1 files changed, 0 insertions, 79 deletions
diff --git a/test/test_all_gf.py b/test/test_all_gf.py
deleted file mode 100644
index 04b0980..0000000
--- a/test/test_all_gf.py
+++ /dev/null
@@ -1,79 +0,0 @@
-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()