plots.py 文件源码

def corrPlotV(dv_true,dv_pred,sv_true,sv_pred,teamName,outName):
    slope, intercept, rvalue, pvalue, std_err = stats.linregress(np.append(dv_true,sv_true),np.append(dv_pred,sv_pred))
    plt.scatter(dv_true,dv_pred,label='Diastolic Volume',marker='o',facecolors='none',edgecolors='r')
    plt.scatter(sv_true,sv_pred,label='Systolic Volume',marker='o',facecolors='none',edgecolors='b')
    plt.xlabel("True Volume (mL)")
    plt.ylabel("Predicted Volume (mL)")
    plt.title("%s\nCorrelation of Volume Predictions with Test Values" % teamName)
    x = np.linspace(0,500,10)
    plt.plot(x,x,color='k',label='guide y = x')
    plt.plot(x,x*slope+intercept,color = 'k',linestyle='--',label='y=%.2fx+%.2f\n$R^2=$%.3f p=%.2e' % (slope,intercept,rvalue**2,pvalue))
    plt.gca().set_xlim((0,500))
    plt.gca().set_ylim((0,500))
    plt.legend(loc='upper left')
    plt.grid()
    plt.savefig("%sCorrVols.png" % outName)
    plt.close()

#plotting prediction vs truth... EF