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Replace np.compress by boolean indexing. #13384

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Feb 16, 2019
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22 changes: 10 additions & 12 deletions lib/matplotlib/axes/_axes.py
Original file line number Diff line number Diff line change
Expand Up @@ -5814,23 +5814,21 @@ def pcolor(self, *args, alpha=None, norm=None, cmap=None, vmin=None,
# don't plot if C or any of the surrounding vertices are masked.
mask = ma.getmaskarray(C) + xymask

compress = np.compress

ravelmask = (mask == 0).ravel()
X1 = compress(ravelmask, ma.filled(X[:-1, :-1]).ravel())
Y1 = compress(ravelmask, ma.filled(Y[:-1, :-1]).ravel())
X2 = compress(ravelmask, ma.filled(X[1:, :-1]).ravel())
Y2 = compress(ravelmask, ma.filled(Y[1:, :-1]).ravel())
X3 = compress(ravelmask, ma.filled(X[1:, 1:]).ravel())
Y3 = compress(ravelmask, ma.filled(Y[1:, 1:]).ravel())
X4 = compress(ravelmask, ma.filled(X[:-1, 1:]).ravel())
Y4 = compress(ravelmask, ma.filled(Y[:-1, 1:]).ravel())
unmask = ~mask
X1 = ma.filled(X[:-1, :-1])[unmask]
Y1 = ma.filled(Y[:-1, :-1])[unmask]
X2 = ma.filled(X[1:, :-1])[unmask]
Y2 = ma.filled(Y[1:, :-1])[unmask]
X3 = ma.filled(X[1:, 1:])[unmask]
Y3 = ma.filled(Y[1:, 1:])[unmask]
X4 = ma.filled(X[:-1, 1:])[unmask]
Y4 = ma.filled(Y[:-1, 1:])[unmask]
npoly = len(X1)

xy = np.stack([X1, Y1, X2, Y2, X3, Y3, X4, Y4, X1, Y1], axis=-1)
verts = xy.reshape((npoly, 5, 2))

C = compress(ravelmask, ma.filled(C[0:Ny - 1, 0:Nx - 1]).ravel())
C = ma.filled(C[:Ny - 1, :Nx - 1])[unmask]

linewidths = (0.25,)
if 'linewidth' in kwargs:
Expand Down
8 changes: 4 additions & 4 deletions lib/matplotlib/cbook/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -1311,23 +1311,23 @@ def _compute_conf_interval(data, med, iqr, bootstrap):
hival = np.percentile(x, whis[1])

# get high extreme
wiskhi = np.compress(x <= hival, x)
wiskhi = x[x <= hival]
if len(wiskhi) == 0 or np.max(wiskhi) < q3:
stats['whishi'] = q3
else:
stats['whishi'] = np.max(wiskhi)

# get low extreme
wisklo = np.compress(x >= loval, x)
wisklo = x[x >= loval]
if len(wisklo) == 0 or np.min(wisklo) > q1:
stats['whislo'] = q1
else:
stats['whislo'] = np.min(wisklo)

# compute a single array of outliers
stats['fliers'] = np.hstack([
np.compress(x < stats['whislo'], x),
np.compress(x > stats['whishi'], x)
x[x < stats['whislo']],
x[x > stats['whishi']],
])

# add in the remaining stats
Expand Down
4 changes: 2 additions & 2 deletions lib/matplotlib/ticker.py
Original file line number Diff line number Diff line change
Expand Up @@ -2641,9 +2641,9 @@ def __call__(self):
mod = np.abs((locs - t0) % majorstep)
cond1 = mod > minorstep / 10.0
cond2 = ~np.isclose(mod, majorstep, atol=0)
locs = locs.compress(cond1 & cond2)
locs = locs[cond1 & cond2]

return self.raise_if_exceeds(np.array(locs))
return self.raise_if_exceeds(locs)

def tick_values(self, vmin, vmax):
raise NotImplementedError('Cannot get tick locations for a '
Expand Down
2 changes: 1 addition & 1 deletion lib/matplotlib/tri/triangulation.py
Original file line number Diff line number Diff line change
Expand Up @@ -117,7 +117,7 @@ def get_masked_triangles(self):
Return an array of triangles that are not masked.
"""
if self.mask is not None:
return self.triangles.compress(1 - self.mask, axis=0)
return self.triangles[~self.mask]
else:
return self.triangles

Expand Down
2 changes: 1 addition & 1 deletion lib/matplotlib/tri/tripcolor.py
Original file line number Diff line number Diff line change
Expand Up @@ -112,7 +112,7 @@ def tripcolor(ax, *args, alpha=1.0, norm=None, cmap=None, vmin=None,
C = C[maskedTris].mean(axis=1)
elif tri.mask is not None:
# Remove color values of masked triangles.
C = C.compress(1-tri.mask)
C = C[~tri.mask]

collection = PolyCollection(verts, **kwargs)

Expand Down
2 changes: 1 addition & 1 deletion lib/matplotlib/tri/tritools.py
Original file line number Diff line number Diff line change
Expand Up @@ -293,7 +293,7 @@ def _total_to_compress_renum(mask, n=None):
n = np.size(mask)
if mask is not None:
renum = np.full(n, -1, dtype=np.int32) # Default num is -1
valid = np.arange(n, dtype=np.int32).compress(~mask, axis=0)
valid = np.arange(n, dtype=np.int32)[~mask]
renum[valid] = np.arange(np.size(valid, 0), dtype=np.int32)
return renum
else:
Expand Down