U Kv fK@s0dZddlZddlmZd ddZd d d ZdS) zcorrelation plots Author: Josef Perktold License: BSD-3 example for usage with different options in statsmodels/sandbox/examples/thirdparty/ex_ratereturn.py N)utilsFRdYlBu_rcCs|dkrd}nd}t|\}}|jd} |dkr6|}|dkrBd}t|trV|\} } n|rdd\} } nd\} } |j||dd| d| f| | d } td| d } t|trt |dkr| gnH|dk r| | |j | dd d dd |j |ddd d ddt|tr*t |dkr*| gn@|dk rj| | |j | dd d dd |j |d ddd|dks~|||r|j| dd||jddd|jddddz|jddddddWntk rYnX|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?)NNZnearest)cmap interpolationZextentvminvmaxg?)minorsmallright)fontsizehorizontalalignment-)r Zrotationr)Z use_gridspecr )whichlengthout) directiontopr -wr)rZ linestylecolorZlw)rZ create_mpl_axshape isinstancetupleZimshownpZarangelistlenZ set_yticksZset_yticklabelsZ set_xticksZset_xticklabels set_titlecolorbarZ tight_layoutZ tick_paramsZgridAttributeError)Zdcorrxnamesynamestitle normcoloraxrZcreate_colorbarfigZnvarsrrZaximZlabelPosr(D/tmp/pip-unpacked-wheel-2v6byqio/statsmodels/graphics/correlation.py plot_corrs`1               r*c Csn|dkr |}|sdgt|}t|}|dk rFtt|t|} n8|dkrZd|} }n$tt|} tt|t| }t|t| d} t| d} tj|| | d| fd}t |D]j\} } | | || d}| || d|kr|ng}| d|dkr |ng}t | |||| |||dq|j d d d d d | d d ddg}|j|jdjd|d|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?)Zfigsize)r"r#r$r%r&rg?g ףp= ?g?)Zbottomleftr rgq= ףp?g?g?r)cax)rintrceilfloatsqrtminrZcreate_mpl_fig enumerateZ add_subplotr*Zsubplots_adjustZadd_axesr ZaxesZimages)ZdcorrstitlesZncolsr%r"r#r'rZn_plotsZnrowsZaspectZvsizeicr&Z_xnamesZ_ynamesr.r(r(r)plot_corr_grid}s6< r8)NNNFNr)NNFNNNr)__doc__Znumpyrrrr*r8r(r(r(r)s   n