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"""

Data resources:

- Main Resources:

- http://www.tomshardware.com/charts/hdd-charts-2013/

- http://www.tomshardware.com/charts/ssd-charts-2013/benchmarks,129.html

- http://en.wikipedia.org/wiki/List_of_device_bit_rates

- Also important

- http://en.wikipedia.org/wiki/Intel_QuickPath_Interconnect

- http://en.wikipedia.org/wiki/DDR3_SDRAM

- http://en.wikipedia.org/wiki/Hard_disk_drive

- http://www.storagereview.com/samsung_ssd_840_review_tlc

- http://en.wikipedia.org/wiki/Solid-state_drive

"""

from collections import defaultdict

import csv

import numpy as np

import pylab as py

def plot_field(names, type, data):

N = len(names)

ind = np.arange(N)

width = 0.35

ax = py.gca()

bar = ax.bar(ind, data['avg'], width, color='r', yerr=data['extend'])

ax.set_ylabel('%s (%s)' % (type, data['unit']))

ax.set_xticks(ind + width)

ax.set_xticklabels([x.replace(" ", '\n')

for x in names], rotation=45, ha='right')

ax.set_yscale('log')

return bar

if __name__ == "__main__":

data = list(csv.DictReader(open("memory_types_data.csv")))

names = [line['type'] for line in data]

values = defaultdict(dict)

for field in data[0].iterkeys():

if field == "type":

continue

f, unit = field.split(" ")

t, name = f.split("_", 1)

values[name]['unit'] = unit.strip('()')

values[name][t] = np.asarray([float(line[field]) for line in data])

for field in values.iterkeys():

values[field]['avg'] = (

values[field]['min'] + values[field]['max']) / 2.0

values[field]['extend'] = values[field]['max'] - values[field]['avg']

for i, f in enumerate(values.iterkeys()):

py.subplot(2, 2, i)

plot_field(names, f, values[f])

py.suptitle("Characteristics of various memory units")

py.savefig("images/memory_types.png")

py.show()