def test_check_array_min_samples_and_features_messages():
# empty list is considered 2D by default:
msg = "0 feature(s) (shape=(1, 0)) while a minimum of 1 is required."
assert_raise_message(ValueError, msg, check_array, [[]])
# If considered a 1D collection when ensure_2d=False, then the minimum
# number of samples will break:
msg = "0 sample(s) (shape=(0,)) while a minimum of 1 is required."
assert_raise_message(ValueError, msg, check_array, [], ensure_2d=False)
# Invalid edge case when checking the default minimum sample of a scalar
msg = "Singleton array array(42) cannot be considered a valid collection."
assert_raise_message(TypeError, msg, check_array, 42, ensure_2d=False)
# But this works if the input data is forced to look like a 2 array with
# one sample and one feature:
X_checked = assert_warns(DeprecationWarning, check_array, [42],
ensure_2d=True)
assert_array_equal(np.array([[42]]), X_checked)
def test_get_affinity_matrix(almost_equal_decimals=5):
""" test different ways to call get_affinity_matrix """
# 1. (No existing affinity, no passed radius, no self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
dist_mat = distance_matrix(X, radius = 1/X.shape[1])
A2 = affinity_matrix(dist_mat, neighbors_radius = 1/X.shape[1])
Geometry = geom.Geometry(X, input_type = 'data')
## Return default Affinity
A = Geometry.get_affinity_matrix()
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 2. (No existing affinity, no passed radius, no self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
dist_mat = distance_matrix(X, radius = 1/X.shape[1])
A2 = affinity_matrix(dist_mat, neighbors_radius = 1/X.shape[1])
Geometry = geom.Geometry(dist_mat, input_type = 'distance')
## Return default
A = Geometry.get_affinity_matrix()
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 3. (No existing affinity, no passed radius, existing self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = radius,
affinity_radius = radius)
## Return with existing radius
A = Geometry.get_affinity_matrix()
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 4. (No existing affinity, no passed radius, existing self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(dist_mat, input_type = 'distance', neighborhood_radius = radius,
affinity_radius = radius)
## Return with existing radius
A = Geometry.get_affinity_matrix()
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 5. (No existing affinity, passed radius, no existing self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = 2)
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = radius)
## Return passed radius affinity, set radius to passed
A = Geometry.get_affinity_matrix(affinity_radius=2)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 6. (No existing affinity, passed radius, no existing self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = 2)
Geometry = geom.Geometry(dist_mat, input_type = 'distance', neighborhood_radius = radius)
## Return passed radius affinity, set radius to passed
A = Geometry.get_affinity_matrix(affinity_radius=2)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 7. (No existing affinity, passed radius equal to existing self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = radius,
affinity_radius = radius)
## Return self.radius affinity
A = Geometry.get_affinity_matrix(affinity_radius=radius)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 8. (No existing affinity, passed radius equal to existing self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(dist_mat, input_type = 'distance', neighborhood_radius = radius,
affinity_radius = radius)
## Return self.radius affinity
A = Geometry.get_affinity_matrix(affinity_radius=radius)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 9. (No existing affinity, passed radius not equal to existing self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
radius = 1
radius2 = 2
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius2)
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = radius,
affinity_radius = radius)
## Return passed radius affinity, set radius to passed
A = Geometry.get_affinity_matrix(affinity_radius=radius2)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
assert(Geometry.affinity_radius == radius2)
# 10. (No existing affinity, passed radius not equal to existing self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
radius = 1
radius2 = 2
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius2)
Geometry = geom.Geometry(dist_mat, input_type = 'distance', neighborhood_radius = radius,
affinity_radius = radius)
## Return passed radius affinity, set radius to passed
A = Geometry.get_affinity_matrix(affinity_radius=radius2)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
assert(Geometry.affinity_radius == radius2)
# 11. (Existing affinity, no passed radius, no self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(X, input_type = 'data')
Geometry.assign_affinity_matrix(A2)
## Return existing affinity
A = Geometry.get_affinity_matrix()
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 12. (Existing affinity, no passed radius, no self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(dist_mat, input_type = 'distance')
Geometry.assign_affinity_matrix(A2)
## Return existing affinity
A = Geometry.get_affinity_matrix()
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 13. (Existing affinity, no passed radius, no self.radius, input_type = affinity)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(A2, input_type = 'affinity')
### Return existing affinity
A = Geometry.get_affinity_matrix()
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 14. (Existing affinity, no passed radius, existing self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = radius,
affinity_radius = radius)
Geometry.assign_affinity_matrix(A2)
### Return existing affinity
A = Geometry.get_affinity_matrix()
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 15. (Existing affinity, no passed radius, existing self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(dist_mat, input_type = 'distance', neighborhood_radius = radius,
affinity_radius = radius)
Geometry.assign_affinity_matrix(A2)
### Return existing affinity
A = Geometry.get_affinity_matrix()
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 16. (Existing affinity, no passed radius, existing self.radius, input_type = affinity)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(A2, input_type = 'affinity', neighborhood_radius = radius,
affinity_radius = radius)
## Return existing affinity
A = Geometry.get_affinity_matrix()
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 17. (Existing affinity, passed radius, no self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = 2)
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = radius)
Geometry.assign_affinity_matrix(A2)
## Compute with passed radius, set self.radius to passed radius
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
A = Geometry.get_affinity_matrix(affinity_radius=radius)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 18. (Existing affinity, passed radius, no self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = 2)
Geometry = geom.Geometry(dist_mat, input_type = 'distance', neighborhood_radius = radius)
Geometry.assign_affinity_matrix(A2)
## Compute with passed radius, set self.radius to passed radius
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
A = Geometry.get_affinity_matrix(affinity_radius=radius)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 19. (Existing affinity, passed radius, no self.radius, input_type = affinity)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = 2)
Geometry = geom.Geometry(A2, input_type = 'affinity', neighborhood_radius = radius)
## Raise error, unknown existing radius, passed radius but input type affinity
msg = ("Input_method was passed as affinity."
"Requested radius was not equal to self.affinity_radius."
"Affinity Matrix cannot be recalculated.")
assert_raise_message(ValueError, msg, Geometry.get_affinity_matrix,
affinity_radius=radius)
# 20. (Existing affinity, passed radius equal to self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = radius,
affinity_radius = radius)
Geometry.assign_affinity_matrix(A2)
## Return existing affinity
A = Geometry.get_affinity_matrix(affinity_radius=radius)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 21. (Existing affinity, passed radius equal to self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(dist_mat, input_type = 'distance', neighborhood_radius = radius,
affinity_radius = radius)
Geometry.assign_affinity_matrix(A2)
## Return existing affinity
A = Geometry.get_affinity_matrix(affinity_radius=radius)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 22. (Existing affinity, passed radius equal to self.radius, input_type = affinity)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(A2, input_type = 'affinity', neighborhood_radius = radius,
affinity_radius = radius)
## Return existing affinity
A = Geometry.get_affinity_matrix(affinity_radius=radius)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
# 23. (Existing affinity, passed radius not equal to self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = radius,
affinity_radius = radius)
Geometry.assign_affinity_matrix(A2)
## Re-calculate with passed radius, set self.radius to passed radius
A2 = affinity_matrix(dist_mat, neighbors_radius = 2)
A = Geometry.get_affinity_matrix(affinity_radius=2)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
assert(Geometry.affinity_radius == 2)
# 24. (Existing affinity, passed radius not equal to self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = radius)
Geometry = geom.Geometry(dist_mat, input_type = 'distance', neighborhood_radius = radius,
affinity_radius = radius)
Geometry.assign_affinity_matrix(A2)
## Re-calculate with passed radius, set self.radius to passed radius
A2 = affinity_matrix(dist_mat, neighbors_radius=2)
A = Geometry.get_affinity_matrix(affinity_radius=2)
assert_array_almost_equal(A.todense(), A2.todense(), almost_equal_decimals)
assert(Geometry.affinity_radius == 2)
# 25. (Existing affinity, passed radius not equal to self.radius, input_type = affinity)
X = np.random.uniform(size = (10,10))
radius = 1
dist_mat = distance_matrix(X, radius = radius)
A2 = affinity_matrix(dist_mat, neighbors_radius = 2)
Geometry = geom.Geometry(A2, input_type = 'affinity', neighborhood_radius = radius,
affinity_radius = 2)
## Raise error, passed affinity re-calculateion not supported.
msg = ("Input_method was passed as affinity."
"Requested radius was not equal to self.affinity_radius."
"Affinity Matrix cannot be recalculated.")
assert_raise_message(ValueError, msg, Geometry.get_affinity_matrix,
affinity_radius=radius)
def test_get_distance_matrix(almost_equal_decimals = 5):
""" test different ways to call get_distance_matrix """
# 1. (Input type = Affinity)
X = np.random.uniform(size = (10,10))
Geometry = geom.Geometry(X, input_type = 'affinity')
## Raise error Affinity matrix passed
msg = ( "input_method was passed as affinity. " "Distance matrix cannot be computed.")
assert_raise_message(ValueError, msg, Geometry.get_distance_matrix)
# 2. (No existing distance, no passed radius, no self.radius, input_type = Data)
X = np.random.uniform(size = (10,10))
Geometry = geom.Geometry(X, input_type = 'data')
## Calculate with default radius
distance_mat = Geometry.get_distance_matrix()
distance_mat2 = distance_matrix(X, radius = 1/X.shape[1])
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
# 3. (No existing distance, no passed radius, existing self.radius, input_type = Data)
X = np.random.uniform(size = (10,10))
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = 1)
## Calculate with existing radius
distance_mat = Geometry.get_distance_matrix()
distance_mat2 = distance_matrix(X, radius = 1)
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
# 4. (No existing distance, passed radius, no existing self.radius, input_type = Data)
X = np.random.uniform(size = (10,10))
Geometry = geom.Geometry(X, input_type = 'data')
## Set current radius to passed, calcualte with passed radius
distance_mat = Geometry.get_distance_matrix(neighborhood_radius = 1)
distance_mat2 = distance_matrix(X, radius = 1)
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
assert(Geometry.neighborhood_radius == 1)
# 5. (No existing distance, passed radius equal to existing self.radius, input_type = Data)
X = np.random.uniform(size = (10,10))
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = 1)
## Calculate with passed radius
distance_mat = Geometry.get_distance_matrix(neighborhood_radius = 1)
distance_mat2 = distance_matrix(X, radius = 1)
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
# 6. (No existing distance, passed radius not equal to existing self.radius, input_type = Data)
X = np.random.uniform(size = (10,10))
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = 1)
## Calculate with passed radius, set new self.radius
distance_mat = Geometry.get_distance_matrix(neighborhood_radius = 2)
distance_mat2 = distance_matrix(X, radius = 2)
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
assert(Geometry.neighborhood_radius == 2)
# 7. (Existing distance, no passed radius, no self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
Geometry = geom.Geometry(X, input_type = 'data')
distance_mat2 = distance_matrix(X, radius = 1)
Geometry.assign_distance_matrix(distance_mat2)
## Return existing distance matrix
distance_mat = Geometry.get_distance_matrix()
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
# 8. (Existing distance, no passed radius, no self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
distance_mat2 = distance_matrix(X, radius = 1)
Geometry = geom.Geometry(distance_mat2, input_type = 'distance')
## Return existing distance matrix
distance_mat = Geometry.get_distance_matrix()
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
# 9. (Existing distance, no passed radius, existing self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius = 1)
distance_mat2 = distance_matrix(X, radius = 1)
Geometry.assign_distance_matrix(distance_mat2)
## Return existing distance Matrix
distance_mat = Geometry.get_distance_matrix()
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
# 10. (Existing distance, no passed radius, existing self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
distance_mat2 = distance_matrix(X, radius = 1)
Geometry = geom.Geometry(distance_mat2, input_type = 'distance', neighborhood_radius = 1)
## Return existing distance matrix
distance_mat = Geometry.get_distance_matrix()
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
# 11. (Existing distance, passed radius, no existing self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
distance_mat2 = distance_matrix(X, radius = 1)
Geometry = geom.Geometry(X, input_type = 'data')
Geometry.assign_distance_matrix(distance_mat2)
## Re-calculate with passed radius, set self.radius to passed radius
distance_mat = Geometry.get_distance_matrix(neighborhood_radius=3)
distance_mat2 = distance_matrix(X, radius = 3)
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
assert(Geometry.neighborhood_radius == 3)
# 12. (Existing distance, passed radius, no existing self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
distance_mat2 = distance_matrix(X, radius = 1)
Geometry = geom.Geometry(distance_mat2, input_type = 'distance')
## Raise error, can't re-calculate
msg = ("input_method was passed as distance."
"requested radius not equal to self.neighborhood_radius."
"distance matrix cannot be re-calculated.")
assert_raise_message(ValueError, msg, Geometry.get_distance_matrix, neighborhood_radius=3)
# 13. (Existing distance, passed radius equal to existing self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
distance_mat2 = distance_matrix(X, radius = 1)
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius=1)
Geometry.assign_distance_matrix(distance_mat2)
## Return existing distance matrix
distance_mat = Geometry.get_distance_matrix(neighborhood_radius=1)
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
# 14. (Existing distance, passed radius equal to existing self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
distance_mat2 = distance_matrix(X, radius = 1)
Geometry = geom.Geometry(distance_mat2, input_type = 'distance', neighborhood_radius = 1)
## Return existing distance matrix
distance_mat = Geometry.get_distance_matrix(neighborhood_radius=1)
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
# 15. (Existing distance, passed radius not equal to existing self.radius, input_type = data)
X = np.random.uniform(size = (10,10))
distance_mat2 = distance_matrix(X, radius = 1)
Geometry = geom.Geometry(X, input_type = 'data', neighborhood_radius=1)
Geometry.assign_distance_matrix(distance_mat2)
## Recompute with passed radius, set self.radius to passed radius
distance_mat2 = distance_matrix(X, radius = 3)
distance_mat = Geometry.get_distance_matrix(neighborhood_radius=3)
assert_array_almost_equal(distance_mat.todense(), distance_mat2.todense(), almost_equal_decimals)
assert(Geometry.neighborhood_radius == 3)
# 16. (Existing distance, passed radius not equal to existing self.radius, input_type = distance)
X = np.random.uniform(size = (10,10))
distance_mat2 = distance_matrix(X, radius = 1)
Geometry = geom.Geometry(distance_mat2, input_type = 'distance', neighborhood_radius = 1)
## Raise error, can't recalculate
msg = ("input_method was passed as distance."
"requested radius not equal to self.neighborhood_radius."
"distance matrix cannot be re-calculated.")
assert_raise_message(ValueError, msg, Geometry.get_distance_matrix, neighborhood_radius=3)
