Modularize plotting APIs #27
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elisaliv
commented
Jul 28, 2023
| self._data_array = super().download_data() | ||
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| def transform_data(self: TimeSeriesPlotInstance): | ||
| df_down = self._data_array.rio.write_crs("EPSG:4326") |
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I still have to change variable names here
elisaliv
commented
Jul 28, 2023
| x=self._data_array.coords["time"], | ||
| markers="o", | ||
| ) | ||
| fig.update_xaxes(title="Month") |
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This should be a variable
| _plot_type: PlotType = PlotType.time_series | ||
| _data_array: DataArray |
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Not sure this is the right type. It becomes a dataframe in line 188
| _data_array: DataArray | ||
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| def __init__( | ||
| self: PlottingInterface, |
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I'd like to use named arguments here
| case DatasetName.eac4: | ||
| assert self.eac4_parameters is not None | ||
| data = EAC4Instance( | ||
| self.eac4_parameters.data_variable, |
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I think it would make sense if we used named args here as well, in the EAC4Instance class. I'd also suggest we make these class names more similar (e.g. EAC4Instance and GHGInstance?)
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The development is not finished yet. I'm opening a PR already so that you can check how I'm doing it and give me any feedback in the comments 🙂