Sun May 6 21:22:46 CDT 2018

1 files changed, 79 insertions, 0 deletions

diff --git a/test/test_all_gf.py b/test/test_all_gf.py
new file mode 100644
index 0000000..04b0980
--- /dev/null
+++ b/test/test_all_gf.py
@@ -0,0 +1,79 @@
+import numpy as np
+import matplotlib as mpl
+mpl.use('Agg')
+import matplotlib.pyplot as plt
+
+import GolemFitPy as gf
+
+FASTMODE = True
+PARAMETERS = [
+    # 'astroFlavorAngle1', 'astroFlavorAngle2',
+    'convNorm',
+    # 'promptNorm', 'muonNorm', 'astroNorm'
+]
+DEFAULTS = [
+    # 4/9., 0., 1., 0., 1., 6.9
+    1.
+]
+RANGES = [
+    # (0, 1), (-1, 1), (0.01, 10), (0., 30), (0.01, 10), (0.01, 30)
+    (0.01, 10)
+]
+BINS = 50
+
+def steering_params():
+    steering_categ = 'p2_0'
+    params = gf.SteeringParams(gf.sampleTag.HESE)
+    if FASTMODE:
+        params.fastmode = True
+    params.quiet = False
+    params.simToLoad= steering_categ.lower()
+    return params
+
+def set_up_as(fitter, params):
+    print 'Injecting the model', params
+    asimov_params = gf.FitParameters(gf.sampleTag.HESE)
+    for x in params.iterkeys():
+        asimov_params.__setattr__(x, float(params[x]))
+    fitter.SetupAsimov(asimov_params)
+    priors = gf.Priors()
+    priors.convNormWidth = 9e9
+    fitter.SetFitPriors(priors)
+
+def setup_fitter(asimov_paramset):
+    datapaths = gf.DataPaths()
+    sparams = steering_params()
+    npp = gf.NewPhysicsParams()
+    fitter = gf.GolemFit(datapaths, sparams, npp)
+    set_up_as(fitter, asimov_paramset)
+    return fitter
+
+def get_llh(fitter, params):
+    fitparams = gf.FitParameters(gf.sampleTag.HESE)
+    for x in params.iterkeys():
+        fitparams.__setattr__(x, float(params[x]))
+    llh = -fitter.EvalLLH(fitparams)
+    return llh
+
+for ip, param in enumerate(PARAMETERS):
+    asimov_paramset = {param: DEFAULTS[ip]}
+    print 'injecting', asimov_paramset
+    fitter = setup_fitter(asimov_paramset)
+    binning = np.linspace(RANGES[ip][0], RANGES[ip][1], BINS)
+    llhs = []
+    for b in binning:
+        test_paramset = {param: b}
+        print 'testing', test_paramset
+        llh = get_llh(fitter, test_paramset)
+        print 'llh', llh
+        llhs.append(llh)
+    plt.plot(binning, llhs)
+    plt.axvline(x=DEFAULTS[ip])
+    plt.xlabel(param)
+    plt.ylabel('LLH')
+    outfile = 'llh_profile_noprior_'
+    if FASTMODE:
+        plt.savefig(outfile + 'fastmode_{0}.png'.format(param))
+    else:
+        plt.savefig(outfile + '{0}.png'.format(param))
+    plt.clf()