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Specify float dtype in numpy ones and zeros #161

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Merged
merged 1 commit into from
Apr 11, 2025
Merged

Specify float dtype in numpy ones and zeros #161

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6 changes: 3 additions & 3 deletions stochtree/bart.py
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Original file line number Diff line number Diff line change
Expand Up @@ -734,13 +734,13 @@ def sample(
)
if self.has_basis:
if sigma_leaf is None:
current_leaf_scale = np.zeros((self.num_basis, self.num_basis))
current_leaf_scale = np.zeros((self.num_basis, self.num_basis), dtype=float)
np.fill_diagonal(
current_leaf_scale,
np.squeeze(np.var(resid_train)) / num_trees_mean,
)
elif isinstance(sigma_leaf, float):
current_leaf_scale = np.zeros((self.num_basis, self.num_basis))
current_leaf_scale = np.zeros((self.num_basis, self.num_basis), dtype=float)
np.fill_diagonal(current_leaf_scale, sigma_leaf)
elif isinstance(sigma_leaf, np.ndarray):
if sigma_leaf.ndim != 2:
Expand Down Expand Up @@ -834,7 +834,7 @@ def sample(
alpha_init = np.array([1])
elif num_rfx_components > 1:
alpha_init = np.concatenate(
(np.ones(1), np.zeros(num_rfx_components - 1))
(np.ones(1, dtype=float), np.zeros(num_rfx_components - 1, dtype=float))
)
else:
raise ValueError("There must be at least 1 random effect component")
Expand Down
6 changes: 3 additions & 3 deletions stochtree/bcf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1163,7 +1163,7 @@ def sample(
raise ValueError("sigma_leaf_mu must be a scalar")
if isinstance(sigma_leaf_tau, float):
if Z_train.shape[1] > 1:
current_leaf_scale_tau = np.zeros((Z_train.shape[1], Z_train.shape[1]))
current_leaf_scale_tau = np.zeros((Z_train.shape[1], Z_train.shape[1]), dtype=float)
np.fill_diagonal(current_leaf_scale_tau, sigma_leaf_tau)
else:
current_leaf_scale_tau = np.array([[sigma_leaf_tau]])
Expand Down Expand Up @@ -1230,7 +1230,7 @@ def sample(
alpha_init = np.array([1])
elif num_rfx_components > 1:
alpha_init = np.concatenate(
(np.ones(1), np.zeros(num_rfx_components - 1))
(np.ones(1, dtype=float), np.zeros(num_rfx_components - 1, dtype=float))
)
else:
raise ValueError("There must be at least 1 random effect component")
Expand Down Expand Up @@ -1488,7 +1488,7 @@ def sample(

# Initialize the leaves of each tree in the treatment forest
if self.multivariate_treatment:
init_tau = np.zeros(Z_train.shape[1])
init_tau = np.zeros(Z_train.shape[1], dtype=float)
else:
init_tau = np.array([0.0])
forest_sampler_tau.prepare_for_sampler(
Expand Down
6 changes: 3 additions & 3 deletions stochtree/config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -113,7 +113,7 @@ def __init__(
raise ValueError("`leaf_dimension` must be an integer greater than 0")
if leaf_model_scale is None:
diag_value = 1.0 / num_trees
leaf_model_scale_array = np.zeros((leaf_dimension, leaf_dimension), float)
leaf_model_scale_array = np.zeros((leaf_dimension, leaf_dimension), dtype=float)
np.fill_diagonal(leaf_model_scale_array, diag_value)
else:
if isinstance(leaf_model_scale, np.ndarray):
Expand All @@ -128,7 +128,7 @@ def __init__(
"`leaf_model_scale` must be positive, if provided as scalar"
)
leaf_model_scale_array = np.zeros(
(leaf_dimension, leaf_dimension), float
(leaf_dimension, leaf_dimension), dtype=float
)
np.fill_diagonal(leaf_model_scale_array, leaf_model_scale)
else:
Expand Down Expand Up @@ -278,7 +278,7 @@ def update_leaf_model_scale(
"`leaf_model_scale` must be positive, if provided as scalar"
)
leaf_model_scale_array = np.zeros(
(self.leaf_dimension, self.leaf_dimension), float
(self.leaf_dimension, self.leaf_dimension), dtype=float
)
np.fill_diagonal(leaf_model_scale_array, leaf_model_scale)
else:
Expand Down
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