudes[counter])[:7] + \
' ' + str(std_amplitudes[counter])[:7]
counter +=1
mb.showinfo('Distances compared to the ground truth', message)
plt.show()
pass
[docs] def loadData(self):
""" Iterate over the images and their deformations
to create a Data object with theirs Points.
"""
particles = self.protocol.outputParticles
data = Data()
for i, particle in enumerate(particles):
pointData = list(map(float, particle._xmipp_nmaDisplacements))
data.addPoint(Point(pointId=particle.getObjId(),
data=pointData,
weight=particle._xmipp_cost.get()))
return data