def test_reading(self):
doc = gemmi.cif.read(full_path('r5wkdsf.ent'))
rblock = gemmi.as_refln_blocks(doc)[0]
self.assertEqual(rblock.spacegroup.hm, 'C 1 2 1')
size = rblock.get_size_for_hkl()
fft_test(self, rblock, 'pdbx_FWT', 'pdbx_PHWT', size)
def test_scaling(self):
doc = gemmi.cif.read(full_path('r5wkdsf.ent'))
rblock = gemmi.as_refln_blocks(doc)[0]
fobs_data = rblock.get_value_sigma('F_meas_au', 'F_meas_sigma_au')
if numpy:
self.assertEqual(fobs_data.value_array.shape, (367, ))
# without mask
fc_data = rblock.get_f_phi('F_calc_au', 'phase_calc')
scaling = gemmi.Scaling(fc_data.unit_cell, fc_data.spacegroup)
scaling.prepare_points(fc_data, fobs_data)
scaling.fit_isotropic_b_approximately()
scaling.fit_parameters()
#print(scaling.k_overall, scaling.b_overall)
scaling.scale_data(fc_data)
def gemmi_sf2map(self, sf_mmcif_in, map_out, f_column, phi_column):
"""
converts input mmCIF file map coefficients to map
:param sf_mmcif_in: mmCIF structure factor input file
:param map_out: map output file
:param f_column: F column
:param phi_column: PHI column
:return: True if worked, False if failed
"""
st = gemmi.read_structure(self.coord_path)
fbox = st.calculate_fractional_box(margin=5)
if sf_mmcif_in:
if os.path.exists(sf_mmcif_in):
doc = gemmi.cif.read(sf_mmcif_in)
rblocks = gemmi.as_refln_blocks(doc)
if (
f_column in rblocks[0].column_labels()
and phi_column in rblocks[0].column_labels()
):
ccp4 = gemmi.Ccp4Map()
ccp4.grid = rblocks[0].transform_f_phi_to_map(f_column, phi_column)
ccp4.update_ccp4_header(2, True)
ccp4.set_extent(fbox)
ccp4.write_ccp4_map(map_out)
if os.path.exists(map_out):
return True
else:
logging.error("output map file {} missing".format(map_out))
else:
logging.error(
"{} {} columns not found in mmCIF {}".format(
f_column, phi_column, sf_mmcif_in
)
)
else:
logging.error("cannot find input file {}".format(sf_mmcif_in))
# command = "{} sf2map -f {} -p {} {} {}".format(gemmi_path, f_column, phi_column, mmcif_in, map_out)
# return self.run_command(command=command, output_file=map_out)
logging.error("converting {} to {} failed".format(sf_mmcif_in, map_out))
return False
import pandas
from matplotlib import pyplot
MTZ_PATH = 'tests/5wkd_phases.mtz.gz'
SFCIF_PATH = 'tests/r5wkdsf.ent'
# make DataFrame from MTZ file
mtz = gemmi.read_mtz_file(MTZ_PATH)
mtz_data = numpy.array(mtz, copy=False)
mtz_df = pandas.DataFrame(data=mtz_data, columns=mtz.column_labels())
# (optional) store Miller indices as integers
mtz_df = mtz_df.astype({label: 'int32' for label in 'HKL'})
# make DataFrame from mmCIF file
cif_doc = gemmi.cif.read(SFCIF_PATH)
rblock = gemmi.as_refln_blocks(cif_doc)[0]
cif_df = pandas.DataFrame(data=rblock.make_index_array(),
columns=['H', 'K', 'L'])
cif_df['F_meas_au'] = rblock.make_float_array('F_meas_au')
cif_df['d'] = rblock.make_d_array()
# merge DataFrames
df = pandas.merge(mtz_df, cif_df, on=['H', 'K', 'L'])
# plot FP from MTZ as a function of F_meas_au from mmCIF
pyplot.rc('font', size=8)
pyplot.figure(figsize=(2, 2))
pyplot.scatter(x=df['F_meas_au'], y=df['FP'], marker=',', s=1, linewidths=0)
pyplot.xlim(xmin=0)
pyplot.ylim(ymin=0)
pyplot.show()
#!/usr/bin/env python
# Read SF-mmCIF file and plot I/sigma as a function of 1/d^2.
import sys
from matplotlib import pyplot
import gemmi
for path in sys.argv[1:]:
doc = gemmi.cif.read(path)
rblock = gemmi.as_refln_blocks(doc)[0]
intensity = rblock.make_float_array('intensity_meas')
sigma = rblock.make_float_array('intensity_sigma')
x = rblock.make_1_d2_array()
y = intensity / sigma
pyplot.figure(figsize=(5,5))
pyplot.hexbin(x, y, gridsize=70, bins='log', cmap='gnuplot2')
pyplot.show()