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Expose number of subsamples in ImageItem auto-level determination (#1638)

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* exposed number of subsamples in auto-level determination

* Removing print statement at @NilsNemitz's request

* make levelSamples count pixels, not pixels * channels

* minimum number of samples can be 2 if we look at pixels anyway

* adjusted minimum levelSamples to 4: Otherwise a 2x2 image downsamples to a single pixel

* extended docstring for level to make the user aware of auto-level subsampling

* subsample towards square array for auto-leveling

* eliminated duplicated code between level downsampling and samples and QuickMinMax method

Co-authored-by: Ogi Moore <ognyan.moore@gmail.com>
This commit is contained in:
Nils Nemitz 2021-06-09 02:25:47 +09:00 committed by GitHub
parent 823988d51c
commit f002d70adc
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1 changed files with 18 additions and 10 deletions
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pyqtgraph/graphicsItems/ImageItem.py
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@ -341,8 +341,14 @@ class ImageItem(GraphicsObject):
or dark points in the data set.
If False, the search will be omitted.
The default is `False` if a ``levels`` keyword argument is given, and `True` otherwise.
levelSamples: int, default 65536
When determining minimum and maximum values, ImageItem
only inspects a subset of pixels no larger than this number.
Setting this larger than the total number of pixels considers all values.
"""
profile = debug.Profiler()
@ -378,10 +384,8 @@ class ImageItem(GraphicsObject):
else:
autoLevels = True
if autoLevels:
img = self.image
while img.size > 2**16:
img = img[::2, ::2]
mn, mx = self._xp.nanmin(img), self._xp.nanmax(img)
level_samples = kargs.pop('levelSamples', 2**16)
mn, mx = self.quickMinMax( targetSize=level_samples )
# mn and mx can still be NaN if the data is all-NaN
if mn == mx or self._xp.isnan(mn) or self._xp.isnan(mx):
mn = 0
@ -457,11 +461,15 @@ class ImageItem(GraphicsObject):
Returns (`min`, `max`).
"""
data = self.image
while data.size > targetSize:
ax = self._xp.argmax(data.shape)
sl = [slice(None)] * data.ndim
sl[ax] = slice(None, None, 2)
data = data[sl]
if targetSize < 2: # keep at least two pixels
targetSize = 2
while True:
h, w = data.shape[:2]
if h * w <= targetSize: break
if h > w:
data = data[::2, ::] # downsample first axis
else:
data = data[::, ::2] # downsample second axis
return self._xp.nanmin(data), self._xp.nanmax(data)
def updateImage(self, *args, **kargs):