def blend_xy_sep_transform(trans1, trans2):
"""
If trans1 and trans2 are SeparableTransformation instances, you can
build a new SeparableTransformation from them by extracting the x and y
bounding points and functions and recomposing a new SeparableTransformation
This function extracts all the relevant bits from trans1 and
trans2 and returns the new Transformation instance. This is
useful, for example, if you want to specify x in data coordinates
and y in axes coordinates.
"""
inboxx = trans1.get_bbox1()
inboxy = trans2.get_bbox1()
outboxx = trans1.get_bbox2()
outboxy = trans2.get_bbox2()
xminIn = inboxx.ll().x()
xmaxIn = inboxx.ur().x()
xminOut = outboxx.ll().x()
xmaxOut = outboxx.ur().x()
yminIn = inboxy.ll().y()
ymaxIn = inboxy.ur().y()
yminOut = outboxy.ll().y()
ymaxOut = outboxy.ur().y()
funcx = trans1.get_funcx()
funcy = trans2.get_funcy()
boxin = Bbox(Point(xminIn, yminIn), Point(xmaxIn, ymaxIn))
boxout = Bbox(Point(xminOut, yminOut), Point(xmaxOut, ymaxOut))
return SeparableTransformation(boxin, boxout, funcx, funcy)
def get_bbox_transform(boxin, boxout):
"""
return the transform that maps transform one bounding box to
another
"""
return SeparableTransformation(boxin, boxout, Func(IDENTITY),
Func(IDENTITY))
def identity_transform():
"""
Get an affine transformation that maps x,y -> x,y
"""
return SeparableTransformation(unit_bbox(), unit_bbox(),
Func(IDENTITY),
Func(IDENTITY))
def scale_sep_transform(sx, sy):
"""
Return a pure scale transformation as a SeparableTransformation;
sx and sy are LazyValue instances (Values or binary opertations on
values)
"""
bboxin = unit_bbox()
bboxout = Bbox(Point(zero(), zero()), Point(sx, sy))
return SeparableTransformation(bboxin, bboxout, Func(IDENTITY),
Func(IDENTITY))
