clevar.match_metrics.recovery.catalog_funcs module

@file clevar/match_metrics/recovery/catalog_funcs.py

Main recovery functions using catalogs, wrapper of array_funcs functions

clevar.match_metrics.recovery.catalog_funcs.plot(cat, col1, col2, bins1, bins2, matching_type, xlabel=None, ylabel=None, scale1='linear', **kwargs)[source]

Plot recovery rate as lines, with each line binned by bins1 inside a bin of bins2.

Parameters

  • cat (clevar.ClCatalog) – ClCatalog with matching information

  • col1 (str) – Names of columns 1 and 2.

  • col2 (str) – Names of columns 1 and 2.

  • bins1 (array, int) – Bins for components 1 and 2.

  • bins2 (array, int) – Bins for components 1 and 2.

  • matching_type (str) – Type of matching to be considered. Must be in: ‘cross’, ‘cat1’, ‘cat2’, ‘multi_cat1’, ‘multi_cat2’, ‘multi_join’

  • mask (array) – Mask of unwanted clusters

  • mask_unmatched (array) – Mask of unwanted unmatched clusters (ex: out of footprint)

  • shape (str) – Shape of the lines. Can be steps or line.

  • ax (matplotlib.axes) – Ax to add plot

  • xlabel (str) – Label of component 1. Default is col1.

  • ylabel (str) – Label of recovery rate.

  • scale1 (str) – Scale of col 1 component

  • plt_kwargs (dict, None) – Additional arguments for pylab.plot. It also includes the possibility of smoothening the line with n_increase, scheme arguments. See clevar.utils.smooth_line for details.

  • lines_kwargs_list (list, None) – List of additional arguments for plotting each line (using pylab.plot). Must have same size as len(bins2)-1

  • add_legend (bool) – Add legend of bins

  • legend_format (function) – Function to format the values of the bins in legend

  • legend_kwargs (dict, None) – Additional arguments for pylab.legend

Returns

info –

Information of data in the plots, it contains the sections:

  • ax: ax used in the plot.

  • data: Binned data used in the plot. It has the sections:

    • recovery: Recovery rate binned with (bin1, bin2). bins where no cluster was found have nan value.

    • edges1: The bin edges along the first dimension.

    • edges2: The bin edges along the second dimension.

    • counts: Counts of all clusters in bins.

    • matched: Counts of matched clusters in bins.

Return type

dict

clevar.match_metrics.recovery.catalog_funcs.plot2D(cat, col1, col2, bins1, bins2, matching_type, xlabel=None, ylabel=None, scale1='linear', scale2='linear', **kwargs)[source]

Plot recovery rate as in 2D bins.

Parameters

  • cat (clevar.ClCatalog) – ClCatalog with matching information

  • col1 (str) – Names of columns 1 and 2.

  • col2 (str) – Names of columns 1 and 2.

  • bins1 (array, int) – Bins for component 1

  • bins2 (array, int) – Bins for component 2

  • matching_type (str) – Type of matching to be considered. Must be in: ‘cross’, ‘cat1’, ‘cat2’, ‘multi_cat1’, ‘multi_cat2’, ‘multi_join’

  • mask (array) – Mask of unwanted clusters

  • mask_unmatched (array) – Mask of unwanted unmatched clusters (ex: out of footprint)

  • ax (matplotlib.axes) – Ax to add plot

  • xlabel (str) – Labels of components 1 and 2. Default is col1, col2.

  • ylabel (str) – Labels of components 1 and 2. Default is col1, col2.

  • scale1 (str) – Scales of col 1, 2 components.

  • scale2 (str) – Scales of col 1, 2 components.

  • plt_kwargs (dict, None) – Additional arguments for pylab.pcolor.

  • add_cb (bool) – Plot colorbar

  • cb_kwargs (dict, None) – Colorbar arguments

  • add_num (int) – Add numbers in each bin

  • num_kwargs (dict, None) – Arguments for number plot (used in plt.text)

Returns

info –

Information of data in the plots, it contains the sections:

  • ax: ax used in the plot.

  • cb (optional): colorbar.

  • data: Binned data used in the plot. It has the sections:

    • recovery: Recovery rate binned with (bin1, bin2). bins where no cluster was found have nan value.

    • edges1: The bin edges along the first dimension.

    • edges2: The bin edges along the second dimension.

    • counts: Counts of all clusters in bins.

    • matched: Counts of matched clusters in bins.

Return type

dict

clevar.match_metrics.recovery.catalog_funcs.plot_panel(cat, col1, col2, bins1, bins2, matching_type, xlabel=None, ylabel=None, scale1='linear', **kwargs)[source]

Plot recovery rate as lines in panels, with each line binned by bins1 and each panel is based on the data inside a bins2 bin.

Parameters

  • cat (clevar.ClCatalog) – ClCatalog with matching information

  • col1 (str) – Names of columns 1 and 2.

  • col2 (str) – Names of columns 1 and 2.

  • bins1 (array, int) – Bins for components 1 and 2.

  • bins2 (array, int) – Bins for components 1 and 2.

  • matching_type (str) – Type of matching to be considered. Must be in: ‘cross’, ‘cat1’, ‘cat2’, ‘multi_cat1’, ‘multi_cat2’, ‘multi_join’

  • mask (array) – Mask of unwanted clusters

  • mask_unmatched (array) – Mask of unwanted unmatched clusters (ex: out of footprint)

  • shape (str) – Shape of the lines. Can be steps or line.

  • xlabel (str) – Label of component 1. Default is col1.

  • ylabel (str) – Label of recovery rate.

  • scale1 (str) – Scale of col 1 component

  • plt_kwargs (dict, None) – Additional arguments for pylab.plot. It also includes the possibility of smoothening the line with n_increase, scheme arguments. See clevar.utils.smooth_line for details.

  • panel_kwargs_list (list, None) – List of additional arguments for plotting each panel (using pylab.plot). Must have same size as len(bins2)-1

  • fig_kwargs (dict, None) – Additional arguments for plt.subplots

  • add_label (bool) – Add bin label to panel

  • label_format (function) – Function to format the values of the bins

Returns

info –

Information of data in the plots, it contains the sections:

  • fig: matplotlib.figure.Figure object.

  • axes: matplotlib.axes used in the plot.

  • data: Binned data used in the plot. It has the sections:

    • recovery: Recovery rate binned with (bin1, bin2). bins where no cluster was found have nan value.

    • edges1: The bin edges along the first dimension.

    • edges2: The bin edges along the second dimension.

    • counts: Counts of all clusters in bins.

    • matched: Counts of matched clusters in bins.

Return type

dict

clevar.match_metrics.recovery.catalog_funcs.skyplot(cat, matching_type, nside=256, nest=True, mask=None, mask_unmatched=None, auto_lim=False, ra_lim=None, dec_lim=None, recovery_label='Recovery Rate', fig=None, figsize=None, **kwargs)[source]

Plot recovery rate in healpix pixels.

Parameters

  • cat (clevar.ClCatalog) – ClCatalog with matching information

  • matching_type (str) – Type of matching to be considered. Must be in: ‘cross’, ‘cat1’, ‘cat2’, ‘multi_cat1’, ‘multi_cat2’, ‘multi_join’

  • nside (int) – Healpix nside

  • nest (bool) – If ordering is nested

  • mask (array) – Mask of unwanted clusters

  • mask_unmatched (array) – Mask of unwanted unmatched clusters (ex: out of footprint)

  • auto_lim (bool) – Set automatic limits for ra/dec.

  • ra_lim (None, list) – Min/max RA for plot.

  • dec_lim (None, list) – Min/max DEC for plot.

  • recovery_label (str) – Lable for colorbar. Default: ‘recovery rate’

  • fig (matplotlib.figure.Figure, None) – Matplotlib figure object. If not provided a new one is created.

  • figsize (tuple) – Width, height in inches (float, float). Default value from hp.cartview.

  • **kwargs –

    Extra arguments for hp.cartview:

    • xsize (int) : The size of the image. Default: 800

    • title (str) : The title of the plot. Default: None

    • min (float) : The minimum range value

    • max (float) : The maximum range value

    • remove_dip (bool) : If True, remove the dipole+monopole

    • remove_mono (bool) : If True, remove the monopole

    • gal_cut (float, scalar) : Symmetric galactic cut for the dipole/monopole fit. Removes points in latitude range [-gal_cut, +gal_cut]

    • format (str) : The format of the scale label. Default: ‘%g’

    • cbar (bool) : Display the colorbar. Default: True

    • notext (bool) : If True, no text is printed around the map

    • norm ({‘hist’, ‘log’, None}) : Color normalization, hist= histogram equalized color mapping, log= logarithmic color mapping, default: None (linear color mapping)

    • cmap (a color map) : The colormap to use (see matplotlib.cm)

    • badcolor (str) : Color to use to plot bad values

    • bgcolor (str) : Color to use for background

    • margins (None or sequence) : Either None, or a sequence (left,bottom,right,top) giving the margins on left,bottom,right and top of the axes. Values are relative to figure (0-1). Default: None

Returns

info –

Information of data in the plots, it contains the sections:

  • fig (matplotlib.pyplot.figure): Figure of the plot. The main can be accessed at info[‘fig’].axes[0], and the colorbar at info[‘fig’].axes[1].

  • nc_pix: Dictionary with the number of clusters in each pixel.

  • nc_mt_pix: Dictionary with the number of matched clusters in each pixel.

Return type

dict