0f03e6529a
* Add default auto doc options * Ensure all references are unique * Use anonymous links to avoid duplicate references * Remove default options, fix wrong module name * Don’t index repeated class * Remove repeated classes included through automodule * Fix warnings * We don’t use our own static directory * Correctly format XML in docs * Fix indentation * Fix overline * Bring TOC to top * Fix definition list * Offset definition lists and examples * Fix erroneous markup * Fix markup * Already included in automodule * Fix args markup * Correct markup for example * Don’t reindex repeated module * Correct XML code block markup * Fix markup errors, change example to doctest * Correct list markup * Make ttx docstring both valid RST and valid help output * Various other boring markup fixes * Fix example indenting * Make docstring valid RST and valid help output * Mock import for reportlab * It’s ok if manual links don’t appear in toctrees * Oops typo, I guess doctests are useful
399 lines
9.0 KiB
Python
399 lines
9.0 KiB
Python
"""Affine 2D transformation matrix class.
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The Transform class implements various transformation matrix operations,
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both on the matrix itself, as well as on 2D coordinates.
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Transform instances are effectively immutable: all methods that operate on the
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transformation itself always return a new instance. This has as the
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interesting side effect that Transform instances are hashable, ie. they can be
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used as dictionary keys.
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This module exports the following symbols:
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Transform
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this is the main class
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Identity
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Transform instance set to the identity transformation
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Offset
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Convenience function that returns a translating transformation
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Scale
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Convenience function that returns a scaling transformation
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:Example:
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>>> t = Transform(2, 0, 0, 3, 0, 0)
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>>> t.transformPoint((100, 100))
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(200, 300)
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>>> t = Scale(2, 3)
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>>> t.transformPoint((100, 100))
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(200, 300)
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>>> t.transformPoint((0, 0))
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(0, 0)
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>>> t = Offset(2, 3)
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>>> t.transformPoint((100, 100))
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(102, 103)
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>>> t.transformPoint((0, 0))
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(2, 3)
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>>> t2 = t.scale(0.5)
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>>> t2.transformPoint((100, 100))
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(52.0, 53.0)
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>>> import math
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>>> t3 = t2.rotate(math.pi / 2)
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>>> t3.transformPoint((0, 0))
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(2.0, 3.0)
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>>> t3.transformPoint((100, 100))
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(-48.0, 53.0)
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>>> t = Identity.scale(0.5).translate(100, 200).skew(0.1, 0.2)
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>>> t.transformPoints([(0, 0), (1, 1), (100, 100)])
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[(50.0, 100.0), (50.550167336042726, 100.60135501775433), (105.01673360427253, 160.13550177543362)]
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>>>
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"""
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from typing import NamedTuple
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__all__ = ["Transform", "Identity", "Offset", "Scale"]
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_EPSILON = 1e-15
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_ONE_EPSILON = 1 - _EPSILON
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_MINUS_ONE_EPSILON = -1 + _EPSILON
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def _normSinCos(v):
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if abs(v) < _EPSILON:
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v = 0
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elif v > _ONE_EPSILON:
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v = 1
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elif v < _MINUS_ONE_EPSILON:
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v = -1
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return v
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class Transform(NamedTuple):
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"""2x2 transformation matrix plus offset, a.k.a. Affine transform.
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Transform instances are immutable: all transforming methods, eg.
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rotate(), return a new Transform instance.
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:Example:
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>>> t = Transform()
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>>> t
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<Transform [1 0 0 1 0 0]>
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>>> t.scale(2)
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<Transform [2 0 0 2 0 0]>
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>>> t.scale(2.5, 5.5)
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<Transform [2.5 0 0 5.5 0 0]>
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>>>
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>>> t.scale(2, 3).transformPoint((100, 100))
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(200, 300)
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Transform's constructor takes six arguments, all of which are
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optional, and can be used as keyword arguments::
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>>> Transform(12)
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<Transform [12 0 0 1 0 0]>
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>>> Transform(dx=12)
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<Transform [1 0 0 1 12 0]>
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>>> Transform(yx=12)
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<Transform [1 0 12 1 0 0]>
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Transform instances also behave like sequences of length 6::
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>>> len(Identity)
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6
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>>> list(Identity)
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[1, 0, 0, 1, 0, 0]
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>>> tuple(Identity)
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(1, 0, 0, 1, 0, 0)
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Transform instances are comparable::
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>>> t1 = Identity.scale(2, 3).translate(4, 6)
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>>> t2 = Identity.translate(8, 18).scale(2, 3)
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>>> t1 == t2
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1
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But beware of floating point rounding errors::
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>>> t1 = Identity.scale(0.2, 0.3).translate(0.4, 0.6)
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>>> t2 = Identity.translate(0.08, 0.18).scale(0.2, 0.3)
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>>> t1
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<Transform [0.2 0 0 0.3 0.08 0.18]>
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>>> t2
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<Transform [0.2 0 0 0.3 0.08 0.18]>
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>>> t1 == t2
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0
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Transform instances are hashable, meaning you can use them as
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keys in dictionaries::
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>>> d = {Scale(12, 13): None}
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>>> d
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{<Transform [12 0 0 13 0 0]>: None}
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But again, beware of floating point rounding errors::
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>>> t1 = Identity.scale(0.2, 0.3).translate(0.4, 0.6)
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>>> t2 = Identity.translate(0.08, 0.18).scale(0.2, 0.3)
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>>> t1
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<Transform [0.2 0 0 0.3 0.08 0.18]>
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>>> t2
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<Transform [0.2 0 0 0.3 0.08 0.18]>
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>>> d = {t1: None}
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>>> d
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{<Transform [0.2 0 0 0.3 0.08 0.18]>: None}
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>>> d[t2]
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Traceback (most recent call last):
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File "<stdin>", line 1, in ?
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KeyError: <Transform [0.2 0 0 0.3 0.08 0.18]>
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"""
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xx: float = 1
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xy: float = 0
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yx: float = 0
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yy: float = 1
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dx: float = 0
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dy: float = 0
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def transformPoint(self, p):
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"""Transform a point.
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:Example:
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>>> t = Transform()
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>>> t = t.scale(2.5, 5.5)
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>>> t.transformPoint((100, 100))
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(250.0, 550.0)
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"""
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(x, y) = p
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xx, xy, yx, yy, dx, dy = self
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return (xx*x + yx*y + dx, xy*x + yy*y + dy)
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def transformPoints(self, points):
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"""Transform a list of points.
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:Example:
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>>> t = Scale(2, 3)
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>>> t.transformPoints([(0, 0), (0, 100), (100, 100), (100, 0)])
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[(0, 0), (0, 300), (200, 300), (200, 0)]
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>>>
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"""
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xx, xy, yx, yy, dx, dy = self
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return [(xx*x + yx*y + dx, xy*x + yy*y + dy) for x, y in points]
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def transformVector(self, v):
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"""Transform an (dx, dy) vector, treating translation as zero.
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:Example:
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>>> t = Transform(2, 0, 0, 2, 10, 20)
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>>> t.transformVector((3, -4))
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(6, -8)
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>>>
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"""
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(dx, dy) = v
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xx, xy, yx, yy = self[:4]
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return (xx*dx + yx*dy, xy*dx + yy*dy)
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def transformVectors(self, vectors):
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"""Transform a list of (dx, dy) vector, treating translation as zero.
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:Example:
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>>> t = Transform(2, 0, 0, 2, 10, 20)
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>>> t.transformVectors([(3, -4), (5, -6)])
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[(6, -8), (10, -12)]
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>>>
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"""
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xx, xy, yx, yy = self[:4]
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return [(xx*dx + yx*dy, xy*dx + yy*dy) for dx, dy in vectors]
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def translate(self, x=0, y=0):
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"""Return a new transformation, translated (offset) by x, y.
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:Example:
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>>> t = Transform()
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>>> t.translate(20, 30)
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<Transform [1 0 0 1 20 30]>
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>>>
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"""
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return self.transform((1, 0, 0, 1, x, y))
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def scale(self, x=1, y=None):
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"""Return a new transformation, scaled by x, y. The 'y' argument
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may be None, which implies to use the x value for y as well.
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:Example:
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>>> t = Transform()
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>>> t.scale(5)
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<Transform [5 0 0 5 0 0]>
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>>> t.scale(5, 6)
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<Transform [5 0 0 6 0 0]>
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>>>
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"""
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if y is None:
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y = x
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return self.transform((x, 0, 0, y, 0, 0))
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def rotate(self, angle):
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"""Return a new transformation, rotated by 'angle' (radians).
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:Example:
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>>> import math
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>>> t = Transform()
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>>> t.rotate(math.pi / 2)
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<Transform [0 1 -1 0 0 0]>
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>>>
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"""
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import math
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c = _normSinCos(math.cos(angle))
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s = _normSinCos(math.sin(angle))
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return self.transform((c, s, -s, c, 0, 0))
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def skew(self, x=0, y=0):
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"""Return a new transformation, skewed by x and y.
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:Example:
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>>> import math
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>>> t = Transform()
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>>> t.skew(math.pi / 4)
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<Transform [1 0 1 1 0 0]>
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>>>
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"""
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import math
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return self.transform((1, math.tan(y), math.tan(x), 1, 0, 0))
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def transform(self, other):
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"""Return a new transformation, transformed by another
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transformation.
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:Example:
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>>> t = Transform(2, 0, 0, 3, 1, 6)
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>>> t.transform((4, 3, 2, 1, 5, 6))
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<Transform [8 9 4 3 11 24]>
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>>>
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"""
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xx1, xy1, yx1, yy1, dx1, dy1 = other
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xx2, xy2, yx2, yy2, dx2, dy2 = self
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return self.__class__(
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xx1*xx2 + xy1*yx2,
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xx1*xy2 + xy1*yy2,
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yx1*xx2 + yy1*yx2,
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yx1*xy2 + yy1*yy2,
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xx2*dx1 + yx2*dy1 + dx2,
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xy2*dx1 + yy2*dy1 + dy2)
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def reverseTransform(self, other):
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"""Return a new transformation, which is the other transformation
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transformed by self. self.reverseTransform(other) is equivalent to
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other.transform(self).
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:Example:
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>>> t = Transform(2, 0, 0, 3, 1, 6)
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>>> t.reverseTransform((4, 3, 2, 1, 5, 6))
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<Transform [8 6 6 3 21 15]>
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>>> Transform(4, 3, 2, 1, 5, 6).transform((2, 0, 0, 3, 1, 6))
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<Transform [8 6 6 3 21 15]>
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>>>
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"""
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xx1, xy1, yx1, yy1, dx1, dy1 = self
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xx2, xy2, yx2, yy2, dx2, dy2 = other
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return self.__class__(
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xx1*xx2 + xy1*yx2,
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xx1*xy2 + xy1*yy2,
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yx1*xx2 + yy1*yx2,
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yx1*xy2 + yy1*yy2,
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xx2*dx1 + yx2*dy1 + dx2,
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xy2*dx1 + yy2*dy1 + dy2)
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def inverse(self):
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"""Return the inverse transformation.
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:Example:
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>>> t = Identity.translate(2, 3).scale(4, 5)
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>>> t.transformPoint((10, 20))
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(42, 103)
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>>> it = t.inverse()
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>>> it.transformPoint((42, 103))
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(10.0, 20.0)
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>>>
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"""
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if self == Identity:
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return self
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xx, xy, yx, yy, dx, dy = self
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det = xx*yy - yx*xy
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xx, xy, yx, yy = yy/det, -xy/det, -yx/det, xx/det
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dx, dy = -xx*dx - yx*dy, -xy*dx - yy*dy
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return self.__class__(xx, xy, yx, yy, dx, dy)
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def toPS(self):
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"""Return a PostScript representation
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:Example:
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>>> t = Identity.scale(2, 3).translate(4, 5)
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>>> t.toPS()
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'[2 0 0 3 8 15]'
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>>>
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"""
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return "[%s %s %s %s %s %s]" % self
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def __bool__(self):
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"""Returns True if transform is not identity, False otherwise.
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:Example:
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>>> bool(Identity)
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False
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>>> bool(Transform())
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False
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>>> bool(Scale(1.))
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False
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>>> bool(Scale(2))
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True
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>>> bool(Offset())
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False
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>>> bool(Offset(0))
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False
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>>> bool(Offset(2))
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True
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"""
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return self != Identity
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def __repr__(self):
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return "<%s [%g %g %g %g %g %g]>" % ((self.__class__.__name__,) + self)
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Identity = Transform()
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def Offset(x=0, y=0):
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"""Return the identity transformation offset by x, y.
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:Example:
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>>> Offset(2, 3)
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<Transform [1 0 0 1 2 3]>
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>>>
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"""
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return Transform(1, 0, 0, 1, x, y)
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def Scale(x, y=None):
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"""Return the identity transformation scaled by x, y. The 'y' argument
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may be None, which implies to use the x value for y as well.
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:Example:
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>>> Scale(2, 3)
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<Transform [2 0 0 3 0 0]>
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>>>
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"""
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if y is None:
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y = x
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return Transform(x, 0, 0, y, 0, 0)
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if __name__ == "__main__":
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import sys
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import doctest
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sys.exit(doctest.testmod().failed)
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