Basic Usage

Imports

from magi.core import forecast
from magi.plotting import fc_plot, acc_plot
from magi.utils import gen_ts
from magi.accuracy import accuracy

Single series R model

Input format should be a series with datetime index

from magi import *
df = gen_ts()
fc_obj = forecast(time_series=df['ts2'],forecast_periods=18,frequency=12)
forecast_dic = fc_obj.R(model='auto.arima(rdata,D=1,stationary=TRUE)')

Plot single series accuracy

fc_plot(forecast_dic)

Calculate accuracy measures single series

acc_dict = accuracy(forecast_dic)

Plot accuracy measures single series

acc_plot(acc_dict)

Multiple Series R model in parallel

Input format should be a dataframe of series with datetime index with datetime index, returning fitted and predicted values in a dataframe

from dask.distributed import Client, LocalCluster
import dask
cluster = LocalCluster()
client = Client(cluster)
df = gen_ts()
fc_obj = forecast(time_series=df,forecast_periods=18,frequency=12)
forecast_df = fc_obj.R(model='thetaf',fit=True)

Plot multiple series results

fc_plot(forecast_df)

Calculate overall accuracy measures multiple series

acc_dict = accuracy(df,forecast_df)

Calculate accuracy measures per series

acc_df = accuracy(df,forecast_df,separate_series=True)

Plot accuracy measures by series

acc_plot(acc_df)