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# ---
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# ---
# # Multiple Formats with Finch
# ## Import
# Let's set the backend and import `sparse`.
# +
import os
os.environ["SPARSE_BACKEND"] = "Finch"
import sparse
import numpy as np
# -
# ## Perform Operations
# Let's create two arrays.
rng = np.random.default_rng(42) # Seed for reproducibility
a = sparse.random((3, 3), density=1 / 6, random_state=rng)
b = sparse.random((3, 3), density=1 / 6, random_state=rng)
# Now let's matrix multiply them.
c = a @ b
# And view the result as a (dense) NumPy array.
c_dense = c.todense()
# Now let's do the same for other formats, and compare the results.
for format in ["coo", "csr", "csc", "dense"]:
af = sparse.asarray(a, format=format)
bf = sparse.asarray(b, format=format)
cf = af @ bf
np.testing.assert_array_equal(c_dense, cf.todense())
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