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# /*##########################################################################
#
# Copyright (c) 2021-2023 European Synchrotron Radiation Facility
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# ###########################################################################*/
"""This module provides the :class:`ImageDataAggregated` items of the :class:`Plot`.
"""
__authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "07/07/2021"
import enum
import logging
from typing import Tuple, Union
import warnings
import numpy
from ....utils.enum import Enum as _Enum
from ....utils.proxy import docstring
from .axis import Axis
from .core import ItemChangedType
from .image import ImageDataBase
from ._pick import PickingResult
_logger = logging.getLogger(__name__)
class ImageDataAggregated(ImageDataBase):
"""Item displaying an image as a density map."""
@enum.unique
class Aggregation(_Enum):
NONE = "none"
"Do not aggregate data, display as is (default)"
MAX = "max"
"Aggregates elements with max (ignore NaNs)"
MEAN = "mean"
"Aggregates elements with mean (ignore NaNs)"
MIN = "min"
"Aggregates elements with min (ignore NaNs)"
def __init__(self):
super().__init__()
self.__cacheLODData = {}
self.__currentLOD = 0, 0
self.__aggregationMode = self.Aggregation.NONE
def setAggregationMode(self, mode: Union[str, Aggregation]):
"""Set the aggregation method used to reduce the data to screen resolution.
:param Aggregation mode: The aggregation method
"""
aggregationMode = self.Aggregation.from_value(mode)
if aggregationMode != self.__aggregationMode:
self.__aggregationMode = aggregationMode
self.__cacheLODData = {} # Clear cache
self._updated(ItemChangedType.VISUALIZATION_MODE)
def getAggregationMode(self) -> Aggregation:
"""Returns the currently used aggregation method."""
return self.__aggregationMode
def _addBackendRenderer(self, backend):
"""Update backend renderer"""
plot = self.getPlot()
assert plot is not None
if not self._isPlotLinear(plot):
# Do not render with non linear scales
return None
data = self.getData(copy=False)
if data.size == 0:
return None # No data to display
aggregationMode = self.getAggregationMode()
if aggregationMode == self.Aggregation.NONE: # Pass data as it is
displayedData = data
scale = self.getScale()
else: # Aggregate data according to level of details
if aggregationMode == self.Aggregation.MAX:
aggregator = numpy.nanmax
elif aggregationMode == self.Aggregation.MEAN:
aggregator = numpy.nanmean
elif aggregationMode == self.Aggregation.MIN:
aggregator = numpy.nanmin
else:
_logger.error("Unsupported aggregation mode")
return None
lodx, lody = self._getLevelOfDetails()
if (lodx, lody) not in self.__cacheLODData:
height, width = data.shape
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=RuntimeWarning)
self.__cacheLODData[(lodx, lody)] = aggregator(
data[
: (height // lody) * lody, : (width // lodx) * lodx
].reshape(height // lody, lody, width // lodx, lodx),
axis=(1, 3),
)
self.__currentLOD = lodx, lody
displayedData = self.__cacheLODData[self.__currentLOD]
sx, sy = self.getScale()
scale = sx * lodx, sy * lody
return backend.addImage(
displayedData,
origin=self.getOrigin(),
scale=scale,
colormap=self._getColormapForRendering(),
alpha=self.getAlpha(),
)
def _getPixelSizeInData(self, axis="left"):
"""Returns the size of a pixel in plot data coordinates
:param str axis: Y axis to use in: 'left' (default), 'right'
:return:
Size (width, height) of a Qt pixel in data coordinates.
Size is None if it cannot be computed
:rtype: Union[List[float],None]
"""
assert axis in ("left", "right")
plot = self.getPlot()
if plot is None:
return None
xaxis = plot.getXAxis()
yaxis = plot.getYAxis(axis)
if xaxis.getScale() != Axis.LINEAR or yaxis.getScale() != Axis.LINEAR:
raise RuntimeError("Only available with linear axes")
xmin, xmax = xaxis.getLimits()
ymin, ymax = yaxis.getLimits()
width, height = plot.getPlotBoundsInPixels()[2:]
if width == 0 or height == 0:
return None
else:
return (xmax - xmin) / width, (ymax - ymin) / height
def _getLevelOfDetails(self) -> Tuple[int, int]:
"""Return current level of details the image is displayed with."""
plot = self.getPlot()
if plot is None or not self._isPlotLinear(plot):
return 1, 1 # Fallback to bas LOD
sx, sy = self.getScale()
xUnitPerPixel, yUnitPerPixel = self._getPixelSizeInData()
lodx = max(1, int(numpy.ceil(xUnitPerPixel / sx)))
lody = max(1, int(numpy.ceil(yUnitPerPixel / sy)))
return lodx, lody
@docstring(ImageDataBase)
def setData(self, data, copy=True):
self.__cacheLODData = {} # Reset cache
super().setData(data)
@docstring(ImageDataBase)
def _setPlot(self, plot):
"""Refresh image when plot limits change"""
previousPlot = self.getPlot()
if previousPlot is not None:
for axis in (previousPlot.getXAxis(), previousPlot.getYAxis()):
axis.sigLimitsChanged.disconnect(self.__plotLimitsChanged)
super()._setPlot(plot)
if plot is not None:
for axis in (plot.getXAxis(), plot.getYAxis()):
axis.sigLimitsChanged.connect(self.__plotLimitsChanged)
def __plotLimitsChanged(self):
"""Trigger update if level of details has changed"""
if (
self.getAggregationMode() != self.Aggregation.NONE
and self.__currentLOD != self._getLevelOfDetails()
):
self._updated()
@docstring(ImageDataBase)
def pick(self, x, y):
result = super().pick(x, y)
if result is None:
return None
# Compute indices in initial data
plot = self.getPlot()
if plot is None:
return None
dataPos = plot.pixelToData(x, y, axis="left", check=True)
if dataPos is None:
return None # Outside plot area
ox, oy = self.getOrigin()
sx, sy = self.getScale()
col = int((dataPos[0] - ox) / sx)
row = int((dataPos[1] - oy) / sy)
height, width = self.getData(copy=False).shape[:2]
if 0 <= col < width and 0 <= row < height:
return PickingResult(self, ((row,), (col,)))
return None
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