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Station class #52

@AdamRJensen

Description

@AdamRJensen

I want to make my life easier. Less copying code snippets from example scripts.

Below is an example workflow that would make QC'ing solar radiation data even easier!

ds = solarpy.SolarDataset.from_t16("filename.csv", freq='1min', map_variables=True)

ds.calculate_solarposition(method="nrel-numpy")

ds.calculate_clearsky(method='cams', email='redacted@gmail.com')

ds.calculate_horizon()

ds.calculate_quality_flags()

# clean slicing that returns a new SolarDataset rather than a raw DataFrame slice, preserving meta and freq
ds.select(start, end)

fig, axes = ds.plot_shading_heatmap(parameter='ghi')

fig, axes = ds.multiplot()

Solar position and other derived variables could also be lazily computed, i.e., only computed when an action is executed that requires it.

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