Module act_one: single HT-tensor operations
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.. automodule:: teneva_ht_jax.act_one


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.. autofunction:: teneva_ht_jax.act_one.get

  **Examples**:

  .. code-block:: python

    d = 8          # Dimension of the tensor
    n = 10         # Mode size for the tensor
    r = [3, 4, 5]  # Ranks for tree layers
    
    # Build the random HT-tensor:
    rng, key = jax.random.split(rng)
    Y = tnv.rand(d, n, r, key)
    
    # Select some tensor element and compute the value:
    k = np.array([0, 1, 2, 3, 4, 5, 6, 7])
    y = tnv.get(Y, k)
    print(y)

    # >>> ----------------------------------------
    # >>> Output:

    # 0.11423279171264825
    # 

  Let multiply the HT-tensor by 2, and check the change of the value in the same multi-index: 

  .. code-block:: python

    Y[-1] = Y[-1] * 2
    y = tnv.get(Y, k)
    print(y)

    # >>> ----------------------------------------
    # >>> Output:

    # 0.2284655834252965
    # 

  We may transform the HT-tensor into full format and check the result:

  .. code-block:: python

    # TODO!
    
    # Y_full = tnv.full(Y) # This function is not ready!
    
    # y_full = Y_full[tuple(k)]
    # print(y_full)
    
    # Let compare values:
    # e = np.abs(y - y_full)
    # print(f'Error : {e:7.1e}')




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