Merge pull request #101 from Kai-Striega/rev/remove-numba

REV: Remove numba

Author: Kai-Striega

.github/workflows/pythonpackage.yml

@@ -8,7 +8,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ["3.9", "3.10", "3.11"]
+        python-version: ["3.9", "3.10", "3.11", "3.12"]
     steps:
     - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}

benchmarks/benchmarks.py

@@ -37,17 +37,11 @@ def setup(self, n_cashflows, cashflow_lengths, rates_lengths):
         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)
-
     def time_for_loop(self, n_cashflows, cashflow_lengths, rates_lengths):
         for rate in self.rates:
             for cashflow in self.cashflows:
                 npf.npv(rate, cashflow)
 
-    def time_broadcast_decimal(self, n_cashflows, cashflow_lengths, rates_lengths):
-        npf.npv(self.rates_decimal, self.cashflows_decimal)
-
     def time_for_loop_decimal(self, n_cashflows, cashflow_lengths, rates_lengths):
         for rate in self.rates_decimal:
             for cashflow in self.cashflows_decimal:

numpy_financial/_financial.py

@@ -13,7 +13,6 @@
 
 from decimal import Decimal
 
-import numba as nb
 import numpy as np
 
 __all__ = ['fv', 'pmt', 'nper', 'ipmt', 'ppmt', 'pv', 'rate',
@@ -47,36 +46,6 @@ def _convert_when(when):
         return [_when_to_num[x] for x in when]
 
 
-def _return_ufunc_like(array):
-    try:
-        # If size of array is one, return scalar
-        return array.item()
-    except ValueError:
-        # Otherwise, return entire array
-        return array
-
-
-def _is_object_array(array):
-    return array.dtype == np.dtype("O")
-
-
-def _use_decimal_dtype(*arrays):
-    return any(_is_object_array(array) for array in arrays)
-
-
-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)
-
-
-def _get_output_array_shape(*arrays):
-    return tuple(array.shape[0] for array in arrays)
-
-
 def fv(rate, nper, pmt, pv, when='end'):
     """Compute the future value.
 
@@ -856,27 +825,6 @@ def irr(values, *, guess=None, tol=1e-12, maxiter=100, raise_exceptions=False):
     return np.nan
 
 
-@nb.njit(parallel=True)
-def _npv_native(rates, values, out):
-    for i in nb.prange(rates.shape[0]):
-        for j in nb.prange(values.shape[0]):
-            acc = 0.0
-            for t in range(values.shape[1]):
-                acc += values[j, t] / ((1.0 + rates[i]) ** t)
-            out[i, j] = acc
-
-
-# We require ``forceobj=True`` here to support decimal.Decimal types
-@nb.jit(forceobj=True)
-def _npv_decimal(rates, values, out):
-    for i in range(rates.shape[0]):
-        for j in range(values.shape[0]):
-            acc = Decimal("0.0")
-            for t in range(values.shape[1]):
-                acc += values[j, t] / ((Decimal("1.0") + rates[i]) ** t)
-            out[i, j] = acc
-
-
 def npv(rate, values):
     r"""Return the NPV (Net Present Value) of a cash flow series.
 
@@ -944,58 +892,16 @@ def npv(rate, values):
     >>> np.round(npf.npv(rate, cashflows) + initial_cashflow, 5)
     3065.22267
 
-    The NPV calculation may be applied to several ``rates`` and ``cashflows``
-    simulatneously. This produces an array of shape
-    ``(len(rates), len(cashflows))``.
-
-    >>> rates = [0.00, 0.05, 0.10]
-    >>> cashflows = [[-4_000, 500, 800], [-5_000, 600, 900]]
-    >>> npf.npv(rates, cashflows).round(2)
-    array([[-2700.  , -3500.  ],
-           [-2798.19, -3612.24],
-           [-2884.3 , -3710.74]])
-
-    The NPV calculation also supports `decimal.Decimal` types, for example
-    if using Decimal ``rates``:
-
-    >>> rates = [Decimal("0.00"), Decimal("0.05"), Decimal("0.10")]
-    >>> cashflows = [[-4_000, 500, 800], [-5_000, 600, 900]]
-    >>> npf.npv(rates, cashflows)
-    array([[Decimal('-2700.0'), Decimal('-3500.0')],
-           [Decimal('-2798.185941043083900226757370'),
-            Decimal('-3612.244897959183673469387756')],
-           [Decimal('-2884.297520661157024793388430'),
-            Decimal('-3710.743801652892561983471074')]], dtype=object)
-
-    This also works for Decimal cashflows.
-
     """
-    rates = np.atleast_1d(rate)
     values = np.atleast_2d(values)
-
-    if rates.ndim != 1:
-        msg = "invalid shape for rates. Rate must be either a scalar or 1d array"
-        raise ValueError(msg)
-
-    if values.ndim != 2:
-        msg = "invalid shape for values. Values must be either a 1d or 2d array"
-        raise ValueError(msg)
-
-    dtype = Decimal if _use_decimal_dtype(rates, values) else np.float64
-
-    if dtype == Decimal:
-        rates = _to_decimal_array_1d(rates)
-        values = _to_decimal_array_2d(values)
-
-    shape = _get_output_array_shape(rates, values)
-    out = np.empty(shape=shape, dtype=dtype)
-
-    if dtype == Decimal:
-        _npv_decimal(rates, values, out)
-    else:
-        _npv_native(rates, values, out)
-
-    return _return_ufunc_like(out)
+    timestep_array = np.arange(0, values.shape[1])
+    npv = (values / (1 + rate) ** timestep_array).sum(axis=1)
+    try:
+        # If size of array is one, return scalar
+        return npv.item()
+    except ValueError:
+        # Otherwise, return entire array
+        return npv
 
 
 def mirr(values, finance_rate, reinvest_rate, *, raise_exceptions=False):

pyproject.toml

@@ -24,6 +24,7 @@ classifiers = [
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3 :: Only",
     "Topic :: Software Development",
     "Topic :: Office/Business :: Financial :: Accounting",
@@ -37,10 +38,8 @@ classifiers = [
 packages = [{include = "numpy_financial"}]
 
 [tool.poetry.dependencies]
-python = "^3.9,<3.12"
+python = "^3.9"
 numpy = "^1.23"
-numba = "^0.58.1"
-
 
 [tool.poetry.group.test.dependencies]
 pytest = "^7.4"

tests/test_financial.py

@@ -250,50 +250,6 @@ def test_npv_decimal(self):
             Decimal("122.894854950942692161628715"),
         )
 
-    def test_npv_broadcast(self):
-        cashflows = [
-            [-15000.0, 1500.0, 2500.0, 3500.0, 4500.0, 6000.0],
-            [-15000.0, 1500.0, 2500.0, 3500.0, 4500.0, 6000.0],
-            [-15000.0, 1500.0, 2500.0, 3500.0, 4500.0, 6000.0],
-            [-15000.0, 1500.0, 2500.0, 3500.0, 4500.0, 6000.0],
-        ]
-        expected_npvs = [[122.8948549, 122.8948549, 122.8948549, 122.8948549]]
-        actual_npvs = npf.npv(0.05, cashflows)
-        assert_allclose(actual_npvs, expected_npvs)
-
-    @pytest.mark.parametrize("dtype", [Decimal, float])
-    def test_npv_broadcast_equals_for_loop(self, dtype):
-        cashflows_str = [
-            ["-15000.0", "1500.0", "2500.0", "3500.0", "4500.0", "6000.0"],
-            ["-25000.0", "1500.0", "2500.0", "3500.0", "4500.0", "6000.0"],
-            ["-35000.0", "1500.0", "2500.0", "3500.0", "4500.0", "6000.0"],
-            ["-45000.0", "1500.0", "2500.0", "3500.0", "4500.0", "6000.0"],
-        ]
-        rates_str = ["-0.05", "0.00", "0.05", "0.10", "0.15"]
-
-        cashflows = numpy.array([[dtype(x) for x in cf] for cf in cashflows_str])
-        rates = numpy.array([dtype(x) for x in rates_str])
-
-        expected = numpy.empty((len(rates), len(cashflows)), dtype=dtype)
-        for i, r in enumerate(rates):
-            for j, cf in enumerate(cashflows):
-                expected[i, j] = npf.npv(r, cf)
-
-        actual = npf.npv(rates, cashflows)
-        assert_equal(actual, expected)
-
-    @pytest.mark.parametrize("rates", ([[1, 2, 3]], numpy.empty(shape=(1, 1, 1))))
-    def test_invalid_rates_shape(self, rates):
-        cashflows = [1, 2, 3]
-        with pytest.raises(ValueError):
-            npf.npv(rates, cashflows)
-
-    @pytest.mark.parametrize("cf", ([[[1, 2, 3]]], numpy.empty(shape=(1, 1, 1))))
-    def test_invalid_cashflows_shape(self, cf):
-        rates = [1, 2, 3]
-        with pytest.raises(ValueError):
-            npf.npv(rates, cf)
-
 
 class TestPmt:
     def test_pmt_simple(self):