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()