from datatool import datatool
import numpy as np
import math

dt = datatool()

dt.load_csv('bluefin_whale_data.csv')

dt.tilemap_attach_col_lat_long('location-lat', 'location-long', 'individual-local-identifier')

# First, the min and max in each direction. Lat is at index 3, long is 4, id is 11
D = dt.get_data_as_array()
min_lat = D[0,4]
max_lat = D[0,4]
min_long = D[0,3]
max_long = D[0,3]

for i in range(D.shape[0]):
    # COPY YOUR CODE FROM the previous exercise here

print('min-lat=', min_lat, 'max-lat=', max_lat)
print('min-long=', min_long, 'max-long=', max_long)

# COPY YOUR CODE FROM the previous exercise here.
# Round min down, round max up

print('min-lat=', min_lat, 'max-lat=', max_lat)
print('min-long=', min_long, 'max-long=', max_long)

# WRITE CODE in this function to determine whether the point
# specified by lat,lon is inside the half-box whose bottom
# left corner is box_lat, box_lon. Return True or False accordingly.
def within(box_lat, box_lon, lat, lon):
    # Copy your code from the previous exercise here

# WRITE CODE in this function to count the number of data points
# from the 2D array D whose lat-lon's are inside the half-box
# whose bottom left corner is box_lat, box_lon.
def count_occurences(box_lat, box_lon):
    # Copy your code from the previous exercise here


# Next, run through the boxes
num_boxes = 0
max_count = 0
best_lat = 0
best_lon = 0
lat = min_lat
while lat < max_lat:
    lon = min_long
    while lon < max_long:
        # Count occurrences within lat to lat+0.5, lon to lon+0.5
        num_boxes += 1
        count = count_occurences(lat, lon)
        if (count > max_count):
            max_count = count
            best_lat = lat
            best_lon = lon
        lon += 0.5
    lat += 0.5

print('After searching', num_boxes, 'boxes: ')
print('  => best box: lat', best_lat, ':', best_lat+0.5, '  lon', best_lon, ':', best_lon+0.5, '  count =', max_count)

dt.tilemap_add_line(best_lat, best_lon, best_lat+0.5, best_lon)
dt.tilemap_add_line(best_lat, best_lon, best_lat, best_lon+0.5)
dt.tilemap_add_line(best_lat, best_lon+0.5, best_lat+0.5, best_lon+0.5)
dt.tilemap_add_line(best_lat+0.5, best_lon, best_lat+0.5, best_lon+0.5)

center = dict(lat = 35, lon =-119)
dt.tilemap_czt(center, zoom=5, title='Best spotting area')
# A bit west of Long Beach, CA, and northwest of Catalina Island

dt.display()