2840.sagews

# A simple function to parse our data file

import os, sys
import datetime

class Record():
    def __init__(self, timestamp, kind, values):
        self.timestamp = timestamp
        self.kind = kind
        self.values = values

def parseRecord(timestamp, kind, rest):
    floats = [float(x.strip()) for x in rest.split(",")]
    r = Record(timestamp, kind, floats)
    return r
        
def parseLog(logfile):
    records = []
    with open(logfile, "r") as f:
        for l in f:
            e = l.split(":")
            r = parseRecord(float(e[0]), e[1].strip(), e[2].strip())
            records.append(r)
    return records

recs = parseLog(DATA+"WorkToJeffs.log")

# Filter out the acceleration and GPS data
acc = [r for r in recs if r.kind == "ACL"]
gps = [r for r in recs if r.kind == "LOC"]
speed = [r for r in recs if r.kind == "VEL"]

# Sanity check
print len(acc), len(gps), len(speed)

4213 153 153

# Plot lateral acceleration
t=[r.timestamp for r in acc]
latAcc=[r.values[0] for r in acc]
p = list_plot(zip(t,latAcc), plotjoined=True)
p.axes_labels(["Time", "Lateral Acceleration (G's) (positive is left turn)"])
p.show()

# Plot front/back acceleration
fbAcc=[r.values[1] for r in acc]
p = list_plot(zip(t,fbAcc), plotjoined=True)
p.axes_labels(["Time", "Braking/Accelerating (G's) (positive is braking)"])
p.show()

# Plot a friction circle
import numpy
#title = text("Acceleration (G's)", (0,1), rgbcolor='black',fontsize=15)
guides = [circle((0,0), r, color='grey', zorder=1) for r in numpy.arange(0,.7501,.25)]
p = scatter_plot(zip(latAcc,fbAcc), edgecolor='red', facecolor='red', marker="o", markersize=4, aspect_ratio=1, axes_labels=("left turn", "braking"))
(sum(guides)+p)

# Plot GPS location
long=[r.values[1] for r in gps]
lat=[r.values[0] for r in gps]
list_plot(zip(long,lat), plotjoined=False, aspect_ratio=1)

# Now show speed as a color along the route
locPoints = [] # [point(p) for p in zip(long, lat)]
allColors = [hue(x) for x in numpy.arange(0, 1, 1/len(lat))]
redToGreen = [(1-x,x,0) for x in numpy.arange(0, 1, 1/len(lat))]
speeds = [r.values[0] for r in speed]
maxSpeed = max(speeds)
for (x,y,s) in zip(long, lat, speeds):
    g = s/maxSpeed
    r = 1-g
    b = 0
    locPoints.append(point((x, y), color=(r,g,b)))
sum(locPoints)

# Plot speed vs. time
x = [r.timestamp for r in speed]
y = [r.values[0] for r in speed]
# Convert to mph
y = [s*2.23693629 for s in y]
p = list_plot(zip(x,y), plotjoined=True)
p.axes_labels(["Time", "Speed (mph)"])
p.show()

print "Top speed was %.2f mph." % max(y)

Top speed was 41.73 mph.

# Sage is the shit.