From 4bc19ead1eb4dd43b6f4c48c5dbb1d0723e25077 Mon Sep 17 00:00:00 2001
From: LukasFrankenQ <lukas.b.franken@gmail.com>
Date: Sun, 13 Aug 2023 13:57:41 +0100
Subject: [PATCH] fixed bug in weekly plotting

---
 config/config.yaml         | 22 ++++++++++++----------
 scripts/plot_timeseries.py | 29 +++++++++++++++++++++++------
 scripts/prepare_network.py |  2 +-
 3 files changed, 36 insertions(+), 17 deletions(-)

diff --git a/config/config.yaml b/config/config.yaml
index 9e6cca6d..96b06231 100644
--- a/config/config.yaml
+++ b/config/config.yaml
@@ -27,8 +27,8 @@ scenario:
   - 'eso' # regions can be 'eso' zones (emphasizing grid conjestion), or 'dno'
   fes: # Future energy scenario considered, can be 
   # - 'CT' # Consumer Transformation
-  - 'FS' # Falling Short
-  # - 'LW' # Leading the Way 
+  # - 'FS' # Falling Short
+  - 'LW' # Leading the Way 
   # - 'ST' # System Transformation
   year: # investment years for myopic and perfect; for overnight, year of cost assumptions can be different and is defined under 'costs'
   - 2023
@@ -65,7 +65,7 @@ flexibility:
   winter_months: [12, 1, 2]
   event_start_hour: 17
   event_end_hour: 19
-  heat_share_smart_tariff: 0.5 # share of consumers with heat pumps that have a smart tariff 
+  smart_heat_rollout_completion: 2030 # year where all heat pumps contribute to smart heat
   heat_shift_size: 3 # hours
   heat_flex_windows:
     morning:
@@ -122,15 +122,17 @@ flexibility:
       freq: h
       month: 1
     year:
-      freq: d
+      freq: w
     shortweek:
-      freq: h
-      start: 2022-01-21
-      end: 2022-01-27
+      start_month: 1
+      start_day: 21
+      end_month: 1
+      end_day: 27
     longweek:
-      freq: h
-      start: 2022-10-28
-      end: 2022-11-04
+      start_month: 10
+      start_day: 28
+      end_month: 11
+      end_day: 4
     do_group: true
     do_group_flex: false 
     add_kirchhoff: true
diff --git a/scripts/plot_timeseries.py b/scripts/plot_timeseries.py
index 57eb0622..97e1776c 100644
--- a/scripts/plot_timeseries.py
+++ b/scripts/plot_timeseries.py
@@ -187,14 +187,14 @@ def make_co2_barplot(n):
     plt.show()
 
 
-def get_timeseries_subset(*args , timeseries_mode="month", config=None):
+def get_timeseries_subset(*args, timeseries_mode="month", config=None):
+
+    assert args, "No dataframes passed"
 
     assert sum(
         [isinstance(arg, pd.DataFrame) or
          isinstance(arg, pd.Series) for arg in args]) == len(args), "Only one DataFrame can be passed as argument"
 
-    assert config is not None, "kwarg config has to be passed as non-None value"
-
     if (mode := timeseries_mode) in ["month", "year"]:
         freq = config["flexibility"]["timeseries_params"][mode].get("freq", "1H")
         month = config["flexibility"]["timeseries_params"][mode].get("month", range(1, 13))
@@ -207,15 +207,29 @@ def get_timeseries_subset(*args , timeseries_mode="month", config=None):
 
     
     elif mode in ["shortweek", "longweek"]:
-        start = config["flexibility"]["timeseries_params"][mode]["start"] 
-        end = config["flexibility"]["timeseries_params"][mode]["end"] 
 
-        s = args[0].index[(args[0].index >= pd.Timestamp(start)) & (args[0].index <= pd.Timestamp(end))]
+        frame = config["flexibility"]["timeseries_params"][mode]
+
+        start = pd.Timestamp(
+            year=2022,
+            month=frame["start_month"],
+            day=frame["start_day"]
+        )
+
+        end = pd.Timestamp(
+            year=2022,
+            month=frame["end_month"],
+            day=frame["end_day"]
+        )
+
+        s = args[0].index[(args[0].index >= start) & (args[0].index <= end)]
 
         args = list(map(lambda x: x.loc[s], args))
 
     else:
         raise ValueError(f"Unknown mode {mode}, should be one of 'month', 'year', 'shortweek', 'longweek'")
+    
+    return args
 
 
 if __name__ == "__main__":
@@ -274,6 +288,9 @@ def get_timeseries_subset(*args , timeseries_mode="month", config=None):
     # def get_timeseries_subset(*args , timeseries_mode="month", config=None):
 
     ts_mode = snakemake.wildcards["timeseries_mode"]
+
+    logger.info(f"Found time series mode {ts_mode}.")
+
     inflow, outflow = get_timeseries_subset(inflow, outflow,
         timeseries_mode=ts_mode,
         config=snakemake.config,
diff --git a/scripts/prepare_network.py b/scripts/prepare_network.py
index 03c41847..45a6889e 100755
--- a/scripts/prepare_network.py
+++ b/scripts/prepare_network.py
@@ -560,7 +560,7 @@ def add_heat_pump_load(
 
     complete_rollout_year = snakemake.config["flexibility"]["heat_shift_size"]
     share_smart_tariff = np.interp(
-        year, 
+        year,
         [2023, complete_rollout_year],
         [0., 1.]
         )