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Bugfix aim and order (#5)

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* fix: 🐞 Fixed an ordering issue when saving to CSV

* chore: 🧹 Ruff clean up
This commit is contained in:
Jake-Pullen
2025-12-24 15:34:58 +00:00
committed by GitHub
parent 0e682aca35
commit 22a338f790
2 changed files with 23 additions and 36 deletions
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modules/generate_timeseries.py
+16 -33
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@@ -56,11 +56,11 @@ class GenerateTimeseries:
xpp = ncols_basin * cellres_basin
ypp = nrows_basin * cellres_basin
start_col = np.floor(xp / cellres_radar)
end_col = np.ceil((xpp + xp) / cellres_radar)
start_col = np.floor(xp / cellres_radar) - 1
end_col = np.ceil((xpp + xp) / cellres_radar) - 1
start_row = np.floor(nrows_radar - ((yp + ypp) / cellres_radar))
end_row = np.ceil(nrows_radar - (yp / cellres_radar))
start_row = np.floor(nrows_radar - ((yp + ypp) / cellres_radar)) + 1
end_row = np.ceil(nrows_radar - (yp / cellres_radar)) + 1
return int(start_col), int(start_row), int(end_col), int(end_row)
@@ -178,43 +178,26 @@ class GenerateTimeseries:
zone_name = loc[3]
if zone_name not in zone_data:
zone_data[zone_name] = {"dates": [], "values": {}}
zone_data[zone_name] = {"dates": set(), "values": {}}
zone_data[zone_name]["values"][zone_id] = results[zone_id]["values"]
zone_data[zone_name]["dates"].extend(results[zone_id]["dates"])
# Create date -> value map for this grid square
raw_dates = results[zone_id]["dates"]
raw_values = results[zone_id]["values"]
date_value_map = dict(zip(raw_dates, raw_values))
# Get unique sorted dates across all zones
for zone_name, data in zone_data.items():
data["dates"] = sorted(set(data["dates"]))
zone_data[zone_name]["values"][zone_id] = date_value_map
zone_data[zone_name]["dates"].update(raw_dates)
# Now write one CSV per zone with aligned timestamps
for zone_name, data in zone_data.items():
dates = data["dates"]
sorted_dates = sorted(data["dates"])
values_dict = data["values"]
# Create aligned DataFrame
df_dict = {"datetime": dates}
for grid_square, values in values_dict.items():
# Align values to the common dates
aligned_values = []
value_iter = iter(values)
date_iter = iter(dates)
current_date = next(date_iter, None)
current_value = next(value_iter, None)
for expected_date in dates:
if current_date == expected_date:
aligned_values.append(current_value)
try:
current_date = next(date_iter)
current_value = next(value_iter)
except StopIteration:
current_date = None
current_value = None
else:
aligned_values.append(None) # Missing value
df_dict = {"datetime": sorted_dates}
for grid_square, dv_map in values_dict.items():
# Align values to the common search dates using the map
aligned_values = [dv_map.get(d) for d in sorted_dates]
df_dict[grid_square] = aligned_values
new_df = pd.DataFrame(df_dict)