import matplotlib.pyplot as plt
import numpy as np
import numpy.ma as ma

class camplotter( object ):
    def __init__( self ):
        chid, y,x,xe,ye,yh,xh,softid,hardid = np.loadtxt("map_dn.txt",unpack=True)
        self.fig = plt.figure()
        self.xe = xe
        self.ye = ye
        self.H = (6,0,30./180.*3.1415926)
        
    def plotcam():
        data = np.random.rand(1440)
        chid, y,x,xe,ye,yh,xh,softid,hardid = np.loadtxt("map_dn.txt",unpack=True)
        fig = plt.figure()
        ax = fig.add_subplot(121, aspect='equal')
        bx = fig.add_subplot(122, aspect='equal')
        
        H = (6,0,30./180.*3.1415926)
        
        ax.scatter( xe, ye , s=40 , alpha=0.75 , marker=H , linewidths=0.)
        bx.scatter( xe, ye , s=40 , alpha=0.75 , marker=H , linewidths=0., c=data)
        plt.show()

    def plotincam( data ):
        ax = fig.add_subplot(aspect='equal')
        ax.scatter(xe,ye,s=40,alpha=0.75,marker=H, c=data)
        plt.show()

    def plotmaskedcam( thr):
        chid, y,x,xe,ye,yh,xh,softid,hardid = np.loadtxt("map_dn.txt",unpack=True)
        data = np.random.rand(1440)
        mdata = ma.masked_greater(data, thr)
        fig = plt.figure()
        ax = fig.add_subplot(111, aspect='equal')
        H = (6,0,30./180.*3.1415926)
        
        a = ma.masked_where(mdata.mask == True, xe)
        b = ma.masked_where(mdata.mask == True, ye)
        
        xm = a.compressed()
        ym = b.compressed()
        dm = mdata.compressed()
        
        print xm
        print ym
        print dm
        ax.scatter(xe,ye,s=80,alpha=0.75,marker=H, c=data, edgecolors='none')
        ax.scatter( xm, ym ,s=80,alpha=1,marker=H,facecolors='none',linewidths=3)
        plt.show()


    def randomcam():
        data = np.random.rand(1440)
        plotincam( data )





if __name__ == '__main__':
    """
    create an instance
    """
    cplt = camplotter()
    # np.savez ( filename, amplitude=maxAmp, time=maxPos, integral=integ)
    npz = np.load('test.npz')
    print npz.files

    data = npz['integral']
    print 'data.shape', data.shape()

    for event in data:
        print 'event.shape', event.shape()