X-Git-Url: https://git.auder.net/images/pieces/Cwda/ww.svg?a=blobdiff_plain;f=reports%2Freport.gj;h=088b43efb9ccd0435c2f61d62acd8de8339b0557;hb=55639673dd1510a02671c4646813ae346cdca4d6;hp=dc4cbd4b8739aa850fdcabdaf3592262e202068e;hpb=d4841a3f15f94ce0520559aed9466c9c3f259d68;p=talweg.git
diff --git a/reports/report.gj b/reports/report.gj
index dc4cbd4..088b43e 100644
--- a/reports/report.gj
+++ b/reports/report.gj
@@ -26,26 +26,30 @@ library(talweg)
ts_data = read.csv(system.file("extdata","pm10_mesures_H_loc_report.csv",package="talweg"))
exo_data = read.csv(system.file("extdata","meteo_extra_noNAs.csv",package="talweg"))
-data = getData(ts_data, exo_data, input_tz = "Europe/Paris", working_tz="Europe/Paris", predict_at=13)
+data = getData(ts_data, exo_data, input_tz = "Europe/Paris", working_tz="Europe/Paris",
+ predict_at=${P}) #predict from P+1 to P+H included
indices_ch = seq(as.Date("2015-01-18"),as.Date("2015-01-24"),"days")
indices_ep = seq(as.Date("2015-03-15"),as.Date("2015-03-21"),"days")
indices_np = seq(as.Date("2015-04-26"),as.Date("2015-05-02"),"days")
-H = 17 #predict from 8am to 12pm
% for i in range(3):
-----
${list_titles[i]}
-----r
-p_nn_exo = computeForecast(data, ${list_indices[i]}, "Neighbors", "Neighbors", simtype="exo", horizon=H)
-p_nn_mix = computeForecast(data, ${list_indices[i]}, "Neighbors", "Neighbors", simtype="mix", horizon=H)
-p_az = computeForecast(data, ${list_indices[i]}, "Average", "Zero", horizon=H) #, memory=183)
-p_pz = computeForecast(data, ${list_indices[i]}, "Persistence", "Zero", horizon=H, same_day=TRUE)
+p_nn_exo = computeForecast(data, ${list_indices[i]}, "Neighbors", "Neighbors",
+ horizon=${H}, simtype="exo")
+p_nn_mix = computeForecast(data, ${list_indices[i]}, "Neighbors", "Neighbors",
+ horizon=${H}, simtype="mix")
+p_az = computeForecast(data, ${list_indices[i]}, "Average", "Zero",
+ horizon=${H})
+p_pz = computeForecast(data, ${list_indices[i]}, "Persistence", "Zero",
+ horizon=${H}, same_day=${'TRUE' if loop.index < 2 else 'FALSE'})
-----r
-e_nn_exo = computeError(data, p_nn_exo, H)
-e_nn_mix = computeError(data, p_nn_mix, H)
-e_az = computeError(data, p_az, H)
-e_pz = computeError(data, p_pz, H)
+e_nn_exo = computeError(data, p_nn_exo, ${H})
+e_nn_mix = computeError(data, p_nn_mix, ${H})
+e_az = computeError(data, p_az, ${H})
+e_pz = computeError(data, p_pz, ${H})
options(repr.plot.width=9, repr.plot.height=7)
plotError(list(e_nn_mix, e_pz, e_az, e_nn_exo), cols=c(1,2,colors()[258], 4))