# **************************************************************************
# *
# * Authors: Josue Gomez Blanco (josue.gomez-blanco@mcgill.ca)
# *
# * Unidad de Bioinformatica of Centro Nacional de Biotecnologia , CSIC
# *
# * 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 3 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'
# *
# **************************************************************************
import logging
logger = logging.getLogger(__name__)
from math import radians, degrees
import numpy as np
import matplotlib.cm as cm
from scipy.ndimage.filters import gaussian_filter
from pwem.convert.transformations import euler_from_matrix
from pyworkflow.gui.plotter import Plotter, plt
import pwem.emlib.metadata as md
import numbers
[docs]class EmPlotter(Plotter):
""" Class to create several plots. """
def __init__(self, x=1, y=1, mainTitle="", **kwargs):
Plotter.__init__(self, x, y, mainTitle, **kwargs)
[docs] def plotAngularDistribution(self, title, rot,
tilt, weight=[], max_p=40,
min_p=5, color='blue'):
""" Create a special type of subplot, representing the angular
distribution of weight projections. """
if weight:
max_w = max(weight)
min_w = min(weight)
a = self.createSubPlot(title,
'Min weight=%(min_w).2f, Max weight=%(max_w).2f'
% locals(), '', projection='polar')
pointSizes = []
for r, t, w in zip(rot, tilt, weight):
pointsize = int((w - min_w) / (max_w - min_w + 0.001) * (max_p - min_p) + min_p)
pointSizes.append(pointsize)
a.scatter(rot, tilt, s=pointSizes, c=color, marker='.')
else:
a = self.createSubPlot(title, 'Non weighted plot', '', projection='polar')
a.scatter(rot, tilt, s=10, c=color, marker='.')
return a
[docs] def plotAngularDistributionHistogram(self, title, rot, tilt):
""" Create a special type of subplot, representing the angular
distribution of weight projections. """
heatmap, xedges, yedges = np.histogram2d(rot, tilt, bins=100)
sigma = min(max(xedges) - min(xedges), max(yedges) - min(yedges)) / 20
heatmap = gaussian_filter(heatmap, sigma=sigma)
heatmapImage = heatmap.T
extent = [xedges[0], xedges[-1], yedges[0], yedges[-1]]
a = self.createSubPlot(title, 'Angular distribution', '')
mappable = a.imshow(heatmapImage, extent=extent, origin='lower', cmap=cm.jet, aspect='auto')
a.set_xlabel('Rotational angle')
a.set_ylabel('Tilt angle')
return mappable
[docs] def plotAngularDistributionFromSet(self, mdSet, title, weightAttr=None, histogram=False, **kwargs):
""" Read the values of the transformation matrix
and plot its histogram or its angular distribution.
:param mdSet: Set with alignment information at with item.getTransform()
:param title: Title of the plot
"""
rots = []
tilts = []
weights = []
if histogram:
for item in mdSet:
rot, tilt, psi = euler_from_matrix(item.getTransform().getMatrix())
rots.append(rot)
tilts.append(tilt)
return self.plotAngularDistributionHistogram(title, rots, tilts)
else:
for item in mdSet:
psi, tilt, rot = euler_from_matrix(item.getTransform().getMatrix(), axes="szyz" )
rots.append(rot)
tilts.append(degrees(tilt))
if weightAttr:
weight = getattr(item, weightAttr).get()
weights.append(weight)
return self.plotAngularDistribution(title, rots, tilts, weights, **kwargs)
[docs] def plotAngularDistributionFromMd(self, mdFile, title, **kwargs):
""" Read the values of rot, tilt and weights from
the metadata and plot the angular distribution.
ANGLES are in DEGREES
In the metadata:
rot: MDL_ANGLE_ROT
tilt: MDL_ANGLE_TILT
weight: MDL_WEIGHT
"""
angMd = md.MetaData(mdFile)
rot = []
tilt = []
if 'histogram' in kwargs:
for row in md.iterRows(angMd):
rot.append(row.getValue(md.MDL_ANGLE_ROT))
tilt.append(row.getValue(md.MDL_ANGLE_TILT))
return self.plotAngularDistributionHistogram(title, rot, tilt)
else:
weight = []
for row in md.iterRows(angMd):
rot.append(radians(row.getValue(md.MDL_ANGLE_ROT)))
tilt.append(row.getValue(md.MDL_ANGLE_TILT))
weight.append(row.getValue(md.MDL_WEIGHT))
return self.plotAngularDistribution(title, rot, tilt, weight, **kwargs)
[docs] def plotHist(self, yValues, nbins, color='blue', **kwargs):
""" Create a histogram. """
# In some cases yValues is a generator, which cannot be indexed
self.hist(list(yValues), nbins, facecolor=color, **kwargs)
[docs] def plotScatter(self, xValues, yValues, color='blue', **kwargs):
""" Create an scatter plot. """
self.scatterP(xValues, yValues, c=color, **kwargs)
[docs] def plotMatrix(self, img
, matrix
, vminData
, vmaxData
, cmap='jet'
, xticksLablesMajor=None
, yticksLablesMajor=None
, rotationX=90.
, rotationY=0.
, **kwargs):
interpolation = kwargs.pop('interpolation', "none")
plot = img.imshow(matrix, interpolation=interpolation, cmap=cmap,
vmin=vminData, vmax=vmaxData, **kwargs)
if xticksLablesMajor is not None:
plt.xticks(range(len(xticksLablesMajor)),
xticksLablesMajor[:len(xticksLablesMajor)],
rotation=rotationX)
if yticksLablesMajor is not None:
plt.yticks(range(len(yticksLablesMajor)),
yticksLablesMajor[:len(yticksLablesMajor)],
rotation=rotationY)
return plot
[docs] def plotData(self, xValues, yValues, color='blue', **kwargs):
""" Shortcut function to plot some values.
Params:
xValues: list of values to show in x-axis
yValues: list of values to show as values in y-axis
color: color for the plot.
**kwargs: keyword arguments that accepts:
marker, linestyle
"""
self.plot(xValues, yValues, color, **kwargs)
[docs] def plotDataBar(self, xValues, yValues, width, color='blue', **kwargs):
""" Shortcut function to plot some values.
Params:
xValues: list of values to show in x-axis
yValues: list of values to show as values in y-axis
color: color for the plot.
**kwargs: keyword arguments that accepts:
marker, linestyle
"""
self.bar(xValues, yValues, width=width, color=color, **kwargs)
[docs] @classmethod
def createFromFile(cls, dbName, dbPreffix, plotType, columnsStr, colorsStr, linesStr,
markersStr, xcolumn, ylabel, xlabel, title, bins, orderColumn,
orderDirection):
columns = columnsStr.split()
colors = colorsStr.split()
lines = linesStr.split()
markers = markersStr.split()
data = PlotData(dbName, dbPreffix, orderColumn, orderDirection)
plotter = Plotter(windowTitle=title)
ax = plotter.createSubPlot(title, xlabel, ylabel)
xvalues = data.getColumnValues(xcolumn) if xcolumn else range(0, data.getSize())
for i, col in enumerate(columns):
yvalues = data.getColumnValues(col)
color = colors[i]
line = lines[i]
colLabel = col if not col.startswith("_") else col[1:]
if bins:
yvalues = data._removeInfinites(yvalues)
ax.hist(yvalues, bins=int(bins), color=color, linestyle=line, label=colLabel)
else:
if plotType == 'Plot':
marker = (markers[i] if not markers[i] == 'none' else None)
ax.plot(xvalues, yvalues, color, marker=marker, linestyle=line, label=colLabel)
else:
ax.scatter(xvalues, yvalues, c=color, label=col, alpha=0.5)
ax.legend()
return plotter
[docs]class PlotData:
""" Small wrapper around table data such as: sqlite or metadata
files. """
def __init__(self, fileName, tableName, orderColumn, orderDirection):
self._orderColumn = orderColumn
self._orderDirection = orderDirection
if fileName.endswith(".db") or fileName.endswith(".sqlite"):
self._table = self._loadSet(fileName, tableName)
self.getColumnValues = self._getValuesFromSet
self.getSize = self._table.getSize
else: # assume a metadata file
self._table = self._loadMd(fileName, tableName)
self.getColumnValues = self._getValuesFromMd
self.getSize = self._table.size
def _loadSet(self, dbName, dbPreffix):
from pyworkflow.mapper.sqlite import SqliteFlatDb
db = SqliteFlatDb(dbName=dbName, tablePrefix=dbPreffix)
if dbPreffix:
setClassName = "SetOf%ss" % db.getSelfClassName()
else:
setClassName = db.getProperty('self') # get the set class name
# FIXME: Check why the import is here
from pwem import Domain
setObj = Domain.getObjects()[setClassName](filename=dbName, prefix=dbPreffix)
return setObj
def _getValuesFromSet(self, columnName):
return [self._getValue(obj, columnName)
for obj in self._table.iterItems(orderBy=self._orderColumn,
direction=self._orderDirection)]
@staticmethod
def _removeInfinites(values):
newValues = []
for value in values:
if isinstance(value, numbers.Number) and value < float("Inf"):
newValues.append(value)
return newValues
def _loadMd(self, fileName, tableName):
label = md.str2Label(self._orderColumn)
tableMd = md.MetaData('%s@%s' % (tableName, fileName))
tableMd.sort(label) # FIXME: use order direction
# TODO: sort metadata by self._orderColumn
return tableMd
def _getValuesFromMd(self, columnName):
label = md.str2Label(columnName)
return [self._table.getValue(label, objId) for objId in self._table]
def _getValue(self, obj, column):
if column == 'id':
return obj.getObjId()
return obj.getNestedValue(column)