import numpy as np
import pandas as pd
import options.lsm as lsm

table = lsm.price_table(100000, 50)
np.transpose(pd.DataFrame.from_dict(table))

	European Price	LSM American Price	LSM American SE	Simulated European Price	Simulated European SE
36 0.2 1	3.844308	4.473337	0.009876	3.841138	0.013635
36 0.2 2	3.763001	4.827320	0.011893	3.982655	0.016281
36 0.4 1	6.711399	7.104770	0.019679	6.711362	0.023006
36 0.4 2	7.700040	8.465423	0.024178	8.184778	0.028316
38 0.2 1	2.851932	3.256599	0.009656	2.855663	0.012149
38 0.2 2	2.990557	3.728441	0.011645	3.155735	0.014785
38 0.4 1	5.834321	6.154242	0.019369	5.837305	0.021935
38 0.4 2	6.978802	7.637595	0.023774	7.442247	0.027542
40 0.2 1	2.066401	2.322347	0.008958	2.079413	0.010584
40 0.2 2	2.355866	2.877937	0.010946	2.501114	0.013323
40 0.4 1	5.059623	5.323717	0.018379	5.057777	0.020805
40 0.4 2	6.325999	6.903202	0.022808	6.719609	0.026494
42 0.2 1	1.464504	1.613934	0.007747	1.456605	0.008882
42 0.2 2	1.841354	2.205585	0.009963	1.960058	0.011901
42 0.4 1	4.378718	4.572274	0.017662	4.386564	0.019659
42 0.4 2	5.735618	6.222996	0.022171	6.062861	0.025483
44 0.2 1	1.016915	1.110343	0.006563	1.011694	0.007398
44 0.2 2	1.429215	1.689388	0.009085	1.528936	0.010495
44 0.4 1	3.782799	3.949719	0.016644	3.776469	0.018460
44 0.4 2	5.201995	5.652219	0.021964	5.572470	0.024679