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-rw-r--r--golemflavor/plot.py56
1 files changed, 28 insertions, 28 deletions
diff --git a/golemflavor/plot.py b/golemflavor/plot.py
index c91f70b..2fc3210 100644
--- a/golemflavor/plot.py
+++ b/golemflavor/plot.py
@@ -7,7 +7,7 @@
Plotting functions for the BSM flavour ratio analysis
"""
-from __future__ import absolute_import, division
+from __future__ import absolute_import, division, print_function
import os
import socket
@@ -127,14 +127,14 @@ def cmap_discretize(cmap, N):
indices = np.linspace(0, 1., N+1)
cdict = {}
for ki,key in enumerate(('red','green','blue')):
- cdict[key] = [ (indices[i], colors_rgba[i-1,ki], colors_rgba[i,ki]) for i in xrange(N+1) ]
+ cdict[key] = [ (indices[i], colors_rgba[i-1,ki], colors_rgba[i,ki]) for i in range(N+1) ]
# Return colormap object.
return mpl.colors.LinearSegmentedColormap(cmap.name + "_%d"%N, cdict, 1024)
def get_limit(scales, statistic, args, mask_initial=False, return_interp=False):
max_st = np.max(statistic)
- print 'scales, stat', zip(scales, statistic)
+ print('scales, stat', zip(scales, statistic))
if args.stat_method is StatCateg.BAYESIAN:
if (statistic[0] - max_st) > np.log(10**(BAYES_K)):
raise AssertionError('Discovered LV!')
@@ -142,7 +142,7 @@ def get_limit(scales, statistic, args, mask_initial=False, return_interp=False):
try:
tck, u = splprep([scales, statistic], s=0)
except:
- print 'Failed to spline'
+ print('Failed to spline')
# return None
raise
sc, st = splev(np.linspace(0, 1, 1000), tck)
@@ -164,14 +164,14 @@ def get_limit(scales, statistic, args, mask_initial=False, return_interp=False):
# null = statistic_rm[0]
if args.stat_method is StatCateg.BAYESIAN:
reduced_ev = -(statistic_rm - null)
- print '[reduced_ev > np.log(10**(BAYES_K))]', np.sum([reduced_ev > np.log(10**(BAYES_K))])
+ print('[reduced_ev > np.log(10**(BAYES_K))]', np.sum([reduced_ev > np.log(10**(BAYES_K))]))
al = scales_rm[reduced_ev > np.log(10**(BAYES_K))]
else:
assert 0
if len(al) == 0:
- print 'No points for DIM {0} [{1}, {2}, {3}]!'.format(
+ print('No points for DIM {0} [{1}, {2}, {3}]!'.format(
args.dimension, *args.source_ratio
- )
+ ))
return None
re = -(statistic-null)[scales > al[0]]
if np.sum(re < np.log(10**(BAYES_K)) - 0.1) >= 2:
@@ -362,9 +362,9 @@ def flavour_contour(frs, nbins, coverage, ax=None, smoothing=0.4,
# Get vertices inside covered region
binx = np.linspace(0, 1, os_nbins+1)
interp_dict = {}
- for i in xrange(len(binx)):
- for j in xrange(len(binx)):
- for k in xrange(len(binx)):
+ for i in range(len(binx)):
+ for j in range(len(binx)):
+ for k in range(len(binx)):
if mask[i][j][k] == 1:
interp_dict[(i, j, k)] = H_s[i, j, k]
vertices = np.array(heatmap(interp_dict, os_nbins))
@@ -459,8 +459,8 @@ def chainer_plot(infile, outfile, outformat, args, llh_paramset, fig_text=None,
raw = np.load(infile)
else:
raw = infile
- print 'raw.shape', raw.shape
- print 'raw', raw
+ print('raw.shape', raw.shape)
+ print('raw', raw)
make_dir(outfile), make_dir
if fig_text is None:
@@ -471,7 +471,7 @@ def chainer_plot(infile, outfile, outformat, args, llh_paramset, fig_text=None,
if ranges is None: ranges = llh_paramset.ranges
if args.plot_angles:
- print "Making triangle plots"
+ print("Making triangle plots")
Tchain = raw
g = plot_Tchain(Tchain, axes_labels, ranges)
@@ -496,14 +496,14 @@ def chainer_plot(infile, outfile, outformat, args, llh_paramset, fig_text=None,
# )
for of in outformat:
- print 'Saving', outfile+'_angles.'+of
+ print('Saving', outfile+'_angles.'+of)
g.export(outfile+'_angles.'+of)
if not hasattr(args, 'plot_elements'):
return
if args.plot_elements:
- print "Making triangle plots"
+ print("Making triangle plots")
if args.fix_mixing_almost:
raise NotImplementedError
nu_index = llh_paramset.from_tag(ParamTag.NUISANCE, index=True)
@@ -552,13 +552,13 @@ def chainer_plot(infile, outfile, outformat, args, llh_paramset, fig_text=None,
mpl.pyplot.figtext(0.5, 0.7, fig_text, fontsize=15)
for of in outformat:
- print 'Saving', outfile+'_elements'+of
+ print('Saving', outfile+'_elements'+of)
g.export(outfile+'_elements.'+of)
def plot_statistic(data, outfile, outformat, args, scale_param, label=None):
"""Make MultiNest factor or LLH value plot."""
- print 'Making Statistic plot'
+ print('Making Statistic plot')
fig_text = gen_figtext(args)
if label is not None: fig_text += '\n' + label
@@ -615,7 +615,7 @@ def plot_statistic(data, outfile, outformat, args, scale_param, label=None):
ax.add_artist(at)
make_dir(outfile)
for of in outformat:
- print 'Saving as {0}'.format(outfile+'.'+of)
+ print('Saving as {0}'.format(outfile+'.'+of))
fig.savefig(outfile+'.'+of, bbox_inches='tight', dpi=150)
@@ -685,7 +685,7 @@ def plot_table_sens(data, outfile, outformat, args, show_lvatmo=True):
ax.spines['bottom'].set_alpha(0.6)
for isrc, src in enumerate(srcs):
- print '== src', src
+ print('== src', src)
argsc.source_ratio = src
if dim in PLANCK_SCALE.iterkeys():
@@ -769,14 +769,14 @@ def plot_table_sens(data, outfile, outformat, args, show_lvatmo=True):
make_dir(outfile)
for of in outformat:
- print 'Saving plot as {0}'.format(outfile+'.'+of)
+ print('Saving plot as {0}'.format(outfile+'.'+of))
fig.savefig(outfile+'.'+of, bbox_inches='tight', dpi=150)
def plot_x(data, outfile, outformat, args, normalise=False):
"""Limit plot as a function of the source flavour ratio for each operator
texture."""
- print 'Making X sensitivity plot'
+ print('Making X sensitivity plot')
dim = args.dimension
if dim < 5: normalise = False
srcs = args.source_ratios
@@ -791,11 +791,11 @@ def plot_x(data, outfile, outformat, args, normalise=False):
data.shape[1], data.shape[0], data.shape[2], data.shape[3]
), np.nan)
- for isrc in xrange(data.shape[0]):
- for itex in xrange(data.shape[1]):
+ for isrc in range(data.shape[0]):
+ for itex in range(data.shape[1]):
r_data[itex][isrc] = data[isrc][itex]
r_data = ma.masked_invalid(r_data)
- print r_data.shape, 'r_data.shape'
+ print(r_data.shape, 'r_data.shape')
fig = plt.figure(figsize=(7, 6))
ax = fig.add_subplot(111)
@@ -866,12 +866,12 @@ def plot_x(data, outfile, outformat, args, normalise=False):
)
for itex, tex in enumerate(textures):
- print '|||| TEX = {0}'.format(tex)
+ print('|||| TEX = {0}'.format(tex))
lims = np.full(len(srcs), np.nan)
for isrc, src in enumerate(srcs):
x = src[0]
- print '|||| X = {0}'.format(x)
+ print('|||| X = {0}'.format(x))
args.source_ratio = src
d = r_data[itex][isrc]
if np.sum(d.mask) > 2: continue
@@ -886,7 +886,7 @@ def plot_x(data, outfile, outformat, args, normalise=False):
size = np.sum(~lims.mask)
if size == 0: continue
- print 'x_arr, lims', zip(x_arr, lims)
+ print('x_arr, lims', zip(x_arr, lims))
if normalise:
zeropoint = 100
else:
@@ -1026,5 +1026,5 @@ def plot_x(data, outfile, outformat, args, normalise=False):
make_dir(outfile)
for of in outformat:
- print 'Saving plot as {0}'.format(outfile + '.' + of)
+ print('Saving plot as {0}'.format(outfile + '.' + of))
fig.savefig(outfile + '.' + of, bbox_inches='tight', dpi=150)
generated by cgit v1.2.3 (git 2.25.1) at 2025-12-17 07:56:45 +0000