* Support List and OptionFilterUniverse for Py filter
* Regression algorithm for testing
* Unit Tests
* Fix for process
* Tighten filters to reduce load on automated testing
* Address review v2
* DataConsolidator Wrapper for Python Consolidators
* Regression Unit Test
* Refactor Regression test
* Bad test fix
* pre review
* self review
* Add RegisterIndicator for Python Consolidator
* Python base class for consolidators
* Modify regression algo to register indicator
* unit test - attach event
* Test fix
* Fix test python imports
* Add license header file and null check
Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
* When a BaseData instance has Nullable fields, the number of data
points per Series is inconsistent, and results in a Series with
a length different from the other Series we produce, resulting
in an error "ValueError: cannot handle a non-unique multi-index!"
when we were constructing the final DataFrame.
Methods: 'diff', 'div', 'divide', 'drop', 'drop_duplicates', 'droplevel', 'dropna', 'dtypes', 'duplicated'
`BackwardsCompatibilityDataFrame_binary_operator` replaces `BackwardsCompatibilityDataFrame_add` to handle all operations (more to be added in future commits)
`Remapper.__getitem__` was not returns a `Remapper` object when the result was `pandas.DataFrame`. It is needed for a sequence of `.loc.` calls.
Refactors `Remapper._self_mapper` to handle tuples where the key can be found in both first and second position.
Update unit tests that should test `Symbol` object as key, but were using `str(Symbol)`.
- AlgorithmPythonWrapper will directly call base OnFrameworkData()
implementation skipping going through python and it's overhead
- Small performance improvement for adding Tick data points into a Ticks
collection
- For python always wrap slice with PythonSlice, so that slice.Get()
works even when no custom data is present, adding test.
- Remove unrequired `GetBuyingPower`
- Making `BuyingPowerModel.GetMaintenanceMarginRequirement` protected
instead of public
- Adding `GetMaximumOrderQuantityForDeltaBuyingPower` to replace
public `GetMaintenanceMarginRequirement` and improve API experience for
consumers like the `DefaultMarginCallModel`
- Adding new unit tests
- Add support for Symbol key access for pandas ix and iloc results
- Wrapp pdf merge, join, concat method results
- Wrapp pandas.concat method result with `Remapper`
- Adding unit tests
- Use `/usr/share/nltk_data` instead of `/root/nltk_data`.
- Adds test for NLTK.
- Tidies the root directory of the docker image
- Adds support to mlfinlab
- Adding `SecurityCacheProvider` this class allows for two different
`Security` to share the same data type cache through different instance
of `SecurityCache`. This is used to directly access custom data types
through their underlying in a peformant maner
- Some small improvements
- Covers another level on inheritance of Market Data by using `Type.IsAssignableFrom`
- Caches the list of `MethodInfo` for custom data types to avoid redefining that list.
When custom data classes inherited from market data classes such as `TradeBar`, it created duplicate entries. Therefore, we need to exclude the common properties in the private field `PandasData._members`.
Adds IRegisteredSecurityDataTypesProvider to track all the data types
registered in the algorithm. Using this data, we can detect if it's
possible that we'll eventually have a property of a certain type name.
For example, consider I wish to use security.Data.TradeBar but we haven't
received any trade bars yet. Before this change a KeyNotFoundException
would be raised, but since we can determine that we expect to have trade
bars, we can detect this and return an empty list when we haven't received
any data yet. This also removes the need to constantly do a HasData<T>()
check before accessing the dynamic members.
Closes#3620
* Deleted regression algorithms because they tested behavior similar to
other existing regression algorithms
* Fixed new bug in regression algorithm due to AddData changes
* Added unit tests for wrapt version and package existence
* Fix issue where data would be set to raw normalization mode
- Moving mapper from C# to Python since some cases did not work when
implemented in C#
- Small changes to `PandasDataFrameHistoryAlgorithm` which runs till the
end with no errors
- Adding more backwards compatible unit tests
- Add Pandas backwards compatibility shim
- Adding `MappingExtensions` which will remove data type from the
`Symbol.ID.Symbol` value to resolve the `MapFile`
- `SecurityIdentifier.TryParse()` will throw when given an invalid
`SecurityType`
Colton Sellers