myvectors 1.1

Exploring VECTOR Mathematics

vector_python_package

:V:E:C:T:O:R:S: made easy This version 1.1 is named as "Suryakant"

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A python package for vector maths

Installation of the Package

pip install myvectors 

having installed "math" python library makes the things smoother

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** Youtube Video Tutorials (https://youtube.com/playlist?list=PL6LEAq5DrlOScWUPGQ4YHr-naw-H7OtKz) (https://youtu.be/Tr-d4uQIgqU)

** Colab Notebook (dont forget to check the colab notebook) (https://colab.research.google.com/drive/1brLl8gHiW6yGqMwDKUrsOXMXHm5I_MBW?usp=sharing)

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Package Functionalities

The vector is represented by LIST[data structure] in the package

ex: if v(2,3,4) is a vector at (2,3,4) in space then it should be written as v1=[2,3,4] where v1 is a list

1.Magnitude of a vector : A=[2,3,4] magnitude of a given vector

import myvectors
from myvectors import mag
A=[2,3,4]
mag(A)

Output : float number

2. Dot product : A=[2,3,4] B = [1,1,2]

Arguments : two vectors whose dot product is required

import myvectors
A=[2,3,4]  
B = [1,1,2]
from myvectors import dot
dot(A,B)

3. Cross product : A=[2,3,4] B = [1,1,2]

Arguments : two vectors whose cross product is required

import myvectors
A=[2,3,4]  
B = [1,1,2] 
from myvectors import cross
cross(A,B)

4.Projection : A=[1,4,0] B=[4,2,4]

Arguments : two vectors here first vector passed as argument is projected over the second vector

import myvectors
A=[1,4,0] 
B=[4,2,4]
from myvectors import projection
projection(A,B)

Output : number i.e projection of A on B

5.Angle : Gives Angle between two vectors A=[3,4,-1] B=[2,-1,1]

Arguments : two vectors , cos/sin , mode(if mode = 0 then angle is in terms of radian if mode = 1 then degrees)

import myvectors
from myvectors import angle
A=[3,4,-1] 
B=[2,-1,1] 
angle(A,B,"cos",0) # angle in terms of cos and radians
angle(A,B,"sin",1) # angle in terms of sin and degrees

Output : angle in radians if mode = 0 or in terms of degree if mode = 1

6. Triangle area : the vertices of triangle be A=[1,1,1] B=[1,2,3] C=[2,3,1]

Arguments : the co - ordinates of the vertices of the triangle

import myvectors
A=[1,1,1] 
B=[1,2,3] 
C=[2,3,1]
from myvectors import trianglearea
trianglearea(A,B,C)

Output : Area

7.sectionsutram : divide the line joining two points in the ratio r1:r2 A=[2,3,4] B=[4,1,-2]

Arguments : two vectors, ei representing type of division ('e'= external and 'i' = internal),r1,r2

import myvectors
A=[2,3,4] 
B=[4,1,-2]
r1 = 1
r2 = 2
from myvectors import sectionsutram
sectionsutram(A,B,ei,r1,r2)

Output: (A list of length 3) basically vector point with x,y,z co-ordinates

8. collinear or not : checks if three vectors are collinear

A=[1,2,3] B=[11,8,12] C=[10,5,7]

import myvectors
A=[1,2,3] 
B=[11,8,12] 
C=[10,5,7]
from myvectors import collinear3
collinear3(A,B,C)

Output : If collinear then output is 1 else 0

9. Scalar Triple Product : if three vectors A,B,C then there scalar triple product is =((AXB)dotproduct(C))

A=[1,2,3] B=[11,8,12] C=[10,5,7]

import myvectors
A=[1,2,3] 
B=[11,8,12] 
C=[10,5,7]
from myvectors import s_triplepro
s_triplepro(A,B,C)

10. Vector Triple Product : if three vectors A,B,C then there scalar triple product is =((AXB)XC)

A=[1,2,3] B=[11,8,12] C=[10,5,7]

import myvectors
A=[1,2,3] 
B=[11,8,12] 
C=[10,5,7]
from myvectors import v_triplepro
v_triplepro(A,B,C)

11. Vector visualization in 3D space: A given vector say 'V' is visualized in 3-Dimensional space

A = [0,0,2]

import myvectors
A = [0,0,2]
from myvectors import draw_vector
draw_vector(A)

Output : A vector representation in 3-D space.

12. Vector Direction Cosines: Given a vector 'V' it gives the diection cosine

A = [1,2,3]

import myvectors
A = [1,2,3]
from myvectors import direction_Cosine
direction_Cosine(A)

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