xfel.command_line package¶
Submodules¶
xfel.command_line.auto_submit module¶
- xfel.command_line.auto_submit.match_runs(dir, use_in_progress)¶
- xfel.command_line.auto_submit.run(args)¶
xfel.command_line.brehm_diederichs module¶
- xfel.command_line.brehm_diederichs.run(args)¶
xfel.command_line.cbf_average module¶
- xfel.command_line.cbf_average.run(argv=None)¶
Compute mean, standard deviation, and maximum projection images from a set of CSPAD cbf images given on the command line.
@param argv Command line argument list @return @c 0 on successful termination, @c 1 on error, and @c 2
for command line syntax errors
xfel.command_line.cluster_42 module¶
xfel.command_line.cluster_intensity_statistics module¶
xfel.command_line.cluster_per_frame_wilson module¶
xfel.command_line.cluster_unit_cell module¶
xfel.command_line.cluster_visualise_orientations module¶
xfel.command_line.convert_gain_map module¶
- xfel.command_line.convert_gain_map.convert_2x2(data)¶
- xfel.command_line.convert_gain_map.convert_detector(raw_data, detector_format_version, address, optical_metrology_path=None)¶
- class xfel.command_line.convert_gain_map.fake_config¶
Bases:
object
- quadMask()¶
- roiMask(i)¶
- sections(i)¶
- class xfel.command_line.convert_gain_map.fake_cspad_ElementV2(data, quad)¶
Bases:
object
- data()¶
- quad()¶
- class xfel.command_line.convert_gain_map.fake_evt(data3d)¶
Bases:
object
- getCsPadQuads(address, env)¶
- getTime()¶
- xfel.command_line.convert_gain_map.fake_get_config(address, env)¶
- xfel.command_line.convert_gain_map.run(args)¶
xfel.command_line.convert_gain_map_cbf module¶
- xfel.command_line.convert_gain_map_cbf.convert_detector(raw_data)¶
- xfel.command_line.convert_gain_map_cbf.run(args)¶
xfel.command_line.cxi_apply_metrology module¶
xfel.command_line.cxi_cspad_pinwheel module¶
- xfel.command_line.cxi_cspad_pinwheel.run(argv=None)¶
xfel.command_line.cxi_diff module¶
- xfel.command_line.cxi_diff.run(args)¶
xfel.command_line.cxi_display_metrology module¶
xfel.command_line.cxi_generate_circular_gain_mask module¶
xfel.command_line.cxi_image2pickle module¶
xfel.command_line.cxi_index module¶
xfel.command_line.cxi_lsf module¶
- xfel.command_line.cxi_lsf.run(argv=None)¶
xfel.command_line.cxi_merge module¶
- xfel.command_line.cxi_merge.consistent_set_and_model(work_params, i_model=None)¶
- xfel.command_line.cxi_merge.get_boundaries_from_sensor_ID(sensor_ID, detector_version_phil=None, image_with_header=None)¶
- xfel.command_line.cxi_merge.get_observations(work_params)¶
- xfel.command_line.cxi_merge.load_result(file_name, ref_bravais_type, reference_cell, params, reindex_op, out, get_predictions_to_edge=False, image_info=None, exclude_CSPAD_sensor=None)¶
- xfel.command_line.cxi_merge.plot_overall_completeness(completeness)¶
- class xfel.command_line.cxi_merge.plot_statistics(prefix, unit_cell_statistics, reference_cell, correlations, min_corr, rejected_fractions, frame_d_min)¶
Bases:
object
Container for assorted histograms of frame statistics. The resolution bin plots are stored separately, since they can be displayed using the loggraph viewer.
- plot_statistics_histograms(figure, n_slots=20)¶
- plot_unit_cell_histograms(figure, a_values, b_values, c_values, n_slots=20, title='Distribution of unit cell edge lengths')¶
- show_all_pyplot(n_slots=20)¶
Display histograms using pyplot. For use in a wxPython GUI the figure should be created separately in a wx.Frame.
- class xfel.command_line.cxi_merge.resolution_bin(i_bin=None, d_range=None, d_min=None, redundancy_asu=None, redundancy_obs=None, redundancy_to_edge=None, absent=None, complete_tag=None, completeness=None, measurements=None, predictions=None, mean_I=None, mean_I_sigI=None, sigmaa=None)¶
Bases:
object
- xfel.command_line.cxi_merge.run(args)¶
- class xfel.command_line.cxi_merge.scaling_manager(miller_set, i_model, params, log=None)¶
Bases:
intensity_data
- add_frame(data)¶
Combine the scaled data from a frame with the current overall dataset. Also accepts None or null_data objects, when data are unusable but we want to record the file as processed.
- finalize_and_save_data()¶
Assemble a Miller array with the summed data, setting the unit cell to the consensus average if desired, and write to an MTZ file (including merged/non-anomalous data too).
- get_overall_correlation(sum_I)¶
Correlate the averaged intensities to the intensities from the reference data set. XXX The sum_I argument is really a kludge!
- get_plot_statistics()¶
- reset()¶
- scale_all(file_names)¶
- scale_frame(file_name, db_mgr)¶
The scale_frame() function populates a back end database with appropriately scaled intensities derived from a single frame. The mark0 scaling algorithm determines the scale factor by correlating the frame’s corrected intensities to those of a reference structure, while the mark1 algorithm applies no scaling at all. The scale_frame() function can be called either serially or via a multiprocessing map() function.
- @note This function must not modify any internal data or the
parallelization will not yield usable results!
@param file_name Path to integration pickle file @param db_mgr Back end database manager @return An intensity_data object
- scale_frame_detail(result, file_name, db_mgr, out)¶
- show_unit_cell_histograms()¶
- static single_reflection_histograms(obs, ISIGI)¶
- sum_intensities()¶
- class xfel.command_line.cxi_merge.scaling_result(**keyword_arguments)¶
Bases:
group_args
Container for any objects that might need to be saved for future use (e.g. in a GUI). Must be pickle-able!
- xfel.command_line.cxi_merge.show_overall_observations(obs, redundancy, summed_wt_I, summed_weight, ISIGI, n_bins=15, out=None, title=None, work_params=None, redundancy_to_edge=None)¶
- class xfel.command_line.cxi_merge.unit_cell_distribution¶
Bases:
object
Container for collecting unit cell edge length statistics - both for frames included in the final dataset, and those rejected due to poor correlation. (Frames with incompatible indexing solutions will not be included.)
- add_cell(unit_cell, rejected=False)¶
- add_cells(uc)¶
Addition operation for unit cell statistics.
- get_average_cell_dimensions()¶
- show_histograms(reference, out, n_slots=20)¶
xfel.command_line.cxi_optical2cbfheader module¶
xfel.command_line.cxi_pbs module¶
- xfel.command_line.cxi_pbs.run(argv=None)¶
xfel.command_line.cxi_pickle2cbf module¶
xfel.command_line.cxi_plotcv module¶
Main idea: go through the integration log files and grep out the difference vectors between observed and predicted spot positions. Plot these “correction vectors”, but do so separately for each ASIC tile, giving an independent check on whether a tile is positioned properly by the tile_translation parameters.
- xfel.command_line.cxi_plotcv.run(args)¶
xfel.command_line.cxi_psana module¶
- xfel.command_line.cxi_psana.run(args)¶
xfel.command_line.cxi_pyana module¶
- xfel.command_line.cxi_pyana.run(args)¶
xfel.command_line.cxi_spots module¶
xfel.command_line.cxi_stream_to_pickle module¶
Utility for converting stream files from CrystFEL version 0.5.3 to cctbx.xfel pickle files.
- xfel.command_line.cxi_stream_to_pickle.check_image(image)¶
- xfel.command_line.cxi_stream_to_pickle.crystfel_to_cctbx_coord_system(abasis, bbasis, cbasis)¶
CrystFEL is RHS with z down the beam, and y to the ceiling. CCTBX.Postrefine is RHS with z to the source, and y to the ceiling.
- xfel.command_line.cxi_stream_to_pickle.image_template()¶
- xfel.command_line.cxi_stream_to_pickle.make_int_pickle(img_dict, filename)¶
- xfel.command_line.cxi_stream_to_pickle.unit_cell_to_symetry_object(img_dict)¶
xfel.command_line.cxi_view module¶
xfel.command_line.cxi_xmerge module¶
- xfel.command_line.cxi_xmerge.run(args)¶
- class xfel.command_line.cxi_xmerge.xscaling_manager(miller_set, i_model, params, log=None)¶
Bases:
scaling_manager
- read_all_mysql()¶
- scale_all()¶
xfel.command_line.get_next_trial_id module¶
xfel.command_line.grid_index module¶
xfel.command_line.histogram_finalise module¶
xfel.command_line.list_db_metadata module¶
- xfel.command_line.list_db_metadata.run(args)¶
xfel.command_line.make_mask module¶
- xfel.command_line.make_mask.point_in_polygon(point, poly)¶
Determine if a point is inside a given polygon or not. Polygon is a list of (x,y) pairs. Code adapted from a dials polygon clipping test algorithm
- xfel.command_line.make_mask.point_inside_circle(x, y, center_x, center_y, radius)¶
Determine if a given point (x,y) is inside a circle whose center is at (center_x,center_y) with radius x.
- xfel.command_line.make_mask.run(argv=None)¶
xfel.command_line.metrology module¶
- xfel.command_line.metrology.get_phil(args)¶
- xfel.command_line.metrology.run(args)¶
- xfel.command_line.metrology.validate_phil(wp)¶
xfel.command_line.monitor_detectors module¶
xfel.command_line.monitor_trials module¶
xfel.command_line.overlay_spectra module¶
- xfel.command_line.overlay_spectra.estimate_signal_to_noise(x, y)¶
- xfel.command_line.overlay_spectra.full_width_half_max(x, y)¶
- xfel.command_line.overlay_spectra.run(args)¶
xfel.command_line.plot_to_subpixel module¶
- xfel.command_line.plot_to_subpixel.run(input=None)¶
xfel.command_line.postrefine module¶
- xfel.command_line.postrefine.determine_mean_I_mproc(frame_no, frame_files, iph)¶
- xfel.command_line.postrefine.postrefine_by_frame_mproc(frame_no, frame_files, iph, miller_array_ref)¶
- xfel.command_line.postrefine.read_input(args)¶
- xfel.command_line.postrefine.scale_frame_by_mean_I_mproc(frame_no, frame_files, iph, mean_of_mean_I)¶
xfel.command_line.print_pickle module¶
- xfel.command_line.print_pickle.generate_data_from_streams(args, verbose=False)¶
- xfel.command_line.print_pickle.generate_streams_from_path(tar_or_other)¶
- xfel.command_line.print_pickle.keywise_printout(data)¶
xfel.command_line.quadrants module¶
- xfel.command_line.quadrants.view_raw_image(path, *command_line, **kwargs)¶
xfel.command_line.radial_average module¶
- xfel.command_line.radial_average.apply_sub_pixel_metrology(tile, x, y, tcx, tcy, phil, handedness=0)¶
- xfel.command_line.radial_average.distance(a, b)¶
- xfel.command_line.radial_average.get_tile_center(tiles, tile)¶
- xfel.command_line.radial_average.get_tile_coords(tiles, tile)¶
returns x1, y1, x2, y2
- xfel.command_line.radial_average.get_tile_id(tiles, x, y)¶
- xfel.command_line.radial_average.run(args, source_data=None)¶
- xfel.command_line.radial_average.show_tiles(the_tiles, img, phil, bc, handedness=0)¶
xfel.command_line.smooth_spectrum module¶
- xfel.command_line.smooth_spectrum.estimate_signal_to_noise(x, y_noisy, y_smoothed, plot=False)¶
Estimate noise in spectra by subtracting a smoothed spectrum from the original noisy unsmoothed spectrum.
- See:
The extraction of signal to noise values in x-ray absorption spectroscopy A. J. Dent, P. C. Stephenson, and G. N. Greaves Rev. Sci. Instrum. 63, 856 (1992); https://doi.org/10.1063/1.1142627
- xfel.command_line.smooth_spectrum.fourier_filter(x, y, cutoff_frequency)¶
- xfel.command_line.smooth_spectrum.interpolate(x, y, half_window=10)¶
- xfel.command_line.smooth_spectrum.pyplot_label_axes(xlabel='Pixel column', ylabel='Intensity', fontsize=20)¶
- xfel.command_line.smooth_spectrum.run(args)¶
xfel.command_line.subtract_background module¶
- xfel.command_line.subtract_background.run(args)¶
- xfel.command_line.subtract_background.signal_to_noise_statistical(signal, background)¶
M.F. Koenig and J.T. Grant, Surface and Interface Analysis, Vol. 7, No.5, 1985, 217
- xfel.command_line.subtract_background.subtract_background(signal, background, plot=False)¶
xfel.command_line.trial_stats module¶
- xfel.command_line.trial_stats.run(args)¶
xfel.command_line.view_pixel_histograms module¶
- exception xfel.command_line.view_pixel_histograms.PixelFitError¶
Bases:
RuntimeError
- xfel.command_line.view_pixel_histograms.check_pixel_histogram_fit(hist, gaussians)¶
- xfel.command_line.view_pixel_histograms.hist_outline(hist)¶
- class xfel.command_line.view_pixel_histograms.pixel_histograms(histograms, estimated_gain=30)¶
Bases:
object
- fit_one_histogram(pixel, n_gaussians=2)¶
- pixels()¶
- plot(pixels=None, starting_pixel=None, fit_gaussians=True, n_gaussians=2, window_title=None, log_scale=False, save_image=False)¶
- plot_gaussians(pixel, n_gaussians=2, log_scale=False)¶
- plot_one_histogram(histogram, window_title=None, title=None, log_scale=False, normalise=False, save_image=False)¶
- single_peak_fit(hist, lower_threshold, upper_threshold, mean, zero_peak_gaussian=None)¶
- xfel.command_line.view_pixel_histograms.run(args)¶
- xfel.command_line.view_pixel_histograms.sliding_average(y, n=3)¶