def reco_energy_plot(config, out=False, batch=False):
# Load median file information
simBase = getSimBase(config)
inFile = '%s_median.npy' % simBase
d = np.load(inFile)
d = d.item()
xbins, ybins, ebins = d['xbins'], d['ybins'], d['ebins']
# Calculate median energy value from bin
energies = d['medians']
energies = energies.T
# Trim down the top of the grid
ycts = energies.sum(axis=1)
yidx = np.where(ycts==0)[0][0] + 2
ybins = ybins[:yidx]
energies = energies[:yidx]
emin, emax = energies[energies!=0].min(), energies[energies!=0].max()
emin, emax = 3.75, 8
ebins = [emin] + getEbins() + [emax]
fig = plt.figure(figsize=(8,6))
ax = fig.add_subplot(111)
X, Y = np.meshgrid(xbins, ybins)
cmap = plt.cm.jet
cmap = cmap_discretize(cmap, ebins)
cmap.set_under('white')
tPars = {'fontsize':16}
p = ax.pcolor(X, Y, energies, cmap=cmap, vmin=emin, vmax=emax)
cb = fig.colorbar(p, ax=ax, ticks=ebins)
cb.ax.set_yticklabels(['%.2f' % ebin for ebin in ebins])
cb.set_label(r'$\mathrm{log}_{10}(E/\mathrm{GeV})$',
rotation=270, labelpad=20, **tPars)
#ax.set_title('Median Energy vs Zenith and Nchannel')
ax.set_xlabel(r'$\mathrm{cos}(\theta_\mathrm{reco})$', **tPars)
ax.set_ylabel(r'$\mathrm{log}_{10}(N_\mathrm{channel})$', **tPars)
ax.set_xlim(xbins.min(), xbins.max())
ax.set_ylim(ybins.min(), ybins.max())
if out != False:
#outFile = '%s/%s_Median_Energy' % (outPrefix, config)
plt.savefig(out, dpi=300, bbox_inches='tight')
if not batch:
plt.show()
def spline(config, inFile, outFile, plot=False):
# Load input median file
d = np.load(inFile)
d = d.item()
xbins, ybins = d['xbins'], d['ybins']
energies = d['medians']
vars = d['var']
vars[vars<1e-15] = np.inf # Variances sufficiently close to 0 aren't real
w = 1/vars
emin, emax = energies[energies!=0].min(), energies.max()
ebins = [emin] + getEbins() + [emax]
axes, knots = [],[]
binList = [xbins, ybins]
nknots = 30
step_scale = 2/5.
for bins in binList:
mids = (bins[1:]+bins[:-1])/2.
axes += [mids]
step = (bins.max() - bins.min()) * step_scale
knots += [np.linspace(bins.min()-step, bins.max()+step, nknots)]
tab = glam.fit(energies, w, axes, knots, order=(4), \
penalties={2:1e-3})
if plot:
# Look at spline fit with finer binning
fitaxes = [[],[]]
fitaxes[0] = np.linspace(xbins.min(),xbins.max(),len(xbins)*3)
fitaxes[1] = np.linspace(ybins.min(),ybins.max(),len(ybins)*3)
fit = glam.grideval(tab, fitaxes)
#err_fit = 10**glam.grideval(err_tab,axes)
fig = plt.figure(figsize=(17,6))
mpl.rc("font", family="serif")
X, Y = np.meshgrid(axes[0], axes[1])
fitX, fitY = np.meshgrid(fitaxes[0], fitaxes[1])
# Setup custom colormap
cmap = plt.cm.jet
cmap = cmap_discretize(cmap, ebins)
cmap.set_under('white')
ax = fig.add_subplot(121)
p = ax.pcolor(fitX, fitY, fit.T, cmap=cmap, vmin=emin, vmax=emax)
cb = fig.colorbar(p, ax=ax)
ax.set_title('Median Energy')
ax.set_xlabel('cos(zenith)')
ax.set_ylabel('log10(Nchannel)')
ax.set_xlim(xbins.min(), xbins.max())
ax.set_ylim(ybins.min(), ybins.max())
ax = fig.add_subplot(122)
p = ax.pcolor(X, Y, energies.T, cmap=cmap, vmin=emin, vmax=emax)
ax.set_title('Median Energy')
ax.set_xlabel('cos(zenith)')
ax.set_ylabel('log10(Nchannel)')
ax.set_xlim(xbins.min(), xbins.max())
ax.set_ylim(ybins.min(), ybins.max())
plt.show()
if outFile:
if os.path.exists(outFile):
os.remove(outFile)
splinefitstable.write(tab, outFile)