Esempio n. 1
0
def run():
    if os.path.exists("xia2-working.phil"):
        sys.argv.append("xia2-working.phil")
    try:
        check_environment()
    except Exception as e:
        traceback.print_exc(file=open("xia2.error", "w"))
        Chatter.write('Status: error "%s"' % str(e))

    # print the version
    Chatter.write(Version)
    Citations.cite("xia2")

    start_time = time.time()

    assert os.path.exists("xia2.json")
    from xia2.Schema.XProject import XProject

    xinfo = XProject.from_json(filename="xia2.json")

    crystals = xinfo.get_crystals()
    for crystal_id, crystal in crystals.iteritems():
        # cwd = os.path.abspath(os.curdir)
        from libtbx import Auto

        scale_dir = PhilIndex.params.xia2.settings.scale.directory
        if scale_dir is Auto:
            scale_dir = "scale"
            i = 0
            while os.path.exists(os.path.join(crystal.get_name(), scale_dir)):
                i += 1
                scale_dir = "scale%i" % i
            PhilIndex.params.xia2.settings.scale.directory = scale_dir
        working_directory = Environment.generate_directory(
            [crystal.get_name(), scale_dir])
        # os.chdir(working_directory)

        crystals[crystal_id]._scaler = None  # reset scaler

        scaler = crystal._get_scaler()
        Chatter.write(xinfo.get_output())
        crystal.serialize()

    duration = time.time() - start_time

    # write out the time taken in a human readable way
    Chatter.write("Processing took %s" %
                  time.strftime("%Hh %Mm %Ss", time.gmtime(duration)))

    # delete all of the temporary mtz files...
    cleanup()

    write_citations()

    xinfo.as_json(filename="xia2.json")

    Environment.cleanup()
Esempio n. 2
0
def xia2_main(stop_after=None):
    '''Actually process something...'''
    Citations.cite('xia2')

    # print versions of related software
    Chatter.write(dials_version())

    ccp4_version = get_ccp4_version()
    if ccp4_version is not None:
        Chatter.write('CCP4 %s' % ccp4_version)

    start_time = time.time()

    CommandLine = get_command_line()
    start_dir = Flags.get_starting_directory()

    # check that something useful has been assigned for processing...
    xtals = CommandLine.get_xinfo().get_crystals()

    no_images = True

    for name in xtals.keys():
        xtal = xtals[name]

        if not xtal.get_all_image_names():

            Chatter.write('-----------------------------------' + \
                          '-' * len(name))
            Chatter.write('| No images assigned for crystal %s |' % name)
            Chatter.write('-----------------------------------' + '-' \
                          * len(name))
        else:
            no_images = False

    args = []

    from xia2.Handlers.Phil import PhilIndex
    params = PhilIndex.get_python_object()
    mp_params = params.xia2.settings.multiprocessing
    njob = mp_params.njob

    from libtbx import group_args

    xinfo = CommandLine.get_xinfo()

    if os.path.exists('xia2.json'):
        from xia2.Schema.XProject import XProject
        xinfo_new = xinfo
        xinfo = XProject.from_json(filename='xia2.json')

        crystals = xinfo.get_crystals()
        crystals_new = xinfo_new.get_crystals()
        for crystal_id in crystals_new.keys():
            if crystal_id not in crystals:
                crystals[crystal_id] = crystals_new[crystal_id]
                continue
            crystals[crystal_id]._scaler = None  # reset scaler
            for wavelength_id in crystals_new[crystal_id].get_wavelength_names(
            ):
                wavelength_new = crystals_new[crystal_id].get_xwavelength(
                    wavelength_id)
                if wavelength_id not in crystals[
                        crystal_id].get_wavelength_names():
                    crystals[crystal_id].add_wavelength(
                        crystals_new[crystal_id].get_xwavelength(
                            wavelength_new))
                    continue
                wavelength = crystals[crystal_id].get_xwavelength(
                    wavelength_id)
                sweeps_new = wavelength_new.get_sweeps()
                sweeps = wavelength.get_sweeps()
                sweep_names = [s.get_name() for s in sweeps]
                sweep_keys = [(s.get_directory(), s.get_template(),
                               s.get_image_range()) for s in sweeps]
                for sweep in sweeps_new:
                    if ((sweep.get_directory(), sweep.get_template(),
                         sweep.get_image_range()) not in sweep_keys):
                        if sweep.get_name() in sweep_names:
                            i = 1
                            while 'SWEEEP%i' % i in sweep_names:
                                i += 1
                            sweep._name = 'SWEEP%i' % i
                            break
                        wavelength.add_sweep(
                            name=sweep.get_name(),
                            sample=sweep.get_xsample(),
                            directory=sweep.get_directory(),
                            image=sweep.get_image(),
                            beam=sweep.get_beam_centre(),
                            reversephi=sweep.get_reversephi(),
                            distance=sweep.get_distance(),
                            gain=sweep.get_gain(),
                            dmin=sweep.get_resolution_high(),
                            dmax=sweep.get_resolution_low(),
                            polarization=sweep.get_polarization(),
                            frames_to_process=sweep.get_frames_to_process(),
                            user_lattice=sweep.get_user_lattice(),
                            user_cell=sweep.get_user_cell(),
                            epoch=sweep._epoch,
                            ice=sweep._ice,
                            excluded_regions=sweep._excluded_regions,
                        )
                        sweep_names.append(sweep.get_name())

    crystals = xinfo.get_crystals()

    failover = params.xia2.settings.failover

    if mp_params.mode == 'parallel' and njob > 1:
        driver_type = mp_params.type
        command_line_args = CommandLine.get_argv()[1:]
        for crystal_id in crystals.keys():
            for wavelength_id in crystals[crystal_id].get_wavelength_names():
                wavelength = crystals[crystal_id].get_xwavelength(
                    wavelength_id)
                sweeps = wavelength.get_sweeps()
                for sweep in sweeps:
                    sweep._get_indexer()
                    sweep._get_refiner()
                    sweep._get_integrater()
                    args.append((group_args(
                        driver_type=driver_type,
                        stop_after=stop_after,
                        failover=failover,
                        command_line_args=command_line_args,
                        nproc=mp_params.nproc,
                        crystal_id=crystal_id,
                        wavelength_id=wavelength_id,
                        sweep_id=sweep.get_name(),
                    ), ))

        from xia2.Driver.DriverFactory import DriverFactory
        default_driver_type = DriverFactory.get_driver_type()

        # run every nth job on the current computer (no need to submit to qsub)
        for i_job, arg in enumerate(args):
            if (i_job % njob) == 0:
                arg[0].driver_type = default_driver_type

        if mp_params.type == "qsub":
            method = "sge"
        else:
            method = "multiprocessing"
        nproc = mp_params.nproc
        qsub_command = mp_params.qsub_command
        if not qsub_command:
            qsub_command = 'qsub'
        qsub_command = '%s -V -cwd -pe smp %d' % (qsub_command, nproc)

        from libtbx import easy_mp
        results = easy_mp.parallel_map(
            process_one_sweep,
            args,
            processes=njob,
            #method=method,
            method="multiprocessing",
            qsub_command=qsub_command,
            preserve_order=True,
            preserve_exception_message=True)

        # Hack to update sweep with the serialized indexers/refiners/integraters
        i_sweep = 0
        for crystal_id in crystals.keys():
            for wavelength_id in crystals[crystal_id].get_wavelength_names():
                wavelength = crystals[crystal_id].get_xwavelength(
                    wavelength_id)
                remove_sweeps = []
                sweeps = wavelength.get_sweeps()
                for sweep in sweeps:
                    success, output, xsweep_dict = results[i_sweep]
                    if output is not None:
                        Chatter.write(output)
                    if not success:
                        Chatter.write('Sweep failed: removing %s' %
                                      sweep.get_name())
                        remove_sweeps.append(sweep)
                    else:
                        assert xsweep_dict is not None
                        Chatter.write('Loading sweep: %s' % sweep.get_name())
                        from xia2.Schema.XSweep import XSweep
                        new_sweep = XSweep.from_dict(xsweep_dict)
                        sweep._indexer = new_sweep._indexer
                        sweep._refiner = new_sweep._refiner
                        sweep._integrater = new_sweep._integrater
                    i_sweep += 1
                for sweep in remove_sweeps:
                    wavelength.remove_sweep(sweep)
                    sample = sweep.get_xsample()
                    sample.remove_sweep(sweep)

    else:
        for crystal_id in crystals.keys():
            for wavelength_id in crystals[crystal_id].get_wavelength_names():
                wavelength = crystals[crystal_id].get_xwavelength(
                    wavelength_id)
                remove_sweeps = []
                sweeps = wavelength.get_sweeps()
                for sweep in sweeps:
                    from dials.command_line.show import show_datablocks
                    from dxtbx.datablock import DataBlock
                    Debug.write(sweep.get_name())
                    Debug.write(
                        show_datablocks([DataBlock([sweep.get_imageset()])]))
                    try:
                        if stop_after == 'index':
                            sweep.get_indexer_cell()
                        else:
                            sweep.get_integrater_intensities()
                        sweep.serialize()
                    except Exception as e:
                        if failover:
                            Chatter.write('Processing sweep %s failed: %s' % \
                                          (sweep.get_name(), str(e)))
                            remove_sweeps.append(sweep)
                        else:
                            raise
                for sweep in remove_sweeps:
                    wavelength.remove_sweep(sweep)
                    sample = sweep.get_xsample()
                    sample.remove_sweep(sweep)

    # save intermediate xia2.json file in case scaling step fails
    xinfo.as_json(filename='xia2.json')

    if stop_after not in ('index', 'integrate'):
        Chatter.write(xinfo.get_output(), strip=False)

    for crystal in crystals.values():
        crystal.serialize()

    # save final xia2.json file in case report generation fails
    xinfo.as_json(filename='xia2.json')

    duration = time.time() - start_time

    # write out the time taken in a human readable way
    Chatter.write('Processing took %s' % \
                  time.strftime("%Hh %Mm %Ss", time.gmtime(duration)))

    if stop_after not in ('index', 'integrate'):
        # and the summary file
        with open('xia2-summary.dat', 'w') as fh:
            for record in xinfo.summarise():
                fh.write('%s\n' % record)

        # looks like this import overwrites the initial command line
        # Phil overrides so... for https://github.com/xia2/xia2/issues/150
        from xia2.command_line.html import generate_xia2_html

        if params.xia2.settings.small_molecule == True:
            params.xia2.settings.report.xtriage_analysis = False
            params.xia2.settings.report.include_radiation_damage = False

        generate_xia2_html(xinfo,
                           filename='xia2.html',
                           params=params.xia2.settings.report)

    write_citations()

    # delete all of the temporary mtz files...
    cleanup()
    Environment.cleanup()
Esempio n. 3
0
      PhilIndex.params.xia2.settings.scale.directory = scale_dir
    working_directory = Environment.generate_directory(
      [crystal.get_name(), scale_dir])
    #os.chdir(working_directory)

    crystals[crystal_id]._scaler = None # reset scaler

    scaler = crystal._get_scaler()
    Chatter.write(xinfo.get_output())
    crystal.serialize()

  duration = time.time() - start_time

  # write out the time taken in a human readable way
  Chatter.write('Processing took %s' % \
                time.strftime("%Hh %Mm %Ss", time.gmtime(duration)))

  # delete all of the temporary mtz files...
  cleanup()

  write_citations()

  xinfo.as_json(filename='xia2.json')

  Environment.cleanup()

  return

if __name__ == '__main__':
  run()
Esempio n. 4
0
def multi_crystal_analysis(stop_after=None):
    '''Actually process something...'''

    assert os.path.exists('xia2.json')
    from xia2.Schema.XProject import XProject
    xinfo = XProject.from_json(filename='xia2.json')

    crystals = xinfo.get_crystals()
    for crystal_id, crystal in crystals.iteritems():
        cwd = os.path.abspath(os.curdir)
        working_directory = Environment.generate_directory(
            [crystal.get_name(), 'analysis'])
        os.chdir(working_directory)

        scaler = crystal._get_scaler()

        #epoch_to_si = {}
        epoch_to_batches = {}
        epoch_to_integrated_intensities = {}
        epoch_to_sweep_name = {}
        epoch_to_experiments_filename = {}
        epoch_to_experiments = {}
        sweep_name_to_epoch = {}
        epoch_to_first_image = {}

        from dxtbx.serialize import load
        try:
            epochs = scaler._sweep_information.keys()
            for epoch in epochs:
                si = scaler._sweep_information[epoch]
                epoch_to_batches[epoch] = si['batches']
                epoch_to_integrated_intensities[epoch] = si[
                    'corrected_intensities']
                epoch_to_sweep_name[epoch] = si['sname']
                sweep_name_to_epoch[si['name']] = epoch
                intgr = si['integrater']
                epoch_to_experiments_filename[
                    epoch] = intgr.get_integrated_experiments()
                epoch_to_experiments[epoch] = load.experiment_list(
                    intgr.get_integrated_experiments())

        except AttributeError:
            epochs = scaler._sweep_handler.get_epochs()
            for epoch in epochs:
                si = scaler._sweep_handler.get_sweep_information(epoch)
                epoch_to_batches[epoch] = si.get_batches()
                epoch_to_integrated_intensities[epoch] = si.get_reflections()
                epoch_to_sweep_name[epoch] = si.get_sweep_name()
                sweep_name_to_epoch[si.get_sweep_name()] = epoch
                intgr = si.get_integrater()
                epoch_to_experiments_filename[
                    epoch] = intgr.get_integrated_experiments()
                epoch_to_experiments[epoch] = load.experiment_list(
                    intgr.get_integrated_experiments())

        from xia2.Wrappers.Dials.StereographicProjection import StereographicProjection
        sp_json_files = {}
        for hkl in ((1, 0, 0), (0, 1, 0), (0, 0, 1)):
            sp = StereographicProjection()
            auto_logfiler(sp)
            sp.set_working_directory(working_directory)
            for experiments in epoch_to_experiments_filename.values():
                sp.add_experiments(experiments)
            sp.set_hkl(hkl)
            sp.run()
            sp_json_files[hkl] = sp.get_json_filename()

        unmerged_mtz = scaler.get_scaled_reflections(
            'mtz_unmerged').values()[0]
        from iotbx.reflection_file_reader import any_reflection_file
        reader = any_reflection_file(unmerged_mtz)

        from xia2.Wrappers.XIA.PlotMultiplicity import PlotMultiplicity
        mult_json_files = {}
        for axis in ('h', 'k', 'l'):
            pm = PlotMultiplicity()
            auto_logfiler(pm)
            pm.set_working_directory(working_directory)
            pm.set_mtz_filename(unmerged_mtz)
            pm.set_slice_axis(axis)
            pm.set_show_missing(True)
            pm.run()
            mult_json_files[axis] = pm.get_json_filename()

        intensities = None
        batches = None
        assert reader.file_type() == 'ccp4_mtz'
        arrays = reader.as_miller_arrays(merge_equivalents=False)
        for ma in arrays:
            if ma.info().labels == ['BATCH']:
                batches = ma
            elif ma.info().labels == ['I', 'SIGI']:
                intensities = ma
            elif ma.info().labels == ['I(+)', 'SIGI(+)', 'I(-)', 'SIGI(-)']:
                intensities = ma

        from xia2.Wrappers.CCP4.Blend import Blend
        hand_blender = Blend()
        hand_blender.set_working_directory(working_directory)
        auto_logfiler(hand_blender)
        Citations.cite('blend')

        from xia2.Handlers.Environment import which
        Rscript_binary = which('Rscript', debug=False)
        if Rscript_binary is None:
            Chatter.write('Skipping BLEND analysis: Rscript not available')
        else:
            for epoch in epochs:
                hand_blender.add_hklin(epoch_to_integrated_intensities[epoch],
                                       label=epoch_to_sweep_name[epoch])
            hand_blender.analysis()
            Chatter.write("Dendrogram saved to: %s" %
                          hand_blender.get_dendrogram_file())
            analysis = hand_blender.get_analysis()
            summary = hand_blender.get_summary()
            clusters = hand_blender.get_clusters()

            ddict = hand_blender.plot_dendrogram()

            phil_files_dir = 'phil_files'
            if not os.path.exists(phil_files_dir):
                os.makedirs(phil_files_dir)

            rows = []
            headers = [
                'Cluster', 'Datasets', 'Multiplicity', 'Completeness', 'LCV',
                'aLCV', 'Average unit cell'
            ]
            completeness = flex.double()
            average_unit_cell_params = []
            for i, cluster in clusters.iteritems():
                print i
                sel_cluster = flex.bool(batches.size(), False)
                cluster_uc_params = [flex.double() for k in range(6)]
                for j in cluster['dataset_ids']:
                    epoch = epochs[j - 1]
                    batch_start, batch_end = epoch_to_batches[epoch]
                    sel_cluster |= ((batches.data() >= batch_start) &
                                    (batches.data() <= batch_end))
                    expts = epoch_to_experiments.get(epoch)
                    assert expts is not None, (epoch)
                    assert len(expts) == 1, len(expts)
                    expt = expts[0]
                    uc_params = expt.crystal.get_unit_cell().parameters()
                    for k in range(6):
                        cluster_uc_params[k].append(uc_params[k])
                intensities_cluster = intensities.select(sel_cluster)
                merging = intensities_cluster.merge_equivalents()
                merged_intensities = merging.array()
                multiplicities = merging.redundancies()
                completeness.append(merged_intensities.completeness())
                average_unit_cell_params.append(
                    tuple(flex.mean(p) for p in cluster_uc_params))
                dataset_ids = cluster['dataset_ids']

                assert min(dataset_ids) > 0
                with open(
                        os.path.join(phil_files_dir,
                                     'blend_cluster_%i_images.phil' % i),
                        'wb') as f:
                    sweep_names = [
                        hand_blender._labels[dataset_id - 1]
                        for dataset_id in dataset_ids
                    ]
                    for sweep_name in sweep_names:
                        expts = epoch_to_experiments.get(
                            sweep_name_to_epoch.get(sweep_name))
                        assert expts is not None, (
                            sweep_name, sweep_name_to_epoch.get(sweep_name))
                        assert len(expts) == 1, len(expts)
                        expt = expts[0]
                        print >> f, 'xia2.settings.input.image = %s' % expt.imageset.get_path(
                            0)

                rows.append([
                    '%i' % i,
                    ' '.join(['%i'] * len(dataset_ids)) % tuple(dataset_ids),
                    '%.1f' % flex.mean(multiplicities.data().as_double()),
                    '%.2f' % completeness[-1],
                    '%.2f' % cluster['lcv'],
                    '%.2f' % cluster['alcv'],
                    '%g %g %g %g %g %g' % average_unit_cell_params[-1]
                ])

            # sort table by completeness
            perm = flex.sort_permutation(completeness)
            rows = [rows[i] for i in perm]

            print
            print 'Unit cell clustering summary:'
            print tabulate(rows, headers, tablefmt='rst')
            print

            blend_html = tabulate(rows, headers, tablefmt='html').replace(
                '<table>',
                '<table class="table table-hover table-condensed">').replace(
                    '<td>', '<td style="text-align: right;">')

    # XXX what about multiple wavelengths?
    with open('batches.phil', 'wb') as f:
        try:
            for epoch, si in scaler._sweep_information.iteritems():
                print >> f, "batch {"
                print >> f, "  id=%s" % si['sname']
                print >> f, "  range=%i,%i" % tuple(si['batches'])
                print >> f, "}"
        except AttributeError:
            for epoch in scaler._sweep_handler.get_epochs():
                si = scaler._sweep_handler.get_sweep_information(epoch)
                print >> f, "batch {"
                print >> f, "  id=%s" % si.get_sweep_name()
                print >> f, "  range=%i,%i" % tuple(si.get_batches())
                print >> f, "}"

    from xia2.Wrappers.XIA.MultiCrystalAnalysis import MultiCrystalAnalysis
    mca = MultiCrystalAnalysis()
    auto_logfiler(mca, extra="MultiCrystalAnalysis")
    mca.add_command_line_args([
        scaler.get_scaled_reflections(format="sca_unmerged").values()[0],
        "unit_cell=%s %s %s %s %s %s" % tuple(scaler.get_scaler_cell()),
        "batches.phil"
    ])
    mca.set_working_directory(working_directory)
    mca.run()

    intensity_clusters = mca.get_clusters()
    rows = []
    headers = [
        'Cluster', 'Datasets', 'Multiplicity', 'Completeness', 'Height',
        'Average unit cell'
    ]
    completeness = flex.double()
    average_unit_cell_params = []
    for i, cluster in intensity_clusters.iteritems():
        sel_cluster = flex.bool(batches.size(), False)
        cluster_uc_params = [flex.double() for k in range(6)]
        for j in cluster['datasets']:
            epoch = epochs[j - 1]
            batch_start, batch_end = epoch_to_batches[epoch]
            sel_cluster |= ((batches.data() >= batch_start) &
                            (batches.data() <= batch_end))
            expts = epoch_to_experiments.get(epoch)
            assert expts is not None, (epoch)
            assert len(expts) == 1, len(expts)
            expt = expts[0]
            uc_params = expt.crystal.get_unit_cell().parameters()
            for k in range(6):
                cluster_uc_params[k].append(uc_params[k])
        intensities_cluster = intensities.select(sel_cluster)
        merging = intensities_cluster.merge_equivalents()
        merged_intensities = merging.array()
        multiplicities = merging.redundancies()
        completeness.append(merged_intensities.completeness())
        average_unit_cell_params.append(
            tuple(flex.mean(p) for p in cluster_uc_params))
        dataset_ids = cluster['datasets']

        rows.append([
            '%i' % int(i),
            ' '.join(['%i'] * len(dataset_ids)) % tuple(dataset_ids),
            '%.1f' % flex.mean(multiplicities.data().as_double()),
            '%.2f' % completeness[-1],
            '%.2f' % cluster['height'],
            '%g %g %g %g %g %g' % average_unit_cell_params[-1]
        ])

    # sort table by completeness
    perm = flex.sort_permutation(completeness)
    rows = [rows[i] for i in perm]

    print 'Intensity clustering summary:'
    print tabulate(rows, headers, tablefmt='rst')
    print

    intensity_clustering_html = tabulate(
        rows, headers, tablefmt='html').replace(
            '<table>',
            '<table class="table table-hover table-condensed">').replace(
                '<td>', '<td style="text-align: right;">')

    import json

    json_data = {}
    if ddict is not None:
        from xia2.Modules.MultiCrystalAnalysis import scipy_dendrogram_to_plotly_json
        json_data['blend_dendrogram'] = scipy_dendrogram_to_plotly_json(ddict)
    else:
        json_data['blend_dendrogram'] = {'data': [], 'layout': {}}

    json_data['intensity_clustering'] = mca.get_dict()
    del json_data['intensity_clustering']['clusters']

    for hkl in ((1, 0, 0), (0, 1, 0), (0, 0, 1)):
        with open(sp_json_files[hkl], 'rb') as f:
            d = json.load(f)
            d['layout'][
                'title'] = 'Stereographic projection (hkl=%i%i%i)' % hkl
            json_data['stereographic_projection_%s%s%s' % hkl] = d

    for axis in ('h', 'k', 'l'):
        with open(mult_json_files[axis], 'rb') as f:
            json_data['multiplicity_%s' % axis] = json.load(f)

    json_str = json.dumps(json_data, indent=2)

    javascript = ['var graphs = %s' % (json_str)]
    javascript.append(
        'Plotly.newPlot(blend_dendrogram, graphs.blend_dendrogram.data, graphs.blend_dendrogram.layout);'
    )
    javascript.append(
        'Plotly.newPlot(intensity_clustering, graphs.intensity_clustering.data, graphs.intensity_clustering.layout);'
    )
    for hkl in ((1, 0, 0), (0, 1, 0), (0, 0, 1)):
        javascript.append(
            'Plotly.newPlot(stereographic_projection_%(hkl)s, graphs.stereographic_projection_%(hkl)s.data, graphs.stereographic_projection_%(hkl)s.layout);'
            % ({
                'hkl': "%s%s%s" % hkl
            }))
    for axis in ('h', 'k', 'l'):
        javascript.append(
            'Plotly.newPlot(multiplicity_%(axis)s, graphs.multiplicity_%(axis)s.data, graphs.multiplicity_%(axis)s.layout);'
            % ({
                'axis': axis
            }))

    html_header = '''
<head>

<!-- Plotly.js -->
<script src="https://cdn.plot.ly/plotly-latest.min.js"></script>

<meta name="viewport" content="width=device-width, initial-scale=1" charset="UTF-8">
<link rel="stylesheet" href="http://maxcdn.bootstrapcdn.com/bootstrap/3.3.5/css/bootstrap.min.css"/>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.3/jquery.min.js"></script>
<script src="http://maxcdn.bootstrapcdn.com/bootstrap/3.3.5/js/bootstrap.min.js"></script>
<style type="text/css">

body {
  /*font-family: Helmet, Freesans, Helvetica, Arial, sans-serif;*/
  margin: 8px;
  min-width: 240px;
  margin-left: 5%;
  margin-right: 5%;
}

.plot {
  float: left;
  width: 1200px;
  height: 800px;
  margin-bottom: 20px;
}

.square_plot {
  float: left;
  width: 800px;
  height: 800px;
  margin-bottom: 20px;
}

</style>

</head>

'''

    html_body = '''

<body>

<div class="page-header">
  <h1>Multi-crystal analysis report</h1>
</div>

<div class="panel-group">

  <div class="panel panel-default">
    <div class="panel-heading" data-toggle="collapse" href="#collapse_multiplicity">
      <h4 class="panel-title">
        <a>Multiplicity plots</a>
      </h4>
    </div>
    <div id="collapse_multiplicity" class="panel-collapse collapse">
      <div class="panel-body">
        <div class="col-xs-12 col-sm-12 col-md-12 square_plot" id="multiplicity_h"></div>
        <div class="col-xs-12 col-sm-12 col-md-12 square_plot" id="multiplicity_k"></div>
        <div class="col-xs-12 col-sm-12 col-md-12 square_plot" id="multiplicity_l"></div>
      </div>
    </div>
  </div>

  <div class="panel panel-default">
    <div class="panel-heading" data-toggle="collapse" href="#collapse_stereographic_projection">
      <h4 class="panel-title">
        <a>Stereographic projections</a>
      </h4>
    </div>
    <div id="collapse_stereographic_projection" class="panel-collapse collapse">
      <div class="panel-body">
        <div class="col-xs-12 col-sm-12 col-md-12 square_plot" id="stereographic_projection_100"></div>
        <div class="col-xs-12 col-sm-12 col-md-12 square_plot" id="stereographic_projection_010"></div>
        <div class="col-xs-12 col-sm-12 col-md-12 square_plot" id="stereographic_projection_001"></div>
      </div>
    </div>
  </div>

  <div class="panel panel-default">
    <div class="panel-heading" data-toggle="collapse" href="#collapse_cell">
      <h4 class="panel-title">
        <a>Unit cell clustering</a>
      </h4>
    </div>
    <div id="collapse_cell" class="panel-collapse collapse">
      <div class="panel-body">
        <div class="col-xs-12 col-sm-12 col-md-12 plot" id="blend_dendrogram"></div>
        <div class="table-responsive" style="width: 800px">
          %(blend_html)s
        </div>
      </div>
    </div>
  </div>

  <div class="panel panel-default">
    <div class="panel-heading" data-toggle="collapse" href="#collapse_intensity">
      <h4 class="panel-title">
        <a>Intensity clustering</a>
      </h4>
    </div>
    <div id="collapse_intensity" class="panel-collapse collapse">
      <div class="panel-body">
        <div class="col-xs-12 col-sm-12 col-md-12 plot" id="intensity_clustering" style="height:1000px"></div>
        <div class="table-responsive" style="width: 800px">
          %(intensity_clustering_html)s
        </div>
      </div>
    </div>
  </div>
</div>

<script>
%(script)s
</script>
</body>
    ''' % {
        'script': '\n'.join(javascript),
        'blend_html': blend_html,
        'intensity_clustering_html': intensity_clustering_html
    }

    html = '\n'.join([html_header, html_body])

    print "Writing html report to: %s" % 'multi-crystal-report.html'
    with open('multi-crystal-report.html', 'wb') as f:
        print >> f, html.encode('ascii', 'xmlcharrefreplace')

    write_citations()

    Environment.cleanup()

    return