def run_fresh(args):
import run_spotfinder
work_params = run_spotfinder.process_args(
args=args,
extra_phil_str="""\
number_of_shots = 10
.type = int
usable_partiality_threshold = 0.1
.type = float
scale_estimation_scale_max = 1e3
.type = float
min_number_of_spots_for_indexing = 16
.type = int
sample_random_seeds = None
.type = int
check_refine_uc_cr = False
.type = bool
index_and_integrate = False
.type = bool
show_refine_uc_cr = False
.type = bool
apply_random_reindexing = True
.type = bool
multiprocessing = False
.type = bool
refine_scales {
max_iterations = None
.type = int
finite_difference_eps = 1e-4
.type = float
}
pickle_image_models = False
.type = bool
write_image_models_to_mtz_files = False
.type = bool
""")
from create import build_i_calc
i_calc = build_i_calc(work_params)
i_calc.p1_anom.show_comprehensive_summary()
print
show_vm_info("After build_i_calc:")
if (work_params.sample_random_seeds is None):
process(work_params, i_calc)
else:
_ = work_params
base36_timestamp = _.base36_timestamp
for _.noise.random_seed in xrange(_.sample_random_seeds):
_.base36_timestamp = base36_timestamp + "_%04d" % _.noise.random_seed
process(_, i_calc)
show_vm_info("Final:")
def run_fresh(args):
from . import run_spotfinder
work_params = run_spotfinder.process_args(
args=args,
extra_phil_str="""\
number_of_shots = 10
.type = int
usable_partiality_threshold = 0.1
.type = float
scale_estimation_scale_max = 1e3
.type = float
min_number_of_spots_for_indexing = 16
.type = int
sample_random_seeds = None
.type = int
check_refine_uc_cr = False
.type = bool
index_and_integrate = False
.type = bool
show_refine_uc_cr = False
.type = bool
apply_random_reindexing = True
.type = bool
multiprocessing = False
.type = bool
refine_scales {
max_iterations = None
.type = int
finite_difference_eps = 1e-4
.type = float
}
pickle_image_models = False
.type = bool
write_image_models_to_mtz_files = False
.type = bool
""")
from .create import build_i_calc
i_calc = build_i_calc(work_params)
i_calc.p1_anom.show_comprehensive_summary()
print
show_vm_info("After build_i_calc:")
if (work_params.sample_random_seeds is None):
process(work_params, i_calc)
else:
_ = work_params
base36_timestamp = _.base36_timestamp
for _.noise.random_seed in xrange(_.sample_random_seeds):
_.base36_timestamp = base36_timestamp + "_%04d" % _.noise.random_seed
process(_, i_calc)
show_vm_info("Final:")
def run(args):
from rstbx.simage import run_spotfinder
work_params = run_spotfinder.process_args(args=args,
extra_phil_str="""\
saturation_level = 1.0
.type = float
""")
if (work_params.wavelength_2 is None):
work_params.wavelength_2 = work_params.wavelength
app = wx.App()
frame = wx.Frame(parent=None,
id=-1,
title="wx_simage",
pos=wx.DefaultPosition,
size=wx.Size(800, 600))
main_panel(parent=frame, work_params=work_params)
frame.Show()
app.MainLoop()
def run(args):
from rstbx.simage import run_spotfinder
work_params = run_spotfinder.process_args(
args=args, extra_phil_str="""\
saturation_level = 1.0
.type = float
""")
if (work_params.wavelength_2 is None):
work_params.wavelength_2 = work_params.wavelength
app = wx.App()
frame = wx.Frame(
parent=None,
id=-1,
title="wx_simage",
pos=wx.DefaultPosition,
size=wx.Size(800, 600))
main_panel(parent=frame, work_params=work_params)
frame.Show()
app.MainLoop()