M/PhK6dZddlZddlmZ d dZ d dZdS) zcorrelation plots Author: Josef Perktold License: BSD-3 example for usage with different options in statsmodels/sandbox/examples/thirdparty/ex_ratereturn.py N)utilsFRdYlBu_rc |d}nd}tj|\}}|jd} ||}|d}t|tr|\} } n |rd\} } nd\} } |||dd| d| f| | } t jd| d z} t|tr)t|dkr| gnZ|X| | | | dd d zd | |ddd d dt|tr)t|dkr| gnR|P| | | | dd d zd | |d dd|dks|||r|| d||dd|ddd |dddddn#t&$rYnwxYw|S)aJPlot correlation of many variables in a tight color grid. Parameters ---------- dcorr : ndarray Correlation matrix, square 2-D array. xnames : list[str], optional Labels for the horizontal axis. If not given (None), then the matplotlib defaults (integers) are used. If it is an empty list, [], then no ticks and labels are added. ynames : list[str], optional Labels for the vertical axis. Works the same way as `xnames`. If not given, the same names as for `xnames` are re-used. title : str, optional The figure title. If None, the default ('Correlation Matrix') is used. If ``title=''``, then no title is added. normcolor : bool or tuple of scalars, optional If False (default), then the color coding range corresponds to the range of `dcorr`. If True, then the color range is normalized to (-1, 1). If this is a tuple of two numbers, then they define the range for the color bar. ax : AxesSubplot, optional If `ax` is None, then a figure is created. If an axis instance is given, then only the main plot but not the colorbar is created. cmap : str or Matplotlib Colormap instance, optional The colormap for the plot. Can be any valid Matplotlib Colormap instance or name. Returns ------- Figure If `ax` is None, the created figure. Otherwise the figure to which `ax` is connected. Examples -------- >>> import numpy as np >>> import matplotlib.pyplot as plt >>> import statsmodels.graphics.api as smg >>> hie_data = sm.datasets.randhie.load_pandas() >>> corr_matrix = np.corrcoef(hie_data.data.T) >>> smg.plot_corr(corr_matrix, xnames=hie_data.names) >>> plt.show() .. plot:: plots/graphics_correlation_plot_corr.py NTFrzCorrelation Matrix)gg?)NNnearest)cmap interpolationextentvminvmaxg?)minorsmallright)fontsizehorizontalalignment-)rrotationr) use_gridspecr)whichlengthout) directiontopr-wr)r linestylecolorlw)r create_mpl_axshape isinstancetupleimshownparangelistlen set_yticksset_yticklabels set_xticksset_xticklabels set_titlecolorbar tight_layout tick_paramsgridAttributeError)dcorrxnamesynamestitle normcoloraxrcreate_colorbarfignvarsr r aximlabelPoss `/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/statsmodels/graphics/correlation.py plot_corrr@sb z!"%%GC KNE ~ }$)U##  dd   dd d 99UYuQu-Dt  E EDyE""S(H&$8CKK1$4$4 b   h hssmC't 444 6$$B$<'/6  8 8 8&$8CKK1$4$4 b   h hssmC't 444 6Gb/6  8 8 8 B;; U. T ---NNN+++NNUUN;;;  Gs#!DDDD       Js3I IIc ||}|sdgt|z}t|}|2ttj|t |z } n]|dkrd|}} nRttj|} ttj|t | z }t |t | z d} tj| dz} tj|| | zdz| f}t|D]^\} } | | || dz}| |z| dzz |kr|ng}| dz|zdkr|ng}t| |||| |||_| d d d d | gd }||jdjd||S)a Create a grid of correlation plots. The individual correlation plots are assumed to all have the same variables, axis labels can be specified only once. Parameters ---------- dcorrs : list or iterable of ndarrays List of correlation matrices. titles : list[str], optional List of titles for the subplots. By default no title are shown. ncols : int, optional Number of columns in the subplot grid. If not given, the number of columns is determined automatically. normcolor : bool or tuple, optional If False (default), then the color coding range corresponds to the range of `dcorr`. If True, then the color range is normalized to (-1, 1). If this is a tuple of two numbers, then they define the range for the color bar. xnames : list[str], optional Labels for the horizontal axis. If not given (None), then the matplotlib defaults (integers) are used. If it is an empty list, [], then no ticks and labels are added. ynames : list[str], optional Labels for the vertical axis. Works the same way as `xnames`. If not given, the same names as for `xnames` are re-used. fig : Figure, optional If given, this figure is simply returned. Otherwise a new figure is created. cmap : str or Matplotlib Colormap instance, optional The colormap for the plot. Can be any valid Matplotlib Colormap instance or name. Returns ------- Figure If `ax` is None, the created figure. Otherwise the figure to which `ax` is connected. Examples -------- >>> import numpy as np >>> import matplotlib.pyplot as plt >>> import statsmodels.api as sm In this example we just reuse the same correlation matrix several times. Of course in reality one would show a different correlation (measuring a another type of correlation, for example Pearson (linear) and Spearman, Kendall (nonlinear) correlations) for the same variables. >>> hie_data = sm.datasets.randhie.load_pandas() >>> corr_matrix = np.corrcoef(hie_data.data.T) >>> sm.graphics.plot_corr_grid([corr_matrix] * 8, xnames=hie_data.names) >>> plt.show() .. plot:: plots/graphics_correlation_plot_corr_grid.py Nrrg?)figsize)r5r6r7r8r9r皙?g ףp= ?g?)bottomleftrr)gq= ףp?rEg?g?r)cax)r)intr&ceilfloatsqrtminrcreate_mpl_fig enumerate add_subplotr@subplots_adjustadd_axesr/axesimages)dcorrstitlesncolsr8r5r6r;rn_plotsnrowsaspectvsizeicr9_xnames_ynamesrHs r?plot_corr_gridr`}sx~ "c&kk!&kkG BGGeEll23344 Q;;g5EE(())E%,, 67788Eu%s + +F GENNQ E  sUV^a-?,G H H HC&!!991 __UE1Q3 / /!EMQqS1E99&&rqSEMQ..&&B!GG6!9%"4 9 9 9 9 9sScBBB ,,... / /CLL!#A&CL000 J)NNNFNr)NNFNNNr)__doc__numpyr&rrr@r`rar?resFK&kkkk\MQ/9``````ra