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2 changes: 1 addition & 1 deletion yt/fields/field_functions.py
Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@ def get_radius(data, field_prefix, ftype):
np.abs(r, r)
np.subtract(r, DW.d[i], rdw)
np.abs(rdw, rdw)
np.minimum(r, rdw, r)
np.minimum(r, rdw, out=r)
np.multiply(r, r, r)
np.add(radius2.d, r, radius2.d)
if data.ds.dimensionality < i + 1:
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4 changes: 2 additions & 2 deletions yt/frontends/tipsy/io.py
Original file line number Diff line number Diff line change
Expand Up @@ -266,7 +266,7 @@ def _update_domain(self, data_file):
pp["Coordinates"]["y"].min(),
pp["Coordinates"]["z"].min(),
],
mi,
out=mi,
)
np.maximum(
ma,
Expand All @@ -275,7 +275,7 @@ def _update_domain(self, data_file):
pp["Coordinates"]["y"].max(),
pp["Coordinates"]["z"].max(),
],
ma,
out=ma,
)
ind += c
# We extend by 1%.
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2 changes: 1 addition & 1 deletion yt/utilities/amr_kdtree/amr_kdtools.py
Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@ def receive_and_reduce(comm, incoming_rank, image, add_to_front, *, use_opacity=
return image

ta = 1.0 - front[:, :, 3]
np.maximum(ta, 0.0, ta)
np.maximum(ta, 0.0, out=ta)
# This now does the following calculation, but in a memory
# conservative fashion
# image[:,:,i ] = front[:,:,i] + ta*back[:,:,i]
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2 changes: 1 addition & 1 deletion yt/utilities/initial_conditions.py
Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ def __call__(self, grid, sub_select=None):
cr2 = self.core_radius**2
for i, ax in enumerate("xyz"):
np.add(r, (grid[ax] - self.center[i]) ** 2.0, r)
np.maximum(r, cr2, r)
np.maximum(r, cr2, out=r)
ind = r <= r2
if sub_select is not None:
ind &= sub_select
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4 changes: 2 additions & 2 deletions yt/visualization/volume_rendering/old_camera.py
Original file line number Diff line number Diff line change
Expand Up @@ -2173,8 +2173,8 @@ def _render(self, double_check, num_threads, image, sampler):
+ width / 2.0 * off2 * east_vector
+ width / 2.0 * off3 * normal_vector
)
np.minimum(mi, this_point, mi)
np.maximum(ma, this_point, ma)
np.minimum(mi, this_point, out=mi)
np.maximum(ma, this_point, out=ma)
# Now we have a bounding box.
data_source = ds.region(self.center, mi, ma)

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