functions for plotting mean or mean and sem of numpy array

binPlots.py

def binMeanPlot(X,Y,ax=None,numBins=8,xmin=None,xmax=None):
    if xmin is None:
        xmin = X.min()
    if xmax is None:
        xmax = X.max()
    if ax is None:
        fig = pylab.figure()
        ax = fig.add_subplot(111)
    bins = np.linspace(xmin,xmax,numBins+1)
    XX = np.array([np.mean((bins[binInd], bins[binInd+1])) for binInd in range(numBins)])
    YY = np.array([np.mean(Y[(X > bins[binInd]) & (X <= bins[binInd+1])]) for binInd in range(numBins)])
    lineHandles = ax.plot(XX,YY)
    return lineHandles[0], XX, YY

def binMeanStdPlot(X,Y,ax=None,numBins=8,xmin=None,xmax=None):
    if xmin is None:
        xmin = X.min()
    if xmax is None:
        xmax = X.max()
    if ax is None:
        fig = pylab.figure()
        ax = fig.add_subplot(111)
    bins = np.linspace(xmin,xmax,numBins+1)
    XX = np.array([np.mean((bins[binInd], bins[binInd+1])) for binInd in range(numBins)])
    YY = np.array([np.mean(Y[(X > bins[binInd]) & (X <= bins[binInd+1])]) for binInd in range(numBins)])
    #XX[np.isnan(YY)]=np.nan
    YYstd = np.array([np.std(Y[(X > bins[binInd]) & (X <= bins[binInd+1])]) for binInd in range(numBins)])
    lineHandles = ax.plot(XX,YY)
    patchHandle = ax.fill_between(XX[~np.isnan(YY)],YY[~np.isnan(YY)]-YYstd[~np.isnan(YY)],YY[~np.isnan(YY)]+YYstd[~np.isnan(YY)])
    patchHandle.set_facecolor([.8, .8, .8])
    patchHandle.set_edgecolor('none')
    return lineHandles[0], patchHandle, XX, YY, YYstd