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pyqtgraph/examples/VideoSpeedTest.py

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Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
# -*- coding: utf-8 -*-
Updates to IsocurveItem, added isocurve example minor updates for other examples
2012-04-04 16:22:43 +00:00
"""
Tests the speed of image updates for an ImageItem and RawImageWidget.
The speed will generally depend on the type of data being shown, whether
it is being scaled and/or converted by lookup table, and whether OpenGL
is used by the view widget
"""
modify environment to choose binding the Example App allows the user to choose a binding and a graphics system to use to execute an example. issue 1: setGraphicsSystem is obsolete and the method no longer exists. thus selecting a graphics system causes an error. issue 2: the choice of binding to use is passed as an extra command line argument to be parsed by initExample. this is problematic for examples that use argparse, such as VideoSpeedTest.py issue 3: if the user has set PYQTGRAPH_QT_LIB, that takes precedence over the choice made in the Example App. this patch fixes the above 3 issues by setting PYQTGRAPH_QT_LIB in the child process' environment and removing the old parsing of the command line arguments
2021-02-22 10:03:06 +00:00
## Add path to library (just for examples; you do not need this)
import initExample
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
import argparse
import sys
Updates to IsocurveItem, added isocurve example minor updates for other examples
2012-04-04 16:22:43 +00:00
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
import numpy as np
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
import pyqtgraph as pg
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
from pyqtgraph.Qt import QtGui, QtCore, QT_LIB
Remove the use of pyqtgraph.ptime (#1914) * Remove the use of pyqtgraph.ptime With us supporting python3.7+, we have no more need for the ptime module and can instead safely use perf_counter for everything. * Address small issues PR turned up * Reword comment in ImageView
2021-07-23 03:57:50 +00:00
from time import perf_counter
Now detects and switches between PyQt / PySide automatically; no need to distribute different versions of the library anymore.
2012-09-09 23:07:36 +00:00
switch to row-major order
2021-03-02 01:18:52 +00:00
pg.setConfigOption('imageAxisOrder', 'row-major')
import template files using importlib this lets us support the various bindings w/o having to add binding specific code. it breaks PyQt4 support since PyQt4 template files are suffixed as "_pyqt" rather than "_pyqt4"
2021-01-14 03:15:34 +00:00
import importlib
ui_template = importlib.import_module(f'VideoTemplate_{QT_LIB.lower()}')
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
try:
import cupy as cp
pg.setConfigOption("useCupy", True)
_has_cupy = True
except ImportError:
cp = None
_has_cupy = False
VideoSpeedTest.py : Add numba checkbox
2021-05-07 07:35:27 +00:00
try:
import numba
_has_numba = True
except ImportError:
numba = None
_has_numba = False
disable opengl vsync for benchmarking
2021-02-22 08:13:53 +00:00
try:
from pyqtgraph.widgets.RawImageWidget import RawImageGLWidget
except ImportError:
RawImageGLWidget = None
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
parser = argparse.ArgumentParser(description="Benchmark for testing video performance")
parser.add_argument('--cuda', default=False, action='store_true', help="Use CUDA to process on the GPU", dest="cuda")
parser.add_argument('--dtype', default='uint8', choices=['uint8', 'uint16', 'float'], help="Image dtype (uint8, uint16, or float)")
parser.add_argument('--frames', default=3, type=int, help="Number of image frames to generate (default=3)")
parser.add_argument('--image-mode', default='mono', choices=['mono', 'rgb'], help="Image data mode (mono or rgb)", dest='image_mode')
parser.add_argument('--levels', default=None, type=lambda s: tuple([float(x) for x in s.split(',')]), help="min,max levels to scale monochromatic image dynamic range, or rmin,rmax,gmin,gmax,bmin,bmax to scale rgb")
parser.add_argument('--lut', default=False, action='store_true', help="Use color lookup table")
parser.add_argument('--lut-alpha', default=False, action='store_true', help="Use alpha color lookup table", dest='lut_alpha')
parser.add_argument('--size', default='512x512', type=lambda s: tuple([int(x) for x in s.split('x')]), help="WxH image dimensions default='512x512'")
args = parser.parse_args(sys.argv[1:])
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
disable opengl vsync for benchmarking
2021-02-22 08:13:53 +00:00
if RawImageGLWidget is not None:
# don't limit frame rate to vsync
sfmt = QtGui.QSurfaceFormat()
sfmt.setSwapInterval(0)
QtGui.QSurfaceFormat.setDefaultFormat(sfmt)
Fix windows hidpi (#1516) * set environment variables before starting QApp * fix-422 * Better support of hidpi * Fix Typo in App-Name * Remove fontScaleFactor bits * Add documenation for hidpi displays * Fix pg not defined
2021-01-27 18:59:07 +00:00
app = pg.mkQApp("Video Speed Test Example")
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
win = QtGui.QMainWindow()
python3 fixes cleaned up examples
2013-02-25 04:09:03 +00:00
win.setWindowTitle('pyqtgraph example: VideoSpeedTest')
import template files using importlib this lets us support the various bindings w/o having to add binding specific code. it breaks PyQt4 support since PyQt4 template files are suffixed as "_pyqt" rather than "_pyqt4"
2021-01-14 03:15:34 +00:00
ui = ui_template.Ui_MainWindow()
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
ui.setupUi(win)
win.show()
Fix VideoSpeedTest to disable RawImageGLWidget when openGL is unavailable
2016-10-26 16:26:01 +00:00
disable opengl vsync for benchmarking
2021-02-22 08:13:53 +00:00
if RawImageGLWidget is None:
Fix VideoSpeedTest to disable RawImageGLWidget when openGL is unavailable
2016-10-26 16:26:01 +00:00
ui.rawGLRadio.setEnabled(False)
ui.rawGLRadio.setText(ui.rawGLRadio.text() + " (OpenGL not available)")
else:
ui.rawGLImg = RawImageGLWidget()
ui.stack.addWidget(ui.rawGLImg)
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
# read in CLI args
ui.cudaCheck.setChecked(args.cuda and _has_cupy)
ui.cudaCheck.setEnabled(_has_cupy)
VideoSpeedTest.py : Add numba checkbox
2021-05-07 07:35:27 +00:00
ui.numbaCheck.setChecked(_has_numba and pg.getConfigOption("useNumba"))
ui.numbaCheck.setEnabled(_has_numba)
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
ui.framesSpin.setValue(args.frames)
ui.widthSpin.setValue(args.size[0])
ui.heightSpin.setValue(args.size[1])
ui.dtypeCombo.setCurrentText(args.dtype)
ui.rgbCheck.setChecked(args.image_mode=='rgb')
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
ui.maxSpin1.setOpts(value=255, step=1)
ui.minSpin1.setOpts(value=0, step=1)
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
levelSpins = [ui.minSpin1, ui.maxSpin1, ui.minSpin2, ui.maxSpin2, ui.minSpin3, ui.maxSpin3]
if args.cuda and _has_cupy:
xp = cp
else:
xp = np
if args.levels is None:
ui.scaleCheck.setChecked(False)
ui.rgbLevelsCheck.setChecked(False)
else:
ui.scaleCheck.setChecked(True)
if len(args.levels) == 2:
ui.rgbLevelsCheck.setChecked(False)
ui.minSpin1.setValue(args.levels[0])
ui.maxSpin1.setValue(args.levels[1])
elif len(args.levels) == 6:
ui.rgbLevelsCheck.setChecked(True)
for spin,val in zip(levelSpins, args.levels):
spin.setValue(val)
else:
raise ValueError("levels argument must be 2 or 6 comma-separated values (got %r)" % (args.levels,))
ui.lutCheck.setChecked(args.lut)
ui.alphaCheck.setChecked(args.lut_alpha)
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
Performance enhancements - HistogramLUTItem avoids using lookup table if possible - GradientEditorItem has a method to ask whether the gradient is trivial (can be applied without the use of a lookup table) - ROI, LinearRegionItem, InfiniteLine no longer redraw for every mouse movement
2012-04-04 13:29:35 +00:00
#ui.graphicsView.useOpenGL() ## buggy, but you can try it if you need extra speed.
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
vb = pg.ViewBox()
ui.graphicsView.setCentralItem(vb)
vb.setAspectLocked()
img = pg.ImageItem()
vb.addItem(img)
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
LUT = None
def updateLUT():
global LUT, ui
dtype = ui.dtypeCombo.currentText()
if dtype == 'uint8':
n = 256
else:
n = 4096
LUT = ui.gradient.getLookupTable(n, alpha=ui.alphaCheck.isChecked())
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
if _has_cupy and xp == cp:
LUT = cp.asarray(LUT)
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
ui.gradient.sigGradientChanged.connect(updateLUT)
updateLUT()
ui.alphaCheck.toggled.connect(updateLUT)
def updateScale():
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
global ui, levelSpins
Bugfixes and updates to functions.py: - generalized makeARGB API: can now process arrays of arbitrary shape. - affineSlice automatically converts vector arguments to array - new function applyLookupTable taken from makeARGB - isosurface function returns array Updated VideoSpeedTest example to follow new makeARGB API LayoutWidget: row argument now accepts 'next' as value ParameterTree bugfix: avoid infinite recursion when accessing non-existent attributes ViewBox: avoid exit error caused when cleanup callback is invoked while python is shutting down
2012-11-23 21:01:25 +00:00
if ui.rgbLevelsCheck.isChecked():
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
for s in levelSpins[2:]:
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
s.setEnabled(True)
else:
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
for s in levelSpins[2:]:
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
s.setEnabled(False)
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
updateScale()
Bugfixes and updates to functions.py: - generalized makeARGB API: can now process arrays of arbitrary shape. - affineSlice automatically converts vector arguments to array - new function applyLookupTable taken from makeARGB - isosurface function returns array Updated VideoSpeedTest example to follow new makeARGB API LayoutWidget: row argument now accepts 'next' as value ParameterTree bugfix: avoid infinite recursion when accessing non-existent attributes ViewBox: avoid exit error caused when cleanup callback is invoked while python is shutting down
2012-11-23 21:01:25 +00:00
ui.rgbLevelsCheck.toggled.connect(updateScale)
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
cache = {}
def mkData():
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
with pg.BusyCursor():
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
global data, cache, ui, xp
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
frames = ui.framesSpin.value()
width = ui.widthSpin.value()
height = ui.heightSpin.value()
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
cacheKey = (ui.dtypeCombo.currentText(), ui.rgbCheck.isChecked(), frames, width, height)
if cacheKey not in cache:
if cacheKey[0] == 'uint8':
dt = xp.uint8
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
loc = 128
scale = 64
mx = 255
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
elif cacheKey[0] == 'uint16':
dt = xp.uint16
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
loc = 4096
scale = 1024
fix: max value of uint16 is 65535
2021-03-02 00:53:44 +00:00
mx = 2**16 - 1
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
elif cacheKey[0] == 'float':
Do not use numpy deprecated type aliases
2021-02-12 22:03:00 +00:00
dt = xp.float32
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
loc = 1.0
scale = 0.1
Fix UnboundLocalError in VideoSpeedTest.
2019-09-09 04:27:29 +00:00
mx = 1.0
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
else:
raise ValueError(f"unable to handle dtype: {cacheKey[0]}")
reduce memory usage during data generation random.normal() generates as float64 and gets converted to a smaller dtype. generating all the needed data in a single call thus uses a lot more memory than is necessary. this changes it such that smaller chunks are generated. data clipping is also changed to be in-place. the gaussian filtering which gave the video a washed-out look is also removed. this also contributed to data generation time.
2021-03-02 01:05:52 +00:00
switch to row-major order
2021-03-02 01:18:52 +00:00
chan_shape = (height, width)
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
if ui.rgbCheck.isChecked():
reduce memory usage during data generation random.normal() generates as float64 and gets converted to a smaller dtype. generating all the needed data in a single call thus uses a lot more memory than is necessary. this changes it such that smaller chunks are generated. data clipping is also changed to be in-place. the gaussian filtering which gave the video a washed-out look is also removed. this also contributed to data generation time.
2021-03-02 01:05:52 +00:00
frame_shape = chan_shape + (3,)
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
else:
reduce memory usage during data generation random.normal() generates as float64 and gets converted to a smaller dtype. generating all the needed data in a single call thus uses a lot more memory than is necessary. this changes it such that smaller chunks are generated. data clipping is also changed to be in-place. the gaussian filtering which gave the video a washed-out look is also removed. this also contributed to data generation time.
2021-03-02 01:05:52 +00:00
frame_shape = chan_shape
data = xp.empty((frames,) + frame_shape, dtype=dt)
view = data.reshape((-1,) + chan_shape)
for idx in range(view.shape[0]):
subdata = xp.random.normal(loc=loc, scale=scale, size=chan_shape)
# note: gaussian filtering has been removed as it slows down array
# creation greatly.
if cacheKey[0] != 'float':
xp.clip(subdata, 0, mx, out=subdata)
view[idx] = subdata
switch to row-major order
2021-03-02 01:18:52 +00:00
data[:, 10:50, 10] = mx
data[:, 48, 9:12] = mx
data[:, 47, 8:13] = mx
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
cache = {cacheKey: data} # clear to save memory (but keep one to prevent unnecessary regeneration)
data = cache[cacheKey]
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
updateLUT()
updateSize()
def updateSize():
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
global ui, vb
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
frames = ui.framesSpin.value()
width = ui.widthSpin.value()
height = ui.heightSpin.value()
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
dtype = xp.dtype(str(ui.dtypeCombo.currentText()))
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
rgb = 3 if ui.rgbCheck.isChecked() else 1
ui.sizeLabel.setText('%d MB' % (frames * width * height * rgb * dtype.itemsize / 1e6))
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
vb.setRange(QtCore.QRectF(0, 0, width, height))
def noticeCudaCheck():
global xp, cache
cache = {}
if ui.cudaCheck.isChecked():
if _has_cupy:
xp = cp
else:
xp = np
ui.cudaCheck.setChecked(False)
else:
xp = np
mkData()
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
VideoSpeedTest.py : Add numba checkbox
2021-05-07 07:35:27 +00:00
def noticeNumbaCheck():
pg.setConfigOption('useNumba', _has_numba and ui.numbaCheck.isChecked())
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
mkData()
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
ui.dtypeCombo.currentIndexChanged.connect(mkData)
Bugfixes and updates to functions.py: - generalized makeARGB API: can now process arrays of arbitrary shape. - affineSlice automatically converts vector arguments to array - new function applyLookupTable taken from makeARGB - isosurface function returns array Updated VideoSpeedTest example to follow new makeARGB API LayoutWidget: row argument now accepts 'next' as value ParameterTree bugfix: avoid infinite recursion when accessing non-existent attributes ViewBox: avoid exit error caused when cleanup callback is invoked while python is shutting down
2012-11-23 21:01:25 +00:00
ui.rgbCheck.toggled.connect(mkData)
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
ui.widthSpin.editingFinished.connect(mkData)
ui.heightSpin.editingFinished.connect(mkData)
ui.framesSpin.editingFinished.connect(mkData)
ui.widthSpin.valueChanged.connect(updateSize)
ui.heightSpin.valueChanged.connect(updateSize)
ui.framesSpin.valueChanged.connect(updateSize)
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
ui.cudaCheck.toggled.connect(noticeCudaCheck)
VideoSpeedTest.py : Add numba checkbox
2021-05-07 07:35:27 +00:00
ui.numbaCheck.toggled.connect(noticeNumbaCheck)
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
ptr = 0
Remove the use of pyqtgraph.ptime (#1914) * Remove the use of pyqtgraph.ptime With us supporting python3.7+, we have no more need for the ptime module and can instead safely use perf_counter for everything. * Address small issues PR turned up * Reword comment in ImageView
2021-07-23 03:57:50 +00:00
lastTime = perf_counter()
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
fps = None
def update():
global ui, ptr, lastTime, fps, LUT, img
if ui.lutCheck.isChecked():
useLut = LUT
else:
useLut = None
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
downsample = ui.downsampleCheck.isChecked()
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
if ui.scaleCheck.isChecked():
Bugfixes and updates to functions.py: - generalized makeARGB API: can now process arrays of arbitrary shape. - affineSlice automatically converts vector arguments to array - new function applyLookupTable taken from makeARGB - isosurface function returns array Updated VideoSpeedTest example to follow new makeARGB API LayoutWidget: row argument now accepts 'next' as value ParameterTree bugfix: avoid infinite recursion when accessing non-existent attributes ViewBox: avoid exit error caused when cleanup callback is invoked while python is shutting down
2012-11-23 21:01:25 +00:00
if ui.rgbLevelsCheck.isChecked():
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
useScale = [
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
[ui.minSpin1.value(), ui.maxSpin1.value()],
[ui.minSpin2.value(), ui.maxSpin2.value()],
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
[ui.minSpin3.value(), ui.maxSpin3.value()]]
else:
useScale = [ui.minSpin1.value(), ui.maxSpin1.value()]
else:
useScale = None
if ui.rawRadio.isChecked():
ui.rawImg.setImage(data[ptr%data.shape[0]], lut=useLut, levels=useScale)
experimental GL video widget temporary fix for text parameter ignoring expanded option Don't use os.EX_OK in pg.exit()
2013-07-10 04:02:16 +00:00
ui.stack.setCurrentIndex(1)
elif ui.rawGLRadio.isChecked():
ui.rawGLImg.setImage(data[ptr%data.shape[0]], lut=useLut, levels=useScale)
ui.stack.setCurrentIndex(2)
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
else:
Added automatic image downsampling (disabled by default) - Reduces aliasing when zoomed out - Improves performance and memory usage for large images Merge branch 'image_downsampling' into develop Conflicts: pyqtgraph/graphicsItems/ImageItem.py
2014-02-18 01:48:22 +00:00
img.setImage(data[ptr%data.shape[0]], autoLevels=False, levels=useScale, lut=useLut, autoDownsample=downsample)
experimental GL video widget temporary fix for text parameter ignoring expanded option Don't use os.EX_OK in pg.exit()
2013-07-10 04:02:16 +00:00
ui.stack.setCurrentIndex(0)
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
#img.setImage(data[ptr%data.shape[0]], autoRange=False)
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
ptr += 1
Remove the use of pyqtgraph.ptime (#1914) * Remove the use of pyqtgraph.ptime With us supporting python3.7+, we have no more need for the ptime module and can instead safely use perf_counter for everything. * Address small issues PR turned up * Reword comment in ImageView
2021-07-23 03:57:50 +00:00
now = perf_counter()
Imported major changes from acq4 project.
2012-03-02 02:55:32 +00:00
dt = now - lastTime
lastTime = now
if fps is None:
fps = 1.0/dt
else:
s = np.clip(dt*3., 0, 1)
fps = fps * (1-s) + (1.0/dt) * s
ui.fpsLabel.setText('%0.2f fps' % fps)
app.processEvents() ## force complete redraw for every plot
timer = QtCore.QTimer()
timer.timeout.connect(update)
timer.start(0)
Performance enhancement: use CUDA in ImageItem (#1466) * Add CLI args to video speed test for easier / automated benchmarking * use a buffer-qimage so we can avoid allocing so much this should improve performance under windows * playing with numba * oh, mins/maxes in the other order * maybe put the cupy in here and see what happens * pre-alloc for gpu and cpu * handle possibility of not having cupy * no numba in this branch * organize imports * name them after their use, not their expected device * cupy.take does not support clip mode, so do it explicitly * add CUDA option to the VideoSpeedTest * rename private attr xp to _xp * handle resizes at the last moment * cupy is less accepting of lists as args * or somehow range isn't allowed? what histogram is this? * construct the array with python objects * get the python value right away * put LUT into cupy if needed * docstring about cuda toolkit version * better handling and display of missing cuda lib * lint * import need * handle switching between cupy and numpy in a single ImageItem * only use xp when necessary we can now depend on numpy >= 1.17, which means __array_function__-implementing cupy can seamlessly pass into numpy functions. the remaining uses of xp are for our functions which need to allocate new data structures, an operation that has to be substrate-specific. remove empty_cupy; just check if the import succeeded, instead. * use an option to control use of cupy * convert cupy.ceil array to int for easier mathing * RawImageWidget gets to use the getCupy function now, too * raise error to calm linters; rename for clarity * Add Generated Template Files * document things better * cruft removal * warnings to communicate when cupy is expected but somehow broken * playing with settings to suss out timeout * playing with more stuff to suss out timeout * replace with empty list * skip test_ExampleApp on linux+pyside2 only Co-authored-by: Luke Campagnola <luke.campagnola@gmail.com> Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
2021-01-20 05:26:24 +00:00
Merged testing code from Kratz Numerous fixes for python 3 compatibility
2012-12-05 05:25:45 +00:00
if __name__ == '__main__':
change all examples to use pg.exec()
2021-05-13 21:28:22 +00:00
pg.exec()