def test_remove_chain_by_name(self):
tolerance = 5e-2
consumer = ChainConsumer()
consumer.add_chain(self.data * 2, name="a")
consumer.add_chain(self.data, name="b")
consumer.remove_chain(chain="a")
consumer.configure()
summary = consumer.analysis.get_summary()
assert isinstance(summary, dict)
actual = np.array(list(summary.values())[0])
expected = np.array([3.5, 5.0, 6.5])
diff = np.abs(expected - actual)
assert np.all(diff < tolerance)
def test_remove_chain_by_name(self):
tolerance = 5e-2
consumer = ChainConsumer()
consumer.add_chain(self.data * 2, name="a")
consumer.add_chain(self.data, name="b")
consumer.remove_chain(chain="a")
consumer.configure()
summary = consumer.analysis.get_summary()
assert isinstance(summary, dict)
actual = np.array(list(summary.values())[0])
expected = np.array([3.5, 5.0, 6.5])
diff = np.abs(expected - actual)
assert np.all(diff < tolerance)
def test_remove_multiple_chains3(self):
tolerance = 5e-2
consumer = ChainConsumer()
consumer.add_chain(self.data * 2, parameters=["p1"], name="a")
consumer.add_chain(self.data, parameters=["p2"], name="b")
consumer.add_chain(self.data * 3, parameters=["p3"], name="c")
consumer.remove_chain(chain=["a", 2])
consumer.configure()
summary = consumer.analysis.get_summary()
assert isinstance(summary, dict)
assert "p2" in summary
assert "p1" not in summary
assert "p3" not in summary
actual = np.array(list(summary.values())[0])
expected = np.array([3.5, 5.0, 6.5])
diff = np.abs(expected - actual)
assert np.all(diff < tolerance)
def test_remove_multiple_chains3(self):
tolerance = 5e-2
consumer = ChainConsumer()
consumer.add_chain(self.data * 2, parameters=["p1"], name="a")
consumer.add_chain(self.data, parameters=["p2"], name="b")
consumer.add_chain(self.data * 3, parameters=["p3"], name="c")
consumer.remove_chain(chain=["a", 2])
consumer.configure()
summary = consumer.analysis.get_summary()
assert isinstance(summary, dict)
assert "p2" in summary
assert "p1" not in summary
assert "p3" not in summary
actual = np.array(list(summary.values())[0])
expected = np.array([3.5, 5.0, 6.5])
diff = np.abs(expected - actual)
assert np.all(diff < tolerance)
