Show only the necessary decimals
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6 changed files with 152 additions and 150 deletions
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@ -43,7 +43,7 @@ class Matrix:
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Example Usage:
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>>> Matrix([(1, 2), (3, 4)])
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Matrix(((1.000, 2.000,), (3.000, 4.000,)))
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Matrix(((1.0, 2.0,), (3.0, 4.0,)))
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"""
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self._entries = self.storage(
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self.storage(self.typing(x) for x in r) for r in data
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@ -73,7 +73,7 @@ class Matrix:
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Example Usage:
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>>> Matrix.from_columns([(1, 2), (3, 4)])
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Matrix(((1.000, 3.000,), (2.000, 4.000,)))
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Matrix(((1.0, 3.0,), (2.0, 4.0,)))
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"""
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return cls(data).transpose()
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@ -89,7 +89,7 @@ class Matrix:
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"""Text representation of a Matrix."""
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name = self.__class__.__name__
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args = ", ".join(
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"(" + ", ".join(f"{c:.3f}" for c in r) + ",)" for r in self._entries
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"(" + ", ".join(repr(c) for c in r) + ",)" for r in self._entries
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)
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return f"{name}(({args}))"
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@ -97,7 +97,7 @@ class Matrix:
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"""Human-readable text representation of a Matrix."""
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name = self.__class__.__name__
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first, last, m, n = self[0], self[-1], self.n_rows, self.n_cols
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return f"{name}(({first:.1f}, ...), ..., (..., {last:.1f}))[{m:d}x{n:d}]"
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return f"{name}(({first!r}, ...), ..., (..., {last!r}))[{m:d}x{n:d}]"
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@property
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def n_rows(self):
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@ -211,13 +211,13 @@ class Matrix:
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Example Usage:
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>>> Matrix([(1, 2), (3, 4)]) + Matrix([(2, 3), (4, 5)])
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Matrix(((3.000, 5.000,), (7.000, 9.000,)))
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Matrix(((3.0, 5.0,), (7.0, 9.0,)))
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>>> Matrix([(1, 2), (3, 4)]) + 5
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Matrix(((6.000, 7.000,), (8.000, 9.000,)))
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Matrix(((6.0, 7.0,), (8.0, 9.0,)))
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>>> 10 + Matrix([(1, 2), (3, 4)])
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Matrix(((11.000, 12.000,), (13.000, 14.000,)))
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Matrix(((11.0, 12.0,), (13.0, 14.0,)))
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"""
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# Matrix addition
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if isinstance(other, self.__class__):
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@ -247,13 +247,13 @@ class Matrix:
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Example Usage:
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>>> Matrix([(2, 3), (4, 5)]) - Matrix([(1, 2), (3, 4)])
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Matrix(((1.000, 1.000,), (1.000, 1.000,)))
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Matrix(((1.0, 1.0,), (1.0, 1.0,)))
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>>> Matrix([(1, 2), (3, 4)]) - 1
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Matrix(((0.000, 1.000,), (2.000, 3.000,)))
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Matrix(((0.0, 1.0,), (2.0, 3.0,)))
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>>> 10 - Matrix([(1, 2), (3, 4)])
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Matrix(((9.000, 8.000,), (7.000, 6.000,)))
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Matrix(((9.0, 8.0,), (7.0, 6.0,)))
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"""
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# As subtraction is the inverse of addition,
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# we first dispatch to .__neg__() to invert the signs of
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@ -286,23 +286,23 @@ class Matrix:
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Example Usage:
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>>> Matrix([(1, 2), (3, 4)]) * Matrix([(1, 2), (3, 4)])
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Matrix(((7.000, 10.000,), (15.000, 22.000,)))
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Matrix(((7.0, 10.0,), (15.0, 22.0,)))
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>>> 2 * Matrix([(1, 2), (3, 4)])
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Matrix(((2.000, 4.000,), (6.000, 8.000,)))
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Matrix(((2.0, 4.0,), (6.0, 8.0,)))
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>>> Matrix([(1, 2), (3, 4)]) * 3
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Matrix(((3.000, 6.000,), (9.000, 12.000,)))
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Matrix(((3.0, 6.0,), (9.0, 12.0,)))
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Matrix-vector and vector-matrix multiplication are not commutative.
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>>> from sample_package import Vector
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>>> Matrix([(1, 2), (3, 4)]) * Vector([5, 6])
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Vector((17.000, 39.000))
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Vector((17.0, 39.0))
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>>> Vector([5, 6]) * Matrix([(1, 2), (3, 4)])
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Vector((23.000, 34.000))
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Vector((23.0, 34.0))
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"""
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# Scalar multiplication
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if isinstance(other, numbers.Number):
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@ -334,7 +334,7 @@ class Matrix:
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Example Usage:
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>>> Matrix([(1, 2), (3, 4)]) / 4
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Matrix(((0.250, 0.500,), (0.750, 1.000,)))
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Matrix(((0.25, 0.5,), (0.75, 1.0,)))
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"""
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# As scalar division division is the same as multiplication
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# with the inverse, we dispatch to .__mul__().
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@ -409,7 +409,7 @@ class Matrix:
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Example Usage:
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>>> Matrix([(1, 2, 3)]).as_vector()
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Vector((1.000, 2.000, 3.000))
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Vector((1.0, 2.0, 3.0))
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"""
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if not (self.n_rows == 1 or self.n_cols == 1):
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raise RuntimeError("one dimension (m or n) must be 1")
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@ -424,9 +424,9 @@ class Matrix:
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Example Usage:
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>>> m = Matrix([(1, 2), (3, 4)])
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>>> m
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Matrix(((1.000, 2.000,), (3.000, 4.000,)))
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Matrix(((1.0, 2.0,), (3.0, 4.0,)))
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>>> m.transpose()
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Matrix(((1.000, 3.000,), (2.000, 4.000,)))
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Matrix(((1.0, 3.0,), (2.0, 4.0,)))
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"""
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return self.__class__(zip(*self._entries))
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@ -42,10 +42,10 @@ class Vector:
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Example Usage:
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>>> Vector([1, 2, 3])
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Vector((1.000, 2.000, 3.000))
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Vector((1.0, 2.0, 3.0))
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>>> Vector(range(3))
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Vector((0.000, 1.000, 2.000))
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Vector((0.0, 1.0, 2.0))
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"""
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self._entries = self.storage(self.typing(x) for x in data)
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if len(self) == 0:
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@ -54,14 +54,14 @@ class Vector:
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def __repr__(self):
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"""Text representation of a Vector."""
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name = self.__class__.__name__
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args = ", ".join(f"{x:.3f}" for x in self)
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args = ", ".join(repr(x) for x in self)
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return f"{name}(({args}))"
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def __str__(self):
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"""Human-readable text representation of a Vector."""
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name = self.__class__.__name__
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first, last, n_entries = self[0], self[-1], len(self)
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return f"{name}({first:.1f}, ..., {last:.1f})[{n_entries:d}]"
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return f"{name}({first!r}, ..., {last!r})[{n_entries:d}]"
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def __len__(self):
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"""Number of entries in a Vector."""
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@ -88,13 +88,13 @@ class Vector:
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Example Usage:
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>>> Vector([1, 2, 3]) + Vector([2, 3, 4])
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Vector((3.000, 5.000, 7.000))
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Vector((3.0, 5.0, 7.0))
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>>> Vector([1, 2, 3]) + 4
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Vector((5.000, 6.000, 7.000))
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Vector((5.0, 6.0, 7.0))
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>>> 10 + Vector([1, 2, 3])
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Vector((11.000, 12.000, 13.000))
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Vector((11.0, 12.0, 13.0))
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"""
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# Vector addition
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if isinstance(other, self.__class__):
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@ -119,13 +119,13 @@ class Vector:
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Example Usage:
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>>> Vector([7, 8, 9]) - Vector([1, 2, 3])
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Vector((6.000, 6.000, 6.000))
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Vector((6.0, 6.0, 6.0))
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>>> Vector([1, 2, 3]) - 1
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Vector((0.000, 1.000, 2.000))
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Vector((0.0, 1.0, 2.0))
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>>> 10 - Vector([1, 2, 3])
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Vector((9.000, 8.000, 7.000))
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Vector((9.0, 8.0, 7.0))
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"""
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# As subtraction is the inverse of addition,
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# we first dispatch to .__neg__() to invert the signs of
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@ -148,10 +148,10 @@ class Vector:
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20.0
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>>> 2 * Vector([1, 2, 3])
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Vector((2.000, 4.000, 6.000))
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Vector((2.0, 4.0, 6.0))
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>>> Vector([1, 2, 3]) * 3
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Vector((3.000, 6.000, 9.000))
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Vector((3.0, 6.0, 9.0))
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"""
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# Dot product
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if isinstance(other, self.__class__):
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@ -176,7 +176,7 @@ class Vector:
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Example Usage:
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>>> Vector([9, 6, 12]) / 3
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Vector((3.000, 2.000, 4.000))
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Vector((3.0, 2.0, 4.0))
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"""
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# As scalar division division is the same as multiplication
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# with the inverse, we dispatch to .__mul__().
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@ -253,9 +253,9 @@ class Vector:
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Example Usage:
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>>> v = Vector([1, 2, 3])
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>>> v.as_matrix()
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Matrix(((1.000,), (2.000,), (3.000,)))
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Matrix(((1.0,), (2.0,), (3.0,)))
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>>> v.as_matrix(column=False)
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Matrix(((1.000, 2.000, 3.000,)))
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Matrix(((1.0, 2.0, 3.0,)))
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"""
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if column:
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return self.matrix_cls([x] for x in self)
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