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* Support registering indicators of type IndicatorBase<BaseData>
* Add IndicatorBase<BaseData> scenario for all the usages of ConvertPythonIndicator
* Add all scenarios in the test case
* Fix IndicatorHistory api for options indicators
Fix for indicators based on OptionIndicatorBase to be able to use IndicatorHistory api. They require proper conversion of indicators from PyObjects
* Fix WarmupIndicator to support multi symbol indicators in Python
* Minor fix for WarmUpIndicator api
* Refactored switch statements for indicator conversion
* Solve comments review
* Refactored WarmUpIndicator to remove duplicated code
* Resolve review comments
---------
Co-authored-by: Jhonathan Abreu <jdabreu25@gmail.com>
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* Adds BroadcastCommand Method
Send a command to all live algorithms.
* Addresses Peer-Review
* Minor tweaks
---------
Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
* Add DualSymbolIndicator unit tests
* Introduce MultiSymbolIndicator for indicators working on multiple symbols
Use the new class as base for DualSymbolIndicator and OptionIndicatorBase.
The OptionIndicatorBase can now detect when ready even if underlying and options market close is different when resolution is daily.
* Accept any BaseData for options indicators
* Improve indicator conversion from python on registration
Also minor fixes
* Cleanup and simplification
* Fix ImpliedVolatility IsReady flag
* Update regression algorithm history count
AutomaticIndicatorWarmupOptionIndicatorsMirrorContractsRegressionAlgorithm history count decreased because options indicators period is now 1 instead of 2
* Address peer review
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* Normalize universe data frames
Universe and (generically BaseDataCollection) data frames are not normalize and unpacked into a data frame, instead of just creating data frames with the universe lists within it
* Fix unit tests and algorithms to expecte new universe dataframe format
* Fixes
* Add PandasConverter.DataFrameGenerator class
* Pandas data frame generator class fixes
* Add comments
* Housekeeping
* Add attributes to mark classes and properties for pandas processing
* Improve pandas properties expanding
Allow and handle duplicate names
* Use PandasData generalization for Lean common data types
* Add points time as column when converting base data collections to data frames
* Cleanup and minor changes
* Minor change
* Pandas data to get type members on demand
* Move Pandas helper classes to their own files
* Minor changes
* Add flatten argument to python history api
This allows users to decide whether they want fully expanded dataframes for universe and other collection data types. Else, master behavior is kept
* Adding missing changes to last commit
* Update Pythonnet version to 2.0.40
* Add flattent argument to algorithm's OptionChain api
* Minor changes
* Housekeeping
* Minor changes
* Bug fix skipping data collection data points
* Add comment
* Set correct exchange time to OptionUniverse instances
* Address peer review and cleanup
* Cleanup
* Minor changes
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* Fix ConsolidateRegressionAlgorithm
- Fix Bitcoin custom data time range. Historical data goes from April 2014
- Fix expected consolidated bar counts
- Fix python Consolidate implementations to respect daily strict times for Daily resolution
* Housekeeping
* Fix pandas converter to handle list of data with different symbols
* Properly convert list of data into dataframe
Take into consideration data for multiple symbols in the same list
* Cleanup
* Index dataframes by symbol object instead of SID string
* Add symbol equality operator to compare against object
* Exclude "ID" from option chain dataframe
* Minor fix
* Add greeks columns directly in option chain dataframe.
Also add pass-through properties for greek values in OptionUniverse
* Some cleanup
* Minor fix
* Add new QCAlgorithm.OptionChains() method
- Use OptionChains as output
- Add DataFrame to OptionChain and OptionChains
- Rename Greeks classes
- Add ISymbolProvider for classes that have a symbol (IBaseData, OptionContract)
* Unify QCAlgorithmOptionChain API
Also refactor OptionContract to handle: (1) Actual market data and option price model data, and (2) OptionUniverse data
* Pass symbol properties to OptionUniverse option chain from algorithm
* Format OptionContract for dataframe
* Minor fix
* Add multiple option chains api regression algorithms and other minor changes
* Address peer review
Add NullGreeks class: keep ModeledGreeks as internal as possible
* Minor fix and add PandasConverter unit tests
* Peer review: Non-thread-safe Lazy for Python
* Handle Greeks unwrapping by PandasData
* PandasData cleanup
* Add data and other minor changes
* Unit test fix
* Update Pythonnet to 2.0.39
* Cleanup
* PandasData handling children class members
Address peer review
* Fix: indexing symbol conversion in pandas mapper
* Fix pandas mapper to convert string keys to symbol only when necessary
* Cleanup
* Cleanup
* Add PandasColumn python class to handle proper indexing
This allows propery hash and equality between Symbols, C# strings and Python strings
* Minor fixes
* Symbol cache improvements
* Minor fix for cache miss
* Revert PandasMapper reserved names and improvements
* Minor fix
* Revert reserved names
* Minor fix for Symbol equality operators
---------
Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
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* Enhance command support
- Enhance command support, adding link helper methods. Adding and
expanding new tests
- Minor improvement for command str representation
* Minor test fix
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* Default daily precise end times
- Enable by default daily precise end times. Updating stats
- Minor fix for algorithm manager consolidator updates, adding new regression test
asserting behavior and updating others
- Minor fix for SubscriptionData creator avoid round down on warmup if
not appropiate
- Adjust consolidators to emit on daily strict end times if requested
daily resolution and setting enabled
- Updating regression algorithms
* Skip daily data on extended market hours
* Some cleanup and self review
* Revert unrequired change
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* First draft of the solution
* First draft of the tests
* Nit changes
* Nit change
* Add improvements
* Improve unit tests
* Regression algos
* Nit change
* Nit changes
* Improve unit tests
* Improve unit test
* Nit change
* Address reviews
* Add indicator helper methods for base Algorithm
- Add indicator helper methods for base algorithm. Adding new unit tests
* Expand indicators helper methods
- Expand indicators helper methods, adding support for C# and custom
indicators too. Adding unit tests
- Expand indicators helper methods to support multiple symbols as input.
Adding unit tests
- Improve conversion of symbol enumerable from python to C# adding unit
tests
* Address reviews
- Keep old QB.Indicator methods for backwards compatibility
- Rename new API to IndicatorHistory, matching
FutureHistory/OptionHistory
- Add new regression algorithms
- Minor improvement to DynamicData so it supports snake name access
* First draft of the solution
* Fix bugs
* Fix bugs
* Fix another overloaded method
* Add new unit test
* Address requested changes
* Address requested changes
* Minor tweaks
---------
Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
* Add Scheduled Universe Selection
- Adding `UniverseSettings.Schedule` that will allow users to
specify a custom selection schedule which is independent of the
underlying data frequency
- Adding unit and regression tests
* Add live trading schedule time shift
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* Refactor universe historical data source
- Add new universe history API methods
- Refactor QuantBook UniverseHistory to use the universe selection
itself instead of a given func
- Refactor and rename fundamental types
- Refactor AddUniverse API to handle universe collection data which
holds another type internally, like fundamental
* Fix minor bug causing ApiDataProvider not to serve Bitfinex universe data
* Further improvements to add universe API
* Handle no selection function
* Implement risk free interest rate as an algorithm model
* Use risk free insterest rate model in Sharpe Ratio indicator
* Address peer review
Also added python wrapper
* Take pyobject as interest rate model in Sharpe Ratio indicator
* Minor fix
* Minor fix
* Address peer review
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* New Fundamental Data
* Minor CIK lookup fix
* Handle live mode & delete unexisting properties
* Minor coarse fundamental adjustment
* Add fundamental history support
* Fix unit tests
* Performance improvements
* Fixes
* Minor regression algorithm fix
* Improvements. Add FundamentalUniverseSelectionModel
* Change default values
* Fix unit test
* Minor tweaks
* Fix unit test
* Minor error handling improvement
* Fix rebase
* Set default always open market hours entry for base security without subscription
Also return proper matching subscription for custom data symbols wihtout subscription.
* Minor changes
* Minor change
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- Custom data universe selection market hours. Adding regression test
asserting the behavior. Updating existing tests due to market hours
change, triggering selection always, even the 4th of July 2018
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* Solve the bug and add unit test
- The bug was raised because if something went wrong trying to register an indicator with a C# or a custom consolidator the exception raised was lost, because the catch sentence didn't return it with another exception
- A unit test was added asserting a exception with a related message was raised each time something went wrong with the consolidator
* Fix bugs and enhance unit tests
* Fix bug
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* Add dataMappingMode parameter to every history api method overload
* Minor unit tests fixes
* Update regression algorithm stats
* Minor changes
* Minor changes
* Add extendedMarket parameter to every history api method overload
* Rename extendedMarketHours parameter
New name is extendedHours as in the History API to standarize parameters naming
* Update generic history overloads to use every matching subscription
* Update regression algorithms stats
* Centralize period-based history error for tick resolution
* Rename extended market hours parameter to extendedMarketHours
* Minor changes
* Minor changes
* Minor unit tests changes
* Minor unit tests changes
* Minor changes
* Minor unit tests changes
* Minor unit tests changes
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* Add fillForward parameters to every History method
* Remove conflicting Python history method
* Undo removing conflicting Python history method
* Minor changes
* Minor changes
* Minor changes
* Add fillForward and extendedMarket parameters to history request factory
* Minor changes
* Minor changes
* Minor changes
* Minor changes
* Minor unit tests changes
* Rename fillForward parameter in History API
New name if fillDataForward as in the Add*Security API to standarize
parameters naming
* Rename fillForward parameter
Using the shorter fillForward in every API
* Memory Related Performance improvements
- Make sure we cleanup & dipose of python related objects during pandas
data generation.
- Disable memoizing enumerable use while creating pandas data frames,
since we do not require it
- Reduce unrequired object creations
- Replace concurrentCollections for ordinary locks
* Decimal parsing typo fix
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* Get history of a given bar type in python
* Separate GetDataFrame in sub methods to avoid dynamic type resolution
* Housekeeping and unit tests update
* Use all requests in python type method history method
* Address changes request
* Reverted some requested changes
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* Add new Python QCAlgorithm.History() method with all parameters and type
* Add regression algorithms
* Using all parameters in History()
* Use private methods to reuse History() code
* Use private methods to reuse History() code
* Add unit tests for QCAlgorithm.Python.History()
* Add unit tests for QCAlgorithm.Python.History()
* Add unit tests for QCAlgorithm.Python.History()
* Add unit tests for QCAlgorithm.Python.History()
* Add unit tests for QCAlgorithm.Python.History()
* Add unit tests for QCAlgorithm.Python.History()
* Asserting history count
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* First commit
* Add unit test
* Change implementation
* Add unit tests
* Nit change
* nit change
* Remove unnecessary methods
* Add more unit tests
* Revert "Add more unit tests"
This reverts commit 1ba2ab7454efafba7c38034a15df3f8e97bc7146.
* Add more unit tests
* Add more unit tests
* Improve Implementation
* Change unit tests
* Remove unit tests
Remove unit tests from AlgorithmRegisterIndicatorTests.cs
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* Add requested History overload
* Add more regression tests
* Revert "Add more regression tests"
This reverts commit 71b279e917629c3d5ed577e39aec74149b052afb.
* Add more regression tests
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`WarmUpIndicator` for Python indicators doesn't return the indicator anymore after #6027. So all overloads should return `void`.
Fixes `SmaCrossUniverseSelectionAlgorithm` [C# and Py].
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* Implement IIndicatorWarmUpPeriodProvider
- Implement IIndicatorWarmUpPeriodProvider in PythonIndicator.cs
- Make a unit test to check whether the WarmUpPeriod is working as expected
- Make a regression test to check the new feature at a system level
* Nit change
* Change Period parameter for WarmUpPeriod parameter
- Change regression test to check if the new parameter keep backwards compatibility with indicators that do not set WarmUpPeriod
* Documentation change
* Fix tests bugs
- In CommonIndicatorTests.cs before finish the test it checks the period.value with the number of samples but for default the period.value was set to -1
* Change names
* Change WarmUp and RegisterIndicator methods
- Lean WarmUp indicator skip custom python indicators that don't define WarmUpPeriod parameter
* Call WarmUpIndicator manually
- Add a new "bridge" method called WarmUpIndicator in QCAlgorithm.Python.cs to set up everything to call WarmUpIndicator in QCAlgorithm.Indicators.cs
- Change the regression algorithm to warm up the indicators manually
* Remove unnecessary code and add more tests
* Nit change
* Revert "Nit change"
This reverts commit da411f59c9e4295d75a11c6c581f615a938dd2c6.
* Fix bugs
* Try fix bugs
* Add C# regression test
- More nit changes
- Fix bugs
* Requested changes
* Remove unnecessary code
* Requested changes
* Nit changes
- Add new Python class to check a custom indicator, which doesn't inherits from PythonIndicator, warms up properly
* Reduce redundant code
* Fix bug and add more unit and regression tests
* - Add more unit tests
* Nit change
* Test cleanup
Co-authored-by: Martin-Molinero <martin@quantconnect.com>
JosueNina