# CSE 140 13wi Lecture 16
# Design Example
# Used to demonstrate the "wishful thinking" approach to creating functions.

import matplotlib.pyplot as plt
import csv

def days_in_month():
    """
    Returns the number of days in the month to process
    """
    # Stub function
    # TODO: Write more detailed implementation
    return 30

def average_delay(rows):
    """
    Given a list of airline delay rows, returns the average delay.
    """
    delays = []
    for row in rows:
        delays.append(float(row["DELAY"]))
    return sum(delays) / len(delays)

def get_delay_vector(rows, days):
    """
    Given a list of rows and days, returns a list containg the average delay on
    each day.
    """
    output = []
    for day in days:
        day_rows = filter_by_column(rows, "DAY_OF_MONTH", str(day))
        output.append(average_delay(day_rows))
    return output

def filter_by_column(rows, column, value):
    """
    Given a list of rows, a column, and a column value, returns a list of all
    rows with the given value in the given column.
    """
    filtered_rows = []
    for row in rows:
        if row[column] == value:
            filtered_rows.append(row)
    return filtered_rows

def plot_airport(rows, airport):
    """
    Given an airport and a list of delay data rows, plots its average delay per
    day.
    """
    
    # Filter rows by airport
    filtered_rows = filter_by_column(rows, "ORIGIN", airport)
    
    # Get x vector
    x_vector = range(1, days_in_month() + 1, 1)
    
    # Get y vector
    y_vector = get_delay_vector(filtered_rows, x_vector)
    
    # Plot vectors
    assert len(x_vector) == len(y_vector)
    plt.plot(x_vector, y_vector, label=airport)

def plot_airports(rows, airports):
    """
    Given a list of airports and airport delay rows, plots the average delay of
    flights for each airport.
    """
    # Initialize plot
    plt.xlabel("Day of Month")
    plt.ylabel("Average Delay (minutes)")
    plt.title("Average delays at " + str(airports))
    
    # Plot each airport
    for airport in airports:
        plot_airport(rows, airport)
    
    # Draw the lengend, show plot
    plt.legend()
    plt.show()

def load_rows(path):
    """
    Returns a list of rows from the CSV file at path. A row is a dictionary that
    maps a column name (a string) to a value (a string).
    """
    output = []
    for row in csv.DictReader(open(path)):
        output.append(row)
    return output

def get_airports():
    """
    Returns the airports to process.
    """
    # Stub function
    # TODO: Write more detailed implementation
    return ["SEA", "JFK", "DFW", "SFO"]

def get_input_path():
    """
    Returns the path of the input CSV file, containing airport delay data.
    """
    # Stub function
    # TODO: Write more detailed implementation
    return "nov.csv"

def main():
    """
    Main program
    """
    # Load rows from CSV file
    rows = load_rows(get_input_path())
    
    # Get airports to graph
    airports = get_airports()
    
    # Plot the airport delays
    plot_airports(rows, airports)
    
if __name__ == "__main__":
    main()