remove pyerf dependency

setup.cfg

@@ -10,7 +10,7 @@ long_description_content_type = text/markdown; charset=UTF-8
 url = http://github.com/cgevans/scikits-bootstrap
 platforms = any
 
-version = 1.1.0
+version = 1.2.0
 
 classifiers =
     Development Status :: 5 - Production/Stable
@@ -37,7 +37,6 @@ package_dir =
 packages = find_namespace:
 install_requires =
     numpy
-    pyerf
     typing_extensions>=4.1; python_version<"3.10"
 tests_require =
     pytest

src/scikits/bootstrap/bootstrap.py

@@ -4,7 +4,7 @@
 lies satisfies some criteria, e.g. lies in some interval."""
 from __future__ import absolute_import, division, print_function, annotations
 
-from math import ceil, sqrt
+from math import ceil, sqrt, erf
 from typing import Sequence, cast, overload
 import sys
 
@@ -28,7 +28,6 @@
     from typing import Union, Iterable, Any, Optional, Iterator, Callable, Tuple
 
 import warnings
-import pyerf
 
 try:
     from numba import njit, prange
@@ -66,16 +65,37 @@
 
 
 def _ncdf_py(x: float) -> float:
-    return 0.5 * (1 + cast(float, pyerf.erf(x / s2)))
-
-
-def _nppf_py(x: float) -> float:
-    return s2 * cast(float, pyerf.erfinv(2 * x - 1))
+    return 0.5 * (1 + cast(float, erf(x / s2)))
+ncdf = np.vectorize(_ncdf_py, [float])
 
 
-nppf = np.vectorize(_nppf_py, [float])
-ncdf = np.vectorize(_ncdf_py, [float])
+def nppf(p):
+    p = np.asarray(p)
+    out = np.empty_like(p, dtype=float)
+    ix1 = (p < 0.02425) & (p > 0)
+    oix1 = np.sqrt(-2 * np.log(p[ix1]))
+    out[ix1] = (
+            (((((-7.784894002430293e-03 * oix1 - 3.223964580411365e-01) * oix1 - 2.400758277161838e00) * oix1 - 2.549732539343734e00) * oix1 + 4.374664141464968e00) * oix1 + 2.938163982698783e00)
+            / ((((7.784695709041462e-03 * oix1 + 3.224671290700398e-01) * oix1 + 2.445134137142996e00) * oix1 + 3.754408661907416e00) * oix1 + 1)
+        )
 
+    ix2 = (0.02425 <= p) & (p <= 0.97575)
+    oix2 = (p[ix2] - 0.5)
+    sq = oix2 * oix2
+    out[ix2] = (
+            (((((-3.969683028665376e01 * sq + 2.209460984245205e02) * sq - 2.759285104469687e02) * sq + 1.383577518672690e02) * sq - 3.066479806614716e01) * sq + 2.506628277459239e00) * oix2
+        ) / (((((-5.447609879822406e01 * sq + 1.615858368580409e02) * sq - 1.556989798598866e02) * sq + 6.680131188771972e01) * sq - 1.328068155288572e01) * sq + 1)
+
+    ix3 = (p > 0.97575) & (p < 1)
+    oix3 = np.sqrt(-2 * np.log(1 - p[ix3]))
+    out[ix3] = -(
+            (((((-7.784894002430293e-03 * oix3 - 3.223964580411365e-01) * oix3 - 2.400758277161838e00) * oix3 - 2.549732539343734e00) * oix3 + 4.374664141464968e00) * oix3 + 2.938163982698783e00)
+            / ((((7.784695709041462e-03 * oix3 + 3.224671290700398e-01) * oix3 + 2.445134137142996e00) * oix3 + 3.754408661907416e00) * oix3 + 1)
+        )
+    out[p == 0] = -np.inf
+    out[p == 1] = np.inf
+
+    return out
 
 __version__ = "1.1.0"