Add George recipe info & make fixes for original recipe 19

Author: sadielbartholomew

docs/source/recipes/plot_19_recipe.py

@@ -1,3 +1,10 @@
+"""
+Recipe 1: Calculating and Plotting Seasonal Mean Pressure at Mean Sea Level
+
+Objective: Calculate and plot the seasonal mean pressure at mean sea level
+from ensemble simulation data for 1941.
+"""
+
 import cfplot as cfp
 import cf
 import numpy as np
@@ -6,65 +13,30 @@
 import matplotlib.pyplot as plt
 
 # 1. Load the dataset
-file_path = "~/Documents/Datasets/ERA5_monthly_averaged_SST.nc"
-f = cf.read(file_path)
+f = cf.read("~/recipes_break/ERA5_monthly_averaged_SST.nc")
 sst = f[0]  # Select the SST variable
 
 # Collapse data by area mean (average over spatial dimensions)
 am = sst.collapse("area: mean")  # equivalent to "X Y: mean"
 am.squeeze(inplace=True)
 
-# Check available coordinates (already found 'dimensioncoordinate0' as the time coordinate)
+# Check available coordinates (already found 'dimensioncoordinate0' as the
+# time coordinate)
 print("Available coordinates:", am.coordinates())
 
-am_data_key = am.coordinate("dimensioncoordinate0", key=True)
-am_copy = am.copy().subspace(**{am_data_key: cf.mam()})
-print(am_copy)
-exit()
-# Retrieve the time coordinate using its internal identifier
-am_data = am.coordinate("dimensioncoordinate0")
-am_data_copy = am_copy.coordinate("dimensioncoordinate0")
-# Convert the time data from 'hours since 1900-01-01' to datetime format
-#time_units = time_coord.units
-#am_time = time_coord.data
-#am_time_datetime = am.subspace(T=cf.dt("2022-12-01 00:00:00"))
-
-# Convert datetime to numeric values for plotting (e.g., using matplotlib date format)
-#am_time_numeric = pd.to_numeric(pd.to_datetime(am_time_datetime))
-
-# Extract data and replace missing values
-#am_data = am.data
-#am_data = np.where(am_data == -32767, np.nan, am_data)
-
-# Create the line plot using the full dataset with numeric x-axis
-
-
-print(am[:10])
-print(am_data[:10].data.datetime_as_string)
+am_dim_key, am_data = am.coordinate("dimensioncoordinate0", item=True)
+am_sub = am.subspace(**{am_dim_key: cf.mam()})
 
-cfp.gopen(file="Recipe3.png")  # Start the plot
+cfp.gopen(file="global_avg_sst_plot.png")
 cfp.lineplot(
-    x=am_data,
-    y=am,
+    am,
     color="blue",
     title="Global Average Sea Surface Temperature",
     ylabel="Temperature (K)",
     xlabel="Time"
 )
-
 cfp.lineplot(
-    x=am_data_copy,
-    y=am_copy,
+    am_sub,
     color="red",
 )
-cfp.gclose()  # Finish the plot
-
-
-# Save the plot to a file using matplotlib
-plt.savefig("global_avg_sst_plot.png")
-
-# Show the plot interactively
-plt.show()
-
-print("Plot created and saved successfully.")
-
+cfp.gclose()