def setup_two_channel_mct(self):
mct = MultiChannelTemplate()
for channel_name in self.channels:
mct.define_channel(name=channel_name,
bins=self.bins,
range=self.range)
for process in self.processes:
mct.define_process(process)
for iris_channel, name in zip([channel_1, channel_2], self.channels):
setosa = iris_channel.query("class_id==1")["sepal_length"].values
versicolor = iris_channel.query(
"(class_id==2)")["sepal_length"].values
virginica = iris_channel.query(
"(class_id==3)")["sepal_length"].values
hsetosa = Hist1d(self.bins, range=self.range, data=setosa)
tsetosa = Template1d("setosa", "length", hsetosa)
hversico = Hist1d(self.bins, range=self.range, data=versicolor)
tversico = Template1d("versicolor", "length", hversico)
hvirgini = Hist1d(self.bins, range=self.range, data=virginica)
tvirgini = Template1d("virginica", "length", hvirgini)
mct.add_template(name, "setosa", tsetosa)
mct.add_template(name, "versicolor", tversico)
mct.add_template(name, "virginica", tvirgini)
return mct
def test_add_data_as_dict(self):
mct = self.setup_two_channel_mct()
hdata_ch1 = Hist1d(self.bins,
self.range,
data=channel_1["sepal_length"])
hdata_ch2 = Hist1d(self.bins,
self.range,
data=channel_2["sepal_length"])
mct.add_data(**{"Test1": hdata_ch1, "Test2": hdata_ch2})
for channel in mct.channels.values():
self.assertTrue(channel.has_data)
def add_variation(self, data, weights_up, weights_down):
"""Add a new covariance matrix from a given systematic variation
of the underlying histogram to the template."""
hup = Hist1d(bins=self._hist.num_bins,
range=self._range,
data=data,
weights=weights_up)
hdown = Hist1d(bins=self._hist.num_bins,
range=self._range,
data=data,
weights=weights_down)
cov_mat = get_systematic_cov_mat(self._flat_bin_counts,
hup.bin_counts.flatten(),
hdown.bin_counts.flatten())
self._add_cov_mat(cov_mat)
def test_hist_from_array_bins(self):
bins = np.linspace(0, 10, 11)
iris_bc, iris_be = np.histogram(self.iris_sepal_length, bins=bins)
iris_hist = Hist1d(data=self.iris_sepal_length, bins=bins)
np.testing.assert_array_equal(iris_hist.bin_counts, iris_bc)
np.testing.assert_array_equal(iris_hist.bin_edges, iris_be)
def test_range(self):
nbins = 10
range = (0, 10)
iris_hist = Hist1d(data=self.iris_sepal_length,
bins=nbins,
range=range)
self.assertEqual(iris_hist.range, (0, 10))
def test_add_not_comp_data(self):
hiris = Hist1d(2, hist_range=self.range, data=iris_data)
with self.assertRaises(RuntimeError) as e:
self.channel.add_data(hiris)
self.assertEqual(
"Given data histogram is not compatible with the Channel.",
str(e.exception))
def test_empty_template(self):
hist = Hist1d(bins=self.bins, range=self.range)
template = Template1d("test", "test_var", hist)
np.testing.assert_array_equal(template.values, hist.bin_counts)
np.testing.assert_array_equal(template.errors, np.zeros(self.bins))
np.testing.assert_array_equal(template.fractions(np.zeros(self.bins)),
np.zeros(self.bins))
def test_nll_contrib_is_scalar(self):
np.random.seed(5)
yields = np.random.randn(self.num_templates) + 50
nui_params = np.random.randn(self.num_templates * self.bins)
hiris = Hist1d(self.bins, hist_range=self.range, data=iris_data)
self.channel.add_data(hiris)
nll_contrib = self.channel.nll_contribution(yields, nui_params)
self.assertEqual(type(nll_contrib), np.float64)
def test_add_non_comp_template(self):
with self.assertRaises(RuntimeError) as e:
hsetosa = Hist1d(5, (3, 4), data=setosa)
self.channel.add_template('bla',
Template1d('test', 'test', hsetosa))
self.assertEqual(
"Trying to add a non compatible template with the Channel.",
str(e.exception))
def setUp(self):
self.bins = 10
self.range = (3, 8)
self.variable = "sepal_length"
hsetosa = Hist1d(self.bins, range=self.range, data=setosa)
self.tsetosa = Template1d("setosa", "length", hsetosa)
hversico = Hist1d(self.bins, range=self.range, data=versicolor)
self.tversico = Template1d("versicolor", "length", hversico)
hvirgini = Hist1d(self.bins, range=self.range, data=virginica)
self.tvirgini = Template1d("virginica", "length", hvirgini)
self.processes = ("setosa", "versicolor", "virginica")
self.channels = ["Test1", "Test2"]
self.templates = [self.tsetosa, self.tversico, self.tvirgini]
self.num_templates = len(self.templates)
self.efficiencies = 0.8
def test_from_binned_data(self):
bins = np.linspace(0, 10, 11)
iris_bc, iris_be = np.histogram(self.iris_sepal_length, bins=bins)
iris_hist = Hist1d.from_binned_data(bin_counts=iris_bc,
bin_edges=iris_be)
np.testing.assert_array_equal(iris_hist.bin_counts, iris_bc)
np.testing.assert_array_equal(iris_hist.bin_errors, np.sqrt(iris_bc))
np.testing.assert_array_equal(iris_hist.bin_edges, iris_be)
def test_hist_with_range_option(self):
nbins = 10
range = (4, 6)
iris_bc, iris_be = np.histogram(self.iris_sepal_length,
bins=nbins,
range=range)
iris_hist = Hist1d(data=self.iris_sepal_length,
bins=nbins,
range=range)
np.testing.assert_array_equal(iris_hist.bin_counts, iris_bc)
np.testing.assert_array_equal(iris_hist.bin_edges, iris_be)
def test_weighted_data(self):
bins = np.linspace(0, 10, 11)
weights = np.random.normal(1, 0.1, (len(self.iris_sepal_length)))
iris_bc, iris_be = np.histogram(self.iris_sepal_length,
weights=weights,
bins=bins)
iris_hist = Hist1d(data=self.iris_sepal_length,
weights=weights,
bins=bins)
np.testing.assert_array_almost_equal(iris_hist.bin_counts, iris_bc)
np.testing.assert_array_equal(iris_hist.bin_edges, iris_be)
def setUp(self):
self.bins = 10
self.range = (3, 8)
self.variable = "length"
hsetosa = Hist1d(self.bins, hist_range=self.range, data=setosa)
self.tsetosa = Template1d("setosa", "length", hsetosa)
hversico = Hist1d(self.bins, hist_range=self.range, data=versicolor)
self.tversico = Template1d("versicolor", "length", hversico)
hvirgini = Hist1d(self.bins, hist_range=self.range, data=virginica)
self.tvirgini = Template1d("virginica", "length", hvirgini)
self.channel = Channel("test", self.bins, self.range)
self.processes = ["setosa", "versicolor", "virginica"]
self.templates = [self.tsetosa, self.tversico, self.tvirgini]
self.num_templates = len(self.templates)
self.efficiencies = 0.8
for process, template in zip(self.processes, self.templates):
self.channel.add_template(process,
template,
efficiency=self.efficiencies)
def test_hist_from_int_bin(self):
nbins = 10
range = (0, 10)
iris_bc, iris_be = np.histogram(self.iris_sepal_length,
bins=nbins,
range=range)
iris_hist = Hist1d(data=self.iris_sepal_length,
bins=nbins,
range=range)
np.testing.assert_array_equal(iris_hist.bin_counts, iris_bc)
np.testing.assert_array_equal(iris_hist.bin_edges, iris_be)
self.assertFalse(iris_hist.is_empty)
def test_hist_bin_mids_widths(self):
nbins = 10
range = (0, 10)
iris_bc, iris_be = np.histogram(self.iris_sepal_length,
bins=nbins,
range=range)
iris_hist = Hist1d(data=self.iris_sepal_length,
bins=nbins,
range=range)
mids = (iris_be[:-1] + iris_be[1:]) / 2
widths = iris_be[1:] - iris_be[:-1]
np.testing.assert_array_equal(iris_hist.bin_mids, mids)
np.testing.assert_array_equal(iris_hist.bin_widths, widths)
def setUp(self):
self.data = np.array([
5.1, 4.9, 4.7, 4.6, 5., 5.4, 4.6, 5., 4.4, 4.9, 5.4, 4.8, 4.8, 4.3,
5.8, 5.7, 5.4, 5.1, 5.7, 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5., 5., 5.2,
5.2, 4.7, 4.8, 5.4, 5.2, 5.5, 4.9, 5., 5.5, 4.9, 4.4, 5.1, 5., 4.5,
4.4, 5., 5.1, 4.8, 5.1, 4.6, 5.3, 5., 7., 6.4, 6.9, 5.5, 6.5, 5.7,
6.3, 4.9, 6.6, 5.2, 5., 5.9, 6., 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6,
5.9, 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6., 5.7, 5.5, 5.5, 5.8, 6.,
5.4, 6., 6.7, 6.3, 5.6, 5.5, 5.5, 6.1, 5.8, 5., 5.6, 5.7, 5.7, 6.2,
5.1, 5.7, 6.3, 5.8, 7.1, 6.3, 6.5, 7.6, 4.9, 7.3, 6.7, 7.2, 6.5,
6.4, 6.8, 5.7, 5.8, 6.4, 6.5, 7.7, 7.7, 6., 6.9, 5.6, 7.7, 6.3,
6.7, 7.2, 6.2, 6.1, 6.4, 7.2, 7.4, 7.9, 6.4, 6.3, 6.1, 7.7, 6.3,
6.4, 6., 6.9, 6.7, 6.9, 5.8, 6.8, 6.7, 6.7, 6.3, 6.5, 6.2, 5.9
])
self.bins = 10
self.range = (2, 7)
self.hist = Hist1d(bins=self.bins, range=self.range, data=self.data)
self.template = Template1d("test", "test_var", self.hist)
def test_add_data(self):
hiris = Hist1d(self.bins, hist_range=self.range, data=iris_data)
self.channel.add_data(hiris)
def test_toy_data_set(self):
htoy = self.channel.generate_toy_dataset()
hiris = Hist1d(self.bins, hist_range=self.range, data=iris_data)
self.assertEqual(htoy.bin_counts.shape, hiris.bin_counts.shape)
self.assertEqual(htoy.bin_edges.shape, hiris.bin_edges.shape)
self.assertEqual(htoy.bin_errors.shape, hiris.bin_errors.shape)
def test_asimov_data_set(self):
hasimov = self.channel.generate_asimov_dataset()
hiris = Hist1d(self.bins, hist_range=self.range, data=iris_data)
np.testing.assert_array_equal(hasimov.bin_counts, hiris.bin_counts)
np.testing.assert_array_equal(hasimov.bin_edges, hiris.bin_edges)
np.testing.assert_array_equal(hasimov.bin_errors, hiris.bin_errors)
def y_projection(self):
return Hist1d.from_binned_data(
np.sum(self.bin_counts, axis=0),
self.y_edges,
np.sqrt(np.sum(self._bin_errors_sq, axis=0))
)
def test_add_data_wo_templates(self):
empty_channel = Channel("test_empty", self.bins, self.range)
hiris = Hist1d(self.bins, hist_range=self.range, data=iris_data)
empty_channel.add_data(hiris)
def test_empty_template(self):
hist = Hist1d(bins=self.bins, hist_range=self.range)
template = Template1d("test", "test_var", hist)
self.assertEqual(template.yield_param, 0)
