[](https://travis-ci.org/t-o-k/scikit-vectors)
# Functions to create n-dimensional vector classes
This is a Python library with functions that create vector classes with 2, 3 or an arbitrary number of dimensions.
The name of the classes to be created, and the names of their vector components are set when calling the functions. The brackets for the vectors and the seperators for their components can also be given as arguments to these functions.
There are 11 functions that create vector classes. Each of them creates vector classes with a certain functionality. 8 of the functions create vector classes with a cartesian coordinate system and 4 of the functions create vector classes with tolerances for comparing vectors.
Created vector classes can be extended with extra functionality for processing their vector instances and ther component values.
Some of the vector classes are suitable for using e.g. NumPy's ndarrays, Pandas Series or SymPy's algebraic expressions as component values.
## Project homepage
https://github.com/t-o-k/scikit-vectors
## Project wiki
https://github.com/t-o-k/scikit-vectors/wiki
The wiki has links to documents that shows how created vector classes can be used.
## Installation
scikit-vectors requires Python version 3.5 or higher.
```shell
pip install scikit-vectors
```
## Examples
In addition to the short examples below, there are some more elaborate ones here:
https://github.com/t-o-k/scikit-vectors_examples
### Simple examples
```python
>>> from math import pi
>>> from skvectors import create_class_Cartesian_3D_Vector
>>> CV3D = create_class_Cartesian_3D_Vector('CV3D', 'xyz', brackets=[ '<< ', ' >>' ])
>>> u = CV3D(3, 0, -4)
>>> print(u)
<< 3, 0, -4 >>
>>> v = CV3D(1, -2, 3) * 2
>>> repr(v)
'CV3D(x=2, y=-4, z=6)'
>>> u.normalize()
CV3D(x=0.6, y=0.0, z=-0.8)
>>> u.dot(v)
-18
>>> u.cross(v)
CV3D(x=-16, y=-26, z=-12)
>>> u = CV3D(4.5, -3.0, -1.5)
>>> v = CV3D(-3, -3, -3)
>>> u.angle(v) / pi
0.49999999999999994
>>> u = CV3D(5, -4, -3)
>>> v = CV3D(-2, 0, 2)
>>> u.project(v)
CV3D(x=4.0, y=-0.0, z=-4.0)
>>> u = CV3D(-5, 0, 0)
>>> v = CV3D(0, 12, 0)
>>> (u - v).length()
13.0
>>> u = CV3D(-3, 4, -5)
>>> u.rotate_x(pi)
CV3D(x=-3, y=-3.9999999999999996, z=5.000000000000001)
>>> u = CV3D(-3, 4, -5)
>>> v = CV3D(0, -10, -8)
>>> u.axis_rotate(v, -pi)
CV3D(x=2.999999999999999, y=-4.0, z=5.0)
>>> u = CV3D(-3, 4, -5)
>>> v = CV3D(-6, 0, 0)
>>> w = CV3D(0, 0, 7)
>>> u.reorient(v, w)
CV3D(x=-5.0, y=4.0, z=3.0)
>>> u = CV3D(0, -1, 2)
>>> v = CV3D(-3, 4, -5)
>>> w = CV3D(3, 1, 2)
>>> u.stp(v, w)
-21
>>>
```
```python
>>> from skvectors import create_class_Simple_Vector
>>> SV = create_class_Simple_Vector('SV', [ 'first', 'second', 'third', 'fourth', 'fifth', 'sixth' ])
>>> u = SV(3, 1, -2, -3, 4, 2)
>>> u
SV(first=3, second=1, third=-2, fourth=-3, fifth=4, sixth=2)
>>> v = SV(2, -2, 1, 3, 1, 4)
>>> u * v + 10
SV(first=16, second=8, third=8, fourth=1, fifth=14, sixth=18)
>>> 2 * (u - v)
SV(first=2, second=6, third=-6, fourth=-12, fifth=6, sixth=-4)
>>> u**v / 2
SV(first=4.5, second=0.5, third=-1.0, fourth=-13.5, fifth=2.0, sixth=8.0)
>>> u *= 2 / v
>>> u
SV(first=3.0, second=-1.0, third=-4.0, fourth=-2.0, fifth=8.0, sixth=1.0)
>>> u.first
3.0
>>> (u + v).sixth
5.0
>>> u.fifth += 20
>>> u
SV(first=3.0, second=-1.0, third=-4.0, fourth=-2.0, fifth=28.0, sixth=1.0)
>>> u.c_add_third(24)
SV(first=3.0, second=-1.0, third=20.0, fourth=-2.0, fifth=28.0, sixth=1.0)
>>> u.c_imul_bar_second(1000)
>>> u
SV(first=3000.0, second=-1.0, third=-4000.0, fourth=-2000.0, fifth=28000.0, sixth=1000.0)
>>> v = SV(0, 1, 2, 3, 4, 5) / 6
>>> round(v, 3)
SV(first=0.0, second=0.167, third=0.333, fourth=0.5, fifth=0.667, sixth=0.833)
>>>
```
### Not so simple example with NumPy
```python
>>> from skvectors import create_class_Cartesian_3D_Vector
>>> import numpy as np
>>> NP3 = \
... create_class_Cartesian_3D_Vector(
... name = 'NP3',
... component_names = [ chr(0x03b1)*2, chr(0x03b2)*2, chr(0x03b3)*2 ],
... brackets = [ chr(0x2770)*2 + ' ', ' ' + chr(0x2771)*2 ],
... sep = ', ',
... cnull = np.array([ 0., 0., 0., 0. ]),
... cunit = np.array([ 1., 1., 1., 1. ]),
... functions = \
... {
... 'eq': np.equal,
... 'ne': np.not_equal,
... 'not': np.logical_not,
... 'and': np.logical_and,
... 'or': np.logical_or,
... 'all': np.all,
... 'any': np.any,
... 'min': np.minimum,
... 'max': np.maximum,
... 'abs': np.absolute,
... 'int': np.rint,
... 'ceil': np.ceil,
... 'copysign': np.copysign,
... 'log10': np.log10,
... 'cos': np.cos,
... 'sin': np.sin,
... 'atan2': np.arctan2,
... 'pi': np.pi
... }
... )
>>> NP3.component_names()
['αα', 'ββ', 'γγ']
>>> u = \
... NP3(
... np.random.randint(-10, 10, size=4),
... np.random.randint(-10, 10, size=4),
... np.random.randint(-10, 10, size=4)
... )
>>> u
NP3(αα=array([ 7., -8., 5., 7.]), ββ=array([-1., -4., 7., -4.]), γγ=array([ 1., 6., -2., 8.]))
>>> u /= 10
>>> u
NP3(αα=array([ 0.7, -0.8, 0.5, 0.7]), ββ=array([-0.1, -0.4, 0.7, -0.4]), γγ=array([ 0.1, 0.6, -0.2, 0.8]))
>>> v = \
... NP3(
... np.array([ -3, 5, -1, 2 ]),
... np.array([ 0, 12, 0, -1 ]),
... np.array([ 4, 0, 0, 2 ])
... )
>>> str(v)
'❰❰ [-3. 5. -1. 2.], [ 0. 12. 0. -1.], [ 4. 0. 0. 2.] ❱❱'
>>> v.length()
array([ 5., 13., 1., 3.])
>>> v.contains(np.array([ 4.0, 2.0, -1.0, 3.0 ]))
array([ True, False, True, False], dtype=bool)
>>> (u - v) * 10
NP3(αα=array([ 37., -58., 15., -13.]), ββ=array([ -1., -124., 7., 6.]), γγ=array([-39., 6., -2., -12.]))
>>> w = NP3(1, -1, 0)
>>> w
NP3(αα=array([ 1., 1., 1., 1.]), ββ=array([-1., -1., -1., -1.]), γγ=array([ 0., 0., 0., 0.]))
>>> u.reorient(v, w)
NP3(αα=array([ 0.1771821 , -0.0652714 , -0.84852814, 0.76479998]), ββ=array([ 0.65801471, 0.8920424 , -0.14142136, -0.83797539]), γγ=array([-0.21359575, 0.6 , -0.2 , 0.05364919]))
>>> u.axis_rotate(NP3(1, -2, 1), np.pi/4)
NP3(αα=array([ 0.51492277, -0.76733621, 0.21325376, 0.26084032]), ββ=array([ 0.00486333, -0.74556654, 0.80444152, -0.53626169]), γγ=array([ 0.49480389, -0.12379688, 0.29562928, 0.96663629]))
>>>
```
## Running the tests
```shell
git clone https://github.com/t-o-k/scikit-vectors
cd scikit-vectors
python3 -m unittest discover
```
Here's more information:
https://travis-ci.org/t-o-k/scikit-vectors
## License information
See the file LICENSE for information on terms & conditions for usage, and a DISCLAIMER OF ALL WARRANTIES.
## Author
Tor Olav Kristensen
http://subcube.com
scikit-vectors-0.6.5.tar.gz （51个子文件） 
scikit-vectors-0.6.5 
MANIFEST.in 46B PKG-INFO 9KB scikit_vectors.egg-info PKG-INFO 9KB
SOURCES.txt 2KB top_level.txt 10B dependency_links.txt 1B setup.cfg 38B setup.py 1KB README.md 7KB skvectors tolerant_cartesian_3d_vectors.py 2KB helper_functions.py 6KB tolerant_cartesian_vectors.py 1KB tests test_cartesian_2d_vector_methods_2d.py 13KB test_vector_methods_3d.py 11KB test_tolerant_cartesian_vector_methods_4d.py 6KB test_simple_vector_methods_3d.py 38KB test_fundamental_vector_methods_3d.py 27KB test_cartesian_3d_vector_methods_3d.py 29KB __init__.py 0B test_create_vector_classes.py 11KB test_cartesian_vector_methods_3d.py 22KB vectors.py 15KB simple_vectors.py 11KB __init__.py 841B tolerant_versatile_vectors.py 8KB cartesian_2d_vectors.py 6KB cartesian_vectors.py 10KB versatile_vectors.py 6KB doc Using_a_Cartesian_2D_Vector_Class.ipynb 10KB
Using_a_Tolerant_Cartesian_2D_Vector_Class.pdf 114KB Using_a_Simple_Vector_Class.ipynb 23KB Using_a_Tolerant_Cartesian_3D_Vector_Class.pdf 116KB Using_a_Tolerant_Cartesian_Vector_Class.ipynb 20KB Using_a_Cartesian_3D_Vector_Class.ipynb 13KB Using_a_Cartesian_Vector_Class.ipynb 14KB Using_a_Tolerant_Cartesian_3D_Vector_Class.ipynb 20KB Using_a_Tolerant_Cartesian_2D_Vector_Class.ipynb 20KB Using_a_Fundamental_Vector_Class.pdf 123KB Using_a_Cartesian_Vector_Class.pdf 105KB Using_a_Simple_Vector_Class.pdf 115KB Using_a_Fundamental_Vector_Class.ipynb 24KB Using_a_Tolerant_Cartesian_Vector_Class.pdf 116KB .ipynb_checkpoints Using_a_Vector_Class-checkpoint.ipynb 11KB Using_a_Cartesian_2D_Vector_Class.pdf 98KB Using_a_Cartesian_3D_Vector_Class.pdf 102KB Using_a_Vector_Class.pdf 98KB Using_a_Vector_Class.ipynb 11KB tolerant_cartesian_2d_vectors.py 2KB cartesian_3d_vectors.py 10KB fundamental_vectors.py 16KB make_tolerant.py 7KB资源评论
