* Check frequency of data
* If sub-daily, use plot_seasonality()
* Format xticks as weekdays for plot_seasonality()
* Display 8 xticks for weekly component
* Issue #1525: Using m.construct_holiday_dataframe() to make sure 'holidays' is a DataFrame.
* #1525 | issuecomment-639399524 | enhancement: have plotly graph the holiday component consistent with matplotlib.
Co-authored-by: Robin Teuwens <teuwens@electris.lu>
* update docstring with mdape in list for python perf metric func
* re-run python notebook cell to generate mdape in results table
* remove comment
Co-authored-by: Ben Letham <bletham@gmail.com>
To solve this [issue](https://github.com/facebook/prophet/issues/1437) by @chongdae
Korean lunar calendar which is different from Chinese lunar calendar is added python-holidays package recently.
This commit is about dropping the Korean and KR class in hdays.py file and hdays_part1(holidays) will work for Korean holidays.
```
import fbprophet.hdays as hdays_part2
import holidays as hdays_part1
``
* add implementation for constant trend
* force k and delta params to be 0s
* add tests and fix n_changepoints, changepoints_t to 0
* Add test for cv with constant trend
* Add docs and test for checking invalid input
* make changes to stan
* add transformed params block in stan and output flat trend vector
* correct syntax
* transformed params syntax
* Fix test and port changes to win stan file
* add test for flat trend function
* Add separate function for flat trend init
* fix test
* Add functions for serializing to/from JSON
* Fix list vs. series type issue, track version
* Avoid DateTimeIndex
* bugfix
* another fix
* Fix copy test
* Fix issue with pre-epoch dates
* Handle empty datetime series
* modified cross_validation to allow custom cutoffs
* moved set period, initials and identify larg. seas
* modified the diagnostics and added the test
* reverted cv default value tests and added a new custom cutoff test
* reorganized to raise the seasonality period warning message even if cutoffs are manually specified
* moved the initials vs. seasonality check
* changed assertCountEqual to assertItemsEqual in cv
* modified to test lengths instread of cutoff values
Co-authored-by: Fusi Marco <Marco.Fusi@valuelab.it>
* sampling iters arg name, logic changes
* Bump cmdstanpy version in requirements to 0.9.5
* Change Model to CmdStanModel
Co-authored-by: Ben Letham <bletham@gmail.com>
* Add multiprocessing Pool and create function for single cutoff forecast
* add params to single forecast function
* Add iterable for input params for pool
* Add docstring for single cutoff forecast func
* Add check for multiprocessing in test_cross_validation
* check ofr is None and is True and add better description for multiprocess in docstring
* Raise error if wrong args chosen and add test
* fix conflicts
* Change arg to True/False, model.kwargs
* docstring units and few more fixes
* change to iterator and add back tqdm to for loop
* add option in diagnosics notebook about multiprocessing option
* add extra test for checking calls to single forecast func
* tqdm
* Added progress bar to the crossvalidation
In order to improve the user experiance a progress bar is added to the crossvalidation loop.
* Update requirements.txt
* Update python/fbprophet/diagnostics.py
* updated further
* Update requirements.txt
