# Design Example
# Quantitative Analysis: Version 1
# For demonstration purposes only

import matplotlib.pyplot as plt

def read_measurements(filename):
    """
    Returns a list of 4-tuples, where each tuple represents a line in the given
    file and is of the form (site, temp, salt, oxygen).
    """
    datafile = open(filename)
    lines = datafile.readlines()
    datafile.close()

    measurements = []
    for row in lines[1:]:
        values = row.split()
        row_tup = (values[0], float(values[1]), float(values[2]), float(values[3]))
        measurements.append(row_tup)

    return measurements

def STplot(measurements):
    """
    Given a list of 4-tuples, generates a scatter plot comparing salinity and
    temperature.
    """
    xs = []
    ys = []
    for row in measurements:
        xs.append(row[2])
        ys.append(row[1])

    plt.plot(xs, ys)
    plt.xlabel("salt")
    plt.ylabel("temp")
    plt.show()

def minimumO2(measurements):
    """
    Given a list of 4-tuples, returns the minimum value of the oxygen
    measurement.
    """
    o2s = [row[3] for row in measurements]

    # o2s = []
    # for row in measurements:
    #     o2s.append(row[3])

    return min(o2s)

# Sample client calls:
row_list = read_measurements("sample_quant.txt")
STplot(row_list)
print "minimum o2 in file:", minimumO2(row_list)