def get_spotfinder(self, distl_params
): #following heuristics_base.register_frames() example
#application-specific adjustments to parameters
#XXX this should probably be a deep copy of parameters.
if distl_params.distl.res.inner != None:
distl_params.distl_lowres_limit = distl_params.distl.res.inner
if distl_params.distl.res.outer != None:
distl_params.force_method2_resolution_limit = distl_params.distl.res.outer
distl_params.distl_highres_limit = distl_params.distl.res.outer
distl_params.distl_force_binning = False
distl_params.distl_permit_binning = False
distl_params.wedgelimit = 1
distl_params.spotfinder_header_tests = False
#unusual location for min spot area tests...
from iotbx.detectors.context.config_detector import beam_center_convention_from_image_object
beam_center_convention_from_image_object(self, distl_params)
# end special min spot area treatment
from spotfinder.applications.practical_heuristics import heuristics_base
from spotfinder.diffraction.imagefiles import file_names
class empty:
pass
E = empty()
E.argv = ["Empty", self.filename]
names = file_names(E)
this_frame = names.frames()[0]
process_dictionary = dict(
twotheta="%f" % self.twotheta,
ybeam="%f" % self.beamy,
xbeam="%f" % self.beamx,
distance="%f" % self.distance,
wavelength="%f" % self.wavelength,
template=[
item.template for item in names.FN if item.number == this_frame
][0],
)
Spotfinder = heuristics_base(process_dictionary, distl_params)
Spotfinder.images[this_frame] = Spotfinder.oneImage(
this_frame, Spotfinder.pd, self)
Spotfinder.determine_maxcell(this_frame, Spotfinder.pd)
Spotfinder.images[this_frame]['spotoutput']['relpath'] = self.filename
from spotfinder.applications.stats_distl import pretty_image_stats
pretty_image_stats(Spotfinder, this_frame)
return Spotfinder, this_frame
def get_spotfinder(self,distl_params): #following heuristics_base.register_frames() example
#application-specific adjustments to parameters
#XXX this should probably be a deep copy of parameters.
if distl_params.distl.res.inner!=None:
distl_params.distl_lowres_limit = distl_params.distl.res.inner
if distl_params.distl.res.outer!=None:
distl_params.force_method2_resolution_limit = distl_params.distl.res.outer
distl_params.distl_highres_limit = distl_params.distl.res.outer
distl_params.distl_force_binning = False
distl_params.distl_permit_binning = False
distl_params.wedgelimit = 1
distl_params.spotfinder_header_tests = False
#unusual location for min spot area tests...
from iotbx.detectors.context.config_detector import beam_center_convention_from_image_object
beam_center_convention_from_image_object(self,distl_params)
# end special min spot area treatment
from spotfinder.applications.practical_heuristics import heuristics_base
from spotfinder.diffraction.imagefiles import file_names
class empty:pass
E = empty()
E.argv = ["Empty",self.filename]
names = file_names(E)
this_frame = names.frames()[0]
process_dictionary = dict(twotheta = "%f"%self.twotheta,
ybeam = "%f"%self.beamy,
xbeam = "%f"%self.beamx,
distance = "%f"%self.distance,
wavelength = "%f"%self.wavelength,
template = [item.template for item in names.FN if item.number==this_frame][0],
)
Spotfinder = heuristics_base(process_dictionary,distl_params)
Spotfinder.images[this_frame] = Spotfinder.oneImage(this_frame,
Spotfinder.pd, self)
Spotfinder.determine_maxcell(this_frame,Spotfinder.pd)
Spotfinder.images[this_frame]['spotoutput']['relpath']=self.filename
from spotfinder.applications.stats_distl import pretty_image_stats
pretty_image_stats(Spotfinder,this_frame)
return Spotfinder,this_frame
def do_POST(self):
T = Timer("do_POST")
parsed = urlparse(self.path)
qs = parse_qs(parsed.query)
expect = self.headers.getheaders("Expect")
if len(expect) >= 1:
if True in [item.find("100") >= 0 for item in expect]:
self.send_response(
100) # untested; has no apparent affect on libcurl
# Get arguments by reading body of request.
# We read this in chunks to avoid straining
# socket.read(); around the 10 or 15Mb mark, some platforms
# begin to have problems (bug #792570).
max_chunk_size = 10 * 1024 * 1024
size_remaining = int(self.headers["content-length"])
L = []
while size_remaining:
chunk_size = min(size_remaining, max_chunk_size)
L.append(self.rfile.read(chunk_size))
size_remaining -= len(L[-1])
data = ''.join(L)
post_data = StringIO(data)
# Parse the multipart/form-data
contentTypeHeader = self.headers.getheaders('content-type').pop()
# Extract the boundary parameter in the content-type header
headerParameters = contentTypeHeader.split(";")
boundary = headerParameters[1].split("=")
boundary = boundary[1].strip()
parts = cgi.parse_multipart(
post_data, {
"boundary":
boundary,
"content-disposition":
self.headers.getheaders('content-disposition')
})
print("*****************************")
for item in parts.keys():
if len(parts[item][0]) < 1000:
print(item, parts[item])
print("*****************************")
from iotbx.detectors.image_from_http_request import module_or_slice_from_http_request
imgobj = module_or_slice_from_http_request(parts)
imgobj.read()
print("Final image object:")
imgobj.show_header()
from spotfinder.diffraction.imagefiles import image_files, file_names
from spotfinder.diffraction.imagefiles import Spotspickle_argument_module
from spotfinder.applications.overall_procedure import spotfinder_no_pickle
class server_imagefiles(image_files):
def __init__(self):
pass
Files = server_imagefiles()
Files.filenames = file_names(
Spotspickle_argument_module(imgobj.filename))
Files.images = [imgobj]
S = spotfinder_no_pickle(Files, s3_passthru="-s3 4", spot_convention=0)
frames = Files.frames()
logfile = StringIO()
sys.stdout = logfile
from spotfinder.applications.stats_distl import pretty_image_stats, notes
for frame in frames:
#pretty_image_stats(S,frame)
#notes(S,frames[0])
module_image_stats(S, frame)
sys.stdout = sys.__stdout__
log = logfile.getvalue()
print(log)
ctype = 'text/plain'
self.send_response(200)
self.send_header("Content-type", ctype)
self.send_header("Content-length", len(log))
self.end_headers()
self.wfile.write(log)
self.opt_logging()
