ó áp7]c@s_dZddlZddlmZdddeddd„Zddeddddd„ZdS(s correlation plots Author: Josef Perktold License: BSD-3 example for usage with different options in statsmodels/sandbox/examples/thirdparty/ex_ratereturn.py iÿÿÿÿNi(tutilstRdYlBu_rc Cs•|dkrt}nt}tj|ƒ\}}|jd} |dkrR|}n|dkrgd}nt|tƒr…|\} } n!|ršd"\} } n d#\} } |j|d|dddd| d| fd | d | ƒ} t j d| ƒd } |dk rR|j | ƒ|j | d d d tƒ|j |ddd …ddddƒn|gkrn|j gƒn|dk rÄ|j | ƒ|j | d d d tƒ|j|ddddddƒn|gkrà|j gƒn|dksü|j|ƒn|r|j| dtƒn|jƒ|jdd ddƒ|jdddtdtƒy)|jtdd ddddd d!ƒWntk rnX|S($s|Plot correlation of many variables in a tight color grid. Parameters ---------- dcorr : ndarray Correlation matrix, square 2-D array. xnames : list of 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 of 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 : Matplotlib AxesSubplot instance, 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 ------- fig : Matplotlib figure instance 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 isCorrelation Matrixgð¿gð?tcmapt interpolationtnearesttextenttvmintvmaxgà?iÿÿÿÿtminorNtfontsizetsmallthorizontalalignmenttrighttrotationi-tt use_gridspectwhichtlengtht directiontoutttopt linestylet-tcolortwtlwi(gð¿gð?(NN(tNonetTruetFalseRt create_mpl_axtshapet isinstancettupletimshowtnptaranget set_ytickstset_yticklabelst set_xtickstset_xticklabelst set_titletcolorbart tight_layoutt tick_paramstgridtAttributeError(tdcorrtxnamestynamesttitlet normcolortaxRtcreate_colorbartfigtnvarsRRtaximtlabelPos((s?lib/python2.7/site-packages/statsmodels/graphics/correlation.pyt plot_corrsV1        !          ) cCs|dkr|}n|s1dgt|ƒ}nt|ƒ}|dk rkttj|t|ƒƒƒ} nP|dkr‡d|} }n4ttj|ƒƒ} ttj|t| ƒƒƒ}t|t| ƒdƒ} tj| ƒd} tj |d| | d| fƒ}x©t |ƒD]›\} } |j | || dƒ}| || d|krZ|ng}| d|dkrz|ng}t | d|d|d || d |d |d |ƒqW|j d dddddddƒ|jddddgƒ}|j|jdjdd|ƒ|S(sG 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 of 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 of 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 of 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 : Matplotlib figure instance, 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 ------- fig : Matplotlib figure instance 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 RiigÍÌÌÌÌÌü?itfigsizeR/R0R1R2R3Rtbottomgš™™™™™¹?tleftg ×£p= ·?R gÍÌÌÌÌÌì?Rgq= ×£pí?gš™™™™™™?gš™™™™™é?itcaxN(RtlentintR"tceiltfloattsqrttminRtcreate_mpl_figt enumeratet add_subplotR9tsubplots_adjusttadd_axesR)taxestimages(tdcorrsttitlestncolsR2R/R0R5Rtn_plotstnrowstaspecttvsizetitcR3t_xnamest_ynamesR=((s?lib/python2.7/site-packages/statsmodels/graphics/correlation.pytplot_corr_grid|s0;    " #$ "!( t__doc__tnumpyR"RRRRR9RV(((s?lib/python2.7/site-packages/statsmodels/graphics/correlation.pyt s   l