Optimize fit predict

[greglucas]

More caching and optimization of numpy functions. Testing calling fit and predict multiple times in a row. I go from 5.7s to 0.57 so a 10x speedup here.

import pysecs
import numpy as np
import time

np.random.seed(0)
sec_locs = np.random.rand(1000, 3) * 100
obs_locs = np.random.rand(100, 3) * 100
obs_B = np.random.rand(5000, 100, 3) * 10000
pred_locs = np.random.rand(5000, 3) * 100

t0 = time.perf_counter()
secs = pysecs.SECS(sec_df_loc=sec_locs)

secs.fit(obs_locs, obs_B=obs_B)
secs.fit(obs_locs, obs_B=obs_B)

secs.predict(pred_locs)
secs.predict(pred_locs)

t1 = time.perf_counter()
print(f"Time taken: {t1 - t0:.4f} seconds")