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)