def test():
"""Test voxelization module"""
import ClearMap.Analysis.Voxelization as self
reload(self)
import ClearMap.Analysis.VoxelizationCode as vox
import numpy
points = numpy.random.rand(200,3) * 10;
#use cython code
vi = vox.voxelizeSphere(points, 20,20,20, 5,5,5);
import ClearMap.Visualization.Plot as Plot
Plot.plotTiling(vi)
#use voxelize
vi = self.voxelize(points, dataSize = (20,20,20), size = (5,5,5));
Plot.plotTiling(vi)
#weighted voxelization
points = numpy.random.rand(10,3) * 10;
weights = numpy.random.rand(10);
#use voxelize
vi = self.voxelize(points, dataSize = (20,20,20), size = (5,5,5));
viw = self.voxelize(points, dataSize = (20,20,20), size = (5,5,5), weights = weights);
Plot.plotTiling(vi)
Plot.plotTiling(viw)
def plotImportPreview(importResult):
"""Plots the prestiched preview file to check orientations and coarse alignment
Arguments:
importResult (str): the base directory of the image data or the import xml file
Returns:
object: plot axes
"""
return cplt.plotTiling(readImportPreview(importResult))
def plotImportPreview(importResult):
"""Plots the prestiched preview file to check orientations and coarse alignment
Arguments:
importResult (str): the base directory of the image data or the import xml file
Returns:
object: plot axes
"""
return cplt.plotTiling(readImportPreview(importResult));
def test():
"""Test the statistics array"""
import ClearMap.Analysis.Statistics as self
reload(self)
import numpy, os
import matplotlib.pyplot as plt
#x = stats.norm.rvs(loc=5,scale=1,size=1500)
#y = stats.norm.rvs(loc=-5,scale=1,size=1500)
s = numpy.ones((5, 4, 20))
s[:, 0:3, :] = -1
x = numpy.random.rand(4, 4, 20)
y = numpy.random.rand(5, 4, 20) + s
# print stats.ttest_ind(x,y, axis = 0, equal_var = False);
pvals, psign = self.tTestVoxelization(x, y, signed=True)
print pvals
pvalscol = self.colorPValues(pvals,
psign,
positive=[255, 0, 0],
negative=[0, 255, 0])
import ClearMap.Visualization.Plot as plt_cm
plot = plt_cm.plotTiling(pvalscol)
plt.show()
# test points
basedir = '/home/vzickus/repos/ClearMap-Debug/ClearMap'
import ClearMap.Settings as settings
pf = os.path.join(basedir,
'Test/Synthetic/cells_transformed_to_reference.csv')
pf = numpy.loadtxt(pf, delimiter=',')
pg = (pf, pf)
pc = self.countPointsGroupInRegions(pg)
pvals, tvals = self.tTestPointsInRegions(pg, pg, signed=True)
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath,
'Test/Data/ImageAnalysis/cfos-substack.tif')
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z=(0, 26))
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.removeBackground(data.astype('float'), size=(3, 3), verbose=True)
from ClearMap.ImageProcessing.Filter.DoGFilter import filterDoG
dataDoG = filterDoG(dataBGR, size=(8, 8, 4), verbose=True)
from ClearMap.ImageProcessing.MaximaDetection import findExtendedMaxima
dataMax = findExtendedMaxima(dataDoG, hMax=None, verbose=True, threshold=10)
from ClearMap.ImageProcessing.MaximaDetection import findCenterOfMaxima
cells = findCenterOfMaxima(data, dataMax)
plt.plotOverlayPoints(data, cells, z=(10, 16))
import ClearMap.IO.IO as io
import os
import ClearMap.Visualization.Plot as plt
import ClearMap.Analysis.Label as lbl
import numpy as np
sampleName = 'LowNIC'
#execfile('/d2/studies/ClearMap/IA_iDISCO/' + sampleName + '/parameter_file_' + sampleName + '.py')
execfile(
'/d2/studies/ClearMap/Alex_Acute_iDISCO/3RB_HighNIC/parameter_file_template_3RB.py'
)
baseDirectory = '/d2/studies/ClearMap/Alex_Acute_iDISCO/NIC_HeatMaps/FiguresForPaper/'
region = 'MSC'
points = io.readPoints(TransformedCellsFile)
data = plt.overlayPoints(AnnotationFile, points.astype(int), pointColor=None)
io.writeData(
os.path.join(BaseDirectory,
sampleName + '_Annotations_Points_Overlay_newAtlas2.tif'),
data)
data = data[:, :, :, 1:]
io.writeData(
os.path.join(BaseDirectory,
sampleName + '_Points_Transformed_newAtlas2.tif'), data)
label = io.readData(AnnotationFile)
label = label.astype('int32')
labelids = np.unique(label)
outside = np.zeros(label.shape, dtype=bool)
"""
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath,
'Test/Data/ImageAnalysis/cfos-substack.tif')
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z=(0, 26))
plt.plotTiling(data, x=(0, 70), y=(0, 50), z=(10, 16))
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath, "Test/Data/ImageAnalysis/cfos-substack.tif")
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z=(0, 26))
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.removeBackground(data.astype("float"), size=(3, 3), verbose=True)
from ClearMap.ImageProcessing.Filter.DoGFilter import filterDoG
dataDoG = filterDoG(dataBGR, size=(8, 8, 4), verbose=True)
from ClearMap.ImageProcessing.MaximaDetection import findExtendedMaxima
dataMax = findExtendedMaxima(dataDoG, hMax=None, verbose=True, threshold=10)
from ClearMap.ImageProcessing.MaximaDetection import findCenterOfMaxima
cells = findCenterOfMaxima(data, dataMax)
plt.plotOverlayPoints(data, cells, z=(10, 16))
io.writeData(os.path.join(resultDir, fName + '_CellShapes.tif'),
255 * dataShape.astype('int32') / dataShape.max())
#cintensity = findIntensity(imgD, points);
#points, intensities = thresholdPoints(points,cintensity, threshold = (5,20), row = (1,1));
points, cellSizesPost = thresholdPoints(points,
cellSizesPre,
threshold=pointsThresh,
row=threshType)
#pdb.set_trace()
#io.writeData(os.path.join(homeDir, 'Results/OverlayWatershed.tif'), overlay_Img);
overlay_Img = plt.fredOverlayPoints(cfos_fn,
points,
pointColor=[200, 0, 0])
io.writeData(os.path.join(resultDir, fName + '_PointsOriginalImg.tif'),
overlay_Img)
overlay_Img = plt.overlayPoints(imgD, points, pointColor=[200, 0, 0])
io.writeData(os.path.join(resultDir, fName + '_PointsFilterDoG.tif'),
overlay_Img)
#Convert points from 3d to 2d
points = numpy.delete(points, 2, axis=1)
io.writePoints(points_fn, points)
##############################################################333
imgR = io.readData(auto_fn)
# -*- coding: utf-8 -*-
"""
Created on Sat Dec 19 04:29:29 2015
@author: ckirst
"""
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath,
'Test/Data/ImageAnalysis/cfos-substack.tif')
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z=(0, 30))
plt.plotTiling(data, inverse=True, z=(10, 16))
#import ClearMap.ImageProcessing.ImageStatistics as stat
#stat.calculateStatistics(filename, method = 'mean', verbose = True)
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.removeBackground(data.astype('float'),
size=(10, 10),
verbose=True)
plt.plotTiling(dataBGR, inverse=True, z=(10, 16))
from ClearMap.ImageProcessing.Filter.DoGFilter import filterDoG
dataDoG = filterDoG(dataBGR, size=(8, 8, 4), verbose=True)
plt.plotTiling(dataDoG, inverse=True, z=(10, 16))
import os
#row = (0,0) : peak intensity from the raw data
#row = (1,1) : peak intensity from the DoG filtered data
#row = (2,2) : peak intensity from the background subtracted data
#row = (3,3) : voxel size from the watershed
points, intensities = thresholdPoints(points,
intensities,
threshold=3000,
row=(0, 0))
io.writePoints(FilteredCellsFile, (points, intensities))
## Check Cell detection (For the testing phase only, remove when running on the full size dataset)
#######################
import ClearMap.Visualization.Plot as plt
pointSource = os.path.join(BaseDirectory, FilteredCellsFile[0])
data = plt.overlayPoints(cFosFile,
pointSource,
pointColor=None,
**cFosFileRange)
io.writeData(os.path.join(BaseDirectory, 'cells_check.tif'), data)
# Transform point coordinates
#############################
points = io.readPoints(CorrectionResamplingPointsParameter["pointSource"])
points = resamplePoints(**CorrectionResamplingPointsParameter)
points = transformPoints(
points,
transformDirectory=CorrectionAlignmentParameter["resultDirectory"],
indices=False,
resultDirectory=None)
CorrectionResamplingPointsInverseParameter["pointSource"] = points
points = resamplePointsInverse(**CorrectionResamplingPointsInverseParameter)
RegistrationResamplingPointParameter["pointSource"] = points
cellSizesPre = findCellSize(dataShape, maxlabel=points.shape[0])
io.writeData(os.path.join(homeDir, 'Results/CellShapes.tif'),
20 * dataShape.astype('int32'))
#cintensity = findIntensity(imgD, points);
#points, intensities = thresholdPoints(points,cintensity, threshold = (5,20), row = (1,1));
points, cellSizesPost = thresholdPoints(points,
cellSizesPre,
threshold=(5, 100),
row=(3, 3))
#pdb.set_trace()
#io.writeData(os.path.join(homeDir, 'Results/OverlayWatershed.tif'), overlay_Img);
overlay_Img = plt.fredOverlayPoints(input_fn, points, pointColor=[200, 0, 0])
io.writeData(os.path.join(homeDir, 'Results/PointsOriginalImg.tif'),
overlay_Img)
overlay_Img = plt.fredOverlayPoints(os.path.join(homeDir,
'Results/FilterDoG.tif'),
points,
pointColor=[200, 0, 0])
io.writeData(os.path.join(homeDir, 'Results/PointsFilterDoG.tif'), overlay_Img)
#################################################################################################
#Convert points from 3d to 2d
points = numpy.delete(points, 2, axis=1)
io.writePoints(points_fn, points)
#Resampled Img
imgR = io.readData(auto_fn)
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath,
'Test/Data/ImageAnalysis/cfos-substack.tif')
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z=(0, 26))
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.removeBackground(data.astype('float'),
size=(10, 10),
verbose=True)
from ClearMap.ImageProcessing.Filter.DoGFilter import filterDoG
dataDoG = filterDoG(dataBGR, size=(8, 8, 4), verbose=True)
plt.plotTiling(dataDoG, inverse=True, z=(10, 16))
# -*- coding: utf-8 -*-
"""
Created on Sat Dec 19 04:29:29 2015
@author: ckirst
"""
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath, 'Test/Data/ImageAnalysis/cfos-substack.tif');
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z = (0,30));
plt.plotTiling(data, inverse = True, z = (10,16));
#import ClearMap.ImageProcessing.ImageStatistics as stat
#stat.calculateStatistics(filename, method = 'mean', verbose = True)
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.removeBackground(data.astype('float'), size=(10,10), verbose = True);
plt.plotTiling(dataBGR, inverse = True, z = (10,16));
from ClearMap.ImageProcessing.Filter.DoGFilter import filterDoG
dataDoG = filterDoG(dataBGR, size=(8,8,4), verbose = True);
plt.plotTiling(dataDoG, inverse = True, z = (10,16));
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath,
'Test/Data/ImageAnalysis/cfos-substack.tif')
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z=(0, 26))
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.removeBackground(data.astype('float'), size=(3, 3), verbose=True)
from ClearMap.ImageProcessing.Filter.DoGFilter import filterDoG
dataDoG = filterDoG(dataBGR, size=(8, 8, 4), verbose=True)
from ClearMap.ImageProcessing.MaximaDetection import findExtendedMaxima
dataMax = findExtendedMaxima(dataDoG, hMax=None, verbose=True, threshold=10)
from ClearMap.ImageProcessing.MaximaDetection import findCenterOfMaxima
cells = findCenterOfMaxima(data, dataMax)
from ClearMap.ImageProcessing.CellSizeDetection import detectCellShape
dataShape = detectCellShape(dataDoG, cells, threshold=15)
plt.plotOverlayLabel(dataDoG / dataDoG.max(), dataShape, z=(10, 16))
import os import ClearMap.Settings as settings filename = os.path.join(settings.ClearMapPath, 'Test/Data/ImageAnalysis/cfos-substack.tif'); import ClearMap.Visualization.Plot as plt import ClearMap.IO as io data = io.readData(filename, z = (0,26)); plt.plotTiling(data, x= (0,70), y = (0,50), z = (10,16));
import ClearMap.Settings as settings
import ClearMap.Visualization.Plot as plt
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
import matplotlib as mplt
BaseDirectory = '/d2/studies/ClearMap/IA_iDISCO/IA1_RB/'
filename = os.path.join(BaseDirectory, 'IA1_RB_cfos_stack.ome.tif')
data = io.readData(filename, z=(600, 650))
# size restriction
fileRange = 'x = (1050, 1350), y = (550,850), z = (25,34)'
""" note that the Z coordinate in fileRange variable are relative to the planes imported in the data variable.
So in this case, you would be imaging planes 675-684.
"""
plt.plotTiling(data, inverse=True, x=(1250, 1350), y=(550, 650), z=(25, 34)) #
# background subtraction
dataBGR = bgr.removeBackground(data.astype('float'),
size=(5, 5),
verbose=False,
save=None)
dataBGR_write = plt.plotTiling(dataBGR,
inverse=True,
x=(1250, 1350),
y=(550, 650),
z=(25, 34))
dataBGR_write = plt.overlayPoints(dataBGR, fileRange)
mplt.pyplot.savefig(os.path.join(BaseDirectory, 'dataBGR_write.tif'))
io.writeData(os.path.join(BaseDirectory, 'background_8.tif'), dataBGR_write)
io.writeData(os.path.join(BaseDirectory, 'cells_check.tif'), data)
import os import ClearMap.Settings as settings filename = os.path.join(settings.ClearMapPath, 'Test/Data/ImageAnalysis/cfos-substack.tif'); import ClearMap.Visualization.Plot as plt import ClearMap.IO as io data = io.readData(filename, z = (0,26)); plt.plotTiling(data);
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath, 'Test/Data/ImageAnalysis/cfos-substack.tif');
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z = (0,26));
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.removeBackground(data.astype('float'), size=(3,3), verbose = True);
from ClearMap.ImageProcessing.Filter.DoGFilter import filterDoG
dataDoG = filterDoG(dataBGR, size=(8,8,4), verbose = True);
from ClearMap.ImageProcessing.MaximaDetection import findExtendedMaxima
dataMax = findExtendedMaxima(dataDoG, hMax = None, verbose = True, threshold = 10);
from ClearMap.ImageProcessing.MaximaDetection import findCenterOfMaxima
cells = findCenterOfMaxima(data, dataMax);
from ClearMap.ImageProcessing.CellSizeDetection import detectCellShape
dataShape = detectCellShape(dataDoG, cells, threshold = 15);
plt.plotOverlayLabel(dataDoG / dataDoG.max(), dataShape, z = (10,16))
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath, 'Test/Data/ImageAnalysis/cfos-substack.tif');
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z = (0,26));
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.removeBackground(data.astype('float'), size=(3,3), verbose = True);
from ClearMap.ImageProcessing.Filter.DoGFilter import filterDoG
dataDoG = filterDoG(dataBGR, size=(8,8,4), verbose = True);
from ClearMap.ImageProcessing.MaximaDetection import findExtendedMaxima
dataMax = findExtendedMaxima(dataDoG, hMax = None, verbose = True, threshold = 10);
plt.plotOverlayLabel(dataDoG / dataDoG.max(), dataMax.astype('int'), z = (10,16), x = (50,100), y = (50,100))
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath, 'Test/Data/ImageAnalysis/cfos-substack.tif');
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z = (0,26));
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.removeBackground(data.astype('float'), size=(3,3), verbose = True);
plt.plotTiling(dataBGR, inverse = True, z = (10,16));
import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath,
'Test/Data/ImageAnalysis/cfos-substack.tif')
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z=(0, 26))
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.removeBackground(data.astype('float'), size=(3, 3), verbose=True)
from ClearMap.ImageProcessing.Filter.DoGFilter import filterDoG
dataDoG = filterDoG(dataBGR, size=(8, 8, 4), verbose=True)
from ClearMap.ImageProcessing.MaximaDetection import findExtendedMaxima
dataMax = findExtendedMaxima(dataDoG, hMax=None, verbose=True, threshold=10)
plt.plotOverlayLabel(dataDoG / dataDoG.max(),
dataMax.astype('int'),
z=(10, 16))
