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dimensions not supportedIncompatible checksums (%s vs 0xce49147 = (next_label, parent, size))Incompatible checksums (%s vs 0xb068931 = (name))Incompatible checksums (%s vs 0x43ddba2 = (a, b, weight))Format string allocated too short, see comment in numpy.pxdEmpty shape tuple for cython.arrayCannot create writable memory view from read-only memoryviewCannot assign to read-only memoryviewCan only create a buffer that is contiguous in memory.Buffer view does not expose stridesunknown dtype code in numpy.pxd (%d)numpy.core.multiarray failed to import<strided and direct or indirect>unable to allocate array data.ndarray is not C contiguousitemsize <= 0 for cython.array__pyx_unpickle_WeightedEdgeInvalid shape in axis %d: %d.Cannot index with type '%s'<contiguous and indirect><MemoryView of %r at 0x%x>__pyx_unpickle_UnionFind<MemoryView of %r object><contiguous and direct><strided and indirect>single_linkage_label<strided and direct>%s(weight=%f, a=%i, 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%sBuffer dtype mismatch, expected '%s' but got %s in '%s.%s'memviewslice is already initialized!%.200s() takes no arguments (%zd given)%.200s() takes exactly one argument (%zd given)Bad call flags in __Pyx_CyFunction_Call. METH_OLDARGS is no longer supported!%.200s() takes no keyword arguments%.200s.%.200s is not a type object%.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject%s.%s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObjectsklearn/cluster/_hierarchical_fast.pyxUnable to initialize pickling for %s__annotations__ must be set to a dict object__kwdefaults__ must be set to a dict object__defaults__ must be set to a tuple objectfunction's dictionary may not be deletedsetting function's dictionary to a non-dict__qualname__ must be set to a string object__name__ must be set to a string objectDoes not understand character buffer dtype format string ('%c')Argument '%.200s' has incorrect type (expected %.200s, got %.200s)sklearn/cluster/_hierarchical_fast.cppView.MemoryView.memoryview.__str__View.MemoryView.memoryview.size.__get__View.MemoryView.memoryview.nbytes.__get__View.MemoryView.memoryview.itemsize.__get__View.MemoryView.memoryview.ndim.__get__View.MemoryView.memoryview.suboffsets.__get__View.MemoryView.memoryview.shape.__get__View.MemoryView.memoryview.setitem_indexedView.MemoryView.array.memview.__get__View.MemoryView.array.__getattr__View.MemoryView.array.__getitem__sklearn.cluster._hierarchical_fast.WeightedEdge.__repr__View.MemoryView.array.__setitem__Subscript deletion not supported by %.200ssklearn.cluster._hierarchical_fast.WeightedEdge.weight.__get__sklearn.cluster._hierarchical_fast.WeightedEdge.b.__get__sklearn.cluster._hierarchical_fast.WeightedEdge.weight.__set__sklearn.cluster._hierarchical_fast.WeightedEdge.a.__get__sklearn.cluster._hierarchical_fast.UnionFind.unionsklearn.cluster._hierarchical_fast.UnionFind.fast_find%s() got multiple values for keyword argument '%U'%.200s() keywords must be strings%s() got an unexpected keyword argument '%U'%.200s() takes %.8s %zd positional argument%.1s (%zd given)View.MemoryView.memoryview.assign_item_from_objectView.MemoryView._memoryviewslice.assign_item_from_objectcalling %R should have returned an instance of BaseException, not %Rraise: exception class must be a subclass of BaseExceptionView.MemoryView.array.__reduce_cython__View.MemoryView.array.__setstate_cython__View.MemoryView.memoryview.convert_item_to_objectView.MemoryView._memoryviewslice.convert_item_to_objectView.MemoryView.memoryview.__reduce_cython__View.MemoryView.memoryview.__setstate_cython__View.MemoryView.memoryview.strides.__get__View.MemoryView._memoryviewslice.__reduce_cython__View.MemoryView._memoryviewslice.__setstate_cython__PyObject_GetBuffer: view==NULL argument is obsoleteView.MemoryView.array.__getbuffer__View.MemoryView.memoryview.__getbuffer__Unexpected format string character: '%c'Expected a dimension of size %zu, got %zuExpected %d dimensions, got %dPython does not define a standard format string size for long double ('g')..Buffer dtype mismatch; next field is at offset %zd but %zd expectedBig-endian buffer not supported on little-endian compilerBuffer acquisition: Expected '{' after 'T'Cannot handle repeated arrays in format stringExpected a dimension of size %zu, got %dExpected a comma in format string, got '%c'Expected %d dimension(s), got %dUnexpected end of format string, expected ')'Buffer has wrong number of dimensions (expected %d, got %d)Item size of buffer (%zd byte%s) does not match size of '%s' (%zd byte%s)sklearn.cluster._hierarchical_fast.compute_ward_distAcquisition count is %d (line %d)__int__ returned non-int (type %.200s).  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    -------
    A tree in the format used by scipy.cluster.hierarchy.
    
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    This is done by using a Union find structure to keep track of merges
    efficiently. This is the private version of the function that assumes that
    ``L`` has been properly validated. See ``single_linkage_label`` for the
    user facing version of this function.

    Parameters
    ----------
    L: array of shape (n_samples - 1, 3)
        The linkage array or MST where each row specifies two samples
        to be merged and a distance or weight at which the merge occurs. This
         array is assumed to be sorted by the distance/weight.

    Returns
    -------
    A tree in the format used by scipy.cluster.hierarchy.
    Merge two IntFloatDicts with the average strategy: when the 
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    values is used.

    Parameters
    ==========
    a, b : IntFloatDict object
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    mask : ndarray array of dtype integer and of dimension 1
        a mask for keys to ignore: if not mask[key] the corresponding key
        is skipped in the output dictionary
    n_a, n_b : float
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    =======
    out : IntFloatDict object
        The IntFloatDict resulting from the merge
    Merge two IntFloatDicts with the max strategy: when the same key is
    present in the two dicts, the max of the two values is used.

    Parameters
    ==========
    a, b : IntFloatDict object
        The IntFloatDicts to merge
    mask : ndarray array of dtype integer and of dimension 1
        a mask for keys to ignore: if not mask[key] the corresponding key
        is skipped in the output dictionary
    n_a, n_b : float
        n_a and n_b are weights for a and b for the merge strategy.
        They are not used in the case of a max merge.

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    out : IntFloatDict object
        The IntFloatDict resulting from the merge
    Returns the heads of the given nodes, as defined by parents.

    Modifies 'heads' and 'not_visited' in-place.

    Parameters
    ----------
    nodes : list of integers
        The nodes to start from
    heads : list of integers
        A list to hold the results (modified inplace)
    parents : array of integers
        The parent structure defining the tree
    not_visited
        The tree nodes to consider (modified inplace)

    Returns the heads of the forest, as defined by parents.

    Parameters
    ----------
    parents : array of integers
        The parent structure defining the forest (ensemble of trees)
    copy : boolean
        If copy is False, the input 'parents' array is modified inplace

    Returns
    -------
    heads : array of integers of same shape as parents
        The indices in the 'parents' of the tree heads

    
    Function returning all the descendent leaves of a set of nodes in the tree.

    Parameters
    ----------
    node : integer
        The node for which we want the descendents.

    children : list of pairs, length n_nodes
        The children of each non-leaf node. Values less than `n_samples` refer
        to leaves of the tree. A greater value `i` indicates a node with
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    n_leaves : integer
        Number of leaves.

    Returns
    -------
    descendent : list of int
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