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76 lines
2.5 KiB
Python
76 lines
2.5 KiB
Python
"""Benchmark the pyqtgraph 0.14 OpenGL viewport against the raster path.
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Measures *render* cost only: the curve data is generated up front and cycled
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frame to frame, so numpy work does not pollute the timing. vsync is disabled
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via the swap interval so the OpenGL path is not pinned to the display refresh.
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python gpu_bench.py [n_points] [n_curves]
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"""
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import sys
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import time
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import numpy as np
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import pyqtgraph as pg
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from qtpy import QtCore, QtGui, QtWidgets
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N_POINTS = int(sys.argv[1]) if len(sys.argv) > 1 else 100_000
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N_CURVES = int(sys.argv[2]) if len(sys.argv) > 2 else 3
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FRAMES = 60
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N_PRESET = 10
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def _bench(use_opengl: bool, label: str, datasets, x) -> float:
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pg.setConfigOption("useOpenGL", use_opengl)
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pg.setConfigOption("enableExperimental", use_opengl)
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win = pg.GraphicsLayoutWidget()
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win.resize(1200, 800)
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plot = win.addPlot()
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curves = []
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for c in range(N_CURVES):
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curve = pg.PlotDataItem(pen=pg.mkPen(pg.intColor(c), width=1))
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plot.addItem(curve)
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curves.append(curve)
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plot.enableAutoRange(False)
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plot.setXRange(0, N_POINTS)
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plot.setYRange(-2, 2)
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win.show()
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deadline = time.perf_counter() + 1.0
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while time.perf_counter() < deadline:
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QtWidgets.QApplication.processEvents()
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viewport = win.viewport().__class__.__name__
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start = time.perf_counter()
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for i in range(FRAMES):
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for c, curve in enumerate(curves):
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curve.setData(x, datasets[(i + c) % N_PRESET])
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win.viewport().repaint()
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QtWidgets.QApplication.processEvents()
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elapsed = time.perf_counter() - start
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win.close()
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fps = FRAMES / elapsed
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print(f" {label:<26} viewport={viewport:<22} {fps:7.1f} fps ({1000 / fps:6.1f} ms/frame)")
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return fps
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if __name__ == "__main__":
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# disable vsync before the QApplication so QOpenGLWidget is not capped at ~60 Hz
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fmt = QtGui.QSurfaceFormat.defaultFormat()
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fmt.setSwapInterval(0)
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QtGui.QSurfaceFormat.setDefaultFormat(fmt)
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app = QtWidgets.QApplication(sys.argv)
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print(f"pyqtgraph {pg.__version__} | Qt {QtCore.qVersion()} | swapInterval=0")
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print(f"{N_CURVES} curves x {N_POINTS:,} points, {FRAMES} frames (data pre-generated)\n")
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x = np.arange(N_POINTS, dtype=np.float64)
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rng = np.random.default_rng(0)
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datasets = [np.sin(x * 0.001 + k) + rng.normal(0, 0.1, N_POINTS) for k in range(N_PRESET)]
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raster = _bench(False, "raster (QPainter)", datasets, x)
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opengl = _bench(True, "opengl (QOpenGLWidget)", datasets, x)
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print(f" -> speedup {opengl / raster:.2f}x")
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