Several scipy special functions now upcast integers to float64

Changed in scipy==1.14.0

Author: ricardoV94

environment.yml

@@ -10,7 +10,7 @@ dependencies:
   - python>=3.10
   - compilers
   - numpy>=1.17.0
-  - scipy>=0.14
+  - scipy>=1.14.0
   - filelock
   - etuples
   - logical-unification

pyproject.toml

@@ -47,7 +47,7 @@ keywords = [
 ]
 dependencies = [
     "setuptools>=59.0.0",
-    "scipy>=0.14",
+    "scipy>=1.14.0",
     "numpy>=1.17.0,<2",
     "filelock",
     "etuples",

pytensor/scalar/basic.py

@@ -1027,6 +1027,17 @@ def upgrade_to_float_no_complex(*types):
     return upgrade_to_float(*types)
 
 
+def upgrade_to_float64_no_complex(*types):
+    """
+    Don't accept complex, otherwise call upgrade_to_float64().
+
+    """
+    for type in types:
+        if type in complex_types:
+            raise TypeError("complex argument not supported")
+    return upgrade_to_float64(*types)
+
+
 def same_out_nocomplex(type):
     if type in complex_types:
         raise TypeError("complex argument not supported")

pytensor/scalar/math.py

@@ -41,6 +41,7 @@
     upcast,
     upgrade_to_float,
     upgrade_to_float64,
+    upgrade_to_float64_no_complex,
     upgrade_to_float_no_complex,
 )
 from pytensor.scalar.basic import abs as scalar_abs
@@ -323,7 +324,7 @@ def c_code(self, node, name, inputs, outputs, sub):
         raise NotImplementedError("only floating point is implemented")
 
 
-gamma = Gamma(upgrade_to_float, name="gamma")
+gamma = Gamma(upgrade_to_float64, name="gamma")
 
 
 class GammaLn(UnaryScalarOp):
@@ -460,7 +461,7 @@ def c_code(self, node, name, inp, out, sub):
         raise NotImplementedError("only floating point is implemented")
 
 
-psi = Psi(upgrade_to_float, name="psi")
+psi = Psi(upgrade_to_float64, name="psi")
 
 
 class TriGamma(UnaryScalarOp):
@@ -549,7 +550,7 @@ def c_code(self, node, name, inp, out, sub):
 
 
 # Scipy polygamma does not support complex inputs: https://github.com/scipy/scipy/issues/7410
-tri_gamma = TriGamma(upgrade_to_float_no_complex, name="tri_gamma")
+tri_gamma = TriGamma(upgrade_to_float64_no_complex, name="tri_gamma")
 
 
 class PolyGamma(BinaryScalarOp):
@@ -880,7 +881,7 @@ def inner_loop_a(sum_a, log_gamma_k_plus_n_plus_1, k_plus_n, log_x):
 
         def inner_loop_b(sum_b, log_gamma_k_plus_n_plus_1, n, k_plus_n, log_x):
             term = exp(k_plus_n * log_x - log_gamma_k_plus_n_plus_1) * psi(k_plus_n + 1)
-            sum_b += term
+            sum_b += term.astype(dtype)
 
             log_gamma_k_plus_n_plus_1 += log1p(k_plus_n)
             n += 1
@@ -1051,7 +1052,7 @@ def __hash__(self):
         return hash(type(self))
 
 
-gammau = GammaU(upgrade_to_float, name="gammau")
+gammau = GammaU(upgrade_to_float64, name="gammau")
 
 
 class GammaL(BinaryScalarOp):
@@ -1089,7 +1090,7 @@ def __hash__(self):
         return hash(type(self))
 
 
-gammal = GammaL(upgrade_to_float, name="gammal")
+gammal = GammaL(upgrade_to_float64, name="gammal")
 
 
 class Jv(BinaryScalarOp):
@@ -1335,7 +1336,7 @@ def c_code_cache_version(self):
             return v
 
 
-sigmoid = Sigmoid(upgrade_to_float, name="sigmoid")
+sigmoid = Sigmoid(upgrade_to_float64, name="sigmoid")
 
 
 class Softplus(UnaryScalarOp):
@@ -1631,6 +1632,7 @@ def _betainc_db_n_dq(f, p, q, n):
             dK = log(x) - reciprocal(p) + psi(p + q) - psi(p)
         else:
             dK = log1p(-x) + psi(p + q) - psi(q)
+        dK = dK.astype(dtype)
 
         derivative = np.array(0, dtype=dtype)
         n = np.array(1, dtype="int16")  # Enough for 200 max iters