84 lines
2.3 KiB
Python
84 lines
2.3 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Display a non-uniform image.
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This example displays 2-d data as an image with non-uniformly
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distributed sample points.
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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.Qt import QtGui, QtCore
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import pyqtgraph as pg
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import numpy as np
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from pyqtgraph.graphicsItems.GradientEditorItem import Gradients
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from pyqtgraph.graphicsItems.NonUniformImage import NonUniformImage
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RPM2RADS = 2 * np.pi / 60
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RADS2RPM = 1 / RPM2RADS
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kfric = 1 # [Ws/rad] angular damping coefficient [0;100]
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kfric3 = 1.5e-6 # [Ws3/rad3] angular damping coefficient (3rd order) [0;10-3]
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psi = 0.2 # [Vs] flux linkage [0.001;10]
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res = 5e-3 # [Ohm] resistance [0;100]
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v_ref = 200 # [V] reference DC voltage [0;1000]
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k_v = 5 # linear voltage coefficient [-100;100]
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# create the (non-uniform) scales
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tau = np.array([0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, 200, 220], dtype=np.float32)
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w = np.array([0, 250, 500, 750, 1000, 1500, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000], dtype=np.float32) * RPM2RADS
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v = 380
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# calculate the power losses
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TAU, W = np.meshgrid(tau, w, indexing='ij')
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V = np.ones_like(TAU) * v
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P_loss = kfric * W + kfric3 * W ** 3 + (res * (TAU / psi) ** 2) + k_v * (V - v_ref)
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P_mech = TAU * W
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P_loss[P_mech > 1.5e5] = np.NaN
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# green - orange - red
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Gradients['gor'] = {'ticks': [(0.0, (74, 158, 71)), (0.5, (255, 230, 0)), (1, (191, 79, 76))], 'mode': 'rgb'}
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app = pg.mkQApp("NonUniform Image Example")
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win = QtGui.QMainWindow()
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cw = pg.GraphicsLayoutWidget()
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win.show()
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win.resize(600, 400)
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win.setCentralWidget(cw)
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win.setWindowTitle('pyqtgraph example: Non-uniform Image')
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p = cw.addPlot(title="Power Losses [W]", row=0, col=0)
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lut = pg.HistogramLUTItem(orientation="horizontal")
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p.setMouseEnabled(x=False, y=False)
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cw.nextRow()
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cw.addItem(lut)
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# load the gradient
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lut.gradient.loadPreset('gor')
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image = NonUniformImage(w * RADS2RPM, tau, P_loss.T)
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image.setLookupTable(lut, autoLevel=True)
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image.setZValue(-1)
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p.addItem(image)
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h = image.getHistogram()
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lut.plot.setData(*h)
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p.showGrid(x=True, y=True)
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p.setLabel(axis='bottom', text='Speed [rpm]')
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p.setLabel(axis='left', text='Torque [Nm]')
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# elevate the grid lines
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p.axes['bottom']['item'].setZValue(1000)
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p.axes['left']['item'].setZValue(1000)
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if __name__ == '__main__':
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pg.exec()
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