r"""This module is used to export complete CoProcessing Python scripts that
can be used in a vtkCPPythonScriptPipeline.

This module uses paraview.cpstate Module to dump the ParaView session state as a
an Python class description that can be then be used in the CoProcessor.

The exported script can be used in a vtkCPPythonScriptPipeline instance for
CoProcessing."""

# -----------------------------------------------------------------------------
# The __output_contents is the templet script that accept 3 arguments:
#  1) The CoProcessor class definition
#  2) The boolean to know if we want to enable live-visualization
#  3) The boolean to know if we need to rescale the data range
# -----------------------------------------------------------------------------
__output_contents = """
from paraview.simple import *
from paraview import coprocessing


#--------------------------------------------------------------
# Code generated from cpstate.py to create the CoProcessor.
# ParaView 5.1.0 64 bits

%s
#--------------------------------------------------------------
# Global variables that will hold the pipeline for each timestep
# Creating the CoProcessor object, doesn't actually create the ParaView pipeline.
# It will be automatically setup when coprocessor.UpdateProducers() is called the
# first time.
coprocessor = CreateCoProcessor()

#--------------------------------------------------------------
# Enable Live-Visualizaton with ParaView
coprocessor.EnableLiveVisualization(%s, %s)


# ---------------------- Data Selection method ----------------------

def RequestDataDescription(datadescription):
    "Callback to populate the request for current timestep"
    global coprocessor
    if datadescription.GetForceOutput() == True:
        # We are just going to request all fields and meshes from the simulation
        # code/adaptor.
        for i in range(datadescription.GetNumberOfInputDescriptions()):
            datadescription.GetInputDescription(i).AllFieldsOn()
            datadescription.GetInputDescription(i).GenerateMeshOn()
        return

    # setup requests for all inputs based on the requirements of the
    # pipeline.
    coprocessor.LoadRequestedData(datadescription)

# ------------------------ Processing method ------------------------

def DoCoProcessing(datadescription):
    "Callback to do co-processing for current timestep"
    global coprocessor

    # Update the coprocessor by providing it the newly generated simulation data.
    # If the pipeline hasn't been setup yet, this will setup the pipeline.
    coprocessor.UpdateProducers(datadescription)

    # Write output data, if appropriate.
    coprocessor.WriteData(datadescription);

    # Write image capture (Last arg: rescale lookup table), if appropriate.
    coprocessor.WriteImages(datadescription, rescale_lookuptable=%s)

    # Live Visualization, if enabled.
    coprocessor.DoLiveVisualization(datadescription, "localhost", 22222)
"""

from paraview import cpstate

def DumpCoProcessingScript(export_rendering, simulation_input_map, screenshot_info,
    rescale_data_range, enable_live_viz, live_viz_frequency,
    cinema_tracks, array_selection, filename=None):
    """Returns a string with the generated CoProcessing script based on the
        options specified.

        First three arguments are same as those expected by
        cpstate.DumpPipeline() function.

        rescale_data_range :- boolean set to true if the LUTs must be scaled on
                              each timestep
        enable_live_viz    :- boolean set to true if the generated script should
                              handle live-visualization.
        live_viz_frequency :- integer specifying how often should
                              the coprocessor send the live data
        cinema_tracks      :- cinema offline visualizer parameters
        array_selection    :- selected value arrays for cinema
        filename           :- if specified, the script is written to the file.
    """
    pipeline_script = cpstate.DumpPipeline(\
        export_rendering, simulation_input_map, screenshot_info, cinema_tracks, array_selection)
    script = __output_contents % (pipeline_script,
                                  enable_live_viz, live_viz_frequency,
                                  rescale_data_range)
    if filename:
        outFile = open(filename, "w")
        outFile.write(script)
        outFile.close()
    return script

def run(filename=None):
    """Create a dummy pipeline and save the coprocessing state in the filename
    specified, if any, else dumps it out on stdout."""

    from paraview import simple, servermanager
    wavelet = simple.Wavelet(registrationName="Wavelet1")
    contour = simple.Contour()
    script = DumpCoProcessingScript(export_rendering=False,
        simulation_input_map={"Wavelet1" : "input"},
        screenshot_info={},
        rescale_data_range=True,
        enable_live_viz=True,
        live_viz_frequency=1,
        cinema_tracks={},
        array_selection = {},
        filename=filename)
    if not filename:
        print "# *** Generated Script Begin ***"
        print script
        print "# *** Generated Script End ***"

if __name__ == "__main__":
    run()

# ---- end ----
