146 lines
5.3 KiB
Python
146 lines
5.3 KiB
Python
# -*- coding: utf-8 -*-
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"""
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This example demonstrates writing a custom Node subclass for use with flowcharts.
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We implement a couple of simple image processing nodes.
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"""
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import initExample ## Add path to library (just for examples; you do not need this)
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from pyqtgraph.flowchart import Flowchart, Node
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import pyqtgraph.flowchart.library as fclib
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from pyqtgraph.flowchart.library.common import CtrlNode
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from pyqtgraph.Qt import QtGui, QtCore
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import pyqtgraph as pg
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import numpy as np
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import scipy.ndimage
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app = QtGui.QApplication([])
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## Create main window with a grid layout inside
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win = QtGui.QMainWindow()
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win.setWindowTitle('pyqtgraph example: FlowchartCustomNode')
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cw = QtGui.QWidget()
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win.setCentralWidget(cw)
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layout = QtGui.QGridLayout()
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cw.setLayout(layout)
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## Create an empty flowchart with a single input and output
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fc = Flowchart(terminals={
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'dataIn': {'io': 'in'},
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'dataOut': {'io': 'out'}
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})
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w = fc.widget()
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layout.addWidget(fc.widget(), 0, 0, 2, 1)
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## Create two ImageView widgets to display the raw and processed data with contrast
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## and color control.
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v1 = pg.ImageView()
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v2 = pg.ImageView()
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layout.addWidget(v1, 0, 1)
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layout.addWidget(v2, 1, 1)
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win.show()
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## generate random input data
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data = np.random.normal(size=(100,100))
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data = 25 * scipy.ndimage.gaussian_filter(data, (5,5))
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data += np.random.normal(size=(100,100))
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data[40:60, 40:60] += 15.0
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data[30:50, 30:50] += 15.0
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#data += np.sin(np.linspace(0, 100, 1000))
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#data = metaarray.MetaArray(data, info=[{'name': 'Time', 'values': np.linspace(0, 1.0, len(data))}, {}])
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## Set the raw data as the input value to the flowchart
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fc.setInput(dataIn=data)
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## At this point, we need some custom Node classes since those provided in the library
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## are not sufficient. Each node will define a set of input/output terminals, a
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## processing function, and optionally a control widget (to be displayed in the
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## flowchart control panel)
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class ImageViewNode(Node):
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"""Node that displays image data in an ImageView widget"""
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nodeName = 'ImageView'
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def __init__(self, name):
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self.view = None
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## Initialize node with only a single input terminal
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Node.__init__(self, name, terminals={'data': {'io':'in'}})
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def setView(self, view): ## setView must be called by the program
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self.view = view
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def process(self, data, display=True):
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## if process is called with display=False, then the flowchart is being operated
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## in batch processing mode, so we should skip displaying to improve performance.
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if display and self.view is not None:
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## the 'data' argument is the value given to the 'data' terminal
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if data is None:
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self.view.setImage(np.zeros((1,1))) # give a blank array to clear the view
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else:
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self.view.setImage(data)
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## register the class so it will appear in the menu of node types.
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## It will appear in the 'display' sub-menu.
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fclib.registerNodeType(ImageViewNode, [('Display',)])
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## We will define an unsharp masking filter node as a subclass of CtrlNode.
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## CtrlNode is just a convenience class that automatically creates its
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## control widget based on a simple data structure.
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class UnsharpMaskNode(CtrlNode):
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"""Return the input data passed through scipy.ndimage.gaussian_filter."""
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nodeName = "UnsharpMask"
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uiTemplate = [
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('sigma', 'spin', {'value': 1.0, 'step': 1.0, 'range': [0.0, None]}),
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('strength', 'spin', {'value': 1.0, 'dec': True, 'step': 0.5, 'minStep': 0.01, 'range': [0.0, None]}),
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]
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def __init__(self, name):
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## Define the input / output terminals available on this node
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terminals = {
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'dataIn': dict(io='in'), # each terminal needs at least a name and
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'dataOut': dict(io='out'), # to specify whether it is input or output
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} # other more advanced options are available
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# as well..
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CtrlNode.__init__(self, name, terminals=terminals)
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def process(self, dataIn, display=True):
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# CtrlNode has created self.ctrls, which is a dict containing {ctrlName: widget}
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sigma = self.ctrls['sigma'].value()
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strength = self.ctrls['strength'].value()
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output = dataIn - (strength * scipy.ndimage.gaussian_filter(dataIn, (sigma,sigma)))
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return {'dataOut': output}
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## register the class so it will appear in the menu of node types.
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## It will appear in a new 'image' sub-menu.
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fclib.registerNodeType(UnsharpMaskNode, [('Image',)])
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## Now we will programmatically add nodes to define the function of the flowchart.
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## Normally, the user will do this manually or by loading a pre-generated
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## flowchart file.
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v1Node = fc.createNode('ImageView', pos=(0, -150))
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v1Node.setView(v1)
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v2Node = fc.createNode('ImageView', pos=(150, -150))
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v2Node.setView(v2)
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fNode = fc.createNode('UnsharpMask', pos=(0, 0))
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fc.connectTerminals(fc['dataIn'], fNode['dataIn'])
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fc.connectTerminals(fc['dataIn'], v1Node['data'])
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fc.connectTerminals(fNode['dataOut'], v2Node['data'])
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fc.connectTerminals(fNode['dataOut'], fc['dataOut'])
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## Start Qt event loop unless running in interactive mode or using pyside.
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if __name__ == '__main__':
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import sys
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if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
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QtGui.QApplication.instance().exec_()
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