Data from experiments with Handheld Tactile Device 04/11/2016
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Type of Data:

The data collected includes Active Thermal data, Passive Thermal Data,
Data from the LM35 sensor, Force data, Contact Mic data, Accelerometer data,
and the Estimated Average Velocity.
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Data File Format

The data is formated in a Pickle file. The data comes in eight columns.

Column 1: Time Data
Column 2: Active Thermal Data
Column 3: Passive Thermal Data
Column 4: LM35 Sensor Data
Column 5: Force Data
Column 6: Contact Mic Data
Column 7: Accelerometer Data
Column 8: Estimated Average Velocity Data


Note 1: Time starts at t = 0 when the handheld device comes in contact with
the object. The time before this will be represented as negative values

Note 2: The LM35 Sensor was unplugged for this experiment so that data will be
represented as zeros in column 4

Note 3: The Estimated Average Velocity was only recorded once when the device
was pushed down on an object. There will only be one value in the first row
while the rest will be "None"

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Accessing and Plotting the Data
The code used here accesses the data from the pickle file using the pickle
module. Follow this link to see the python documentation of pickle
https://docs.python.org/3/library/pickle.html#what-can-be-pickled-and-unpickled

We used Python 2.7.12 on Ubuntu 12.04 to create the pickle file.
You can look at the documentation that corresponds to the version of Python
that you are using.

We also used the Plotly api to generate the graphs you see on the website.
To use the api, create an account on https://plot.ly/ . Once you set up your
account, follow the setup instructions to use the Plotly api with python. The
setup instructions can be found here: https://plot.ly/python/getting-started/
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Sample Code
The code below uses Python 2.7.12 on Ubuntu 14.04 to access the data and
generate graphs using the plotly api.

#!/usr/bin/python
# -*- coding: utf-8 -*-
import pickle as pk
import plotly.plotly as py
import plotly.graph_objs as go

## Retrieves data from the Pickle File
def load_pickle(filename):
    try:
        p = open(filename, 'r')
    except IOError:
        print("The file cannot be opened")
        return None
    try:
        pickle_obj = pk.load(p)
    except ValueError:
        print("Loading Pickle File failed. Trying Again.")
        p.close()
        p = open(filename, 'r')
        pickle_obj = pk.load(p)
    p.close()
    return pickle_obj

## Plots the data using the plotly api
def plot_atherm_ply(data):
    t = []
    atherm = []
    for item in data:
        t.append(item[0])
        atherm.append(item[1])

    trace0 = go.Scatter(
        x = t,
        y = atherm,
        mode = 'line',
        line = dict(
                color = ('rgb(205, 12, 24)'),
                width = 2
            )
        )
    plot_data = [trace0]
    plot_layout = dict(
        title = 'Active Thermal Temperature over Time',
        xaxis = dict(title = 'Time (seconds)'),
        yaxis = dict(title = 'Temperature (°C)'),
        )
    figure = dict(data = plot_data, layout = plot_layout)
    py.plot(figure)
def plot_ptherm_ply(data):
    t = []
    ptherm = []
    for item in data:
        t.append(item[0])
        ptherm.append(item[2])
    trace0 = go.Scatter(
        x = t,
        y = ptherm,
        mode = 'line',
        line = dict(
            width = 2
            )
        )
    plot_data = [trace0]
    plot_layout = dict(
        title = 'Passive Thermal Temperature over Time',
        xaxis = dict(title = 'Time (seconds)'),
        yaxis = dict(title = 'Temperature (°C)'),
        )
    figure = dict(data = plot_data, layout = plot_layout)
    py.plot(figure)

data = load_pickle('trial_5_processed.pkl')
plot_ptherm_ply(data)
plot_atherm_ply(data)