Fix different vert level conflict when plotting

Remove this code because if the cases have different number of vertical levels, then the concat datasets will cause problems (they will combine the levels into the new lev dim).

```python
#Check to see if any cases were successful
if runname_LT:
    runname_LT=xr.DataArray(runname_LT, dims='run', coords=[np.arange(0,len(runname_LT),1)], name='run')
```

Also clean up code for readability, and change data read in (plus CESM time fix) to new data class method.

Author: justin-richling

scripts/plotting/tape_recorder.py

@@ -89,6 +89,8 @@ def tape_recorder(adfobj):
         # Filter the list to include only strings that are exactly in the substrings list
         base_hist_strs = [string for string in baseline_hist_strs if string in substrings]
         hist_strs = case_hist_strs + base_hist_strs
+    else:
+        hist_strs = case_hist_strs
     #End if
 
     if not case_ts_locs:
@@ -126,6 +128,7 @@ def tape_recorder(adfobj):
 
     #This may have to change if other variables are desired in this plot type?
     plot_name = plot_loc / f"{var}_TapeRecorder_ANN_Special_Mean.{plot_type}"
+
     print(f"\t - Plotting annual tape recorder for {var}")
 
     # Check redo_plot. If set to True: remove old plot, if it already exists:
@@ -138,11 +141,8 @@ def tape_recorder(adfobj):
     elif (redo_plot) and plot_name.is_file():
         plot_name.unlink()
 
-    #Make dictionary for case names and associated timeseries file locations and hist strings
-    runs_LT2={}
-    for i,val in enumerate(test_nicknames):
-        runs_LT2[val] = [case_ts_locs[i], hist_strs[i]]
-
+    # Plotting
+    #---------
     # MLS data
     mls = xr.open_dataset(obs_loc / "mls_h2o_latNpressNtime_3d_monthly_v5.nc")
     mls = mls.rename(x='lat', y='lev', t='time')
@@ -158,38 +158,7 @@ def tape_recorder(adfobj):
     era5 = era5.groupby('time.month').mean('time')
     era5_data = era5.Q
 
-    alldat=[]
-    runname_LT=[]
-    for idx,key in enumerate(runs_LT2):
-        # Search for files
-        ts_loc = Path(runs_LT2[key][0])
-        hist_str = runs_LT2[key][1]
-        fils= sorted(ts_loc.glob(f'*{hist_str}.{var}.*.nc'))
-        dat = pf.load_dataset(fils)
-        if not dat:
-            dmsg = f"\t No data for `{var}` found in {fils}, case will be skipped in tape recorder plot."
-            print(dmsg)
-            adfobj.debug_log(dmsg)
-            continue
-        dat = fixcesmtime(dat,start_years[idx],end_years[idx])
-        datzm = dat.mean('lon')
-        dat_tropics = cosweightlat(datzm[var], -10, 10)
-        dat_mon = dat_tropics.groupby('time.month').mean('time').load()
-        alldat.append(dat_mon)
-        runname_LT.append(key)
-
-    #Check to see if any cases were successful
-    if runname_LT:
-        runname_LT=xr.DataArray(runname_LT, dims='run', coords=[np.arange(0,len(runname_LT),1)], name='run')
-        alldat_concat_LT = xr.concat(alldat, dim=runname_LT)
-    else:
-        msg = f"WARNING: No cases seem to be available, please check time series files for {var}."
-        msg += "\n\tNo tape recorder plots will be made."
-        print(msg)
-        #End tape recorder plotting script:
-        return
-
-    #Set up figure for plots
+    #Set up figure and plot MLS and ERA5 data
     fig = plt.figure(figsize=(16,16))
     x1, x2, y1, y2 = get5by5coords_zmplots()
 
@@ -205,15 +174,42 @@ def tape_recorder(adfobj):
                       'ERA5',x1[1],x2[1],y1[1],y2[1], cmap=cmap, paxis='pre',
                       taxis='month',climo_yrs="1980-2020")
 
+
     #Loop over case(s) and start count at 2 to account for MLS and ERA5 plots above
+    runname_LT=[]
     count=2
-    for irun in np.arange(0,alldat_concat_LT.run.size,1):
-        title = f"{alldat_concat_LT.run.isel(run=irun).values}"
-        ax = plot_pre_mon(fig, alldat_concat_LT.isel(run=irun),
-                          plot_step, plot_min, plot_max, title,
+    for idx,key in enumerate(test_nicknames):
+        # Search for files
+        ts_loc = Path(case_ts_locs[idx])
+        hist_str = hist_strs[idx]
+        fils = sorted(ts_loc.glob(f'*{hist_str}.{var}.*.nc'))
+        dat = adfobj.data.load_timeseries_dataset(fils)
+
+        if not dat:
+            dmsg = f"\t No data for `{var}` found in {fils}, case will be skipped in tape recorder plot."
+            print(dmsg)
+            adfobj.debug_log(dmsg)
+            continue
+
+        #Grab time slice based on requested years (if applicable)
+        dat = dat.sel(time=slice(str(start_years[idx]).zfill(4),str(end_years[idx]).zfill(4)))
+        datzm = dat.mean('lon')
+        dat_tropics = cosweightlat(datzm[var], -10, 10)
+        dat_mon = dat_tropics.groupby('time.month').mean('time').load()
+        ax = plot_pre_mon(fig, dat_mon,
+                          plot_step, plot_min, plot_max, key,
                           x1[count],x2[count],y1[count],y2[count],cmap=cmap, paxis='lev',
-                          taxis='month',climo_yrs=f"{start_years[irun]}-{end_years[irun]}")
+                          taxis='month',climo_yrs=f"{start_years[idx]}-{end_years[idx]}")
         count=count+1
+        runname_LT.append(key)
+
+    #Check to see if any cases were successful
+    if not runname_LT:
+        msg = f"WARNING: No cases seem to be available, please check time series files for {var}."
+        msg += "\n\tNo tape recorder plots will be made."
+        print(msg)
+        #End tape recorder plotting script:
+        return
 
     #Shift colorbar if there are less than 5 subplots
     # There will always be at least 2 (MLS and ERA5)
@@ -348,17 +344,6 @@ def precip_cmap(n, nowhite=False):
 
 #########
 
-def fixcesmtime(dat,syear,eyear):
-    """
-    Fix the CESM timestamp with a simple set of dates
-    """
-    timefix = pd.date_range(start=f'1/1/{syear}', end=f'12/1/{eyear}', freq='MS') # generic time coordinate from a non-leap-year
-    dat = dat.assign_coords({"time":timefix})
-
-    return dat
-
-#########
-
 def get5by5coords_zmplots():
     """
     positioning for 5x5 plots