def test_plot_results_no_axis(datadir):
data = json.load(open(datadir.join("hypotest_results.json")))
matplotlib.use("agg") # Use non-gui backend
fig, ax = plt.subplots()
ax.set_yscale("log") # Also test log y detection
brazil.plot_results(data["testmus"], data["results"], test_size=0.05)
return fig
def test_plot_results_components(datadir):
data = json.load(open(datadir.join("tail_probs_hypotest_results.json")))
fig = Figure()
ax = fig.subplots()
brazil.plot_results(data["testmus"],
data["results"],
test_size=0.05,
ax=ax,
components=True)
return fig
def test_plot_results_components_data_structure(datadir):
"""
test results should have format of: [CLs_obs, [CLsb, CLb], [CLs_exp band]]
"""
data = json.load(open(datadir.join("hypotest_results.json")))
fig = Figure()
ax = fig.subplots()
with pytest.raises(ValueError):
brazil.plot_results(data["testmus"],
data["results"],
test_size=0.05,
ax=ax,
components=True)
def test_plot_results(datadir):
data = json.load(open(datadir.join("hypotest_results.json")))
fig = Figure()
ax = fig.subplots()
brazil_band_collection = brazil.plot_results(data["testmus"],
data["results"],
test_size=0.05,
ax=ax)
assert brazil_band_collection.axes == ax
return fig
def test_brazil_band_collection(datadir):
data = json.load(open(datadir.join("hypotest_results.json")))
fig = Figure()
ax = fig.subplots()
brazil_band_collection = brazil.plot_results(data["testmus"],
data["results"],
test_size=0.05,
ax=ax)
assert brazil_band_collection.cls_obs is not None
assert brazil_band_collection.cls_exp is not None
assert len(brazil_band_collection.cls_exp) == 5
assert brazil_band_collection.one_sigma_band is not None
assert brazil_band_collection.two_sigma_band is not None
assert brazil_band_collection.test_size is not None
assert brazil_band_collection.clsb is None
assert brazil_band_collection.clb is None
assert brazil_band_collection.axes == ax
data = json.load(open(datadir.join("tail_probs_hypotest_results.json")))
fig = Figure()
ax = fig.subplots()
brazil_band_collection = brazil.plot_results(data["testmus"],
data["results"],
test_size=0.05,
ax=ax,
components=True)
assert brazil_band_collection.cls_obs is not None
assert brazil_band_collection.cls_exp is not None
assert len(brazil_band_collection.cls_exp) == 5
assert brazil_band_collection.one_sigma_band is not None
assert brazil_band_collection.two_sigma_band is not None
assert brazil_band_collection.test_size is not None
assert brazil_band_collection.clsb is not None
assert brazil_band_collection.clb is not None
assert brazil_band_collection.axes == ax
def test_plot_results_components_no_clb(datadir):
data = json.load(open(datadir.join("tail_probs_hypotest_results.json")))
fig = Figure()
ax = fig.subplots()
brazil_band_collection = brazil.plot_results(
data["testmus"],
data["results"],
test_size=0.05,
ax=ax,
components=True,
no_clb=True,
)
assert brazil_band_collection.clsb is not None
assert brazil_band_collection.clb is None
return fig
model = workspace.model()
data = workspace.data(model)
n_points = 4
test_mus = np.linspace(1.0, 1.2, n_points)
fit_results = [
pyhf.infer.hypotest(mu,
data,
model,
return_expected_set=True,
calctype="toybased",
ntoys=ntoys) for mu in test_mus
]
fig, ax = plt.subplots()
brazil.plot_results(test_mus, fit_results, ax=ax)
_buffer = 0.02
ax.set_xlim(1.0 - _buffer, 1.2 + _buffer)
ax.set_ylim(0.0, 0.2)
extensions = ["pdf", "png"]
for ext in extensions:
fig.savefig(f"poi_scan_pyhf.{ext}")
ax.set_ylim(1e-3, 0.2)
ax.semilogy()
for ext in extensions:
fig.savefig(f"poi_scan_logy_pyhf.{ext}")
def test_brazil():
data = json.load(open('tests/contrib/hypotestresults.json'))
fig, ax = plt.subplots(1, 1)
brazil.plot_results(ax, data['testmus'], data['results'], test_size=0.05)
return fig
model = workspace.model()
data = workspace.data(model)
n_points = 4
test_mus = np.linspace(1.0, 1.2, n_points)
fit_results = [
pyhf.infer.hypotest(mu,
data,
model,
return_expected_set=True,
calctype="toybased",
ntoys=ntoys) for mu in test_mus
]
fig, ax = plt.subplots()
brazil.plot_results(ax, test_mus, fit_results)
ax.set_xlabel(r"$\mu$")
ax.set_ylabel(r"$\mathrm{CL}_{s}$")
_buffer = 0.02
ax.set_xlim(1.0 - _buffer, 1.2 + _buffer)
ax.set_ylim(0.0, 0.2)
extensions = ["pdf", "png"]
for ext in extensions:
fig.savefig(f"poi_scan_pyhf.{ext}")
ax.set_ylim(1e-3, 0.2)
ax.semilogy()
for ext in extensions:
fig.savefig(f"poi_scan_logy_pyhf.{ext}")