Python PlotExecutable.add_input_opt方法代码示例

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_coinc_info(workflow,
                    singles,
                    bank,
                    coinc,
                    num,
                    out_dir,
                    exclude=None,
                    require=None,
                    tags=None):
    tags = [] if tags is None else tags
    makedir(out_dir)
    name = 'page_coincinfo'
    secs = requirestr(workflow.cp.get_subsections(name), require)
    secs = excludestr(secs, exclude)
    files = FileList([])
    node = PlotExecutable(
        workflow.cp, name, ifos=workflow.ifos, out_dir=out_dir,
        tags=tags).create_node()
    node.add_input_list_opt('--single-trigger-files', singles)
    node.add_input_opt('--statmap-file', coinc)
    node.add_input_opt('--bank-file', bank)
    node.add_opt('--n-loudest', str(num))
    node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
    workflow += node
    files += node.output_files
    return files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_inference_samples_plot(
                    workflow, inference_file, output_dir, parameters=None,
                    name="inference_samples", analysis_seg=None, tags=None):
    # default values
    tags = [] if tags is None else tags
    analysis_seg = workflow.analysis_time \
                       if analysis_seg is None else analysis_seg

    # make the directory that will contain the output files
    makedir(output_dir)

    # make a node for plotting the posterior as a corner plot
    node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
                      out_dir=output_dir, universe="local",
                      tags=tags).create_node()

    # add command line options
    node.add_input_opt("--input-file", inference_file)
    node.new_output_file_opt(analysis_seg, ".png", "--output-file")
    node.add_opt("--parameters", " ".join(parameters))

    # add node to workflow
    workflow += node

    return node.output_files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_inference_corner_plot(workflow, mcmc_file, output_dir, config_file,
                    name="mcmc_corner", analysis_seg=None, tags=None):
    """ Sets up the corner plot of the posteriors in the workflow.

    Parameters
    ----------
    workflow: pycbc.workflow.Workflow
        The core workflow instance we are populating
    mcmc_file: pycbc.workflow.File
        The file with MCMC samples.
    output_dir: str
        The directory to store result plots and files.
    config_file: str
        The path to the inference configuration file that has a
        [variable_args] section.
    name: str
        The name in the [executables] section of the configuration file
        to use.
    analysis_segs: {None, glue.segments.Segment}
       The segment this job encompasses. If None then use the total analysis
       time from the workflow.
    tags: {None, optional}
        Tags to add to the minifollowups executables.

    Returns
    -------
    pycbc.workflow.FileList
        A list of result and output files. 
    """

    # default values
    tags = [] if tags is None else tags
    analysis_seg = workflow.analysis_time \
                       if analysis_seg is None else analysis_seg

    # read config file to get variables that vary
    cp = WorkflowConfigParser([config_file])
    variable_args = cp.options("variable_args")

    # add derived mass parameters if mass1 and mass2 in variable_args
    if "mass1" in variable_args and "mass2" in variable_args:
        variable_args += ["mchirp", "eta"]

    # make the directory that will contain the output files
    makedir(output_dir)

    # make a node for plotting the posterior as a corner plot
    node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
                      out_dir=output_dir, universe="local",
                      tags=tags).create_node()

    # add command line options
    node.add_input_opt("--input-file", mcmc_file)
    node.new_output_file_opt(analysis_seg, ".png", "--output-file")

    # add node to workflow
    workflow += node

    return node.output_files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_inference_corner_plot(workflow, inference_file, output_dir,
                    variable_args=None,
                    name="inference_posterior", analysis_seg=None, tags=None):
    """ Sets up the corner plot of the posteriors in the workflow.

    Parameters
    ----------
    workflow: pycbc.workflow.Workflow
        The core workflow instance we are populating
    inference_file: pycbc.workflow.File
        The file with posterior samples.
    output_dir: str
        The directory to store result plots and files.
    config_file: str
        The path to the inference configuration file that has a
        [variable_args] section.
    variable_args : list
        A list of parameters to use instead of [variable_args].
    name: str
        The name in the [executables] section of the configuration file
        to use.
    analysis_segs: {None, glue.segments.Segment}
       The segment this job encompasses. If None then use the total analysis
       time from the workflow.
    tags: {None, optional}
        Tags to add to the minifollowups executables.

    Returns
    -------
    pycbc.workflow.FileList
        A list of result and output files. 
    """

    # default values
    tags = [] if tags is None else tags
    analysis_seg = workflow.analysis_time \
                       if analysis_seg is None else analysis_seg

    # make the directory that will contain the output files
    makedir(output_dir)

    # make a node for plotting the posterior as a corner plot
    node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
                      out_dir=output_dir, universe="local",
                      tags=tags).create_node()

    # add command line options
    node.add_input_opt("--input-file", inference_file)
    node.new_output_file_opt(analysis_seg, ".png", "--output-file")
    node.add_opt("--variable-args", " ".join(variable_args))

    # add node to workflow
    workflow += node

    return node.output_files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_inference_prior_plot(workflow, config_file, output_dir,
                    sections=None, name="inference_prior",
                    analysis_seg=None, tags=None):
    """ Sets up the corner plot of the priors in the workflow.

    Parameters
    ----------
    workflow: pycbc.workflow.Workflow
        The core workflow instance we are populating
    config_file: pycbc.workflow.File
        The WorkflowConfigParser parasable inference configuration file..
    output_dir: str
        The directory to store result plots and files.
    sections : list
        A list of subsections to use.
    name: str
        The name in the [executables] section of the configuration file
        to use.
    analysis_segs: {None, ligo.segments.Segment}
       The segment this job encompasses. If None then use the total analysis
       time from the workflow.
    tags: {None, optional}
        Tags to add to the inference executables.

    Returns
    -------
    pycbc.workflow.FileList
        A list of result and output files.
    """

    # default values
    tags = [] if tags is None else tags
    analysis_seg = workflow.analysis_time \
                       if analysis_seg is None else analysis_seg

    # make the directory that will contain the output files
    makedir(output_dir)

    # make a node for plotting the posterior as a corner plot
    node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
                      out_dir=output_dir, universe="local",
                      tags=tags).create_node()

    # add command line options
    node.add_input_opt("--config-file", config_file)
    node.new_output_file_opt(analysis_seg, ".png", "--output-file")
    if sections is not None:
        node.add_opt("--sections", " ".join(sections))

    # add node to workflow
    workflow += node

    return node.output_files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_inj_info(workflow, injection_file, injection_index, num, out_dir, tags=None):
    tags = [] if tags is None else tags
    makedir(out_dir)
    name = "page_injinfo"
    files = FileList([])
    node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos, out_dir=out_dir, tags=tags).create_node()
    node.add_input_opt("--injection-file", injection_file)
    node.add_opt("--injection-index", str(injection_index))
    node.add_opt("--n-nearest", str(num))
    node.new_output_file_opt(workflow.analysis_time, ".html", "--output-file")
    workflow += node
    files += node.output_files
    return files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_single_template_plots(workflow, segs, seg_name, coinc, bank, num, out_dir, 
                               exclude=None, require=None, tags=None):
    tags = [] if tags is None else tags
    makedir(out_dir)
    name = 'single_template_plot'
    secs = requirestr(workflow.cp.get_subsections(name), require)  
    secs = excludestr(secs, exclude)
    files = FileList([])
    for tag in secs:
        for ifo in workflow.ifos:
            # Reanalyze the time around the trigger in each detector
            node = PlotExecutable(workflow.cp, 'single_template', ifos=[ifo],
                                 out_dir=out_dir, tags=[tag] + tags).create_node()
            node.add_input_opt('--statmap-file', coinc)
            node.add_opt('--n-loudest', str(num))
            node.add_input_opt('--inspiral-segments', segs[ifo])
            node.add_opt('--segment-name', seg_name)
            node.add_input_opt('--bank-file', bank)
            node.new_output_file_opt(workflow.analysis_time, '.hdf', '--output-file')
            data = node.output_files[0]
            workflow += node
            
            # Make the plot for this trigger and detector
            node = PlotExecutable(workflow.cp, name, ifos=[ifo],
                                  out_dir=out_dir, tags=[tag] + tags).create_node()
            node.add_input_opt('--single-template-file', data)
            node.new_output_file_opt(workflow.analysis_time, '.png', '--output-file')
            workflow += node
            files += node.output_files
    return files      

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_coinc_info(workflow, singles, bank, coinc, num, out_dir, tags=None):
    tags = [] if tags is None else tags
    makedir(out_dir)
    name = "page_coincinfo"
    files = FileList([])
    node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos, out_dir=out_dir, tags=tags).create_node()
    node.add_input_list_opt("--single-trigger-files", singles)
    node.add_input_opt("--statmap-file", coinc)
    node.add_input_opt("--bank-file", bank)
    node.add_opt("--n-loudest", str(num))
    node.new_output_file_opt(workflow.analysis_time, ".html", "--output-file")
    workflow += node
    files += node.output_files
    return files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_inference_acceptance_rate_plot(workflow, mcmc_file, output_dir,
                    name="mcmc_rate", analysis_seg=None, tags=None):
    """ Sets up the acceptance rate plot in the workflow.

    Parameters
    ----------
    workflow: pycbc.workflow.Workflow
        The core workflow instance we are populating
    mcmc_file: pycbc.workflow.File
        The file with MCMC samples.
    output_dir: str
        The directory to store result plots and files.
    name: str
        The name in the [executables] section of the configuration file
        to use.
    analysis_segs: {None, glue.segments.Segment}
       The segment this job encompasses. If None then use the total analysis
       time from the workflow.
    tags: {None, optional}
        Tags to add to the minifollowups executables.

    Returns
    -------
    pycbc.workflow.FileList
        A list of result and output files. 
    """

    # default values
    tags = [] if tags is None else tags
    analysis_seg = workflow.analysis_time \
                       if analysis_seg is None else analysis_seg

    # make the directory that will contain the output files
    makedir(output_dir)

    # make a node for plotting the acceptance rate
    node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
                      out_dir=output_dir, tags=tags).create_node()

    # add command line options
    node.add_input_opt("--input-file", mcmc_file)
    node.new_output_file_opt(analysis_seg, ".png", "--output-file")

    # add node to workflow
    workflow += node

    return node.output_files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_sngl_ifo(workflow, sngl_file, bank_file, trigger_id, out_dir, ifo, tags=None, rank=None):
    """Setup a job to create sngl detector sngl ifo html summary snippet.
    """
    tags = [] if tags is None else tags
    makedir(out_dir)
    name = "page_snglinfo"
    files = FileList([])
    node = PlotExecutable(workflow.cp, name, ifos=[ifo], out_dir=out_dir, tags=tags).create_node()
    node.add_input_opt("--single-trigger-file", sngl_file)
    node.add_input_opt("--bank-file", bank_file)
    node.add_opt("--trigger-id", str(trigger_id))
    if rank is not None:
        node.add_opt("--n-loudest", str(rank))
    node.add_opt("--instrument", ifo)
    node.new_output_file_opt(workflow.analysis_time, ".html", "--output-file")
    workflow += node
    files += node.output_files
    return files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_coinc_info(workflow, singles, bank, coinc, out_dir,
                    n_loudest=None, trig_id=None, file_substring=None,
                    tags=None):
    tags = [] if tags is None else tags
    makedir(out_dir)
    name = 'page_coincinfo'
    files = FileList([])
    node = PlotExecutable(workflow.cp, name, ifos=workflow.ifos,
                              out_dir=out_dir, tags=tags).create_node()
    node.add_input_list_opt('--single-trigger-files', singles)
    node.add_input_opt('--statmap-file', coinc)
    node.add_input_opt('--bank-file', bank)
    if n_loudest is not None:
        node.add_opt('--n-loudest', str(n_loudest))
    if trig_id is not None:
        node.add_opt('--trigger-id', str(trig_id))
    if file_substring is not None:
        node.add_opt('--statmap-file-subspace-name', file_substring)
    node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
    workflow += node
    files += node.output_files
    return files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_single_template_plots(workflow, segs, data_read_name, analyzed_name,
                                  params, out_dir, inj_file=None, exclude=None,
                                  require=None, tags=None, params_str=None,
                                  use_exact_inj_params=False):
    tags = [] if tags is None else tags
    makedir(out_dir)
    name = 'single_template_plot'
    secs = requirestr(workflow.cp.get_subsections(name), require)
    secs = excludestr(secs, exclude)
    files = FileList([])
    for tag in secs:
        for ifo in workflow.ifos:
            # Reanalyze the time around the trigger in each detector
            node = PlotExecutable(workflow.cp, 'single_template', ifos=[ifo],
                              out_dir=out_dir, tags=[tag] + tags).create_node()
            if use_exact_inj_params:
                node.add_opt('--use-params-of-closest-injection')
            else:
                node.add_opt('--mass1', "%.6f" % params['mass1'])
                node.add_opt('--mass2', "%.6f" % params['mass2'])
                node.add_opt('--spin1z',"%.6f" % params['spin1z'])
                node.add_opt('--spin2z',"%.6f" % params['spin2z'])
            # str(numpy.float64) restricts to 2d.p. BE CAREFUL WITH THIS!!!
            str_trig_time = '%.6f' %(params[ifo + '_end_time'])
            node.add_opt('--trigger-time', str_trig_time)
            node.add_input_opt('--inspiral-segments', segs)
            if inj_file is not None:
                node.add_input_opt('--injection-file', inj_file)
            node.add_opt('--data-read-name', data_read_name)
            node.add_opt('--data-analyzed-name', analyzed_name)
            node.new_output_file_opt(workflow.analysis_time, '.hdf',
                                     '--output-file', store_file=False)
            data = node.output_files[0]
            workflow += node
            # Make the plot for this trigger and detector
            node = PlotExecutable(workflow.cp, name, ifos=[ifo],
                              out_dir=out_dir, tags=[tag] + tags).create_node()
            node.add_input_opt('--single-template-file', data)
            node.new_output_file_opt(workflow.analysis_time, '.png',
                                     '--output-file')
            title="'%s SNR and chi^2 timeseries" %(ifo) 
            if params_str is not None:
                title+= " using %s" %(params_str)
            title+="'"
            node.add_opt('--plot-title', title)
            caption = "'The SNR and chi^2 timeseries around the injection"
            if params_str is not None:
                caption += " using %s" %(params_str)
            if use_exact_inj_params:
                caption += ". The injection itself was used as the template.'"
            else:
                caption += ". The template used has the following parameters: "
                caption += "mass1=%s, mass2=%s, spin1z=%s, spin2z=%s'"\
                       %(params['mass1'], params['mass2'], params['spin1z'],
                         params['spin2z'])
            node.add_opt('--plot-caption', caption)
            workflow += node
            files += node.output_files
    return files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_singles_timefreq(workflow, single, bank_file, start, end, out_dir, veto_file=None, tags=None):
    tags = [] if tags is None else tags
    makedir(out_dir)
    name = "plot_singles_timefreq"

    node = PlotExecutable(workflow.cp, name, ifos=[single.ifo], out_dir=out_dir, tags=tags).create_node()
    node.add_input_opt("--trig-file", single)
    node.add_input_opt("--bank-file", bank_file)
    node.add_opt("--gps-start-time", int(start))
    node.add_opt("--gps-end-time", int(end))

    if veto_file:
        node.add_input_opt("--veto-file", veto_file)

    node.add_opt("--detector", single.ifo)
    node.new_output_file_opt(workflow.analysis_time, ".png", "--output-file")
    workflow += node
    return node.output_files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_sngl_ifo(workflow, sngl_file, bank_file, num, out_dir, ifo,
                  veto_file=None, veto_segment_name=None, tags=None):
    """Setup a job to create sngl detector sngl ifo html summary snippet.
    """
    tags = [] if tags is None else tags
    makedir(out_dir)
    name = 'page_snglinfo'
    files = FileList([])
    node = PlotExecutable(workflow.cp, name, ifos=[ifo],
                              out_dir=out_dir, tags=tags).create_node()
    node.add_input_opt('--single-trigger-file', sngl_file)
    node.add_input_opt('--bank-file', bank_file)
    if veto_file is not None:
        assert(veto_segment_name is not None)
        node.add_input_opt('--veto-file', veto_file)
        node.add_opt('--veto-segment-name', veto_segment_name)
    node.add_opt('--n-loudest', str(num))
    node.add_opt('--instrument', ifo)
    node.new_output_file_opt(workflow.analysis_time, '.html', '--output-file')
    workflow += node
    files += node.output_files
    return files

# 需要导入模块: from pycbc.workflow.plotting import PlotExecutable [as 别名]
# 或者: from pycbc.workflow.plotting.PlotExecutable import add_input_opt [as 别名]
def make_inference_single_parameter_plots(workflow, mcmc_file, output_dir,
                    config_file, samples_name="mcmc_samples",
                    auto_name="mcmc_acf", analysis_seg=None, tags=None):
    """ Sets up single-parameter plots from MCMC in the workflow.

    Parameters
    ----------
    workflow: pycbc.workflow.Workflow
        The core workflow instance we are populating
    mcmc_file: pycbc.workflow.File
        The file with MCMC samples.
    output_dir: str
        The directory to store result plots and files.
    config_file: str
        The path to the inference configuration file that has a
        [variable_args] section.
    samples_name: str
        The name in the [executables] section of the configuration file
        to use for the plot that shows all samples.
    auto_name: str
        The name in the [executables] section of the configuration file
        to use for the autocorrelation function plot.
    analysis_segs: {None, glue.segments.Segment}
       The segment this job encompasses. If None then use the total analysis
       time from the workflow.
    tags: {None, optional}
        Tags to add to the minifollowups executables.

    Returns
    -------
    files: pycbc.workflow.FileList
        A list of result and output files. 
    """

    # default values
    tags = [] if tags is None else tags
    analysis_seg = workflow.analysis_time \
                       if analysis_seg is None else analysis_seg

    # read config file to get variables that vary
    cp = WorkflowConfigParser([config_file])
    variable_args = cp.options("variable_args")

    # make the directory that will contain the output files
    makedir(output_dir)

    # list of all output files
    files = FileList()

    # make a set of plots for each parameter
    for arg in variable_args:

        # make a node for plotting all the samples
        samples_node = PlotExecutable(workflow.cp, samples_name,
                          ifos=workflow.ifos, out_dir=output_dir,
                          tags=tags + [arg]).create_node()

        # add command line options
        samples_node.add_input_opt("--input-file", mcmc_file)
        samples_node.new_output_file_opt(analysis_seg, ".png", "--output-file")
        samples_node.add_opt("--variable-args", arg)
        samples_node.add_opt("--labels", arg)

        # make node for plotting the autocorrelation function for each walker
        auto_node = PlotExecutable(workflow.cp, auto_name, ifos=workflow.ifos,
                          out_dir=output_dir, tags=tags + [arg]).create_node()

        # add command line options
        auto_node.add_input_opt("--input-file", mcmc_file)
        auto_node.new_output_file_opt(analysis_seg, ".png", "--output-file")
        auto_node.add_opt("--variable-args", arg)

        # add nodes to workflow
        workflow += samples_node
        workflow += auto_node

        # add files to output files list
        files += samples_node.output_files
        files += auto_node.output_files

    return files