def test_edge_cases_visualization_subplot(self):
"""`visualization.Visualization.subplot`: Edge Case Validator.
Tests the behavior of `Visualization.subplot` with edge cases.
Raises:
Exception: If at least one `Exception` raised is not of the expected
kind.
"""
x = _compose(list, _np.random.uniform)(0.0,
100.0,
size=self.data_shape[0])
"""list of float: Random x-values."""
values = {
name: _compose(list, _np.random.uniform)(0.0, 100.0,
size=self.data_shape[0]) \
for name in ["observations", "predictions"]
}
""":obj:`list of float`: Contains all y-values."""
v = Visualization("Title", (1, 1))
"""Visualization: Plotter instance."""
for ModelWrapper in self.wrappers.values():
with self.assertRaises(IndexError):
# Suplot index out of range.
v._subplot(1, x, values)
with self.assertRaises(TypeError):
# Empty `x`-values.
v._subplot([], values, 0)
with self.assertRaises(TypeError):
# Empty `y`-values.
v._subplot(x, {}, 0)
v.close()
def test_invalid_args_visualization_subplot(self):
"""`visualization.Visualization.subplot`: Argument Validator.
Tests the behavior of `Visualization.subplot` with invalid
argument counts and values.
Raises:
Exception: If at least one `Exception` raised is not of the expected
kind.
"""
x = _compose(list, _np.random.uniform)(0.0,
100.0,
size=self.data_shape[0])
"""list of float: Random x-values."""
values = {
name: _compose(list, _np.random.uniform)(0.0, 100.0,
size=self.data_shape[0]) \
for name in ["observations", "predictions"]
}
""":obj:`list of float`: Contains all y-values."""
v = Visualization("Title", (1, 1))
"""Visualization: Plotter instance."""
with self.assertRaises(TypeError):
# No arguments.
v._subplot()
with self.assertRaises(TypeError):
# Only one argument.
v._subplot(x)
with self.assertRaises(TypeError):
# Only two arguments.
v._subplot(x, values)
with self.assertRaises(TypeError):
# Too many arguments.
v._subplot(x, values, 0, "Title", "X-label", "Y-label", True,
"extra")
with self.assertRaises(TypeError):
# Invalid keyword.
v._subplot(x, values, 0, key="value")
with self.assertRaises(TypeError):
# `None` instead of list `x`.
v._subplot(None, values, 0)
with self.assertRaises(TypeError):
# np.matrix instead of list `x`.
v._subplot(_np.matrix(x), values, 0)
with self.assertRaises(TypeError):
# `None` instead of dict of lists `values`.
v._subplot(x, None, 0)
with self.assertRaises(TypeError):
value_list = {k: _np.matrix(val) for k, val in values.iteritems()}
""":obj:`np.matrix`: Lists in `values` mapped to matrices."""
# Dict of np.matrix instead of dict of lists `values`.
v._subplot(x, value_list, 0)
with self.assertRaises(TypeError):
# List instead of dict of lists `values`.
v._subplot(x, x, 0)
with self.assertRaises(TypeError):
# Incompatible x- and y-values.
values_hat = {
name: _compose(list, _np.random.uniform)(0.0, 100.0,
size=self.data_shape[1]) \
for name in ["observations", "predictions"]
}
""":obj:`list of float`: Contains all y-values."""
v._subplot(x, values, 0)
with self.assertRaises(TypeError):
# `None` instead of int `subplot`.
v._subplot(x, values, None)
with self.assertRaises(TypeError):
# Float instead of int `subplot`.
v._subplot(x, values, 5.6)
with self.assertRaises(TypeError):
# Non-string `title`.
v._subplot(x, values, 0, title=["hello", "bye"])
with self.assertRaises(TypeError):
# Non-string `xlabel`.
v._subplot(x, values, 0, xlabel=["hello", "bye"])
with self.assertRaises(TypeError):
# Non-string `ylabel`.
v._subplot(x, values, 0, ylabel=["hello", "bye"])
