scientimate.distancecart¶
distxy, theta = scientimate.distancecart(x1, y1, x2, y2, CalcMethod='1d', dispout='no')
Description¶
Calculate distance from (x1,y1) to (x2,y2) on cartesian coordinate
Inputs¶
- x1
- x of start point (first point)
- y1
- y of start point (first point)
- x2
- x of end point (last point)
- y2
- y of end point (last point)
- CalcMethod=’1d’
- Distance calculation method‘1d’: use 1d array‘pdist2’: Use 2d distance function‘vector’: Use vectorized distance
- dispout=’no’
- Define to display outputs or not (‘yes’: display, ‘no’: not display)
Outputs¶
- distxy
- Distance from (x1,y1) to (x2,y2)returns M*N array where M=length(x1) and N=length(x2)mth row associated with mth point in (x,y)nth column is associated with nth point in (x2,y2)
- theta
- Angle from start point to end point in (Degree)returns M*N array where M=length(x1) and N=length(x2)mth row associated with mth point in (x,y)nth column is associated with nth point in (x2,y2)
Examples¶
import scientimate as sm
import numpy as np
x1=10*np.random.rand(100)
y1=10*np.random.rand(100)
x2=[2.5,5,7.5]
y2=[3,6,9]
distxy,theta=sm.distancecart(x1,y1,x2,y2,'1d','yes')
x1=10*np.random.rand(100)
y1=10*np.random.rand(100)
x2=100*np.random.rand(10)
y2=100*np.random.rand(10)
distxy,theta=sm.distancecart(x1,y1,x2,y2,'pdist2','yes')