Plot utils#

Visualization utils.

class lsst.cst.visualization.Band(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)#: Exposure bands available.

class lsst.cst.visualization.BoxInteract(image_display, options=BoxInteractOptions(color='red'))#

Interactive plot with a selectable box tool to show extra information.

Parameters:

options (BoxInteractOptions, Optional) – Box plot options.
image_display (ImageDisplay) –

options#: alias of BoxInteractOptions

show()#: Show interactive display.

class lsst.cst.visualization.ButlerCalExpDataFactory(configuration, collection)#

Factory of calexp from a Butler.

Parameters:

configuration (Configuration) – Configuration available for a butler.
collection (Collection) – Collection to be searched (in order) when reading datasets.

get_cal_exp_data(calexp_id)#

Check for the exposure in the Butler collection and returns a handler to get exposure information.

Parameters:: calexp_id (CalExpId) – CalExp information to search for.
Raises:: ValueError – When the Exposure could not be found inside the butler collection.
Returns:: exposure_data – Instance of a CalExpData which can be used to obtain exposure data.
Return type:: CalExpData

class lsst.cst.visualization.CalExpData#

Interface to get information from a Calexp.

abstract property cal_exp_id#

Exposure Identifier

Returns:: exposure_id – Information of the exposure.
Return type:: ExposureId

abstract get_image()#

Plot image .

Returns:: calexp – Exposure data from calexp.
Return type:: numpy.ndarray

abstract get_image_bounds()#

Exposure Image bounds.

Returns:: image_bounds – Bounds of the cal_exp Exposure.
Return type:: Tuple[int]

abstract get_sources()#

Calexp sources.

Returns:: sources – Sources from the calexp.
Return type:: pandas.DataFrame

class lsst.cst.visualization.CalExpDataFactory#

Interface for the CalExp Factories

get_cal_exp_data(calexp_id)#

Check for the exposure and returns a handler to get exposure information.

Parameters:: calexp_id (CalExpId) – CalExp information to search for.
Raises:: ValueError: – When the CalExp data could not be found.
Returns:: exposure_data – Instance of a CalExpData which can be used to obtain exposure data.
Return type:: CalExpData

class lsst.cst.visualization.CalExpId(visit, detector, band)#

Calexp information.

Parameters:

visit (int) –
detector (int) –
band (Band) –

as_dict()#

Return CalExpId as a dictionary

Returns:: cal_exp_id – CalExpId information as a dictionary
Return type:: dict

class lsst.cst.visualization.CalExpImageDisplay(cal_exp_data, title=None, xlabel='X', ylabel='Y', show_detections=True, image_options=ImageOptions(cmap='Greys_r', height=600, width=700, xaxis='bottom', yaxis='left', padding=0.01, font_size={'title': '8pt'}, colorbar=True, toolbar='right', show_grid=True, tools=[]))#

Plot using Calexp data, includes the image and also the sources.

Parameters:

cal_exp_data (CalExpData) – cal exp data to be plot
title (str, Optional) – Plot title. Default value: CalExpId information.
xlabel (str, Optional) – Plot xlabel. Default value: ‘X’.
ylabel (str, Optional) – Plot ylabel. Default value: ‘Y’.
show_detections (bool, Optional) – True if detections should be added to the plot. Default value: True.
image_options (ImageOptions, Optional) – Image options.

delete()#: Delete underlying image.

property image#

Underlying image.

Returns:: image – Underlying image used to create the plot.
Return type:: np.ndarray

options#: alias of ImageOptions

rasterize()#: Rasterize the image.

render()#: Render the image.

show()#: Show the image.

property sources#

Exposure sources.

Returns:: sources – Sources from the exposure
Return type:: Tuple[pandas.Series]

property transformed_image#

Underlying transformed image.

Returns:: image – Underlying transformed image shown in the plot.
Return type:: np.ndarray

class lsst.cst.visualization.Collection(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)#: Collections available: - i22: 2.2i/runs/DP0.2 .

class lsst.cst.visualization.Configuration(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)#: Butler configurations available - DP02: dp02.

class lsst.cst.visualization.HTMLSaver(output_dir='/home/runner')#

HTML plot saver

Parameters:: output_dir (str, default: '/home/runner') –

save(plot, filename)#

Save image as html in filename.

Parameters:

filename (str) – Name and path of the file where the image will be saved.
plot (ImageDisplay | _InteractiveDisplay) –

class lsst.cst.visualization.HoverSources(image_display, options=PointsOptions(fill_color=None, size=9, color='darkorange', marker='o'))#

Interactive display including the sources.

Parameters:

options (PointsOptions, Optional) – Display points options.
image_display (ImageDisplay) –

options#: alias of PointsOptions

show()#: Show interactive display.

class lsst.cst.visualization.ImageArrayDisplay(image, bounds, title=None, xlabel='X', ylabel='Y', options=ImageOptions(cmap='Greys_r', height=600, width=700, xaxis='bottom', yaxis='left', padding=0.01, font_size={'title': '8pt'}, colorbar=True, toolbar='right', show_grid=True, tools=[]))#

Plot for an ExposureF

Parameters:

image (numpy.ndarray) – image array to be show in the plot.
title (str) – title of the plot.
xlabel (str) – label for the x coordinates.
ylabel (str) – label for the y coordinates.
options (Options) – Options for the underlying plot object.
bounds (tuple[float]) –

property image#

Underlying image.

Returns:: image – Underlying image used to create the plot.
Return type:: np.ndarray

options#: alias of ImageOptions

rasterize()#: Rasterize the image.

render()#: Render the image.

show()#: Show the image.

property sources#

Exposure sources.

Returns:: sources – Sources from the exposure
Return type:: Tuple[pandas.Series]

property transformed_image#

Underlying transformed image.

Returns:: image – Underlying transformed image shown in the plot.
Return type:: np.ndarray

class lsst.cst.visualization.ImageDisplay#

Plot interface image.

delete()#: Delete underlying image.

static from_cal_exp_data(cal_exp_data, title=None, xlabel='X', ylabel='Y', show_detections=True, image_options=ImageOptions(cmap='Greys_r', height=600, width=700, xaxis='bottom', yaxis='left', padding=0.01, font_size={'title': '8pt'}, colorbar=True, toolbar='right', show_grid=True, tools=[]))#

Create a Plot class for CalExpData.

Parameters:

cal_exp_data (CalExpData) – exposure instance returned from butler.
title (str) – title of the plot.
xlabel (str) – label for the x coordinates.
ylabel (str) – label for the y coordinates.
image_options (ImageOptions) – Options for the underlying plot object.
sources_options (PointsOptions) – Options for the underlying sources plot object.
show_detections (bool, default: True) –

Returns:

results – Plot instance for the exposureF including sources.

Return type:

Plot

static from_image_array(image, bounds, title='No title', xlabel='X', ylabel='Y', image_options=ImageOptions(cmap='Greys_r', height=600, width=700, xaxis='bottom', yaxis='left', padding=0.01, font_size={'title': '8pt'}, colorbar=True, toolbar='right', show_grid=True, tools=[]))#

Create a Plot class for the exposureF image.

Parameters:

image (numpy.array) – image to be plotted.
bounds (tuple[float]) – image bounds.
title (str) – title of the plot.
xlabel (str) – label for the x coordinates.
ylabel (str) – label for the y coordinates.
image_options (ImageOptions) – Options for the underlying plot object.

Returns:

results – Plot instance for the exposureF

Return type:

Plot

abstract property image#

Underlying image.

Returns:: image – Underlying image used to create the plot.
Return type:: np.ndarray

abstract rasterize()#: Rasterize the image.

abstract render()#: Render the image.

abstract show()#: Show the image.

abstract property sources#

Exposure sources.

Returns:: sources – Sources from the exposure
Return type:: Tuple[pandas.Series]

property transformed_image#

Underlying transformed image.

Returns:: image – Underlying transformed image shown in the plot.
Return type:: np.ndarray

class lsst.cst.visualization.ImageOptions(cmap='Greys_r', height=600, width=700, xaxis='bottom', yaxis='left', padding=0.01, font_size=<factory>, colorbar=True, toolbar='right', show_grid=True, tools=<factory>)#

Image plot options.

Parameters:

cmap (str) – sets the colormap of the image, for example: Greys_r, viridis, plasma, inferno, magma, cividis or rainbow.
height (int) – Height of the plot in pixels.
width (int) – Width of the plot in pixels.
xaxis (str) – Position of the xaxis ‘bottom’, ‘top’.
yaxis (str) – Position of the yaxis.
padding (float) – space around the plot.
font_size (dict) – Font size for axis labels, titles, and legend.
colorbar (bool) – adds a colorbar to the plot.
toolbar (str) – toolbar position ‘left’, ‘right’, ‘above’, bellow’.
show_grid (bool) – displays grid lines on the plot.
tools (list) – List of Bokeh tools to include to the default ones. []

to_dict()#: Returns a dictionary with the keys as option name and the values as the option value.

class lsst.cst.visualization.OnClickInteract(image_display, options=OnClickInteractOptions(color='white', marker='x', size=20))#

Interactive display with a tap tool to show extra information.

Parameters:

options (OnClickInteract, Optional) – Interact display options.
image_display (ImageDisplay) –

options#: alias of OnClickInteractOptions

show()#: Show interactive display.

class lsst.cst.visualization.Options#

Interface with the indispensable methods of how an Option class should act like.

abstract to_dict()#: Returns a dictionary with the keys as option name and the values as the option value.