8000 Allow passing infinite rcount & ccount to plot_surface, plot_wireframe. · matplotlib/matplotlib@6f5a530 · GitHub
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anntzeranntzer
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Allow passing infinite rcount & ccount to plot_surface, plot_wireframe.
Passing an infinite rcount and ccount is the easiest way to ensure the data does not get downsampled (which I still think is a misfeature, but that's a battle for another day), but would result in a stride of zero; instead, ensure that the stride is at least 1.
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‎lib/mpl_toolkits/mplot3d/axes3d.py

Lines changed: 18 additions & 18 deletions
Original file line numberDiff line numberDiff line change
@@ -1570,8 +1570,8 @@ def plot_surface(self, X, Y, Z, *args, **kwargs):
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The *rcount* and *ccount* kwargs, which both default to 50,
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determine the maximum number of samples used in each direction. If
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the input data is larger, it will be downsampled to these numbers
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of points.
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the input data is larger, it will be downsampled (by slicing) to
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these numbers of points.
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Parameters
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----------
@@ -1580,8 +1580,8 @@ def plot_surface(self, X, Y, Z, *args, **kwargs):
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rcount, ccount : int
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Maximum number of samples used in each direction. If the input
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data is larger, it will be downsampled to these numbers of points.
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Defaults to 50.
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data is larger, it will be downsampled (by slicing) to these
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numbers of points. Defaults to 50.
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rstride, cstride : int
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Downsampling stride in each direction. These arguments are
@@ -1637,14 +1637,14 @@ def plot_surface(self, X, Y, Z, *args, **kwargs):
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# So, only compute strides from counts
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# if counts were explicitly given
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if has_count:
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rstride = int(np.ceil(rows / rcount))
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cstride = int(np.ceil(cols / ccount))
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rstride = int(max(np.ceil(rows / rcount), 1))
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cstride = int(max(np.ceil(cols / ccount), 1))
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else:
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# If the strides are provided then it has priority.
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# Otherwise, compute the strides from the counts.
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if not has_stride:
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rstride = int(np.ceil(rows / rcount))
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cstride = int(np.ceil(cols / ccount))
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rstride = int(max(np.ceil(rows / rcount), 1))
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cstride = int(max(np.ceil(cols / ccount), 1))
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if 'facecolors' in kwargs:
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fcolors = kwargs.pop('facecolors')
@@ -1795,8 +1795,8 @@ def plot_wireframe(self, X, Y, Z, *args, **kwargs):
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The *rcount* and *ccount* kwargs, which both default to 50,
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determine the maximum number of samples used in each direction. If
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the input data is larger, it will be downsampled to these numbers
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of points.
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the input data is larger, it will be downsampled (by slicing) to
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these numbers of points.
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Parameters
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----------
@@ -1805,10 +1805,10 @@ def plot_wireframe(self, X, Y, Z, *args, **kwargs):
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rcount, ccount : int
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Maximum number of samples used in each direction. If the input
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data is larger, it will be downsampled to these numbers of points.
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Setting a count to zero causes the data to be not sampled in the
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corresponding direction, producing a 3D line plot rather than a
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wireframe plot. Defaults to 50.
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data is larger, it will be downsampled (by slicing) to these
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numbers of points. Setting a count to zero causes the data to be
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not sampled in the corresponding direction, producing a 3D line
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plot rather than a wireframe plot. Defaults to 50.
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rstride, cstride : int
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Downsampling stride in each direction. These arguments are
@@ -1848,14 +1848,14 @@ def plot_wireframe(self, X, Y, Z, *args, **kwargs):
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# So, only compute strides from counts
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# if counts were explicitly given
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if has_count:
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rstride = int(np.ceil(rows / rcount)) if rcount else 0
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cstride = int(np.ceil(cols / ccount)) if ccount else 0
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rstride = int(max(np.ceil(rows / rcount), 1)) if rcount else 0
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cstride = int(max(np.ceil(cols / ccount), 1)) if ccount else 0
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else:
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# If the strides are provided then it has priority.
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# Otherwise, compute the strides from the counts.
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if not has_stride:
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rstride = int(np.ceil(rows / rcount)) if rcount else 0
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cstride = int(np.ceil(cols / ccount)) if ccount else 0
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rstride = int(max(np.ceil(rows / rcount), 1)) if rcount else 0
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cstride = int(max(np.ceil(cols / ccount), 1)) if ccount else 0
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# We want two sets of lines, one running along the "rows" of
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# Z and another set of lines running along the "columns" of Z.

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