67 lines
2.5 KiB
Python
67 lines
2.5 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Demonstration of ScatterPlotWidget for exploring structure in tabular data.
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The widget consists of four components:
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1) A list of column names from which the user may select 1 or 2 columns
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to plot. If one column is selected, the data for that column will be
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plotted in a histogram-like manner by using pg.pseudoScatter().
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If two columns are selected, then the
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scatter plot will be generated with x determined by the first column
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that was selected and y by the second.
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2) A DataFilter that allows the user to select a subset of the data by
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specifying multiple selection criteria.
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3) A ColorMap that allows the user to determine how points are colored by
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specifying multiple criteria.
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4) A PlotWidget for displaying the data.
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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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import pyqtgraph as pg
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from pyqtgraph.Qt import QtCore, QtGui
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import numpy as np
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pg.mkQApp()
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# Make up some tabular data with structure
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data = np.empty(1000, dtype=[('x_pos', float), ('y_pos', float),
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('count', int), ('amplitude', float),
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('decay', float), ('type', 'U10')])
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strings = ['Type-A', 'Type-B', 'Type-C', 'Type-D', 'Type-E']
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typeInds = np.random.randint(5, size=1000)
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data['type'] = np.array(strings)[typeInds]
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data['x_pos'] = np.random.normal(size=1000)
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data['x_pos'][data['type'] == 'Type-A'] -= 1
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data['x_pos'][data['type'] == 'Type-B'] -= 1
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data['x_pos'][data['type'] == 'Type-C'] += 2
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data['x_pos'][data['type'] == 'Type-D'] += 2
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data['x_pos'][data['type'] == 'Type-E'] += 2
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data['y_pos'] = np.random.normal(size=1000) + data['x_pos']*0.1
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data['y_pos'][data['type'] == 'Type-A'] += 3
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data['y_pos'][data['type'] == 'Type-B'] += 3
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data['amplitude'] = data['x_pos'] * 1.4 + data['y_pos'] + np.random.normal(size=1000, scale=0.4)
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data['count'] = (np.random.exponential(size=1000, scale=100) * data['x_pos']).astype(int)
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data['decay'] = np.random.normal(size=1000, scale=1e-3) + data['amplitude'] * 1e-4
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data['decay'][data['type'] == 'Type-A'] /= 2
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data['decay'][data['type'] == 'Type-E'] *= 3
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# Create ScatterPlotWidget and configure its fields
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spw = pg.ScatterPlotWidget()
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spw.setFields([
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('x_pos', {'units': 'm'}),
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('y_pos', {'units': 'm'}),
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('count', {}),
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('amplitude', {'units': 'V'}),
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('decay', {'units': 's'}),
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('type', {'mode': 'enum', 'values': strings}),
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])
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spw.setData(data)
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spw.show()
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if __name__ == '__main__':
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pg.exec()
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