From 13ac670f0befaaa21523ec6817da68d829f9e6dc Mon Sep 17 00:00:00 2001
From: Doug Davis <ddavis@anaconda.com>
Date: Wed, 14 Apr 2021 15:35:32 -0400
Subject: [PATCH] cleaning

---
 setup.py              |  3 ---
 src/pygram11/_bh.py   | 20 -------------------
 src/pygram11/_hist.py | 25 -----------------------
 tests/test_bh.py      | 46 -------------------------------------------
 4 files changed, 94 deletions(-)
 delete mode 100644 src/pygram11/_bh.py
 delete mode 100644 tests/test_bh.py

diff --git a/setup.py b/setup.py
index b080412..3776f44 100644
--- a/setup.py
+++ b/setup.py
@@ -183,9 +183,6 @@ def get_extensions():
 
 
 extras_require = {
-    "bh": [
-        "boost-histogram",
-    ],
     "test": [
         "pytest",
     ],
diff --git a/src/pygram11/_bh.py b/src/pygram11/_bh.py
deleted file mode 100644
index 8e9f629..0000000
--- a/src/pygram11/_bh.py
+++ /dev/null
@@ -1,20 +0,0 @@
-from typing import Optional
-
-import numpy as np
-
-try:
-    import boost_histogram as bh
-except ImportError:
-    raise ImportError("Install boost-histogram to use bh=... feature")
-
-
-def store_results_in_bh(
-    h: bh.Histogram,
-    counts: np.ndarray,
-    variances: Optional[np.ndarray] = None,
-) -> None:
-    if variances is None:
-        h[...] = counts
-    else:
-        h.view()["value"] = counts
-        h.view()["variance"] = variances
diff --git a/src/pygram11/_hist.py b/src/pygram11/_hist.py
index c90a541..4dff1ea 100644
--- a/src/pygram11/_hist.py
+++ b/src/pygram11/_hist.py
@@ -140,7 +140,6 @@ def fix1d(
     density: bool = False,
     flow: bool = False,
     cons_var: bool = False,
-    bh: Optional[Any] = None,
 ) -> Tuple[np.ndarray, Union[np.ndarray, None]]:
     r"""Histogram data with fixed (uniform) bin widths.
 
@@ -164,9 +163,6 @@ def fix1d(
     cons_var : bool
         If ``True``, conserve the variance rather than return the
         standard error (square root of the variance).
-    bh : boost_histogram.Histogram, optional
-        Pass a boost_histogram.Histogram object to store the resulting
-        counts and variances.
 
     Raises
     ------
@@ -208,10 +204,6 @@ def fix1d(
         if density:
             width = (xmax - xmin) / bins
             result = _densify_fixed_counts(result, width)
-        if bh is not None:
-            from ._bh import store_results_in_bh
-
-            store_results_in_bh(bh, result)
         return result, None
 
     if np.shape(x) != np.shape(weights):
@@ -223,11 +215,6 @@ def fix1d(
         result = _densify_fixed_weighted_counts(result, width)
     counts, variances = result
 
-    if bh is not None:
-        from ._bh import store_results_in_bh
-
-        store_results_in_bh(bh, counts, variances)
-
     if cons_var:
         return counts, variances
     return counts, np.sqrt(variances)
@@ -497,7 +484,6 @@ def fix2d(
     weights: Optional[np.ndarray] = None,
     flow: bool = False,
     cons_var: bool = False,
-    bh: Optional[Any] = None,
 ) -> Tuple[np.ndarray, Optional[np.ndarray]]:
     r"""Histogram two dimensional data with fixed (uniform) binning.
 
@@ -524,9 +510,6 @@ def fix2d(
     cons_var : bool
         If ``True``, conserve the variance rather than return the
         standard error (square root of the variance).
-    bh : boost_histogram.Histogram, optional
-        Pass a boost_histogram.Histogram object to store the resulting
-        counts and variances.
 
     Raises
     ------
@@ -578,20 +561,12 @@ def fix2d(
 
     if weights is None:
         result = _f2d(x, y, int(nx), xmin, xmax, int(ny), ymin, ymax, flow)
-        if bh is not None:
-            from ._bh import store_results_in_bh
-
-            store_results_in_bh(bh, result)
         return result, None
 
     counts, variances = _f2dw(
         x, y, weights, int(nx), xmin, xmax, int(ny), ymin, ymax, flow
     )
 
-    if bh is not None:
-        from ._bh import store_results_in_bh
-
-        store_results_in_bh(bh, counts, variances)
     if cons_var:
         return counts, variances
     return counts, np.sqrt(variances)
diff --git a/tests/test_bh.py b/tests/test_bh.py
deleted file mode 100644
index e981e1c..0000000
--- a/tests/test_bh.py
+++ /dev/null
@@ -1,46 +0,0 @@
-import numpy as np
-import boost_histogram as bh
-
-import pygram11 as pg
-import pygram11._bh as pgbh
-
-RNG = np.random.default_rng(123)
-
-
-def test_f1d():
-    x = RNG.standard_normal(size=(20000,))
-    w = RNG.uniform(0.25, 1.1, size=x.shape)
-    bins = 12
-    range = (-3.1, 3.1)
-    h1 = bh.Histogram(
-        bh.axis.Regular(bins, range[0], range[1]), storage=bh.storage.Weight()
-    )
-    counts, variances = pg.fix1d(
-        x, bins=bins, range=range, weights=w, cons_var=True, bh=h1
-    )
-    assert np.allclose(h1.counts(), counts)
-    assert np.allclose(h1.variances(), variances)
-
-
-def test_f2d():
-    x = RNG.standard_normal(size=(20000,))
-    y = RNG.standard_normal(size=(20000,))
-    w = RNG.uniform(0.25, 1.1, size=x.shape)
-    bins = (12, 14)
-    range = ((-3.1, 3.1), (-2.99, 2.99))
-    h1 = bh.Histogram(
-        bh.axis.Regular(bins[0], range[0][0], range[0][1]),
-        bh.axis.Regular(bins[1], range[1][0], range[1][1]),
-        storage=bh.storage.Weight(),
-    )
-    counts, variances = pg.fix2d(
-        x,
-        y,
-        bins=bins,
-        range=range,
-        weights=w,
-        cons_var=True,
-        bh=h1,
-    )
-    assert np.allclose(h1.counts(), counts)
-    assert np.allclose(h1.variances(), variances)