#import astigmaticPSF as PSF
import dhPSF as PSF
if (len(sys.argv) != 5):
print "usage: <dax> <bin> <frames> <num_objects>"
exit()
# Peak height.
intensity = 500.0
# Image size.
x_size = 256
y_size = 256
dax_data = daxwriter.DaxWriter(sys.argv[1], x_size, y_size)
i3_data = writeinsight3.I3Writer(sys.argv[2])
num_frames = int(sys.argv[3])
num_objects = int(sys.argv[4])
for i in range(num_frames):
print "Generating frame:", i
# Generate locations
x_vals = numpy.zeros(num_objects)
y_vals = numpy.zeros(num_objects)
z_vals = numpy.zeros(num_objects)
h_vals = numpy.ones(num_objects) * intensity
for j in range(num_objects):
# Random locations.
def peakFinding(find_peaks, movie_file, mlist_file, parameters):
# open files for input & output
movie_data = datareader.inferReader(movie_file)
[movie_x, movie_y, movie_l] = movie_data.filmSize()
# if the i3 file already exists, read it in,
# write it out & start the analysis from the
# end.
total_peaks = 0
if (os.path.exists(mlist_file)):
print "Found", mlist_file
i3data_in = readinsight3.loadI3File(mlist_file)
try:
curf = int(numpy.max(i3data_in['fr']))
except ValueError:
curf = 0
print " Starting analysis at frame:", curf
i3data = writeinsight3.I3Writer(mlist_file)
if (curf > 0):
i3data.addMolecules(i3data_in)
total_peaks = i3data_in['x'].size
else:
curf = 0
i3data = writeinsight3.I3Writer(mlist_file)
# process parameters
if hasattr(parameters, "start_frame"):
if (parameters.start_frame >= curf) and (parameters.start_frame <
movie_l):
curf = parameters.start_frame
if hasattr(parameters, "max_frame"):
if (parameters.max_frame > 0) and (parameters.max_frame < movie_l):
movie_l = parameters.max_frame
# analyze the movie
# catch keyboard interrupts & "gracefully" exit.
try:
while (curf < movie_l):
#for j in range(l):
# Set up the analysis.
image = movie_data.loadAFrame(curf) - parameters.baseline
mask = (image < 1.0)
if (numpy.sum(mask) > 0):
print " Removing negative values in frame", curf
image[mask] = 1.0
# Find and fit the peaks.
[peaks, residual] = find_peaks.analyzeImage(image)
# Save the peaks.
if (type(peaks) == type(numpy.array([]))):
# remove unconverged peaks
peaks = find_peaks.getConvergedPeaks(peaks)
# save results
if (parameters.orientation == "inverted"):
i3data.addMultiFitMolecules(peaks,
movie_x,
movie_y,
curf + 1,
parameters.pixel_size,
inverted=True)
else:
i3data.addMultiFitMolecules(peaks,
movie_x,
movie_y,
curf + 1,
parameters.pixel_size,
inverted=False)
total_peaks += peaks.shape[0]
print "Frame:", curf, peaks.shape[0], total_peaks
else:
print "Frame:", curf, 0, total_peaks
curf += 1
print ""
i3data.close()
find_peaks.cleanUp()
return 0
except KeyboardInterrupt:
print "Analysis stopped."
i3data.close()
find_peaks.cleanUp()
return 1
# Save results.
fx = fdecon.getXVector()
print numpy.min(fx), numpy.max(fx)
decon_data = daxwriter.DaxWriter(sys.argv[3], fx.shape[0], fx.shape[1])
for i in range(fx.shape[2]):
decon_data.addFrame(fx[:, :, i])
decon_data.close()
# Find peaks in the decon data.
peaks = fdecon.getPeaks(parameters.fista_threshold, 5)
zci = utilC.getZCenterIndex()
z_min, z_max = fdecon.getZRange()
peaks[:, zci] = 1.0e-3 * ((z_max - z_min) * peaks[:, zci] + z_min)
i3_writer = writeinsight3.I3Writer(sys.argv[3][:-4] + "_flist.bin")
i3_writer.addMultiFitMolecules(peaks, x_size, y_size, 1,
parameters.pixel_size)
i3_writer.close()
#
# The MIT License
#
# Copyright (c) 2016 Zhuang Lab, Harvard University
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# Create a test .bin file for evaluating RCC correction.
#
# Hazen 10/14
#
import numpy
import sys
import sa_library.writeinsight3 as writeinsight3
if (len(sys.argv) != 2):
print "usage: <out.bin>"
exit()
i3_out = writeinsight3.I3Writer(sys.argv[1])
n_locs = 100
def addMol(x,y,frame):
x += numpy.random.normal(scale = 0.05, size = n_locs)
y += numpy.random.normal(scale = 0.05, size = n_locs)
i3_out.addMoleculesWithXYFrame(x,y,i)
x1 = 255.0 * numpy.random.uniform(size = n_locs)
y1 = 255.0 * numpy.random.uniform(size = n_locs)
x2 = 255.0 * numpy.random.uniform(size = n_locs)
y2 = 255.0 * numpy.random.uniform(size = n_locs)
dx = 0.0
dy = 0.0
# Setup
#
src_directory = os.path.dirname(__file__)
if (len(sys.argv) != 5):
print "usage: cs_analysis <dax_file> <params_file> <hres_file> <bin_file>"
exit()
movie_data = datareader.inferReader(sys.argv[1])
#
# FIXME:
#
# This should also start at the same frame as hres in the event of a restart.
#
i3_file = writeinsight3.I3Writer(sys.argv[4])
params = parameters.Parameters(sys.argv[2])
#
# Load the a matrix and setup the homotopy image analysis class.
#
a_mat_file = params.a_matrix
print "Using A matrix file:", a_mat_file
a_mat = setup_A_matrix.loadAMatrix(a_mat_file)
image = movie_data.loadAFrame(0)
htia = homotopy_imagea_c.HomotopyIA(a_mat, params.epsilon, image.shape)
#