def xyimage(self, x, y, data, title=None, alpha_mask=None, alpha=None,
background_color=None, colormap=None,
interpolation='linear', eliminate_outliers=None,
xformat='%.1f', yformat='%.1f', zformat='%.1f'):
"""
Make an xyimage `plot item` (image with non-linear X/Y axes) from data
(:py:class:`guiqwt.image.XYImageItem` object)
* x: 1D NumPy array (or tuple, list: will be converted to array)
* y: 1D NumPy array (or tuple, list: will be converted to array
* data: 2D NumPy array (image pixel data)
* title: image title (optional)
* interpolation: 'nearest', 'linear' (default), 'antialiasing' (5x5)
"""
param = XYImageParam(title=_("Image"), icon='image.png')
self.__set_image_param(param, title, alpha_mask, alpha, interpolation,
background=background_color, colormap=colormap,
xformat=xformat, yformat=yformat,
zformat=zformat)
if isinstance(x, (list, tuple)):
x = array(x)
if isinstance(y, (list, tuple)):
y = array(y)
image = XYImageItem(x, y, data, param)
if eliminate_outliers is not None:
image.set_lut_range(lut_range_threshold(image, 256,
eliminate_outliers))
return image
def set_item(self, item):
"""Set associated item -- must be a TrImageItem object"""
assert isinstance(item, TrImageItem)
self.item = item
self.item_original_state = (item.can_select(),
item.can_move(),
item.can_resize(),
item.can_rotate())
self.item_original_crop = item.get_crop()
self.item_original_transform = item.get_transform()
self.item.set_selectable(True)
self.item.set_movable(True)
self.item.set_resizable(False)
self.item.set_rotatable(True)
item.set_lut_range(lut_range_threshold(item, 256, 2.))
item.set_interpolation(INTERP_LINEAR)
plot = self.get_plot()
plot.add_item(self.item)
# Setting the item as active item (even if the cropping rectangle item
# will also be set as active item just below), for the image tools to
# register this item (contrast, ...):
plot.set_active_item(self.item)
self.item.unselect()
def trimage(self, data=None, filename=None, title=None, alpha_mask=None,
alpha=None, background_color=None, colormap=None,
x0=0.0, y0=0.0, angle=0.0, dx=1.0, dy=1.0,
interpolation='linear', eliminate_outliers=None,
xformat='%.1f', yformat='%.1f', zformat='%.1f'):
"""
Make a transformable image `plot item` (image with an arbitrary
affine transform)
(:py:class:`guiqwt.image.TrImageItem` object)
* data: 2D NumPy array (image pixel data)
* filename: image filename (if data is not specified)
* title: image title (optional)
* x0, y0: position
* angle: angle (radians)
* dx, dy: pixel size along X and Y axes
* interpolation: 'nearest', 'linear' (default), 'antialiasing' (5x5)
"""
param = TrImageParam(title=_("Image"), icon='image.png')
data, filename, title = self._get_image_data(data, filename, title,
to_grayscale=True)
self.__set_image_param(param, title, alpha_mask, alpha, interpolation,
background=background_color, colormap=colormap,
x0=x0, y0=y0, angle=angle, dx=dx, dy=dy,
xformat=xformat, yformat=yformat,
zformat=zformat)
image = TrImageItem(data, param)
image.set_filename(filename)
if eliminate_outliers is not None:
image.set_lut_range(lut_range_threshold(image, 256,
eliminate_outliers))
return image
def maskedimage(
self,
data=None,
mask=None,
filename=None,
title=None,
alpha_mask=False,
alpha=1.0,
xdata=[None, None],
ydata=[None, None],
pixel_size=None,
center_on=None,
background_color=None,
colormap=None,
show_mask=False,
fill_value=None,
interpolation="linear",
eliminate_outliers=None,
xformat="%.1f",
yformat="%.1f",
zformat="%.1f",
):
"""
Make a masked image `plot item` from data
(:py:class:`guiqwt.image.MaskedImageItem` object)
"""
assert isinstance(xdata, (tuple, list)) and len(xdata) == 2
assert isinstance(ydata, (tuple, list)) and len(ydata) == 2
param = MaskedImageParam(title=_("Image"), icon="image.png")
data, filename, title = self._get_image_data(data, filename, title, to_grayscale=True)
assert data.ndim == 2, "Data must have 2 dimensions"
if pixel_size is None:
assert center_on is None, "Ambiguous parameters: both `center_on`" " and `xdata`/`ydata` were specified"
xmin, xmax = xdata
ymin, ymax = ydata
else:
xmin, xmax, ymin, ymax = self.compute_bounds(data, pixel_size, center_on)
self.__set_image_param(
param,
title,
alpha_mask,
alpha,
interpolation,
background=background_color,
colormap=colormap,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
show_mask=show_mask,
fill_value=fill_value,
xformat=xformat,
yformat=yformat,
zformat=zformat,
)
image = MaskedImageItem(data, mask, param)
image.set_filename(filename)
if eliminate_outliers is not None:
image.set_lut_range(lut_range_threshold(image, 256, eliminate_outliers))
return image
def xyimage(self, taurusmodel=None, **kwargs):
if taurusmodel is None:
return guiqwt.builder.PlotItemBuilder.xyimage(self, **kwargs)
title = kwargs.get('title', taurusmodel)
data = kwargs.get('data', None)
alpha_mask = kwargs.get('alpha_mask', None)
alpha = kwargs.get('alpha', None)
background_color = kwargs.get('background_color', None)
colormap = kwargs.get('colormap', None)
interpolation = kwargs.get('interpolation', 'linear')
eliminate_outliers = kwargs.get('eliminate_outliers', None)
xformat = kwargs.get('xformat', '%.1f')
yformat = kwargs.get('yformat', '%.1f')
zformat = kwargs.get('zformat', '%.1f')
if data is None:
x = y = None
else:
x = numpy.arange(data.shape[0])
y = numpy.arange(data.shape[1])
data = numpy.ones((251, 251))
x, y = numpy.arange(251) * 333, numpy.arange(251) * 1000
param = XYImageParam(title=_("Image"), icon='image.png')
self.set_image_param(param,
title,
alpha_mask,
alpha,
interpolation,
background=background_color,
colormap=colormap,
xformat=xformat,
yformat=yformat,
zformat=zformat)
image = TaurusXYImageItem(param)
image.setModel(taurusmodel)
if eliminate_outliers is not None:
image.set_lut_range(
lut_range_threshold(image, 256, eliminate_outliers))
return image
def image(self, data=None, filename=None, title=None, alpha_mask=None,
alpha=None, background_color=None, colormap=None,
xdata=[None, None], ydata=[None, None],
pixel_size=None, center_on=None,
interpolation='linear', eliminate_outliers=None,
xformat='%.1f', yformat='%.1f', zformat='%.1f'):
"""
Make an image `plot item` from data
(:py:class:`guiqwt.image.ImageItem` object or
:py:class:`guiqwt.image.RGBImageItem` object if data has 3 dimensions)
"""
assert isinstance(xdata, (tuple, list)) and len(xdata) == 2
assert isinstance(ydata, (tuple, list)) and len(ydata) == 2
param = ImageParam(title=_("Image"), icon='image.png')
data, filename, title = self._get_image_data(data, filename, title,
to_grayscale=True)
if data.ndim == 3:
return self.rgbimage(data=data, filename=filename, title=title,
alpha_mask=alpha_mask, alpha=alpha)
assert data.ndim == 2, "Data must have 2 dimensions"
if pixel_size is None:
assert center_on is None, "Ambiguous parameters: both `center_on`"\
" and `xdata`/`ydata` were specified"
xmin, xmax = xdata
ymin, ymax = ydata
else:
xmin, xmax, ymin, ymax = self.compute_bounds(data, pixel_size,
center_on)
self.__set_image_param(param, title, alpha_mask, alpha, interpolation,
background=background_color,
colormap=colormap,
xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
xformat=xformat, yformat=yformat,
zformat=zformat)
image = ImageItem(data, param)
image.set_filename(filename)
if eliminate_outliers is not None:
image.set_lut_range(lut_range_threshold(image, 256,
eliminate_outliers))
return image
def xyimage(self, taurusmodel=None, **kwargs):
if taurusmodel is None:
return guiqwt.builder.PlotItemBuilder.xyimage(self, **kwargs)
title = kwargs.get('title', taurusmodel)
data = kwargs.get('data', None)
alpha_mask = kwargs.get('alpha_mask', None)
alpha = kwargs.get('alpha', None)
background_color = kwargs.get('background_color', None)
colormap = kwargs.get('colormap', None)
interpolation = kwargs.get('interpolation', 'linear')
eliminate_outliers = kwargs.get('eliminate_outliers', None)
xformat = kwargs.get('xformat', '%.1f')
yformat = kwargs.get('yformat', '%.1f')
zformat = kwargs.get('zformat', '%.1f')
if data is None:
x = y = None
else:
x = numpy.arange(data.shape[0])
y = numpy.arange(data.shape[1])
data = numpy.ones((251, 251))
x, y = numpy.arange(251) * 333, numpy.arange(251) * 1000
param = XYImageParam(title=_("Image"), icon='image.png')
self.set_image_param(param, title, alpha_mask, alpha, interpolation,
background=background_color, colormap=colormap,
xformat=xformat, yformat=yformat,
zformat=zformat)
image = TaurusXYImageItem(param)
image.setModel(taurusmodel)
if eliminate_outliers is not None:
image.set_lut_range(lut_range_threshold(image, 256,
eliminate_outliers))
return image
def image(self, taurusmodel=None, **kwargs):
"""
Extension to meth:`guiqwt.builder.PlotItemBuilder.image` to support passing a
'taurusmodel' as a keyword argument instead passing 'data' or 'filename'.
"""
if taurusmodel is None:
image = guiqwt.builder.PlotItemBuilder.image(self, **kwargs)
else:
title = kwargs.get('title', taurusmodel)
data = kwargs.get('data', None)
filename = kwargs.get('filename', None)
alpha_mask = kwargs.get('alpha_mask', None)
alpha = kwargs.get('alpha', None)
background_color = kwargs.get('background_color', None)
colormap = kwargs.get('colormap', None)
xdata = kwargs.get('xdata', [None, None])
ydata = kwargs.get('ydata', [None, None])
pixel_size = kwargs.get('pixel_size', None)
interpolation = kwargs.get('interpolation', 'linear')
eliminate_outliers = kwargs.get('eliminate_outliers', None)
xformat = kwargs.get('xformat', '%.1f')
yformat = kwargs.get('yformat', '%.1f')
zformat = kwargs.get('zformat', '%.1f')
forceRGB = kwargs.get('force_rgb', False)
assert isinstance(xdata, (tuple, list)) and len(xdata) == 2
assert isinstance(ydata, (tuple, list)) and len(ydata) == 2
assert filename is None
assert data is None
param = ImageParam(title=_("Image"), icon='image.png')
from taurus import Attribute
if pixel_size is None:
xmin, xmax = xdata
ymin, ymax = ydata
else:
attr = Attribute(taurusmodel)
valueobj = attr.read()
data = getattr(valueobj, 'rvalue', numpy.zeros((1, 1)))
attrdata = data
if isinstance(data, Quantity):
attrdata = data.magnitude
xmin, xmax, ymin, ymax = self.compute_bounds(attrdata,
pixel_size)
self.set_image_param(param, title, alpha_mask, alpha, interpolation,
background=background_color,
colormap=colormap,
xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
xformat=xformat, yformat=yformat,
zformat=zformat)
from taurus.core import DataType
if forceRGB:
if Attribute(taurusmodel).getType() == DataType.DevEncoded:
image = TaurusEncodedRGBImageItem(param)
else:
image = TaurusRGBImageItem(param)
else:
if Attribute(taurusmodel).getType() == DataType.DevEncoded:
image = TaurusEncodedImageItem(param)
else:
image = TaurusImageItem(param)
image.setModel(taurusmodel)
if eliminate_outliers is not None:
image.set_lut_range(lut_range_threshold(image, 256,
eliminate_outliers))
return image
def maskedimage(
self,
data=None,
mask=None,
filename=None,
title=None,
alpha_mask=False,
alpha=1.0,
xdata=[None, None],
ydata=[None, None],
pixel_size=None,
center_on=None,
background_color=None,
colormap=None,
show_mask=False,
fill_value=None,
interpolation="linear",
eliminate_outliers=None,
xformat="%.1f",
yformat="%.1f",
zformat="%.1f",
):
"""
Make a masked image `plot item` from data
(:py:class:`guiqwt.image.MaskedImageItem` object)
"""
assert isinstance(xdata, (tuple, list)) and len(xdata) == 2
assert isinstance(ydata, (tuple, list)) and len(ydata) == 2
param = MaskedImageParam(title=_("Image"), icon="image.png")
data, filename, title = self._get_image_data(
data, filename, title, to_grayscale=True
)
assert data.ndim == 2, "Data must have 2 dimensions"
if pixel_size is None:
assert center_on is None, (
"Ambiguous parameters: both `center_on`"
" and `xdata`/`ydata` were specified"
)
xmin, xmax = xdata
ymin, ymax = ydata
else:
xmin, xmax, ymin, ymax = self.compute_bounds(data, pixel_size, center_on)
self.__set_image_param(
param,
title,
alpha_mask,
alpha,
interpolation,
background=background_color,
colormap=colormap,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
show_mask=show_mask,
fill_value=fill_value,
xformat=xformat,
yformat=yformat,
zformat=zformat,
)
image = MaskedImageItem(data, mask, param)
image.set_filename(filename)
if eliminate_outliers is not None:
image.set_lut_range(lut_range_threshold(image, 256, eliminate_outliers))
return image