Data Visualization#

Tools for plotting data.

lsst.cst data science plot display utilities. Next modules are available: - displays: Display available for data plotting. - options: Options for data displaying.

class lsst.cst.data_visualization.DataImageDisplay(data)#

Scatter plots and figures creation management.

Parameters:: data (DataWrapper) – Data used to create plots.

create_axe(data_identifier, label=None, range=None, unit='N/A')#

Create Axe information to be used on scatter plots.

Parameters:

data_identifier (str) – Column indentifier from data used to draw the plot.
label (str, optional) – Axe label.
range (Tuple[float, float], optional) – Axe range.
unit (str, optional) – Axe units.

Returns:

axe_information – Axe information to be used in a scatter plot.

Return type:

hv.Dimension

create_figure(identifier, options=FigureOptions(height=600, tools=['pan,box_zoom,box_select,lasso_select,reset,help'], width=700, xlabel='X', ylabel='Y'))#

Creates a new figure and save the reference for future use.

Parameters:

identifier (str) – Figure identifier, used to use it as figure reference.
figure_options (FigureOptions, optional) – Created figure options.
options (FigureOptions, default: FigureOptions(height=600, tools=['pan,box_zoom,box_select,lasso_select,reset,help'], width=700, xlabel='X', ylabel='Y')) –

Returns:

figure – Data figure instance class.

Return type:

DataFigure

Raises:

AssertionError – Identifier already taken by another figure.:

get_figure(figure_identifier)#

Returns previously created figure: identified by the figure_identifier.

Parameters:: figure_identifier (str) – Unique identifier for a figure.
Returns:: figure – Figure identified by figure_identifier string.
Return type:: DataFigure
Raises:: AssertionError – Figure id is not found:

show(layout, tools_position='above')#

Show selected figures already created and configured.

Parameters:

layout (list) – List containing the figures to be shown.
tools_position (str) – Selected position for the toolbar.

show_data_shade(columns=None, options=DataShadeOptions(cmap='Viridis', fontsize={'title': 16, 'xlabel': 14, 'ylabel': 14, 'ticks': 12}, height=600, padding=0.05, show_grid=True, xlabel='X', xlim=None, ylabel='Y', ylim=None, tools=[], width=700))#

Creates datashader plot using selected columns from data.

Parameters:

columns (Tuple[hv.Dimension | str, hv.Dimension | str], optional) – Data columns selected to create the datashader plot, if non columns are passed the two first columns from data will be used.
options (DataShadeOptions, optional) – Scatter plot options.

Returns:

plot – Datashader plot.

Return type:

holoviews.core.spaces.DynamicMap

show_histogram(field, options=HistogramOptions(color='darkorange', fontscale=1.2, height=600, title='No title', xlabel='X', width=700, ylabel='Y'))#

Creates histogram plot using selected columns from data.

Parameters:

field (str) – Data column selected to create the histogram plot.
options (HistogramOptions, optional) – Histogram plot options.

Returns:

plot – Histogram plot.

Return type:

hv.Histogram

show_scatter(columns=None, options=HVScatterOptions(alpha=1.0, color='darkorange', fontsize={'title': 16, 'xlabel': 14, 'ylabel': 14, 'ticks': 12}, height=600, invert_xaxis=False, invert_yaxis=False, marker='circle', size=5, title=None, toolbar_position='above', tools=[], width=700, xlabel='X', ylabel='Y'))#

Creates scatter plot using selected columns from data.

Parameters:

columns (Tuple[hv.Dimension | str, hv.Dimension | str], optional) – Data columns to create the scatter plot, if non columns are passed the two first columns from data will be used.
options (ScatterOptions, optional) – Scatter plot options.

Returns:

plot – Scatter plot.

Return type:

hv.Scatter

class lsst.cst.data_visualization.DataShadeOptions(cmap='Viridis', fontsize=<factory>, height=600, padding=0.05, show_grid=True, xlabel='X', xlim=None, ylabel='Y', ylim=None, tools=<factory>, width=700)#

Datashade options

Parameters:

cmap (str, optional) – color mapping to be applied to the Datashader plot.
fontsize (dict[str, str], optional) – Size of the diferent elements in the plot: title, xlabel, ylabel, ticks.
height (int, optional) – Height of the plot in pixels.
padding (float, optional) – Extra space is added around the data points in the plot.
show_grid (bool, optional) – Show plot grid.
xlabel (str, optional) – xlabel value.
xlim (Tuple[float, float], optional) – X axes limits.
ylabel (str, optional) – ylabel value.
ylim (Tuple[float, float], optional) – Y axes limits.
tools (List = field(default_factory=list)) – Plot tools available.
width (int, optional) – Width of the plot in pixels.

to_dict()#

Create and returns a dictionary from class attributes, where key is the name of the attribute and value its value. Instance attributes with None value will not be included.

Returns:: options – Option key and values as dictionary.
Return type:: dict

class lsst.cst.data_visualization.FigureOptions(height=600, tools=<factory>, width=700, xlabel='X', ylabel='Y')#

Figure plot options.

Parameters:

height (int, optional) – Height of the plot in pixels.
tools (List, optional) – Figure tools available.
width (int) – Width of the plot in pixels.
xlabel (str, optional) – xlabel value.
ylabel (str, optional) – ylabel value.

to_dict()#

Create and returns a dictionary from class attributes, where key is the name of the attribute and value its value. Instance attributes with None value will not be included.

Returns:: options – Option key and values as dictionary.
Return type:: dict

class lsst.cst.data_visualization.GeometricPlots#

Static functions to create HV plots with geometric figures.

static points(points, options=PointsOptions(alpha=1.0, color='darkorange', fontsize={'title': 16, 'xlabel': 14, 'ylabel': 14, 'ticks': 12}, height=600, size=5, title=None, width=700, xlabel=None, ylabel=None))#

Create a plot with the selected points on it.

Parameters:

points (List[Tuple[float, float]]) – Points to be plot.
options (PointsOptions) – Points plot options.

Returns:

plot – Plot with the points draw on it.

Return type:

hv.Points

static polygons(region_data, kdims=None, vdims=None, tooltips=None, options=PolygonOptions(alpha=0.0, cmap=None, color=None, height=600, tools=None, hover_alpha=0.3, line_color='blue', line_alpha=1.0, title=None, width=700, xlabel=None, ylabel=None))#

Create a plot with the selected polygons on it.

Parameters:

polygon_information (list[PolygonInformation]) – Polygon information, including the vertex and other data to be shown.
kdims (Optional[Tuple[str, str]]) – X and Y vertex points values.
vdims (Optional[Tuple[str, str]]) – Other column information to be shown.
tooltipls (Optional[List[Tuple[str, str]]]) – On hoover text information.
options (PointsOptions) – Polygon plot options.
region_data (list[PolygonInformation]) –
tooltips (Optional[List[Tuple[str, str]]], default: None) –

Returns:

plot – Plot with the polygons draw on it.

Return type:

hv.Points

class lsst.cst.data_visualization.HVScatterOptions(alpha=1.0, color='darkorange', fontsize=<factory>, height=600, invert_xaxis=False, invert_yaxis=False, marker='circle', size=5, title=None, toolbar_position='above', tools=<factory>, width=700, xlabel='X', ylabel='Y')#

Holoviews Scatter Options.

Parameters:

alpha (float, optional) – Plot points alpha value.
color (str, optional) – Plot points color.
fontsize (dict, optional) – dictionary selecting fontsize for different elements on the plot.
invert_xaxis (bool, optional) – Invert xaxis of the plot.
invert_yaxis (bool = False) – Invert xaxis of the plot.
height (int, optional) – Height of the plot in pixels.
marker (str, optional) – Plot points marker type.
size (int, optional) – Plot points marker type.
toolbar (str, optional) – Toolbar position.
tools (List, optional) – Plot tools available.
width (int, optional) – Width of the plot in pixels.
xlabel (str, optional) – xlabel value.
ylabel (str) – ylabel value.
title (Optional[str], default: None) –
toolbar_position (str, default: 'above') –

to_dict()#

Create and returns a dictionary from class attributes, where key is the name of the attribute and value its value. Instance attributes with None value will not be included.

Returns:: options – Option key and values as dictionary.
Return type:: dict

class lsst.cst.data_visualization.HistogramOptions(color='darkorange', fontscale=1.2, height=600, title='No title', xlabel='X', width=700, ylabel='Y')#

Plot histogram options

Parameters:

color (str, optional) – Histogram bars color.
fontscale (float, optional) – Histogram labels fontsize.
height (int, optional) – Height of the plot in pixels.
title (str, optional) – Plot title.
xlabel (str, optional) – xlabel value.
width (int, optional) – Width of the plot in pixels.
ylabel (str, optional) – ylabel value.

to_dict()#

Create and returns a dictionary from class attributes, where key is the name of the attribute and value its value. Instance attributes with None value will not be included.

Returns:: options – Option key and values as dictionary.
Return type:: dict

class lsst.cst.data_visualization.PointsOptions(alpha=1.0, color='darkorange', fontsize=<factory>, height=600, size=5, title=None, width=700, xlabel=None, ylabel=None)#

Points plot options.

Parameters:

alpha (float, optional) – Plot points alpha value.
color (str, optional) – Plot points color.
fontsize (dict[str, str], optional) – Size of the diferent elements in the plot: title, xlabel, ylabel, ticks.
height (int, optional) – Height of the plot in pixels.
size (int, optional) – Points marker size.
title (str, optional) – Plot title.
width (int, optional) – Width of the plot in pixels.
xlabel (str, optional) – xlabel value.
ylabel (str) – ylabel value.

to_dict()#

Create and returns a dictionary from class attributes, where key is the name of the attribute and value its value. Instance attributes with None value will not be included.

Returns:: options – Option key and values as dictionary.
Return type:: dict

class lsst.cst.data_visualization.PolygonOptions(alpha=0.0, cmap=None, color=None, height=600, tools=None, hover_alpha=0.3, line_color='blue', line_alpha=1.0, title=None, width=700, xlabel=None, ylabel=None)#

Polygon plot options.

Parameters:

alpha (float, optional) – Polygons alpha value.
cmap (dict[str, str], optional) – Color map.
color (str) – Polygon fill color.
height (int, optional) – Height of the plot in pixels.
tools (List, optional) – Plot tools available.
hover_alpha (float, optional) – Polygon alpha value on hover.
line_color (List, optional) – Polygon line color.
line_alpha (List, optional) – Polygon line alpha value.
title (str, optional) – Plot title.
width (int, optional) – Width of the plot in pixels.
xlabel (str, optional) – xlabel value.
ylabel (str) – ylabel value.

to_dict()#

Create and returns a dictionary from class attributes, where key is the name of the attribute and value its value. Instance attributes with None value will not be included.

Returns:: options – Option key and values as dictionary.
Return type:: dict

class lsst.cst.data_visualization.ScatterOptions(alpha=1.0, color='darkorange', marker='circle', size=5)#

Bokeh Scatter plot options.

Parameters:

alpha (float, optional) – Plot points alpha value.
color (str, optional) – Plot points color.
marker (str, optional) – Plot points marker type.
size (int, optional) – Plot points marker size.

to_dict()#

Create and returns a dictionary from class attributes, where key is the name of the attribute and value its value. Instance attributes with None value will not be included.

Returns:: options – Option key and values as dictionary.
Return type:: dict

lsst.cst.data_visualization.create_polygons_and_point_plot(df, points)#

Draw list of boxes in a dataframe and list of points.

Parameters:

df (pd.DataFrame) – Information of the polygons to draw. Should have next columns: llcra, ulcra, llcra, urcra, llcdec, ulcdec, llcdec, urcdev, band, ccdVisitId
points (List[Tuple[float, float]]) – List of tuple of points that will be drawn at the plot.

Returns:

plot – Panel Row containing the polygons and points.

Return type:

pn.Row