betaeconst=BETAECONST,betaecrit=BETAECRIT,

bscl=BSCL,gmin=GAMMAMIN,gmax=GAMMAMAX,pnth=PNTH):

""" run grtrans single image"""

print("Run image, bscl=%.2f"%bscl)

size = 0.5*FOV

uout = 1./(DEPTH*size)

# pressure scale is fixed!

pscl = (bscl**2)/(8*np.pi)

# TO TURN OFF FARADAY CONVERSTION

epcoefindx=[1,1,1,1,1,1,1]

#epcoefindx=[1,1,1,1,0,1,1]

x=gr.grtrans()

x.write_grtrans_inputs(fname+'_im.in', oname=fname+'_im.out',

fname='RRJET', phi0=0.,

pegasratio=pegasratio,

betaeconst=betaeconst, betaecrit=betaecrit,

ximax=XIMAX, bscl=bscl, pscl=pscl,

nfreq=1,fmin=RFGHZ*1.e9,fmax=RFGHZ*1.e9,

gmin=gmin, gmax=gmax, p2=pnth, p1=pnth,

fpositron=fpositron,

epcoefindx=epcoefindx,

ename='POLSYNCHPL',

nvals=4,

spin=A, standard=1,

uout=uout,

mbh=MBH,

nmu=1,mumin=mu,mumax=mu,

gridvals=[-size,size,-size,size],

nn=[NPIX,NPIX,NGEO],

hindf=1,hnt=1,

muval=1.)

# run grtrans

if RERUN:

x.run_grtrans()

# load image data

x.read_grtrans_output()

# pixel sizes

#da = x.ab[x.nx,0]-x.ab[0,0]

da = x.ab[x.ny,0]-x.ab[0,0] ##TODO -- is this right ordering?

db = x.ab[1,1]-x.ab[0,1]

if (da!=db): raise Exception("pixel da!=db")

psize = da*(cmperrg/bhdist)

#image values

ivals = x.ivals[:,0,0]*LumFac*da*db*LumtoJy

qvals = x.ivals[:,1,0]*LumFac*da*db*LumtoJy

uvals = x.ivals[:,2,0]*LumFac*da*db*LumtoJy

vvals = x.ivals[:,3,0]*LumFac*da*db*LumtoJy

# mask pixels with I < 0

imask = ivals < 0.

ivals[imask] = 0.

qvals[imask] = 0.

uvals[imask] = 0.

vvals[imask] = 0.

# correct orientation for eht-imaging

ivals = (np.flipud(np.transpose(ivals.reshape((NPIX,NPIX))))).flatten()

qvals = -(np.flipud(np.transpose(qvals.reshape((NPIX,NPIX))))).flatten()

uvals = -(np.flipud(np.transpose(uvals.reshape((NPIX,NPIX))))).flatten()

vvals = (np.flipud(np.transpose(vvals.reshape((NPIX,NPIX))))).flatten()

imdata = (ivals, qvals, uvals, vvals, psize)

# Rotate the image

if ROTANG!=0:

imdata = rotateimdata(imdata, ROTANG, interp='cubic')

# save image

if SAVEOUT:

save_im_fits(imdata, fname + ('_%.0f.fits'%RFGHZ), freq_ghz=RFGHZ)

# display images

if DISPLAYOUT:

#tmax=5.e10

#pmax=2.e10

tmax = np.max( ivals*3.254e13/((RFGHZ*1.e9)**2 * psize**2))

pmax = np.max( np.sqrt(qvals**2 + uvals**2)*3.254e13/((RFGHZ*1.e9)**2 * psize**2))

betaeconst=BETAECONST,betaecrit=BETAECRIT,

gmin=GAMMAMIN,gmax=GAMMAMAX,pnth=PNTH):

""" run grtrans single image to find the bscl that gives the correct flux with bisection,

for all other parameters fixed """

# convergance parameters

bedge_stop = 1

fluxconvratio = .05

itermax = 20

# these image parameters are fixed for now

fov_search = FOV/2.

npix_search = int(NPIX/2)

size = 0.5*fov_search

uout = 1./(DEPTH*size)

bsclmin0 = bsclmin

bsclmax0 = bsclmax

for i in range(itermax):

# bscl by bisection

bscl = (bsclmax+bsclmin)/2.

if bsclmax0-bscl < bedge_stop:

print("did not find solution -- to close to bsclmax!")

break

if bscl-bsclmin0 < bedge_stop:

print("did not find solution -- to close to bsclmin!")

break

# pressure scale is fixed!

pscl = (bscl**2)/(8*np.pi)

x=gr.grtrans()

x.write_grtrans_inputs(fname+'_SEARCH.in', oname=fname+'_SEARCH.out',

fname='RRJET', phi0=0., pegasratio=pegasratio,

betaeconst=betaeconst, betaecrit=betaecrit,

ximax=XIMAX, bscl=bscl, pscl=pscl,

nfreq=1,fmin=RFGHZ*1.e9,fmax=RFGHZ*1.e9,

gmin=gmin, gmax=gmax, p2=pnth, p1=pnth,

fpositron=fpositron,

ename='POLSYNCHPL',

nvals=1,

spin=A, standard=1,

uout=uout,

mbh=MBH,

nmu=1,mumin=mu,mumax=mu,

gridvals=[-size,size,-size,size],

nn=[npix_search,npix_search,NGEO],

hindf=1,hnt=1,

muval=1.)

# run grtrans

x.run_grtrans()

# load image data

x.read_grtrans_output()

# pixel sizes

#da = x.ab[x.nx,0]-x.ab[0,0]

da = x.ab[x.ny,0]-x.ab[0,0] ##TODO -- is this right ordering?

db = x.ab[1,1]-x.ab[0,1]

if (da!=db): raise Exception("pixel da!=db")

psize = da*(cmperrg/bhdist)

#image values

ivals = x.ivals[:,0,0]*LumFac*da*db*LumtoJy

imask = ivals < 0.

ivals[imask] = 0.

#total flux

tflux = np.sum(ivals)

tfluxdiff = tflux-flux

tfluxdiff_rel = np.abs(tfluxdiff/flux)

print("iter %i %.1f | %.3f/%.3f %.2f"%(i+1,bscl,tflux,flux,tfluxdiff_rel))

# flux must monotonically increase with bscl, if all other params fixed

if tfluxdiff_rel < fluxconvratio:

print("solution: bscl=%.2f, tflux=%.3f" %(bscl,tflux))

break

if (tflux<flux):

bsclmin=bscl

elif (tflux>flux):

bsclmax=bscl

if i==itermax-1:

print("did not find solution -- reached itermax!")

break

betaeconst=BETAECONST,betaecrit=BETAECRIT,

bscl=BSCL,gmin=GAMMAMIN,gmax=GAMMAMAX,pnth=PNTH):

"""Run grtrans spectrum"""

size_spec = 0.5*FOV_SPEC

uout_spec = 1./(DEPTH*size_spec)

npix_x = NPIX_SPEC

npix_y = NPIX_SPEC

size_x = size_spec

size_y = size_spec

# pressure scale is fixed!

pscl = (bscl**2)/(8*np.pi)

x=gr.grtrans()

x.write_grtrans_inputs(fname+'_spec.in', oname=fname+'_spec.out',

fname='RRJET', phi0=0., pegasratio=pegasratio,

betaeconst=betaeconst, betaecrit=betaecrit,

ximax=XIMAX, bscl=bscl, pscl=pscl,

nfreq=NFREQ,fmin=FMIN,fmax=FMAX,

gmin=gmin, gmax=gmax, p2=pnth, p1=pnth,

fpositron=fpositron,

ename='POLSYNCHPL',

nvals=4,

spin=A, standard=1,

uout=uout_spec,

mbh=MBH,

nmu=1,mumin=mu,mumax=mu,

gridvals=[-size_x,size_x,-size_y,size_y],

nn=[npix_x,npix_y,NGEO],

hindf=1,hnt=1,

muval=1.)

# run grtrans

if RERUN:

x.run_grtrans()

# load spectrum

x.read_grtrans_output()

x.calc_freqs(NFREQ)

x.convert_to_lum()

spec = x.spec[0][0:NFREQ]

qspec = x.spec[1][0:NFREQ]

uspec = x.spec[2][0:NFREQ]

vspec = x.spec[3][0:NFREQ]

if npix_x==1 or npix_y==1:

spec *= 0.5 # divide by 2 because we have +/- r in the strip

qspec *= 0.5

uspec *= 0.5

vspec *= 0.5

freqs = x.freqs

# save spectrum

if SAVEOUT:

outdat = np.vstack([freqs,spec,qspec,uspec,vspec]).T

np.savetxt(fname + '_spec.txt', outdat)

# display spectrum

if DISPLAYOUT:

# plot Stokes I spectrum -- nu*Lnu

f=plt.figure(111,figsize=(16,16))

plt.clf()

ax=f.add_subplot(111)

plt.rc('text', usetex=True)

plt.rc('font', family='serif')

plt.xscale('log')

plt.yscale('log')

plt.xlabel('$\\nu$ (Hz)', size=26)

plt.ylabel('$\\nu L_{\\nu}$ (erg s$^{-1}$)', size=26)

plt.xlim([1.e9,1.e16])

plt.ylim([1.e39,1.e42])

plt.tick_params(axis='both',labelsize=22)

plt.ion()

ax = plot_m87_data(ax)

#linestyles=['solid','dashdot','dashed']

ls = 'solid'

spec_interp = interp1d(np.log10(freqs), np.log10(spec), kind=2)

logfreqs_plot = np.linspace(np.log10(FMIN), np.log10(FMAX), 500)

logspec_plot = spec_interp(logfreqs_plot)

plt.plot(10**logfreqs_plot, 10**(logfreqs_plot+logspec_plot), 'k-',

linewidth=2, label=r'I, $f_p=%.1f$'%FPOSITRON, linestyle=ls)

plt.legend()

#########################

# plot Stokes I spectrum -- Fnu

f=plt.figure(222,figsize=(16,16))

plt.clf()

ax=f.add_subplot(111)

plt.rc('text', usetex=True)

plt.rc('font', family='serif')

plt.xscale('log')

plt.yscale('log')

plt.xlabel('$\\nu$ (Hz)', size=26)

plt.ylabel('$F_{\\nu}$ (Jy)', size=26)

plt.xlim([1.e9,1.e16])

plt.ylim([1.e-5,10.])

plt.tick_params(axis='both',labelsize=22)

plt.ion()

ax = plot_m87_data_Jy(ax)

#linestyles=['solid','dashdot','dashed']

ls = 'solid'

spec *= LumtoJy

spec_interp = interp1d(np.log10(freqs), np.log10(spec), kind=2)

logfreqs_plot = np.linspace(np.log10(FMIN), np.log10(FMAX), 500)

logspec_plot = spec_interp(logfreqs_plot)

#plt.plot(freqs, freqs*spec, 'k-', linewidth=2, label=r'I, $f_p=%.1f$'%FPOSITRON, linestyle=ls)

plt.plot(10**logfreqs_plot, 10**(logspec_plot), 'k-',

linewidth=2, label=r'I, $f_p=%.1f$'%FPOSITRON, linestyle=ls)

(I_im, Q_im, U_im, V_im, psize) = imdata

I_im = I_im.reshape((NPIX,NPIX))

Q_im = Q_im.reshape((NPIX,NPIX))

U_im = U_im.reshape((NPIX,NPIX))

V_im = V_im.reshape((NPIX,NPIX))

# convert to brightness temperature Tb

totalflux = np.sum(I_im)

factor = 3.254e13/((RFGHZ*1.e9)**2 * psize**2)

I_im *= factor

Q_im *= factor

U_im *= factor

V_im *= factor

# Polarization Vectors

P_im = np.abs(Q_im + 1j*U_im)

m_im = P_im/I_im

thin = NPIX//nvec

mask = I_im > veccut * np.max(I_im)

mask2 = mask[::thin, ::thin]

m = m_im[::thin, ::thin][mask2]

x = (np.array([[i for i in range(NPIX)] for j in range(NPIX)])[::thin, ::thin])

x = x[mask2]

y = (np.array([[j for i in range(NPIX)] for j in range(NPIX)])[::thin, ::thin])

y = y[mask2]

a = (-np.sin(np.angle(Q_im+1j*U_im)/2)[::thin, ::thin])

a = a[mask2]

b = ( np.cos(np.angle(Q_im+1j*U_im)/2)[::thin, ::thin])

b = b[mask2]

P_im[np.logical_not(mask)]=0.

m_im[np.logical_not(mask)]=0.

# ticks

xticks = ticks(NPIX, FOV/float(NPIX))

yticks = ticks(NPIX, FOV/float(NPIX))

# display Stokes I

plt.figure(0)

im = plt.imshow(I_im, cmap=plt.get_cmap(cfun), interpolation='gaussian',vmin=0,vmax=tmax)

cb = plt.colorbar(im, fraction=0.046, pad=0.04, orientation="vertical")

cb.set_label('Tb (K)', fontsize=14)

plt.title(("Stokes I, %.2f GHz, %.2f Jy" % (RFGHZ, totalflux)), fontsize=16)

plt.xticks(xticks[0], xticks[1])

plt.yticks(yticks[0], yticks[1])

plt.xlabel('x/rg')

plt.ylabel('y/rg')

# display Stokes Q

plt.figure(1)

im = plt.imshow(Q_im, cmap=plt.get_cmap(cfun2), interpolation='gaussian',vmin=-pmax,vmax=pmax)

cb = plt.colorbar(im, fraction=0.046, pad=0.04, orientation="vertical")

cb.set_label('Tb (K)', fontsize=14)

plt.title(("Stokes Q, %.2f GHz " % (RFGHZ)), fontsize=16)

plt.xticks(xticks[0], xticks[1])

plt.yticks(yticks[0], yticks[1])

plt.xlabel('x/rg')

plt.ylabel('y/rg')

# display Stokes U

plt.figure(2)

im = plt.imshow(U_im, cmap=plt.get_cmap(cfun2), interpolation='gaussian',vmin=-pmax,vmax=pmax)

cb = plt.colorbar(im, fraction=0.046, pad=0.04, orientation="vertical")

cb.set_label('Tb (K)', fontsize=14)

plt.title(("Stokes U, %.2f GHz " % (RFGHZ)), fontsize=16)

plt.xticks(xticks[0], xticks[1])

plt.yticks(yticks[0], yticks[1])

plt.xlabel('x/rg')

plt.ylabel('y/rg')

# display Stokes V

plt.figure(3)

im = plt.imshow(V_im, cmap=plt.get_cmap(cfun2), interpolation='gaussian',vmin=-pmax,vmax=pmax)

cb = plt.colorbar(im, fraction=0.046, pad=0.04, orientation="vertical")

cb.set_label('Tb (K)', fontsize=14)

voi = np.sum(V_im)/np.sum(I_im)

plt.title(("Stokes V, %.2f GHz , V/I=%.2f " % (RFGHZ, voi)), fontsize=16)

plt.xticks(xticks[0], xticks[1])

plt.yticks(yticks[0], yticks[1])

plt.xlabel('x/rg')

plt.ylabel('y/rg')

# display P

plt.figure(4)

im = plt.imshow(P_im, cmap=plt.get_cmap(cfun), interpolation='gaussian',vmin=0,vmax=pmax)

cb = plt.colorbar(im, fraction=0.046, pad=0.04, orientation="vertical")

cb.set_label('Tb (K)', fontsize=14)

poi = np.sum(P_im)/np.sum(I_im)

plt.title(("P, %.2f GHz , P/I=%.2f" % (RFGHZ,poi)), fontsize=16)

plt.xticks(xticks[0], xticks[1])

plt.yticks(yticks[0], yticks[1])

plt.xlabel('x/rg')

plt.ylabel('y/rg')

# display m

plt.figure(5)

im = plt.imshow(m_im, cmap=plt.get_cmap('viridis'), interpolation='gaussian')

cb = plt.colorbar(im, fraction=0.046, pad=0.04, orientation="vertical")

cb.set_label('P/I', fontsize=14)

plt.title(("P/I, %.2f GHz , P/I=%.2f" % (RFGHZ,poi)), fontsize=16)

plt.xticks(xticks[0], xticks[1])

plt.yticks(yticks[0], yticks[1])

plt.xlabel('x/rg')

plt.ylabel('y/rg')

# display I with pol ticks

plt.figure(6)

im = plt.imshow(I_im, cmap=plt.get_cmap(cfun), interpolation='gaussian',vmin=0,vmax=tmax)

cb = plt.colorbar(im, fraction=0.046, pad=0.04, orientation="vertical")

cb.set_label('Tb (K)', fontsize=14)

plt.title(("I, %.2f GHz " % (RFGHZ)), fontsize=16)

plt.xticks(xticks[0], xticks[1])

plt.yticks(yticks[0], yticks[1])

plt.xlabel('x/rg')

plt.ylabel('y/rg')

plt.quiver(x, y, a, b,

headaxislength=20, headwidth=1, headlength=.01, minlength=0, minshaft=1,

width=.01*NPIX, units='x', pivot='mid', color='k', angles='uv',

scale=1.0/thin)

plt.quiver(x, y, a, b,

headaxislength=20, headwidth=1, headlength=.01, minlength=0, minshaft=1,

width=.005*NPIX, units='x', pivot='mid', color='w', angles='uv',

"""Return a list of ticklocs and ticklabels

psize should be in desired units

"""

axisdim = int(axisdim)

nticks = int(nticks)

if not axisdim % 2: axisdim += 1

if nticks % 2: nticks -= 1

tickspacing = float((axisdim-1))/nticks

ticklocs = np.arange(0, axisdim+1, tickspacing) - 0.5

ticklabels= np.around(psize * np.arange((axisdim-1)/2.0, -(axisdim)/2.0, -tickspacing), decimals=1)

(imvec, qvec, uvec, vvec, psize) = imdata

order=3

if interp=='linear': order=1

elif interp=='cubic': order=3

elif interp=='quintic': order=5

# Define an interpolation function

def rot_imvec(imvec):

imarr_rot = interpolation.rotate(imvec.reshape((NPIX, NPIX)),

angle, reshape=False, order=order,

mode='constant',

cval=0.0, prefilter=True)

return imarr_rot.flatten()

# Make new image vectors

imvec_rot = rot_imvec(imvec)

vvec_rot = rot_imvec(vvec)

qvec_rot = rot_imvec(qvec)

uvec_rot = rot_imvec(uvec)

# correctly transform Q,U

rlvec_rot = np.exp(1j*2*angle*degree) * (qvec_rot + 1j*uvec_rot)

qvec_rot = np.real(rlvec_rot)

uvec_rot = np.imag(rlvec_rot)

imdata_out = (imvec_rot, qvec_rot, uvec_rot, vvec_rot, psize)

mjd=MJD, source=SOURCE, ra=RA, dec=DEC):

# unpack the image data

(imvec, qvec, uvec, vvec, psize) = imdata

# Create header and fill in some values

header = fits.Header()

header['OBJECT'] = source

header['CTYPE1'] = 'RA---SIN'

header['CTYPE2'] = 'DEC--SIN'

header['CDELT1'] = -psize/degree

header['CDELT2'] = psize/degree

header['OBSRA'] = ra * 180/12.

header['OBSDEC'] = dec

header['FREQ'] = freq_ghz * 1.e9

#TODO these are the default values for centered images

#TODO support for arbitrary CRPIX?

header['CRPIX1'] = NPIX/2. + .5

header['CRPIX2'] = NPIX/2. + .5

header['MJD'] = float(mjd)

header['TELESCOP'] = 'VLBI'

header['BUNIT'] = 'JY/PIXEL'

header['STOKES'] = 'I'

# Create the fits image

image = np.reshape(imvec,(NPIX,NPIX))[::-1,:] #flip y axis!

hdu = fits.PrimaryHDU(image, header=header)

hdulist = [hdu]

if len(qvec):

qimage = np.reshape(qvec,(NPIX,NPIX))[::-1,:]

uimage = np.reshape(uvec,(NPIX,NPIX))[::-1,:]

header['STOKES'] = 'Q'

hduq = fits.ImageHDU(qimage, name='Q', header=header)

header['STOKES'] = 'U'

hduu = fits.ImageHDU(uimage, name='U', header=header)

hdulist = [hdu, hduq, hduu]

if len(vvec):

vimage = np.reshape(vvec,(NPIX,NPIX))[::-1,:]

header['STOKES'] = 'V'

hduv = fits.ImageHDU(vimage, name='V', header=header)

hdulist.append(hduv)

hdulist = fits.HDUList(hdulist)

# Save fits

try:

hdulist.writeto(fname, overwrite=True)

except:

hdulist.writeto(fname, clobber=True)

CAPSIZE = .8

if NEWDATA:

# Data from 2017 eht campaign

data1 = np.loadtxt(M87DIR + '/m87_sed_2017.dat')

data=data1

freqsdat = data[:,1]

lumval = freqsdat*data[:,3] / LumtoJy

lumerr = freqsdat*data[:,4] / LumtoJy

(_,caps,_) = plt.errorbar(freqsdat,lumval,yerr=lumerr,fmt='o',

color='k',ecolor='k',markersize=4*CAPSIZE,

markerfacecolor=None,capthick=CAPSIZE,capsize=CAPSIZE*4)

for cap in caps:

cap.set_color('black')

else:

# data table 1 -- core flux in quiescent --- lower resolution

data1 = np.loadtxt(M87DIR + '/m87_data_1.txt')

data=data1

freqsdat = data[:,0]

lumval = freqsdat*data[:,1] / LumtoJy

lumerr = freqsdat*data[:,2] / LumtoJy

(_,caps,_) = plt.errorbar(freqsdat,lumval,yerr=lumerr,fmt='o',color='k',ecolor='k',

markersize=4*CAPSIZE,

markerfacecolor=None,capthick=CAPSIZE,capsize=CAPSIZE*4)

for cap in caps:

cap.set_color('black')

# Michael total flux

datam = np.loadtxt(M87DIR + '/m87_data_michael.txt')

data=datam

freqsdat = data[:,0]

lumval = freqsdat*data[:,1] / LumtoJy

lumerr = freqsdat*data[:,2] / LumtoJy

(_,caps,_) = plt.errorbar(freqsdat,lumval,yerr=lumerr,fmt="v",color='c',ecolor='c',

markersize=6*CAPSIZE,capthick=2*CAPSIZE,capsize=CAPSIZE*4,zorder=10)

for cap in caps:

cap.set_color('c')

#cap.set_markeredgewidth(2)

# # Michael core flux

# datam = np.loadtxt(M87DIR + '/m87_data_michael_core.txt')

# data=datam

# freqsdat = data[:,0]

# lumval = freqsdat*data[:,1] / LumtoJy

# lumerr = freqsdat*data[:,2] / LumtoJy

# (_,caps,_) = plt.errorbar(freqsdat,lumval,yerr=lumerr,fmt='^',color='m',ecolor='m',

# markersize=6*CAPSIZE,capthick=2*CAPSIZE,

# capsize=CAPSIZE*4, zorder=10)

# for cap in caps:

# cap.set_color('m')

CAPSIZE = .8

if NEWDATA:

# data from 2017 eht campaign

data1 = np.loadtxt(M87DIR + '/m87_sed_2017.dat')

data=data1

freqsdat = data[:,1]

lumval = data[:,3]

lumerr = data[:,4]

(_,caps,_) = plt.errorbar(freqsdat,lumval,yerr=lumerr,fmt='o',

color='k',ecolor='k',markersize=4*CAPSIZE,

markerfacecolor=None,capthick=CAPSIZE,capsize=CAPSIZE*4)

for cap in caps:

cap.set_color('black')

else:

# data table 1 -- core flux in quiescent --- lower resolution

data1 = np.loadtxt(M87DIR + '/m87_data_1.txt')

data=data1

freqsdat = data[:,0]

lumval = data[:,1]

lumerr = data[:,2]

(_,caps,_) = plt.errorbar(freqsdat,lumval,yerr=lumerr,fmt='o',

color='k',ecolor='k',markersize=4*CAPSIZE,

markerfacecolor=None,capthick=CAPSIZE,capsize=CAPSIZE*4)

for cap in caps:

cap.set_color('black')

# Michael total flux

datam = np.loadtxt(M87DIR + '/m87_data_michael.txt')

data=datam

freqsdat = data[:,0]

lumval = data[:,1]

lumerr = data[:,2]

(_,caps,_) = plt.errorbar(freqsdat,lumval,yerr=lumerr,fmt="v",color='c',ecolor='c',

markersize=6*CAPSIZE,capthick=2*CAPSIZE,capsize=CAPSIZE*4,zorder=10)

for cap in caps:

cap.set_color('c')

#cap.set_markeredgewidth(2)

"""Return a list of ticklocs and ticklabels

psize should be in desired units

"""

axisdim = int(axisdim)

nticks = int(nticks)

if not axisdim % 2: axisdim += 1

if nticks % 2: nticks -= 1

tickspacing = float((axisdim-1))/nticks

ticklocs = np.arange(0, axisdim+1, tickspacing) - 0.5

ticklabels= np.around(psize * np.arange((axisdim-1)/2.0, -(axisdim)/2.0, -tickspacing), decimals=1)