Solutions to the exercises of part 3

Finding the total mass of a peptide chain

First the module, contained in a file called PeptideChain.py:

import string

# Translation table from one-letter codes to three-letter codes.
residue_name = {'a': 'ala', 'r': 'arg', 'n': 'asn', 'd': 'asp', 'c': 'cys',
		'q': 'gln', 'e': 'glu', 'g': 'gly', 'h': 'his', 'i': 'ile',
		'l': 'leu', 'k': 'lys', 'm': 'met', 'f': 'phe', 'p': 'pro',
		's': 'ser', 't': 'thr', 'w': 'trp', 'y': 'tyr', 'v': 'val'}

# Table of residue masses.
residue_mass = {'ala': 71.0790184654,
		'arg': 157.196106437,
		'asn': 114.104059219,
		'asp': 114.080688839,
		'cys': 103.143406585,
		'gln': 128.131048075,
		'glu': 128.107677695,
		'gly': 57.0520296093,
		'his': 137.141527428,
		'ile': 113.159985034,
		'leu': 113.159985034,
		'lys': 129.182660137,
		'met': 131.197384297,
		'phe': 147.17714379,
		'pro': 97.1170442246,
		'ser': 87.0783231891,
		'thr': 101.105312045,
		'trp': 186.213916723,
		'tyr': 163.176448514,
		'val': 99.1329961777}

# The additional mass of a peptide chain due to the termini.
terminus_mass = 18.0152566767

# The function that does the calculation
def totalMass(peptide_chain):
    mass = terminus_mass
    for residue in peptide_chain:
	residue = string.lower(residue)
	if len(residue) == 1:
	    residue = residue_name[residue]
	mass = mass + residue_mass[residue]
    return mass

Note the use of two dictionaries to store the information about residues.

Next, a simple application that uses this module:

from PeptideChain import totalMass

print totalMass('AEG')
print totalMass(['ala', 'arg', 'gly', 'his'])

Reading and writing matrices

The module MatrixIO.py:

from Scientific.IO.TextFile import TextFile
import string
import Numeric

def readMatrix(filename):
    rows = []
    for line in TextFile(filename):
        columns = []
        for number in string.split(line):
            columns.append(string.atof(number))
	rows.append(columns)
    return Numeric.array(rows)

def writeMatrix(a, filename):
    file = TextFile(filename, 'w')
    for line in a:
	for number in line:
	    file.write(`number` + ' ')
	file.write('\n')
    file.close()

In the first function, the function string.atof is applied to all elements of a list. This is such a frequent operation that a special shorthand has been introduced: the function map(function, sequence) applies a function to each element of a sequence and returns a list of the results. This makes it possible to replace the lines

        columns = []
        for number in string.split(line):
            columns.append(string.atof(number))

by the single line columns = map(string.atof, string.split(line)).

Data processing

First the generation of the test data:

import MatrixIO
import Numeric

for i in range(1, 51):
    time = Numeric.arrayrange(10.)
    values = 4.*Numeric.ones(10)
    parameters = (i, -3.5)
    data = Numeric.zeros((11, 2), Numeric.Float)
    data[0] = parameters
    data[1:, 0] = time
    data[1:, 1] = values
    MatrixIO.writeMatrix(data, "data"+`i`)

Note how everything is put into one large array before output; this trick allows the use of the matrix output function written in the last exercise. The result of the analysis program must be a constant time series whose value is twice the sum of the integers from 1 to 50, i.e. 50*51 = 2550.

And now the program that "analyses" the data files.

import MatrixIO
import Numeric
import Gnuplot

total = 0.

for i in range(1, 51):
    data = MatrixIO.readMatrix("data"+`i`)
    time = data[1:, 0]
    values = data[1:, 1]
    parameters = data[0]
    total = total + parameters[0]*Numeric.sqrt(values)

plot_data = Numeric.transpose(Numeric.array([time, total]))
Gnuplot.plot(plot_data)

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