<gh_stars>1-10
#!/usr/bin/env python
"""
Created on Wed Dec 30 16:20:38 2015

@author: <NAME>
"""

import os, glob
import scipy as sp
import matplotlib
import pdb
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib import ticker
import matplotlib.colors as colors
import matplotlib.gridspec as gridspec
import seaborn as sns
from SimISR.IonoContainer import IonoContainer, makeionocombined
from SimISR.utilFunctions import readconfigfile
from GeoData.GeoData import GeoData
from GeoData.utilityfuncs import readIono


defmap = 'viridis'# color map
fs=18# fontsize
fscb=12
lw=2 #line width
ne_red=1e-10
nemin,nemax=[0.*ne_red,3e11*ne_red]
temin,temax=[0,4e3]
timin,timax=[0,4e3]
necbarstr='$N_e$($10^{10}$m$^{-3}$)'
tecbarstr='$T_e$($^{\circ}$K)'
ticbarstr='$T_i$($^{\circ}$K)'
ercbarstr='%Error'
#%% For sorting
def ke(item):
    if item[0].isdigit():
        return int(item.partition(' ')[0])
    else:
        return float('inf')
#%% Plot input data
def plotinputdata(testdir,imgdir,wtimes=False):
    """
    This will plot all of the input data with each time step as a pcolor images of
    electron density and ion tempreture.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images.
    """

    if os.path.exists(imgdir):
        imgfiles = glob.glob(os.path.join(imgdir,'*.png'))
        for imgf in imgfiles:
            os.remove(imgf)
    else:
        os.mkdir(imgdir)

    filelist = glob.glob(os.path.join(testdir,'Origparams','*.h5'))
    numlist = [os.path.splitext(os.path.split(x)[-1])[0] for x in filelist]
    numdict = {numlist[i]:filelist[i] for i in range(len(filelist))}
    slist = sorted(numlist,key=ke)
    imcount = 0
    filetemplate = 'inputdata'
    dsetname = os.path.split(os.path.dirname(testdir))[-1]
    print "Plotting input data for "+dsetname

    if 'perryplane' in testdir.lower():
        xlim = [-200.,360.]
        xticks = [-150.,0.,150.,300.]
        allparams = True
        ncols=3
        figsize = (15,7)
    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300.]
        allparams = False
        ncols=1
        figsize = (5,7)
    ylim = [100.,500.]
    f1 =  True
    for inumn, inum in enumerate(slist):
        print "{0} Input for {1} of {2}".format(dsetname,inumn,len(slist))
        ifile = numdict[inum]
        iono = IonoContainer.readh5(ifile)
        Iono1 = GeoData(readIono,[iono])
        nt = Iono1.times.shape[0]
        rng = sp.sqrt(Iono1.dataloc[:,0]**2+Iono1.dataloc[:,1]**2)*sp.sign(Iono1.dataloc[:,1])
        z = Iono1.dataloc[:,2]
        rngvec = sp.unique(rng)
        zvec = sp.unique(z)
        rngmat = rng.reshape(len(zvec),len(rngvec))
        zmat = z.reshape(len(zvec),len(rngvec))
        Ne = Iono1.data['Ne'].reshape(len(zvec),len(rngvec),nt)*ne_red
        Ti = Iono1.data['Ti'].reshape(len(zvec),len(rngvec),nt)
        Te = Iono1.data['Te'].reshape(len(zvec),len(rngvec),nt)
        for itimen,itime in enumerate(Iono1.times):
            if f1:
                f1=False
                t0 = itime[0]
            fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize ,sharey=True)
            if allparams:
                avec = axmat.flatten()
            else:
                avec =[axmat]

            plt.sca(avec[0])
            plt.xticks(xticks)
            plt.tick_params(labelsize=16)
            avec[0].set_xlabel('X Plane in km',fontsize=fs)
            avec[0].set_ylabel('Alt in km',fontsize=fs)
            pc1 = avec[0].pcolor(rngmat,zmat,Ne[:,:,itimen],cmap = defmap,vmin=nemin,vmax=nemax)
            avec[0].set_xlim(xlim)
            avec[0].set_ylim(ylim)
            avec[0].set_title('Electron Density',fontsize=fs)
            
           #pc1.set_norm(colors.LogNorm(vmin=5e8,vmax=5e12))
            tick_locator = ticker.MaxNLocator(nbins=5)
            
            cb1 = plt.colorbar(pc1, ax=avec[0])
            cb1.ax.xaxis.set_label_position('top')
            cb1.ax.set_xlabel(necbarstr,fontsize=fscb)
            cb1.locator = tick_locator
            cb1.update_ticks()
            if allparams:
                plt.sca(avec[1])
                plt.xticks(xticks)
                plt.tick_params(labelsize=16)
                avec[1].set_xlabel('X Plane in km',fontsize=fs)
                pc2 = avec[1].pcolor(rngmat,zmat,Te[:,:,itimen],cmap = defmap,vmin=temin,vmax=temax)
                avec[1].set_xlim(xlim)
                avec[1].set_ylim(ylim)
                avec[1].set_title('Electron Temperature',fontsize=fs)

                cb2 = plt.colorbar(pc2, ax=avec[1])
                cb2.ax.xaxis.set_label_position('top')
                cb2.ax.set_xlabel(tecbarstr,fontsize=fscb)
                cb2.locator = tick_locator
                cb2.update_ticks()
                
                plt.sca(avec[2])
                plt.xticks(xticks)
                plt.tick_params(labelsize=16)
                avec[2].set_xlabel('X Plane in km',fontsize=fs)
                pc3 = avec[2].pcolor(rngmat,zmat,Ti[:,:,itimen],cmap = defmap,vmin=timin,vmax=timax)
                avec[2].set_xlim(xlim)
                avec[2].set_ylim(ylim)
                avec[2].set_title('Ion Temperature',fontsize=fs)

                cb3 = plt.colorbar(pc3, ax=avec[2])
                cb3.ax.xaxis.set_label_position('top')
                cb3.ax.set_xlabel(ticbarstr,fontsize=fscb)
                cb3.locator = tick_locator
                cb3.update_ticks()
            plt.tight_layout()
            if wtimes:
                plt.subplots_adjust(top=0.9)
                spti = fig.suptitle('Parameters at {0} seconds'.format(int(itime[0]-t0)),fontsize=24)
            fname= '{0:0>3}_'.format(imcount)+filetemplate+'.png'
            
           # for ax in avec:
            #    for label in (ax.get_xticklabels() + ax.get_yticklabels()):
             #       label.set_fontsize(20)
            imcount=imcount+1
            plt.savefig(os.path.join(imgdir,fname),dpi=200)
            plt.close(fig)
#%%Plot output data
def plotoutput(testdir,imgdir,config,wtimes=False,fitpath='Fitted',fitfile='fitteddata.h5'):
    """
    This will plot all of the fitted data with each time step as a pcolor images of
    electron density and electron density from power mesurements.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images.
    """
    sns.set_style('whitegrid')
    (sensdict,simparams)=readconfigfile(config)
    tvec = simparams['Timevec']
    if os.path.exists(imgdir):
        imgfiles = glob.glob(os.path.join(imgdir,'*.png'))
        for imgf in imgfiles:
            os.remove(imgf)
    else:
        os.mkdir(imgdir)
    filename = os.path.join(testdir,fitpath,fitfile)
    iono = IonoContainer.readh5(filename)
    Iono1 = GeoData(readIono,[iono])
    nt = Iono1.times.shape[0]
    if Iono1.coordnames.lower()=='spherical':
        rngrdr =Iono1.dataloc[:,0].astype('float32')
        sign1 = sp.sign(Iono1.dataloc[:,1])
        el = Iono1.dataloc[:,2].astype('float32')
        elvec,elinv = sp.unique(el,return_inverse=True)
        nbeams = len(elvec)
        nrg = len(rngrdr)/nbeams
        
        Rngrdrmat = sp.reshape(rngrdr,(nrg,nbeams))
        Signmat = sp.reshape(sign1,(nrg,nbeams))
        Elmat = sp.reshape(el,(nrg,nbeams))
    
        Xmat = Rngrdrmat*Signmat*sp.cos(Elmat*sp.pi/180.)
        Zmat = Rngrdrmat*sp.sin(Elmat*sp.pi/180.)
        Ne = Iono1.data['Ne'].reshape(nrg,nbeams,nt)*ne_red
        Te = Iono1.data['Te'].reshape(nrg,nbeams,nt)
        Ti = Iono1.data['Ti'].reshape(nrg,nbeams,nt)
    elif Iono1.coordnames.lower()=='cartesian':
        rng = sp.sqrt(Iono1.dataloc[:,0]**2+Iono1.dataloc[:,1]**2)*sp.sign(Iono1.dataloc[:,1]).astype('float32')
        z = Iono1.dataloc[:,2].astype('float32')
        rngvec = sp.unique(rng)
        zvec = sp.unique(z)
        Xmat = rng.reshape(len(zvec),len(rngvec))
        Zmat = z.reshape(len(zvec),len(rngvec))
        Ne = Iono1.data['Ne'].reshape(len(zvec),len(rngvec),nt)*ne_red
        Ti = Iono1.data['Ti'].reshape(len(zvec),len(rngvec),nt)
        Te = Iono1.data['Te'].reshape(len(zvec),len(rngvec),nt)
    imcount=0
    filetemplate = 'fitteddata'

    dsetname = os.path.split(os.path.dirname(testdir))[-1]
    print "Plotting Output data for "+dsetname

    if 'perryplane' in testdir.lower():
        xlim = [-200.,360.]
        xticks = [-150.,0.,150.,300.]
        allparams=True
        ncols=3
        figsize = (15,7)
    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300]
        allparams = False
        ncols=1
        figsize = (5,7)
    ylim = [100.,500]
    for itimen,itime in enumerate(Iono1.times):
        print "{0} Output for {1} of {2}".format(dsetname,itimen,len(Iono1.times))
        
        
        Nemat = Ne[:,:,itimen]
        Timat = Ti[:,:,itimen]
        Temat = Te[:,:,itimen]
        
        fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize,sharey=True)
        if allparams:
            avec=axmat.flatten()
        else:
            avec=[axmat]

        plt.sca(avec[0])
        avec[0].set_xlabel('X Plane in km',fontsize=fs)
        avec[0].set_ylabel('Alt in km',fontsize=fs)
        pc1 = avec[0].pcolor(Xmat,Zmat,Nemat,cmap = defmap,vmin=nemin,vmax=nemax)
        plt.tick_params(labelsize=16)
        plt.xticks(xticks)
        avec[0].set_xlim(xlim)
        avec[0].set_ylim(ylim)
        avec[0].set_title('Electron Density',fontsize=fs)
        tick_locator = ticker.MaxNLocator(nbins=5)
            
        cb1 = plt.colorbar(pc1, ax=avec[0])
        cb1.ax.xaxis.set_label_position('top')
        cb1.ax.set_xlabel(necbarstr,fontsize=fscb)
        cb1.locator = tick_locator
        cb1.update_ticks()
        if allparams:

            
            plt.sca(avec[1])
            plt.tick_params(labelsize=16)
            plt.xticks(xticks)
            avec[1].set_xlabel('X Plane in km',fontsize=fs)
            pc2 = avec[1].pcolor(Xmat,Zmat,Temat,cmap = defmap,vmin=temin,vmax=temax)
            avec[1].set_xlim(xlim)
            avec[1].set_ylim(ylim)
            avec[1].set_title('Electron Temperature',fontsize=fs)

            cb2 = plt.colorbar(pc2, ax=avec[1])
            cb2.ax.xaxis.set_label_position('top')
            cb2.ax.set_xlabel(tecbarstr,fontsize=fscb)
            cb2.locator = tick_locator
            cb2.update_ticks()
            plt.sca(avec[2])
            plt.xticks(xticks)
            plt.tick_params(labelsize=16)
            avec[2].set_xlabel('X Plane in km',fontsize=fs)
            pc3 = avec[2].pcolor(Xmat,Zmat,Timat,cmap = defmap,vmin=timin,vmax=timax)
            avec[2].set_xlim(xlim)
            avec[2].set_ylim(ylim)
            avec[2].set_title('Ion Temperature',fontsize=fs)
            #        for ax in avec:
            #            for label in (ax.get_xticklabels() + ax.get_yticklabels()):
            #                label.set_fontsize(20)

            cb3 = plt.colorbar(pc3, ax=avec[2])
            cb3.ax.xaxis.set_label_position('top')
            cb3.ax.set_xlabel(ticbarstr,fontsize=fscb)
            cb3.locator = tick_locator
            cb3.update_ticks()	
        
        plt.tight_layout()
        if wtimes:
            plt.subplots_adjust(top=0.9)
            spti = fig.suptitle('Parameters at {0} seconds'.format(int(tvec[itimen])),fontsize=24)       

        fname= '{0:0>3}_'.format(imcount)+filetemplate+'.png'
        plt.savefig(os.path.join(imgdir,fname),dpi=300)
        imcount=imcount+1
        plt.close(fig)
#%% Error plotting 
def ploterrors(testdir,imgdir,config,wtimes=False,fitpath='Fitted',fitfile='fitteddata.h5'):
    """
    This will plot all of the fitted data with each time step as a pcolor images of
    electron density and electron density from power mesurements.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images.
    """
    sns.set_style('whitegrid')
    (sensdict,simparams)=readconfigfile(config)
    tvec = simparams['Timevec']
    filetemplate = 'fitteddataerrorp'
    cred=3.
    if os.path.exists(imgdir):
        imgfiles = glob.glob(os.path.join(imgdir,'*'+filetemplate+'.png'))
        for imgf in imgfiles:
            os.remove(imgf)
    else:
        os.mkdir(imgdir)
    filename = os.path.join(testdir,fitpath,fitfile)
    iono = IonoContainer.readh5(filename)
    Iono1 = GeoData(readIono,[iono])
    rngrdr =Iono1.dataloc[:,0].astype('float32')
    sign1 = sp.sign(Iono1.dataloc[:,1])
    el = Iono1.dataloc[:,2].astype('float32')
    elvec,elinv = sp.unique(el,return_inverse=True)
    nbeams = len(elvec)
    nrg = len(rngrdr)/nbeams
    nt = Iono1.times.shape[0]
    Rngrdrmat = sp.reshape(rngrdr,(nrg,nbeams))
    Signmat = sp.reshape(sign1,(nrg,nbeams))
    Elmat = sp.reshape(el,(nrg,nbeams))

    Xmat = Rngrdrmat*Signmat*sp.cos(Elmat*sp.pi/180.)
    Zmat = Rngrdrmat*sp.sin(Elmat*sp.pi/180.)


    nNe = Iono1.data['nNe'].reshape(nrg,nbeams,nt)*ne_red
    nTe = Iono1.data['nTe'].reshape(nrg,nbeams,nt)
    nTi = Iono1.data['nTi'].reshape(nrg,nbeams,nt)
    

    imcount=0
    
    dsetname = os.path.split(os.path.dirname(testdir))[-1]
    print "Plotting Output error data for "+dsetname

    if 'perryplane' in testdir.lower():
        xlim = [-200.,360.]
        xticks = [-150.,0.,150.,300.]
        allparams=True
        ncols=3
        figsize = (15,7)
    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300]
        allparams = False
        ncols=1
        figsize = (5,7)
    ylim = [100.,500]
    for itimen,itime in enumerate(Iono1.times):
        print "{0} Output for {1} of {2}".format(dsetname,itimen,len(Iono1.times))
        
        
        Nemat = nNe[:,:,itimen]
        Timat = nTi[:,:,itimen]
        Temat = nTe[:,:,itimen]
        
        fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize,sharey=True)
        if allparams:
            avec=axmat.flatten()
        else:
            avec=[axmat]

        plt.sca(avec[0])
        avec[0].set_xlabel('X Plane in km',fontsize=fs)
        avec[0].set_ylabel('Alt in km',fontsize=fs)
        pc1 = avec[0].pcolor(Xmat,Zmat,Nemat,cmap = defmap,vmin=nemin/cred,vmax=nemax/cred)
        plt.tick_params(labelsize=16)
        plt.xticks(xticks)
        avec[0].set_xlim(xlim)
        avec[0].set_ylim(ylim)
        avec[0].set_title('Electron Density Error',fontsize=fs)
        tick_locator = ticker.MaxNLocator(nbins=5)
            
        cb1 = plt.colorbar(pc1, ax=avec[0])
        cb1.ax.xaxis.set_label_position('top')
        cb1.ax.set_xlabel(necbarstr,fontsize=fscb)
        cb1.locator = tick_locator
        cb1.update_ticks()
        if allparams:

            
            plt.sca(avec[1])
            plt.tick_params(labelsize=16)
            plt.xticks(xticks)
            avec[1].set_xlabel('X Plane in km',fontsize=fs)
            pc2 = avec[1].pcolor(Xmat,Zmat,Temat,cmap = defmap,vmin=temin/cred,vmax=temax/cred)
            avec[1].set_xlim(xlim)
            avec[1].set_ylim(ylim)
            avec[1].set_title('Electron Temperature Error',fontsize=fs)

            cb2 = plt.colorbar(pc2, ax=avec[1])
            cb2.ax.xaxis.set_label_position('top')
            cb2.ax.set_xlabel(tecbarstr,fontsize=fscb)
            cb2.locator = tick_locator
            cb2.update_ticks()
            plt.sca(avec[2])
            plt.xticks(xticks)
            plt.tick_params(labelsize=16)
            avec[2].set_xlabel('X Plane in km',fontsize=fs)
            pc3 = avec[2].pcolor(Xmat,Zmat,Timat,cmap = defmap,vmin=timin/cred,vmax=timax/cred)
            avec[2].set_xlim(xlim)
            avec[2].set_ylim(ylim)
            avec[2].set_title('Ion Temperature Error',fontsize=fs)

            cb3 = plt.colorbar(pc3, ax=avec[2])
            cb3.ax.xaxis.set_label_position('top')
            cb3.ax.set_xlabel(ticbarstr,fontsize=fscb)
            cb3.locator = tick_locator
            cb3.update_ticks()	
        
        plt.tight_layout()
        if wtimes:
            plt.subplots_adjust(top=0.9)
            spti = fig.suptitle('Error at {0} seconds'.format(int(tvec[itimen])),fontsize=24)
       

        fname= '{0:0>3}_'.format(imcount)+filetemplate+'.png'
        plt.savefig(os.path.join(imgdir,fname),dpi=300)
        imcount=imcount+1
        plt.close(fig)

def plotpercenterror(testdir,imgdir,config,wtimes=False,fitpath='Fitted',fitfile='fitteddata.h5'):
    """
    This will plot all of the fitted data with each time step as a pcolor images of
    electron density and electron density from power mesurements.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images.
    """
    sns.set_style('whitegrid')
    (sensdict,simparams)=readconfigfile(config)
    tvec = simparams['Timevec']
    filetemplate = 'fitteddataerrorpercent'
    if os.path.exists(imgdir):
        imgfiles = glob.glob(os.path.join(imgdir,'*'+filetemplate+'.png'))
        for imgf in imgfiles:
            os.remove(imgf)
    else:
        os.mkdir(imgdir)
    filename = os.path.join(testdir,fitpath,fitfile)
    iono = IonoContainer.readh5(filename)
    Iono1 = GeoData(readIono,[iono])
    rngrdr =Iono1.dataloc[:,0].astype('float32')
    sign1 = sp.sign(Iono1.dataloc[:,1])
    el = Iono1.dataloc[:,2].astype('float32')
    elvec,elinv = sp.unique(el,return_inverse=True)
    nbeams = len(elvec)
    nrg = len(rngrdr)/nbeams
    nt = Iono1.times.shape[0]
    Rngrdrmat = sp.reshape(rngrdr,(nrg,nbeams))
    Signmat = sp.reshape(sign1,(nrg,nbeams))
    Elmat = sp.reshape(el,(nrg,nbeams))
    permin,permax=[0.,100.]
    Xmat = Rngrdrmat*Signmat*sp.cos(Elmat*sp.pi/180.)
    Zmat = Rngrdrmat*sp.sin(Elmat*sp.pi/180.)

    Ne = Iono1.data['Ne'].reshape(nrg,nbeams,nt)
    Ti = Iono1.data['Ti'].reshape(nrg,nbeams,nt)
    Te = Iono1.data['Te'].reshape(nrg,nbeams,nt)
    nNe = 100.*Iono1.data['nNe'].reshape(nrg,nbeams,nt)/Ne
    nTe = 100.*Iono1.data['nTe'].reshape(nrg,nbeams,nt)/Te
    nTi = 100.*Iono1.data['nTi'].reshape(nrg,nbeams,nt)/Ti
    

    imcount=0
    
    dsetname = os.path.split(os.path.dirname(testdir))[-1]
    print "Plotting Output error data for "+dsetname

    if 'perryplane' in testdir.lower():
        xlim = [-200.,360.]
        xticks = [-150.,0.,150.,300.]
        allparams=True
        ncols=3
        figsize = (15,7)
    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300]
        allparams = False
        ncols=1
        figsize = (5,7)
    ylim = [100.,500]
    for itimen,itime in enumerate(Iono1.times):
        print "{0} Output for {1} of {2}".format(dsetname,itimen,len(Iono1.times))
        
        
        Nemat = nNe[:,:,itimen]
        Timat = nTi[:,:,itimen]
        Temat = nTe[:,:,itimen]
        
        fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize,sharey=True)
        if allparams:
            avec=axmat.flatten()
        else:
            avec=[axmat]

        plt.sca(avec[0])
        avec[0].set_xlabel('X Plane in km',fontsize=fs)
        avec[0].set_ylabel('Alt in km',fontsize=fs)
        pc1 = avec[0].pcolor(Xmat,Zmat,Nemat,cmap = defmap,vmin=permin,vmax=permax)
        plt.tick_params(labelsize=16)
        plt.xticks(xticks)
        avec[0].set_xlim(xlim)
        avec[0].set_ylim(ylim)
        avec[0].set_title('Electron Density % Error',fontsize=fs)
        tick_locator = ticker.MaxNLocator(nbins=5)
            
        cb1 = plt.colorbar(pc1, ax=avec[0])
        cb1.ax.xaxis.set_label_position('top')
        cb1.ax.set_xlabel(ercbarstr,fontsize=fscb)
        cb1.locator = tick_locator
        cb1.update_ticks()
        if allparams:

            
            plt.sca(avec[1])
            plt.tick_params(labelsize=16)
            plt.xticks(xticks)
            avec[1].set_xlabel('X Plane in km',fontsize=fs)
            pc2 = avec[1].pcolor(Xmat,Zmat,Temat,cmap = defmap,vmin=permin,vmax=permax)
            avec[1].set_xlim(xlim)
            avec[1].set_ylim(ylim)
            avec[1].set_title('Electron Temperature % Error',fontsize=fs)

            cb2 = plt.colorbar(pc2, ax=avec[1])
            cb2.ax.xaxis.set_label_position('top')
            cb2.ax.set_xlabel(ercbarstr,fontsize=fscb)
            cb2.locator = tick_locator
            cb2.update_ticks()
            plt.sca(avec[2])
            plt.xticks(xticks)
            plt.tick_params(labelsize=16)
            avec[2].set_xlabel('X Plane in km',fontsize=fs)
            pc3 = avec[2].pcolor(Xmat,Zmat,Timat,cmap = defmap,vmin=permin,vmax=permax)
            avec[2].set_xlim(xlim)
            avec[2].set_ylim(ylim)
            avec[2].set_title('Ion Temperature % Error',fontsize=fs)

            cb3 = plt.colorbar(pc3, ax=avec[2])
            cb3.ax.xaxis.set_label_position('top')
            cb3.ax.set_xlabel(ercbarstr,fontsize=fscb)
            cb3.locator = tick_locator
            cb3.update_ticks()	
        
        plt.tight_layout()
        if wtimes:
            plt.subplots_adjust(top=0.9)
            spti = fig.suptitle('Percent Error at {0} seconds'.format(int(tvec[itimen])),fontsize=24)
       

        fname= '{0:0>3}_'.format(imcount)+filetemplate+'.png'
        plt.savefig(os.path.join(imgdir,fname),dpi=300)
        imcount=imcount+1
        plt.close(fig)

#%% 
def plotacf(testdir,imgdir,wtimes=False,acfpath='ACFInv',lagfile='00lags.h5',filetemplate=None,lag=0):
    """
    This will plot all of the fitted data with each time step as a pcolor images of
    electron density and electron density from power mesurements.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images.
    """

#    if os.path.exists(imgdir):
#        imgfiles = glob.glob(os.path.join(imgdir,'*.png'))
#        for imgf in imgfiles:
#            os.remove(imgf)
    if not os.path.exists(imgdir):
        os.mkdir(imgdir)
    filename = os.path.join(testdir,acfpath,lagfile)
    iono = IonoContainer.readh5(filename)
#    if iono.Param_List.shape[-1]==1:
#        nemax=1e10
#        nemin=0
    nt = iono.Time_Vector.shape[0]
    if set(iono.Coord_Vecs)=={'r','theta','phi'}:
        rngrdr =iono.Sphere_Coords[:,0].astype('float32')
        sign1 = sp.sign(iono.Sphere_Coords[:,1])
        el = iono.Sphere_Coords[:,2].astype('float32')
        elvec,elinv = sp.unique(el,return_inverse=True)
        nbeams = len(elvec)
        nrg = len(rngrdr)/nbeams
        
        Rngrdrmat = sp.reshape(rngrdr,(nrg,nbeams))
        Signmat = sp.reshape(sign1,(nrg,nbeams))
        Elmat = sp.reshape(el,(nrg,nbeams))
    
        Xmat = Rngrdrmat*Signmat*sp.cos(Elmat*sp.pi/180.)
        Zmat = Rngrdrmat*sp.sin(Elmat*sp.pi/180.)
        Ne = iono.Param_List[:,:,lag].reshape(nrg,nbeams,nt).real*ne_red
    elif set(iono.Coord_Vecs)=={'x','y','z'}:
        rng = sp.sqrt(iono.Cart_Coords[:,0]**2+iono.Cart_Coords[:,1]**2)*sp.sign(iono.Cart_Coords[:,1]).astype('float32')
        z = iono.Cart_Coords[:,2].astype('float32')
        rngvec = sp.unique(rng)
        zvec = sp.unique(z)
        Xmat = rng.reshape(len(zvec),len(rngvec))
        Zmat = z.reshape(len(zvec),len(rngvec))
        Ne = iono.Param_List[:,:,lag].reshape(len(zvec),len(rngvec),nt).real*ne_red
    imcount=0
    if filetemplate is None:
        filetemplate = 'acflag{0}'.format(lag)

    dsetname = os.path.split(os.path.dirname(testdir))[-1]
    print "Plotting Output data for "+dsetname

    if 'perryplane' in testdir.lower():
        xlim = [-200.,360.]
        xticks = [-150.,0.,150.,300.]

    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300]
    ncols=1
    figsize = (5,7)
    ylim = [100.,500]
    for itimen,itime in enumerate(iono.Time_Vector):
        print "{0} Output for {1} of {2}".format(dsetname,itimen,len(iono.Time_Vector))
        
        
        Nemat = Ne[:,:,itimen]

        
        fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize,sharey=True)

        avec=[axmat]

        plt.sca(avec[0])
        avec[0].set_xlabel('X Plane in km',fontsize=fs)
        avec[0].set_ylabel('Alt in km',fontsize=fs)
        pc1 = avec[0].pcolor(Xmat,Zmat,Nemat,cmap = defmap,vmin=nemin,vmax=nemax)
        plt.tick_params(labelsize=16)
        plt.xticks(xticks)
        avec[0].set_xlim(xlim)
        avec[0].set_ylim(ylim)
        avec[0].set_title('',fontsize=fs)
        tick_locator = ticker.MaxNLocator(nbins=5)
            
        cb1 = plt.colorbar(pc1, ax=avec[0])
        cb1.ax.xaxis.set_label_position('top')
        cb1.ax.set_xlabel(necbarstr)
        cb1.locator = tick_locator
        cb1.update_ticks()
        plt.tight_layout()

        fname= '{0:0>3}_'.format(imcount)+filetemplate+'.png'
        plt.savefig(os.path.join(imgdir,fname),dpi=300)
        imcount=imcount+1
        plt.close(fig)
        
#%% Alpha and error plotting
def plotalphaerror(alphaarr,errorarr,errorlagarr):
    """ This will plot the error with respect then alpha parameter for the 
        constraint. 
    """
    sns.set_style('whitegrid')
    sns.set_context('notebook')
    Nlag=errorlagarr.shape[-1]
    
    
    nlagplot=4.
    nrows=1+int(sp.ceil(float(Nlag)/(2*nlagplot)))

    fig=plt.figure(figsize=(8,4*nrows),facecolor='w')
    gs=gridspec.GridSpec(nrows,2)
    axmain=plt.subplot(gs[0,:])
    axlist=[plt.subplot(gs[int(sp.floor(float(i)/2.)+1),int(sp.mod(i,2))]) for i in range(2*(nrows-1))]
    
    axmain.plot(alphaarr,errorarr)
    axmain.set_xscale('log')
    axmain.set_yscale('log')
    axmain.set_title('Error From All Lags Added',fontsize=fs)
    axmain.set_ylabel('Error',fontsize=fs)
    axmain.set_xlabel(r'$\gamma$',fontsize=fs)
    
    for iaxn,iax in enumerate(axlist):
        strlist=[]
        handlist=[]
        for ilag in range(int(nlagplot)):
            curlag=int(iaxn*nlagplot+ilag)
            if curlag>=Nlag:
                break
            handlist.append(iax.plot(alphaarr,errorlagarr[:,curlag])[0])
            strlist.append('Lag {0}'.format(curlag))
        iax.set_xscale('log')
        iax.set_yscale('log')
        iax.set_title('Error From Lags',fontsize=fs)
        iax.set_ylabel('Error',fontsize=fs)
        iax.set_xlabel(r'$\gamma$',fontsize=fs)
        iax.legend(handlist,strlist,loc='upper right',fontsize='large')
    plt.tight_layout()
    return(fig,axlist,axmain)
    
def plotalphaerrorpub(alphaarr,errorarr,errorlagarr):
    """ This will plot the error with respect then alpha parameter for the 
        constraint. 
    """
    sns.set_style('whitegrid')
    sns.set_context('notebook')
    Nlag=errorlagarr.shape[-1]
    
    
    nlagplot=4.
    nrows=1+int(sp.ceil(float(Nlag)/(2*nlagplot)))
    
    fig,ax=plt.subplots(nrows=1,ncols=1,figsize=(8,4),facecolor='w')
    
    ax.plot(alphaarr,errorarr)
    ax.set_xscale('log')
    ax.set_yscale('log')
    ax.set_title('Error Lag Zero',fontsize=fs)
    ax.set_ylabel('Error',fontsize=fs)
    ax.set_xlabel(r'$\gamma$',fontsize=fs)
    

    return(fig,ax)


#%% 
def plotLcurve(alphaarr,datadif,constdif):
    """ 
    This will plot the L-curve for the first lag.
    """
    sns.set_style('whitegrid')
    sns.set_context('notebook')

    
    fig ,axmat= plt.subplots(nrows=1,ncols=1,facecolor='w',figsize=(6,6),sharey=True)
    axlist=axmat
    
    iax = axmat
    curlag=0
    axlist=iax.plot(datadif[:,curlag],constdif[:,curlag])[0]
    iax.set_xscale('log')
    iax.set_yscale('log')
    iax.set_title('L Curve',fontsize=fs)
    iax.set_xlabel(r'$\|Ax-b\|_2$',fontsize=fs)
    iax.set_ylabel(r'$f(x)$',fontsize=fs)
    plt.tight_layout()
    
    
    return(fig,axlist)
    
def plotLcurveall(alphaarr,datadif,constdif):
    """ 
    This will plot the L-curve for all of the lags
    """
    sns.set_style('whitegrid')
    sns.set_context('notebook')
    Nlag=datadif.shape[-1]
    
    
    nlagplot=4.
    nrows=int(sp.ceil(float(Nlag)/(2*nlagplot)))
    
    fig ,axmat= plt.subplots(nrows=nrows,ncols=2,facecolor='w',figsize=(8,4*nrows),sharey=True)
    axlist=axmat.flatten()
    
    
    for iaxn,iax in enumerate(axlist):
        strlist=[]
        handlist=[]
        for ilag in range(int(nlagplot)):
            curlag=int(iaxn*nlagplot+ilag)
            if curlag>=Nlag:
                break
            handlist.append(iax.plot(datadif[:,curlag],constdif[:,curlag])[0])
            strlist.append('Lag {0}'.format(curlag))
        iax.set_xscale('log')
        iax.set_yscale('log')
        iax.set_title('L Curve',fontsize=fs)
        iax.set_xlabel(r'$\|Ax-b\|_2$',fontsize=fs)
        iax.set_ylabel(r'$f(x)$',fontsize=fs)
        iax.legend(handlist,strlist,loc='upper right',fontsize='large')
    plt.tight_layout()
    return(fig,axlist)
def plotbackground(testdir,figname):
    """ 
    Plots the background densities and temperatures. 
    """
    sns.set_style('whitegrid')
    sns.set_context('notebook')
    sns.color_palette("hls", 8)
    filelist = glob.glob(os.path.join(testdir,'Origparams','*.h5'))
    numlist = [os.path.splitext(os.path.split(x)[-1])[0] for x in filelist]
    numdict = {numlist[i]:filelist[i] for i in range(len(filelist))}
    ylim = [100.,500.]
    slist = sorted(numlist,key=ke)
    ifile = numdict[slist[0]]
    Iono_in = IonoContainer.readh5(ifile)
    numz=sp.sum(Iono_in.Cart_Coords[:,2]==Iono_in.Cart_Coords[0,2])
    redcoords=Iono_in.Cart_Coords[numz/2::numz]
    z=redcoords[:,2]
    begdata = Iono_in.Param_List[numz/2::numz]
    allni=begdata[:,0,:-1,0]
    allti=begdata[:,0,:-1,1]
    T_all = begdata[:,0,:,1]    
    N_all=begdata[:,0,:,0]
    Te = begdata[:,0,-1,-1]
    Ne = begdata[:,0,-1,0]
    tini=allti*allni
    Nisum=allni.sum(-1)
    Ti=tini.sum(-1)/Nisum
    ncols=2
    figsize = (5*ncols,7)
    
    handlist=[]
    fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize,sharey=True)
    for i in range(len(Iono_in.Species)):
        p1=axmat[0].plot(N_all[:,i],z,label=Iono_in.Species[i],linewidth=lw)[0]
        handlist.append(p1)
    axmat[0].set_ylabel('Alt in km',fontsize=fs)
    axmat[0].set_ylim(ylim)
    axmat[0].set_xlabel(r'Number Density in m$^{-3}$',fontsize=fs)
    axmat[0].set_title('Ion and Electron Densities',fontsize=fs)
    axmat[0].set_xscale('log')
    axmat[0].set_xlim([1e2,3e11])
    axmat[0].legend(handlist,Iono_in.Species,loc='upper left',fontsize='large')
    
#    handlist2=[]
    p2=axmat[1].plot(Te,z,Ti,z,linewidth=lw)
#    for i in range(len(Iono_in.Species)):
#        p1=axmat[1].plot(T_all[:,i],z,label=Iono_in.Species[i],linewidth=lw)[0]
#        handlist2.append(p1)
    axmat[1].set_title('Ion and Electron Temperatures',fontsize=fs)
    axmat[1].set_xlabel(r'Temperature in $^{\circ}$K',fontsize=fs)
    axmat[1].set_xlim([0,2e3])
    axmat[1].set_ylim(ylim)
#    axmat[1].legend(handlist2,Iono_in.Species,loc='upper left',fontsize='large')
    axmat[1].legend(p2,['Te','Ti'],loc='upper left')
    
    fig.savefig(figname,dpi=300)

def plotlines(inputlist,fitiono,alt,times,fig, axvec,paramlist=['Ne','Te','Ti']):
    """
    Plots the values along a specific alittude. 
    """
    inputiono = makeionocombined(inputlist)
    Iono1 = GeoData(readIono,[inputiono])
    fitiono = IonoContainer.readh5(fitiono)
    fitGeo = GeoData(readIono,[fitiono])
    
    #paramlist = ['Ne','Te','Ti']
    (x,y,z) = inputiono.Cart_Coords.transpose()
    r = sp.sqrt(x**2+y**2)*sp.sign(y)
    incoords = sp.column_stack((r,z,sp.ones_like(z)))
    ru,zu =[ sp.unique(r),sp.unique(z)]
    Rmat,Zmat = sp.meshgrid(ru,zu)
    zinput = sp.argmin(sp.absolute(zu-alt))
    
    (xf,yf,zf) = fitiono.Cart_Coords.transpose()
    rf = sp.sqrt(xf**2+yf**2)*sp.sign(yf)
    outcoords = sp.column_stack((rf,zf,sp.ones_like(zf)))
    rfu,zfu =[ sp.unique(rf),sp.unique(zf)]
    Rfmat,Zfmat = sp.meshgrid(rfu,zfu)
    zoutput = sp.argmin(sp.absolute(zfu-alt))
    
    fitGeo.interpolate(incoords,Iono1.coordnames,method='linear',fill_value=sp.nan,twodinterp = True,oldcoords=outcoords)

    uz = sp.unique(z)
    ur = sp.unique(r)
    (rmat,zmat) = sp.meshgrid(ur,uz)
    
    inputdata = {}
    for iparm in paramlist:
        if iparm =='Nepow':
            iparm='Ne'
        curdata = Iono1.data[iparm][:,times[0]]
        
        inputdata[iparm] = sp.reshape(curdata,Rmat.shape)[zinput]

    outputdata = {}
    for iparm in paramlist:
        curdata = fitGeo.data[iparm][:, times[1]]
        outputdata[iparm] = sp.reshape(curdata,Rmat.shape)[zinput]
    
    #fig, axvec = plt.subplots(len(paramlist),1,sharey=False,figsize=(12,5*len(paramlist)))
    
    for ipn,iparam in enumerate(paramlist):
        ax = axvec[ipn]
        p1, = ax.plot(ru,inputdata[iparam],'b-',label='In',linewidth=3)
        p2, = ax.plot(ru,outputdata[iparam],'b--',label='Out',linewidth=3)
        ax.set_title(iparam)
        ax.set_xlabel('X Plane in km')
#        gi = sp.gradient(inputdata[iparam])/sp.gradient(ru)
#        go = sp.gradient(outputdata[iparam])/sp.gradient(ru)
#        p3, = ax2.plot(ru,gi,'g-',label='Grad In',linewidth=3)
#        p4, = ax2.plot(ru,go,'g--',label='Grad Out',linewidth=3)
        ax.yaxis.label.set_color(p1.get_color())
        #ax2.yaxis.label.set_color(p3.get_color())
        lines = [p1,p2]#,p3,p4]
        ax.legend(lines,[l.get_label() for l in lines])
    
    plt.tight_layout()    
    return(lines)

def plotgradlines(inputlist,fitiono,alt,times,paramlist=['Ne','Te','Ti']):
    """
    Plots the values along a specific alittude. 
    """
    inputiono = makeionocombined(inputlist)
    Iono1 = GeoData(readIono,[inputiono])
    fitiono = IonoContainer.readh5(fitiono)
    fitGeo = GeoData(readIono,[fitiono])
    
    paramlist = ['Ne','Te','Ti']
    (x,y,z) = inputiono.Cart_Coords.transpose()
    r = sp.sqrt(x**2+y**2)*sp.sign(y)
    incoords = sp.column_stack((r,z,sp.ones_like(z)))
    ru,zu =[ sp.unique(r),sp.unique(z)]
    Rmat,Zmat = sp.meshgrid(ru,zu)
    zinput = sp.argmin(sp.absolute(zu-alt))
    
    (xf,yf,zf) = fitiono.Cart_Coords.transpose()
    rf = sp.sqrt(xf**2+yf**2)*sp.sign(yf)
    outcoords = sp.column_stack((rf,zf,sp.ones_like(zf)))
    rfu,zfu =[ sp.unique(rf),sp.unique(zf)]
    Rfmat,Zfmat = sp.meshgrid(rfu,zfu)
    zoutput = sp.argmin(sp.absolute(zfu-alt))
    
    fitGeo.interpolate(incoords,Iono1.coordnames,method='linear',fill_value=sp.nan,twodinterp = True,oldcoords=outcoords)

    uz = sp.unique(z)
    ur = sp.unique(r)
    (rmat,zmat) = sp.meshgrid(ur,uz)
    
    inputdata = {}
    for iparm in paramlist:
        if iparm =='Nepow':
            iparm='Ne'
        curdata = Iono1.data[iparm][:,times[0]]
        
        inputdata[iparm] = sp.reshape(curdata,Rmat.shape)[zinput]

    outputdata = {}
    for iparm in paramlist:
        curdata = fitGeo.data[iparm][:, times[1]]
        outputdata[iparm] = sp.reshape(curdata,Rmat.shape)[zinput]
    
    fig, axvec = plt.subplots(len(paramlist),1,sharey=False,figsize=(12,5*len(paramlist)))
    
    for ipn,iparam in enumerate(paramlist):
        ax = axvec[ipn]
        ax2 = ax.twinx()
        p1, = ax.plot(ru,inputdata[iparam],'b-',label='In',linewidth=3)
        p2, = ax.plot(ru,outputdata[iparam],'b--',label='Out',linewidth=3)
        ax.set_title(iparam)
        ax.set_xlabel('X Plane in km')
        gi = sp.gradient(inputdata[iparam])/sp.gradient(ru)
        go = sp.gradient(outputdata[iparam])/sp.gradient(ru)
        p3, = ax2.plot(ru,gi,'g-',label='Grad In',linewidth=3)
        p4, = ax2.plot(ru,go,'g--',label='Grad Out',linewidth=3)
        ax.yaxis.label.set_color(p1.get_color())
        ax2.yaxis.label.set_color(p3.get_color())
        lines = [p1,p2,p3,p4]
        ax.legend(lines,[l.get_label() for l in lines])
    
    plt.tight_layout()    
    return(fig)

def plotsampling(testdir,outfile, ifile=None, wtimes=False):
    """This will plot all of the input data with each time step as a pcolor images of
    electron density and ion temperature.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images."""

  
    imcount = 0
    if ifile is None:
        filelist = glob.glob(os.path.join(testdir,'Origparams','*.h5'))
        numlist = [os.path.splitext(os.path.split(x)[-1])[0] for x in filelist]
        numdict = {numlist[i]:filelist[i] for i in range(len(filelist))}
        slist = sorted(numlist,key=ke)
        inumn=0
        inum = slist[0]
        dsetname = os.path.split(os.path.dirname(testdir))[-1]
        print "Plotting input data for "+dsetname

        print "{0} Input for {1} of {2}".format(dsetname,inumn,len(slist))
        ifile = numdict[inum]
        iono = IonoContainer.readh5(ifile)
    filetemplate = 'inputdata'

    if 'perryplane' in testdir.lower():
        xlim = [-150.,360.]
        xticks = [0.,150.,300.]
        allparams = True
        ncols=3
        figsize = (5,7)
    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300.]
        allparams = False
        ncols=1
        figsize = (5,7)
    ylim = [100.,500.]
    f1 =  True
    
   
    if iono.Param_List.shape[-1]==1:
        nemax=1e10*ne_red
        nemin=0
    iono2 = IonoContainer.readh5(outfile)
    xout,yout,zout = iono2.Cart_Coords.transpose()
    rout=sp.sqrt(xout**2+yout**2)
    Iono1 = GeoData(readIono,[iono])
    nt = Iono1.times.shape[0]
    rng = sp.sqrt(Iono1.dataloc[:,0]**2+Iono1.dataloc[:,1]**2)*sp.sign(Iono1.dataloc[:,1]).astype('float32')
    z = Iono1.dataloc[:,2].astype('float32')
    rngvec = sp.unique(rng)
    zvec = sp.unique(z)
    rngmat = rng.reshape(len(zvec),len(rngvec))
    zmat = z.reshape(len(zvec),len(rngvec))
    if 'Ne' in Iono1.data.keys():
        Ne = Iono1.data['Ne'].reshape(len(zvec),len(rngvec),nt)*ne_red
    elif '0' in Iono1.data.keys():
        Ne = Iono1.data['Ne'].reshape(len(zvec),len(rngvec),nt)*ne_red

    itimen=0
    itime = Iono1.times[0]
    if f1:
        f1=False
        t0 = itime[0]
        fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize ,sharey=True)
        if allparams:
            avec = axmat.flatten()
        else:
            avec =[axmat]

    plt.sca(avec[0])
    plt.xticks(xticks)
    plt.tick_params(labelsize=16)
    avec[0].set_xlabel('X Plane in km',fontsize=fs)
    avec[0].set_ylabel('Alt in km',fontsize=fs)
    pc1 = avec[0].pcolor(rngmat,zmat,Ne[:,:,itimen],cmap = defmap,vmin=nemin,vmax=nemax)
    avec[0].set_xlim(xlim)
    avec[0].set_ylim(ylim)
    
    
   #pc1.set_norm(colors.LogNorm(vmin=5e8,vmax=5e12))
    tick_locator = ticker.MaxNLocator(nbins=5)
    
    cb1 = plt.colorbar(pc1, ax=avec[0])
    cb1.ax.xaxis.set_label_position('top')
    cb1.ax.set_xlabel(necbarstr,fontsize=fscb)
    cb1.locator = tick_locator
    cb1.update_ticks()
    plot1 = avec[0].plot(rout,zout,'w.',markersize=3)

    plt.tight_layout()
    if wtimes:
        plt.subplots_adjust(top=0.9)
        spti = fig.suptitle('Parameters at {0} seconds'.format(int(itime[0]-t0)),fontsize=24)
    return (fig,avec)
#!/usr/bin/env python
"""
Created on Wed Dec 30 16:20:38 2015

@author: <NAME>
"""

import os, glob
import scipy as sp
import matplotlib
import pdb
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib import ticker
import matplotlib.colors as colors
import matplotlib.gridspec as gridspec
import seaborn as sns
from SimISR.IonoContainer import IonoContainer, makeionocombined
from SimISR.utilFunctions import readconfigfile
from GeoData.GeoData import GeoData
from GeoData.utilityfuncs import readIono


defmap = 'viridis'# color map
fs=18# fontsize
fscb=12
lw=2 #line width
ne_red=1e-10
nemin,nemax=[0.*ne_red,3e11*ne_red]
temin,temax=[0,4e3]
timin,timax=[0,4e3]
necbarstr='$N_e$($10^{10}$m$^{-3}$)'
tecbarstr='$T_e$($^{\circ}$K)'
ticbarstr='$T_i$($^{\circ}$K)'
ercbarstr='%Error'
#%% For sorting
def ke(item):
    if item[0].isdigit():
        return int(item.partition(' ')[0])
    else:
        return float('inf')
#%% Plot input data
def plotinputdata(testdir,imgdir,wtimes=False):
    """
    This will plot all of the input data with each time step as a pcolor images of
    electron density and ion tempreture.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images.
    """

    if os.path.exists(imgdir):
        imgfiles = glob.glob(os.path.join(imgdir,'*.png'))
        for imgf in imgfiles:
            os.remove(imgf)
    else:
        os.mkdir(imgdir)

    filelist = glob.glob(os.path.join(testdir,'Origparams','*.h5'))
    numlist = [os.path.splitext(os.path.split(x)[-1])[0] for x in filelist]
    numdict = {numlist[i]:filelist[i] for i in range(len(filelist))}
    slist = sorted(numlist,key=ke)
    imcount = 0
    filetemplate = 'inputdata'
    dsetname = os.path.split(os.path.dirname(testdir))[-1]
    print "Plotting input data for "+dsetname

    if 'perryplane' in testdir.lower():
        xlim = [-200.,360.]
        xticks = [-150.,0.,150.,300.]
        allparams = True
        ncols=3
        figsize = (15,7)
    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300.]
        allparams = False
        ncols=1
        figsize = (5,7)
    ylim = [100.,500.]
    f1 =  True
    for inumn, inum in enumerate(slist):
        print "{0} Input for {1} of {2}".format(dsetname,inumn,len(slist))
        ifile = numdict[inum]
        iono = IonoContainer.readh5(ifile)
        Iono1 = GeoData(readIono,[iono])
        nt = Iono1.times.shape[0]
        rng = sp.sqrt(Iono1.dataloc[:,0]**2+Iono1.dataloc[:,1]**2)*sp.sign(Iono1.dataloc[:,1])
        z = Iono1.dataloc[:,2]
        rngvec = sp.unique(rng)
        zvec = sp.unique(z)
        rngmat = rng.reshape(len(zvec),len(rngvec))
        zmat = z.reshape(len(zvec),len(rngvec))
        Ne = Iono1.data['Ne'].reshape(len(zvec),len(rngvec),nt)*ne_red
        Ti = Iono1.data['Ti'].reshape(len(zvec),len(rngvec),nt)
        Te = Iono1.data['Te'].reshape(len(zvec),len(rngvec),nt)
        for itimen,itime in enumerate(Iono1.times):
            if f1:
                f1=False
                t0 = itime[0]
            fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize ,sharey=True)
            if allparams:
                avec = axmat.flatten()
            else:
                avec =[axmat]

            plt.sca(avec[0])
            plt.xticks(xticks)
            plt.tick_params(labelsize=16)
            avec[0].set_xlabel('X Plane in km',fontsize=fs)
            avec[0].set_ylabel('Alt in km',fontsize=fs)
            pc1 = avec[0].pcolor(rngmat,zmat,Ne[:,:,itimen],cmap = defmap,vmin=nemin,vmax=nemax)
            avec[0].set_xlim(xlim)
            avec[0].set_ylim(ylim)
            avec[0].set_title('Electron Density',fontsize=fs)
            
           #pc1.set_norm(colors.LogNorm(vmin=5e8,vmax=5e12))
            tick_locator = ticker.MaxNLocator(nbins=5)
            
            cb1 = plt.colorbar(pc1, ax=avec[0])
            cb1.ax.xaxis.set_label_position('top')
            cb1.ax.set_xlabel(necbarstr,fontsize=fscb)
            cb1.locator = tick_locator
            cb1.update_ticks()
            if allparams:
                plt.sca(avec[1])
                plt.xticks(xticks)
                plt.tick_params(labelsize=16)
                avec[1].set_xlabel('X Plane in km',fontsize=fs)
                pc2 = avec[1].pcolor(rngmat,zmat,Te[:,:,itimen],cmap = defmap,vmin=temin,vmax=temax)
                avec[1].set_xlim(xlim)
                avec[1].set_ylim(ylim)
                avec[1].set_title('Electron Temperature',fontsize=fs)

                cb2 = plt.colorbar(pc2, ax=avec[1])
                cb2.ax.xaxis.set_label_position('top')
                cb2.ax.set_xlabel(tecbarstr,fontsize=fscb)
                cb2.locator = tick_locator
                cb2.update_ticks()
                
                plt.sca(avec[2])
                plt.xticks(xticks)
                plt.tick_params(labelsize=16)
                avec[2].set_xlabel('X Plane in km',fontsize=fs)
                pc3 = avec[2].pcolor(rngmat,zmat,Ti[:,:,itimen],cmap = defmap,vmin=timin,vmax=timax)
                avec[2].set_xlim(xlim)
                avec[2].set_ylim(ylim)
                avec[2].set_title('Ion Temperature',fontsize=fs)

                cb3 = plt.colorbar(pc3, ax=avec[2])
                cb3.ax.xaxis.set_label_position('top')
                cb3.ax.set_xlabel(ticbarstr,fontsize=fscb)
                cb3.locator = tick_locator
                cb3.update_ticks()
            plt.tight_layout()
            if wtimes:
                plt.subplots_adjust(top=0.9)
                spti = fig.suptitle('Parameters at {0} seconds'.format(int(itime[0]-t0)),fontsize=24)
            fname= '{0:0>3}_'.format(imcount)+filetemplate+'.png'
            
           # for ax in avec:
            #    for label in (ax.get_xticklabels() + ax.get_yticklabels()):
             #       label.set_fontsize(20)
            imcount=imcount+1
            plt.savefig(os.path.join(imgdir,fname),dpi=200)
            plt.close(fig)
#%%Plot output data
def plotoutput(testdir,imgdir,config,wtimes=False,fitpath='Fitted',fitfile='fitteddata.h5'):
    """
    This will plot all of the fitted data with each time step as a pcolor images of
    electron density and electron density from power mesurements.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images.
    """
    sns.set_style('whitegrid')
    (sensdict,simparams)=readconfigfile(config)
    tvec = simparams['Timevec']
    if os.path.exists(imgdir):
        imgfiles = glob.glob(os.path.join(imgdir,'*.png'))
        for imgf in imgfiles:
            os.remove(imgf)
    else:
        os.mkdir(imgdir)
    filename = os.path.join(testdir,fitpath,fitfile)
    iono = IonoContainer.readh5(filename)
    Iono1 = GeoData(readIono,[iono])
    nt = Iono1.times.shape[0]
    if Iono1.coordnames.lower()=='spherical':
        rngrdr =Iono1.dataloc[:,0].astype('float32')
        sign1 = sp.sign(Iono1.dataloc[:,1])
        el = Iono1.dataloc[:,2].astype('float32')
        elvec,elinv = sp.unique(el,return_inverse=True)
        nbeams = len(elvec)
        nrg = len(rngrdr)/nbeams
        
        Rngrdrmat = sp.reshape(rngrdr,(nrg,nbeams))
        Signmat = sp.reshape(sign1,(nrg,nbeams))
        Elmat = sp.reshape(el,(nrg,nbeams))
    
        Xmat = Rngrdrmat*Signmat*sp.cos(Elmat*sp.pi/180.)
        Zmat = Rngrdrmat*sp.sin(Elmat*sp.pi/180.)
        Ne = Iono1.data['Ne'].reshape(nrg,nbeams,nt)*ne_red
        Te = Iono1.data['Te'].reshape(nrg,nbeams,nt)
        Ti = Iono1.data['Ti'].reshape(nrg,nbeams,nt)
    elif Iono1.coordnames.lower()=='cartesian':
        rng = sp.sqrt(Iono1.dataloc[:,0]**2+Iono1.dataloc[:,1]**2)*sp.sign(Iono1.dataloc[:,1]).astype('float32')
        z = Iono1.dataloc[:,2].astype('float32')
        rngvec = sp.unique(rng)
        zvec = sp.unique(z)
        Xmat = rng.reshape(len(zvec),len(rngvec))
        Zmat = z.reshape(len(zvec),len(rngvec))
        Ne = Iono1.data['Ne'].reshape(len(zvec),len(rngvec),nt)*ne_red
        Ti = Iono1.data['Ti'].reshape(len(zvec),len(rngvec),nt)
        Te = Iono1.data['Te'].reshape(len(zvec),len(rngvec),nt)
    imcount=0
    filetemplate = 'fitteddata'

    dsetname = os.path.split(os.path.dirname(testdir))[-1]
    print "Plotting Output data for "+dsetname

    if 'perryplane' in testdir.lower():
        xlim = [-200.,360.]
        xticks = [-150.,0.,150.,300.]
        allparams=True
        ncols=3
        figsize = (15,7)
    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300]
        allparams = False
        ncols=1
        figsize = (5,7)
    ylim = [100.,500]
    for itimen,itime in enumerate(Iono1.times):
        print "{0} Output for {1} of {2}".format(dsetname,itimen,len(Iono1.times))
        
        
        Nemat = Ne[:,:,itimen]
        Timat = Ti[:,:,itimen]
        Temat = Te[:,:,itimen]
        
        fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize,sharey=True)
        if allparams:
            avec=axmat.flatten()
        else:
            avec=[axmat]

        plt.sca(avec[0])
        avec[0].set_xlabel('X Plane in km',fontsize=fs)
        avec[0].set_ylabel('Alt in km',fontsize=fs)
        pc1 = avec[0].pcolor(Xmat,Zmat,Nemat,cmap = defmap,vmin=nemin,vmax=nemax)
        plt.tick_params(labelsize=16)
        plt.xticks(xticks)
        avec[0].set_xlim(xlim)
        avec[0].set_ylim(ylim)
        avec[0].set_title('Electron Density',fontsize=fs)
        tick_locator = ticker.MaxNLocator(nbins=5)
            
        cb1 = plt.colorbar(pc1, ax=avec[0])
        cb1.ax.xaxis.set_label_position('top')
        cb1.ax.set_xlabel(necbarstr,fontsize=fscb)
        cb1.locator = tick_locator
        cb1.update_ticks()
        if allparams:

            
            plt.sca(avec[1])
            plt.tick_params(labelsize=16)
            plt.xticks(xticks)
            avec[1].set_xlabel('X Plane in km',fontsize=fs)
            pc2 = avec[1].pcolor(Xmat,Zmat,Temat,cmap = defmap,vmin=temin,vmax=temax)
            avec[1].set_xlim(xlim)
            avec[1].set_ylim(ylim)
            avec[1].set_title('Electron Temperature',fontsize=fs)

            cb2 = plt.colorbar(pc2, ax=avec[1])
            cb2.ax.xaxis.set_label_position('top')
            cb2.ax.set_xlabel(tecbarstr,fontsize=fscb)
            cb2.locator = tick_locator
            cb2.update_ticks()
            plt.sca(avec[2])
            plt.xticks(xticks)
            plt.tick_params(labelsize=16)
            avec[2].set_xlabel('X Plane in km',fontsize=fs)
            pc3 = avec[2].pcolor(Xmat,Zmat,Timat,cmap = defmap,vmin=timin,vmax=timax)
            avec[2].set_xlim(xlim)
            avec[2].set_ylim(ylim)
            avec[2].set_title('Ion Temperature',fontsize=fs)
            #        for ax in avec:
            #            for label in (ax.get_xticklabels() + ax.get_yticklabels()):
            #                label.set_fontsize(20)

            cb3 = plt.colorbar(pc3, ax=avec[2])
            cb3.ax.xaxis.set_label_position('top')
            cb3.ax.set_xlabel(ticbarstr,fontsize=fscb)
            cb3.locator = tick_locator
            cb3.update_ticks()	
        
        plt.tight_layout()
        if wtimes:
            plt.subplots_adjust(top=0.9)
            spti = fig.suptitle('Parameters at {0} seconds'.format(int(tvec[itimen])),fontsize=24)       

        fname= '{0:0>3}_'.format(imcount)+filetemplate+'.png'
        plt.savefig(os.path.join(imgdir,fname),dpi=300)
        imcount=imcount+1
        plt.close(fig)
#%% Error plotting 
def ploterrors(testdir,imgdir,config,wtimes=False,fitpath='Fitted',fitfile='fitteddata.h5'):
    """
    This will plot all of the fitted data with each time step as a pcolor images of
    electron density and electron density from power mesurements.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images.
    """
    sns.set_style('whitegrid')
    (sensdict,simparams)=readconfigfile(config)
    tvec = simparams['Timevec']
    filetemplate = 'fitteddataerrorp'
    cred=3.
    if os.path.exists(imgdir):
        imgfiles = glob.glob(os.path.join(imgdir,'*'+filetemplate+'.png'))
        for imgf in imgfiles:
            os.remove(imgf)
    else:
        os.mkdir(imgdir)
    filename = os.path.join(testdir,fitpath,fitfile)
    iono = IonoContainer.readh5(filename)
    Iono1 = GeoData(readIono,[iono])
    rngrdr =Iono1.dataloc[:,0].astype('float32')
    sign1 = sp.sign(Iono1.dataloc[:,1])
    el = Iono1.dataloc[:,2].astype('float32')
    elvec,elinv = sp.unique(el,return_inverse=True)
    nbeams = len(elvec)
    nrg = len(rngrdr)/nbeams
    nt = Iono1.times.shape[0]
    Rngrdrmat = sp.reshape(rngrdr,(nrg,nbeams))
    Signmat = sp.reshape(sign1,(nrg,nbeams))
    Elmat = sp.reshape(el,(nrg,nbeams))

    Xmat = Rngrdrmat*Signmat*sp.cos(Elmat*sp.pi/180.)
    Zmat = Rngrdrmat*sp.sin(Elmat*sp.pi/180.)


    nNe = Iono1.data['nNe'].reshape(nrg,nbeams,nt)*ne_red
    nTe = Iono1.data['nTe'].reshape(nrg,nbeams,nt)
    nTi = Iono1.data['nTi'].reshape(nrg,nbeams,nt)
    

    imcount=0
    
    dsetname = os.path.split(os.path.dirname(testdir))[-1]
    print "Plotting Output error data for "+dsetname

    if 'perryplane' in testdir.lower():
        xlim = [-200.,360.]
        xticks = [-150.,0.,150.,300.]
        allparams=True
        ncols=3
        figsize = (15,7)
    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300]
        allparams = False
        ncols=1
        figsize = (5,7)
    ylim = [100.,500]
    for itimen,itime in enumerate(Iono1.times):
        print "{0} Output for {1} of {2}".format(dsetname,itimen,len(Iono1.times))
        
        
        Nemat = nNe[:,:,itimen]
        Timat = nTi[:,:,itimen]
        Temat = nTe[:,:,itimen]
        
        fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize,sharey=True)
        if allparams:
            avec=axmat.flatten()
        else:
            avec=[axmat]

        plt.sca(avec[0])
        avec[0].set_xlabel('X Plane in km',fontsize=fs)
        avec[0].set_ylabel('Alt in km',fontsize=fs)
        pc1 = avec[0].pcolor(Xmat,Zmat,Nemat,cmap = defmap,vmin=nemin/cred,vmax=nemax/cred)
        plt.tick_params(labelsize=16)
        plt.xticks(xticks)
        avec[0].set_xlim(xlim)
        avec[0].set_ylim(ylim)
        avec[0].set_title('Electron Density Error',fontsize=fs)
        tick_locator = ticker.MaxNLocator(nbins=5)
            
        cb1 = plt.colorbar(pc1, ax=avec[0])
        cb1.ax.xaxis.set_label_position('top')
        cb1.ax.set_xlabel(necbarstr,fontsize=fscb)
        cb1.locator = tick_locator
        cb1.update_ticks()
        if allparams:

            
            plt.sca(avec[1])
            plt.tick_params(labelsize=16)
            plt.xticks(xticks)
            avec[1].set_xlabel('X Plane in km',fontsize=fs)
            pc2 = avec[1].pcolor(Xmat,Zmat,Temat,cmap = defmap,vmin=temin/cred,vmax=temax/cred)
            avec[1].set_xlim(xlim)
            avec[1].set_ylim(ylim)
            avec[1].set_title('Electron Temperature Error',fontsize=fs)

            cb2 = plt.colorbar(pc2, ax=avec[1])
            cb2.ax.xaxis.set_label_position('top')
            cb2.ax.set_xlabel(tecbarstr,fontsize=fscb)
            cb2.locator = tick_locator
            cb2.update_ticks()
            plt.sca(avec[2])
            plt.xticks(xticks)
            plt.tick_params(labelsize=16)
            avec[2].set_xlabel('X Plane in km',fontsize=fs)
            pc3 = avec[2].pcolor(Xmat,Zmat,Timat,cmap = defmap,vmin=timin/cred,vmax=timax/cred)
            avec[2].set_xlim(xlim)
            avec[2].set_ylim(ylim)
            avec[2].set_title('Ion Temperature Error',fontsize=fs)

            cb3 = plt.colorbar(pc3, ax=avec[2])
            cb3.ax.xaxis.set_label_position('top')
            cb3.ax.set_xlabel(ticbarstr,fontsize=fscb)
            cb3.locator = tick_locator
            cb3.update_ticks()	
        
        plt.tight_layout()
        if wtimes:
            plt.subplots_adjust(top=0.9)
            spti = fig.suptitle('Error at {0} seconds'.format(int(tvec[itimen])),fontsize=24)
       

        fname= '{0:0>3}_'.format(imcount)+filetemplate+'.png'
        plt.savefig(os.path.join(imgdir,fname),dpi=300)
        imcount=imcount+1
        plt.close(fig)

def plotpercenterror(testdir,imgdir,config,wtimes=False,fitpath='Fitted',fitfile='fitteddata.h5'):
    """
    This will plot all of the fitted data with each time step as a pcolor images of
    electron density and electron density from power mesurements.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images.
    """
    sns.set_style('whitegrid')
    (sensdict,simparams)=readconfigfile(config)
    tvec = simparams['Timevec']
    filetemplate = 'fitteddataerrorpercent'
    if os.path.exists(imgdir):
        imgfiles = glob.glob(os.path.join(imgdir,'*'+filetemplate+'.png'))
        for imgf in imgfiles:
            os.remove(imgf)
    else:
        os.mkdir(imgdir)
    filename = os.path.join(testdir,fitpath,fitfile)
    iono = IonoContainer.readh5(filename)
    Iono1 = GeoData(readIono,[iono])
    rngrdr =Iono1.dataloc[:,0].astype('float32')
    sign1 = sp.sign(Iono1.dataloc[:,1])
    el = Iono1.dataloc[:,2].astype('float32')
    elvec,elinv = sp.unique(el,return_inverse=True)
    nbeams = len(elvec)
    nrg = len(rngrdr)/nbeams
    nt = Iono1.times.shape[0]
    Rngrdrmat = sp.reshape(rngrdr,(nrg,nbeams))
    Signmat = sp.reshape(sign1,(nrg,nbeams))
    Elmat = sp.reshape(el,(nrg,nbeams))
    permin,permax=[0.,100.]
    Xmat = Rngrdrmat*Signmat*sp.cos(Elmat*sp.pi/180.)
    Zmat = Rngrdrmat*sp.sin(Elmat*sp.pi/180.)

    Ne = Iono1.data['Ne'].reshape(nrg,nbeams,nt)
    Ti = Iono1.data['Ti'].reshape(nrg,nbeams,nt)
    Te = Iono1.data['Te'].reshape(nrg,nbeams,nt)
    nNe = 100.*Iono1.data['nNe'].reshape(nrg,nbeams,nt)/Ne
    nTe = 100.*Iono1.data['nTe'].reshape(nrg,nbeams,nt)/Te
    nTi = 100.*Iono1.data['nTi'].reshape(nrg,nbeams,nt)/Ti
    

    imcount=0
    
    dsetname = os.path.split(os.path.dirname(testdir))[-1]
    print "Plotting Output error data for "+dsetname

    if 'perryplane' in testdir.lower():
        xlim = [-200.,360.]
        xticks = [-150.,0.,150.,300.]
        allparams=True
        ncols=3
        figsize = (15,7)
    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300]
        allparams = False
        ncols=1
        figsize = (5,7)
    ylim = [100.,500]
    for itimen,itime in enumerate(Iono1.times):
        print "{0} Output for {1} of {2}".format(dsetname,itimen,len(Iono1.times))
        
        
        Nemat = nNe[:,:,itimen]
        Timat = nTi[:,:,itimen]
        Temat = nTe[:,:,itimen]
        
        fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize,sharey=True)
        if allparams:
            avec=axmat.flatten()
        else:
            avec=[axmat]

        plt.sca(avec[0])
        avec[0].set_xlabel('X Plane in km',fontsize=fs)
        avec[0].set_ylabel('Alt in km',fontsize=fs)
        pc1 = avec[0].pcolor(Xmat,Zmat,Nemat,cmap = defmap,vmin=permin,vmax=permax)
        plt.tick_params(labelsize=16)
        plt.xticks(xticks)
        avec[0].set_xlim(xlim)
        avec[0].set_ylim(ylim)
        avec[0].set_title('Electron Density % Error',fontsize=fs)
        tick_locator = ticker.MaxNLocator(nbins=5)
            
        cb1 = plt.colorbar(pc1, ax=avec[0])
        cb1.ax.xaxis.set_label_position('top')
        cb1.ax.set_xlabel(ercbarstr,fontsize=fscb)
        cb1.locator = tick_locator
        cb1.update_ticks()
        if allparams:

            
            plt.sca(avec[1])
            plt.tick_params(labelsize=16)
            plt.xticks(xticks)
            avec[1].set_xlabel('X Plane in km',fontsize=fs)
            pc2 = avec[1].pcolor(Xmat,Zmat,Temat,cmap = defmap,vmin=permin,vmax=permax)
            avec[1].set_xlim(xlim)
            avec[1].set_ylim(ylim)
            avec[1].set_title('Electron Temperature % Error',fontsize=fs)

            cb2 = plt.colorbar(pc2, ax=avec[1])
            cb2.ax.xaxis.set_label_position('top')
            cb2.ax.set_xlabel(ercbarstr,fontsize=fscb)
            cb2.locator = tick_locator
            cb2.update_ticks()
            plt.sca(avec[2])
            plt.xticks(xticks)
            plt.tick_params(labelsize=16)
            avec[2].set_xlabel('X Plane in km',fontsize=fs)
            pc3 = avec[2].pcolor(Xmat,Zmat,Timat,cmap = defmap,vmin=permin,vmax=permax)
            avec[2].set_xlim(xlim)
            avec[2].set_ylim(ylim)
            avec[2].set_title('Ion Temperature % Error',fontsize=fs)

            cb3 = plt.colorbar(pc3, ax=avec[2])
            cb3.ax.xaxis.set_label_position('top')
            cb3.ax.set_xlabel(ercbarstr,fontsize=fscb)
            cb3.locator = tick_locator
            cb3.update_ticks()	
        
        plt.tight_layout()
        if wtimes:
            plt.subplots_adjust(top=0.9)
            spti = fig.suptitle('Percent Error at {0} seconds'.format(int(tvec[itimen])),fontsize=24)
       

        fname= '{0:0>3}_'.format(imcount)+filetemplate+'.png'
        plt.savefig(os.path.join(imgdir,fname),dpi=300)
        imcount=imcount+1
        plt.close(fig)

#%% 
def plotacf(testdir,imgdir,wtimes=False,acfpath='ACFInv',lagfile='00lags.h5',filetemplate=None,lag=0):
    """
    This will plot all of the fitted data with each time step as a pcolor images of
    electron density and electron density from power mesurements.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images.
    """

#    if os.path.exists(imgdir):
#        imgfiles = glob.glob(os.path.join(imgdir,'*.png'))
#        for imgf in imgfiles:
#            os.remove(imgf)
    if not os.path.exists(imgdir):
        os.mkdir(imgdir)
    filename = os.path.join(testdir,acfpath,lagfile)
    iono = IonoContainer.readh5(filename)
#    if iono.Param_List.shape[-1]==1:
#        nemax=1e10
#        nemin=0
    nt = iono.Time_Vector.shape[0]
    if set(iono.Coord_Vecs)=={'r','theta','phi'}:
        rngrdr =iono.Sphere_Coords[:,0].astype('float32')
        sign1 = sp.sign(iono.Sphere_Coords[:,1])
        el = iono.Sphere_Coords[:,2].astype('float32')
        elvec,elinv = sp.unique(el,return_inverse=True)
        nbeams = len(elvec)
        nrg = len(rngrdr)/nbeams
        
        Rngrdrmat = sp.reshape(rngrdr,(nrg,nbeams))
        Signmat = sp.reshape(sign1,(nrg,nbeams))
        Elmat = sp.reshape(el,(nrg,nbeams))
    
        Xmat = Rngrdrmat*Signmat*sp.cos(Elmat*sp.pi/180.)
        Zmat = Rngrdrmat*sp.sin(Elmat*sp.pi/180.)
        Ne = iono.Param_List[:,:,lag].reshape(nrg,nbeams,nt).real*ne_red
    elif set(iono.Coord_Vecs)=={'x','y','z'}:
        rng = sp.sqrt(iono.Cart_Coords[:,0]**2+iono.Cart_Coords[:,1]**2)*sp.sign(iono.Cart_Coords[:,1]).astype('float32')
        z = iono.Cart_Coords[:,2].astype('float32')
        rngvec = sp.unique(rng)
        zvec = sp.unique(z)
        Xmat = rng.reshape(len(zvec),len(rngvec))
        Zmat = z.reshape(len(zvec),len(rngvec))
        Ne = iono.Param_List[:,:,lag].reshape(len(zvec),len(rngvec),nt).real*ne_red
    imcount=0
    if filetemplate is None:
        filetemplate = 'acflag{0}'.format(lag)

    dsetname = os.path.split(os.path.dirname(testdir))[-1]
    print "Plotting Output data for "+dsetname

    if 'perryplane' in testdir.lower():
        xlim = [-200.,360.]
        xticks = [-150.,0.,150.,300.]

    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300]
    ncols=1
    figsize = (5,7)
    ylim = [100.,500]
    for itimen,itime in enumerate(iono.Time_Vector):
        print "{0} Output for {1} of {2}".format(dsetname,itimen,len(iono.Time_Vector))
        
        
        Nemat = Ne[:,:,itimen]

        
        fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize,sharey=True)

        avec=[axmat]

        plt.sca(avec[0])
        avec[0].set_xlabel('X Plane in km',fontsize=fs)
        avec[0].set_ylabel('Alt in km',fontsize=fs)
        pc1 = avec[0].pcolor(Xmat,Zmat,Nemat,cmap = defmap,vmin=nemin,vmax=nemax)
        plt.tick_params(labelsize=16)
        plt.xticks(xticks)
        avec[0].set_xlim(xlim)
        avec[0].set_ylim(ylim)
        avec[0].set_title('',fontsize=fs)
        tick_locator = ticker.MaxNLocator(nbins=5)
            
        cb1 = plt.colorbar(pc1, ax=avec[0])
        cb1.ax.xaxis.set_label_position('top')
        cb1.ax.set_xlabel(necbarstr)
        cb1.locator = tick_locator
        cb1.update_ticks()
        plt.tight_layout()

        fname= '{0:0>3}_'.format(imcount)+filetemplate+'.png'
        plt.savefig(os.path.join(imgdir,fname),dpi=300)
        imcount=imcount+1
        plt.close(fig)
        
#%% Alpha and error plotting
def plotalphaerror(alphaarr,errorarr,errorlagarr):
    """ This will plot the error with respect then alpha parameter for the 
        constraint. 
    """
    sns.set_style('whitegrid')
    sns.set_context('notebook')
    Nlag=errorlagarr.shape[-1]
    
    
    nlagplot=4.
    nrows=1+int(sp.ceil(float(Nlag)/(2*nlagplot)))

    fig=plt.figure(figsize=(8,4*nrows),facecolor='w')
    gs=gridspec.GridSpec(nrows,2)
    axmain=plt.subplot(gs[0,:])
    axlist=[plt.subplot(gs[int(sp.floor(float(i)/2.)+1),int(sp.mod(i,2))]) for i in range(2*(nrows-1))]
    
    axmain.plot(alphaarr,errorarr)
    axmain.set_xscale('log')
    axmain.set_yscale('log')
    axmain.set_title('Error From All Lags Added',fontsize=fs)
    axmain.set_ylabel('Error',fontsize=fs)
    axmain.set_xlabel(r'$\gamma$',fontsize=fs)
    
    for iaxn,iax in enumerate(axlist):
        strlist=[]
        handlist=[]
        for ilag in range(int(nlagplot)):
            curlag=int(iaxn*nlagplot+ilag)
            if curlag>=Nlag:
                break
            handlist.append(iax.plot(alphaarr,errorlagarr[:,curlag])[0])
            strlist.append('Lag {0}'.format(curlag))
        iax.set_xscale('log')
        iax.set_yscale('log')
        iax.set_title('Error From Lags',fontsize=fs)
        iax.set_ylabel('Error',fontsize=fs)
        iax.set_xlabel(r'$\gamma$',fontsize=fs)
        iax.legend(handlist,strlist,loc='upper right',fontsize='large')
    plt.tight_layout()
    return(fig,axlist,axmain)
    
def plotalphaerrorpub(alphaarr,errorarr,errorlagarr):
    """ This will plot the error with respect then alpha parameter for the 
        constraint. 
    """
    sns.set_style('whitegrid')
    sns.set_context('notebook')
    Nlag=errorlagarr.shape[-1]
    
    
    nlagplot=4.
    nrows=1+int(sp.ceil(float(Nlag)/(2*nlagplot)))
    
    fig,ax=plt.subplots(nrows=1,ncols=1,figsize=(8,4),facecolor='w')
    
    ax.plot(alphaarr,errorarr)
    ax.set_xscale('log')
    ax.set_yscale('log')
    ax.set_title('Error Lag Zero',fontsize=fs)
    ax.set_ylabel('Error',fontsize=fs)
    ax.set_xlabel(r'$\gamma$',fontsize=fs)
    

    return(fig,ax)


#%% 
def plotLcurve(alphaarr,datadif,constdif):
    """ 
    This will plot the L-curve for the first lag.
    """
    sns.set_style('whitegrid')
    sns.set_context('notebook')

    
    fig ,axmat= plt.subplots(nrows=1,ncols=1,facecolor='w',figsize=(6,6),sharey=True)
    axlist=axmat
    
    iax = axmat
    curlag=0
    axlist=iax.plot(datadif[:,curlag],constdif[:,curlag])[0]
    iax.set_xscale('log')
    iax.set_yscale('log')
    iax.set_title('L Curve',fontsize=fs)
    iax.set_xlabel(r'$\|Ax-b\|_2$',fontsize=fs)
    iax.set_ylabel(r'$f(x)$',fontsize=fs)
    plt.tight_layout()
    
    
    return(fig,axlist)
    
def plotLcurveall(alphaarr,datadif,constdif):
    """ 
    This will plot the L-curve for all of the lags
    """
    sns.set_style('whitegrid')
    sns.set_context('notebook')
    Nlag=datadif.shape[-1]
    
    
    nlagplot=4.
    nrows=int(sp.ceil(float(Nlag)/(2*nlagplot)))
    
    fig ,axmat= plt.subplots(nrows=nrows,ncols=2,facecolor='w',figsize=(8,4*nrows),sharey=True)
    axlist=axmat.flatten()
    
    
    for iaxn,iax in enumerate(axlist):
        strlist=[]
        handlist=[]
        for ilag in range(int(nlagplot)):
            curlag=int(iaxn*nlagplot+ilag)
            if curlag>=Nlag:
                break
            handlist.append(iax.plot(datadif[:,curlag],constdif[:,curlag])[0])
            strlist.append('Lag {0}'.format(curlag))
        iax.set_xscale('log')
        iax.set_yscale('log')
        iax.set_title('L Curve',fontsize=fs)
        iax.set_xlabel(r'$\|Ax-b\|_2$',fontsize=fs)
        iax.set_ylabel(r'$f(x)$',fontsize=fs)
        iax.legend(handlist,strlist,loc='upper right',fontsize='large')
    plt.tight_layout()
    return(fig,axlist)
def plotbackground(testdir,figname):
    """ 
    Plots the background densities and temperatures. 
    """
    sns.set_style('whitegrid')
    sns.set_context('notebook')
    sns.color_palette("hls", 8)
    filelist = glob.glob(os.path.join(testdir,'Origparams','*.h5'))
    numlist = [os.path.splitext(os.path.split(x)[-1])[0] for x in filelist]
    numdict = {numlist[i]:filelist[i] for i in range(len(filelist))}
    ylim = [100.,500.]
    slist = sorted(numlist,key=ke)
    ifile = numdict[slist[0]]
    Iono_in = IonoContainer.readh5(ifile)
    numz=sp.sum(Iono_in.Cart_Coords[:,2]==Iono_in.Cart_Coords[0,2])
    redcoords=Iono_in.Cart_Coords[numz/2::numz]
    z=redcoords[:,2]
    begdata = Iono_in.Param_List[numz/2::numz]
    allni=begdata[:,0,:-1,0]
    allti=begdata[:,0,:-1,1]
    T_all = begdata[:,0,:,1]    
    N_all=begdata[:,0,:,0]
    Te = begdata[:,0,-1,-1]
    Ne = begdata[:,0,-1,0]
    tini=allti*allni
    Nisum=allni.sum(-1)
    Ti=tini.sum(-1)/Nisum
    ncols=2
    figsize = (5*ncols,7)
    
    handlist=[]
    fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize,sharey=True)
    for i in range(len(Iono_in.Species)):
        p1=axmat[0].plot(N_all[:,i],z,label=Iono_in.Species[i],linewidth=lw)[0]
        handlist.append(p1)
    axmat[0].set_ylabel('Alt in km',fontsize=fs)
    axmat[0].set_ylim(ylim)
    axmat[0].set_xlabel(r'Number Density in m$^{-3}$',fontsize=fs)
    axmat[0].set_title('Ion and Electron Densities',fontsize=fs)
    axmat[0].set_xscale('log')
    axmat[0].set_xlim([1e2,3e11])
    axmat[0].legend(handlist,Iono_in.Species,loc='upper left',fontsize='large')
    
#    handlist2=[]
    p2=axmat[1].plot(Te,z,Ti,z,linewidth=lw)
#    for i in range(len(Iono_in.Species)):
#        p1=axmat[1].plot(T_all[:,i],z,label=Iono_in.Species[i],linewidth=lw)[0]
#        handlist2.append(p1)
    axmat[1].set_title('Ion and Electron Temperatures',fontsize=fs)
    axmat[1].set_xlabel(r'Temperature in $^{\circ}$K',fontsize=fs)
    axmat[1].set_xlim([0,2e3])
    axmat[1].set_ylim(ylim)
#    axmat[1].legend(handlist2,Iono_in.Species,loc='upper left',fontsize='large')
    axmat[1].legend(p2,['Te','Ti'],loc='upper left')
    
    fig.savefig(figname,dpi=300)

def plotlines(inputlist,fitiono,alt,times,fig, axvec,paramlist=['Ne','Te','Ti']):
    """
    Plots the values along a specific alittude. 
    """
    inputiono = makeionocombined(inputlist)
    Iono1 = GeoData(readIono,[inputiono])
    fitiono = IonoContainer.readh5(fitiono)
    fitGeo = GeoData(readIono,[fitiono])
    
    #paramlist = ['Ne','Te','Ti']
    (x,y,z) = inputiono.Cart_Coords.transpose()
    r = sp.sqrt(x**2+y**2)*sp.sign(y)
    incoords = sp.column_stack((r,z,sp.ones_like(z)))
    ru,zu =[ sp.unique(r),sp.unique(z)]
    Rmat,Zmat = sp.meshgrid(ru,zu)
    zinput = sp.argmin(sp.absolute(zu-alt))
    
    (xf,yf,zf) = fitiono.Cart_Coords.transpose()
    rf = sp.sqrt(xf**2+yf**2)*sp.sign(yf)
    outcoords = sp.column_stack((rf,zf,sp.ones_like(zf)))
    rfu,zfu =[ sp.unique(rf),sp.unique(zf)]
    Rfmat,Zfmat = sp.meshgrid(rfu,zfu)
    zoutput = sp.argmin(sp.absolute(zfu-alt))
    
    fitGeo.interpolate(incoords,Iono1.coordnames,method='linear',fill_value=sp.nan,twodinterp = True,oldcoords=outcoords)

    uz = sp.unique(z)
    ur = sp.unique(r)
    (rmat,zmat) = sp.meshgrid(ur,uz)
    
    inputdata = {}
    for iparm in paramlist:
        if iparm =='Nepow':
            iparm='Ne'
        curdata = Iono1.data[iparm][:,times[0]]
        
        inputdata[iparm] = sp.reshape(curdata,Rmat.shape)[zinput]

    outputdata = {}
    for iparm in paramlist:
        curdata = fitGeo.data[iparm][:, times[1]]
        outputdata[iparm] = sp.reshape(curdata,Rmat.shape)[zinput]
    
    #fig, axvec = plt.subplots(len(paramlist),1,sharey=False,figsize=(12,5*len(paramlist)))
    
    for ipn,iparam in enumerate(paramlist):
        ax = axvec[ipn]
        p1, = ax.plot(ru,inputdata[iparam],'b-',label='In',linewidth=3)
        p2, = ax.plot(ru,outputdata[iparam],'b--',label='Out',linewidth=3)
        ax.set_title(iparam)
        ax.set_xlabel('X Plane in km')
#        gi = sp.gradient(inputdata[iparam])/sp.gradient(ru)
#        go = sp.gradient(outputdata[iparam])/sp.gradient(ru)
#        p3, = ax2.plot(ru,gi,'g-',label='Grad In',linewidth=3)
#        p4, = ax2.plot(ru,go,'g--',label='Grad Out',linewidth=3)
        ax.yaxis.label.set_color(p1.get_color())
        #ax2.yaxis.label.set_color(p3.get_color())
        lines = [p1,p2]#,p3,p4]
        ax.legend(lines,[l.get_label() for l in lines])
    
    plt.tight_layout()    
    return(lines)

def plotgradlines(inputlist,fitiono,alt,times,paramlist=['Ne','Te','Ti']):
    """
    Plots the values along a specific alittude. 
    """
    inputiono = makeionocombined(inputlist)
    Iono1 = GeoData(readIono,[inputiono])
    fitiono = IonoContainer.readh5(fitiono)
    fitGeo = GeoData(readIono,[fitiono])
    
    paramlist = ['Ne','Te','Ti']
    (x,y,z) = inputiono.Cart_Coords.transpose()
    r = sp.sqrt(x**2+y**2)*sp.sign(y)
    incoords = sp.column_stack((r,z,sp.ones_like(z)))
    ru,zu =[ sp.unique(r),sp.unique(z)]
    Rmat,Zmat = sp.meshgrid(ru,zu)
    zinput = sp.argmin(sp.absolute(zu-alt))
    
    (xf,yf,zf) = fitiono.Cart_Coords.transpose()
    rf = sp.sqrt(xf**2+yf**2)*sp.sign(yf)
    outcoords = sp.column_stack((rf,zf,sp.ones_like(zf)))
    rfu,zfu =[ sp.unique(rf),sp.unique(zf)]
    Rfmat,Zfmat = sp.meshgrid(rfu,zfu)
    zoutput = sp.argmin(sp.absolute(zfu-alt))
    
    fitGeo.interpolate(incoords,Iono1.coordnames,method='linear',fill_value=sp.nan,twodinterp = True,oldcoords=outcoords)

    uz = sp.unique(z)
    ur = sp.unique(r)
    (rmat,zmat) = sp.meshgrid(ur,uz)
    
    inputdata = {}
    for iparm in paramlist:
        if iparm =='Nepow':
            iparm='Ne'
        curdata = Iono1.data[iparm][:,times[0]]
        
        inputdata[iparm] = sp.reshape(curdata,Rmat.shape)[zinput]

    outputdata = {}
    for iparm in paramlist:
        curdata = fitGeo.data[iparm][:, times[1]]
        outputdata[iparm] = sp.reshape(curdata,Rmat.shape)[zinput]
    
    fig, axvec = plt.subplots(len(paramlist),1,sharey=False,figsize=(12,5*len(paramlist)))
    
    for ipn,iparam in enumerate(paramlist):
        ax = axvec[ipn]
        ax2 = ax.twinx()
        p1, = ax.plot(ru,inputdata[iparam],'b-',label='In',linewidth=3)
        p2, = ax.plot(ru,outputdata[iparam],'b--',label='Out',linewidth=3)
        ax.set_title(iparam)
        ax.set_xlabel('X Plane in km')
        gi = sp.gradient(inputdata[iparam])/sp.gradient(ru)
        go = sp.gradient(outputdata[iparam])/sp.gradient(ru)
        p3, = ax2.plot(ru,gi,'g-',label='Grad In',linewidth=3)
        p4, = ax2.plot(ru,go,'g--',label='Grad Out',linewidth=3)
        ax.yaxis.label.set_color(p1.get_color())
        ax2.yaxis.label.set_color(p3.get_color())
        lines = [p1,p2,p3,p4]
        ax.legend(lines,[l.get_label() for l in lines])
    
    plt.tight_layout()    
    return(fig)

def plotsampling(testdir,outfile, ifile=None, wtimes=False):
    """This will plot all of the input data with each time step as a pcolor images of
    electron density and ion temperature.
    Inputs
    testdir - The directory with the input data in h5 files formated for the ionocontainer structure.
    imgdir - The directory that holds the images."""

  
    imcount = 0
    if ifile is None:
        filelist = glob.glob(os.path.join(testdir,'Origparams','*.h5'))
        numlist = [os.path.splitext(os.path.split(x)[-1])[0] for x in filelist]
        numdict = {numlist[i]:filelist[i] for i in range(len(filelist))}
        slist = sorted(numlist,key=ke)
        inumn=0
        inum = slist[0]
        dsetname = os.path.split(os.path.dirname(testdir))[-1]
        print "Plotting input data for "+dsetname

        print "{0} Input for {1} of {2}".format(dsetname,inumn,len(slist))
        ifile = numdict[inum]
        iono = IonoContainer.readh5(ifile)
    filetemplate = 'inputdata'

    if 'perryplane' in testdir.lower():
        xlim = [-150.,360.]
        xticks = [0.,150.,300.]
        allparams = True
        ncols=3
        figsize = (5,7)
    else:
        xlim = [0.,400.]
        xticks = [0.,150.,300.]
        allparams = False
        ncols=1
        figsize = (5,7)
    ylim = [100.,500.]
    f1 =  True
    
   
    if iono.Param_List.shape[-1]==1:
        nemax=1e10*ne_red
        nemin=0
    iono2 = IonoContainer.readh5(outfile)
    xout,yout,zout = iono2.Cart_Coords.transpose()
    rout=sp.sqrt(xout**2+yout**2)
    Iono1 = GeoData(readIono,[iono])
    nt = Iono1.times.shape[0]
    rng = sp.sqrt(Iono1.dataloc[:,0]**2+Iono1.dataloc[:,1]**2)*sp.sign(Iono1.dataloc[:,1]).astype('float32')
    z = Iono1.dataloc[:,2].astype('float32')
    rngvec = sp.unique(rng)
    zvec = sp.unique(z)
    rngmat = rng.reshape(len(zvec),len(rngvec))
    zmat = z.reshape(len(zvec),len(rngvec))
    if 'Ne' in Iono1.data.keys():
        Ne = Iono1.data['Ne'].reshape(len(zvec),len(rngvec),nt)*ne_red
    elif '0' in Iono1.data.keys():
        Ne = Iono1.data['Ne'].reshape(len(zvec),len(rngvec),nt)*ne_red

    itimen=0
    itime = Iono1.times[0]
    if f1:
        f1=False
        t0 = itime[0]
        fig ,axmat= plt.subplots(nrows=1,ncols=ncols,facecolor='w',figsize=figsize ,sharey=True)
        if allparams:
            avec = axmat.flatten()
        else:
            avec =[axmat]

    plt.sca(avec[0])
    plt.xticks(xticks)
    plt.tick_params(labelsize=16)
    avec[0].set_xlabel('X Plane in km',fontsize=fs)
    avec[0].set_ylabel('Alt in km',fontsize=fs)
    pc1 = avec[0].pcolor(rngmat,zmat,Ne[:,:,itimen],cmap = defmap,vmin=nemin,vmax=nemax)
    avec[0].set_xlim(xlim)
    avec[0].set_ylim(ylim)
    
    
   #pc1.set_norm(colors.LogNorm(vmin=5e8,vmax=5e12))
    tick_locator = ticker.MaxNLocator(nbins=5)
    
    cb1 = plt.colorbar(pc1, ax=avec[0])
    cb1.ax.xaxis.set_label_position('top')
    cb1.ax.set_xlabel(necbarstr,fontsize=fscb)
    cb1.locator = tick_locator
    cb1.update_ticks()
    plot1 = avec[0].plot(rout,zout,'w.',markersize=3)

    plt.tight_layout()
    if wtimes:
        plt.subplots_adjust(top=0.9)
        spti = fig.suptitle('Parameters at {0} seconds'.format(int(itime[0]-t0)),fontsize=24)
    return (fig,avec)
#!/usr/bin/env python Created on Wed Dec 30 16:20:38 2015  @author: <NAME> # fontsize #line width #%% For sorting #%% Plot input data This will plot all of the input data with each time step as a pcolor images of     electron density and ion tempreture.     Inputs     testdir - The directory with the input data in h5 files formated for the ionocontainer structure.     imgdir - The directory that holds the images. #pc1.set_norm(colors.LogNorm(vmin=5e8,vmax=5e12)) # for ax in avec: #    for label in (ax.get_xticklabels() + ax.get_yticklabels()): #       label.set_fontsize(20) #%%Plot output data This will plot all of the fitted data with each time step as a pcolor images of     electron density and electron density from power mesurements.     Inputs     testdir - The directory with the input data in h5 files formated for the ionocontainer structure.     imgdir - The directory that holds the images. #        for ax in avec: #            for label in (ax.get_xticklabels() + ax.get_yticklabels()): #                label.set_fontsize(20) #%% Error plotting This will plot all of the fitted data with each time step as a pcolor images of     electron density and electron density from power mesurements.     Inputs     testdir - The directory with the input data in h5 files formated for the ionocontainer structure.     imgdir - The directory that holds the images. This will plot all of the fitted data with each time step as a pcolor images of     electron density and electron density from power mesurements.     Inputs     testdir - The directory with the input data in h5 files formated for the ionocontainer structure.     imgdir - The directory that holds the images. #%% This will plot all of the fitted data with each time step as a pcolor images of     electron density and electron density from power mesurements.     Inputs     testdir - The directory with the input data in h5 files formated for the ionocontainer structure.     imgdir - The directory that holds the images. #    if os.path.exists(imgdir): #        imgfiles = glob.glob(os.path.join(imgdir,'*.png')) #        for imgf in imgfiles: #            os.remove(imgf) #    if iono.Param_List.shape[-1]==1: #        nemax=1e10 #        nemin=0 #%% Alpha and error plotting This will plot the error with respect then alpha parameter for the          constraint. This will plot the error with respect then alpha parameter for the          constraint. #%% This will plot the L-curve for the first lag. This will plot the L-curve for all of the lags Plots the background densities and temperatures. #    handlist2=[] #    for i in range(len(Iono_in.Species)): #        p1=axmat[1].plot(T_all[:,i],z,label=Iono_in.Species[i],linewidth=lw)[0] #        handlist2.append(p1) #    axmat[1].legend(handlist2,Iono_in.Species,loc='upper left',fontsize='large') Plots the values along a specific alittude. #paramlist = ['Ne','Te','Ti'] #fig, axvec = plt.subplots(len(paramlist),1,sharey=False,figsize=(12,5*len(paramlist))) #        gi = sp.gradient(inputdata[iparam])/sp.gradient(ru) #        go = sp.gradient(outputdata[iparam])/sp.gradient(ru) #        p3, = ax2.plot(ru,gi,'g-',label='Grad In',linewidth=3) #        p4, = ax2.plot(ru,go,'g--',label='Grad Out',linewidth=3) #ax2.yaxis.label.set_color(p3.get_color()) #,p3,p4] Plots the values along a specific alittude. This will plot all of the input data with each time step as a pcolor images of     electron density and ion temperature.     Inputs     testdir - The directory with the input data in h5 files formated for the ionocontainer structure.     imgdir - The directory that holds the images. #pc1.set_norm(colors.LogNorm(vmin=5e8,vmax=5e12))