def resolution_plots_and_stats(self):
self.merging_stats = merging_statistics.dataset_statistics(
self.intensities,
n_bins=self.params.resolution_bins,
cc_one_half_significance_level=self.params.
cc_half_significance_level,
eliminate_sys_absent=self.params.eliminate_sys_absent,
use_internal_variance=self.params.use_internal_variance,
assert_is_not_unique_set_under_symmetry=False,
)
intensities_anom = self.intensities.as_anomalous_array()
intensities_anom = intensities_anom.map_to_asu().customized_copy(
info=self.intensities.info())
self.merging_stats_anom = merging_statistics.dataset_statistics(
intensities_anom,
n_bins=self.params.resolution_bins,
anomalous=True,
cc_one_half_significance_level=self.params.
cc_half_significance_level,
eliminate_sys_absent=self.params.eliminate_sys_absent,
use_internal_variance=self.params.use_internal_variance,
assert_is_not_unique_set_under_symmetry=False,
)
is_centric = self.intensities.space_group().is_centric()
plotter = ResolutionPlotsAndStats(self.merging_stats,
self.merging_stats_anom, is_centric)
d = OrderedDict()
d.update(plotter.cc_one_half_plot(method=self.params.cc_half_method))
d.update(plotter.i_over_sig_i_plot())
d.update(plotter.completeness_plot())
d.update(plotter.multiplicity_vs_resolution_plot())
overall_stats = plotter.overall_statistics_table(
self.params.cc_half_method)
merging_stats = plotter.merging_statistics_table(
self.params.cc_half_method)
return overall_stats, merging_stats, d
def test_ResolutionPlotsAndStats(iobs):
i_obs_anom = iobs.as_anomalous_array()
iobs_anom = i_obs_anom.map_to_asu().customized_copy(info=iobs.info())
n_bins = 2
result = dataset_statistics(iobs,
assert_is_not_unique_set_under_symmetry=False,
n_bins=n_bins)
anom_result = dataset_statistics(
iobs_anom,
assert_is_not_unique_set_under_symmetry=False,
anomalous=True,
n_bins=n_bins,
)
plotter = ResolutionPlotsAndStats(result, anom_result)
assert plotter.d_star_sq_ticktext == [
"1.26", "1.19", "1.13", "1.08", "1.04"
]
assert plotter.d_star_sq_tickvals == pytest.approx(
[0.6319, 0.7055, 0.7792, 0.8528, 0.9264], 1e-4)
tables = plotter.statistics_tables()
assert len(tables) == 2 # overall and per resolution
# test plots individually
d = plotter.cc_one_half_plot()
assert len(d["cc_one_half"]["data"]) == 4
assert all(len(x["x"]) == n_bins for x in d["cc_one_half"]["data"])
d = plotter.i_over_sig_i_plot()
assert len(d["i_over_sig_i"]["data"]) == 1
assert len(d["i_over_sig_i"]["data"][0]["y"]) == n_bins
d = plotter.r_pim_plot()
assert len(d["r_pim"]["data"]) == 1
assert len(d["r_pim"]["data"][0]["y"]) == n_bins
d = plotter.completeness_plot()
assert len(d["completeness"]["data"]) == 2
assert len(d["completeness"]["data"][0]["y"]) == n_bins
d = plotter.multiplicity_vs_resolution_plot()
assert len(d["multiplicity_vs_resolution"]["data"]) == 2
assert len(d["multiplicity_vs_resolution"]["data"][0]["y"]) == n_bins
# now try centric options and sigma tau for cc_one_half
plotter = ResolutionPlotsAndStats(result, anom_result, is_centric=True)
d = plotter.cc_one_half_plot(method="sigma_tau")
assert len(d["cc_one_half"]["data"]) == 4
assert all(len(x["x"]) == n_bins for x in d["cc_one_half"]["data"][:2])
assert d["cc_one_half"]["data"][2] == {} # no anomalous plots
assert d["cc_one_half"]["data"][3] == {} # no anomalous plots
d = plotter.completeness_plot()
assert len(d["completeness"]["data"]) == 2
assert len(d["completeness"]["data"][0]["y"]) == n_bins
assert d["completeness"]["data"][1] == {}
d = plotter.multiplicity_vs_resolution_plot()
assert len(d["multiplicity_vs_resolution"]["data"]) == 2
assert len(d["multiplicity_vs_resolution"]["data"][0]["y"]) == n_bins
assert d["multiplicity_vs_resolution"]["data"][1] == {}
plots = plotter.make_all_plots()
assert list(plots.keys()) == [
"cc_one_half",
"i_over_sig_i",
"completeness",
"multiplicity_vs_resolution",
"r_pim",
]
for plot in plots.values():
assert plot["layout"]["xaxis"][
"ticktext"] == plotter.d_star_sq_ticktext
assert plot["layout"]["xaxis"][
"tickvals"] == plotter.d_star_sq_tickvals
def test_ResolutionPlotsAndStats(iobs):
i_obs_anom = iobs.as_anomalous_array()
iobs_anom = i_obs_anom.map_to_asu().customized_copy(info=iobs.info())
n_bins = 2
result = dataset_statistics(
iobs, assert_is_not_unique_set_under_symmetry=False, n_bins=n_bins
)
anom_result = dataset_statistics(
iobs_anom,
assert_is_not_unique_set_under_symmetry=False,
anomalous=True,
n_bins=n_bins,
)
plotter = ResolutionPlotsAndStats(result, anom_result)
assert plotter.d_star_sq_ticktext == ["1.74", "1.53", "1.38", "1.27", "1.18"]
assert plotter.d_star_sq_tickvals == pytest.approx(
[
0.32984033277048164,
0.42706274943714834,
0.524285166103815,
0.6215075827704818,
0.7187299994371485,
],
1e-4,
)
tables = plotter.statistics_tables()
assert len(tables) == 2 # overall and per resolution
# test plots individually
d = plotter.cc_one_half_plot()
assert len(d["cc_one_half"]["data"]) == 6
assert all(len(x["x"]) == n_bins for x in d["cc_one_half"]["data"][:4])
d["cc_one_half"]["data"][0]["x"] == [
0.5 * (uctbx.d_as_d_star_sq(b.d_max) + uctbx.d_as_d_star_sq(b.d_min))
for b in result.bins
]
d = plotter.i_over_sig_i_plot()
assert len(d["i_over_sig_i"]["data"]) == 1
assert len(d["i_over_sig_i"]["data"][0]["y"]) == n_bins
d = plotter.r_pim_plot()
assert len(d["r_pim"]["data"]) == 1
assert len(d["r_pim"]["data"][0]["y"]) == n_bins
d = plotter.completeness_plot()
assert len(d["completeness"]["data"]) == 2
assert len(d["completeness"]["data"][0]["y"]) == n_bins
d = plotter.multiplicity_vs_resolution_plot()
assert len(d["multiplicity_vs_resolution"]["data"]) == 2
assert len(d["multiplicity_vs_resolution"]["data"][0]["y"]) == n_bins
# now try centric options and sigma tau for cc_one_half
plotter = ResolutionPlotsAndStats(result, anom_result, is_centric=True)
d = plotter.cc_one_half_plot(method="sigma_tau")
assert len(d["cc_one_half"]["data"]) == 6
assert all(len(x["x"]) == n_bins for x in d["cc_one_half"]["data"][:2])
assert d["cc_one_half"]["data"][2] == {} # no anomalous plots
assert d["cc_one_half"]["data"][3] == {} # no anomalous plots
assert d["cc_one_half"]["data"][4] == {} # no cc_fit
assert d["cc_one_half"]["data"][5] == {} # no d_min
d = plotter.completeness_plot()
assert len(d["completeness"]["data"]) == 2
assert len(d["completeness"]["data"][0]["y"]) == n_bins
assert d["completeness"]["data"][1] == {}
d = plotter.multiplicity_vs_resolution_plot()
assert len(d["multiplicity_vs_resolution"]["data"]) == 2
assert len(d["multiplicity_vs_resolution"]["data"][0]["y"]) == n_bins
assert d["multiplicity_vs_resolution"]["data"][1] == {}
plots = plotter.make_all_plots()
assert list(plots.keys()) == [
"cc_one_half",
"i_over_sig_i",
"completeness",
"multiplicity_vs_resolution",
"r_pim",
]
for plot in plots.values():
assert plot["layout"]["xaxis"]["ticktext"] == plotter.d_star_sq_ticktext
assert plot["layout"]["xaxis"]["tickvals"] == plotter.d_star_sq_tickvals