if item[0].isdigit():

return int(item.partition(' ')[0])

else:

"""

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)

"""

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

"""

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

"""

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

"""

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

""" 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()

""" 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)

"""

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()

"""

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()

"""

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')

"""

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()

"""

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()

"""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