From 2bde7359535832f8ce5475499796df085670fa31 Mon Sep 17 00:00:00 2001
From: Ben Elliston <bje@air.net.au>
Date: Thu, 25 Jan 2024 15:44:49 +1100
Subject: [PATCH] Pandas now produces a FutureWarning for frequency descriptor
 'H'. Use 'h' instead.

* nemo/context.py: Use 'h' for hourly frequency ('H' is deprecated).
* nemo/nem.py, nemo/sim.py: Likewise.
* tests/test_context.py, tests/test_sim.py: Likewise.
---
 nemo/context.py       | 2 +-
 nemo/nem.py           | 2 +-
 nemo/sim.py           | 2 +-
 tests/test_context.py | 2 +-
 tests/test_sim.py     | 2 +-
 5 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/nemo/context.py b/nemo/context.py
index 85047600..986bc9c2 100644
--- a/nemo/context.py
+++ b/nemo/context.py
@@ -127,7 +127,7 @@ def __str__(self):
             # constant). Group by the deltas.
             date_range = pd.date_range(self.unserved.index[0],
                                        periods=len(self.unserved.index),
-                                       freq='H')
+                                       freq='h')
             deltas = self.unserved.groupby(self.unserved.index - date_range)
             unserved_events = [k for k, g in deltas]
             string += 'Number of unserved energy events: '
diff --git a/nemo/nem.py b/nemo/nem.py
index 171ff2a2..5c162b25 100644
--- a/nemo/nem.py
+++ b/nemo/nem.py
@@ -47,7 +47,7 @@
     'demand data must start at midnight'
 
 # Calculate hourly demand, averaging half-hours n and n+1.
-hourly_regional_demand = demand.resample('H', closed='right').mean()
+hourly_regional_demand = demand.resample('h', closed='right').mean()
 
 # Now put the demand into polygon resolution according to the load
 # apportioning figures given in each region's polygons field.
diff --git a/nemo/sim.py b/nemo/sim.py
index 6256060a..e950a04b 100644
--- a/nemo/sim.py
+++ b/nemo/sim.py
@@ -135,7 +135,7 @@ def run(context, starthour=None, endhour=None):
         starthour = context.demand.index.min()
     if endhour is None:
         endhour = context.demand.index.max()
-    date_range = pd.date_range(starthour, endhour, freq='H')
+    date_range = pd.date_range(starthour, endhour, freq='h')
 
     _sim(context, date_range)
 
diff --git a/tests/test_context.py b/tests/test_context.py
index eea3fe10..e795a7ee 100644
--- a/tests/test_context.py
+++ b/tests/test_context.py
@@ -79,7 +79,7 @@ def test_str_with_unserved(self):
         # Dummy lambda functions for testing
         self.context.surplus_energy = lambda: 300
         self.context.unserved_percent = lambda: 0.5
-        rng = pd.date_range(start='2022-01-01', end='2022-01-02', freq='H')
+        rng = pd.date_range(start='2022-01-01', end='2022-01-02', freq='h')
         self.context.unserved = pd.Series(index=rng, data=range(len(rng)))
         output = str(self.context)
 
diff --git a/tests/test_sim.py b/tests/test_sim.py
index f44fe40e..49f636ad 100644
--- a/tests/test_sim.py
+++ b/tests/test_sim.py
@@ -24,7 +24,7 @@ class TestSim(unittest.TestCase):
     def setUp(self):
         """Test harness setup."""
         self.context = Context()
-        self.date_range = pd.date_range('2010-01-01', '2010-01-02', freq='H')
+        self.date_range = pd.date_range('2010-01-01', '2010-01-02', freq='h')
         self.generation = np.zeros((len(self.date_range),
                                     len(self.context.generators)))
         self.spill = np.zeros((len(self.date_range),