Refine nametuple tutorial #1071
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Parth-Vachhani
commented
May 30, 2024
Parth-Vachhani
commented
- Describe your pull request as transparent as possible
- What functionality does it implement?
- Where is it located?
- How does the API look?
- ...
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- Share your knowledge: Insights/Remarks
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- For new features: Remember the documentation!
This is not really "basic" and can lead to errors. I still left it in and put some additional explanation so that beginners learn about the concept but do not have it in their code without thinking about it.
Set oemof.network requirement to stable release
We require the experimental feature warning.
I think it will increase maintainability if we do not have to care for compatibility with Pandas 1.x. (I used new features for a solph tutorial and people had unexpected problems because of unsupported features in their Pandas installation.)
…anced readability.
Explicitly pass `custom_properties` to `network.Node` class
Although it is just an example, having hard-coded unreachable code can be considered bad style.
Co-authored-by: Patrik Schönfeldt <github@patrikschoenfeldt.de>
Co-authored-by: Patrik Schönfeldt <github@patrikschoenfeldt.de>
… British 'Optimise'-Spelling-version
Improved variable naming and formatting in 'basic_example.py' for enh…
Deactivate dump/restore in basic example
…etConverter Multiple Outputs for OffsetConverter
I did not touch the multi-period-model as I think the constraint for this (experimental) mode needs refactoring anyway.
The auto-stretch feature of the _Sequence contained hidden magic, as it tracked the last "entry" that has been accessed and pretended to have a length based on this. So, outcomes depend on something that is assumed to be a read access. Also, self.data was erived from UserList but never really supported all of the expected functionality in a consistent way. The new _FakeSequence is a lot simpler. In particular it has an explicit (fake) length that needs to be set before casting to (stretched) lists. The default length is still set, because there is an entry, and to allow to directly iterate over a _FakeSequence, e.g. in sum().
To allow this, some checks need to more explicit, now. As solph.sequence will return a _FakeSequence or a numpy.array, other members of _FakeSequence mimic the API of numpy.array. In particular, this allows min/max/sum operations in constant time.
We can test for the _FakeSequence class to see that something really is a scalar.
…uence Replace _Sequence by _FakeSequence
…ral_limit Allow lower limit for generic_integral_limit
Formulate full_load_time docstring specific for energy
…l-level Fix/storage costs for initial level
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