From 4b80d15c267fc515d93d88a4f43997f2fc10a1dc Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 10:09:39 -0400
Subject: [PATCH 01/14] Remove Numpy 1 limitation

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 712eaa8f11..c4eabef52f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -36,7 +36,7 @@ dependencies = [
     "joblib",
     "matplotlib >= 3.2.0",
     "mrcfile",
-    "numpy>=1.21.5, <2.0.0",
+    "numpy>=1.21.5",
     "packaging",
     "pooch>=1.7.0",
     "pillow",

From af32d27f70b89dee75425bdc31e846c422451eee Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 10:14:07 -0400
Subject: [PATCH 02/14] latest np2, Inf to inf

---
 src/aspire/basis/basis.py  | 4 ++--
 src/aspire/basis/fb_2d.py  | 4 ++--
 src/aspire/basis/fb_3d.py  | 4 ++--
 src/aspire/basis/fle_2d.py | 2 +-
 4 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/src/aspire/basis/basis.py b/src/aspire/basis/basis.py
index 23c770674a..ee6aee2d02 100644
--- a/src/aspire/basis/basis.py
+++ b/src/aspire/basis/basis.py
@@ -373,9 +373,9 @@ def __init__(self, size, ell_max=None, dtype=np.float32):
         :param size: The size of the vectors for which to define the basis.
             Currently only square images and cubic volumes are supported.
         :param ell_max: The maximum order ell of the basis elements. If no input
-            (= None), it will be set to np.Inf and the basis includes all
+            (= None), it will be set to np.inf and the basis includes all
             ell such that the resulting basis vectors are concentrated
-            below the Nyquist frequency (default Inf).
+            below the Nyquist frequency (default inf).
         """
         if ell_max is None:
             ell_max = np.inf
diff --git a/src/aspire/basis/fb_2d.py b/src/aspire/basis/fb_2d.py
index 2698e41ed6..18f7b83478 100644
--- a/src/aspire/basis/fb_2d.py
+++ b/src/aspire/basis/fb_2d.py
@@ -31,9 +31,9 @@ def __init__(self, size, ell_max=None, dtype=np.float32):
             May be a 2-tuple or an integer, in which case a square basis is assumed.
             Currently only square images are supported.
         :ell_max: The maximum order ell of the basis elements. If no input
-            (= None), it will be set to np.Inf and the basis includes all
+            (= None), it will be set to np.inf and the basis includes all
             ell such that the resulting basis vectors are concentrated
-            below the Nyquist frequency (default Inf).
+            below the Nyquist frequency (default inf).
         """
 
         if isinstance(size, int):
diff --git a/src/aspire/basis/fb_3d.py b/src/aspire/basis/fb_3d.py
index b787ff618f..dedd52025c 100644
--- a/src/aspire/basis/fb_3d.py
+++ b/src/aspire/basis/fb_3d.py
@@ -26,9 +26,9 @@ def __init__(self, size, ell_max=None, dtype=np.float32):
             May be a 3-tuple or an integer, in which case a cubic basis is assumed.
             Currently only cubic images are supported.
         :param ell_max: The maximum order ell of the basis elements. If no input
-            (= None), it will be set to np.Inf and the basis includes all
+            (= None), it will be set to np.inf and the basis includes all
             ell such that the resulting basis vectors are concentrated
-            below the Nyquist frequency (default Inf).
+            below the Nyquist frequency (default inf).
         """
         if isinstance(size, int):
             size = (size, size, size)
diff --git a/src/aspire/basis/fle_2d.py b/src/aspire/basis/fle_2d.py
index 76330e6fba..ffce0ea284 100644
--- a/src/aspire/basis/fle_2d.py
+++ b/src/aspire/basis/fle_2d.py
@@ -358,7 +358,7 @@ def _lap_eig_disk(self):
         num_ells = 1 + 2 * max_ell
         self._ells = np.zeros((num_ells, max_k), dtype=int)
         self._ks = np.zeros((num_ells, max_k), dtype=int)
-        self.bessel_zeros = np.ones((num_ells, max_k), dtype=np.float64) * np.Inf
+        self.bessel_zeros = np.ones((num_ells, max_k), dtype=np.float64) * np.inf
 
         # keep track of which order Bessel function we're on
         self._ells[0, :] = 0

From 03aceb8d1be7059c73906125c9797d8e36e19735 Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 10:48:23 -0400
Subject: [PATCH 03/14] row_stack to vstack

---
 src/aspire/basis/fpswf_2d.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/aspire/basis/fpswf_2d.py b/src/aspire/basis/fpswf_2d.py
index 21be9270d2..6eac1a91db 100644
--- a/src/aspire/basis/fpswf_2d.py
+++ b/src/aspire/basis/fpswf_2d.py
@@ -87,7 +87,7 @@ def _precomp(self):
         self.quad_rule_radial_wts = e
         self.num_angular_pts = f
 
-        us_fft_pts = np.row_stack((self.quad_rule_pts_x, self.quad_rule_pts_y))
+        us_fft_pts = np.vstack((self.quad_rule_pts_x, self.quad_rule_pts_y))
         us_fft_pts = self.bandlimit / self.rcut * us_fft_pts
         (
             blk_r,

From 2d43bf300b366514c720b6afd06f192dab721c24 Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 10:58:51 -0400
Subject: [PATCH 04/14] np2 copy False -> None

---
 src/aspire/abinitio/commonline_base.py       |  2 +-
 src/aspire/abinitio/commonline_c3_c4.py      |  2 +-
 src/aspire/abinitio/commonline_d2.py         |  4 ++--
 src/aspire/abinitio/commonline_sync3n.py     | 18 +++++++++---------
 src/aspire/apple/picking.py                  |  4 ++--
 src/aspire/basis/basis.py                    |  2 +-
 src/aspire/basis/fle_2d.py                   |  8 +++-----
 src/aspire/basis/fpswf_2d.py                 |  2 +-
 src/aspire/classification/averager2d.py      |  2 +-
 src/aspire/classification/rir_class2d.py     |  2 +-
 src/aspire/ctf/ctf_estimator.py              |  4 ++--
 src/aspire/image/image.py                    |  6 +++---
 src/aspire/nufft/cufinufft.py                |  2 +-
 src/aspire/nufft/finufft.py                  |  4 ++--
 src/aspire/numeric/complex_pca/validation.py | 10 +++++-----
 src/aspire/numeric/pyfftw_fft.py             |  2 +-
 src/aspire/operators/blk_diag_matrix.py      |  4 ++--
 src/aspire/operators/diag_matrix.py          |  2 +-
 src/aspire/reconstruction/mean.py            |  2 +-
 src/aspire/sinogram/sinogram.py              |  2 +-
 src/aspire/source/micrograph.py              |  2 +-
 src/aspire/utils/bot_align.py                |  8 ++++----
 src/aspire/utils/matrix.py                   |  2 +-
 src/aspire/utils/misc.py                     |  6 +++---
 src/aspire/utils/rotation.py                 |  6 +++---
 src/aspire/volume/volume.py                  |  2 +-
 tests/test_FFBbasis3D.py                     |  4 ++--
 tests/test_coef.py                           |  8 ++++----
 tests/test_complexPCA.py                     |  2 +-
 tests/test_diag_matrix.py                    |  2 +-
 tests/test_downsample.py                     |  4 ++--
 tests/test_matrix.py                         |  4 ++--
 tests/test_mean_estimator.py                 |  4 ++--
 tests/test_micrograph_source.py              |  2 +-
 tests/test_orient_sdp.py                     |  2 +-
 tests/test_polar_ft.py                       |  2 +-
 tests/test_simulation.py                     |  2 +-
 tests/test_volume.py                         |  6 +++---
 38 files changed, 75 insertions(+), 77 deletions(-)

diff --git a/src/aspire/abinitio/commonline_base.py b/src/aspire/abinitio/commonline_base.py
index fe456c645e..2cd80b61fa 100644
--- a/src/aspire/abinitio/commonline_base.py
+++ b/src/aspire/abinitio/commonline_base.py
@@ -149,7 +149,7 @@ def _prepare_pf(self):
             #   Apply mask in doubles (allow imgs to upcast as needed)
             imgs = imgs * fuzz_mask
             #   Cast to desired type
-            imgs = Image(imgs.asnumpy().astype(self.dtype, copy=False))
+            imgs = Image(imgs.asnumpy().astype(self.dtype, copy=None))
 
         # Obtain coefficients of polar Fourier transform for input 2D images
         pft = PolarFT(
diff --git a/src/aspire/abinitio/commonline_c3_c4.py b/src/aspire/abinitio/commonline_c3_c4.py
index 242094b745..bc2956ec0d 100644
--- a/src/aspire/abinitio/commonline_c3_c4.py
+++ b/src/aspire/abinitio/commonline_c3_c4.py
@@ -693,7 +693,7 @@ def _J_sync_power_method(self, vijs):
         while itr < max_iters and residual > epsilon:
             itr += 1
             # Note, this appears to need double precision for accuracy in the following division.
-            vec_new = self._signs_times_v(vijs, vec).astype(np.float64, copy=False)
+            vec_new = self._signs_times_v(vijs, vec).astype(np.float64, copy=None)
             vec_new = vec_new / norm(vec_new)
             residual = norm(vec_new - vec)
             vec = vec_new
diff --git a/src/aspire/abinitio/commonline_d2.py b/src/aspire/abinitio/commonline_d2.py
index a8e951c642..93b2e9bc0a 100644
--- a/src/aspire/abinitio/commonline_d2.py
+++ b/src/aspire/abinitio/commonline_d2.py
@@ -1149,12 +1149,12 @@ def _sync_colors(self, Rijs):
 
         # Seed eigs initial vector for iterative method.
         # scipy LinearOperator needs doubles for some architectures (arm).
-        v0 = randn(3 * n_pairs, seed=self.seed).astype(np.float64, copy=False)
+        v0 = randn(3 * n_pairs, seed=self.seed).astype(np.float64, copy=None)
 
         v0 = v0 / norm(v0)
         vals, colors = la.eigs(color_mat, k=3, which="LR", v0=v0)
         vals = np.real(vals)
-        colors = np.real(colors).astype(self.dtype, copy=False)
+        colors = np.real(colors).astype(self.dtype, copy=None)
         colors = np.sign(colors[0]) * colors  # Stable eigs
         cp, _ = self._unmix_colors(colors[:, :2])
 
diff --git a/src/aspire/abinitio/commonline_sync3n.py b/src/aspire/abinitio/commonline_sync3n.py
index 5afa771c69..aa11a2348a 100644
--- a/src/aspire/abinitio/commonline_sync3n.py
+++ b/src/aspire/abinitio/commonline_sync3n.py
@@ -197,7 +197,7 @@ def _sync3n_S_to_rot(self, S, W=None, n_eigs=4):
         """
 
         # Critical this occurs in double precision
-        S = S.astype(np.float64, copy=False)
+        S = S.astype(np.float64, copy=None)
 
         if n_eigs < 3:
             raise ValueError(
@@ -213,7 +213,7 @@ def _sync3n_S_to_rot(self, S, W=None, n_eigs=4):
                 )
             # Initialize D
             # Critical this occurs in double precision
-            W = W.astype(np.float64, copy=False)
+            W = W.astype(np.float64, copy=None)
             D = np.mean(W, axis=1)
 
             Dhalf = D
@@ -664,8 +664,8 @@ def _pairs_probabilities_cupy(self, Rijs, P2, A, a, B, b, x0):
         )
 
         # accumulate over thread results
-        ln_f_arb = ln_f_arb_dev.get().astype(self.dtype, copy=False)
-        ln_f_ind = ln_f_ind_dev.get().astype(self.dtype, copy=False)
+        ln_f_arb = ln_f_arb_dev.get().astype(self.dtype, copy=None)
+        ln_f_ind = ln_f_ind_dev.get().astype(self.dtype, copy=None)
 
         return ln_f_ind, ln_f_arb
 
@@ -748,8 +748,8 @@ def fun(x, B, P, b, x0, A=A, a=a):
 
         popt, pcov = curve_fit(
             fun,
-            hist_x.astype(np.float64, copy=False),
-            scores_hist.astype(np.float64, copy=False),
+            hist_x.astype(np.float64, copy=None),
+            scores_hist.astype(np.float64, copy=None),
             p0=start_values,
             bounds=(lower_bounds, upper_bounds),
             method="trf",  # MATLAB used method "LAR" with algo "Trust-Region"
@@ -1043,7 +1043,7 @@ def _J_sync_power_method(self, Rijs):
         while itr < max_iters and residual > epsilon:
             itr += 1
             # Todo, this code code actually needs double precision for accuracy... forcing.
-            vec_new = self._signs_times_v(Rijs, vec).astype(np.float64, copy=False)
+            vec_new = self._signs_times_v(Rijs, vec).astype(np.float64, copy=None)
             vec_new = vec_new / norm(vec_new)
             residual = norm(vec_new - vec)
             vec = vec_new
@@ -1073,7 +1073,7 @@ def _signs_times_v(self, Rijs, vec):
         else:
             new_vec = self._signs_times_v_host(Rijs, vec)
 
-        return new_vec.astype(vec.dtype, copy=False)
+        return new_vec.astype(vec.dtype, copy=None)
 
     def _signs_times_v_host(self, Rijs, vec):
         """
@@ -1177,7 +1177,7 @@ def _signs_times_v_cupy(self, Rijs, vec):
         )
 
         # dtoh
-        new_vec = new_vec_dev.get().astype(vec.dtype, copy=False)
+        new_vec = new_vec_dev.get().astype(vec.dtype, copy=None)
 
         return new_vec
 
diff --git a/src/aspire/apple/picking.py b/src/aspire/apple/picking.py
index d64d16c773..d54cf61f1d 100644
--- a/src/aspire/apple/picking.py
+++ b/src/aspire/apple/picking.py
@@ -149,7 +149,7 @@ def read_micrograph(self):
         self.original_im = (
             DiskMicrographSource(self.filename)
             .asnumpy()[0]
-            .astype(np.float32, copy=False)
+            .astype(np.float32, copy=None)
         )
 
         # Discard outer pixels
@@ -167,7 +167,7 @@ def read_micrograph(self):
         # Note, float64 required for signal.correlate call accuracy.
         im = np.asarray(
             PILImage.fromarray(im).resize(size, PILImage.Resampling.BICUBIC)
-        ).astype(np.float64, copy=False)
+        ).astype(np.float64, copy=None)
 
         im = signal.correlate(
             im,
diff --git a/src/aspire/basis/basis.py b/src/aspire/basis/basis.py
index ee6aee2d02..6baf16f769 100644
--- a/src/aspire/basis/basis.py
+++ b/src/aspire/basis/basis.py
@@ -62,7 +62,7 @@ def __init__(self, basis, data, dtype=None):
             )
         self.basis = basis
 
-        self._data = data.astype(self.dtype, copy=False)
+        self._data = data.astype(self.dtype, copy=None)
         self.ndim = self._data.ndim
         self.shape = self._data.shape
         self.stack_ndim = self._data.ndim - 1
diff --git a/src/aspire/basis/fle_2d.py b/src/aspire/basis/fle_2d.py
index ffce0ea284..6499919110 100644
--- a/src/aspire/basis/fle_2d.py
+++ b/src/aspire/basis/fle_2d.py
@@ -314,7 +314,7 @@ def _compute_nufft_points(self):
         )
         grid_xy[0] = xp.cos(phi)  # x
         grid_xy[1] = xp.sin(phi)  # y
-        grid_xy = grid_xy * nodes * h
+        grid_xy[:] = grid_xy * nodes * h
         self.grid_xy = grid_xy.reshape(2, -1)
 
     def _build_interpolation_matrix(self):
@@ -643,7 +643,7 @@ def _step1(self, z):
         num_img = z.shape[0]
         z = z[:, :, : self.num_angular_nodes // 2].reshape(num_img, -1)
         im = anufft(
-            z.astype(complex_type(self.dtype), copy=False),
+            z.astype(complex_type(self.dtype), copy=None),
             self.grid_xy,
             (self.nres, self.nres),
             epsilon=self.epsilon,
@@ -798,9 +798,7 @@ def filter_to_basis_mat(self, f, **kwargs):
         omega = 2 * xp.pi * xp.vstack((omegax.flatten("C"), omegay.flatten("C")))
 
         h_vals2d = (
-            xp.asarray(h_fun(omega))
-            .reshape(n_k, n_theta)
-            .astype(self.dtype, copy=False)
+            xp.asarray(h_fun(omega)).reshape(n_k, n_theta).astype(self.dtype, copy=None)
         )
         h_vals = xp.sum(h_vals2d, axis=1) / n_theta
 
diff --git a/src/aspire/basis/fpswf_2d.py b/src/aspire/basis/fpswf_2d.py
index 6eac1a91db..aa7b9913d9 100644
--- a/src/aspire/basis/fpswf_2d.py
+++ b/src/aspire/basis/fpswf_2d.py
@@ -99,7 +99,7 @@ def _precomp(self):
         ) = self._pswf_integration_sub_routine()
 
         self.us_fft_pts = us_fft_pts.astype(
-            self.dtype, copy=False
+            self.dtype, copy=None
         )  # TODO, debug where this is incorrect dtype
         self.blk_r = blk_r
         self.num_angular_pts = num_angular_pts
diff --git a/src/aspire/classification/averager2d.py b/src/aspire/classification/averager2d.py
index b447a6d91c..644359c9e7 100644
--- a/src/aspire/classification/averager2d.py
+++ b/src/aspire/classification/averager2d.py
@@ -82,7 +82,7 @@ def _cls_images(self, cls, src=None):
             source for a certain operation (ie alignment).
         """
         src = src or self.src
-        return src.images[cls].asnumpy().astype(self.dtype, copy=False)
+        return src.images[cls].asnumpy().astype(self.dtype, copy=None)
 
 
 class AligningAverager2D(Averager2D):
diff --git a/src/aspire/classification/rir_class2d.py b/src/aspire/classification/rir_class2d.py
index 19a3479ffe..dde35ef050 100644
--- a/src/aspire/classification/rir_class2d.py
+++ b/src/aspire/classification/rir_class2d.py
@@ -390,7 +390,7 @@ def _sk_pca(self, M):
         #   We use an extension of SK that is hacked to admit complex.
         pca = ComplexPCA(
             self.bispectrum_components,
-            copy=False,  # careful, overwrites data matrix... we'll handle the copies.
+            copy=None,  # careful, overwrites data matrix... we'll handle the copies.
             svd_solver="auto",  # use randomized (Halko) for larger problems
             random_state=self.seed,
         )
diff --git a/src/aspire/ctf/ctf_estimator.py b/src/aspire/ctf/ctf_estimator.py
index b6983cb071..39f2998a21 100644
--- a/src/aspire/ctf/ctf_estimator.py
+++ b/src/aspire/ctf/ctf_estimator.py
@@ -241,7 +241,7 @@ def estimate_psd(self, blocks, tapers_1d):
         """
 
         num_1d_tapers = tapers_1d.shape[-1]
-        tapers_1d = tapers_1d.astype(complex_type(self.dtype), copy=False)
+        tapers_1d = tapers_1d.astype(complex_type(self.dtype), copy=None)
 
         blocks_mt = np.zeros(blocks[0, :, :].shape, dtype=self.dtype)
 
@@ -768,7 +768,7 @@ def estimate_ctf(
             micrograph = mrc.data
 
         # Try to match dtype used in Basis instance
-        micrograph = micrograph.astype(dtype, copy=False)
+        micrograph = micrograph.astype(dtype, copy=None)
 
         micrograph_blocks = ctf_object.preprocess_micrograph(micrograph, psd_size)
 
diff --git a/src/aspire/image/image.py b/src/aspire/image/image.py
index 757362870d..6d0f3b8960 100644
--- a/src/aspire/image/image.py
+++ b/src/aspire/image/image.py
@@ -195,7 +195,7 @@ def __init__(self, data, pixel_size=None, dtype=None):
         if not data.shape[-1] == data.shape[-2]:
             raise ValueError("Only square ndarrays are supported.")
 
-        self._data = data.astype(self.dtype, copy=False)
+        self._data = data.astype(self.dtype, copy=None)
         self.ndim = self._data.ndim
         self.shape = self._data.shape
         self.stack_ndim = self._data.ndim - 2
@@ -543,7 +543,7 @@ def load(filepath, dtype=None):
 
         # Attempt casting when user provides dtype
         if dtype is not None:
-            im = im.astype(dtype, copy=False)
+            im = im.astype(dtype, copy=None)
 
         # Return as Image instance
         return Image(im, pixel_size=pixel_size)
@@ -658,7 +658,7 @@ def backproject(self, rot_matrices, symmetry_group=None, zero_nyquist=True):
 
             # TODO: rotated_grids might as well give us correctly shaped array in the first place
             pts_rot = aspire.volume.rotated_grids(L, rotations).astype(
-                self.dtype, copy=False
+                self.dtype, copy=None
             )
             pts_rot = pts_rot.reshape((3, -1))
 
diff --git a/src/aspire/nufft/cufinufft.py b/src/aspire/nufft/cufinufft.py
index fd869aacfd..2660f4ea46 100644
--- a/src/aspire/nufft/cufinufft.py
+++ b/src/aspire/nufft/cufinufft.py
@@ -30,7 +30,7 @@ def __init__(self, sz, fourier_pts, epsilon=1e-8, ntransforms=1, **kwargs):
         # ASPIRE-Python/703
         # Cast to doubles.
         self._original_dtype = fourier_pts.dtype
-        fourier_pts = fourier_pts.astype(np.float64, copy=False)
+        fourier_pts = fourier_pts.astype(np.float64, copy=None)
 
         # Basic dtype passthough.
         dtype = fourier_pts.dtype
diff --git a/src/aspire/nufft/finufft.py b/src/aspire/nufft/finufft.py
index efc1a062f2..e396d76124 100644
--- a/src/aspire/nufft/finufft.py
+++ b/src/aspire/nufft/finufft.py
@@ -99,7 +99,7 @@ def transform(self, signal):
         ), f"Signal frame to be transformed must have shape {self.sz}"
 
         # FINUFFT was designed for a complex input array
-        signal = np.array(signal, copy=False, dtype=self.complex_dtype, order="C")
+        signal = np.array(signal, copy=None, dtype=self.complex_dtype, order="C")
 
         result = self._transform_plan.execute(signal)
 
@@ -130,7 +130,7 @@ def adjoint(self, signal):
                 signal = signal.reshape(self.num_pts)
 
         # FINUFFT was designed for a complex input array
-        signal = np.array(signal, copy=False, dtype=self.complex_dtype, order="C")
+        signal = np.array(signal, copy=None, dtype=self.complex_dtype, order="C")
 
         result = self._adjoint_plan.execute(signal)
 
diff --git a/src/aspire/numeric/complex_pca/validation.py b/src/aspire/numeric/complex_pca/validation.py
index 7fafedfe18..11d7aaba9f 100644
--- a/src/aspire/numeric/complex_pca/validation.py
+++ b/src/aspire/numeric/complex_pca/validation.py
@@ -81,7 +81,7 @@ def _ensure_sparse_format(
         Data type of result. If None, the dtype of the input is preserved.
 
     copy : boolean
-        Whether a forced copy will be triggered. If copy=False, a copy might
+        Whether a forced copy will be triggered. If copy=None, a copy might
         be triggered by a conversion.
 
     force_all_finite : boolean or 'allow-nan', (default=True)
@@ -173,7 +173,7 @@ def check_array(
     accept_large_sparse=True,
     dtype="numeric",
     order=None,
-    copy=False,
+    copy=None,
     force_all_finite=True,
     ensure_2d=True,
     allow_nd=False,
@@ -216,13 +216,13 @@ def check_array(
 
     order : 'F', 'C' or None (default=None)
         Whether an array will be forced to be fortran or c-style.
-        When order is None (default), then if copy=False, nothing is ensured
+        When order is None (default), then if copy=None, nothing is ensured
         about the memory layout of the output array; otherwise (copy=True)
         the memory layout of the returned array is kept as close as possible
         to the original array.
 
     copy : boolean (default=False)
-        Whether a forced copy will be triggered. If copy=False, a copy might
+        Whether a forced copy will be triggered. If copy=None, a copy might
         be triggered by a conversion.
 
     force_all_finite : boolean or 'allow-nan', (default=True)
@@ -365,7 +365,7 @@ def check_array(
                     array = np.asarray(array, order=order)
                     if array.dtype.kind == "f":
                         _assert_all_finite(array, allow_nan=False, msg_dtype=dtype)
-                    array = array.astype(dtype, casting="unsafe", copy=False)
+                    array = array.astype(dtype, casting="unsafe", copy=None)
                 else:
                     array = np.asarray(array, order=order, dtype=dtype)
             except ComplexWarning:
diff --git a/src/aspire/numeric/pyfftw_fft.py b/src/aspire/numeric/pyfftw_fft.py
index 95a8ea80f7..4503b42b38 100644
--- a/src/aspire/numeric/pyfftw_fft.py
+++ b/src/aspire/numeric/pyfftw_fft.py
@@ -139,7 +139,7 @@ def ifftn(self, a, axes=None, workers=-1):
         # FFTW_BACKWARD requires complex input array, cast as needed.
         # See https://pyfftw.readthedocs.io/en/latest/source/pyfftw/pyfftw.html#scheme-table
         comp_type = complex_type(a.dtype)
-        a = a.astype(comp_type, copy=False)
+        a = a.astype(comp_type, copy=None)
 
         mutex.acquire()
         try:
diff --git a/src/aspire/operators/blk_diag_matrix.py b/src/aspire/operators/blk_diag_matrix.py
index 3e493f9525..af882ecc68 100644
--- a/src/aspire/operators/blk_diag_matrix.py
+++ b/src/aspire/operators/blk_diag_matrix.py
@@ -91,7 +91,7 @@ def append(self, blk):
         :param blk: Block to append (ndarray).
         """
 
-        self.data.append(blk.astype(self.dtype, copy=False))
+        self.data.append(blk.astype(self.dtype, copy=None))
         self.nblocks += 1
         self.reset_cache()
 
@@ -130,7 +130,7 @@ def __setitem__(self, key, value):
         Convenience wrapper, setter on self.data.
         """
 
-        self.data[key] = value.astype(self.dtype, copy=False)
+        self.data[key] = value.astype(self.dtype, copy=None)
         self.reset_cache()
 
     def __len__(self):
diff --git a/src/aspire/operators/diag_matrix.py b/src/aspire/operators/diag_matrix.py
index 4c94ab83d1..68d6a728ae 100644
--- a/src/aspire/operators/diag_matrix.py
+++ b/src/aspire/operators/diag_matrix.py
@@ -45,7 +45,7 @@ def __init__(self, data, dtype=None):
         self.dtype = np.dtype(dtype)
 
         # Assign the `data`
-        self._data = data.astype(self.dtype, copy=False)
+        self._data = data.astype(self.dtype, copy=None)
 
         # Assign shapes from `data`
         self.count = self._data.shape[-1]
diff --git a/src/aspire/reconstruction/mean.py b/src/aspire/reconstruction/mean.py
index d0cade9754..56f0624e8d 100644
--- a/src/aspire/reconstruction/mean.py
+++ b/src/aspire/reconstruction/mean.py
@@ -102,7 +102,7 @@ def _compute_kernel(self):
             _range = np.arange(i, min(self.src.n, i + self.batch_size), dtype=int)
             sq_filters_f = evaluate_src_filters_on_grid(self.src, _range) ** 2
             amplitudes_sq = (self.src.amplitudes[_range] ** 2).astype(
-                self.dtype, copy=False
+                self.dtype, copy=None
             )
 
             for k in range(self.r):
diff --git a/src/aspire/sinogram/sinogram.py b/src/aspire/sinogram/sinogram.py
index 7c7bb43662..0f82b0c479 100644
--- a/src/aspire/sinogram/sinogram.py
+++ b/src/aspire/sinogram/sinogram.py
@@ -37,7 +37,7 @@ def __init__(self, data, dtype=None):
                 f"Invalid data shape: {data.shape}. Expected shape: (..., angles, radial_points), where '...' is the stack number."
             )
 
-        self._data = data.astype(self.dtype, copy=False)
+        self._data = data.astype(self.dtype, copy=None)
         self.ndim = self._data.ndim
         self.shape = self._data.shape
         self.stack_shape = self._data.shape[:-2]
diff --git a/src/aspire/source/micrograph.py b/src/aspire/source/micrograph.py
index 5aa35e389c..86b161d822 100644
--- a/src/aspire/source/micrograph.py
+++ b/src/aspire/source/micrograph.py
@@ -155,7 +155,7 @@ def __init__(self, micrographs, dtype=None, pixel_size=None):
         )
 
         # We're already backed by an array, access it directly.
-        self._data = micrographs.astype(self.dtype, copy=False)
+        self._data = micrographs.astype(self.dtype, copy=None)
 
     def _images(self, indices):
         """
diff --git a/src/aspire/utils/bot_align.py b/src/aspire/utils/bot_align.py
index fc8fbe4fdc..e94888d92e 100644
--- a/src/aspire/utils/bot_align.py
+++ b/src/aspire/utils/bot_align.py
@@ -139,7 +139,7 @@ def cost(new, t=t, q=q):
             Loss function for surrogate problems.
             """
             kx = np.array(
-                [cov_fun(new.astype(dtype, copy=False), R[j]) for j in range(t)]
+                [cov_fun(new.astype(dtype, copy=None), R[j]) for j in range(t)]
             )
             mu = kx @ q
             return mu
@@ -151,7 +151,7 @@ def euclidean_grad(new, t=t, q=q):
             """
             # Corresponds to equation 11 in the paper.
             kx_grad = np.array(
-                [cov_fun_grad(new.astype(dtype, copy=False), R[j]) for j in range(t)]
+                [cov_fun_grad(new.astype(dtype, copy=None), R[j]) for j in range(t)]
             )
 
             kx_grad = kx_grad.reshape((t, 9))
@@ -168,7 +168,7 @@ def euclidean_grad(new, t=t, q=q):
             verbosity=verbosity,
         )
         result = optimizer.run(problem)
-        R_new = result.point.astype(dtype, copy=False)
+        R_new = result.point.astype(dtype, copy=None)
 
         loss[t] = loss_fun(R_new)
         R[t] = R_new
@@ -190,7 +190,7 @@ def loss_u(u):
             """
             Convert the alignment loss function over SO(3) to be over R^3.
             """
-            u = u.astype(dtype, copy=False)
+            u = u.astype(dtype, copy=None)
             R = sign * Rotation.from_rotvec(u).matrices[0]
             v_rot = vol_given_ds.rotate(Rotation(R)).asnumpy()[0]
             return norm(vol_ref_ds - v_rot)
diff --git a/src/aspire/utils/matrix.py b/src/aspire/utils/matrix.py
index 71c709608b..bc802f87f8 100644
--- a/src/aspire/utils/matrix.py
+++ b/src/aspire/utils/matrix.py
@@ -462,7 +462,7 @@ def nearest_rotations(A, allow_reflection=False):
         # If det(U)*det(V) = -1, we negate the third singular value to
         # ensure we have a rotation.
         neg_det_idx = np.linalg.det(U) * np.linalg.det(V) < 0
-        U[neg_det_idx] = U[neg_det_idx] @ np.diag((1, 1, -1)).astype(dtype, copy=False)
+        U[neg_det_idx] = U[neg_det_idx] @ np.diag((1, 1, -1)).astype(dtype, copy=None)
 
     rots = U @ V
 
diff --git a/src/aspire/utils/misc.py b/src/aspire/utils/misc.py
index a3f9917024..087454de5e 100644
--- a/src/aspire/utils/misc.py
+++ b/src/aspire/utils/misc.py
@@ -135,7 +135,7 @@ def gaussian_1d(size, mu=0, sigma=1, dtype=np.float64):
 
     p = (g["x"] - mu) ** 2 / (2 * sigma**2)
 
-    return np.exp(-p).astype(dtype, copy=False)
+    return np.exp(-p).astype(dtype, copy=None)
 
 
 def gaussian_2d(size, mu=(0, 0), sigma=(1, 1), indexing="yx", dtype=np.float64):
@@ -180,7 +180,7 @@ def gaussian_2d(size, mu=(0, 0), sigma=(1, 1), indexing="yx", dtype=np.float64):
         2 * sigma[1] ** 2
     )
 
-    return np.exp(-p).astype(dtype, copy=False)
+    return np.exp(-p).astype(dtype, copy=None)
 
 
 def gaussian_3d(size, mu=(0, 0, 0), sigma=(1, 1, 1), indexing="zyx", dtype=np.float64):
@@ -228,7 +228,7 @@ def gaussian_3d(size, mu=(0, 0, 0), sigma=(1, 1, 1), indexing="zyx", dtype=np.fl
         + (g["z"] - mu[2]) ** 2 / (2 * sigma[2] ** 2)
     )
 
-    return np.exp(-p).astype(dtype, copy=False)
+    return np.exp(-p).astype(dtype, copy=None)
 
 
 def bump_3d(size, spread=1, dtype=np.float64):
diff --git a/src/aspire/utils/rotation.py b/src/aspire/utils/rotation.py
index 07a31df9df..fb643914bf 100644
--- a/src/aspire/utils/rotation.py
+++ b/src/aspire/utils/rotation.py
@@ -256,7 +256,7 @@ def from_euler(values, dtype=None):
         """
         dtype = dtype or getattr(values, "dtype", np.float32)
         rotations = sp_rot.from_euler("ZYZ", values, degrees=False)
-        matrices = rotations.as_matrix().astype(dtype, copy=False)
+        matrices = rotations.as_matrix().astype(dtype, copy=None)
         return Rotation(matrices)
 
     @staticmethod
@@ -324,7 +324,7 @@ def from_rotvec(vec, dtype=None):
         """
         dtype = dtype or vec.dtype
         rots = sp_rot.from_rotvec(vec)
-        matrices = rots.as_matrix().astype(dtype, copy=False)
+        matrices = rots.as_matrix().astype(dtype, copy=None)
         return Rotation(matrices)
 
     @staticmethod
@@ -337,7 +337,7 @@ def from_matrix(values, dtype=None):
         :return: new Rotation object
         """
         dtype = dtype or values.dtype
-        return Rotation(values.astype(dtype, copy=False))
+        return Rotation(values.astype(dtype, copy=None))
 
     @staticmethod
     def generate_random_rotations(
diff --git a/src/aspire/volume/volume.py b/src/aspire/volume/volume.py
index eae985a794..1954a1cbd5 100644
--- a/src/aspire/volume/volume.py
+++ b/src/aspire/volume/volume.py
@@ -105,7 +105,7 @@ def __init__(self, data, dtype=None, pixel_size=None, symmetry_group=None):
         if not (data.shape[-1] == data.shape[-2] == data.shape[-3]):
             raise ValueError("Only cubed ndarrays are supported.")
 
-        self._data = data.astype(self.dtype, copy=False)
+        self._data = data.astype(self.dtype, copy=None)
         self.ndim = self._data.ndim
         self.shape = self._data.shape
         self.stack_ndim = self._data.ndim - 3
diff --git a/tests/test_FFBbasis3D.py b/tests/test_FFBbasis3D.py
index 03bdfdd21b..3992f5d374 100644
--- a/tests/test_FFBbasis3D.py
+++ b/tests/test_FFBbasis3D.py
@@ -470,7 +470,7 @@ def testFFBBasis3DEvaluate(self, basis):
 
     def testFFBBasis3DEvaluate_t(self, basis):
         x = np.load(os.path.join(DATA_DIR, "ffbbasis3d_xcoef_in_8_8_8.npy")).T  # RCOPT
-        x = x.astype(basis.dtype, copy=False)
+        x = x.astype(basis.dtype, copy=None)
         result = basis.evaluate_t(Volume(x))
 
         ref = np.load(os.path.join(DATA_DIR, "ffbbasis3d_vcoef_out_8_8_8.npy"))[..., 0]
@@ -479,7 +479,7 @@ def testFFBBasis3DEvaluate_t(self, basis):
 
     def testFFBBasis3DExpand(self, basis):
         x = np.load(os.path.join(DATA_DIR, "ffbbasis3d_xcoef_in_8_8_8.npy")).T  # RCOPT
-        x = x.astype(basis.dtype, copy=False)
+        x = x.astype(basis.dtype, copy=None)
         result = basis.expand(x)
 
         ref = np.load(os.path.join(DATA_DIR, "ffbbasis3d_vcoef_out_exp_8_8_8.npy"))[
diff --git a/tests/test_coef.py b/tests/test_coef.py
index 3ace0ddec5..2a283d16e4 100644
--- a/tests/test_coef.py
+++ b/tests/test_coef.py
@@ -90,7 +90,7 @@ def coef_fixture(basis, stack, dtype):
     # shape.
     size = stack + (basis.count,)
 
-    coef_np = np.random.random(size=size).astype(dtype, copy=False)
+    coef_np = np.random.random(size=size).astype(dtype, copy=None)
 
     return Coef(basis, coef_np, dtype=dtype)
 
@@ -212,7 +212,7 @@ def test_add(basis, coef_fixture):
     Tests addition operation against pure Numpy.
     """
     # Make array
-    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=False)
+    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=None)
     # Construct Coef
     c = Coef(basis, x)
 
@@ -231,7 +231,7 @@ def test_sub(basis, coef_fixture):
     Tests subtraction operation against pure Numpy.
     """
     # Make array
-    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=False)
+    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=None)
     # Construct Coef
     c = Coef(basis, x)
 
@@ -264,7 +264,7 @@ def test_mul(basis, coef_fixture):
     Tests multiplication operation against pure Numpy.
     """
     # Make array
-    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=False)
+    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=None)
     # Construct Coef
     c = Coef(basis, x)
 
diff --git a/tests/test_complexPCA.py b/tests/test_complexPCA.py
index 509b0b84a5..1c224324d7 100644
--- a/tests/test_complexPCA.py
+++ b/tests/test_complexPCA.py
@@ -53,7 +53,7 @@ def testLargeFitTransform(self):
         """
 
         pca = ComplexPCA(
-            n_components=self.components_large, copy=False, svd_solver="full"
+            n_components=self.components_large, copy=None, svd_solver="full"
         )
 
         # Input data matrix X should be (n_samples, m_features)
diff --git a/tests/test_diag_matrix.py b/tests/test_diag_matrix.py
index 05805912c9..30f2b76faa 100644
--- a/tests/test_diag_matrix.py
+++ b/tests/test_diag_matrix.py
@@ -65,7 +65,7 @@ def diag_matrix_fixture(stack, matrix_size, dtype):
     """
     shape = (2,) + stack + (matrix_size,)
     # Internally convert dtype.  Passthrough will be checked explicitly in `test_dtype_passthrough` and `test_dtype_cast`
-    d_np = np.random.random(shape).astype(dtype, copy=False)
+    d_np = np.random.random(shape).astype(dtype, copy=None)
     d1 = DiagMatrix(d_np[0])
     d2 = DiagMatrix(d_np[1])
 
diff --git a/tests/test_downsample.py b/tests/test_downsample.py
index 6c1cac82dd..1af37d7281 100644
--- a/tests/test_downsample.py
+++ b/tests/test_downsample.py
@@ -148,7 +148,7 @@ def emdb_vol():
 
 @pytest.fixture(scope="module")
 def volume(emdb_vol, res, dtype):
-    vol = emdb_vol.astype(dtype, copy=False)
+    vol = emdb_vol.astype(dtype, copy=None)
     vol = vol.downsample(res)
     return vol
 
@@ -266,7 +266,7 @@ def test_pixel_size():
     dsL = 5  # downsampled
 
     # Construct a small test Image
-    img = Image(np.random.random((1, L, L)).astype(DTYPE, copy=False), pixel_size=1.23)
+    img = Image(np.random.random((1, L, L)).astype(DTYPE, copy=None), pixel_size=1.23)
 
     # Downsample the image
     result = img.downsample(dsL)
diff --git a/tests/test_matrix.py b/tests/test_matrix.py
index 728200b9b3..be6829d3fa 100644
--- a/tests/test_matrix.py
+++ b/tests/test_matrix.py
@@ -356,7 +356,7 @@ def test_nearest_rotations(dtype):
     rots = Rotation.generate_random_rotations(n_rots, seed=0, dtype=dtype).matrices
 
     # Add some noise to the rotations.
-    noise = 1e-3 * randn(n_rots * 9, seed=0).astype(dtype, copy=False).reshape(
+    noise = 1e-3 * randn(n_rots * 9, seed=0).astype(dtype, copy=None).reshape(
         n_rots, 3, 3
     )
     noisy_rots = rots + noise
@@ -381,7 +381,7 @@ def test_nearest_rotations_reflection(dtype):
 
     # Add a reflection and some noise to the rotation.
     refl = rot @ np.diag((1, -1, 1)).astype(dtype)
-    noise = 1e-3 * randn(9, seed=0).astype(dtype, copy=False).reshape(3, 3)
+    noise = 1e-3 * randn(9, seed=0).astype(dtype, copy=None).reshape(3, 3)
     noisy_refl = refl + noise
 
     # Find nearest rotation.
diff --git a/tests/test_mean_estimator.py b/tests/test_mean_estimator.py
index e6b2a2f837..3e7f915193 100644
--- a/tests/test_mean_estimator.py
+++ b/tests/test_mean_estimator.py
@@ -115,8 +115,8 @@ def test_adjoint(sim, basis, estimator):
     L = sim.L
     n = sim.n
 
-    u = np.random.rand(n, L, L).astype(sim.dtype, copy=False)
-    v = np.random.rand(L, L, L).astype(sim.dtype, copy=False)
+    u = np.random.rand(n, L, L).astype(sim.dtype, copy=None)
+    v = np.random.rand(L, L, L).astype(sim.dtype, copy=None)
 
     proj = Volume(v).project(rots)
     backproj = Image(u).backproject(rots)
diff --git a/tests/test_micrograph_source.py b/tests/test_micrograph_source.py
index d4793cf61f..c44e703cbb 100644
--- a/tests/test_micrograph_source.py
+++ b/tests/test_micrograph_source.py
@@ -56,7 +56,7 @@ def image_data_fixture(micrograph_count, micrograph_size, dtype):
     This generates a Numpy array with prescribed shape and dtype.
     """
     img_np = np.random.rand(micrograph_count, micrograph_size, micrograph_size)
-    return img_np.astype(dtype, copy=False)
+    return img_np.astype(dtype, copy=None)
 
 
 # =====
diff --git a/tests/test_orient_sdp.py b/tests/test_orient_sdp.py
index 22658ee06a..aa215d1766 100644
--- a/tests/test_orient_sdp.py
+++ b/tests/test_orient_sdp.py
@@ -152,7 +152,7 @@ def test_ATA_solver():
     rots = Rotation.generate_random_rotations(n=n_rots, seed=seed, dtype=dtype).matrices
 
     # Create a simple reference linear transformation A that is rank-3.
-    A_ref = np.diag([1, 2, 3]).astype(dtype, copy=False)
+    A_ref = np.diag([1, 2, 3]).astype(dtype, copy=None)
 
     # Create v1 and v2 such that A_ref*v1=R1 and A_ref*v2=R2, R1 and R2 are the first
     # and second columns of all rotations.
diff --git a/tests/test_polar_ft.py b/tests/test_polar_ft.py
index 425d5e14bb..4ec69b67e4 100644
--- a/tests/test_polar_ft.py
+++ b/tests/test_polar_ft.py
@@ -203,7 +203,7 @@ def test_half_to_full_transform(stack_shape):
     """
     img_size = 32
     image = Image(
-        np.random.rand(*stack_shape, img_size, img_size).astype(np.float32, copy=False)
+        np.random.rand(*stack_shape, img_size, img_size).astype(np.float32, copy=None)
     )
     pft = PolarFT(size=img_size)
     pf = pft.transform(image)
diff --git a/tests/test_simulation.py b/tests/test_simulation.py
index 944e2e7c06..46b00d2ce9 100644
--- a/tests/test_simulation.py
+++ b/tests/test_simulation.py
@@ -82,7 +82,7 @@ def testPassthroughFromVol(self):
         without an explcit Simulation dtype.
         """
         for dtype in (np.float32, np.float64):
-            sim = Simulation(vols=self.vol.astype(dtype, copy=False))
+            sim = Simulation(vols=self.vol.astype(dtype, copy=None))
             # Did we assign the right type?
             self.assertTrue(sim.dtype == dtype)
 
diff --git a/tests/test_volume.py b/tests/test_volume.py
index d220860784..74c77c5cc5 100644
--- a/tests/test_volume.py
+++ b/tests/test_volume.py
@@ -163,10 +163,10 @@ def test_astype(vols_1, dtype):
 
 def test_astype_copy(vols_1):
     """
-    `astype(copy=False)` is an optimization partially mimicked from numpy.
+    `astype(copy=None)` is an optimization partially mimicked from numpy.
     """
-    # Same dtype, copy=False
-    v2 = vols_1.astype(vols_1.dtype, copy=False)
+    # Same dtype, copy=None
+    v2 = vols_1.astype(vols_1.dtype, copy=None)
     # Details should match,
     assert isinstance(v2, Volume)
     assert np.allclose(v2.asnumpy(), vols_1.asnumpy())

From 54d7a508cd1dc775f05e7fe86791a96c34a35369 Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 14:19:48 -0400
Subject: [PATCH 05/14] np2 breaks np.sign for complex

---
 src/aspire/utils/matrix.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/aspire/utils/matrix.py b/src/aspire/utils/matrix.py
index bc802f87f8..534c027b30 100644
--- a/src/aspire/utils/matrix.py
+++ b/src/aspire/utils/matrix.py
@@ -493,7 +493,7 @@ def fix_signs(u):
     # Now we only care about the sign +1/-1.
     #  The following corrects for any numerical division noise,
     #  and also remaps 0 to +1.
-    signs = np.sign(signs * 2 + 1)
+    signs = np.sign(signs.real * 2 + 1)
 
     # Apply signs elementwise to matrix
     return u * signs

From 4f13006b5e0ffe2f96958b7f7b5fa64dcf10a1cf Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 15:06:13 -0400
Subject: [PATCH 06/14] np2 multiply xform dtype cast

---
 src/aspire/image/xform.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/aspire/image/xform.py b/src/aspire/image/xform.py
index 0759c819e8..38f65d9bee 100644
--- a/src/aspire/image/xform.py
+++ b/src/aspire/image/xform.py
@@ -144,8 +144,9 @@ def __init__(self, factor):
         self.multipliers = np.array(factor)
 
     def _forward(self, im, indices):
+
         if self.multipliers.size == 1:  # if we have a scalar multiplier
-            im_new = im * self.multipliers
+            im_new = im * self.multipliers.astype(im.dtype)
         else:
             im_new = im * self.multipliers[indices]
 

From 71a5e05449d13fee336778289b9d17bc65940887 Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 15:11:03 -0400
Subject: [PATCH 07/14] sk pca copy False

---
 src/aspire/classification/rir_class2d.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/aspire/classification/rir_class2d.py b/src/aspire/classification/rir_class2d.py
index dde35ef050..19a3479ffe 100644
--- a/src/aspire/classification/rir_class2d.py
+++ b/src/aspire/classification/rir_class2d.py
@@ -390,7 +390,7 @@ def _sk_pca(self, M):
         #   We use an extension of SK that is hacked to admit complex.
         pca = ComplexPCA(
             self.bispectrum_components,
-            copy=None,  # careful, overwrites data matrix... we'll handle the copies.
+            copy=False,  # careful, overwrites data matrix... we'll handle the copies.
             svd_solver="auto",  # use randomized (Halko) for larger problems
             random_state=self.seed,
         )

From c151f9df6a724d06bfc38e97c94ac85eaf0d415c Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 15:11:51 -0400
Subject: [PATCH 08/14] sk pca copy False

---
 tests/test_complexPCA.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_complexPCA.py b/tests/test_complexPCA.py
index 1c224324d7..509b0b84a5 100644
--- a/tests/test_complexPCA.py
+++ b/tests/test_complexPCA.py
@@ -53,7 +53,7 @@ def testLargeFitTransform(self):
         """
 
         pca = ComplexPCA(
-            n_components=self.components_large, copy=None, svd_solver="full"
+            n_components=self.components_large, copy=False, svd_solver="full"
         )
 
         # Input data matrix X should be (n_samples, m_features)

From 680a426d19a248dae5f5bc0600120b43762beba6 Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 15:28:01 -0400
Subject: [PATCH 09/14] another great np2 improvement

---
 src/aspire/image/image.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/aspire/image/image.py b/src/aspire/image/image.py
index 6d0f3b8960..bd9dfa22a1 100644
--- a/src/aspire/image/image.py
+++ b/src/aspire/image/image.py
@@ -72,7 +72,7 @@ def normalize_bg(imgs, bg_radius=1.0, do_ramp=True):
 
     # Apply mask images and calculate mean and std values of background
     imgs_masked = imgs * mask
-    denominator = np.sum(mask)
+    denominator = np.count_nonzero(mask)  # scalar int
     first_moment = np.sum(imgs_masked, axis=(1, 2)) / denominator
     second_moment = np.sum(imgs_masked**2, axis=(1, 2)) / denominator
     mean = first_moment.reshape(-1, 1, 1)

From 3585686cc34e74938cc7335c7022a5834c18feab Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 15:39:22 -0400
Subject: [PATCH 10/14] sqrt(weight) dtype not same as weight

---
 src/aspire/__init__.py                       | 15 +++++++++++++++
 src/aspire/abinitio/commonline_base.py       |  2 +-
 src/aspire/abinitio/commonline_c3_c4.py      |  2 +-
 src/aspire/abinitio/commonline_d2.py         |  4 ++--
 src/aspire/abinitio/commonline_sync3n.py     | 20 ++++++++++----------
 src/aspire/apple/picking.py                  |  4 ++--
 src/aspire/basis/basis.py                    |  2 +-
 src/aspire/basis/fle_2d.py                   |  6 ++++--
 src/aspire/basis/fpswf_2d.py                 |  2 +-
 src/aspire/classification/averager2d.py      |  2 +-
 src/aspire/covariance/covar2d.py             |  2 +-
 src/aspire/ctf/ctf_estimator.py              |  4 ++--
 src/aspire/image/image.py                    |  6 +++---
 src/aspire/nufft/cufinufft.py                |  2 +-
 src/aspire/nufft/finufft.py                  |  4 ++--
 src/aspire/numeric/complex_pca/validation.py | 10 +++++-----
 src/aspire/numeric/pyfftw_fft.py             |  2 +-
 src/aspire/operators/blk_diag_matrix.py      |  4 ++--
 src/aspire/operators/diag_matrix.py          |  2 +-
 src/aspire/reconstruction/estimator.py       |  1 -
 src/aspire/reconstruction/kernel.py          |  4 ++--
 src/aspire/reconstruction/mean.py            | 19 ++++++++++---------
 src/aspire/sinogram/sinogram.py              |  2 +-
 src/aspire/source/micrograph.py              |  2 +-
 src/aspire/utils/bot_align.py                |  8 ++++----
 src/aspire/utils/matrix.py                   |  4 ++--
 src/aspire/utils/misc.py                     |  8 ++++----
 src/aspire/utils/rotation.py                 |  6 +++---
 src/aspire/volume/volume.py                  |  2 +-
 tests/test_FFBbasis3D.py                     |  4 ++--
 tests/test_coef.py                           |  8 ++++----
 tests/test_diag_matrix.py                    |  2 +-
 tests/test_downsample.py                     |  4 ++--
 tests/test_matrix.py                         |  4 ++--
 tests/test_mean_estimator.py                 |  4 ++--
 tests/test_micrograph_source.py              |  2 +-
 tests/test_orient_sdp.py                     |  2 +-
 tests/test_polar_ft.py                       |  2 +-
 tests/test_simulation.py                     |  2 +-
 tests/test_volume.py                         |  6 +++---
 40 files changed, 104 insertions(+), 87 deletions(-)

diff --git a/src/aspire/__init__.py b/src/aspire/__init__.py
index 9c80750c9c..8273099c75 100644
--- a/src/aspire/__init__.py
+++ b/src/aspire/__init__.py
@@ -2,11 +2,14 @@
 import logging.config
 import os
 import pkgutil
+import warnings
 from datetime import datetime
 from pathlib import Path
 
 import confuse
+import numpy as np
 import pooch
+from packaging.version import parse as parse_version
 
 import aspire
 from aspire.exceptions import handle_exception
@@ -84,3 +87,15 @@ def __getattr__(attr):
         return importlib.import_module(f"aspire.{attr}")
     else:
         raise AttributeError(f"module `{__name__}` has no attribute `{attr}`.")
+
+
+if parse_version(np.version.version) >= parse_version("2.0.0"):
+    # ImportWarnings are generally filtered, but raise this one for now.
+    with warnings.catch_warnings():
+        warnings.simplefilter("default")
+        warnings.warn(
+            "ASPIRE's Numpy 2 support is in beta.  If you experience a runtime"
+            "crash relating to mismatched dtypes or a Numpy call please try"
+            ' `pip install "numpy<2"` and report to ASPIRE developers.',
+            ImportWarning,
+        )
diff --git a/src/aspire/abinitio/commonline_base.py b/src/aspire/abinitio/commonline_base.py
index 2cd80b61fa..fe456c645e 100644
--- a/src/aspire/abinitio/commonline_base.py
+++ b/src/aspire/abinitio/commonline_base.py
@@ -149,7 +149,7 @@ def _prepare_pf(self):
             #   Apply mask in doubles (allow imgs to upcast as needed)
             imgs = imgs * fuzz_mask
             #   Cast to desired type
-            imgs = Image(imgs.asnumpy().astype(self.dtype, copy=None))
+            imgs = Image(imgs.asnumpy().astype(self.dtype, copy=False))
 
         # Obtain coefficients of polar Fourier transform for input 2D images
         pft = PolarFT(
diff --git a/src/aspire/abinitio/commonline_c3_c4.py b/src/aspire/abinitio/commonline_c3_c4.py
index bc2956ec0d..242094b745 100644
--- a/src/aspire/abinitio/commonline_c3_c4.py
+++ b/src/aspire/abinitio/commonline_c3_c4.py
@@ -693,7 +693,7 @@ def _J_sync_power_method(self, vijs):
         while itr < max_iters and residual > epsilon:
             itr += 1
             # Note, this appears to need double precision for accuracy in the following division.
-            vec_new = self._signs_times_v(vijs, vec).astype(np.float64, copy=None)
+            vec_new = self._signs_times_v(vijs, vec).astype(np.float64, copy=False)
             vec_new = vec_new / norm(vec_new)
             residual = norm(vec_new - vec)
             vec = vec_new
diff --git a/src/aspire/abinitio/commonline_d2.py b/src/aspire/abinitio/commonline_d2.py
index 93b2e9bc0a..a8e951c642 100644
--- a/src/aspire/abinitio/commonline_d2.py
+++ b/src/aspire/abinitio/commonline_d2.py
@@ -1149,12 +1149,12 @@ def _sync_colors(self, Rijs):
 
         # Seed eigs initial vector for iterative method.
         # scipy LinearOperator needs doubles for some architectures (arm).
-        v0 = randn(3 * n_pairs, seed=self.seed).astype(np.float64, copy=None)
+        v0 = randn(3 * n_pairs, seed=self.seed).astype(np.float64, copy=False)
 
         v0 = v0 / norm(v0)
         vals, colors = la.eigs(color_mat, k=3, which="LR", v0=v0)
         vals = np.real(vals)
-        colors = np.real(colors).astype(self.dtype, copy=None)
+        colors = np.real(colors).astype(self.dtype, copy=False)
         colors = np.sign(colors[0]) * colors  # Stable eigs
         cp, _ = self._unmix_colors(colors[:, :2])
 
diff --git a/src/aspire/abinitio/commonline_sync3n.py b/src/aspire/abinitio/commonline_sync3n.py
index aa11a2348a..a0db2263ec 100644
--- a/src/aspire/abinitio/commonline_sync3n.py
+++ b/src/aspire/abinitio/commonline_sync3n.py
@@ -197,7 +197,7 @@ def _sync3n_S_to_rot(self, S, W=None, n_eigs=4):
         """
 
         # Critical this occurs in double precision
-        S = S.astype(np.float64, copy=None)
+        S = S.astype(np.float64, copy=False)
 
         if n_eigs < 3:
             raise ValueError(
@@ -213,7 +213,7 @@ def _sync3n_S_to_rot(self, S, W=None, n_eigs=4):
                 )
             # Initialize D
             # Critical this occurs in double precision
-            W = W.astype(np.float64, copy=None)
+            W = W.astype(np.float64, copy=False)
             D = np.mean(W, axis=1)
 
             Dhalf = D
@@ -266,7 +266,7 @@ def _sync3n_S_to_rot(self, S, W=None, n_eigs=4):
         # Enforce we are returning actual rotations
         rotations = nearest_rotations(rotations, allow_reflection=True)
 
-        return rotations.astype(self.dtype)
+        return rotations.astype(self.dtype, copy=False)
 
     def _construct_sync3n_matrix(self, Rij):
         """
@@ -664,8 +664,8 @@ def _pairs_probabilities_cupy(self, Rijs, P2, A, a, B, b, x0):
         )
 
         # accumulate over thread results
-        ln_f_arb = ln_f_arb_dev.get().astype(self.dtype, copy=None)
-        ln_f_ind = ln_f_ind_dev.get().astype(self.dtype, copy=None)
+        ln_f_arb = ln_f_arb_dev.get().astype(self.dtype, copy=False)
+        ln_f_ind = ln_f_ind_dev.get().astype(self.dtype, copy=False)
 
         return ln_f_ind, ln_f_arb
 
@@ -748,8 +748,8 @@ def fun(x, B, P, b, x0, A=A, a=a):
 
         popt, pcov = curve_fit(
             fun,
-            hist_x.astype(np.float64, copy=None),
-            scores_hist.astype(np.float64, copy=None),
+            hist_x.astype(np.float64, copy=False),
+            scores_hist.astype(np.float64, copy=False),
             p0=start_values,
             bounds=(lower_bounds, upper_bounds),
             method="trf",  # MATLAB used method "LAR" with algo "Trust-Region"
@@ -1043,7 +1043,7 @@ def _J_sync_power_method(self, Rijs):
         while itr < max_iters and residual > epsilon:
             itr += 1
             # Todo, this code code actually needs double precision for accuracy... forcing.
-            vec_new = self._signs_times_v(Rijs, vec).astype(np.float64, copy=None)
+            vec_new = self._signs_times_v(Rijs, vec).astype(np.float64, copy=False)
             vec_new = vec_new / norm(vec_new)
             residual = norm(vec_new - vec)
             vec = vec_new
@@ -1073,7 +1073,7 @@ def _signs_times_v(self, Rijs, vec):
         else:
             new_vec = self._signs_times_v_host(Rijs, vec)
 
-        return new_vec.astype(vec.dtype, copy=None)
+        return new_vec.astype(vec.dtype, copy=False)
 
     def _signs_times_v_host(self, Rijs, vec):
         """
@@ -1177,7 +1177,7 @@ def _signs_times_v_cupy(self, Rijs, vec):
         )
 
         # dtoh
-        new_vec = new_vec_dev.get().astype(vec.dtype, copy=None)
+        new_vec = new_vec_dev.get().astype(vec.dtype, copy=False)
 
         return new_vec
 
diff --git a/src/aspire/apple/picking.py b/src/aspire/apple/picking.py
index d54cf61f1d..d64d16c773 100644
--- a/src/aspire/apple/picking.py
+++ b/src/aspire/apple/picking.py
@@ -149,7 +149,7 @@ def read_micrograph(self):
         self.original_im = (
             DiskMicrographSource(self.filename)
             .asnumpy()[0]
-            .astype(np.float32, copy=None)
+            .astype(np.float32, copy=False)
         )
 
         # Discard outer pixels
@@ -167,7 +167,7 @@ def read_micrograph(self):
         # Note, float64 required for signal.correlate call accuracy.
         im = np.asarray(
             PILImage.fromarray(im).resize(size, PILImage.Resampling.BICUBIC)
-        ).astype(np.float64, copy=None)
+        ).astype(np.float64, copy=False)
 
         im = signal.correlate(
             im,
diff --git a/src/aspire/basis/basis.py b/src/aspire/basis/basis.py
index 6baf16f769..ee6aee2d02 100644
--- a/src/aspire/basis/basis.py
+++ b/src/aspire/basis/basis.py
@@ -62,7 +62,7 @@ def __init__(self, basis, data, dtype=None):
             )
         self.basis = basis
 
-        self._data = data.astype(self.dtype, copy=None)
+        self._data = data.astype(self.dtype, copy=False)
         self.ndim = self._data.ndim
         self.shape = self._data.shape
         self.stack_ndim = self._data.ndim - 1
diff --git a/src/aspire/basis/fle_2d.py b/src/aspire/basis/fle_2d.py
index 6499919110..fc22352c18 100644
--- a/src/aspire/basis/fle_2d.py
+++ b/src/aspire/basis/fle_2d.py
@@ -643,7 +643,7 @@ def _step1(self, z):
         num_img = z.shape[0]
         z = z[:, :, : self.num_angular_nodes // 2].reshape(num_img, -1)
         im = anufft(
-            z.astype(complex_type(self.dtype), copy=None),
+            z.astype(complex_type(self.dtype), copy=False),
             self.grid_xy,
             (self.nres, self.nres),
             epsilon=self.epsilon,
@@ -798,7 +798,9 @@ def filter_to_basis_mat(self, f, **kwargs):
         omega = 2 * xp.pi * xp.vstack((omegax.flatten("C"), omegay.flatten("C")))
 
         h_vals2d = (
-            xp.asarray(h_fun(omega)).reshape(n_k, n_theta).astype(self.dtype, copy=None)
+            xp.asarray(h_fun(omega))
+            .reshape(n_k, n_theta)
+            .astype(self.dtype, copy=False)
         )
         h_vals = xp.sum(h_vals2d, axis=1) / n_theta
 
diff --git a/src/aspire/basis/fpswf_2d.py b/src/aspire/basis/fpswf_2d.py
index aa7b9913d9..6eac1a91db 100644
--- a/src/aspire/basis/fpswf_2d.py
+++ b/src/aspire/basis/fpswf_2d.py
@@ -99,7 +99,7 @@ def _precomp(self):
         ) = self._pswf_integration_sub_routine()
 
         self.us_fft_pts = us_fft_pts.astype(
-            self.dtype, copy=None
+            self.dtype, copy=False
         )  # TODO, debug where this is incorrect dtype
         self.blk_r = blk_r
         self.num_angular_pts = num_angular_pts
diff --git a/src/aspire/classification/averager2d.py b/src/aspire/classification/averager2d.py
index 644359c9e7..b447a6d91c 100644
--- a/src/aspire/classification/averager2d.py
+++ b/src/aspire/classification/averager2d.py
@@ -82,7 +82,7 @@ def _cls_images(self, cls, src=None):
             source for a certain operation (ie alignment).
         """
         src = src or self.src
-        return src.images[cls].asnumpy().astype(self.dtype, copy=None)
+        return src.images[cls].asnumpy().astype(self.dtype, copy=False)
 
 
 class AligningAverager2D(Averager2D):
diff --git a/src/aspire/covariance/covar2d.py b/src/aspire/covariance/covar2d.py
index a4f1971b78..d2e7dafe43 100644
--- a/src/aspire/covariance/covar2d.py
+++ b/src/aspire/covariance/covar2d.py
@@ -607,7 +607,7 @@ def _calc_op(self):
             ctf_basis_k_sq = ctf_basis_k_t @ ctf_basis_k
             A_mean_k = weight * ctf_basis_k_sq
             A_mean += A_mean_k
-            A_covar_k = np.sqrt(weight) * ctf_basis_k_sq
+            A_covar_k = np.sqrt(weight).astype(self.dtype) * ctf_basis_k_sq
             A_covar[k] = A_covar_k
 
             M_covar += A_covar_k
diff --git a/src/aspire/ctf/ctf_estimator.py b/src/aspire/ctf/ctf_estimator.py
index 39f2998a21..b6983cb071 100644
--- a/src/aspire/ctf/ctf_estimator.py
+++ b/src/aspire/ctf/ctf_estimator.py
@@ -241,7 +241,7 @@ def estimate_psd(self, blocks, tapers_1d):
         """
 
         num_1d_tapers = tapers_1d.shape[-1]
-        tapers_1d = tapers_1d.astype(complex_type(self.dtype), copy=None)
+        tapers_1d = tapers_1d.astype(complex_type(self.dtype), copy=False)
 
         blocks_mt = np.zeros(blocks[0, :, :].shape, dtype=self.dtype)
 
@@ -768,7 +768,7 @@ def estimate_ctf(
             micrograph = mrc.data
 
         # Try to match dtype used in Basis instance
-        micrograph = micrograph.astype(dtype, copy=None)
+        micrograph = micrograph.astype(dtype, copy=False)
 
         micrograph_blocks = ctf_object.preprocess_micrograph(micrograph, psd_size)
 
diff --git a/src/aspire/image/image.py b/src/aspire/image/image.py
index bd9dfa22a1..1e980e88dd 100644
--- a/src/aspire/image/image.py
+++ b/src/aspire/image/image.py
@@ -195,7 +195,7 @@ def __init__(self, data, pixel_size=None, dtype=None):
         if not data.shape[-1] == data.shape[-2]:
             raise ValueError("Only square ndarrays are supported.")
 
-        self._data = data.astype(self.dtype, copy=None)
+        self._data = data.astype(self.dtype, copy=False)
         self.ndim = self._data.ndim
         self.shape = self._data.shape
         self.stack_ndim = self._data.ndim - 2
@@ -543,7 +543,7 @@ def load(filepath, dtype=None):
 
         # Attempt casting when user provides dtype
         if dtype is not None:
-            im = im.astype(dtype, copy=None)
+            im = im.astype(dtype, copy=False)
 
         # Return as Image instance
         return Image(im, pixel_size=pixel_size)
@@ -658,7 +658,7 @@ def backproject(self, rot_matrices, symmetry_group=None, zero_nyquist=True):
 
             # TODO: rotated_grids might as well give us correctly shaped array in the first place
             pts_rot = aspire.volume.rotated_grids(L, rotations).astype(
-                self.dtype, copy=None
+                self.dtype, copy=False
             )
             pts_rot = pts_rot.reshape((3, -1))
 
diff --git a/src/aspire/nufft/cufinufft.py b/src/aspire/nufft/cufinufft.py
index 2660f4ea46..fd869aacfd 100644
--- a/src/aspire/nufft/cufinufft.py
+++ b/src/aspire/nufft/cufinufft.py
@@ -30,7 +30,7 @@ def __init__(self, sz, fourier_pts, epsilon=1e-8, ntransforms=1, **kwargs):
         # ASPIRE-Python/703
         # Cast to doubles.
         self._original_dtype = fourier_pts.dtype
-        fourier_pts = fourier_pts.astype(np.float64, copy=None)
+        fourier_pts = fourier_pts.astype(np.float64, copy=False)
 
         # Basic dtype passthough.
         dtype = fourier_pts.dtype
diff --git a/src/aspire/nufft/finufft.py b/src/aspire/nufft/finufft.py
index e396d76124..a955ab20d0 100644
--- a/src/aspire/nufft/finufft.py
+++ b/src/aspire/nufft/finufft.py
@@ -99,7 +99,7 @@ def transform(self, signal):
         ), f"Signal frame to be transformed must have shape {self.sz}"
 
         # FINUFFT was designed for a complex input array
-        signal = np.array(signal, copy=None, dtype=self.complex_dtype, order="C")
+        signal = np.asarray(signal, dtype=self.complex_dtype, order="C")
 
         result = self._transform_plan.execute(signal)
 
@@ -130,7 +130,7 @@ def adjoint(self, signal):
                 signal = signal.reshape(self.num_pts)
 
         # FINUFFT was designed for a complex input array
-        signal = np.array(signal, copy=None, dtype=self.complex_dtype, order="C")
+        signal = np.asarray(signal, dtype=self.complex_dtype, order="C")
 
         result = self._adjoint_plan.execute(signal)
 
diff --git a/src/aspire/numeric/complex_pca/validation.py b/src/aspire/numeric/complex_pca/validation.py
index 11d7aaba9f..7fafedfe18 100644
--- a/src/aspire/numeric/complex_pca/validation.py
+++ b/src/aspire/numeric/complex_pca/validation.py
@@ -81,7 +81,7 @@ def _ensure_sparse_format(
         Data type of result. If None, the dtype of the input is preserved.
 
     copy : boolean
-        Whether a forced copy will be triggered. If copy=None, a copy might
+        Whether a forced copy will be triggered. If copy=False, a copy might
         be triggered by a conversion.
 
     force_all_finite : boolean or 'allow-nan', (default=True)
@@ -173,7 +173,7 @@ def check_array(
     accept_large_sparse=True,
     dtype="numeric",
     order=None,
-    copy=None,
+    copy=False,
     force_all_finite=True,
     ensure_2d=True,
     allow_nd=False,
@@ -216,13 +216,13 @@ def check_array(
 
     order : 'F', 'C' or None (default=None)
         Whether an array will be forced to be fortran or c-style.
-        When order is None (default), then if copy=None, nothing is ensured
+        When order is None (default), then if copy=False, nothing is ensured
         about the memory layout of the output array; otherwise (copy=True)
         the memory layout of the returned array is kept as close as possible
         to the original array.
 
     copy : boolean (default=False)
-        Whether a forced copy will be triggered. If copy=None, a copy might
+        Whether a forced copy will be triggered. If copy=False, a copy might
         be triggered by a conversion.
 
     force_all_finite : boolean or 'allow-nan', (default=True)
@@ -365,7 +365,7 @@ def check_array(
                     array = np.asarray(array, order=order)
                     if array.dtype.kind == "f":
                         _assert_all_finite(array, allow_nan=False, msg_dtype=dtype)
-                    array = array.astype(dtype, casting="unsafe", copy=None)
+                    array = array.astype(dtype, casting="unsafe", copy=False)
                 else:
                     array = np.asarray(array, order=order, dtype=dtype)
             except ComplexWarning:
diff --git a/src/aspire/numeric/pyfftw_fft.py b/src/aspire/numeric/pyfftw_fft.py
index 4503b42b38..95a8ea80f7 100644
--- a/src/aspire/numeric/pyfftw_fft.py
+++ b/src/aspire/numeric/pyfftw_fft.py
@@ -139,7 +139,7 @@ def ifftn(self, a, axes=None, workers=-1):
         # FFTW_BACKWARD requires complex input array, cast as needed.
         # See https://pyfftw.readthedocs.io/en/latest/source/pyfftw/pyfftw.html#scheme-table
         comp_type = complex_type(a.dtype)
-        a = a.astype(comp_type, copy=None)
+        a = a.astype(comp_type, copy=False)
 
         mutex.acquire()
         try:
diff --git a/src/aspire/operators/blk_diag_matrix.py b/src/aspire/operators/blk_diag_matrix.py
index af882ecc68..3e493f9525 100644
--- a/src/aspire/operators/blk_diag_matrix.py
+++ b/src/aspire/operators/blk_diag_matrix.py
@@ -91,7 +91,7 @@ def append(self, blk):
         :param blk: Block to append (ndarray).
         """
 
-        self.data.append(blk.astype(self.dtype, copy=None))
+        self.data.append(blk.astype(self.dtype, copy=False))
         self.nblocks += 1
         self.reset_cache()
 
@@ -130,7 +130,7 @@ def __setitem__(self, key, value):
         Convenience wrapper, setter on self.data.
         """
 
-        self.data[key] = value.astype(self.dtype, copy=None)
+        self.data[key] = value.astype(self.dtype, copy=False)
         self.reset_cache()
 
     def __len__(self):
diff --git a/src/aspire/operators/diag_matrix.py b/src/aspire/operators/diag_matrix.py
index 68d6a728ae..4c94ab83d1 100644
--- a/src/aspire/operators/diag_matrix.py
+++ b/src/aspire/operators/diag_matrix.py
@@ -45,7 +45,7 @@ def __init__(self, data, dtype=None):
         self.dtype = np.dtype(dtype)
 
         # Assign the `data`
-        self._data = data.astype(self.dtype, copy=None)
+        self._data = data.astype(self.dtype, copy=False)
 
         # Assign shapes from `data`
         self.count = self._data.shape[-1]
diff --git a/src/aspire/reconstruction/estimator.py b/src/aspire/reconstruction/estimator.py
index 2bf0ec3366..ac5e9caeca 100644
--- a/src/aspire/reconstruction/estimator.py
+++ b/src/aspire/reconstruction/estimator.py
@@ -159,7 +159,6 @@ def apply_kernel(self, vol_coef, kernel=None):
 
         if kernel is None:
             kernel = self.kernel
-
         vol = Coef(self.basis, vol_coef).evaluate()  # returns a Volume
         vol = kernel.convolve_volume(vol)  # returns a Volume
         vol_coef = self.basis.evaluate_t(vol)
diff --git a/src/aspire/reconstruction/kernel.py b/src/aspire/reconstruction/kernel.py
index 84d4e61409..9a86a244f2 100644
--- a/src/aspire/reconstruction/kernel.py
+++ b/src/aspire/reconstruction/kernel.py
@@ -32,7 +32,7 @@ def __add__(self, delta):
             to be able to use it within optimization loops. This operator allows one to use the FourierKernel object
             with the underlying 'kernel' attribute tweaked with a regularization parameter.
         """
-        new_kernel = self.kernel + delta
+        new_kernel = self.kernel + float(delta)
         return FourierKernel(new_kernel)
 
     def circularize(self):
@@ -191,7 +191,7 @@ def __add__(self, delta):
 
     def circularize(self):
         _L = self.M // 2
-        xx = np.empty((self.r, self.r, _L, _L, _L))
+        xx = np.empty((self.r, self.r, _L, _L, _L), self.dtype)
         for k in range(self.r):
             for j in range(self.r):
                 xx[k, j] = FourierKernel(self.kermat[k, j]).circularize().real
diff --git a/src/aspire/reconstruction/mean.py b/src/aspire/reconstruction/mean.py
index 56f0624e8d..b380c8788c 100644
--- a/src/aspire/reconstruction/mean.py
+++ b/src/aspire/reconstruction/mean.py
@@ -5,10 +5,9 @@
 from scipy.linalg import norm
 from scipy.sparse.linalg import LinearOperator
 
-from aspire import config
 from aspire.basis import Coef
 from aspire.nufft import anufft
-from aspire.numeric import fft
+from aspire.numeric import config, fft
 from aspire.numeric.scipy import cg
 from aspire.operators import evaluate_src_filters_on_grid
 from aspire.reconstruction import Estimator, FourierKernel, FourierKernelMatrix
@@ -102,7 +101,7 @@ def _compute_kernel(self):
             _range = np.arange(i, min(self.src.n, i + self.batch_size), dtype=int)
             sq_filters_f = evaluate_src_filters_on_grid(self.src, _range) ** 2
             amplitudes_sq = (self.src.amplitudes[_range] ** 2).astype(
-                self.dtype, copy=None
+                self.dtype, copy=False
             )
 
             for k in range(self.r):
@@ -139,7 +138,7 @@ def _compute_kernel(self):
                     if j != k:
                         kernel[j, k] += batch_kernel
 
-        kermat_f = np.zeros((self.r, self.r, _2L, _2L, _2L))
+        kermat_f = np.zeros((self.r, self.r, _2L, _2L, _2L), dtype=self.dtype)
         logger.info("Computing non-centered Fourier Transform Kernel Mat")
         for k in range(self.r):
             for j in range(self.r):
@@ -184,10 +183,12 @@ def src_backward(self):
                     i,
                     self.weights[:, k],
                     symmetry_group=symmetry_group,
-                ) / (self.src.n * sym_order)
+                ) / float(self.src.n * sym_order)
                 vol_rhs[k] += batch_vol_rhs.astype(self.dtype)
 
-        res = np.sqrt(self.src.n * sym_order) * self.basis.evaluate_t(vol_rhs)
+        res = np.sqrt(self.src.n * sym_order, dtype=self.dtype) * self.basis.evaluate_t(
+            vol_rhs
+        )
         logger.info(f"Determined weighted adjoint mappings. Shape = {res.shape}")
 
         return res
@@ -210,6 +211,7 @@ def conj_grad(self, b_coef, x0=None, tol=1e-5, regularizer=0):
             precond_kernel = self.precond_kernel
             if regularizer > 0:
                 precond_kernel += regularizer
+
             M = LinearOperator(
                 (self.r * count, self.r * count),
                 matvec=partial(self.apply_kernel, kernel=precond_kernel),
@@ -262,7 +264,7 @@ def cb(xk):
                 f"Conjugate gradient unable to converge after {info} iterations."
             )
 
-        return x.reshape(self.r, self.basis.count)
+        return x.reshape(self.r, self.basis.count).astype(self.dtype, copy=False)
 
     def apply_kernel(self, vol_coef, kernel=None):
         """
@@ -283,8 +285,7 @@ def apply_kernel(self, vol_coef, kernel=None):
         vols_out = Volume(
             np.zeros((self.r, self.src.L, self.src.L, self.src.L), dtype=self.dtype)
         )
-
-        vol = Coef(self.basis, vol_coef).evaluate()
+        vol = Coef(self.basis, vol_coef.astype(self.dtype, copy=False)).evaluate()
 
         for k in range(self.r):
             for j in range(self.r):
diff --git a/src/aspire/sinogram/sinogram.py b/src/aspire/sinogram/sinogram.py
index 0f82b0c479..7c7bb43662 100644
--- a/src/aspire/sinogram/sinogram.py
+++ b/src/aspire/sinogram/sinogram.py
@@ -37,7 +37,7 @@ def __init__(self, data, dtype=None):
                 f"Invalid data shape: {data.shape}. Expected shape: (..., angles, radial_points), where '...' is the stack number."
             )
 
-        self._data = data.astype(self.dtype, copy=None)
+        self._data = data.astype(self.dtype, copy=False)
         self.ndim = self._data.ndim
         self.shape = self._data.shape
         self.stack_shape = self._data.shape[:-2]
diff --git a/src/aspire/source/micrograph.py b/src/aspire/source/micrograph.py
index 86b161d822..5aa35e389c 100644
--- a/src/aspire/source/micrograph.py
+++ b/src/aspire/source/micrograph.py
@@ -155,7 +155,7 @@ def __init__(self, micrographs, dtype=None, pixel_size=None):
         )
 
         # We're already backed by an array, access it directly.
-        self._data = micrographs.astype(self.dtype, copy=None)
+        self._data = micrographs.astype(self.dtype, copy=False)
 
     def _images(self, indices):
         """
diff --git a/src/aspire/utils/bot_align.py b/src/aspire/utils/bot_align.py
index e94888d92e..fc8fbe4fdc 100644
--- a/src/aspire/utils/bot_align.py
+++ b/src/aspire/utils/bot_align.py
@@ -139,7 +139,7 @@ def cost(new, t=t, q=q):
             Loss function for surrogate problems.
             """
             kx = np.array(
-                [cov_fun(new.astype(dtype, copy=None), R[j]) for j in range(t)]
+                [cov_fun(new.astype(dtype, copy=False), R[j]) for j in range(t)]
             )
             mu = kx @ q
             return mu
@@ -151,7 +151,7 @@ def euclidean_grad(new, t=t, q=q):
             """
             # Corresponds to equation 11 in the paper.
             kx_grad = np.array(
-                [cov_fun_grad(new.astype(dtype, copy=None), R[j]) for j in range(t)]
+                [cov_fun_grad(new.astype(dtype, copy=False), R[j]) for j in range(t)]
             )
 
             kx_grad = kx_grad.reshape((t, 9))
@@ -168,7 +168,7 @@ def euclidean_grad(new, t=t, q=q):
             verbosity=verbosity,
         )
         result = optimizer.run(problem)
-        R_new = result.point.astype(dtype, copy=None)
+        R_new = result.point.astype(dtype, copy=False)
 
         loss[t] = loss_fun(R_new)
         R[t] = R_new
@@ -190,7 +190,7 @@ def loss_u(u):
             """
             Convert the alignment loss function over SO(3) to be over R^3.
             """
-            u = u.astype(dtype, copy=None)
+            u = u.astype(dtype, copy=False)
             R = sign * Rotation.from_rotvec(u).matrices[0]
             v_rot = vol_given_ds.rotate(Rotation(R)).asnumpy()[0]
             return norm(vol_ref_ds - v_rot)
diff --git a/src/aspire/utils/matrix.py b/src/aspire/utils/matrix.py
index 534c027b30..f33aa47b23 100644
--- a/src/aspire/utils/matrix.py
+++ b/src/aspire/utils/matrix.py
@@ -1,5 +1,5 @@
 """
-Utilties for arrays/n-dimensional matrices.
+Utilities for arrays/n-dimensional matrices.
 """
 
 import numpy as np
@@ -462,7 +462,7 @@ def nearest_rotations(A, allow_reflection=False):
         # If det(U)*det(V) = -1, we negate the third singular value to
         # ensure we have a rotation.
         neg_det_idx = np.linalg.det(U) * np.linalg.det(V) < 0
-        U[neg_det_idx] = U[neg_det_idx] @ np.diag((1, 1, -1)).astype(dtype, copy=None)
+        U[neg_det_idx] = U[neg_det_idx] @ np.diag((1, 1, -1)).astype(dtype, copy=False)
 
     rots = U @ V
 
diff --git a/src/aspire/utils/misc.py b/src/aspire/utils/misc.py
index 087454de5e..5485c42788 100644
--- a/src/aspire/utils/misc.py
+++ b/src/aspire/utils/misc.py
@@ -1,5 +1,5 @@
 """
-Miscellaneous Utilities that have no better place (yet).
+Miscellaneous utilities that have no better place (yet).
 """
 
 import hashlib
@@ -135,7 +135,7 @@ def gaussian_1d(size, mu=0, sigma=1, dtype=np.float64):
 
     p = (g["x"] - mu) ** 2 / (2 * sigma**2)
 
-    return np.exp(-p).astype(dtype, copy=None)
+    return np.exp(-p).astype(dtype, copy=False)
 
 
 def gaussian_2d(size, mu=(0, 0), sigma=(1, 1), indexing="yx", dtype=np.float64):
@@ -180,7 +180,7 @@ def gaussian_2d(size, mu=(0, 0), sigma=(1, 1), indexing="yx", dtype=np.float64):
         2 * sigma[1] ** 2
     )
 
-    return np.exp(-p).astype(dtype, copy=None)
+    return np.exp(-p).astype(dtype, copy=False)
 
 
 def gaussian_3d(size, mu=(0, 0, 0), sigma=(1, 1, 1), indexing="zyx", dtype=np.float64):
@@ -228,7 +228,7 @@ def gaussian_3d(size, mu=(0, 0, 0), sigma=(1, 1, 1), indexing="zyx", dtype=np.fl
         + (g["z"] - mu[2]) ** 2 / (2 * sigma[2] ** 2)
     )
 
-    return np.exp(-p).astype(dtype, copy=None)
+    return np.exp(-p).astype(dtype, copy=False)
 
 
 def bump_3d(size, spread=1, dtype=np.float64):
diff --git a/src/aspire/utils/rotation.py b/src/aspire/utils/rotation.py
index fb643914bf..07a31df9df 100644
--- a/src/aspire/utils/rotation.py
+++ b/src/aspire/utils/rotation.py
@@ -256,7 +256,7 @@ def from_euler(values, dtype=None):
         """
         dtype = dtype or getattr(values, "dtype", np.float32)
         rotations = sp_rot.from_euler("ZYZ", values, degrees=False)
-        matrices = rotations.as_matrix().astype(dtype, copy=None)
+        matrices = rotations.as_matrix().astype(dtype, copy=False)
         return Rotation(matrices)
 
     @staticmethod
@@ -324,7 +324,7 @@ def from_rotvec(vec, dtype=None):
         """
         dtype = dtype or vec.dtype
         rots = sp_rot.from_rotvec(vec)
-        matrices = rots.as_matrix().astype(dtype, copy=None)
+        matrices = rots.as_matrix().astype(dtype, copy=False)
         return Rotation(matrices)
 
     @staticmethod
@@ -337,7 +337,7 @@ def from_matrix(values, dtype=None):
         :return: new Rotation object
         """
         dtype = dtype or values.dtype
-        return Rotation(values.astype(dtype, copy=None))
+        return Rotation(values.astype(dtype, copy=False))
 
     @staticmethod
     def generate_random_rotations(
diff --git a/src/aspire/volume/volume.py b/src/aspire/volume/volume.py
index 1954a1cbd5..eae985a794 100644
--- a/src/aspire/volume/volume.py
+++ b/src/aspire/volume/volume.py
@@ -105,7 +105,7 @@ def __init__(self, data, dtype=None, pixel_size=None, symmetry_group=None):
         if not (data.shape[-1] == data.shape[-2] == data.shape[-3]):
             raise ValueError("Only cubed ndarrays are supported.")
 
-        self._data = data.astype(self.dtype, copy=None)
+        self._data = data.astype(self.dtype, copy=False)
         self.ndim = self._data.ndim
         self.shape = self._data.shape
         self.stack_ndim = self._data.ndim - 3
diff --git a/tests/test_FFBbasis3D.py b/tests/test_FFBbasis3D.py
index 3992f5d374..03bdfdd21b 100644
--- a/tests/test_FFBbasis3D.py
+++ b/tests/test_FFBbasis3D.py
@@ -470,7 +470,7 @@ def testFFBBasis3DEvaluate(self, basis):
 
     def testFFBBasis3DEvaluate_t(self, basis):
         x = np.load(os.path.join(DATA_DIR, "ffbbasis3d_xcoef_in_8_8_8.npy")).T  # RCOPT
-        x = x.astype(basis.dtype, copy=None)
+        x = x.astype(basis.dtype, copy=False)
         result = basis.evaluate_t(Volume(x))
 
         ref = np.load(os.path.join(DATA_DIR, "ffbbasis3d_vcoef_out_8_8_8.npy"))[..., 0]
@@ -479,7 +479,7 @@ def testFFBBasis3DEvaluate_t(self, basis):
 
     def testFFBBasis3DExpand(self, basis):
         x = np.load(os.path.join(DATA_DIR, "ffbbasis3d_xcoef_in_8_8_8.npy")).T  # RCOPT
-        x = x.astype(basis.dtype, copy=None)
+        x = x.astype(basis.dtype, copy=False)
         result = basis.expand(x)
 
         ref = np.load(os.path.join(DATA_DIR, "ffbbasis3d_vcoef_out_exp_8_8_8.npy"))[
diff --git a/tests/test_coef.py b/tests/test_coef.py
index 2a283d16e4..3ace0ddec5 100644
--- a/tests/test_coef.py
+++ b/tests/test_coef.py
@@ -90,7 +90,7 @@ def coef_fixture(basis, stack, dtype):
     # shape.
     size = stack + (basis.count,)
 
-    coef_np = np.random.random(size=size).astype(dtype, copy=None)
+    coef_np = np.random.random(size=size).astype(dtype, copy=False)
 
     return Coef(basis, coef_np, dtype=dtype)
 
@@ -212,7 +212,7 @@ def test_add(basis, coef_fixture):
     Tests addition operation against pure Numpy.
     """
     # Make array
-    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=None)
+    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=False)
     # Construct Coef
     c = Coef(basis, x)
 
@@ -231,7 +231,7 @@ def test_sub(basis, coef_fixture):
     Tests subtraction operation against pure Numpy.
     """
     # Make array
-    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=None)
+    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=False)
     # Construct Coef
     c = Coef(basis, x)
 
@@ -264,7 +264,7 @@ def test_mul(basis, coef_fixture):
     Tests multiplication operation against pure Numpy.
     """
     # Make array
-    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=None)
+    x = np.random.random(size=coef_fixture.shape).astype(coef_fixture.dtype, copy=False)
     # Construct Coef
     c = Coef(basis, x)
 
diff --git a/tests/test_diag_matrix.py b/tests/test_diag_matrix.py
index 30f2b76faa..05805912c9 100644
--- a/tests/test_diag_matrix.py
+++ b/tests/test_diag_matrix.py
@@ -65,7 +65,7 @@ def diag_matrix_fixture(stack, matrix_size, dtype):
     """
     shape = (2,) + stack + (matrix_size,)
     # Internally convert dtype.  Passthrough will be checked explicitly in `test_dtype_passthrough` and `test_dtype_cast`
-    d_np = np.random.random(shape).astype(dtype, copy=None)
+    d_np = np.random.random(shape).astype(dtype, copy=False)
     d1 = DiagMatrix(d_np[0])
     d2 = DiagMatrix(d_np[1])
 
diff --git a/tests/test_downsample.py b/tests/test_downsample.py
index 1af37d7281..6c1cac82dd 100644
--- a/tests/test_downsample.py
+++ b/tests/test_downsample.py
@@ -148,7 +148,7 @@ def emdb_vol():
 
 @pytest.fixture(scope="module")
 def volume(emdb_vol, res, dtype):
-    vol = emdb_vol.astype(dtype, copy=None)
+    vol = emdb_vol.astype(dtype, copy=False)
     vol = vol.downsample(res)
     return vol
 
@@ -266,7 +266,7 @@ def test_pixel_size():
     dsL = 5  # downsampled
 
     # Construct a small test Image
-    img = Image(np.random.random((1, L, L)).astype(DTYPE, copy=None), pixel_size=1.23)
+    img = Image(np.random.random((1, L, L)).astype(DTYPE, copy=False), pixel_size=1.23)
 
     # Downsample the image
     result = img.downsample(dsL)
diff --git a/tests/test_matrix.py b/tests/test_matrix.py
index be6829d3fa..728200b9b3 100644
--- a/tests/test_matrix.py
+++ b/tests/test_matrix.py
@@ -356,7 +356,7 @@ def test_nearest_rotations(dtype):
     rots = Rotation.generate_random_rotations(n_rots, seed=0, dtype=dtype).matrices
 
     # Add some noise to the rotations.
-    noise = 1e-3 * randn(n_rots * 9, seed=0).astype(dtype, copy=None).reshape(
+    noise = 1e-3 * randn(n_rots * 9, seed=0).astype(dtype, copy=False).reshape(
         n_rots, 3, 3
     )
     noisy_rots = rots + noise
@@ -381,7 +381,7 @@ def test_nearest_rotations_reflection(dtype):
 
     # Add a reflection and some noise to the rotation.
     refl = rot @ np.diag((1, -1, 1)).astype(dtype)
-    noise = 1e-3 * randn(9, seed=0).astype(dtype, copy=None).reshape(3, 3)
+    noise = 1e-3 * randn(9, seed=0).astype(dtype, copy=False).reshape(3, 3)
     noisy_refl = refl + noise
 
     # Find nearest rotation.
diff --git a/tests/test_mean_estimator.py b/tests/test_mean_estimator.py
index 3e7f915193..e6b2a2f837 100644
--- a/tests/test_mean_estimator.py
+++ b/tests/test_mean_estimator.py
@@ -115,8 +115,8 @@ def test_adjoint(sim, basis, estimator):
     L = sim.L
     n = sim.n
 
-    u = np.random.rand(n, L, L).astype(sim.dtype, copy=None)
-    v = np.random.rand(L, L, L).astype(sim.dtype, copy=None)
+    u = np.random.rand(n, L, L).astype(sim.dtype, copy=False)
+    v = np.random.rand(L, L, L).astype(sim.dtype, copy=False)
 
     proj = Volume(v).project(rots)
     backproj = Image(u).backproject(rots)
diff --git a/tests/test_micrograph_source.py b/tests/test_micrograph_source.py
index c44e703cbb..d4793cf61f 100644
--- a/tests/test_micrograph_source.py
+++ b/tests/test_micrograph_source.py
@@ -56,7 +56,7 @@ def image_data_fixture(micrograph_count, micrograph_size, dtype):
     This generates a Numpy array with prescribed shape and dtype.
     """
     img_np = np.random.rand(micrograph_count, micrograph_size, micrograph_size)
-    return img_np.astype(dtype, copy=None)
+    return img_np.astype(dtype, copy=False)
 
 
 # =====
diff --git a/tests/test_orient_sdp.py b/tests/test_orient_sdp.py
index aa215d1766..22658ee06a 100644
--- a/tests/test_orient_sdp.py
+++ b/tests/test_orient_sdp.py
@@ -152,7 +152,7 @@ def test_ATA_solver():
     rots = Rotation.generate_random_rotations(n=n_rots, seed=seed, dtype=dtype).matrices
 
     # Create a simple reference linear transformation A that is rank-3.
-    A_ref = np.diag([1, 2, 3]).astype(dtype, copy=None)
+    A_ref = np.diag([1, 2, 3]).astype(dtype, copy=False)
 
     # Create v1 and v2 such that A_ref*v1=R1 and A_ref*v2=R2, R1 and R2 are the first
     # and second columns of all rotations.
diff --git a/tests/test_polar_ft.py b/tests/test_polar_ft.py
index 4ec69b67e4..425d5e14bb 100644
--- a/tests/test_polar_ft.py
+++ b/tests/test_polar_ft.py
@@ -203,7 +203,7 @@ def test_half_to_full_transform(stack_shape):
     """
     img_size = 32
     image = Image(
-        np.random.rand(*stack_shape, img_size, img_size).astype(np.float32, copy=None)
+        np.random.rand(*stack_shape, img_size, img_size).astype(np.float32, copy=False)
     )
     pft = PolarFT(size=img_size)
     pf = pft.transform(image)
diff --git a/tests/test_simulation.py b/tests/test_simulation.py
index 46b00d2ce9..944e2e7c06 100644
--- a/tests/test_simulation.py
+++ b/tests/test_simulation.py
@@ -82,7 +82,7 @@ def testPassthroughFromVol(self):
         without an explcit Simulation dtype.
         """
         for dtype in (np.float32, np.float64):
-            sim = Simulation(vols=self.vol.astype(dtype, copy=None))
+            sim = Simulation(vols=self.vol.astype(dtype, copy=False))
             # Did we assign the right type?
             self.assertTrue(sim.dtype == dtype)
 
diff --git a/tests/test_volume.py b/tests/test_volume.py
index 74c77c5cc5..d220860784 100644
--- a/tests/test_volume.py
+++ b/tests/test_volume.py
@@ -163,10 +163,10 @@ def test_astype(vols_1, dtype):
 
 def test_astype_copy(vols_1):
     """
-    `astype(copy=None)` is an optimization partially mimicked from numpy.
+    `astype(copy=False)` is an optimization partially mimicked from numpy.
     """
-    # Same dtype, copy=None
-    v2 = vols_1.astype(vols_1.dtype, copy=None)
+    # Same dtype, copy=False
+    v2 = vols_1.astype(vols_1.dtype, copy=False)
     # Details should match,
     assert isinstance(v2, Volume)
     assert np.allclose(v2.asnumpy(), vols_1.asnumpy())

From 4d5b3a050bb3d22f8504eb365c63c5934f4340d5 Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Wed, 9 Oct 2024 16:19:09 -0400
Subject: [PATCH 11/14] looks like np2 impacted mrcfile as well

---
 tests/test_mrc.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/tests/test_mrc.py b/tests/test_mrc.py
index 363db73a6c..723a45464c 100644
--- a/tests/test_mrc.py
+++ b/tests/test_mrc.py
@@ -81,15 +81,13 @@ def testUpdate(self):
             with mrcfile.new_mmap(
                 files[1], shape=(self.n, self.n), mrc_mode=2, overwrite=True
             ) as mrc:
-                mrc.set_data(self.a.astype(np.float32))
+                mrc.set_data(self.a)
+                self.stats.update_header(mrc)
                 mrc.header.time = epoch
                 mrc.header.label[0] = label
 
             # Our homebrew and mrcfile files should now match to the bit.
             comparison = sha256sum(files[0]) == sha256sum(files[1])
-            # Expected hash:
-            # 71355fa0bcd5b989ff88166962ea5d2b78ea032933bd6fda41fbdcc1c6d1a009
             logging.debug(f"sha256(file0): {sha256sum(files[0])}")
             logging.debug(f"sha256(file1): {sha256sum(files[1])}")
-
             self.assertTrue(comparison)

From 2e03ac4d771a2e87a82db4e053c1527dd0317e38 Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Mon, 21 Oct 2024 12:46:55 -0400
Subject: [PATCH 12/14] Tox wants explicit stack level

---
 src/aspire/__init__.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/aspire/__init__.py b/src/aspire/__init__.py
index 8273099c75..a5145dcd5f 100644
--- a/src/aspire/__init__.py
+++ b/src/aspire/__init__.py
@@ -98,4 +98,5 @@ def __getattr__(attr):
             "crash relating to mismatched dtypes or a Numpy call please try"
             ' `pip install "numpy<2"` and report to ASPIRE developers.',
             ImportWarning,
+            stacklevel=1,
         )

From 4f7a9d48563c2424835e4d5d3b8792c75d364214 Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Tue, 22 Oct 2024 08:29:17 -0400
Subject: [PATCH 13/14] missing space in warning message

---
 src/aspire/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/aspire/__init__.py b/src/aspire/__init__.py
index a5145dcd5f..686280e8e9 100644
--- a/src/aspire/__init__.py
+++ b/src/aspire/__init__.py
@@ -95,7 +95,7 @@ def __getattr__(attr):
         warnings.simplefilter("default")
         warnings.warn(
             "ASPIRE's Numpy 2 support is in beta.  If you experience a runtime"
-            "crash relating to mismatched dtypes or a Numpy call please try"
+            " crash relating to mismatched dtypes or a Numpy call please try"
             ' `pip install "numpy<2"` and report to ASPIRE developers.',
             ImportWarning,
             stacklevel=1,

From 5e75e20c4c7e4baf4c00cbbaafa6d433bc212264 Mon Sep 17 00:00:00 2001
From: Garrett Wright <garrettwrong@gmail.com>
Date: Tue, 22 Oct 2024 08:31:25 -0400
Subject: [PATCH 14/14] misc cleanup, reducing pr delta from draft work

---
 src/aspire/image/xform.py              | 1 -
 src/aspire/reconstruction/estimator.py | 1 +
 src/aspire/reconstruction/mean.py      | 4 ++--
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/src/aspire/image/xform.py b/src/aspire/image/xform.py
index 38f65d9bee..8003b4a1c5 100644
--- a/src/aspire/image/xform.py
+++ b/src/aspire/image/xform.py
@@ -144,7 +144,6 @@ def __init__(self, factor):
         self.multipliers = np.array(factor)
 
     def _forward(self, im, indices):
-
         if self.multipliers.size == 1:  # if we have a scalar multiplier
             im_new = im * self.multipliers.astype(im.dtype)
         else:
diff --git a/src/aspire/reconstruction/estimator.py b/src/aspire/reconstruction/estimator.py
index ac5e9caeca..2bf0ec3366 100644
--- a/src/aspire/reconstruction/estimator.py
+++ b/src/aspire/reconstruction/estimator.py
@@ -159,6 +159,7 @@ def apply_kernel(self, vol_coef, kernel=None):
 
         if kernel is None:
             kernel = self.kernel
+
         vol = Coef(self.basis, vol_coef).evaluate()  # returns a Volume
         vol = kernel.convolve_volume(vol)  # returns a Volume
         vol_coef = self.basis.evaluate_t(vol)
diff --git a/src/aspire/reconstruction/mean.py b/src/aspire/reconstruction/mean.py
index b380c8788c..e3888ee200 100644
--- a/src/aspire/reconstruction/mean.py
+++ b/src/aspire/reconstruction/mean.py
@@ -5,9 +5,10 @@
 from scipy.linalg import norm
 from scipy.sparse.linalg import LinearOperator
 
+from aspire import config
 from aspire.basis import Coef
 from aspire.nufft import anufft
-from aspire.numeric import config, fft
+from aspire.numeric import fft
 from aspire.numeric.scipy import cg
 from aspire.operators import evaluate_src_filters_on_grid
 from aspire.reconstruction import Estimator, FourierKernel, FourierKernelMatrix
@@ -211,7 +212,6 @@ def conj_grad(self, b_coef, x0=None, tol=1e-5, regularizer=0):
             precond_kernel = self.precond_kernel
             if regularizer > 0:
                 precond_kernel += regularizer
-
             M = LinearOperator(
                 (self.r * count, self.r * count),
                 matvec=partial(self.apply_kernel, kernel=precond_kernel),