Currently, the usage of np.array() inside the _process_coordinate_data fails when attempting to merge 1D arrays with different sizes. This can be resolved by replacing np.array() with np.concatenate(), which effectively merges 1D arrays with varying shapes into a single 1D array.
Example code:
import numpy as np
day1 = np.random.randint(10, size=(5))
print(day1)
day2 = np.random.randint(10, size=(4))
print(day2)
allDays1 = np.array([day1, day2]) # not worked
allDays2 = np.concatenate([day1, day2]) # worked
print(allDays1)
Currently, the usage of
np.array()
inside the_process_coordinate_data
fails when attempting to merge 1D arrays with different sizes. This can be resolved by replacing np.array() withnp.concatenate()
, which effectively merges 1D arrays with varying shapes into a single 1D array.Example code: