add possibility for outpit file, parameterize report.gj
authorBenjamin Auder <benjamin.auder@somewhere>
Thu, 16 Mar 2017 19:10:51 +0000 (20:10 +0100)
committerBenjamin Auder <benjamin.auder@somewhere>
Thu, 16 Mar 2017 19:10:51 +0000 (20:10 +0100)
reports/ipynb_generator.py
reports/report.gj

index fedfa40..339f96a 100755 (executable)
@@ -17,7 +17,7 @@ shortname2language = dict(
     tex='Tex',
     )
 
-def read(text, argv=sys.argv[2:]):
+def read(text, argv=sys.argv[3:]):
     lines = text.splitlines()
     # First read all include statements
     for i in range(len(lines)):
@@ -122,17 +122,18 @@ def write(cells):
 def driver():
     """Compile a document and its variables."""
     try:
-        filename = sys.argv[1]
+        inputfile = sys.argv[1]
         with open(filename, 'r') as f:
             text = f.read()
+        outputfile = '-' if len(sys.argv) <= 2 else sys.argv[2]
     except (IndexError, IOError) as e:
-        print('Usage: %s filename' % (sys.argv[0]))
+        print('Usage: %s inputfile [outputfile|- [Mako args]]' % (sys.argv[0]))
         print(e)
         sys.exit(1)
-    cells = read(text, argv=sys.argv[2:])
+    cells = read(text, argv=sys.argv[3:])
     filestr = write(cells)
     # Assuming file extension .gj (generate Jupyter); TODO: less strict
-    filename = filename[:-3] + '.ipynb'
+    outputfile = inputfile[:-3]+'.ipynb' if outputfile == '-' else outputfile
     with open(filename, 'w') as f:
         f.write(filestr)
 
index dc4cbd4..3524e10 100644 (file)
@@ -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):
 -----
 <h2 style="color:blue;font-size:2em">${list_titles[i]}</h2>
 -----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)
 -----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))