Python Filter

[JonasLukasczyk]

This PR adds the following features:

• A TextView that allows users to edit multi-line strings that are provided as the output of the view.
• A generic Python filter that given any input data object (first input port) executes any python code (second input port) to produce some output data object (first output port). The input and output ports of the filter are already available as the variables "inputs" and "outputs" when the code is executed. Below you can find an example.
• The Python filter also detects if the code input is actually a filepath, in which case the filter uses the content of the referenced file. The filter also attaches a file listener and automatically updates the pipeline when the file changes.
• The pycinema core module now provides the imageFromMatplotlibFigure utility function that takes a matplotlib figure as an input and produces a pycinema image data object.

Here is an example script that uses all new features:

import pycinema
import pycinema.filters
import pycinema.theater
import pycinema.theater.views

# pycinema settings
PYCINEMA = { 'VERSION' : '2.1.0'}

# layout
vf0 = pycinema.theater.Theater.instance.centralWidget()
vf0.setHorizontalOrientation()
vf1 = vf0.insertFrame(0)
vf1.setHorizontalOrientation()
vf2 = vf1.insertFrame(0)
vf2.setVerticalOrientation()
vf2.insertView( 0, pycinema.theater.views.NodeEditorView() )
TableView_0 = vf2.insertView( 1, pycinema.theater.views.TableView() )
vf2.setSizes([425, 425])
vf3 = vf1.insertFrame(1)
vf3.setVerticalOrientation()
ImageView_0 = vf3.insertView( 0, pycinema.theater.views.ImageView() )
TextView_0 = vf3.insertView( 1, pycinema.theater.views.TextView() )
vf3.setSizes([404, 446])
vf1.setSizes([510, 510])
vf0.setSizes([1024])

# filters
CinemaDatabaseReader_0 = pycinema.filters.CinemaDatabaseReader()
Calculator_0 = pycinema.filters.Calculator()
TableQuery_0 = pycinema.filters.TableQuery()
Python_0 = pycinema.filters.Python()

# properties
TableView_0.inputs.table.set(Calculator_0.outputs.table, False)
ImageView_0.inputs.images.set(Python_0.outputs.outputs, False)
CinemaDatabaseReader_0.inputs.path.set("./data/ScalarImages.cdb/", False)
CinemaDatabaseReader_0.inputs.file_column.set("FILE", False)
Calculator_0.inputs.table.set(TableQuery_0.outputs.table, False)
Calculator_0.inputs.label.set("result", False)
Calculator_0.inputs.expression.set("time*id", False)
TableQuery_0.inputs.table.set(CinemaDatabaseReader_0.outputs.table, False)
TableQuery_0.inputs.sql.set("SELECT * FROM input", False)
Python_0.inputs.inputs.set(Calculator_0.outputs.table, False)
Python_0.inputs.code.set(TextView_0.outputs.text, False)
TextView_0.inputs.text.set('''
from pycinema import getColumnFromTable, imageFromMatplotlibFigure
import matplotlib.pyplot as plt

# use offscreen backend
import matplotlib as mpl
mpl.use('Agg')

outputs = []
for column in ['result','time','phi','theta']:

  figure = plt.figure()
  plt.plot(
    getColumnFromTable(inputs, "id"),
    getColumnFromTable(inputs, column)
  )
  plt.xlabel('id')
  plt.ylabel(column)
  plt.title('id x ' + column)

  outputs.append( imageFromMatplotlibFigure(figure) )

  plt.close(figure)

''', False)

# execute pipeline
TableView_0.update()