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machine-learning
MLAir
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516651c3
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516651c3
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4 years ago
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leufen1
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added more information to docs, /close
#272
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include current develop
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Resolve "release v1.3.0"
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Resolve "individual transformation"
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@@ -286,6 +286,35 @@ Custom Data Handler
method is modified (see previous bullet).
* (optionally) Overwrite the base class :py:`self.get_coordinates()` method to return coordinates as dictionary with
keys *lon* and *lat*.
* (recommended) It is highly recommended to stay with our naming convention of data axis for an better integration into
MLAir. In principle, the naming can be set from outside and changed to any naming, but this must be done consequently.
We recommend therefore to use the following convention:
============== =========== =============================================================================================
dimension name default meaning
============== =========== =============================================================================================
time_dim "datetime" temporal axis, every new entry along this axis is assumed to be a new sample
iter_dim "Stations" iter axis that is a collection of different data "sources", this could be a collection of
stations or also a temporal split for a single year.
window_dim "window" this axis is the "2nd" dimension of each samples. This could be 2D data if only a single
timestamp is provided for each sample. In the default data handler, we use this dimension to
provide lagged data in each sample.
target_dim "variables" the target dim indicates where to find the target vector. Furthermore, this also contains
information on the "3rd" dimension of each sample. On input site, this can be used to provide
different channels (e.g. color channels). On target site, this indicates the dimension along
the target variable can be found. In the default data handler this dimension is used to flag
different variables.
filter_dim "filter" This is a custom dimension, which is used by some specific data handlers implemented by the
authors. It could be described as the "4th" dimension. It is always possible to define a
custom 4th dimension, but it could happen, that some parts of the code will not work very
well with this additional dimension. But have a try and otherwise report a bug.
============== =========== =============================================================================================
.. note::
The following code snippets are not up to date currently. Please read the requirements above for in-depth
information what MLAir is expecting from a custom data handler!
.. code-block:: python
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