def checker(path_to_input, path_to_output):
true_output = {}
user_output = {}
with open(path_to_input, 'r') as f:
true_len = int(f.readline())
true_inp_pts = [
list(map(float,
f.readline().split())) for _ in range(true_len)
]
true_pts = ConvexHull(true_inp_pts).vertices
true_pts = [true_inp_pts[x] for x in true_pts]
true_pts += [true_pts[0]]
if isinstance(true_pts, np.ndarray):
true_pts = true_pts.tolist()
true_pts = true_pts[:-1]
true_pts = [true_inp_pts.index(x) + 1 for x in true_pts]
with open(path_to_output, 'r') as f:
t = float(f.readline())
output_len = int(f.readline())
# output_pts = [list(map(float, f.readline().split())) for _ in range(output_len)]
output_pts = list(map(int, f.readline().split()))
user_output['list'] = output_pts
true_output['list'] = true_pts
print(t)
return user_output, true_output, output_pts == true_pts
def convexhull(self, vertices=True):
if vertices:
hull = ConvexHull(self.points).vertices
return [
self.points[vertex, :2].reshape(1, -1)
for vertex in hull.tolist()
]
else:
return ConvexHull(self.points)
def CH_vertices(l):
point = SA.get_point(l)
hull = CH(point).vertices
hull = hull.tolist()
count = 0
result = []
while len(hull) != 0:
if count in hull:
result.append(point[count])
hull.remove(count)
count += 1
return result
def calc_plot_json(observer, sat_id, radial, angular, long, lat):
if sat_id == 0:
v = plot_update(radial, angular, -long, lat)
v = rotation(observer.observer_coordinate.lon / u.deg + 90, -observer.observer_coordinate.lat / u.deg, v, n)
else:
v = plot_update(radial, angular, -long, lat)
v = rotation(observer.observer_coordinate.lon / u.deg + 90, observer.observer_coordinate.lat / u.deg, v, n)
points = np.array(list(zip(np.ravel(v[0]), np.ravel(v[2]))))
hull = ConvexHull(points, qhull_options='QbB')
# sun center point on the picture
# obtains CRVAL1 = r_x and CRVAL = r_y
sun_x_center, sun_y_center = observer.reference_pixel
# used to determine how far the lemniscate must be moved
# due to the picture not having the sun in the exact center
# 128 = have of the dimensions of the plot
x_translate = (sun_x_center / u.pix) - 128
y_translate = (sun_y_center / u.pix) - 128
# determines aspect ratio for distance from satellite
pic_width_ratio = pic_wcs_length(observer, 256, 128, r_x=128, r_y=128)
lem_distance_c_ratio = (AU_REFERENCE_CUBE * u.AU).to(u.km) / pic_width_ratio
hull = np.array(((points[hull.vertices, 0] * lem_distance_c_ratio + x_translate),
(points[hull.vertices, 1] * lem_distance_c_ratio + y_translate)))
return json.dumps(hull.tolist())