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Commit 13cbda4d authored by David Schäfer's avatar David Schäfer
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remove git relicts

parent d0c2fada
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7 merge requests!685Release 2.4,!684Release 2.4,!567Release 2.2.1,!566Release 2.2,!501Release 2.1,!372fix doctest snippets,!369Current documentation
...@@ -132,11 +132,7 @@ model via the method :py:func:`saqc.roll <Functions.saqc.roll>`. ...@@ -132,11 +132,7 @@ model via the method :py:func:`saqc.roll <Functions.saqc.roll>`.
.. code-block:: python .. code-block:: python
<<<<<<< HEAD
>>> i_saqc = i_saqc.roll(field='incidents', target='incidents_mean', func=np.mean, winsz='13D') >>> i_saqc = i_saqc.roll(field='incidents', target='incidents_mean', func=np.mean, winsz='13D')
=======
i_saqc = i_saqc.rolling.roll(field='incidents_model', func=np.mean, window='13D')
>>>>>>> develop
The :py:attr:`field` parameter is passed the variable name, we want to calculate the rolling mean of. The :py:attr:`field` parameter is passed the variable name, we want to calculate the rolling mean of.
The :py:attr:`target` parameter holds the name, we want to store the results of the calculation to. The :py:attr:`target` parameter holds the name, we want to store the results of the calculation to.
...@@ -151,12 +147,7 @@ under the name ``ǹp.median``. We just calculate another model curve for the ``" ...@@ -151,12 +147,7 @@ under the name ``ǹp.median``. We just calculate another model curve for the ``"
.. code-block:: python .. code-block:: python
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>>> i_saqc = i_saqc.roll(field='incidents', target='incidents_median', func=np.median, winsz='13D') >>> i_saqc = i_saqc.roll(field='incidents', target='incidents_median', func=np.median, winsz='13D')
=======
i_saqc = i_saqc.tools.copy(field='incidents', new_field='incidents_median')
i_saqc = i_saqc.rolling.roll(field='incidents_median', func=np.median, window='13D')
>>>>>>> develop
We chose another :py:attr:`target` value for the rolling *median* calculation, in order to not override our results from We chose another :py:attr:`target` value for the rolling *median* calculation, in order to not override our results from
the previous rolling *mean* calculation. the previous rolling *mean* calculation.
...@@ -176,13 +167,8 @@ Another common approach, is, to fit polynomials of certain degrees to the data. ...@@ -176,13 +167,8 @@ Another common approach, is, to fit polynomials of certain degrees to the data.
.. code-block:: python .. code-block:: python
<<<<<<< HEAD
>>> i_saqc = i_saqc.fitPolynomial(field='incidents', target='incidents_polynomial', polydeg=2 ,winsz='13D') >>> i_saqc = i_saqc.fitPolynomial(field='incidents', target='incidents_polynomial', polydeg=2 ,winsz='13D')
=======
i_saqc = i_saqc.tools.copy(field='incidents', new_field='incidents_polynomial')
i_saqc = i_saqc.curvefit.fitPolynomial(field='incidents_polynomial', order=2,
winsz='13D')
>>>>>>> develop
It also takes a :py:attr:`winsz` parameter, determining the size of the fitting window. It also takes a :py:attr:`winsz` parameter, determining the size of the fitting window.
The parameter, :py:attr:`polydeg` refers to the size of the rolling window, the polynomials get fitted to. The parameter, :py:attr:`polydeg` refers to the size of the rolling window, the polynomials get fitted to.
...@@ -243,8 +229,6 @@ To see all the results obtained so far, plotted in one figure window, we make us ...@@ -243,8 +229,6 @@ To see all the results obtained so far, plotted in one figure window, we make us
:alt: :alt:
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Residues and Scores Residues and Scores
------------------- -------------------
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