8 examples of 'how to take 2d array input in python using numpy' in Python

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def as2d( ar ):
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    """
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    If the input array is 2D return it, if it is 1D, append a dimension,
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    making it a column vector.
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    """
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    if ar.ndim == 2:
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        return ar
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    else: # Assume 1!
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        aux = np.array( ar, copy = False )
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        aux.shape = (ar.shape[0], 1)
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        return aux

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def convert_image_np_2d(inp):
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    inp = denorm(inp)
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    inp = inp.numpy()
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    # mean = np.array([x/255.0 for x in [125.3,123.0,113.9]])
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    # std = np.array([x/255.0 for x in [63.0,62.1,66.7]])
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    # inp = std*
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    return inp

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def _convert_to_numpy(data):
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    """Returns tuple data with all elements converted to numpy ndarrays"""
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    if data is None:
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        return None
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    elif isinstance(data, tuple):
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        return tuple([_convert_to_numpy(d) for d in data])
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    elif isinstance(data, np.ndarray):
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        return data
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    elif isinstance(data, (pd.DataFrame, pd.Series)):
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        return data.to_numpy()
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    else:
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        raise Exception("Unsupported type %s" % str(type(data)))

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def _atleast_2d_with_dtype(value, dtype=None):
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    if dtype is not None:
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        value = np.array(value, dtype=dtype)
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    arr = np.atleast_2d(value)
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    return arr

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def data_tranform2d(data):
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    """
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    :param data:
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    :return data2d:
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    Returns the data array reshaped into 2-dimensions
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    """
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    shape, dimensions = data_shape(data)
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    if dimensions == 1:
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        raise TypeError('Data must have dimensions between 2 and 4')
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    elif dimensions == 2:
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        return data
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    elif dimensions == 3:
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        return np.reshape(data, (shape[0]*shape[1], shape[2]))
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    elif dimensions == 4:
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        return np.reshape(data, (shape[0]*shape[1]*shape[2], shape[3]))
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    else:
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        raise TypeError('Data must have dimensions between 2 and 4')

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def array(a):
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    return numpy.array(a)

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def atleast_3d(ary):
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    """
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    numpy.atleast_3d adds axes on either side of a 1d array's axis, but I want the new axes to come afterward.
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    :param ary:
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    :type ary:
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    :return:
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    :rtype:
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    """
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    ary = numpy.asanyarray(ary)
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    if len(ary.shape) == 0:
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        result = ary.reshape(1, 1, 1)
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    elif len(ary.shape) == 1:
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        result = ary[:, None, None]
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    elif len(ary.shape) == 2:
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        result = ary[:,:, None]
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    else:
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        result = ary
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    return result

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def array2d(X, dtype=None, order=None, copy=False):
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    """Returns at least 2-d array with data from X"""
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    if sp.issparse(X):
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        raise TypeError('A sparse matrix was passed, but dense data '
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                        'is required. Use X.toarray() to convert to dense.')
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    X_2d = np.asarray(np.atleast_2d(X), dtype=dtype, order=order)
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    _assert_all_finite(X_2d)
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    if X is X_2d and copy:
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        X_2d = safe_copy(X_2d)
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    return X_2d