@@ -1016,20 +1016,20 @@ def guess(self, f, n_verify=100, max_exponent=10, sequence=None):
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ALGORITHM:
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- For the purposes of this description, the left vector valued sequence
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- associated with a regular sequence consists of the left vector
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- multiplied by the corresponding matrix product, but without the right
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- vector of the regular sequence.
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+ For the purposes of this description, the right vector valued sequence
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+ associated with a regular sequence consists of the
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+ corresponding matrix product multiplied by the right vector,
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+ but without the right vector of the regular sequence.
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- The algorithm maintains a left vector valued sequence consisting
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- of the left vector valued sequence of the argument ``sequence``
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+ The algorithm maintains a right vector valued sequence consisting
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+ of the right vector valued sequence of the argument ``sequence``
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(replaced by an empty tuple if ``sequence`` is ``None``) plus several
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components of the shape `m \mapsto f(k^t\cdot m +r)` for suitable
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``t`` and ``r``.
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Implicitly, the algorithm also maintains a `d \times n_\mathrm{verify}` matrix ``A``
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- (where ``d`` is the dimension of the left vector valued sequence)
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- whose columns are the current left vector valued sequence evaluated at
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+ (where ``d`` is the dimension of the right vector valued sequence)
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+ whose columns are the current right vector valued sequence evaluated at
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the non-negative integers less than `n_\mathrm{verify}` and ensures that this
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matrix has full row rank.
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@@ -1282,12 +1282,12 @@ def guess(self, f, n_verify=100, max_exponent=10, sequence=None):
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# `k**t * m + r`
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# The elements of `lines` will correspond to the current components
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- # of the left vector valued sequence described in the algorithm section
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+ # of the right vector valued sequence described in the algorithm section
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# of the docstring.
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def values (m , lines ):
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"""
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- Return current (as defined by ``lines``) left vector valued
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+ Return current (as defined by ``lines``) right vector valued
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sequence for argument ``m``.
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"""
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return tuple (seq (m )) + tuple (f (k ** t_R * m + r_R ) for t_R , r_R in lines )
@@ -1302,7 +1302,7 @@ def some_inverse_U_matrix(lines):
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The output is the inverse of the invertible submatrix and
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the corresponding list of column indices (i.e., arguments to
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- the current left vector valued sequence).
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+ the current right vector valued sequence).
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"""
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d = len (seq (0 )) + len (lines )
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