arplothdf5

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from __future__ import print_function

from optparse import OptionParser

from carchive import h5data

import numpy as np

from matplotlib import pyplot as plt
from matplotlib import mlab
import matplotlib.dates as mdates

# trace line style codes
_styles=[
    'b-',
    'g--',
    'r-.',
    'c--',
    'm-.',
    'k--',
]

def opts():
    par=OptionParser(
    usage='%prog [options] <file.h5[:/path]>',
    description='Plot output of arget -E hdf5'
    )
    return par

class Sampler(object):
    """Sample all the y values at the x position given
    by the cursor.
    """
    def __init__(self, fig):
        self.F = fig
        self._cid = fig.canvas.mpl_connect('key_press_event', self.onpress)
    def disconnect(self):
        self.F.mpl_disconnect(self._sid)
    def onpress(self, event):
        #print(self,event.key)
        if event.key=='y' and event.inaxes:
            data = []
            ax = event.inaxes
            for L in ax.get_lines():
                X, Y = L.pv.mtime, L.pv.value
                Xp = mlab.find(X<=event.xdata)
                if len(Xp):
                    data.append((L, Xp[-1]))
                else:
                    data.append((L, None))

            data.sort(key=lambda v:v[0].pv.name)
            self.show(event, data)
    def show(self, event, data):
        print('All Y values at X=',mdates.num2date(event.xdata))
        for L, i in data:
            if i is None:
                print("Not Connected\t%s"%L.pv.name)
            else:
                print("%s\t%s\t%s\t%s"%(mdates.num2date(L.pv.mtime[i]),L.pv.name,L.pv.value[i], h5data.sevr2str(L.pv.severity[i])))

class RePlay(object):
    """Replay the events in the visible X region
    """
    def __init__(self, fig):
        self.F = fig
        self._cid = fig.canvas.mpl_connect('key_press_event', self.onpress)
    def disconnect(self):
        self.F.mpl_disconnect(self._sid)
    def onpress(self, event):
        #print(self,event.key)
        if event.key=='p' and event.inaxes:
            start, end = event.inaxes.get_xbound()

            inits=[]
            deltas=[]
            for L in event.inaxes.get_lines():
                X, Y = L.pv.mtime, L.pv.value

                # Get sample at start of region
                Np = mlab.find(X<=start)
                if len(Np):
                    inits.append((L, Np[-1]))
                else:
                    inits.append((L, None))
            
                # Get samples occuring within the region
                Np = mlab.find(np.logical_and(X>start, X<=end))
                for i in Np:
                    deltas.append((L, X[i], i))

            inits.sort(key=lambda T:T[0].pv.name)
            deltas.sort(key=lambda T:T[1])
            self.show(event, start, end, inits, deltas)
    def show(self, event, start, end, inits, deltas):
        start = mdates.num2date(start)
        print("Values at", start)
        for L, i in inits:
            if i is None:
                print(" Not Connected\t%s"%L.pv.name)
            else:
                print(" %s\t%s\t%s\t%s"%(mdates.num2date(L.pv.mtime[i]),L.pv.name,L.pv.value[i], h5data.sevr2str(L.pv.severity[i])))
        print("Changed within", mdates.num2date(end)-start)
        for L, T, i in deltas:
            print(" %s\t%s\t%s\t%s"%(mdates.num2date(L.pv.mtime[i]),L.pv.name,L.pv.value[i], h5data.sevr2str(L.pv.severity[i])))

def main():
    par=opts()
    opt, args = par.parse_args()

    G=h5data.H5Data(args[0])
    
    pvs=list(G)

    fig = plt.figure()
    H=[Sampler(fig), RePlay(fig)]
    ax = fig.add_subplot(111)

    L=[None]*len(pvs)

    for i,pv in enumerate(pvs):
        S=_styles[i%len(_styles)]
        data = G[pv]
        if not data.scalar:
            print('skipping >1d',pv,data['value'].shape)
            continue
        
        data.mtime = mdates.epoch2num(data.time)
        
        Xp, Yp = data.plotdata()
        
        L[i] = ax.plot(mdates.epoch2num(Xp), Yp, S)[0]
        L[i].pv = data # attach raw data for later use

    print(len(L),'lines')
    
    for A in fig.axes:
        loc = mdates.AutoDateLocator()
        fmt = mdates.AutoDateFormatter(loc)
        A.xaxis.set_major_formatter(fmt)
        A.xaxis.set_major_locator(loc)
    #fig.autofmt_xdate()
    
    plt.show()

if __name__=='__main__':
    main()