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style: Normalise numpy imports with import numpy as np

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The convention when importing numpy is to use `import numpy as np`

Fixes: unconventional-import-alias (ICN001)
Ruff rule: https://docs.astral.sh/ruff/rules/unconventional-import-alias/
This commit is contained in:
Edouard Choinière
2025-02-08 16:48:57 +00:00
parent 45f9e89f5d
commit 95cafd1a3f
26 changed files with 233 additions and 233 deletions
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40
wx/lib/floatcanvas/Utilities/BBox.py
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@@ -15,9 +15,9 @@ A Bounding Box object and assorted utilities , subclassed from a numpy array
"""
import numpy as N
import numpy as np
class BBox(N.ndarray):
class BBox(np.ndarray):
"""
A Bounding Box object:
@@ -61,12 +61,12 @@ class BBox(N.ndarray):
fromPoints
"""
arr = N.array(data, float)
arr = np.array(data, float)
arr.shape = (2,2)
if arr[0,0] > arr[1,0] or arr[0,1] > arr[1,1]:
# note: zero sized BB OK.
raise ValueError("BBox values not aligned: \n minimum values must be less that maximum values")
return N.ndarray.__new__(subtype, shape=arr.shape, dtype=arr.dtype, buffer=arr)
return np.ndarray.__new__(subtype, shape=arr.shape, dtype=arr.dtype, buffer=arr)
def Overlaps(self, BB):
"""
@@ -77,7 +77,7 @@ class BBox(N.ndarray):
If they are just touching, returns True
"""
if N.isinf(self).all() or N.isinf(BB).all():
if np.isinf(self).all() or np.isinf(BB).all():
return True
if ( (self[1,0] >= BB[0,0]) and (self[0,0] <= BB[1,0]) and
(self[1,1] >= BB[0,1]) and (self[0,1] <= BB[1,1]) ):
@@ -130,7 +130,7 @@ class BBox(N.ndarray):
"""
if self.IsNull():
self[:] = BB
elif N.isnan(BB).all(): ## BB may be a regular array, so I can't use IsNull
elif np.isnan(BB).all(): ## BB may be a regular array, so I can't use IsNull
pass
else:
if BB[0,0] < self[0,0]: self[0,0] = BB[0,0]
@@ -141,7 +141,7 @@ class BBox(N.ndarray):
return None
def IsNull(self):
return N.isnan(self).all()
return np.isnan(self).all()
## fixme: it would be nice to add setter, too.
def _getLeft(self):
@@ -179,7 +179,7 @@ class BBox(N.ndarray):
## Save the ndarray __eq__ for internal use.
Array__eq__ = N.ndarray.__eq__
Array__eq__ = np.ndarray.__eq__
def __eq__(self, BB):
"""
__eq__(BB) The equality operator
@@ -187,7 +187,7 @@ class BBox(N.ndarray):
A == B if and only if all the entries are the same
"""
if self.IsNull() and N.isnan(BB).all(): ## BB may be a regular array, so I can't use IsNull
if self.IsNull() and np.isnan(BB).all(): ## BB may be a regular array, so I can't use IsNull
return True
else:
return self.Array__eq__(BB).all()
@@ -212,8 +212,8 @@ def asBBox(data):
if isinstance(data, BBox):
return data
arr = N.asarray(data, float)
return N.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
arr = np.asarray(data, float)
return np.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
def fromPoints(Points):
"""
@@ -225,10 +225,10 @@ def fromPoints(Points):
If a single point is passed in, a zero-size Bounding Box is returned.
"""
Points = N.asarray(Points, float).reshape(-1,2)
Points = np.asarray(Points, float).reshape(-1,2)
arr = N.vstack( (Points.min(0), Points.max(0)) )
return N.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
arr = np.vstack( (Points.min(0), Points.max(0)) )
return np.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
def fromBBArray(BBarray):
"""
@@ -243,8 +243,8 @@ def fromBBArray(BBarray):
# BBarray = N.asarray(BBarray, float).reshape(-1,2)
# arr = N.vstack( (BBarray.min(0), BBarray.max(0)) )
BBarray = N.asarray(BBarray, float).reshape(-1,2,2)
arr = N.vstack( (BBarray[:,0,:].min(0), BBarray[:,1,:].max(0)) )
BBarray = np.asarray(BBarray, float).reshape(-1,2,2)
arr = np.vstack( (BBarray[:,0,:].min(0), BBarray[:,1,:].max(0)) )
return asBBox(arr)
#return asBBox( (upperleft, lowerright) ) * 2
@@ -260,8 +260,8 @@ def NullBBox():
"""
arr = N.array(((N.nan, N.nan),(N.nan, N.nan)), float)
return N.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
arr = np.array(((np.nan, np.nan),(np.nan, np.nan)), float)
return np.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
def InfBBox():
"""
@@ -269,8 +269,8 @@ def InfBBox():
"""
arr = N.array(((-N.inf, -N.inf),(N.inf, N.inf)), float)
return N.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
arr = np.array(((-np.inf, -np.inf),(np.inf, np.inf)), float)
return np.ndarray.__new__(BBox, shape=arr.shape, dtype=arr.dtype, buffer=arr)
class RectBBox(BBox):
"""