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from time import perf_counter
import numpy as np
import pyqtgraph as pg
app = pg.mkQApp()
plt = pg.PlotWidget()
app.processEvents()
## Putting this at the beginning or end does not have much effect
plt.show()
## The auto-range is recomputed after each item is added,
## so disabling it before plotting helps
plt.enableAutoRange(False, False)
def plot():
start = perf_counter()
n = 15
pts = 100
x = np.linspace(0, 0.8, pts)
y = np.random.random(size=pts)*0.8
for i in range(n):
for j in range(n):
## calling PlotWidget.plot() generates a PlotDataItem, which
## has a bit more overhead than PlotCurveItem, which is all
## we need here. This overhead adds up quickly and makes a big
## difference in speed.
plt.addItem(pg.PlotCurveItem(x=x+i, y=y+j))
dt = perf_counter() - start
print(f"Create plots took: {dt * 1000:.3f} ms")
## Plot and clear 5 times, printing the time it took
for _ in range(5):
plt.clear()
plot()
app.processEvents()
plt.autoRange()
def fastPlot():
## Different approach: generate a single item with all data points.
## This runs many times faster.
start = perf_counter()
n = 15
pts = 100
x = np.linspace(0, 0.8, pts)
y = np.random.random(size=pts)*0.8
shape = (n, n, pts)
xdata = np.empty(shape)
xdata[:] = x + np.arange(shape[1]).reshape((1,-1,1))
ydata = np.empty(shape)
ydata[:] = y + np.arange(shape[0]).reshape((-1,1,1))
conn = np.ones(shape, dtype=bool)
conn[...,-1] = False # make sure plots are disconnected
item = pg.PlotCurveItem()
item.setData(xdata.ravel(), ydata.ravel(), connect=conn.ravel())
plt.addItem(item)
dt = perf_counter() - start
print("Create plots took: %0.3fms" % (dt*1000))
## Plot and clear 5 times, printing the time it took
for _ in range(5):
plt.clear()
fastPlot()
app.processEvents()
plt.autoRange()
if __name__ == '__main__':
pg.exec()
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