def read_xmap(mapin=''):
log_string = '\n >> clipper_tools: io.maps.read_xmap'
log_string += '\n mapin: %s' % mapin
xml_root = etree.Element('input_file')
if mapin is not '':
map_file = clipper.CCP4MAPfile()
map_file.open_read(mapin)
map_data = clipper.Xmap_double()
map_file.import_xmap_double(map_data)
map_file.close_read()
log_string += '\n << read_xmap has finished\n'
xml_root.attrib['name'] = mapin
xml_root.attrib['type'] = 'xmap'
xml_root.attrib['ok'] = 'yes'
return log_string, xml_root, map_data
def read_xmap(mapin=""):
log_string = "\n >> clipper_tools: io.maps.read_xmap"
log_string += "\n mapin: %s" % mapin
xml_root = etree.Element('input_file')
if mapin is not "":
map_file = clipper.CCP4MAPfile()
map_file.open_read(mapin)
map_data = clipper.Xmap_double()
map_file.import_xmap_double(map_data)
map_file.close_read()
log_string += "\n << read_xmap has finished\n"
xml_root.attrib['name'] = mapin
xml_root.attrib['type'] = "xmap"
xml_root.attrib['ok'] = "yes"
return log_string, xml_root, map_data
def prepare_map(mapin='', resol=8.0, callback=_callbacks.interactive_flush):
"""Reads EM map, sets origin to 0, pads cell and computes finely-sampled structure factors
Parameters:
mapin -- a string path to a map that will be read into a clipper.NXmap_float object
resol -- estimated resolution (float)
callback -- a function that takes care of log string and xml flushing
Returns:
a plain text log string, an XML etree and a clipper.HKL_data_F_phi_float object"""
def determine_extent(numpy_in, tolerance):
"""Reads numpy array, determines the extent of the electron density
Parameters:
numpy_in -- a numpy array containing grid points
tolerance -- number of points in a plane with value greater than 1 sigma
Returns:
a vector of grid indices: (min_u, max_u, min_v, max_v, min_w, max_w)"""
log_string = ''
min = clipper.Coord_orth()
max = clipper.Coord_orth()
map_mean = numpy.mean(map_numpy)
map_std = numpy.std(map_numpy)
mask = map_numpy > map_mean + map_std
sum_u = sum(sum(mask))
sum_w = sum(sum(numpy.transpose(mask)))
sum_v = sum(numpy.transpose(sum(mask)))
log_string += '\n >> dumping 1D summaries of the map\'s content:\n\n >> U:\n %s\n' % sum_u
log_string += '\n >> V:\n %s\n' % sum_v
log_string += '\n >> W:\n %s\n' % sum_w
point_list = []
for idx_u, val_u in enumerate(sum_u):
if val_u > tolerance:
point_list.append(idx_u)
min_u = point_list[0]
max_u = point_list[-1]
log_string += '\n >> First meaningful U: %i ; Last meaningful U: %i' % (
min_u, max_u)
point_list = []
for idx_v, val_v in enumerate(sum_v):
if val_v > tolerance:
point_list.append(idx_v)
min_v = point_list[0]
max_v = point_list[-1]
log_string += '\n >> First meaningful V: %i ; Last meaningful V: %i' % (
min_v, max_v)
point_list = []
for idx_w, val_w in enumerate(sum_w):
if val_w > tolerance:
point_list.append(idx_w)
min_w = point_list[0]
max_w = point_list[-1]
log_string += '\n >> First meaningful W: %i ; Last meaningful W: %i\n' % (
min_w, max_w)
extent = [min_u, max_u, min_v, max_v, min_w, max_w]
return extent, log_string
################# end determine_extent ################
############### main function ################
# create log string so console-based apps get some feedback
log_string = '\n >> clipper_tools: mr_from_em.prepare_map'
log_string += '\n mapin: %s' % mapin
log_string += '\n resol: %s' % resol
# create XML tree, to be merged in a global structured results file
xml_root = etree.Element('structure_factors')
xml_root.attrib['mapin'] = mapin
xml_root.attrib['resol'] = str(resol)
callback(log_string, xml_root)
phaser_params = {}
nxmap = clipper.NXmap_double()
xmap = clipper.Xmap_double()
map_file = clipper.CCP4MAPfile()
sg = clipper.Spacegroup.p1()
resol *= 0.9
resolution = clipper.Resolution(resol)
# nothing in, nothing out
if mapin == '':
return log_string, xml_root, None
# read the cryoEM map into nxmap, get map data irrespective of origin
map_file.open_read(mapin)
map_file.import_nxmap_double(nxmap)
map_file.close_read()
log_string += '\n >> file %s has been read as nxmap' % mapin
callback(log_string, xml_root)
# read the cryoEM map into xmap to get cell dimensions, etc.
map_file.open_read(mapin)
map_file.import_xmap_double(xmap)
map_file.close_read()
log_string += '\n >> file %s has been read as xmap' % mapin
callback(log_string, xml_root)
log_string += '\n >> cell parameters: %s' % xmap.cell().format()
log_string += '\n original translation: %s' % nxmap.operator_orth_grid(
).trn()
# put map content in a numpy data structure
map_numpy = numpy.zeros(
(nxmap.grid().nu(), nxmap.grid().nv(), nxmap.grid().nw()),
dtype='double')
log_string += '\n >> exporting a numpy array of %i x %i x %i grid points' \
% (nxmap.grid().nu(), nxmap.grid().nv(), nxmap.grid().nw())
callback(log_string, xml_root)
data_points = nxmap.export_numpy(map_numpy)
log_string += '\n >> %i data points have been exported' % data_points
callback(log_string, xml_root)
map_mean = numpy.mean(map_numpy)
map_stdv = numpy.std(map_numpy)
log_string += '\n >> map mean (stdev): %.4f (%.4f)' % (map_mean, map_stdv)
# compute the extent
extent, temp_log = determine_extent(map_numpy, 30)
log_string += temp_log
extent_list = [
extent[1] - extent[0], extent[3] - extent[2], extent[5] - extent[4]
]
max_extent = max(extent_list)
# create padded xmap and import numpy array
origin_trans = clipper.vec3_double(
extent[0] + ((extent[1] - extent[0]) / 2),
extent[2] + ((extent[3] - extent[2]) / 2),
extent[4] + ((extent[5] - extent[4]) / 2))
large_a = (xmap.cell().a() *
(max_extent + xmap.grid_asu().nu())) / xmap.grid_asu().nu()
large_b = (xmap.cell().b() *
(max_extent + xmap.grid_asu().nv())) / xmap.grid_asu().nv()
large_c = (xmap.cell().c() *
(max_extent + xmap.grid_asu().nw())) / xmap.grid_asu().nw()
cell_desc = clipper.Cell_descr(large_a, large_b, large_c, \
xmap.cell().alpha(), xmap.cell().beta(), xmap.cell().gamma())
large_p1_cell = clipper.Cell(cell_desc)
large_grid_sampling = clipper.Grid_sampling(
max_extent + xmap.grid_asu().nu(), max_extent + xmap.grid_asu().nv(),
max_extent + xmap.grid_asu().nw())
large_xmap = clipper.Xmap_double(sg, large_p1_cell, large_grid_sampling)
log_string += '\n >> new grid: nu=%i nv=%i nw=%i' % (large_xmap.grid_asu(
).nu(), large_xmap.grid_asu().nv(), large_xmap.grid_asu().nw())
log_string += '\n >> putting map into a large p1 cell...'
log_string += '\n >> new cell parameters: %s' % large_p1_cell.format()
callback(log_string, xml_root)
large_xmap.import_numpy(map_numpy)
# dump map to disk
map_file = clipper.CCP4MAPfile()
map_file.open_write('mapout_padded.mrc')
map_file.export_xmap_double(large_xmap)
map_file.close_write()
log_string += '\n >> map file mapout_padded.mrc written to disk'
callback(log_string, xml_root)
# import it back to nxmap so we can trivially shift the origin
map_file.open_read('mapout_padded.mrc')
map_file.import_nxmap_double(nxmap)
map_file.close_read()
log_string += '\n >> file mapout_padded.mrc has been read back as nxmap'
callback(log_string, xml_root)
# now shift the origin
rtop_zero = clipper.RTop_double(nxmap.operator_orth_grid().rot(),
origin_trans)
log_string += '\n >> moving origin...'
log_string += '\n original translation: %s new origin: %s' % (
nxmap.operator_orth_grid().trn(), rtop_zero.trn())
callback(log_string, xml_root)
nxmap_zero = clipper.NXmap_double(nxmap.grid(), rtop_zero)
nxmap_zero.import_numpy(map_numpy)
# dump map to disk
map_file.open_write('mapout_padded_zero.mrc')
map_file.export_nxmap_double(nxmap_zero)
map_file.close_write()
log_string += '\n >> map file mapout_padded_zero.mrc written to disk'
callback(log_string, xml_root)
# read it back to an xmap so we can fft-it
new_xmap = clipper.Xmap_double()
map_file.open_read('mapout_padded_zero.mrc')
map_file.import_xmap_double(new_xmap)
map_file.close_read()
log_string += '\n >> map file mapout_padded_zero.mrc read back as xmap'
callback(log_string, xml_root)
# create HKL_info using user-supplied resolution parameter
hkl_info = clipper.HKL_info(sg, large_p1_cell, resolution, True)
# fft the map
f_phi = clipper.HKL_data_F_phi_float(hkl_info, large_p1_cell)
log_string += '\n >> now computing map coefficients to %0.1f A resolution...' % resol
callback(log_string, xml_root)
new_xmap.fft_to(f_phi)
log_string += '\n >> writing map coefficients to MTZ file mapout_padded_zero.mtz'
callback(log_string, xml_root)
# setup an MTZ file so we can export our map coefficients
mtzout = clipper.CCP4MTZfile()
mtzout.open_write('mapout_padded_zero.mtz')
mtzout.export_hkl_info(f_phi.hkl_info())
mtzout.export_hkl_data(f_phi, '*/*/[F, PHI]')
mtzout.close_write()
log_string += '\n >> all done'
callback(log_string, xml_root)
return log_string, xml_root, f_phi, phaser_params
def cut_by_model(mapin="",
pdbin="",
ipradius=1.5,
ipresol=8.0,
ipbfact=0.0,
callback=callbacks.interactive_flush):
xmap = clipper.Xmap_double()
sg = clipper.Spacegroup.p1()
resolution = clipper.Resolution(ipresol)
# create log string so console-based apps get some feedback
log_string = "\n >> clipper_tools: em.cut_density.cut_by_model"
log_string += "\n mapin: %s" % mapin
log_string += "\n pdbin: %s" % pdbin
log_string += "\n bfact: %s" % ipbfact
log_string += "\n resol: %s" % ipresol
log_string += "\n radius: %s" % ipradius
# create XML tree, to be merged in a global structured results file
xml_root = etree.Element('program')
xml_root.attrib['name'] = 'cut_by_model'
xml_root.attrib['user'] = getpass.getuser()
xml_root.attrib['date'] = time.strftime("%c")
params = etree.SubElement(xml_root, 'parameters')
params.attrib['mapin'] = mapin
params.attrib['pdbin'] = pdbin
params.attrib['b_factor'] = str(ipbfact)
params.attrib['resolution'] = str(ipresol)
params.attrib['mask_radius'] = str(ipradius)
callback(log_string, xml_root)
# nothing in, nothing out
if mapin == "" or pdbin == "":
return log_string, xml_root, None
# read the input atomic model
from clipper_tools.io.molecules import read_pdb
log_string_sub, xml_sub, mmol = read_pdb(pdbin)
log_string += log_string_sub
xml_root.append(xml_sub)
callback(log_string, xml_root)
# read the cryoEM map into xmap to get cell dimensions, etc.
from clipper_tools.io.maps import read_xmap
log_sub, xml_sub, xmap = read_xmap(mapin)
log_string += log_sub
xml_root.append(xml_sub)
callback(log_string, xml_root)
grid_sampling = clipper.Grid_sampling(xmap.grid_asu().nu(),
xmap.grid_asu().nv(),
xmap.grid_asu().nw())
log_string += "\n >> cell parameters: %s" % xmap.cell().format()
callback(log_string, xml_root)
# put map content in a numpy data structure
import numpy
map_numpy = numpy.zeros(
(xmap.grid_asu().nu(), xmap.grid_asu().nv(), xmap.grid_asu().nw()),
dtype='double')
log_string += "\n >> exporting a numpy array of %i x %i x %i grid points" \
% (xmap.grid_asu().nu(), xmap.grid_asu().nv(), xmap.grid_asu().nw())
data_points = xmap.export_numpy(map_numpy)
callback(log_string, xml_root)
atom_list = mmol.model().atom_list()
mask = clipper.Xmap_float(xmap.spacegroup(), xmap.cell(), grid_sampling)
masker = clipper.EDcalc_mask_float(ipradius)
masker.compute(mask, atom_list)
mask_matrix = numpy.zeros(
(xmap.grid_asu().nu(), xmap.grid_asu().nv(), xmap.grid_asu().nw()),
dtype='double')
mask_points = mask.export_numpy(mask_matrix)
log_string += "\n >> the original map has %i points and the computed mask has %i points" % (
data_points, mask_points)
callback(log_string, xml_root)
masked_array = map_numpy * mask_matrix
log_string += "\n >> non-zero values: original= %i ; mask=%i ; product=%i" % (
numpy.count_nonzero(map_numpy), numpy.count_nonzero(mask_matrix),
numpy.count_nonzero(masked_array))
xmap.import_numpy(masked_array)
# create HKL_info using user-supplied resolution parameter
hkl_info = clipper.HKL_info(xmap.spacegroup(), xmap.cell(), resolution,
True)
# fft the map
f_phi = clipper.HKL_data_F_phi_float(hkl_info, xmap.cell())
log_string += "\n >> now computing map coefficients to %0.1f A resolution..." % ipresol
callback(log_string, xml_root)
xmap.fft_to(f_phi)
log_string += "\n >> writing map coefficients to MTZ file mapout_cut_density.mtz"
callback(log_string, xml_root)
if ipbfact != 0.0:
f_phi.compute_scale_u_iso_fphi(1.0, clipper.Util.b2u(-ipbfact), f_phi)
log_string += "\n >> and applying B factor correction - using %3.2f\n" % ipbfact
# setup an MTZ file so we can export our map coefficients
from clipper_tools.io.map_coefficients import write_to_mtz
log_sub, xml_sub = write_to_mtz(f_phi, "mapout_cut_density.mtz")
log_string += log_sub
xml_root.append(xml_sub)
log_string += "\n >> all done"
xml_root.attrib['ok'] = 'yes'
callback(log_string, xml_root)
from clipper_tools.callbacks import offline_flush
offline_flush(log_string, xml_root)