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More memory efficient biot_savart_2d (#107)
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* More memory efficient biot_savart_2d
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@loganbvh
loganbvh committed Oct 4, 2023
1 parent 9454774 commit 9661fb0
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10 changes: 5 additions & 5 deletions docs/notebooks/field-sources.ipynb
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"name": "stdout",
"output_type": "stream",
"text": [
"x = 0.7650684631746568\n",
"y = 0.7478751704881408\n",
"z = 0.18189859902136085\n",
"x = 0.3396785462775239\n",
"y = 0.5560346157741703\n",
"z = 0.47978056547366055\n",
"field(x, y, z) = 5.0\n"
]
}
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6 changes: 3 additions & 3 deletions docs/notebooks/logo.ipynb
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"\n",
"import superscreen as sc\n",
"\n",
"SAVE = False"
"SAVE = True"
]
},
{
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20 changes: 10 additions & 10 deletions docs/notebooks/polygons.ipynb
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10 changes: 5 additions & 5 deletions docs/notebooks/quickstart.ipynb
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12 changes: 6 additions & 6 deletions docs/notebooks/scanning-squid.ipynb
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"Solver iterations: 100%|███████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:01<00:00, 2.77it/s]\n",
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"Solver iterations: 100%|███████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:03<00:00, 1.52it/s]\n"
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"Solver iterations: 100%|███████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:01<00:00, 2.81it/s]\n",
"Solver iterations: 100%|███████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:03<00:00, 1.41it/s]\n",
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6 changes: 3 additions & 3 deletions docs/notebooks/terminal-currents.ipynb
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"Holes: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2.91it/s]\n"
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46 changes: 14 additions & 32 deletions superscreen/distance.py
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import numpy as np


@numba.njit(fastmath=True, parallel=True)
def pairwise_difference(xA: np.ndarray, xB: np.ndarray):
"""Pairwise different between two 1D arrays.
This is equivalent to ``numpy.subtract.outer(XA, XB)``.
Args:
xA: A shape (n,) array
xB: A shep (m,) array
Returns:
A shape (n, m) array of pairwise differences.
"""
out = np.empty((xA.shape[0], xB.shape[0]), dtype=xA.dtype)
for i in numba.prange(xA.shape[0]):
for j in range(xB.shape[0]):
out[i, j] = xA[i] - xB[j]
return out


@numba.njit(fastmath=True, parallel=True)
def sqeuclidean_distance_2d(XA: np.ndarray, XB: np.ndarray):
"""Squared Euclidean pointwise distance between two 2D arrays."""
out = np.empty((XA.shape[0], XB.shape[0]), dtype=XA.dtype)
for i in numba.prange(XA.shape[0]):
for j in range(XB.shape[0]):
out[i, j] = (XA[i, 0] - XB[j, 0]) ** 2 + (XA[i, 1] - XB[j, 1]) ** 2
dx = XA[i, 0] - XB[j, 0]
dy = XA[i, 1] - XB[j, 1]
out[i, j] = dx * dx + dy * dy
return out


Expand All @@ -38,11 +20,10 @@ def sqeuclidean_distance_3d(XA: np.ndarray, XB: np.ndarray):
out = np.empty((XA.shape[0], XB.shape[0]), dtype=XA.dtype)
for i in numba.prange(XA.shape[0]):
for j in range(XB.shape[0]):
out[i, j] = (
(XA[i, 0] - XB[j, 0]) ** 2
+ (XA[i, 1] - XB[j, 1]) ** 2
+ (XA[i, 2] - XB[j, 2]) ** 2
)
dx = XA[i, 0] - XB[j, 0]
dy = XA[i, 1] - XB[j, 1]
dz = XA[i, 2] - XB[j, 2]
out[i, j] = dx * dx + dy * dy + dz * dz
return out


Expand All @@ -52,7 +33,9 @@ def euclidean_distance_2d(XA: np.ndarray, XB: np.ndarray):
out = np.empty((XA.shape[0], XB.shape[0]), dtype=XA.dtype)
for i in numba.prange(XA.shape[0]):
for j in range(XB.shape[0]):
out[i, j] = np.sqrt((XA[i, 0] - XB[j, 0]) ** 2 + (XA[i, 1] - XB[j, 1]) ** 2)
dx = XA[i, 0] - XB[j, 0]
dy = XA[i, 1] - XB[j, 1]
out[i, j] = np.sqrt(dx * dx + dy * dy)
return out


Expand All @@ -62,11 +45,10 @@ def euclidean_distance_3d(XA: np.ndarray, XB: np.ndarray):
out = np.empty((XA.shape[0], XB.shape[0]), dtype=XA.dtype)
for i in numba.prange(XA.shape[0]):
for j in range(XB.shape[0]):
out[i, j] = np.sqrt(
(XA[i, 0] - XB[j, 0]) ** 2
+ (XA[i, 1] - XB[j, 1]) ** 2
+ (XA[i, 2] - XB[j, 2]) ** 2
)
dx = XA[i, 0] - XB[j, 0]
dy = XA[i, 1] - XB[j, 1]
dz = XA[i, 2] - XB[j, 2]
out[i, j] = np.sqrt(dx * dx + dy * dy + dz * dz)
return out


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