#import argparse
#parser = argparse.ArgumentParser(description = 'Script to generate correlation v/s duration plots of x triggers\n.
#The duration plotted against is of the x triggers')
#parser.add_argument('channelName', type=str, help='Name of the correlation statistic file which contains data such as correlation, duration, significance etc.')
#args = parser.parse_args()
#fileDir = args.channelName
if (len(sys.argv) < 2):
print 'Provide atleast one file name'
fileDir = sys.argv[1:]
channelName = fileDir[0].split('results/')[1].split('/')[0].split(
'+')[0].split('H1-')[1]
correlation = np.asarray([])
duration = np.asraay([])
for iFile in fileDir:
corrData = np.loadtxt(fileDir[iFile]).reshape(-1, 15)
correlation = np.append(correlation, corrData[:, 1])
duration = np.append(duration, corrData[:, 9])
plt.figure()
plt.plot(duration, correlation, '.')
plt.title('Correlation vs trigger durations of %s channel' % (channelName))
plt.ylabel('correlation statistic $r$')
plt.xlabel('trigger durations')
plt.savefig('./corr_vs_duration_%s.png' % (channelName))
plt.close()
import matplotlib.pyplt as plt
#import argparse
#parser = argparse.ArgumentParser(description = 'Script to generate correlation v/s duration plots of x triggers\n.
#The duration plotted against is of the x triggers')
#parser.add_argument('channelName', type=str, help='Name of the correlation statistic file which contains data such as correlation, duration, significance etc.')
#args = parser.parse_args()
#fileDir = args.channelName
if(len(sys.argv)<2):
print 'Provide atleast one file name'
fileDir = sys.argv[1:]
channelName = fileDir[0].split('results/')[1].split('/')[0].split('+')[0].split('H1-')[1]
correlation = np.asarray([])
duration = np.asraay([])
for iFile in fileDir:
corrData = np.loadtxt(fileDir[iFile]).reshape(-1, 15)
correlation = np.append(correlation, corrData[:, 1])
duration = np.append(duration, corrData[:, 9])
plt.figure()
plt.plot(duration, correlation, '.')
plt.title('Correlation vs trigger durations of %s channel' %(channelName))
plt.ylabel('correlation statistic $r$')
plt.xlabel('trigger durations')
plt.savefig('./corr_vs_duration_%s.png'%(channelName))
plt.close()
def chi2plot(model_dict, outfile_loc=None):
targets = list(np.unique([k.split("_")[0] for k in model_dict.keys()]))
agb_mods = list(np.unique(["_".join(k.split("_")[1:4]) for k in model_dict.keys()]))
cols = ["darkgreen", "navy", "darkred"]
fig, axs = plt.subplots(ncols=2, nrows=2, sharex=True, sharey=False, figsize=(10, 10))
offsets = np.linspace(0, 1, len(targets))
for key, val in model_dict.items():
if "std" in key:
continue
target = key.split("_")[0]
errval = model_dict[key.replace("mean", "std")]
ioff = targets.index(target)
agb_mod = "_".join(key.split("_")[1:4])
col = cols[agb_mods.index(agb_mod)]
sym = "o"
if not agb_mod.endswith("nov13"):
mfc = "white"
else:
mfc = col
if not "nov13" in agb_mod:
sym = "*"
ax_row = 0
ax_col = 0
if not "_agb" in key:
ax_row = 1
if "ir" in key:
ax_col = 1
ax = axs[ax_row][ax_col]
ax.errorbar(
offsets[ioff],
val,
yerr=errval,
marker=sym,
color=col,
ms=12,
mfc=mfc,
ecolor="black",
mew=1.5,
elinewidth=2,
)
ax.set_ylabel("$\chi^2$", fontsize=20)
ax.xaxis.set_ticks(offsets)
ax.set_xticklabels(["$%s$" % t.replace("-deep", "").replace("-", "\!-\!").upper() for t in targets])
[t.set_rotation(30) for t in ax.get_xticklabels()]
# ymaxs[ax_num] = np.max([val, ymaxs[ax_num]])
axs[0][0].set_title(r"$\rm{Optical}$", fontsize=20)
axs[0][1].set_title(r"$\rm{NIR}$", fontsize=20)
[ax.set_ylim(0, 25) for ax in axs[:, 0]]
[ax.set_ylim(0, 10) for ax in axs[:, 1]]
fig.subplots_adjust(hspace=0.1)
xlims = ax.get_xlim()
off = np.diff(offsets)[0]
ax.set_xlim(xlims[0] - off / 2, xlims[1] + off / 2)
sym = ["o", "o", "*"]
mfc = [cols[0], "None", "None"]
[
axs[0, 0].plot(
-99,
99,
sym[j],
mfc=mfc[j],
ms=12,
mew=1.5,
color=cols[j],
label="$%s$" % model_plots.translate_model_name(agb_mods[j].split("_")[-1]),
)
for j in range(len(agb_mods))
]
axs[0, 0].legend(loc=0, numpoints=1)
[ax.annotate(r"$\rm{TP\!-\!AGB\ Only}$", (0.02, 0.02), fontsize=16, xycoords="axes fraction") for ax in axs[0, :]]
if outfile_loc is None:
outfile_loc = os.getcwd()
outfile = os.path.join(outfile_loc, "chi2_plot.png")
plt.tick_params(labelsize=16)
plt.savefig(outfile, dpi=150)
return axs
