clevar.match_metrics.recovery.array_funcs module

@file clevar/match_metrics/recovery/array_funcs.py

Main recovery functions using arrays.

clevar.match_metrics.recovery.array_funcs.get_recovery_rate(values1, values2, bins1, bins2, is_matched)

Get recovery rate binned in 2 components

Parameters

• values1 (array) – Component 1 and 2.

• values2 (array) – Component 1 and 2.

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

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

• is_matched (array (boolean)) – Boolean array indicating matching status

Returns

Binned recovery rate. Its sections are:

• 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.array_funcs.plot(values1, values2, bins1, bins2, is_matched, shape='steps', ax=None, plt_kwargs=None, lines_kwargs_list=None, add_legend=True, legend_format=<function <lambda>>, legend_kwargs=None)

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

Parameters

• values1 (array) – Component 1 and 2.

• values2 (array) – Component 1 and 2.

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

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

• is_matched (array (boolean)) – Boolean array indicating matching status

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

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

• 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.array_funcs.plot2D(values1, values2, bins1, bins2, is_matched, ax=None, plt_kwargs=None, add_cb=True, cb_kwargs=None, add_num=False, num_kwargs=None)

Plot recovery rate as in 2D bins.

Parameters

• values1 (array) – Component 1 and 2.

• values2 (array) – Component 1 and 2.

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

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

• is_matched (array (boolean)) – Boolean array indicating matching status

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

• 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.array_funcs.plot_panel(values1, values2, bins1, bins2, is_matched, shape='steps', plt_kwargs=None, panel_kwargs_list=None, fig_kwargs=None, add_label=True, label_format=<function <lambda>>)

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

• values1 (array) – Component 1 and 2.

• values2 (array) – Component 1 and 2.

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

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

• is_matched (array (boolean)) – Boolean array indicating matching status

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

• 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.array_funcs.skyplot(ra, dec, is_matched, nside=256, nest=True, auto_lim=False, ra_lim=None, dec_lim=None, recovery_label='Recovery Rate', fig=None, figsize=None, **kwargs)

Plot recovery rate in healpix pixels.

Parameters

• ra (numpy array) – Ra array in degrees

• dec (numpy array) – Dec array in degrees

• is_matched (array (boolean)) – Boolean array indicating matching status

• nside (int) – Healpix nside

• nest (bool) – If ordering is nested

• 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