To reduce complexity, and make it easier to add more images and tests,
the images in the `test-data` repository should be merged with the main
repository. Furthermore, we can remove a lot of the subprocess work in
the image_testing.py file, as we no longer need to have it interact with
git.
The images are not the same. Images were regenerated with Qt6, and now
have proper big and little endian handling thanks to @pijyoi
Second commit is a slightly modified variant of
2e135ab282d6007b34a3854921be54d0e9efb241 authored by @pijyoi
it is to convert qimages to RGBA8888 for testing. Image
files were regenerated images for the big/little handling
Fixed issue with bogus test from test_NonUniformImage and generated a
new image
* refactor out _ndarray_to_qimage()
* combine levels back with lut
* make use of Grayscale8, RGB888 and Indexed8 QImage formats
Grayscale8 and RGB888 images are those that are ready for display
without further processing.
* add Grayscale16
* apply the efflut early for uint16 mono/rgb, uint8 rgb
* ndarray indexing is faster than np.take
* handle uint16 rgb(a) with no levels same as levels=[0, 65535]
* add support for Format_RGBA64
* fix: support colormaps of shape (h, 1)
* check ImageItem uint8 and uint16 QImage formats
* uint16 mono with rgb lut -> RGBX8888
* got width and height swapped in array dimensions
* set ImageItem as row-major
* no need to form a 1d 32-bit lut for array indexing
you can index (y, x) into a lookup table of shape (nentry, 3) or
(nentry, 4) and get an output of shape (y, x, 3) or (y, x, 4)
* Revert "no need to form a 1d 32-bit lut for array indexing"
This reverts commit 45cf3100de.
* distinguish between levels_lut and colors_lut
this allows uint16 images with user lut to be rendered as
Format_Indexed8
* uint8 (1-chan) images should always combine to efflut
this efflut will then be used for Indexed8 format color table.
previously, we would be taking a performance hit with doing a numpy
lookup with levels_lut.
* adapt benchmarks/makeARGB.py to renderImageItem.py
* restructure uint8 and uint16 codepaths
* normalize 1-chan images to ndim==2 earlier up
* refactor long code into functions
* bug: qimage may not be assigned
* fix: assign to self.qimage only if not None
* for uint16, do rescale rather than do levels_lut lookup
* cases 2,3 are already handled
i.e. no more using lut to do rescale of uint16 image data.
* rescale rgb images by computation, not by memory lookup
* setImage() does not take an output argument
* try to be cupy compatible
use "xp" instead of numpy module
* add numba to benchmarking
* fix: lut_big is dtype uint8 with more than 256 entries
* bug: applying colors_lut needs C-order
* support float with no nans
* fix: variable could be uninitialized
* add float32 format tests
* avoid explicitly forcing to C-contiguous
* cache effective lut only if combination took place
every one of the four branches now does its own return.
this makes it easier to follow.
* fix cupy benchmark : typo in renderQImage
* remove for loop of 1 iteration
* use float32 for floating point benchmark
* superceded by renderImageItem.py
* lint
* benchmark without lut conversion
* put the lut onto the substrate
* fix editor complaints
* handle lack of cupy
* leading underscores imply privacy
Co-authored-by: KIU Shueng Chuan <nixchuan@gmail.com>
* added convenience functions to better handle plotting with gradients
* docstring correction, example name correction
* retrying to get documentation format right
* another attempt at cleaning up docs
* Don't hardcode timer type (and docs fixing attempt)
* more docstring re-formatting
* linebreaks in docstrings
* more documentation adjustments
* documentation pass
* some corrections to documentation
* more adjustments to documentation
* again?
* removed some whitespace and redundant blank lines, changed some checks '== None' to 'is None'
* fixed mis-spelling QColor as Qcolor
* Improve HistogramLUTItem docs, a few cosmetic changes
* Initial implementation of horizontally-oriented HistogramLUTItem
- Also adds support in HistogramLUTWidget
- Fixes AxisItem orientation bug for vertical orientation
- Make use of GradientEditorItem orientation (fixes another bug for
vertical orientation)
- Use horizontal orientation in an example for demonstration
* Remove unused HistogramLUTItem option
* A few more minor fixups
* Copy paste bug
* Use f-strings
* Update from review and a couple more minor updates
* Woops
* Add doc for orientation arg
* Add top/bottom orientation to doc. Expand on levelMode doc a bit
* do not cache the cupy so the config option can be set later
* getCupy will always return None if the option is not set
* test of failing behavior
* divorce skip from option; restore option after test
* implement rescale using numba
* workaround to pass test_makeARGB.py
* key on (input, output) manually
* remove minimum version check
* signature needs to be a list of signatures
numba considers it a mistake for single-item non-list but works around
it internally
* add numba test to test_makeARGB.py
* add numba as dependency in CI
* handle properly the case where useNumba was already True
* restore useCupy setting after test
* filter numba nan warning
* don't make changes to test_cupy_makeARGB_...
This change makes use of QPointF methods which perform faster than the python
equivalent methods. Furthermore, some tests are added.
* Set __slots__ to empty tuple for pg.Point
* Make Point.angle() behave as Vector.angle()
Static code checker identified multiple places where a file is opened
but is not necessarily closed. This commit addressed that with the
exception of RemoteGraphicsView.py
In a few places in the library, we are doing the conversion from radians
to degrees just so we can call QTransform.rotate(), but there is a
QTransform.rotateRadians() method which would be more suitable, thus
making it so we do not have to handle the conversions ourselves
python any and all are able to break early the moment they come across a
member of the iterable that meets the condition; but having a list
comprehension nested within breaks that ability to exit early, as the
list comprehension has to finish being constructed first before it can
be evaluated
Various places in the library attempt to check if scalars are finite
via numpy methods, which are intended to be used on numpy arrays. Using
the math module equivalent functions on scalars is significantly faster.
In a few places, I also use numpy methods explicitly (np.all vs. all)
Many places in the library were doing radian to degree conversion
via the manual calculation. Doing timeit benchmarks on my system, I
am able to get a 4x speedup by using math.degrees or math.radians
instead
Significant performance issues have been identified with np.clip
and thus clip_array was created to speed up the operation. In addition
clip_scalar was created to clip a scalar value between two other values
this commit replaces many uses of np.clip from operating on scalars to
using clip_scalar instead
