def decimate(input_files,output_file,bin_factor):
input_files = glob.glob(input_files)
print "processing %d files"%len(input_files)
img = ndimage_file.read_image(input_files[0])
nsize = img.shape[0]/2
for input_file in input_files:
print 'processing ', input_file
output_file = spider_utility.spider_filename(output_file, input_file)
for i, img in enumerate(ndimage_file.iter_images(input_file)):
img = ndimage_interpolate.downsample(img, bin_factor)
#img = ndimage_interpolate.interpolate_ft(img, (nsize,nsize))
ndimage_file.write_image(output_file, img, i)
'''
import sys
#sys.path.append('/home/robertl/tmp/arachnid-0.0.1/')
from arachnid.core.app import tracing
from arachnid.core.metadata import format
from arachnid.core.image import ndimage_file
from arachnid.core.image import reconstruct
import numpy,logging
if __name__ == "__main__":
image_file = sys.argv[1]
align_file = sys.argv[2]
output = sys.argv[3]
thread_count=16
tracing.configure_logging()
#Note: this code assuming you are reconstructing a dala stack or a translated stack
# Read an alignment file
align,header = format.read_alignment(align_file, ndarray=True)
logging.error("Reconstructing %d particles"%len(align))
assert(header[0]=='id')
index = align[:, 0].astype(numpy.int)
align[:, 1] = numpy.rad2deg(align[:, 1])
iter_single_images = ndimage_file.iter_images(image_file, index)
image_size = ndimage_file.read_image(image_file).shape[0]
vol = reconstruct.reconstruct_bp3f_mp(iter_single_images, image_size, align, thread_count=thread_count)
ndimage_file.write_image(output, vol)
.. literalinclude:: ../../arachnid/snippets/image/shift.py
:language: python
:lines: 17-
:linenos:
'''
import sys
from arachnid.core.metadata import format
from arachnid.core.metadata import spider_utility
from arachnid.core.metadata import relion_utility
from arachnid.core.image import ndimage_file
from arachnid.core.image import ndimage_utility
if __name__ == '__main__':
# Parameters
input_file = sys.argv[1]
output_file = sys.argv[2]
mult=1.0
# Read an alignment file
align = format.read(input_file, numeric=True)
for i in xrange(len(align)):
filename, id = relion_utility.relion_file(align[i].rlnImageName)
img = ndimage_file.read_image(filename, id-1)
img = ndimage_utility.fourier_shift(img, align[i].rlnOriginX, align[i].rlnOriginY)
ndimage_file.write_image(spider_utility.spider_filename(output_file, filename), img, id-1)
.. literalinclude:: ../../arachnid/snippets/image/rotate_translate_images.py
:language: python
:lines: 16-
:linenos:
'''
from arachnid.core.metadata import format
from arachnid.core.metadata import spider_utility
from arachnid.core.image import ndimage_file
from arachnid.core.image import rotate
import itertools
import sys
if __name__ == '__main__':
# Parameters
align_file = sys.argv[1]
image_file = sys.argv[2]
output_file = sys.argv[3]
# Read an alignment file
align, header = format.read_alignment(align_file, ndarray=True)
align[:, 16]-=1
iter_single_images = ndimage_file.iter_images(image_file, align[:, 15:17])
iter_single_images = itertools.imap(rotate.rotate_image, iter_single_images, align)
for i, img in enumerate(iter_single_images):
ndimage_file.write_image(spider_utility.spider_filename(output_file, int(align[i, 4])), img)
.. sourcecode:: sh
$ python unstack.py
.. note::
You must have Arachnid installed to run this script
.. literalinclude:: ../../arachnid/snippets/image/unstack.py
:language: python
:lines: 20-
:linenos:
'''
from arachnid.core.metadata import spider_utility
from arachnid.core.image import ndimage_file
if __name__ == '__main__':
# Parameters
input_stack = "stack_001.dat"
output_image = 'image_001_00000.dat'
# Script
for i, img in enumerate(ndimage_file.iter_images(input_stack)):
output_image = spider_utility.spider_filename(output_image, i+1)
ndimage_file.write_image(output_image, img)
if __name__ == "__main__":
tracing.configure_logging()
image_file = sys.argv[1] # phase_flip_dala_stack.spi
align_file = sys.argv[2] # align.spi
param_file = sys.argv[3]
output = sys.argv[4] # raw_vol.spi
bin_factor = float(
sys.argv[5]) if len(sys.argv) > 5 else 1.0 # raw_vol.spi
thread_count = 32
extra = spider_params.read(param_file)
extra.update(spider_params.update_params(bin_factor, **extra))
print "Loaded param file"
extra.update(thread_count=thread_count)
align, header = format.read_alignment(align_file, ndarray=True)
logging.error("Reconstructing %d particles" % len(align))
selection = align[:, 15:17]
align[:, 6:8] /= extra['apix']
iter_single_images = ndimage_file.iter_images(image_file, selection)
image_size = ndimage_file.read_image(image_file).shape[0]
vol = reconstruct.reconstruct_bp3f_mp(iter_single_images,
image_size,
align,
process_image=process_image,
**extra)
if vol is not None:
ndimage_file.write_image(output, vol)
extra = spider_params.read(param_file)
extra.update(spider_params.update_params(bin_factor, **extra))
print "Loaded param file"
extra.update(thread_count=thread_count)
align, header = format.read_alignment(align_file, ndarray=True)
logging.error("Reconstructing %d particles" % len(align))
if align.shape[1] > 17:
selection = align[:, 15:17]
selection[:, 1] -= 1
#align[:, 6:8] /= extra['apix']
else:
selection = align[:, 4].astype(numpy.int) - 1
image_size = ndimage_file.read_image(image_file).shape[0]
even = numpy.arange(0, len(selection), 2, dtype=numpy.int)
odd = numpy.arange(1, len(selection), 2, dtype=numpy.int)
iter_single_images1 = ndimage_file.iter_images(image_file, selection[even])
iter_single_images2 = ndimage_file.iter_images(image_file, selection[odd])
align1 = align[even]
align2 = align[odd]
vol = reconstruct.reconstruct3_bp3f_mp(image_size, iter_single_images1,
iter_single_images2, align1, align2,
**extra)
if vol is not None:
ndimage_file.write_image(output, vol[0])
ndimage_file.write_image(format_utility.add_prefix(output, 'h1_'),
vol[1])
ndimage_file.write_image(format_utility.add_prefix(output, 'h2_'),
vol[2])
import glob
if __name__ == '__main__':
# Parameters
input_files = sys.argv[1]
output_file = sys.argv[2]
params_file = sys.argv[3]
bin_factor = int(sys.argv[4])
input_files = glob.glob(input_files)
print "processing %d files"%len(input_files)
radius = spider_params.read(params_file)['pixel_diameter']/2
img = ndimage_file.read_image(input_files[0])
mask = ndimage_utility.model_disk(radius, img.shape)*-1+1
mask = ndimage_interpolate.downsample(mask, bin_factor)
for input_file in input_files:
print 'processing ', input_file
output_file = spider_utility.spider_filename(output_file, input_file)
for i, img in enumerate(ndimage_file.iter_images(input_file)):
img = ndimage_interpolate.downsample(img, bin_factor)
img=ndimage_utility.normalize_standard(img, mask)
ndimage_file.write_image(output_file, img, i)
def bin(align_param_file, ref_ang_file, pref_image_in, pref_image_out, pref_sel, pref_sel_all,thres):
# read in the alignment parameters and the reference angles
# 1st column is psi, 2nd is theta, and 3rd is phi
align = spider.parse(align_param_file)
#align,header = format.read_alignment(align_param_file, ndarray=True)
print("Reconstructing %d particles"%len(align))
#assert(header[0]=='id')
# read in reference angles
refang = spider.parse(ref_ang_file)
index = align[:, 0].astype(np.int)
#refang, header = format.read_alignment(ref_ang_file, ndarray=True)
#assert(header[0]=='id')
# from degree to radian from column 1
align[:,1:4] = np.deg2rad(align[:,1:4])
refang[:,1:4] = np.deg2rad(refang[:,1:4])
# read in pref of images
iter_single_images = ndimage_file.iter_images(pref_image_in, index)
# form unit directional vectors
rphi = mcol(refang[:,3])
rtheta = mcol(refang[:,2])
unit_v = get_unitv(rphi,rtheta)
# 2-array to track indeces of particles in the same angle bin
# Max number of particles in the same angle bin
MAX = 5000
index = np.zeros((refang.shape[0],MAX))
# array to track the number of particles in each bin
quant = np.zeros((refang.shape[0]))
# binning: loop through particles
for i, img in enumerate(iter_single_images):
# direction of one particle
phi = align[i,3]
theta = align[i,2]
uv = get_unitv(phi,theta)
# read in image
#print i
#img = ndimage_file.read_image(img)
if theta > math.pi:
img = get_mirror(img)
ndimage_file.write_image(pref_image_out, img, i)
# multiply with all ref ang and store the largest
ip = np.dot(unit_v,uv.T)
# store the largest in the right bin
bin = ip.argmax()
index[bin,quant[bin]] = align[i,0]
quant[bin] += 1
#print index
# adjust the psi angle
rpsi = refang[bin,1]
rtheta = refang[bin,2]
rphi = refang[bin,3]
psi = adjust_psi(rpsi,rtheta,rphi,theta,phi)
align[i,1] = psi
# loop through the bins and keep only those with more than 'thres' particles
S = [] # will hold the selected bin numbers
count = 0
for j in range(refang.shape[0]):
sz = len(np.nonzero(index[j,:])[0])
if sz > thres:
table = index[j,0:sz]
#print table
filename = pref_sel + '{:05d}'.format(j)
spider.write(filename,table)
S.append(j)
#print S
spider.write(pref_sel_all,S)
.. literalinclude:: ../../arachnid/snippets/image/rotate_translate_images.py
:language: python
:lines: 16-
:linenos:
'''
from arachnid.core.metadata import format
from arachnid.core.metadata import spider_utility
from arachnid.core.image import ndimage_file
from arachnid.core.image import rotate
import itertools
import sys
if __name__ == '__main__':
# Parameters
align_file = sys.argv[1]
image_file = sys.argv[2]
output_file = sys.argv[3]
# Read an alignment file
align, header = format.read_alignment(align_file, ndarray=True)
align[:, 16] -= 1
iter_single_images = ndimage_file.iter_images(image_file, align[:, 15:17])
iter_single_images = itertools.imap(rotate.rotate_image,
iter_single_images, align)
for i, img in enumerate(iter_single_images):
ndimage_file.write_image(
spider_utility.spider_filename(output_file, int(align[i, 4])), img)
To run:
.. sourcecode:: sh
$ python unstack.py
.. note::
You must have Arachnid installed to run this script
.. literalinclude:: ../../arachnid/snippets/image/unstack.py
:language: python
:lines: 20-
:linenos:
'''
from arachnid.core.metadata import spider_utility
from arachnid.core.image import ndimage_file
if __name__ == '__main__':
# Parameters
input_stack = "stack_001.dat"
output_image = 'image_001_00000.dat'
# Script
for i, img in enumerate(ndimage_file.iter_images(input_stack)):
output_image = spider_utility.spider_filename(output_image, i + 1)
ndimage_file.write_image(output_image, img)