How to use the pyemma.coordinates.transform.transformer.StreamingTransformerRandomAccessStrategy function in pyEMMA

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github markovmodel / PyEMMA / pyemma / coordinates / transform / transformer.py View on Github external
def _set_random_access_strategies(self):
        if self.in_memory and self._Y_source is not None:
            self._ra_cuboid = self._Y_source._ra_cuboid
            self._ra_linear_strategy = self._Y_source._ra_linear_strategy
            self._ra_linear_itraj_strategy = self._Y_source._ra_linear_itraj_strategy
            self._ra_jagged = self._Y_source._ra_jagged
            self._is_random_accessible = True
        elif self.data_producer is not None:
            self._ra_jagged = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_jagged)
            self._ra_linear_itraj_strategy = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_linear_itraj_strategy)
            self._ra_linear_strategy = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_linear_strategy)
            self._ra_cuboid = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_cuboid)
            self._is_random_accessible = self.data_producer._is_random_accessible
        else:
            self._ra_jagged = self._ra_linear_itraj_strategy = self._ra_linear_strategy \
                = self._ra_cuboid = None
            self._is_random_accessible = False
github markovmodel / PyEMMA / pyemma / coordinates / transform / transformer.py View on Github external
def _set_random_access_strategies(self):
        if self.in_memory and self._Y_source is not None:
            self._ra_cuboid = self._Y_source._ra_cuboid
            self._ra_linear_strategy = self._Y_source._ra_linear_strategy
            self._ra_linear_itraj_strategy = self._Y_source._ra_linear_itraj_strategy
            self._ra_jagged = self._Y_source._ra_jagged
            self._is_random_accessible = True
        elif self.data_producer is not None:
            self._ra_jagged = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_jagged)
            self._ra_linear_itraj_strategy = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_linear_itraj_strategy)
            self._ra_linear_strategy = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_linear_strategy)
            self._ra_cuboid = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_cuboid)
            self._is_random_accessible = self.data_producer._is_random_accessible
        else:
            self._ra_jagged = self._ra_linear_itraj_strategy = self._ra_linear_strategy \
                = self._ra_cuboid = None
            self._is_random_accessible = False
github markovmodel / PyEMMA / pyemma / coordinates / transform / transformer.py View on Github external
def _set_random_access_strategies(self):
        if self.in_memory and self._Y_source is not None:
            self._ra_cuboid = self._Y_source._ra_cuboid
            self._ra_linear_strategy = self._Y_source._ra_linear_strategy
            self._ra_linear_itraj_strategy = self._Y_source._ra_linear_itraj_strategy
            self._ra_jagged = self._Y_source._ra_jagged
            self._is_random_accessible = True
        elif self.data_producer is not None:
            self._ra_jagged = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_jagged)
            self._ra_linear_itraj_strategy = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_linear_itraj_strategy)
            self._ra_linear_strategy = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_linear_strategy)
            self._ra_cuboid = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_cuboid)
            self._is_random_accessible = self.data_producer._is_random_accessible
        else:
            self._ra_jagged = self._ra_linear_itraj_strategy = self._ra_linear_strategy \
                = self._ra_cuboid = None
            self._is_random_accessible = False
github markovmodel / PyEMMA / pyemma / coordinates / transform / transformer.py View on Github external
def _set_random_access_strategies(self):
        if self.in_memory and self._Y_source is not None:
            self._ra_cuboid = self._Y_source._ra_cuboid
            self._ra_linear_strategy = self._Y_source._ra_linear_strategy
            self._ra_linear_itraj_strategy = self._Y_source._ra_linear_itraj_strategy
            self._ra_jagged = self._Y_source._ra_jagged
            self._is_random_accessible = True
        elif self.data_producer is not None:
            self._ra_jagged = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_jagged)
            self._ra_linear_itraj_strategy = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_linear_itraj_strategy)
            self._ra_linear_strategy = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_linear_strategy)
            self._ra_cuboid = \
                StreamingTransformerRandomAccessStrategy(self, self.data_producer._ra_cuboid)
            self._is_random_accessible = self.data_producer._is_random_accessible
        else:
            self._ra_jagged = self._ra_linear_itraj_strategy = self._ra_linear_strategy \
                = self._ra_cuboid = None
            self._is_random_accessible = False
github markovmodel / PyEMMA / pyemma / coordinates / transform / transformer.py View on Github external
def __init__(self, source, parent_strategy):
        super(StreamingTransformerRandomAccessStrategy, self).__init__(source)
        self._parent_strategy = parent_strategy
        self._max_slice_dimension = self._parent_strategy._max_slice_dimension