'''
    DS2000
    Spring 2020
    Source code from class - matplotlib
'''

import csv
import matplotlib.pyplot as plt

DATE = 0
TIME = 1
LAT = 2
LONG = 3
WIND = 4
PRESSURE = 5

CATEGORIES = {'Cat 1' : 95, 'Cat 2' : 110, 'Cat 3' : 129,
              'Cat 4': 156, 'Cat 5': 200}

def process_file(filename):
    ''' Function: process_file
        Parameter: Name of the file (a string)
        Returns: nested list of strings, the contents
                 of the file
        Does: assumes the file to be read is a CSV file
    '''
    data = []
    counter = 0
    with open(filename) as infile:
        csv_contents = csv.reader(infile, delimiter = ',')
        for row in csv_contents:
            if counter == 0:
                counter += 1
            else:
                data.append(row)
    return data

def speed_only(hurricane_data):
    ''' Function: speed_only
        Parameters: Nested list of strings, from CSV file
        Returns: list of just the speed values (ints)
    '''
    speed = []
    for row in hurricane_data:
        speed.append(int(row[WIND]))
    return speed

def graph_wind(speed_list):
    ''' Function: graph_wind
        Parameters: list of speed values over time (floats)
        Returns: nothing, just renders a linechart of the speed
    '''
    plt.plot(speed_list)
    plt.xlabel('Time')
    plt.ylabel('Wind Speed')
    plt.title('Changes in windspeed over time')
    plt.show()

def max_speeds(hurricane_data, categories):
    ''' Function: max_speeds
        parameters: Nested list of hurricane data
        Returns: list of ints -- the number of times the hurricane
                 was in each category
    '''
    speeds = list(categories.values())
    num_per_category = [0 for i in range(len(speeds))]
    for row in hurricane_data:
        for i in range(len(speeds)):
            if int(row[WIND]) < speeds[i]:
                num_per_category[i] += 1
                break
    return num_per_category
  

def speed_histogram(max_speeds, categories):
    ''' Function: speed_histogram
        Parameters: nested list of hurricane data dictionary of
                    category-to-max wind speed
        Returns: nothing, renders a histogram of how often the
                 hurricane was in each category
    '''

    pos = [i for i in range(len(categories))]
    plt.bar(pos, max_speeds)
    plt.xticks(pos, categories.keys())
    plt.title('Time spent in each category')
    plt.show()


def main():
    hurricane_data = process_file('irma.csv')
    speeds = speed_only(hurricane_data)
    graph_wind(speeds)

    speed_buckets = max_speeds(hurricane_data, CATEGORIES)
    speed_histogram(speed_buckets, CATEGORIES)

main()