BENCH: NPV: Actually create decimal arrays in benchmarks

This fixes a bug where we weren't creating decimal arrays in the benchmark.
Instead of creating an array and setting the dtype we manually make a list of
Decimals and create an array from that list.

Author: Kai-Striega

benchmarks/benchmarks.py

@@ -5,6 +5,15 @@
 import numpy_financial as npf
 
 
+def _to_decimal_array_1d(array):
+    return np.array([Decimal(x) for x in array.tolist()])
+
+
+def _to_decimal_array_2d(array):
+    decimals = [Decimal(x) for row in array.tolist() for x in row]
+    return np.array(decimals).reshape(array.shape)
+
+
 class Npv2D:
 
     param_names = ["n_cashflows", "cashflow_lengths", "rates_lengths"]
@@ -25,8 +34,8 @@ def setup(self, n_cashflows, cashflow_lengths, rates_lengths):
         cf_shape = (n_cashflows, cashflow_lengths)
         self.cashflows = rng.standard_normal(cf_shape)
         self.rates = rng.standard_normal(rates_lengths)
-        self.cashflows_decimal = rng.standard_normal(cf_shape).astype(Decimal)
-        self.rates_decimal = rng.standard_normal(rates_lengths).astype(Decimal)
+        self.cashflows_decimal = _to_decimal_array_2d(self.cashflows)
+        self.rates_decimal = _to_decimal_array_1d(self.rates)
 
     def time_broadcast(self, n_cashflows, cashflow_lengths, rates_lengths):
         npf.npv(self.rates, self.cashflows)