From 6ae9e5f9483d5a83c15476bfc5baa86d50840b5b Mon Sep 17 00:00:00 2001
From: Adriano Meligrana <68152031+Tortar@users.noreply.github.com>
Date: Thu, 28 Nov 2024 23:46:32 +0100
Subject: [PATCH] Update get_parameters_and_initial_conditions.jl

---
 .../get_parameters_and_initial_conditions.jl  | 25 +++++++++----------
 1 file changed, 12 insertions(+), 13 deletions(-)

diff --git a/examples/get_parameters_and_initial_conditions.jl b/examples/get_parameters_and_initial_conditions.jl
index e0a20e3..cc946ce 100644
--- a/examples/get_parameters_and_initial_conditions.jl
+++ b/examples/get_parameters_and_initial_conditions.jl
@@ -3,21 +3,23 @@
 import BeforeIT as Bit
 using Dates, FileIO
 
-
-# We start from loading the calibration oject for italy, which contains 4 datasets: calibration_data, figaro, data, and ea
-# These are saved within BeforeIT for the Italian case, and would need to be appropriately generated for other countries
+# We start from loading the calibration object for italy, which contains 
+# 4 datasets: `calibration_data`, `figaro`, `data`, and `ea`. These are
+# saved within `BeforeIT.jl` for the Italian case, and would need to be
+# appropriately generated for other countries.
 
 cal = Bit.ITALY_CALIBRATION
-
 fieldnames(typeof(cal))
 
-# These are essentually 4 dictionaries with well defined keys, such as
+# These are essentially 4 dictionaries with well defined keys, such as
+
 println(keys(cal.calibration))
 println(keys(cal.figaro))
 println(keys(cal.data))
 println(keys(cal.ea))
 
 # The object also contains two time variables related to the data
+
 println(cal.max_calibration_date)
 println(cal.estimation_date)
 
@@ -26,19 +28,18 @@ println(cal.estimation_date)
 calibration_date = DateTime(2010, 03, 31)
 parameters, initial_conditions = Bit.get_params_and_initial_conditions(cal, calibration_date; scale = 0.01)
 
-# In sgeneral, we might want to repeat this operation for multiple quarters.
-# In the following, we loop over all quarters from 2010Q1 to 2019Q4
+# In general, we might want to repeat this operation for multiple quarters.
+# In the following, we loop over all quarters from `2010Q1` to `2019Q4`
 # and save the parameters and initial conditions in separate files.
 # We can then load these files later to run the model for each quarter.
+
 start_calibration_date = DateTime(2010, 03, 31)
 end_calibration_date = DateTime(2019, 12, 31)
 
 for calibration_date in collect(start_calibration_date:Dates.Month(3):end_calibration_date)
     params, init_conds = Bit.get_params_and_initial_conditions(cal, calibration_date; scale = 0.0005)
     save(
-        "data/" *
-        "italy/" *
-        "/parameters/" *
+        "data/italy/parameters/" *
         string(year(calibration_date)) *
         "Q" *
         string(Dates.quarterofyear(calibration_date)) *
@@ -46,9 +47,7 @@ for calibration_date in collect(start_calibration_date:Dates.Month(3):end_calibr
         params,
     )
     save(
-        "data/" *
-        "italy/" *
-        "/initial_conditions/" *
+        "data/italy/initial_conditions/" *
         string(year(calibration_date)) *
         "Q" *
         string(Dates.quarterofyear(calibration_date)) *