Plot binned mean and mean plus/minus std using python

python scripts to plot mean and mean plus/minus std for data in time bin:

	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

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