missing py files

Author: andrzejnovak

plot_single_gof.py

@@ -0,0 +1,78 @@
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+from matplotlib import transforms
+import numpy as np
+import ROOT as r
+import mplhep as hep
+import argparse 
+
+plt.style.use(hep.style.ROOT)
+
+def get_vals(fname):
+    rfile = r.TFile.Open(fname)
+    rtree = rfile.Get("limit")
+    vals = []
+    for i in range(rtree.GetEntries()):
+        rtree.GetEntry(i)
+        mu = rtree.limit
+        vals.append(mu)
+    return vals
+
+def gofplot(datafile, mcfile, year=2017, savename='fplotX', nbins=130, algo='saturated'):
+    gofs = np.array(get_vals(mcfile))
+    gof_data = get_vals(datafile)[0]
+
+    print("XXXXXXX")
+    print(gof_data)
+    print(np.array([np.around(np.mean(gofs) + x * np.std(gofs), 3) for x in [-3,-2,-1,0,1,2,3]]))
+    print("XXXXXXX")
+
+    from scipy.stats import chi2
+    x_lim = np.max(gofs) * 1.2
+    x_low = np.min(gofs) * 0.9
+    x = np.linspace(x_low, x_lim, 200)
+    bins = np.linspace(0, x_lim, 50)
+    width = bins[1] - bins[0]
+
+    fig, ax = plt.subplots()
+    trans = transforms.blended_transform_factory(ax.transData, ax.transAxes)
+    if algo == 'saturated':
+        ax.plot(x, len(gofs) * width * chi2.pdf(x, np.mean(gofs)), color='red', label='$\chi^2 fit$, ndf = {:.2f}'.format(np.mean(gofs)))
+    h, _, _ = ax.hist(gofs, bins, facecolor='none', edgecolor='black', histtype='stepfilled', lw=2,
+            label="Toys, N = {}".format(len(gofs)))
+    ax.hist(gofs[gofs > gof_data], bins, facecolor='steelblue', edgecolor='gray', histtype='stepfilled', alpha=0.3,
+            label='p-value = {}'.format(round(float(len(gofs[gofs > gof_data]))/len(gofs), 3)));
+    print("P-value", round(float(len(gofs[gofs > gof_data]))/len(gofs), 3))
+    ax.annotate("", xy=(gof_data, 0), xycoords=trans,
+                xytext=(gof_data, 0.25), textcoords=trans,
+                arrowprops=dict(lw='4', color='b', arrowstyle="->,head_length=1.5,head_width=0.5"),
+                )
+    ax.plot([], [], color='blue', lw=2, label="Observed = {:.2f}".format(gof_data))
+
+    ax.legend()
+    hep.cms.label(llabel='Private Work', data=True, year=year, ax=ax)
+    ax.set_xlim(np.mean(gofs)-np.std(gofs)*4, np.mean(gofs)+np.std(gofs)*5)
+    ax.set_ylim(0, max(h) * 1.4)
+    if algo == 'saturated':
+        xlab = r"$-2log(\lambda)$"
+    else:
+        xlab = "KS"
+    ax.set_xlabel(xlab , x=1, ha='right')
+    ax.set_ylabel("Pseudoexperiments", y=1, ha='right')
+    fig.savefig('{}.pdf'.format(savename), dpi=300, transparent=True, bbox_inches='tight')
+    fig.savefig('{}.png'.format(savename), dpi=300, transparent=True, bbox_inches='tight')
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description='Make plots for ftest/gof files.')
+    parser.add_argument('datagof')
+    parser.add_argument('mcgofs')
+    parser.add_argument("--year", choices=['2016', '2017', '2018', ""], default="")
+    parser.add_argument("--algo", choices=['saturated', 'KS'], default="saturated")
+    args = parser.parse_args()
+
+sname = "plots/gof_" + args.year + "_" + args.algo
+gofplot(args.datagof, args.mcgofs, year=args.year, savename=sname, algo=args.algo)
+
+