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Commit 42f2e5e6 authored by Patrick Godwin's avatar Patrick Godwin
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fix issues, syntax in various plotting scripts and submodules

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1 merge request!26Refactor plotting routines + remove unused functionality
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gstlal-inspiral/bin/gstlal_inspiral_plot_sensitivity
+ 4
− 7
View file @ 42f2e5e6
......@@ -25,7 +25,6 @@ import os
import sqlite3
import sys
from matplotlib import pyplot
import numpy
from ligo.lw import ligolw
......@@ -42,15 +41,13 @@ from lal.utils import CacheEntry
from gstlal import imr_utils
from gstlal import dagparts
from gstlal.plots import sensitivity as plotsens
from matplotlib import pyplot
__author__ = "Stephen Privitera <sprivite@caltech.edu>, Chad Hanna <channa@perimeterinstitute.ca>, Kipp Cannon <kipp.cannon@ligo.org>"
__version__ = "git id %s" % "" # FIXME
__date__ = "" # FIXME
pyplot.rc('font',**{'family':'serif','serif':['Computer Modern Roman']})
matplotlib.rcParams.update({"text.usetex": True})
def source_type_distance_chirp_mass_bins_from_sims(sims, distbins = 200):
"""
......@@ -107,7 +104,7 @@ class upper_limit(object):
# read the zero lag databases first
for f in self.opts.zero_lag_database:
if opts.verbose:
print >> sys.stdout, "\nGathering search data from zero-lag database: %s...." % (f,)
print(f"Gathering search data from zero-lag database: {f}....", file=sys.stderr)
working_filename = dbtables.get_connection_filename(f, tmp_path=opts.tmp_space, verbose = opts.verbose)
connection = sqlite3.connect(str(working_filename))
......@@ -130,7 +127,7 @@ class upper_limit(object):
self.total_injections = {}
for f in self.opts.injection_database:
if opts.verbose:
print("Reading results of injection analysis from %s ..."%f)
print(f"Reading results of injection analysis from {f} ...", file=sys.stderr)
working_filename = dbtables.get_connection_filename(f, tmp_path=opts.tmp_space, verbose = opts.verbose)
connection = sqlite3.connect(str(working_filename))
for inst in self.instrument_combos:
......@@ -593,7 +590,7 @@ for bin_type in opts.bin_types:
fig_far = plotsens.plot_sensitivity_vs_far(far_vols, fars, UL.livetime, instr, bins, bin_type)
fig_far_range = plotsens.plot_range_vs_far(far_vols, fars, UL.livetime, instr, bins, bin_type)
fig_snr = plotsens.plot_sensitivity_vs_far(snr_vols, snrs, UL.livetime, instr, bins, bin_type)
fig_eff = plotsens.plot_fiducial_efficiency(eff_fids, opts.fiducial_far, inste, bins, bin_type)
fig_eff = plotsens.plot_fiducial_efficiency(eff_fids, opts.fiducial_far, instr, bins, bin_type)
# save and close figures
ifostr = "%s_%s" % (UL.searched_instruments, "".join(sorted(instr)))
......
gstlal-inspiral/bin/gstlal_inspiral_plotsummary
+ 8
− 8
View file @ 42f2e5e6
......@@ -794,7 +794,7 @@ FROM
for participating_instruments, sims in sorted(self.found_in.items(), key = (lambda x: lsctables.instrumentsproperty.set(x[0]))):
if cnt == 0:
ifo_count_summary["".join(sorted(participating_instruments))] = len(sims)
found[participating_instruments] = (
found_data[participating_instruments] = (
[x_func(sim) for sim in sims],
[y_func(sim, participating_instruments) for sim in sims]
)
......@@ -960,7 +960,7 @@ class ParameterAccuracyPlots(object):
r"Inj. $M_{\mathrm{total}}$ ($\mathrm{M}_{\odot}$)",
r"(Rec. $M_{\mathrm{total}}$ - Inj. $M_{\mathrm{total}}$) / Inj. $M_{\mathrm{total}}$",
"FAR (Hz)",
r"Fractional $M_{\mathrm{total}}$ Accuracy in %s (%s Injections)" % waveform.replace("_", "\_"))
r"Fractional $M_{\mathrm{total}}$ Accuracy in %s (%s Injections)" % (instrument, waveform.replace("_", "\_"))
)
yield fig, "mtotal_acc_frac_scatter_%s_%s" % (waveform, instrument), False
......@@ -1011,7 +1011,7 @@ class ParameterAccuracyPlots(object):
[sim.time_at_instrument(sngl.ifo, {sngl.ifo: 0.0}) for sim, sngl, far in pairs],
[(sngl.end - sim.time_at_instrument(sngl.ifo, {sngl.ifo: 0.0}))*1000. for sim, sngl, far in pairs],
r"Injection End Time (GPS s)",
r"Rec. End Time - Injection End Time (ms)"
r"Rec. End Time - Injection End Time (ms)",
r"End Time Accuracy in %s (%s Injections)" % (instrument, waveform.replace("_", "\_"))
)
yield fig, "t_acc_scatter_%s_%s" % (waveform, instrument), False
......@@ -1044,7 +1044,7 @@ class ParameterAccuracyPlots(object):
fig = plotsumm.plot_param_accuracy_histogram(
numpy.array([(sngl.snr - self.get_inj_snr(sim, instrument)) for sim, sngl, far in pairs]),
r"(Rec. SNR - Inj SNR)", "Number",
r"(Rec. SNR - Inj SNR)",
r"SNR Diff in %s (%s Injections)" % (instrument, waveform.replace("_", "\_"))
)
yield fig, "snr_diff_hist_%s_%s" % (waveform, instrument), False
......@@ -1188,7 +1188,7 @@ WHERE
bg_chieffs = numpy.array(self.background[instrument].chieff)[sortable]
# mass dependence of chisq
fig = plot_mass_chi2_snr2_background(inj_mcs, inj_chisq, inj_snrs, bg_mcs, bg_chisq, bg_snrs, instrument)
fig = plotsumm.plot_mass_chi2_snr2_background(inj_mcs, inj_chisq, inj_snrs, bg_mcs, bg_chisq, bg_snrs, instrument)
yield fig, "chi2_vs_mc_vs_rho_%s" % instrument, False
# background parameter distributions
......@@ -1422,10 +1422,10 @@ WHERE
self.zerolag_snr.append(snr)
def finish(self):
fig = plot_candidate_lnL_vs_snr(self.snr_min, self.background_snr, self.background_ln_likelihood_ratio)
fig = plotsumm.plot_candidate_lnL_vs_snr(self.snr_min, self.background_snr, self.background_ln_likelihood_ratio)
yield fig, "lr_vs_snr", False
fig = plot_candidate_lnL_vs_snr(
fig = plotsumm.plot_candidate_lnL_vs_snr(
self.snr_min, self.background_snr, self.background_ln_likelihood_ratio,
self.zerolag_snr, self.zerolag_ln_likelihood_ratio
)
......@@ -1441,7 +1441,7 @@ WHERE
if ln_likelihood_ratio:
# ln(L) in ascending order
zerolag_stats = numpy.array(sorted(ln_likelihood_ratio, reverse = True))
fig = plotsumm.create_rate_vs_lnL_plot(zerolag_stats, self.fapfar, is_open_box)
fig = plotsumm.plot_rate_vs_lnL(zerolag_stats, self.fapfar, is_open_box)
yield fig, "count_vs_lr", is_open_box
if self.background_ln_likelihood_ratio:
......
gstlal-inspiral/python/plots/sensitivity.py
+ 6
− 6
View file @ 42f2e5e6
......@@ -88,11 +88,11 @@ def fiducial_efficiency_to_range_label(eff_fid, bins, zero_bin, bin_type):
iterutils.MultiIter(*bins.upper())
):
ds = (zero_bin.lower() + zero_bin.upper()) / 2
center = numpy.array([eff_fid[(d,) + bin_mid] for d in ds])
lo = numpy.array([eff_fid_lo[(d,) + bin_mid] for d in ds])
hi = numpy.array([eff_fid_hi[(d,) + bin_mid] for d in ds])
center = numpy.array([eff_fid[1][(d,) + bin_mid] for d in ds])
lo = numpy.array([eff_fid[0][(d,) + bin_mid] for d in ds])
hi = numpy.array([eff_fid[2][(d,) + bin_mid] for d in ds])
yield lo, center, hi, bin_type_to_label(bin_type, bin_lo, bin_mid, bin_hi)
yield lo, center, hi, ds, bin_type_to_label(bin_type, bin_lo, bin_mid, bin_hi)
def vt_to_range(volume, livetime):
return (volume / (4 * math.pi * livetime / 3))**(1./3)
......@@ -212,12 +212,12 @@ def plot_fiducial_efficiency(eff_fids, fiducial_far, ifos, bins, bin_type):
# plot the volume/range versus far/snr for each bin
mbins = rate.NDBins(bins[1:])
labels = []
for lo, center, hi, label in fiducial_efficiency_to_range_label(eff_fids, mbins, bins[0], bin_type):
for lo, eff, hi, ds, label in fiducial_efficiency_to_range_label(eff_fids, mbins, bins[0], bin_type):
labels.append(label)
# NOTE create regular plots, and define log x,y scales below
# since otherwise, fill_between allocates too many blocks and crashes
line, = ax_eff.plot(ds, eff, label=label, linewidth=2 )
line, = ax_eff.plot(ds, eff, label=label, linewidth=2)
ax_eff.fill_between(ds, lo, hi, alpha=0.5, color=line.get_color())
ax_eff.set_xlabel("Distance (Mpc)")
......
gstlal-inspiral/python/plots/summary.py
+ 1
− 1
View file @ 42f2e5e6
......@@ -172,7 +172,7 @@ def plot_snr_chi2_background(ifo, min_snr, injections, background, zerolag=None)
axes.loglog(injections[ifo].snr, injections[ifo].chi2, 'r.', label = "Inj")
axes.loglog(background[ifo].snr, background[ifo].chi2, "kx", label = "Background")
if zerolag:
axes.loglog(zerolag[ifo].snr, self.zerolag[ifo].chi2, "bx", label = "Zero-lag")
axes.loglog(zerolag[ifo].snr, zerolag[ifo].chi2, "bx", label = "Zero-lag")
axes.set_title(fr"$\chi^{2}$ vs.\ $\rho$ in {ifo}")
else:
axes.set_title(fr"$\chi^{2}$ vs.\ $\rho$ in {ifo} (Closed box)")
......
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