# CACHING INPUT PARAMETERS
proxy = Proxy()
transform_points_numpy = proxy.function('compas.geometry.transform_points_numpy')
# create a proxy funciton
pts = [[0,0,0], [1,0,0]]
pts_cache = proxy.cache(pts) # cache the object to server side and return its reference
print(pts_cache) # will print: {'cached': some_unique_id}
T = Translation().from_vector([100, 0, 0]).matrix
result = transform_points_numpy(pts_cache, T) # call the function through proxy
print(result) # will print: [[100.0, 0.0 ,0.0], [101.0, 0.0, 0.0]]
# CACHING RETURNED DATA
transform_points_numpy = proxy.function('compas.geometry.transform_points_numpy', cache=True)
# this function will now return a cache object instead of the actual data
pts = [[0,0,0], [1,0,0]]
pts_cache = proxy.cache(pts)
print(pts_cache) # will print: {'cached': some_unique_id}
T = Translation().from_vector([100, 0, 0]).matrix
result_cache = transform_points_numpy(pts_cache, T) # call the function through proxy
print(result_cache) # will print: {'cached': some_unique_id}
result = proxy.get(result_cache) # fetch the actual data of the cache object
print(result) # will print: [[100.0, 0.0 ,0.0], [101.0, 0.0, 0.0]]
pts = transform_points(pts, T)
result1 = pts
end = time.time()
print('transform 10k points 100 times (native python): ', end - start, 's')
# USING CLOUD WITH CACHE
from compas_cloud import Proxy
proxy = Proxy()
transform_points_numpy = proxy.function(
'compas.geometry.transform_points_numpy', cache=True)
pts = [[i, 0, 0] for i in range(0, 10000)]
T = Translation([100, 0, 0]).matrix
start = time.time()
pts = proxy.cache(pts)
for i in range(0, 100):
pts = transform_points_numpy(pts, T)
result2 = proxy.get(pts)
end = time.time()
print('transform 10k points 100 times (cloud numpy): ', end - start, 's')
assert result1 == result2