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Center location fix #3

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Center location fix #3

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17 changes: 14 additions & 3 deletions step/quantification.py
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Original file line number Diff line number Diff line change
Expand Up @@ -191,6 +191,10 @@ def get_central_loc(storms: np.ndarray, precip: np.ndarray, lats: np.ndarray, lo
# initialize an array to store our result, but of type object to allow us to store an array in each cell
result = np.zeros((lifetime, total_storms)).astype(object)

# convert lats and longs from degree to radian
lats = lats / 180. * np.pi
longs = longs / 180. * np.pi

# create arrays of x, y, and z values for the cartesian grid in R3
x_array = np.cos(lats) * np.cos(longs)
y_array = np.cos(lats) * np.sin(longs)
Expand Down Expand Up @@ -223,9 +227,16 @@ def get_central_loc(storms: np.ndarray, precip: np.ndarray, lats: np.ndarray, lo
h_avg = sqrt((x_avg ** 2) + (y_avg ** 2))

# the central location on earth's surface is given by the following
central_location[0] = 2 * atan(y_avg / (sqrt((y_avg ** 2) + (x_avg ** 2)) + x_avg))
central_location[1] = 2 * atan(z_avg / (sqrt((z_avg ** 2) + (h_avg ** 2)) + h_avg))

tmp_lon = atan(y_avg / x_avg)/np.pi*180
tmp_lat = atan(z_avg / h_avg)/np.pi*180
if tmp_lon > 0:
### convert to degree west is the longitude is consider in degree east
tmp_lon -= 180
# put longitude and latitude to the first and second dimensions
central_location[0] = tmp_lon
central_location[1] = tmp_lat


# and we place it in the appropriate spot in the array
result[time_index][label] = central_location

Expand Down