cross_from_above deprecated in future matplotlib… replacement function?
It seems that matplotlib will deprecate the cross_from_above and cross_from_below functions in the upcoming version 3.1
This is a shame as they're very useful tools for "returning the indices where a 1D array crosses a threshold from above/below". See current documentation at: https://matplotlib.org/api/mlab_api.html
I can't find any discussion of this online so wonder if there are replacement functions that I should be using instead for the same functionality?
python numpy matplotlib indexing scipy
asked Nov 15 '18 at 3:04
SFlowtYSFlowtY
224
add a comment |
It seems that matplotlib will deprecate the cross_from_above and cross_from_below functions in the upcoming version 3.1
This is a shame as they're very useful tools for "returning the indices where a 1D array crosses a threshold from above/below". See current documentation at: https://matplotlib.org/api/mlab_api.html
I can't find any discussion of this online so wonder if there are replacement functions that I should be using instead for the same functionality?
python numpy matplotlib indexing scipy
asked Nov 15 '18 at 3:04
SFlowtYSFlowtY
224
add a comment |
It seems that matplotlib will deprecate the cross_from_above and cross_from_below functions in the upcoming version 3.1
This is a shame as they're very useful tools for "returning the indices where a 1D array crosses a threshold from above/below". See current documentation at: https://matplotlib.org/api/mlab_api.html
I can't find any discussion of this online so wonder if there are replacement functions that I should be using instead for the same functionality?
python numpy matplotlib indexing scipy
asked Nov 15 '18 at 3:04
SFlowtYSFlowtY
224
It seems that matplotlib will deprecate the cross_from_above and cross_from_below functions in the upcoming version 3.1
This is a shame as they're very useful tools for "returning the indices where a 1D array crosses a threshold from above/below". See current documentation at: https://matplotlib.org/api/mlab_api.html
I can't find any discussion of this online so wonder if there are replacement functions that I should be using instead for the same functionality?
python numpy matplotlib indexing scipy
python numpy matplotlib indexing scipy
asked Nov 15 '18 at 3:04
SFlowtYSFlowtY
224
asked Nov 15 '18 at 3:04
SFlowtYSFlowtY
224
asked Nov 15 '18 at 3:04
SFlowtYSFlowtY
224
asked Nov 15 '18 at 3:04
SFlowtYSFlowtY
224
asked Nov 15 '18 at 3:04
SFlowtYSFlowtY
224
224
add a comment |
add a comment |
1 Answer
1
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oldest
votes
There is no replacement for these functions. But they aren't very complicated. Here is the literal copy of the source code.
def cross_from_above(x, threshold):
"""
return the indices into *x* where *x* crosses some threshold from above.
"""
x = np.asarray(x)
ind = np.nonzero((x[:-1] >= threshold) & (x[1:] < threshold))[0]
if len(ind):
return ind+1
else:
return ind
and
def cross_from_below(x, threshold):
"""
return the indices into *x* where *x* crosses some threshold from below.
"""
x = np.asarray(x)
ind = np.nonzero((x[:-1] < threshold) & (x[1:] >= threshold))[0]
if len(ind):
return ind+1
else:
return ind
where np is numpy.
Essentially they both contain a single line of code, which is easy to replicate or modified in any actual use case.
answered Nov 15 '18 at 3:16
ImportanceOfBeingErnestImportanceOfBeingErnest
139k13162241
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
There is no replacement for these functions. But they aren't very complicated. Here is the literal copy of the source code.
def cross_from_above(x, threshold):
"""
return the indices into *x* where *x* crosses some threshold from above.
"""
x = np.asarray(x)
ind = np.nonzero((x[:-1] >= threshold) & (x[1:] < threshold))[0]
if len(ind):
return ind+1
else:
return ind
and
def cross_from_below(x, threshold):
"""
return the indices into *x* where *x* crosses some threshold from below.
"""
x = np.asarray(x)
ind = np.nonzero((x[:-1] < threshold) & (x[1:] >= threshold))[0]
if len(ind):
return ind+1
else:
return ind
where np is numpy.
Essentially they both contain a single line of code, which is easy to replicate or modified in any actual use case.
answered Nov 15 '18 at 3:16
ImportanceOfBeingErnestImportanceOfBeingErnest
139k13162241
add a comment |
There is no replacement for these functions. But they aren't very complicated. Here is the literal copy of the source code.
def cross_from_above(x, threshold):
"""
return the indices into *x* where *x* crosses some threshold from above.
"""
x = np.asarray(x)
ind = np.nonzero((x[:-1] >= threshold) & (x[1:] < threshold))[0]
if len(ind):
return ind+1
else:
return ind
and
def cross_from_below(x, threshold):
"""
return the indices into *x* where *x* crosses some threshold from below.
"""
x = np.asarray(x)
ind = np.nonzero((x[:-1] < threshold) & (x[1:] >= threshold))[0]
if len(ind):
return ind+1
else:
return ind
where np is numpy.
Essentially they both contain a single line of code, which is easy to replicate or modified in any actual use case.
answered Nov 15 '18 at 3:16
ImportanceOfBeingErnestImportanceOfBeingErnest
139k13162241
add a comment |
There is no replacement for these functions. But they aren't very complicated. Here is the literal copy of the source code.
def cross_from_above(x, threshold):
"""
return the indices into *x* where *x* crosses some threshold from above.
"""
x = np.asarray(x)
ind = np.nonzero((x[:-1] >= threshold) & (x[1:] < threshold))[0]
if len(ind):
return ind+1
else:
return ind
and
def cross_from_below(x, threshold):
"""
return the indices into *x* where *x* crosses some threshold from below.
"""
x = np.asarray(x)
ind = np.nonzero((x[:-1] < threshold) & (x[1:] >= threshold))[0]
if len(ind):
return ind+1
else:
return ind
where np is numpy.
Essentially they both contain a single line of code, which is easy to replicate or modified in any actual use case.
answered Nov 15 '18 at 3:16
ImportanceOfBeingErnestImportanceOfBeingErnest
139k13162241
There is no replacement for these functions. But they aren't very complicated. Here is the literal copy of the source code.
def cross_from_above(x, threshold):
"""
return the indices into *x* where *x* crosses some threshold from above.
"""
x = np.asarray(x)
ind = np.nonzero((x[:-1] >= threshold) & (x[1:] < threshold))[0]
if len(ind):
return ind+1
else:
return ind
and
def cross_from_below(x, threshold):
"""
return the indices into *x* where *x* crosses some threshold from below.
"""
x = np.asarray(x)
ind = np.nonzero((x[:-1] < threshold) & (x[1:] >= threshold))[0]
if len(ind):
return ind+1
else:
return ind
where np is numpy.
Essentially they both contain a single line of code, which is easy to replicate or modified in any actual use case.
answered Nov 15 '18 at 3:16
ImportanceOfBeingErnestImportanceOfBeingErnest
139k13162241
answered Nov 15 '18 at 3:16
ImportanceOfBeingErnestImportanceOfBeingErnest
139k13162241
answered Nov 15 '18 at 3:16
ImportanceOfBeingErnestImportanceOfBeingErnest
139k13162241
answered Nov 15 '18 at 3:16
ImportanceOfBeingErnestImportanceOfBeingErnest
139k13162241
139k13162241
add a comment |
add a comment |
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