from scitools.std import *
import scitools.filetable as ft
infile = open('xy.dat', 'r')
x, y = ft.read_columns(infile)
infile.close()
print 'The maximum y coordinate is %6.4f' % max(y)
print 'The minimum y coordinate is %6.4f' % min(y)
plot(x,y, xlabel='x', ylabel='y')
raw_input('Press Enter to quit: ')
'''
python read_2columns_filetable.py
The maximum y coordinate is 0.9482
The minimum y coordinate is -0.9482
Press Enter to quit:
'''
'''
Uses the Trapezoidal rule to calculate the velocity
at time step k (each time step is dt) from discrete measurements
of acceleration
k specifices the time to measure velocity (k * dt)
dt is the time step
a is the list of acceleration measurements
The function returns a velocity
'''
# note: k < len(a)
return dt*(1./2*a[0] + 1./2*a[-1] + sum(a[1:k]))
filename = 'acc.dat'
infile = open(filename, 'r')
accel = ft.read_columns(infile)[0]
infile.close()
print 'v(t_k) = %f' % (v(dt, k, accel))
plot(range(len(accel)),accel,
xlabel='Units of time elapsed (delta t)',
ylabel='Accelaration m/s^2',
title='Acceleration v. Time')
raw_input('Press Enter to quit: ')
'''
python acc2vel_v1.py .5 40
v(t_k) = 9.839308
Press Enter to quit:
'''
import scitools.filetable as ft def v_pos(k,x,s): ''' Simple formula for calculating velocity in one dimension for an array with positions recorded in increments of time step s 0 <= k < len(x)-1 The function returns the one-dimensional velocity ''' return (x[k+1] - x[k])/float(s) filename = 'pos.dat' infile = open(filename, 'r') s = float(infile.readline()) x,y = ft.read_columns(infile) infile.close() t = [s*i for i in range(0,len(x))] vx = [0]*(len(x)-1) vy = [0]*(len(y)-1) for i in range(len(x)-1): vx[i] = v_pos(i,x,s) vy[i] = v_pos(i,y,s) figure() plot(t[:-1],vx, xlabel='Time (s)', ylabel='Velocity in x-direction', title='V_x v. time')
# -*- coding: utf-8 -*-
import glob, os, shutil
from math import cos, pi, exp
from numpy import *
import scitools.filetable as ft
#from scitools.easyviz import *
import sys
file = open('result.out', 'r')
file.readline()
X, Y, Z, U, V, W, P, T = ft.read_columns(file)
for i in xrange(X.shape[0]):
print X[i], T[i]
'''
Uses the Trapezoidal rule to calculate the velocity
at time step k (each time step is dt) from discrete measurements
of acceleration
k specifices the time to measure velocity (k * dt)
dt is the time step
a is the list of acceleration measurements
The function returns a velocity
'''
# note: k < len(a)
return dt * (1. / 2 * a[0] + 1. / 2 * a[-1] + sum(a[1:k]))
filename = 'acc.dat'
infile = open(filename, 'r')
accel = ft.read_columns(infile)[0]
infile.close()
print 'v(t_k) = %f' % (v(dt, k, accel))
plot(range(len(accel)),
accel,
xlabel='Units of time elapsed (delta t)',
ylabel='Accelaration m/s^2',
title='Acceleration v. Time')
raw_input('Press Enter to quit: ')
'''
python acc2vel_v1.py .5 40
v(t_k) = 9.839308
Press Enter to quit:
'''