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Fix compute error state handling #89

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Fix compute error state handling #89

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22 changes: 12 additions & 10 deletions causing/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,6 @@ def __post_init__(self):
self.graph.add_node(var)
self.trans_graph = networkx.transitive_closure(self.graph, reflexive=True)

@np.errstate(all="raise")
def compute(
self,
xdat: np.array,
Expand All @@ -59,7 +58,7 @@ def compute(
fixed_to_yind: int = None,
fixed_vals: list = None,
# override default parameter values
parameters: dict[str, float] = {},
parameters: dict[str, float] | None = None,
) -> np.array:
"""Compute y values for given x values

Expand All @@ -69,16 +68,19 @@ def compute(
assert xdat.ndim == 2, f"xdat must be m*tau (is {xdat.ndim}-dimensional)"
assert xdat.shape[0] == self.mdim, f"xdat must be m*tau (is {xdat.shape})"
tau = xdat.shape[1]
if parameters is None:
parameters = {}
parameters = self.parameters | parameters

yhat = np.array([[float("nan")] * tau] * len(self.yvars))
for i, eq in enumerate(self._model_lam):
if fixed_yind == i:
yhat[i, :] = fixed_yval
else:
eq_inputs = np.array(
[[*xval, *yval] for xval, yval in zip(xdat.T, yhat.T)]
)
with np.errstate(all="raise"):
yhat = np.array([[float("nan")] * tau] * len(self.yvars))
for i, eq in enumerate(self._model_lam):
if fixed_yind == i:
yhat[i, :] = fixed_yval
else:
eq_inputs = np.array(
[[*xval, *yval] for xval, yval in zip(xdat.T, yhat.T)]
)
if fixed_to_yind == i:
eq_inputs[:, fixed_from_ind] = fixed_vals

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