def calculate_animation(self, dt):
'''
based on the assumption that dt goes from 0 to 1
'''
if dt > 1: raise
if self.angle != 0:
t1 = dt * self.angle
t2 = self.angle - t1
next = old_div(
(sin(t2) * self.start_point + sin(t1) * self.end_point),
self.sinangle)
else:
T = Transform()
d = {"type": "spin"}
d["omega"] = dt * 360
d["n1"] = self.rot_vec[0]
d["n2"] = self.rot_vec[1]
d["n3"] = self.rot_vec[2]
T.set_rotation(d)
next = T * self.start_point
#next = Vec3f(self.start_point[0],self.start_point[1],self.start_point[2])
self.arc_points[self.stage].append(self.radius * next)
self.target.arc_animation_update(self.arc_points)
def calculate_animation(self, dt):
"""
based on the assumption that dt goes from 0 to 1
"""
if dt > 1:
raise
if self.angle != 0:
t1 = dt * self.angle
t2 = self.angle - t1
next = (sin(t2) * self.start_point + sin(t1) * self.end_point) / self.sinangle
else:
T = Transform()
d = {"type": "spin"}
d["omega"] = dt * 360
d["n1"] = self.rot_vec[0]
d["n2"] = self.rot_vec[1]
d["n3"] = self.rot_vec[2]
T.set_rotation(d)
next = T * self.start_point
# next = Vec3f(self.start_point[0],self.start_point[1],self.start_point[2])
self.arc_points[self.stage].append(self.radius * next)
self.target.arc_animation_update(self.arc_points)
def __establish_sphere_points(self, stage):
self.start_point = self.transforms[stage].transpose() * self.z_point
self.end_point = self.transforms[stage + 1].transpose() * self.z_point
if self.start_point != self.end_point:
self.angle = acos(self.start_point.dot(self.end_point))
self.omega = 1
else:
self.angle = 0
normal = Vec3f(-self.start_point[2], 0, -self.start_point[0])
normal.normalize()
T = Transform()
d = {"type": "spin"}
d["omega"] = self.omega
d["n1"] = normal[0]
d["n2"] = normal[1]
d["n3"] = normal[2]
T.set_rotation(d)
self.rot_vec = self.start_point
p = self.start_point
self.start_point = T * self.rot_vec
self.end_point = T * self.rot_vec
self.omega += 1
self.sinangle = sin(self.angle)
self.arc_points.append([])
def mult_transform(v1, v2):
from EMAN2 import Transform
T1 = Transform({
"type": "spider",
"phi": v1[0],
"theta": v1[1],
"psi": v1[2],
"tx": 0.0,
"ty": 0.0,
"tz": 0.0,
"mirror": 0,
"scale": 1.0
})
T2 = Transform({
"type": "spider",
"phi": v2[0],
"theta": v2[1],
"psi": v2[2],
"tx": 0.0,
"ty": 0.0,
"tz": 0.0,
"mirror": 0,
"scale": 1.0
})
T = T1 * T2
return [
T.get_params("spider")["phi"],
T.get_params("spider")["theta"],
T.get_params("spider")["psi"]
]
def __establish_sphere_points(self, stage):
self.start_point = self.transforms[stage].transpose() * self.z_point
self.end_point = self.transforms[stage + 1].transpose() * self.z_point
if self.start_point != self.end_point:
self.angle = acos(self.start_point.dot(self.end_point))
self.omega = 1
else:
self.angle = 0
normal = Vec3f(-self.start_point[2], 0, -self.start_point[0])
normal.normalize()
T = Transform()
d = {"type": "spin"}
d["omega"] = self.omega
d["n1"] = normal[0]
d["n2"] = normal[1]
d["n3"] = normal[2]
T.set_rotation(d)
self.rot_vec = self.start_point
p = self.start_point
self.start_point = T * self.rot_vec
self.end_point = T * self.rot_vec
self.omega += 1
self.sinangle = sin(self.angle)
self.arc_points.append([])
def apply_rotation_gaps(angleset1, qrot):
from EMAN2 import Transform, Vec2f
import types
if (type(qrot) == list):
rot = Transform({
"type": "spider",
"phi": qrot[0],
"theta": qrot[1],
"psi": qrot[2]
})
else:
rot = qrot
for i in range(len(angleset1)):
if (len(angleset1[i]) > 1):
T1 = Transform({
"type": "spider",
"phi": angleset1[i][0],
"theta": angleset1[i][1],
"psi": angleset1[i][2],
"tx": 0.0,
"ty": 0.0,
"tz": 0.0,
"mirror": 0,
"scale": 1.0
})
T1.set_trans(Vec2f(-angleset1[i][3], -angleset1[i][4]))
T = T1 * rot
d = T.get_params("spider")
angleset1[i] = [d["phi"], d["theta"], d["psi"], -d["tx"], -d["ty"]]
def apply_rotation_gaps(angleset1, qrot):
from EMAN2 import Transform, Vec2f
import types
if(type(qrot) == types.ListType): rot = Transform({"type":"spider","phi":qrot[0],"theta":qrot[1],"psi":qrot[2]})
else: rot = qrot
for i in xrange(len(angleset1)):
if(len(angleset1[i]) > 1):
T1 = Transform({"type":"spider","phi":angleset1[i][0],"theta":angleset1[i][1],"psi":angleset1[i][2],"tx":0.0,"ty":0.0,"tz":0.0,"mirror":0,"scale":1.0})
T1.set_trans(Vec2f(-angleset1[i][3], -angleset1[i][4]))
T = T1*rot
d = T.get_params("spider")
angleset1[i] = [d["phi"], d["theta"], d["psi"], -d["tx"], -d["ty"]]
def subtract(particle,
dens,
sub_dens,
recenter=None,
no_frc=False,
low_cutoff=0.0,
high_cutoff=0.7071):
"""
Perform projection subtraction on one particle image.
:param particle: Tuple holding original (particle EMData, particle MetaData)
:param dens: Whole density map
:param sub_dens: Subtraction density map
:param recenter: Vector between CoM before and after subtraction, or None to skip recenter operation (default None)
:param no_frc: Skip FRC normalization (default False)
:param low_cutoff: Low cutoff frequency in FRC normalization (default 0.0)
:param high_cutoff: High cutoff frequency in FRC normalization (default 0.7071)
:return: Result object
"""
ptcl, meta = particle[0], particle[1]
ctfproj = make_proj(dens, meta)
ctfproj_sub = make_proj(sub_dens, meta)
if no_frc: # Direct subtraction only.
ptcl_sub = ptcl - ctfproj_sub
else: # Per-particle FRC normalization.
ptcl_sub = ptcl.process(
"math.sub.optimal", {
"ref": ctfproj,
"actual": ctfproj_sub,
"low_cutoff_frequency": low_cutoff,
"high_cutoff_frequency": high_cutoff
})
ptcl_norm_sub = ptcl_sub.process("normalize")
if recenter is not None:
# Rotate the coordinate frame of the CoM difference vector by the Euler angles.
t = Transform()
t.set_rotation({
'psi': meta.psi,
'phi': meta.phi,
'theta': meta.theta,
'type': 'spider'
})
shift = t.transform(recenter)
# The change in the origin is the projection of the transformed difference vector on the new xy plane.
meta.x_origin += shift[0]
meta.y_origin += shift[1]
return Result(ptcl, meta, ctfproj, ctfproj_sub, ptcl_sub, ptcl_norm_sub)
def average2dtransform(data, return_avg_pixel_error=False):
from math import pi, sin, cos, radians, degrees
L = len(data)
sum_cosa = 0.0
sum_sina = 0.0
sx = 0.0
sy = 0.0
for j in xrange(L):
sum_cosa += cos(radians(data[j][0]))
sum_sina += sin(radians(data[j][0]))
sx += data[j][1]
sy += data[j][2]
sx /= L
sy /= L
sqrtP = sqrt(sum_cosa**2+sum_sina**2)
# Get ave transform params
H = Transform({"type":"2D"})
H.set_matrix([sum_cosa/sqrtP, sum_sina/sqrtP, 0.0, sx, -sum_sina/sqrtP, sum_cosa/sqrtP, 0.0, sy, 0.0, 0.0, 1.0, 0.0])
dd = H.get_params("2D")
H = Transform({"type":"2D","alpha":dd[ "alpha" ],"tx":dd[ "tx" ],"ty": dd[ "ty" ],"mirror":0,"scale":1.0})
dd = H.get_params("2D")
if return_avg_pixel_error:
return sum(sqr_pixel_error)/N
else:
return [dd[ "alpha" ], dd[ "tx" ], dd[ "ty" ]]
def updateMatrices(self, params, xformtype):
"""
The matrcies are updated in such a way that each is done in the standard cooridnate system and the std coord system is not perturbed by the others
@type params: List
@param params: A list defining how the transform in each active node is modified
@type xfromtype: sting
@param xformtype: The sort of transform we wish to do
"""
if self.is_selected:
if xformtype == "rotate":
if self.parent:
self.transform.rotate_origin_newbasis(self.getParentMatrixProduct(), params[0], params[1], params[2], params[3])
else:
self.transform.rotate_origin(Transform({"type":"spin","omega":params[0],"n1":params[1],"n2":params[2],"n3":params[3]}))
elif xformtype == "translate":
if self.parent:
self.transform.translate_newbasis(self.getParentMatrixProduct(), params[0], params[1], params[2])
else:
self.transform.translate(params[0], params[1], params[2])
elif xformtype == "scale":
self.transform.scale(params[0])
else:
raise Exception,"Invalid transformation type"
# Now tell all children to update
# TODO: we MIGHT want to get rid of the recursive part of this algorithm
# instead, the calling function would get a list of all selected nodes, and apply transformations to each
for child in self.children:
child.updateMatrices(params, xformtype) #Note: the transformation is only applied to SELECTED nodes
def _on_EMAN_rotation(self, value):
self._set_rotation_std_coords(
Transform({
"type": "eman",
"az": self.emanazslider.getValue(),
"alt": self.emanaltslider.getValue(),
"phi": self.emanphislider.getValue()
}))
self.inspector().updateSceneGraph()
def _on_Imagic_rotation(self, value):
self._set_rotation_std_coords(
Transform({
"type": "imagic",
"gamma": self.imagicgammaslider.getValue(),
"beta": self.imagicbetaslider.getValue(),
"alpha": self.imagicalphaslider.getValue()
}))
self.inspector().updateSceneGraph()
def _on_Spider_rotation(self, value):
self._set_rotation_std_coords(
Transform({
"type": "spider",
"psi": self.spiderpsislider.getValue(),
"theta": self.spiderthetaslider.getValue(),
"phi": self.spiderphislider.getValue()
}))
self.inspector().updateSceneGraph()
def _on_MRC_rotation(self, value):
self._set_rotation_std_coords(
Transform({
"type": "mrc",
"phi": self.mrcpsislider.getValue(),
"theta": self.mrcthetaslider.getValue(),
"omega": self.mrcomegaslider.getValue()
}))
self.inspector().updateSceneGraph()
def _on_XYZ_rotation(self, value):
self._set_rotation_std_coords(
Transform({
"type": "xyz",
"ztilt": self.xyzzslider.getValue(),
"ytilt": self.xyzyslider.getValue(),
"xtilt": self.xyzxslider.getValue()
}))
self.inspector().updateSceneGraph()
def _on_translation(self, value):
"""
Need to contain the right coords. And do translation in the correct corrd system
"""
tt = t = Transform({"tx":self.tx.getValue(),"ty":self.ty.getValue(),"tz":self.tz.getValue()})
tp = self.item3d().getParentMatrixProduct()
if tp: tt = tp.inverse()*t
self.item3d().getTransform().set_trans(tt.get_trans())
self.inspector().updateSceneGraph()
def transform_com(com, ptcl):
t = Transform()
if len(com) == 3:
t.set_rotation({'psi': meta.psi, 'phi': meta.phi, 'theta': meta.theta, 'type': 'spider'})
else:
t.set_rotation({'psi': meta.psi})
shift = t.transform(com)
# The change in the origin is the projection of the transformed difference vector on the new xy plane.
return shift[0], shift[1]
def getTransformFromDict(attribdict):
""" Return a transform using a dict created using the above function"""
return Transform({
"type": "eman",
"az": float(attribdict["az"].text()),
"alt": float(attribdict["alt"].text()),
"phi": float(attribdict["phi"].text()),
"tx": float(attribdict["tx"].text()),
"ty": float(attribdict["ty"].text()),
"tz": float(attribdict["tz"].text()),
"scale": float(attribdict["zoom"].text())
})
def setUsingDictionary(self, dictionary):
"""
Set item attributes using a dictionary, used in session restoration
"""
self.setTransform(Transform(dictionary["TRANSFORMATION"]))
self.setVisibleItem(dictionary["VISIBLE"])
self.setSelectedItem(dictionary["SELECTED"])
try:
self.setHiddenSelected(dictionary["HIDDENSEL"])
except:
pass
self.setLabel(dictionary["NAME"])
def _on_spin_rotation(self, value):
v = Vec3f(self.spinn1slider.getValue(), self.spinn2slider.getValue(),
self.spinn3slider.getValue())
v.normalize()
self._set_rotation_std_coords(
Transform({
"type": "spin",
"omega": self.spinomegaslider.getValue(),
"n1": v[0],
"n2": v[1],
"n3": v[2]
}))
self.inspector().updateSceneGraph()
def apply_rotation(angleset1, qrot):
from EMAN2 import Transform, Vec2f
"""
if indexes != None:
new_ang1 = []
new_ang2 = []
for i in indexes:
new_ang1.append(angleset1[i])
new_ang2.append(angleset2[i])
angleset1 = new_ang1
angleset2 = new_ang2
"""
import types
if(type(qrot) == types.ListType): rot = Transform({"type":"spider","phi":qrot[0],"theta":qrot[1],"psi":qrot[2]})
else: rot = qrot
for i in xrange(len(angleset1)):
T1 = Transform({"type":"spider","phi":angleset1[i][0],"theta":angleset1[i][1],"psi":angleset1[i][2],"tx":0.0,"ty":0.0,"tz":0.0,"mirror":0,"scale":1.0})
T1.set_trans(Vec2f(-angleset1[i][3], -angleset1[i][4]))
T = T1*rot
d = T.get_params("spider")
angleset1[i] = [d["phi"], d["theta"], d["psi"], -d["tx"], -d["ty"]]
def _on_sgirot_rotation(self, value):
v = Vec3f(self.sgirotn1slider.getValue(),
self.sgirotn2slider.getValue(),
self.sgirotn3slider.getValue())
v.normalize()
self._set_rotation_std_coords(
Transform({
"type": "sgirot",
"q": self.sgirotqslider.getValue(),
"n1": v[0],
"n2": v[1],
"n3": v[2]
}))
self.inspector().updateSceneGraph()
def _on_quaternion_rotation(self, value):
v = Vec4f(self.quaternione0slider.getValue(),
self.quaternione1slider.getValue(),
self.quaternione2slider.getValue(),
self.quaternione3slider.getValue())
v.normalize()
self._set_rotation_std_coords(
Transform({
"type": "quaternion",
"e0": v[0],
"e1": v[1],
"e2": v[2],
"e3": v[3]
}))
self.inspector().updateSceneGraph()
def make_proj(dens, meta):
"""
Project and CTF filter density according to particle metadata.
:param dens: EMData density
:param meta: Particle metadata (Euler angles and CTF parameters)
:return: CTF-filtered projection
"""
t = Transform()
t.set_rotation({'psi': meta.psi, 'phi': meta.phi, 'theta': meta.theta, 'type': 'spider'})
t.set_trans(-meta.x_origin, -meta.y_origin)
proj = dens.project("standard", t)
ctf = generate_ctf(meta.ctf_params)
ctf_proj = filt_ctf(proj, ctf)
return ctf_proj
def __init__(self, parent=None, children=[], transform=None):
"""
@type parent: EMItem3D
@param parent: the parent node to the current node or None for the root node
@type children: list
@param children: the child nodes
@type transform: Transform or None
@param transform: The transformation (rotation, scaling, translation) that should be applied before rendering this node and its children
"""
self.label = None # Customisabl label, used to label the inspector in the tree
self.setParent(parent)
self.setChildren(children)
if not transform: transform = Transform()
self.transform = transform
self.is_visible = True
self.is_selected = False
self.hide_selection = False
self.item_inspector = None # This is an inspector widget
self.EMQTreeWidgetItem = None # This is an inspector tree item
self.boundingboxsize = None
self.getAndSetUniqueInteger()
def execute(self):
'''
The main function - executes the job of performing all v all boot strapped probe generation
'''
if self.logger: E2progress(self.logger, 0.0)
# all_v_all_cmd = self.get_all_v_all_cmd()
# all_v_all_output = self.get_all_v_all_output()
#
# # NOTE: calling the allvall program is probably not strictly necessary, seeing
# # as there is a generic framework for generating and executing alignment jobs
# # implemented below that would be easily adaptable to this - however I left it
# # because doing it this way is absolutely equivalent and has the same cost.
# all_v_all_cmd += " --output="+all_v_all_output
# print "executing",all_v_all_cmd
# if self.logger: E2progress(self.logger,0.01)
# if ( launch_childprocess(all_v_all_cmd) != 0 ):
# print "Failed to execute %s" %all_v_all_cmd
# sys.exit(1)
# if self.logger: E2progress(self.logger,0.02)
#
# images = []
# images.append(EMData(all_v_all_output,0))
# images.append(EMData(all_v_all_output,1))
# images.append(EMData(all_v_all_output,2))
# images.append(EMData(all_v_all_output,3))
# images.append(EMData(all_v_all_output,4))
# images.append(EMData(all_v_all_output,5))
# images.append(EMData(all_v_all_output,6))
#
start_n = len(self.files) # the number of averages produced
images = []
e = EMData(start_n, start_n)
e.to_zero()
images.append(e)
for j in range(6):
images.append(e.copy())
# keep tracks of the names of the new files
big_n = images[0].get_xsize() * (images[0].get_xsize() - 1) / 2.0
iter = 1
current_files = self.files
alignment_jobs = [] # a list of comparisons to be performed
for i in range(len(current_files)):
for j in range(i + 1, len(current_files)):
alignment_jobs.append([i, j])
self.register_current_images(images)
self.register_current_files(self.files)
alignments_manager = EMTomoAlignments(self.options)
alignments_manager.execute(alignment_jobs, self.files, self)
self.write_current_images(self.files)
# this loop
while True:
couples = self.get_couples(images[0])
taken = list(range(images[0].get_xsize()))
done = False
if len(couples) == 1 and len(taken) == 2: done = True
#print len(couples),len(taken)
new_files = []
# write the averages of the couples to disk, store the new names
for i, j in couples:
image_1 = EMData(current_files[j], 0)
image_2 = EMData(current_files[i], 0)
image_1_weight = 1
if image_1.has_attr("total_inc"):
image_1_weight = image_1["total_inc"]
image_2_weight = 1
if image_2.has_attr("total_inc"):
image_2_weight = image_2["total_inc"]
total_weight = image_1_weight + image_2_weight
image_1.mult(old_div(float(image_1_weight), total_weight))
image_2.mult(old_div(float(image_2_weight), total_weight))
d = {}
d["type"] = "eman"
d["tx"] = images[1].get(i, j)
d["ty"] = images[2].get(i, j)
d["tz"] = images[3].get(i, j)
d["az"] = images[4].get(i, j)
d["alt"] = images[5].get(i, j)
d["phi"] = images[6].get(i, j)
t = Transform(d)
image_1.process_inplace("xform", {"transform": t})
image_2 += image_1
image_2.set_attr(
"src_image",
current_files[j]) # so we can recollect how it was created
image_2.set_attr(
"added_src_image",
current_files[i]) # so we can recollect how it was created
image_2.set_attr("added_src_transform",
t) # so we can recollect how it was created
image_2.set_attr("added_src_cmp", images[0](
i, j)) # so we can recollect how it was created
image_2.set_attr(
"total_inc",
total_weight) # so we can recollect how it was created
output_name = numbered_bdb("bdb:" + self.options.path +
"#tomo_ave_0" + str(iter - 1))
image_2.write_image(output_name, 0)
if self.options.dbls: self.save_to_workflow_db(output_name)
new_files.append(output_name)
taken.remove(i)
taken.remove(j)
if done: break
num_new = len(new_files) # the number of averages produced
new_n = len(new_files) + len(taken)
new_images = []
e = EMData(new_n, new_n)
e.to_zero()
new_images.append(e)
for j in range(6):
new_images.append(e.copy())
for i, idxi in enumerate(taken):
new_files.append(current_files[idxi])
for j, idxj in enumerate(taken):
if i == j: continue
else:
new_images[0].set(num_new + i, num_new + j,
images[0].get(idxi, idxj))
new_images[1].set(num_new + i, num_new + j,
images[1].get(idxi, idxj))
new_images[2].set(num_new + i, num_new + j,
images[2].get(idxi, idxj))
new_images[3].set(num_new + i, num_new + j,
images[3].get(idxi, idxj))
new_images[4].set(num_new + i, num_new + j,
images[4].get(idxi, idxj))
new_images[5].set(num_new + i, num_new + j,
images[5].get(idxi, idxj))
new_images[6].set(num_new + i, num_new + j,
images[6].get(idxi, idxj))
alignment_jobs = [] # a list of comparisons to be performed
for i in range(num_new):
for j in range(i + 1, len(new_files)):
alignment_jobs.append([i, j])
if self.logger:
E2progress(self.logger,
1.0 - old_div(len(alignment_jobs), big_n))
self.register_current_images(new_images)
self.register_current_files(new_files)
alignments_manager = EMTomoAlignments(self.options)
alignments_manager.execute(alignment_jobs, new_files, self)
self.write_current_images(new_files)
current_files = new_files
images = new_images
iter += 1
print(couples, taken)
if self.logger: E2progress(self.logger, 1.0)
def main():
def params_3D_2D_NEW(phi, theta, psi, s2x, s2y, mirror):
# the final ali2d parameters already combine shifts operation first and rotation operation second for parameters converted from 3D
if mirror:
m = 1
alpha, sx, sy, scalen = compose_transform2(0, s2x, s2y, 1.0, 540.0-psi, 0, 0, 1.0)
else:
m = 0
alpha, sx, sy, scalen = compose_transform2(0, s2x, s2y, 1.0, 360.0-psi, 0, 0, 1.0)
return alpha, sx, sy, m
progname = os.path.basename(sys.argv[0])
usage = progname + " prj_stack --ave2D= --var2D= --ave3D= --var3D= --img_per_grp= --fl= --aa= --sym=symmetry --CTF"
parser = OptionParser(usage, version=SPARXVERSION)
parser.add_option("--output_dir", type="string" , default="./", help="Output directory")
parser.add_option("--ave2D", type="string" , default=False, help="Write to the disk a stack of 2D averages")
parser.add_option("--var2D", type="string" , default=False, help="Write to the disk a stack of 2D variances")
parser.add_option("--ave3D", type="string" , default=False, help="Write to the disk reconstructed 3D average")
parser.add_option("--var3D", type="string" , default=False, help="Compute 3D variability (time consuming!)")
parser.add_option("--img_per_grp", type="int" , default=100, help="Number of neighbouring projections.(Default is 100)")
parser.add_option("--no_norm", action="store_true", default=False, help="Do not use normalization.(Default is to apply normalization)")
#parser.add_option("--radius", type="int" , default=-1 , help="radius for 3D variability" )
parser.add_option("--npad", type="int" , default=2 , help="Number of time to pad the original images.(Default is 2 times padding)")
parser.add_option("--sym" , type="string" , default="c1", help="Symmetry. (Default is no symmetry)")
parser.add_option("--fl", type="float" , default=0.0, help="Low pass filter cutoff in absolute frequency (0.0 - 0.5) and is applied to decimated images. (Default - no filtration)")
parser.add_option("--aa", type="float" , default=0.02 , help="Fall off of the filter. Use default value if user has no clue about falloff (Default value is 0.02)")
parser.add_option("--CTF", action="store_true", default=False, help="Use CFT correction.(Default is no CTF correction)")
#parser.add_option("--MPI" , action="store_true", default=False, help="use MPI version")
#parser.add_option("--radiuspca", type="int" , default=-1 , help="radius for PCA" )
#parser.add_option("--iter", type="int" , default=40 , help="maximum number of iterations (stop criterion of reconstruction process)" )
#parser.add_option("--abs", type="float" , default=0.0 , help="minimum average absolute change of voxels' values (stop criterion of reconstruction process)" )
#parser.add_option("--squ", type="float" , default=0.0 , help="minimum average squared change of voxels' values (stop criterion of reconstruction process)" )
parser.add_option("--VAR" , action="store_true", default=False, help="Stack of input consists of 2D variances (Default False)")
parser.add_option("--decimate", type ="float", default=0.25, help="Image decimate rate, a number less than 1. (Default is 0.25)")
parser.add_option("--window", type ="int", default=0, help="Target image size relative to original image size. (Default value is zero.)")
#parser.add_option("--SND", action="store_true", default=False, help="compute squared normalized differences (Default False)")
#parser.add_option("--nvec", type="int" , default=0 , help="Number of eigenvectors, (Default = 0 meaning no PCA calculated)")
parser.add_option("--symmetrize", action="store_true", default=False, help="Prepare input stack for handling symmetry (Default False)")
parser.add_option("--overhead", type ="float", default=0.5, help="python overhead per CPU.")
(options,args) = parser.parse_args()
#####
from mpi import mpi_init, mpi_comm_rank, mpi_comm_size, mpi_recv, MPI_COMM_WORLD
from mpi import mpi_barrier, mpi_reduce, mpi_bcast, mpi_send, MPI_FLOAT, MPI_SUM, MPI_INT, MPI_MAX
#from mpi import *
from applications import MPI_start_end
from reconstruction import recons3d_em, recons3d_em_MPI
from reconstruction import recons3d_4nn_MPI, recons3d_4nn_ctf_MPI
from utilities import print_begin_msg, print_end_msg, print_msg
from utilities import read_text_row, get_image, get_im, wrap_mpi_send, wrap_mpi_recv
from utilities import bcast_EMData_to_all, bcast_number_to_all
from utilities import get_symt
# This is code for handling symmetries by the above program. To be incorporated. PAP 01/27/2015
from EMAN2db import db_open_dict
# Set up global variables related to bdb cache
if global_def.CACHE_DISABLE:
from utilities import disable_bdb_cache
disable_bdb_cache()
# Set up global variables related to ERROR function
global_def.BATCH = True
# detect if program is running under MPI
RUNNING_UNDER_MPI = "OMPI_COMM_WORLD_SIZE" in os.environ
if RUNNING_UNDER_MPI: global_def.MPI = True
if options.output_dir =="./": current_output_dir = os.path.abspath(options.output_dir)
else: current_output_dir = options.output_dir
if options.symmetrize :
if RUNNING_UNDER_MPI:
try:
sys.argv = mpi_init(len(sys.argv), sys.argv)
try:
number_of_proc = mpi_comm_size(MPI_COMM_WORLD)
if( number_of_proc > 1 ):
ERROR("Cannot use more than one CPU for symmetry preparation","sx3dvariability",1)
except:
pass
except:
pass
if not os.path.exists(current_output_dir): os.mkdir(current_output_dir)
# Input
#instack = "Clean_NORM_CTF_start_wparams.hdf"
#instack = "bdb:data"
from logger import Logger,BaseLogger_Files
if os.path.exists(os.path.join(current_output_dir, "log.txt")): os.remove(os.path.join(current_output_dir, "log.txt"))
log_main=Logger(BaseLogger_Files())
log_main.prefix = os.path.join(current_output_dir, "./")
instack = args[0]
sym = options.sym.lower()
if( sym == "c1" ):
ERROR("There is no need to symmetrize stack for C1 symmetry","sx3dvariability",1)
line =""
for a in sys.argv:
line +=" "+a
log_main.add(line)
if(instack[:4] !="bdb:"):
#if output_dir =="./": stack = "bdb:data"
stack = "bdb:"+current_output_dir+"/data"
delete_bdb(stack)
junk = cmdexecute("sxcpy.py "+instack+" "+stack)
else: stack = instack
qt = EMUtil.get_all_attributes(stack,'xform.projection')
na = len(qt)
ts = get_symt(sym)
ks = len(ts)
angsa = [None]*na
for k in range(ks):
#Qfile = "Q%1d"%k
#if options.output_dir!="./": Qfile = os.path.join(options.output_dir,"Q%1d"%k)
Qfile = os.path.join(current_output_dir, "Q%1d"%k)
#delete_bdb("bdb:Q%1d"%k)
delete_bdb("bdb:"+Qfile)
#junk = cmdexecute("e2bdb.py "+stack+" --makevstack=bdb:Q%1d"%k)
junk = cmdexecute("e2bdb.py "+stack+" --makevstack=bdb:"+Qfile)
#DB = db_open_dict("bdb:Q%1d"%k)
DB = db_open_dict("bdb:"+Qfile)
for i in range(na):
ut = qt[i]*ts[k]
DB.set_attr(i, "xform.projection", ut)
#bt = ut.get_params("spider")
#angsa[i] = [round(bt["phi"],3)%360.0, round(bt["theta"],3)%360.0, bt["psi"], -bt["tx"], -bt["ty"]]
#write_text_row(angsa, 'ptsma%1d.txt'%k)
#junk = cmdexecute("e2bdb.py "+stack+" --makevstack=bdb:Q%1d"%k)
#junk = cmdexecute("sxheader.py bdb:Q%1d --params=xform.projection --import=ptsma%1d.txt"%(k,k))
DB.close()
#if options.output_dir =="./": delete_bdb("bdb:sdata")
delete_bdb("bdb:" + current_output_dir + "/"+"sdata")
#junk = cmdexecute("e2bdb.py . --makevstack=bdb:sdata --filt=Q")
sdata = "bdb:"+current_output_dir+"/"+"sdata"
print(sdata)
junk = cmdexecute("e2bdb.py " + current_output_dir +" --makevstack="+sdata +" --filt=Q")
#junk = cmdexecute("ls EMAN2DB/sdata*")
#a = get_im("bdb:sdata")
a = get_im(sdata)
a.set_attr("variabilitysymmetry",sym)
#a.write_image("bdb:sdata")
a.write_image(sdata)
else:
from fundamentals import window2d
sys.argv = mpi_init(len(sys.argv), sys.argv)
myid = mpi_comm_rank(MPI_COMM_WORLD)
number_of_proc = mpi_comm_size(MPI_COMM_WORLD)
main_node = 0
shared_comm = mpi_comm_split_type(MPI_COMM_WORLD, MPI_COMM_TYPE_SHARED, 0, MPI_INFO_NULL)
myid_on_node = mpi_comm_rank(shared_comm)
no_of_processes_per_group = mpi_comm_size(shared_comm)
masters_from_groups_vs_everything_else_comm = mpi_comm_split(MPI_COMM_WORLD, main_node == myid_on_node, myid_on_node)
color, no_of_groups, balanced_processor_load_on_nodes = get_colors_and_subsets(main_node, MPI_COMM_WORLD, myid, \
shared_comm, myid_on_node, masters_from_groups_vs_everything_else_comm)
overhead_loading = options.overhead*number_of_proc
#memory_per_node = options.memory_per_node
#if memory_per_node == -1.: memory_per_node = 2.*no_of_processes_per_group
keepgoing = 1
current_window = options.window
current_decimate = options.decimate
if len(args) == 1: stack = args[0]
else:
print(( "usage: " + usage))
print(( "Please run '" + progname + " -h' for detailed options"))
return 1
t0 = time()
# obsolete flags
options.MPI = True
#options.nvec = 0
options.radiuspca = -1
options.iter = 40
options.abs = 0.0
options.squ = 0.0
if options.fl > 0.0 and options.aa == 0.0:
ERROR("Fall off has to be given for the low-pass filter", "sx3dvariability", 1, myid)
#if options.VAR and options.SND:
# ERROR("Only one of var and SND can be set!", "sx3dvariability", myid)
if options.VAR and (options.ave2D or options.ave3D or options.var2D):
ERROR("When VAR is set, the program cannot output ave2D, ave3D or var2D", "sx3dvariability", 1, myid)
#if options.SND and (options.ave2D or options.ave3D):
# ERROR("When SND is set, the program cannot output ave2D or ave3D", "sx3dvariability", 1, myid)
#if options.nvec > 0 :
# ERROR("PCA option not implemented", "sx3dvariability", 1, myid)
#if options.nvec > 0 and options.ave3D == None:
# ERROR("When doing PCA analysis, one must set ave3D", "sx3dvariability", 1, myid)
if current_decimate>1.0 or current_decimate<0.0:
ERROR("Decimate rate should be a value between 0.0 and 1.0", "sx3dvariability", 1, myid)
if current_window < 0.0:
ERROR("Target window size should be always larger than zero", "sx3dvariability", 1, myid)
if myid == main_node:
img = get_image(stack, 0)
nx = img.get_xsize()
ny = img.get_ysize()
if(min(nx, ny) < current_window): keepgoing = 0
keepgoing = bcast_number_to_all(keepgoing, main_node, MPI_COMM_WORLD)
if keepgoing == 0: ERROR("The target window size cannot be larger than the size of decimated image", "sx3dvariability", 1, myid)
import string
options.sym = options.sym.lower()
# if global_def.CACHE_DISABLE:
# from utilities import disable_bdb_cache
# disable_bdb_cache()
# global_def.BATCH = True
if myid == main_node:
if not os.path.exists(current_output_dir): os.mkdir(current_output_dir)# Never delete output_dir in the program!
img_per_grp = options.img_per_grp
#nvec = options.nvec
radiuspca = options.radiuspca
from logger import Logger,BaseLogger_Files
#if os.path.exists(os.path.join(options.output_dir, "log.txt")): os.remove(os.path.join(options.output_dir, "log.txt"))
log_main=Logger(BaseLogger_Files())
log_main.prefix = os.path.join(current_output_dir, "./")
if myid == main_node:
line = ""
for a in sys.argv: line +=" "+a
log_main.add(line)
log_main.add("-------->>>Settings given by all options<<<-------")
log_main.add("Symmetry : %s"%options.sym)
log_main.add("Input stack : %s"%stack)
log_main.add("Output_dir : %s"%current_output_dir)
if options.ave3D: log_main.add("Ave3d : %s"%options.ave3D)
if options.var3D: log_main.add("Var3d : %s"%options.var3D)
if options.ave2D: log_main.add("Ave2D : %s"%options.ave2D)
if options.var2D: log_main.add("Var2D : %s"%options.var2D)
if options.VAR: log_main.add("VAR : True")
else: log_main.add("VAR : False")
if options.CTF: log_main.add("CTF correction : True ")
else: log_main.add("CTF correction : False ")
log_main.add("Image per group : %5d"%options.img_per_grp)
log_main.add("Image decimate rate : %4.3f"%current_decimate)
log_main.add("Low pass filter : %4.3f"%options.fl)
current_fl = options.fl
if current_fl == 0.0: current_fl = 0.5
log_main.add("Current low pass filter is equivalent to cutoff frequency %4.3f for original image size"%round((current_fl*current_decimate),3))
log_main.add("Window size : %5d "%current_window)
log_main.add("sx3dvariability begins")
symbaselen = 0
if myid == main_node:
nima = EMUtil.get_image_count(stack)
img = get_image(stack)
nx = img.get_xsize()
ny = img.get_ysize()
nnxo = nx
nnyo = ny
if options.sym != "c1" :
imgdata = get_im(stack)
try:
i = imgdata.get_attr("variabilitysymmetry").lower()
if(i != options.sym):
ERROR("The symmetry provided does not agree with the symmetry of the input stack", "sx3dvariability", 1, myid)
except:
ERROR("Input stack is not prepared for symmetry, please follow instructions", "sx3dvariability", 1, myid)
from utilities import get_symt
i = len(get_symt(options.sym))
if((nima/i)*i != nima):
ERROR("The length of the input stack is incorrect for symmetry processing", "sx3dvariability", 1, myid)
symbaselen = nima/i
else: symbaselen = nima
else:
nima = 0
nx = 0
ny = 0
nnxo = 0
nnyo = 0
nima = bcast_number_to_all(nima)
nx = bcast_number_to_all(nx)
ny = bcast_number_to_all(ny)
nnxo = bcast_number_to_all(nnxo)
nnyo = bcast_number_to_all(nnyo)
if current_window > max(nx, ny):
ERROR("Window size is larger than the original image size", "sx3dvariability", 1)
if current_decimate == 1.:
if current_window !=0:
nx = current_window
ny = current_window
else:
if current_window == 0:
nx = int(nx*current_decimate+0.5)
ny = int(ny*current_decimate+0.5)
else:
nx = int(current_window*current_decimate+0.5)
ny = nx
symbaselen = bcast_number_to_all(symbaselen)
# check FFT prime number
from fundamentals import smallprime
is_fft_friendly = (nx == smallprime(nx))
if not is_fft_friendly:
if myid == main_node:
log_main.add("The target image size is not a product of small prime numbers")
log_main.add("Program adjusts the input settings!")
### two cases
if current_decimate == 1.:
nx = smallprime(nx)
ny = nx
current_window = nx # update
if myid == main_node:
log_main.add("The window size is updated to %d."%current_window)
else:
if current_window == 0:
nx = smallprime(int(nx*current_decimate+0.5))
current_decimate = float(nx)/nnxo
ny = nx
if (myid == main_node):
log_main.add("The decimate rate is updated to %f."%current_decimate)
else:
nx = smallprime(int(current_window*current_decimate+0.5))
ny = nx
current_window = int(nx/current_decimate+0.5)
if (myid == main_node):
log_main.add("The window size is updated to %d."%current_window)
if myid == main_node:
log_main.add("The target image size is %d"%nx)
if radiuspca == -1: radiuspca = nx/2-2
if myid == main_node: log_main.add("%-70s: %d\n"%("Number of projection", nima))
img_begin, img_end = MPI_start_end(nima, number_of_proc, myid)
"""
if options.SND:
from projection import prep_vol, prgs
from statistics import im_diff
from utilities import get_im, model_circle, get_params_proj, set_params_proj
from utilities import get_ctf, generate_ctf
from filter import filt_ctf
imgdata = EMData.read_images(stack, range(img_begin, img_end))
if options.CTF:
vol = recons3d_4nn_ctf_MPI(myid, imgdata, 1.0, symmetry=options.sym, npad=options.npad, xysize=-1, zsize=-1)
else:
vol = recons3d_4nn_MPI(myid, imgdata, symmetry=options.sym, npad=options.npad, xysize=-1, zsize=-1)
bcast_EMData_to_all(vol, myid)
volft, kb = prep_vol(vol)
mask = model_circle(nx/2-2, nx, ny)
varList = []
for i in xrange(img_begin, img_end):
phi, theta, psi, s2x, s2y = get_params_proj(imgdata[i-img_begin])
ref_prj = prgs(volft, kb, [phi, theta, psi, -s2x, -s2y])
if options.CTF:
ctf_params = get_ctf(imgdata[i-img_begin])
ref_prj = filt_ctf(ref_prj, generate_ctf(ctf_params))
diff, A, B = im_diff(ref_prj, imgdata[i-img_begin], mask)
diff2 = diff*diff
set_params_proj(diff2, [phi, theta, psi, s2x, s2y])
varList.append(diff2)
mpi_barrier(MPI_COMM_WORLD)
"""
if options.VAR: # 2D variance images have no shifts
#varList = EMData.read_images(stack, range(img_begin, img_end))
from EMAN2 import Region
for index_of_particle in range(img_begin,img_end):
image = get_im(stack, index_of_proj)
if current_window > 0: varList.append(fdecimate(window2d(image,current_window,current_window), nx,ny))
else: varList.append(fdecimate(image, nx,ny))
else:
from utilities import bcast_number_to_all, bcast_list_to_all, send_EMData, recv_EMData
from utilities import set_params_proj, get_params_proj, params_3D_2D, get_params2D, set_params2D, compose_transform2
from utilities import model_blank, nearest_proj, model_circle, write_text_row, wrap_mpi_gatherv
from applications import pca
from statistics import avgvar, avgvar_ctf, ccc
from filter import filt_tanl
from morphology import threshold, square_root
from projection import project, prep_vol, prgs
from sets import Set
from utilities import wrap_mpi_recv, wrap_mpi_bcast, wrap_mpi_send
import numpy as np
if myid == main_node:
t1 = time()
proj_angles = []
aveList = []
tab = EMUtil.get_all_attributes(stack, 'xform.projection')
for i in range(nima):
t = tab[i].get_params('spider')
phi = t['phi']
theta = t['theta']
psi = t['psi']
x = theta
if x > 90.0: x = 180.0 - x
x = x*10000+psi
proj_angles.append([x, t['phi'], t['theta'], t['psi'], i])
t2 = time()
log_main.add( "%-70s: %d\n"%("Number of neighboring projections", img_per_grp))
log_main.add("...... Finding neighboring projections\n")
log_main.add( "Number of images per group: %d"%img_per_grp)
log_main.add( "Now grouping projections")
proj_angles.sort()
proj_angles_list = np.full((nima, 4), 0.0, dtype=np.float32)
for i in range(nima):
proj_angles_list[i][0] = proj_angles[i][1]
proj_angles_list[i][1] = proj_angles[i][2]
proj_angles_list[i][2] = proj_angles[i][3]
proj_angles_list[i][3] = proj_angles[i][4]
else: proj_angles_list = 0
proj_angles_list = wrap_mpi_bcast(proj_angles_list, main_node, MPI_COMM_WORLD)
proj_angles = []
for i in range(nima):
proj_angles.append([proj_angles_list[i][0], proj_angles_list[i][1], proj_angles_list[i][2], int(proj_angles_list[i][3])])
del proj_angles_list
proj_list, mirror_list = nearest_proj(proj_angles, img_per_grp, range(img_begin, img_end))
all_proj = Set()
for im in proj_list:
for jm in im:
all_proj.add(proj_angles[jm][3])
all_proj = list(all_proj)
index = {}
for i in range(len(all_proj)): index[all_proj[i]] = i
mpi_barrier(MPI_COMM_WORLD)
if myid == main_node:
log_main.add("%-70s: %.2f\n"%("Finding neighboring projections lasted [s]", time()-t2))
log_main.add("%-70s: %d\n"%("Number of groups processed on the main node", len(proj_list)))
log_main.add("Grouping projections took: %12.1f [m]"%((time()-t2)/60.))
log_main.add("Number of groups on main node: ", len(proj_list))
mpi_barrier(MPI_COMM_WORLD)
if myid == main_node:
log_main.add("...... Calculating the stack of 2D variances \n")
# Memory estimation. There are two memory consumption peaks
# peak 1. Compute ave, var;
# peak 2. Var volume reconstruction;
# proj_params = [0.0]*(nima*5)
aveList = []
varList = []
#if nvec > 0: eigList = [[] for i in range(nvec)]
dnumber = len(all_proj)# all neighborhood set for assigned to myid
pnumber = len(proj_list)*2. + img_per_grp # aveList and varList
tnumber = dnumber+pnumber
vol_size2 = nx**3*4.*8/1.e9
vol_size1 = 2.*nnxo**3*4.*8/1.e9
proj_size = nnxo*nnyo*len(proj_list)*4.*2./1.e9 # both aveList and varList
orig_data_size = nnxo*nnyo*4.*tnumber/1.e9
reduced_data_size = nx*nx*4.*tnumber/1.e9
full_data = np.full((number_of_proc, 2), -1., dtype=np.float16)
full_data[myid] = orig_data_size, reduced_data_size
if myid != main_node: wrap_mpi_send(full_data, main_node, MPI_COMM_WORLD)
if myid == main_node:
for iproc in range(number_of_proc):
if iproc != main_node:
dummy = wrap_mpi_recv(iproc, MPI_COMM_WORLD)
full_data[np.where(dummy>-1)] = dummy[np.where(dummy>-1)]
del dummy
mpi_barrier(MPI_COMM_WORLD)
full_data = wrap_mpi_bcast(full_data, main_node, MPI_COMM_WORLD)
# find the CPU with heaviest load
minindx = np.argsort(full_data, 0)
heavy_load_myid = minindx[-1][1]
total_mem = sum(full_data)
if myid == main_node:
if current_window == 0:
log_main.add("Nx: current image size = %d. Decimated by %f from %d"%(nx, current_decimate, nnxo))
else:
log_main.add("Nx: current image size = %d. Windowed to %d, and decimated by %f from %d"%(nx, current_window, current_decimate, nnxo))
log_main.add("Nproj: number of particle images.")
log_main.add("Navg: number of 2D average images.")
log_main.add("Nvar: number of 2D variance images.")
log_main.add("Img_per_grp: user defined image per group for averaging = %d"%img_per_grp)
log_main.add("Overhead: total python overhead memory consumption = %f"%overhead_loading)
log_main.add("Total memory) = 4.0*nx^2*(nproj + navg +nvar+ img_per_grp)/1.0e9 + overhead: %12.3f [GB]"%\
(total_mem[1] + overhead_loading))
del full_data
mpi_barrier(MPI_COMM_WORLD)
if myid == heavy_load_myid:
log_main.add("Begin reading and preprocessing images on processor. Wait... ")
ttt = time()
#imgdata = EMData.read_images(stack, all_proj)
imgdata = [ None for im in range(len(all_proj))]
for index_of_proj in range(len(all_proj)):
#image = get_im(stack, all_proj[index_of_proj])
if( current_window > 0): imgdata[index_of_proj] = fdecimate(window2d(get_im(stack, all_proj[index_of_proj]),current_window,current_window), nx, ny)
else: imgdata[index_of_proj] = fdecimate(get_im(stack, all_proj[index_of_proj]), nx, ny)
if (current_decimate> 0.0 and options.CTF):
ctf = imgdata[index_of_proj].get_attr("ctf")
ctf.apix = ctf.apix/current_decimate
imgdata[index_of_proj].set_attr("ctf", ctf)
if myid == heavy_load_myid and index_of_proj%100 == 0:
log_main.add(" ...... %6.2f%% "%(index_of_proj/float(len(all_proj))*100.))
mpi_barrier(MPI_COMM_WORLD)
if myid == heavy_load_myid:
log_main.add("All_proj preprocessing cost %7.2f m"%((time()-ttt)/60.))
log_main.add("Wait untill reading on all CPUs done...")
'''
imgdata2 = EMData.read_images(stack, range(img_begin, img_end))
if options.fl > 0.0:
for k in xrange(len(imgdata2)):
imgdata2[k] = filt_tanl(imgdata2[k], options.fl, options.aa)
if options.CTF:
vol = recons3d_4nn_ctf_MPI(myid, imgdata2, 1.0, symmetry=options.sym, npad=options.npad, xysize=-1, zsize=-1)
else:
vol = recons3d_4nn_MPI(myid, imgdata2, symmetry=options.sym, npad=options.npad, xysize=-1, zsize=-1)
if myid == main_node:
vol.write_image("vol_ctf.hdf")
print_msg("Writing to the disk volume reconstructed from averages as : %s\n"%("vol_ctf.hdf"))
del vol, imgdata2
mpi_barrier(MPI_COMM_WORLD)
'''
from applications import prepare_2d_forPCA
from utilities import model_blank
from EMAN2 import Transform
if not options.no_norm:
mask = model_circle(nx/2-2, nx, nx)
if options.CTF:
from utilities import pad
from filter import filt_ctf
from filter import filt_tanl
if myid == heavy_load_myid:
log_main.add("Start computing 2D aveList and varList. Wait...")
ttt = time()
inner=nx//2-4
outer=inner+2
xform_proj_for_2D = [ None for i in range(len(proj_list))]
for i in range(len(proj_list)):
ki = proj_angles[proj_list[i][0]][3]
if ki >= symbaselen: continue
mi = index[ki]
dpar = Util.get_transform_params(imgdata[mi], "xform.projection", "spider")
phiM, thetaM, psiM, s2xM, s2yM = dpar["phi"],dpar["theta"],dpar["psi"],-dpar["tx"]*current_decimate,-dpar["ty"]*current_decimate
grp_imgdata = []
for j in range(img_per_grp):
mj = index[proj_angles[proj_list[i][j]][3]]
cpar = Util.get_transform_params(imgdata[mj], "xform.projection", "spider")
alpha, sx, sy, mirror = params_3D_2D_NEW(cpar["phi"], cpar["theta"],cpar["psi"], -cpar["tx"]*current_decimate, -cpar["ty"]*current_decimate, mirror_list[i][j])
if thetaM <= 90:
if mirror == 0: alpha, sx, sy, scale = compose_transform2(alpha, sx, sy, 1.0, phiM - cpar["phi"], 0.0, 0.0, 1.0)
else: alpha, sx, sy, scale = compose_transform2(alpha, sx, sy, 1.0, 180-(phiM - cpar["phi"]), 0.0, 0.0, 1.0)
else:
if mirror == 0: alpha, sx, sy, scale = compose_transform2(alpha, sx, sy, 1.0, -(phiM- cpar["phi"]), 0.0, 0.0, 1.0)
else: alpha, sx, sy, scale = compose_transform2(alpha, sx, sy, 1.0, -(180-(phiM - cpar["phi"])), 0.0, 0.0, 1.0)
imgdata[mj].set_attr("xform.align2d", Transform({"type":"2D","alpha":alpha,"tx":sx,"ty":sy,"mirror":mirror,"scale":1.0}))
grp_imgdata.append(imgdata[mj])
if not options.no_norm:
for k in range(img_per_grp):
ave, std, minn, maxx = Util.infomask(grp_imgdata[k], mask, False)
grp_imgdata[k] -= ave
grp_imgdata[k] /= std
if options.fl > 0.0:
for k in range(img_per_grp):
grp_imgdata[k] = filt_tanl(grp_imgdata[k], options.fl, options.aa)
# Because of background issues, only linear option works.
if options.CTF: ave, var = aves_wiener(grp_imgdata, SNR = 1.0e5, interpolation_method = "linear")
else: ave, var = ave_var(grp_imgdata)
# Switch to std dev
# threshold is not really needed,it is just in case due to numerical accuracy something turns out negative.
var = square_root(threshold(var))
set_params_proj(ave, [phiM, thetaM, 0.0, 0.0, 0.0])
set_params_proj(var, [phiM, thetaM, 0.0, 0.0, 0.0])
aveList.append(ave)
varList.append(var)
xform_proj_for_2D[i] = [phiM, thetaM, 0.0, 0.0, 0.0]
'''
if nvec > 0:
eig = pca(input_stacks=grp_imgdata, subavg="", mask_radius=radiuspca, nvec=nvec, incore=True, shuffle=False, genbuf=True)
for k in range(nvec):
set_params_proj(eig[k], [phiM, thetaM, 0.0, 0.0, 0.0])
eigList[k].append(eig[k])
"""
if myid == 0 and i == 0:
for k in xrange(nvec):
eig[k].write_image("eig.hdf", k)
"""
'''
if (myid == heavy_load_myid) and (i%100 == 0):
log_main.add(" ......%6.2f%% "%(i/float(len(proj_list))*100.))
del imgdata, grp_imgdata, cpar, dpar, all_proj, proj_angles, index
if not options.no_norm: del mask
if myid == main_node: del tab
# At this point, all averages and variances are computed
mpi_barrier(MPI_COMM_WORLD)
if (myid == heavy_load_myid):
log_main.add("Computing aveList and varList took %12.1f [m]"%((time()-ttt)/60.))
xform_proj_for_2D = wrap_mpi_gatherv(xform_proj_for_2D, main_node, MPI_COMM_WORLD)
if (myid == main_node):
write_text_row(xform_proj_for_2D, os.path.join(current_output_dir, "params.txt"))
del xform_proj_for_2D
mpi_barrier(MPI_COMM_WORLD)
if options.ave2D:
from fundamentals import fpol
from applications import header
if myid == main_node:
log_main.add("Compute ave2D ... ")
km = 0
for i in range(number_of_proc):
if i == main_node :
for im in range(len(aveList)):
aveList[im].write_image(os.path.join(current_output_dir, options.ave2D), km)
km += 1
else:
nl = mpi_recv(1, MPI_INT, i, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
nl = int(nl[0])
for im in range(nl):
ave = recv_EMData(i, im+i+70000)
"""
nm = mpi_recv(1, MPI_INT, i, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
nm = int(nm[0])
members = mpi_recv(nm, MPI_INT, i, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
ave.set_attr('members', map(int, members))
members = mpi_recv(nm, MPI_FLOAT, i, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
ave.set_attr('pix_err', map(float, members))
members = mpi_recv(3, MPI_FLOAT, i, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
ave.set_attr('refprojdir', map(float, members))
"""
tmpvol=fpol(ave, nx, nx,1)
tmpvol.write_image(os.path.join(current_output_dir, options.ave2D), km)
km += 1
else:
mpi_send(len(aveList), 1, MPI_INT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
for im in range(len(aveList)):
send_EMData(aveList[im], main_node,im+myid+70000)
"""
members = aveList[im].get_attr('members')
mpi_send(len(members), 1, MPI_INT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
mpi_send(members, len(members), MPI_INT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
members = aveList[im].get_attr('pix_err')
mpi_send(members, len(members), MPI_FLOAT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
try:
members = aveList[im].get_attr('refprojdir')
mpi_send(members, 3, MPI_FLOAT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
except:
mpi_send([-999.0,-999.0,-999.0], 3, MPI_FLOAT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
"""
if myid == main_node:
header(os.path.join(current_output_dir, options.ave2D), params='xform.projection', fimport = os.path.join(current_output_dir, "params.txt"))
mpi_barrier(MPI_COMM_WORLD)
if options.ave3D:
from fundamentals import fpol
t5 = time()
if myid == main_node: log_main.add("Reconstruct ave3D ... ")
ave3D = recons3d_4nn_MPI(myid, aveList, symmetry=options.sym, npad=options.npad)
bcast_EMData_to_all(ave3D, myid)
if myid == main_node:
if current_decimate != 1.0: ave3D = resample(ave3D, 1./current_decimate)
ave3D = fpol(ave3D, nnxo, nnxo, nnxo) # always to the orignal image size
set_pixel_size(ave3D, 1.0)
ave3D.write_image(os.path.join(current_output_dir, options.ave3D))
log_main.add("Ave3D reconstruction took %12.1f [m]"%((time()-t5)/60.0))
log_main.add("%-70s: %s\n"%("The reconstructed ave3D is saved as ", options.ave3D))
mpi_barrier(MPI_COMM_WORLD)
del ave, var, proj_list, stack, alpha, sx, sy, mirror, aveList
'''
if nvec > 0:
for k in range(nvec):
if myid == main_node:log_main.add("Reconstruction eigenvolumes", k)
cont = True
ITER = 0
mask2d = model_circle(radiuspca, nx, nx)
while cont:
#print "On node %d, iteration %d"%(myid, ITER)
eig3D = recons3d_4nn_MPI(myid, eigList[k], symmetry=options.sym, npad=options.npad)
bcast_EMData_to_all(eig3D, myid, main_node)
if options.fl > 0.0:
eig3D = filt_tanl(eig3D, options.fl, options.aa)
if myid == main_node:
eig3D.write_image(os.path.join(options.outpout_dir, "eig3d_%03d.hdf"%(k, ITER)))
Util.mul_img( eig3D, model_circle(radiuspca, nx, nx, nx) )
eig3Df, kb = prep_vol(eig3D)
del eig3D
cont = False
icont = 0
for l in range(len(eigList[k])):
phi, theta, psi, s2x, s2y = get_params_proj(eigList[k][l])
proj = prgs(eig3Df, kb, [phi, theta, psi, s2x, s2y])
cl = ccc(proj, eigList[k][l], mask2d)
if cl < 0.0:
icont += 1
cont = True
eigList[k][l] *= -1.0
u = int(cont)
u = mpi_reduce([u], 1, MPI_INT, MPI_MAX, main_node, MPI_COMM_WORLD)
icont = mpi_reduce([icont], 1, MPI_INT, MPI_SUM, main_node, MPI_COMM_WORLD)
if myid == main_node:
u = int(u[0])
log_main.add(" Eigenvector: ",k," number changed ",int(icont[0]))
else: u = 0
u = bcast_number_to_all(u, main_node)
cont = bool(u)
ITER += 1
del eig3Df, kb
mpi_barrier(MPI_COMM_WORLD)
del eigList, mask2d
'''
if options.ave3D: del ave3D
if options.var2D:
from fundamentals import fpol
from applications import header
if myid == main_node:
log_main.add("Compute var2D...")
km = 0
for i in range(number_of_proc):
if i == main_node :
for im in range(len(varList)):
tmpvol=fpol(varList[im], nx, nx,1)
tmpvol.write_image(os.path.join(current_output_dir, options.var2D), km)
km += 1
else:
nl = mpi_recv(1, MPI_INT, i, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
nl = int(nl[0])
for im in range(nl):
ave = recv_EMData(i, im+i+70000)
tmpvol=fpol(ave, nx, nx,1)
tmpvol.write_image(os.path.join(current_output_dir, options.var2D), km)
km += 1
else:
mpi_send(len(varList), 1, MPI_INT, main_node, SPARX_MPI_TAG_UNIVERSAL, MPI_COMM_WORLD)
for im in range(len(varList)):
send_EMData(varList[im], main_node, im+myid+70000)# What with the attributes??
mpi_barrier(MPI_COMM_WORLD)
if myid == main_node:
from applications import header
header(os.path.join(current_output_dir, options.var2D), params = 'xform.projection',fimport = os.path.join(current_output_dir, "params.txt"))
mpi_barrier(MPI_COMM_WORLD)
if options.var3D:
if myid == main_node: log_main.add("Reconstruct var3D ...")
t6 = time()
# radiusvar = options.radius
# if( radiusvar < 0 ): radiusvar = nx//2 -3
res = recons3d_4nn_MPI(myid, varList, symmetry = options.sym, npad=options.npad)
#res = recons3d_em_MPI(varList, vol_stack, options.iter, radiusvar, options.abs, True, options.sym, options.squ)
if myid == main_node:
from fundamentals import fpol
if current_decimate != 1.0: res = resample(res, 1./current_decimate)
res = fpol(res, nnxo, nnxo, nnxo)
set_pixel_size(res, 1.0)
res.write_image(os.path.join(current_output_dir, options.var3D))
log_main.add("%-70s: %s\n"%("The reconstructed var3D is saved as ", options.var3D))
log_main.add("Var3D reconstruction took %f12.1 [m]"%((time()-t6)/60.0))
log_main.add("Total computation time %f12.1 [m]"%((time()-t0)/60.0))
log_main.add("sx3dvariability finishes")
from mpi import mpi_finalize
mpi_finalize()
if RUNNING_UNDER_MPI: global_def.MPI = False
global_def.BATCH = False
def __new__(cls,filename,application,force_plot=False,force_2d=False,old=None):
file_type = Util.get_filename_ext(filename)
em_file_type = EMUtil.get_image_ext_type(file_type)
if not file_exists(filename): return None
if force_plot and force_2d:
# ok this sucks but it suffices for the time being
print("Error, the force_plot and force_2d options are mutually exclusive")
return None
if force_plot:
from .emplot2d import EMPlot2DWidget
if isinstance(old,EMPlot2DWidget): widget = old
else: widget = EMPlot2DWidget(application=application)
widget.set_data_from_file(filename)
return widget
if em_file_type != IMAGE_UNKNOWN or filename[:4] == "bdb:":
n = EMUtil.get_image_count(filename)
nx,ny,nz = gimme_image_dimensions3D(filename)
if n > 1 and nz == 1:
if force_2d:
a = EMData()
data=a.read_images(filename)
else:
data = None # This is like a flag - the ImageMXWidget only needs the file name
elif nz == 1:
data = [EMData(filename,0)]
else:
data = EMData()
data.read_image(filename,0,not force_2d) # This should be 3-D. We read the header-only here
data = [data]
if data != None and len(data) == 1: data = data[0]
if force_2d or isinstance(data,EMData) and data.get_zsize()==1:
if isinstance(data,list) or data.get_ysize() != 1:
from .emimage2d import EMImage2DWidget
if isinstance(old,EMImage2DWidget): widget = old
else: widget= EMImage2DWidget(application=application)
else:
from .emplot2d import EMPlot2DWidget
if isinstance(old,EMPlot2DWidget): widget = old
else: widget = EMPlot2DWidget(application=application)
widget.set_data_from_file(filename)
return widget
elif isinstance(data,EMData):
if isinstance(old,EMScene3D): widget = old
else: widget = EMScene3D()
# print n,data
for ii in range(n):
data=EMData(filename,ii)
datai = EMDataItem3D(data, transform=Transform())
widget.insertNewNode(os.path.basename(filename), datai, parentnode=widget)
isosurface = EMIsosurface(datai, transform=Transform())
widget.insertNewNode("Iso", isosurface, parentnode=datai)
return widget
elif data == None or isinstance(data,list):
from .emimagemx import EMImageMXWidget
if isinstance(old,EMImageMXWidget): widget = old
else: widget = EMImageMXWidget(application=application)
data = filename
else:
print(filename)
raise # weirdness, this should never happen
widget.set_data(data,filename)
return widget
else:
from .emplot2d import EMPlot2DWidget
if isinstance(old,EMPlot2DWidget): widget = old
else: widget = EMPlot2DWidget(application=application)
widget.set_data_from_file(filename)
return widget
def __new__(cls,data=None,old=None,app=None,force_2d=False,force_plot=False,filename="",replace=True):
"""This will create a new EMImage* object depending on the type of 'data'. If
old= is provided, and of the appropriate type, it will be used rather than creating
a new instance.
"""
if isinstance(data,EMData) and data.get_size()==0: raise RuntimeError("Can not display an EMData object that has no pixels")
from EMAN2 import remove_directories_from_name
if force_plot and force_2d:
# ok this sucks but it suffices for the time being
print("Error, the force_plot and force_2d options are mutually exclusive")
return None
if force_plot or (isinstance(data,EMData) and data.get_zsize()==1 and data.get_ysize()==1):
from .emplot2d import EMPlot2DWidget
if old:
if isinstance(old,EMPlot2DWidget) :
old.set_data(data,remove_directories_from_name(filename),replace)
return old
widget = EMPlot2DWidget(application=app)
widget.set_data(data,remove_directories_from_name(filename),replace)
return widget
elif force_2d or (isinstance(data,EMData) and data.get_zsize()==1):
from .emimage2d import EMImage2DWidget
if old:
if isinstance(old,EMImage2DWidget) :
old.set_data(data,filename)
return old
widget = EMImage2DWidget(application=app)
widget.set_data(data,filename)
return widget
elif isinstance(data,EMData):
if isinstance(old,EMScene3D): widget = old
else: widget = EMScene3D()
data = EMDataItem3D(data, transform=Transform())
#data.setSelectedItem(True)
isosurface = EMIsosurface(data, transform=Transform())
widget.insertNewNode(os.path.basename(filename), data, parentnode=widget)
widget.insertNewNode("Iso", isosurface, parentnode=data)
return widget
elif isinstance(data,list) and isinstance(data[0],EMData):
from .emimagemx import EMImageMXWidget
if old:
if isinstance(old,EMImageMXWidget) :
old.set_data(data,filename)
return old
widget = EMImageMXWidget(application=app)
widget.set_data(data,filename)
return widget
elif isinstance(data,list):
from .emplot3d import EMPlot3DWidgetNew
if (isinstance(data[0],list) or isinstance(data[0],tuple)) and len(data) > 2:
if old:
if isinstance(old,EMPlot3DWidgetNew) :
old.set_data(data,remove_directories_from_name(filename),replace)
return old
widget = EMPlot3DWidgetNew()
widget.set_data(data,remove_directories_from_name(filename),replace)
return widget
else:
from .emplot2d import EMPlot2DWidget
if old:
if isinstance(old,EMPlot2DWidget) :
old.set_data(data,remove_directories_from_name(filename),replace)
return old
widget = EMPlot2DWidget(application=app)
widget.set_data(data,remove_directories_from_name(filename),replace)
return widget
else:
raise Exception("data must be a single EMData object or a list of EMData objects")