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import cPickle
import scipy
import numpy as np
import matplotlib.pyplot as plt
import data
def compute_number_coordinates():
train_it = data.train_it()
# Count the number of coordinates
n_coordinates = 0
for ride in train_it:
n_coordinates += len(ride[-1])
print n_coordinates
return n_coordinates
def extract_coordinates(n_coordinates=None):
"""Extract coordinates from the dataset and store them in a numpy array"""
if n_coordinates is None:
n_coordinates = compute_number_coordinates()
coordinates = np.zeros((n_coordinates, 2), dtype="float32")
train_it = data.train_it()
c = 0
for ride in train_it:
for point in ride[-1]:
coordinates[c] = point
c += 1
cPickle.dump(coordinates, open(data.DATA_PATH + "/coordinates_array.pkl", "wb"))
def draw_map(coordinates, xrg, yrg):
hist, xx, yy = np.histogram2d(coordinates[:, 0], coordinates[:, 1], bins=2000, range=[xrg, yrg])
plt.imshow(np.log(hist))
plt.savefig(data.DATA_PATH + "/analysis/xyhmap.pdf")
scipy.misc.imsave(data.DATA_PATH + "/analysis/xymap.png", np.log(hist))
if __name__ == "__main__":
# extract_coordinates(n_coordinates=83360928)
coordinates = cPickle.load(open(data.DATA_PATH + "/coordinates_array.pkl", "rb"))
xrg = [-8.75, -8.55]
yrg = [41.05, 41.25]
draw_map(coordinates, xrg, yrg)
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