Pedro Capelastegui

app.py currently lacks any unit tests. We should fix this.

We have been experimenting with using dask (https://dask.org/) to support parallel processing. Unfortunately, the code for some of these experiments has been left in tests.test_forecast.py in the main branch. We...

https://github.com/sky-uk/anticipy/community 3 missing elements: - Code of conduct - Issue templates - Pull request template

Before we start to optimise performance, we need to set up some benchmarks. Pandas uses the asv library (https://github.com/airspeed-velocity/asv), we can try that out.

Our forecast logic uses ForecastModel objects that encapsulate model functions and add additional features such as: - model composition: add and multiply models with the '+' and '*' operators -...

By default, run_forecast() includes naive models in the list of models to fit, and selects them when the performance of other models is poor. We should explain this in the...

We have seen forecasts crashing with the following error: ``` df_fcast4_err = forecast.run_forecast(df_fcast_input4_err, col_name_y='value', col_name_x='date', extrapolate_years=1) File "/home/jupyter_user/workspace/nsa.notebooks-voice/virtual/lib/python3.9/site-packages/anticipy/forecast.py", line 928, in run_forecast return run_forecast_single(df_y, File "/home/jupyter_user/workspace/nsa.notebooks-voice/virtual/lib/python3.9/site-packages/anticipy/forecast.py", line 1386, in run_forecast_single...

When calling `facet_wrap` with multiple facet variables, empty groups are included. This is somewhat inconvenient, and deviates from regular ggplot2 behaviour. Example: ```python import pandas as pd import numpy as...