exporttooml

Export logical data to OML:

pofalse = False
status = exporttooml('pofalse', 'omlfalse')
print(status)

1

Export integer data to OML:

point = 999
status = exporttooml('point','omlint')
print(status)

1

Export precision data to OML:

pofloat=9.99
status = exporttooml('pofloat','omlfloat')
print(status)

1

Export complex data to OML:

pocomp=9+9j
status = exporttooml('pocomp','omlcomp')
print(status)

1

Export string data to OML:

postring="String Data"
status = exporttooml('postring','omlstring')
print(status)

1

Export list data to OML:

polist  = ["a","b","c","d"]
status = exporttooml('polist','omlcell')
print(status)

1

Export dictionary data to OML:

polist  = ["a","b","c","d"]
podict = {"key1":1,"key2" : polist }
status = exporttooml('podict','omlstruct')
print(status)

1

Export matrix data to OML:

import numpy as np
pomatrix = np.matrix("1 2; 3 4")
status = exporttooml('pomatrix','omlmatrix')
print(status)

1

Export an nd matrix data to OML:

import numpy as np
pondarray = np.arange(720).reshape(6,4,2,3,5)
status = exporttooml('pondarray','omlndmatrix')
print(status)

1

Export Scipy CSC sparse matrix data to OML.

import numpy as np;
from scipy.sparse import csc_matrix
row = np.array([0, 2, 2, 0, 1, 2])
col = np.array([0, 0, 1, 2, 2, 2])
data = np.array([1, 2, 3, 4, 5, 6])
csc = csc_matrix((data, (row, col)), shape=(3, 3))
status=exporttooml('csc','csc')
print(status)

1

Export Scipy non-CSC sparse matrix data to OML.

import numpy as np;
from scipy.sparse import csr_matrix
row = np.array([0, 2, 2, 0, 1, 2])
col = np.array([0, 0, 1, 2, 2, 2])
data = np.array([1, 2, 3, 4, 5, 6])
csr = csr_matrix((data, (row, col)), shape=(3, 3))
csc = csr.tocsc()
status=exporttooml('csc','csc')
print(status)

1

Any error reported is returned as a string. Returns 1 on success.