diff --git a/docs/assets/pipeline.svg b/docs/assets/pipeline.svg index 8c67c7ab..a38b6480 100644 --- a/docs/assets/pipeline.svg +++ b/docs/assets/pipeline.svg @@ -24,12 +24,12 @@ inkscape:deskcolor="#d1d1d1" inkscape:document-units="mm" inkscape:zoom="1.4142136" - inkscape:cx="289.20667" - inkscape:cy="-54.800776" - inkscape:window-width="2488" - inkscape:window-height="1262" + inkscape:cx="206.82873" + inkscape:cy="8.4852811" + inkscape:window-width="1800" + inkscape:window-height="1035" inkscape:window-x="0" - inkscape:window-y="25" + inkscape:window-y="44" inkscape:window-maximized="0" inkscape:current-layer="layer1" /> + y="49.623287" /> Pipeline + x="26.058722" + y="84.056198">Pipeline Basis: Set all basis states. This method corresponds sklearn transformer ``fit``. As fit, it must receive the input and - it must set all basis states, i.e. kernel_ and all the states relative to the input shape. + it must set all basis states, i.e. ``kernel_`` and all the states relative to the input shape. The difference between this method and the transformer ``fit`` is in the expected input structure, where the transformer ``fit`` method requires the inputs to be concatenated in a 2D array, while here each input is provided as a separate time series for each basis element. @@ -323,7 +323,7 @@ def setup_basis(self, *xi: NDArray) -> Basis: Set all basis states. This method corresponds sklearn transformer ``fit``. As fit, it must receive the input and - it must set all basis states, i.e. kernel_ and all the states relative to the input shape. + it must set all basis states, i.e. ``kernel_`` and all the states relative to the input shape. The difference between this method and the transformer ``fit`` is in the expected input structure, where the transformer ``fit`` method requires the inputs to be concatenated in a 2D array, while here each input is provided as a separate time series for each basis element. @@ -539,7 +539,7 @@ def setup_basis(self, *xi: NDArray) -> Basis: Set all basis states. This method corresponds sklearn transformer ``fit``. As fit, it must receive the input and - it must set all basis states, i.e. kernel_ and all the states relative to the input shape. + it must set all basis states, i.e. ``kernel_`` and all the states relative to the input shape. The difference between this method and the transformer ``fit`` is in the expected input structure, where the transformer ``fit`` method requires the inputs to be concatenated in a 2D array, while here each input is provided as a separate time series for each basis element.