Kalman-and-Bayesian-Filters.../baseball.py
2014-06-02 23:08:47 -07:00

83 lines
1.8 KiB
Python

# -*- coding: utf-8 -*-
"""
Spyder Editor
This temporary script file is located here:
/home/rlabbe/.spyder2/.temp.py
"""
"""
Computes the trajectory of a stitched baseball with air drag.
Takes altitude into account (higher altitude means further travel) and the
stitching on the baseball influencing drag.
This is based on the book Computational Physics by N. Giordano.
The takeaway point is that the drag coefficient on a stitched baseball is
LOWER the higher its velocity, which is somewhat counterintuitive.
"""
import math
import matplotlib.pyplot as plt
def a_drag (vel, altitude):
""" returns the drag coefficient of a baseball at a given velocity (m/s)
and altitude (m).
"""
v_d = 35
delta = 5
y_0 = 1.0e4
val = 0.0039 + 0.0058 / (1 + math.exp((vel - v_d)/delta))
val *= math.exp(-altitude / y_0)
return val
def compute_trajectory(v_0_mph, theta, v_wind_mph=0, alt_ft = 0.0, dt = 0.01):
### comput
theta = math.radians(theta)
v_0 = v_0_mph * 0.447 # mph to m/s
v_x = v_0 * math.cos(theta)
v_y = v_0 * math.sin(theta)
v_wind = v_wind_mph * 0.447 # mph to m/s
altitude = alt_ft / 3.28 # to m/s
ground_level = altitude
x = [0.0]
y = [altitude]
i = 0
while y[i] >= ground_level:
g = 9.8
v = math.sqrt((v_x - v_wind) **2+ v_y**2)
x.append(x[i] + v_x * dt)
y.append(y[i] + v_y * dt)
v_x = v_x - a_drag(v, altitude) * v * (v_x - v_wind) * dt
v_y = v_y - a_drag(v, altitude) * v * v_y * dt - g * dt
i += 1
return (x,y)
if __name__ == "__main__":
x,y = compute_trajectory(v_0_mph = 110., theta=35., v_wind_mph = 0., alt_ft=5000.)
plt.plot (x, y)
plt.show()