Merge pull request #53 from eleanorfrajka/eleanor-patch-5

[feat] Added some checks for cells that expect particular variables (e.g., CHLA or DOXY)
OceanGlidersCommunity · Oct 31, 2024 · b68aad2 · b68aad2
2 parents 8dff4a4 + 7d76da0
commit b68aad2
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Showing 2 changed files with 42 additions and 22 deletions.
diff --git a/glidertest/tools.py b/glidertest/tools.py
@@ -66,14 +66,19 @@ def updown_bias(ds, var='PSAL', v_res=1):
     """
     p = 1  # Horizontal resolution
     z = v_res  # Vertical resolution
-    varG, profG, depthG = grid2d(ds.PROFILE_NUMBER, ds.DEPTH, ds[var], p, z)
+    if var in ds.variables:
+        varG, profG, depthG = grid2d(ds.PROFILE_NUMBER, ds.DEPTH, ds[var], p, z)
 
-    grad = np.diff(varG, axis=0)  # Horizontal gradients
+        grad = np.diff(varG, axis=0)  # Horizontal gradients
 
-    dc = np.nanmean(grad[0::2, :], axis=0)  # Dive - CLimb
-    cd = np.nanmean(grad[1::2, :], axis=0)  # Climb - Dive
+        dc = np.nanmean(grad[0::2, :], axis=0)  # Dive - CLimb
+        cd = np.nanmean(grad[1::2, :], axis=0)  # Climb - Dive
+
+        df = pd.DataFrame(data={'dc': dc, 'cd': cd, 'depth': depthG[0, :]})
+    else:
+        print(f'{var} is not in the dataset')
+        df = pd.DataFrame()
 
-    df = pd.DataFrame(data={'dc': dc, 'cd': cd, 'depth': depthG[0, :]})
     return df
 
 
@@ -96,13 +101,17 @@ def plot_updown_bias(df: pd.DataFrame, ax: plt.Axes = None, xlabel='Temperature
     else:
         fig = plt.gcf()
 
-    ax.plot(df.dc, df.depth, label='Dive-Climb')
-    ax.plot(df.cd, df.depth, label='Climb-Dive')
-    ax.legend(loc=3)
-    lims = np.abs(df.dc)
-    ax.set_xlim(-np.nanpercentile(lims, 99.5), np.nanpercentile(lims, 99.5))
+    if not all(hasattr(df, attr) for attr in ['dc', 'depth']):
+        ax.text(0.5, 0.55, xlabel, va='center', ha='center', transform=ax.transAxes, bbox=dict(facecolor='white', alpha=0.5, edgecolor='none'))
+        ax.text(0.5, 0.45, 'data unavailable', va='center', ha='center', transform=ax.transAxes, bbox=dict(facecolor='white', alpha=0.5, edgecolor='none'))
+    else:
+        ax.plot(df.dc, df.depth, label='Dive-Climb')
+        ax.plot(df.cd, df.depth, label='Climb-Dive')
+        ax.legend(loc=3)
+        lims = np.abs(df.dc)
+        ax.set_xlim(-np.nanpercentile(lims, 99.5), np.nanpercentile(lims, 99.5))
+        ax.set_ylim(df.depth.max() + 1, -df.depth.max() / 30)
     ax.set_xlabel(xlabel)
-    ax.set_ylim(df.depth.max() + 10, -df.depth.max() / 30)
     ax.grid()
     return fig, ax
 
@@ -139,6 +148,13 @@ def plot_basic_vars(ds, v_res=1, start_prof=0, end_prof=-1):
     z = v_res
     tempG, profG, depthG = grid2d(ds.PROFILE_NUMBER, ds.DEPTH, ds.TEMP, p, z)
     salG, profG, depthG = grid2d(ds.PROFILE_NUMBER, ds.DEPTH, ds.PSAL, p, z)
+
+    if 'DENSITY' not in ds.variables:
+        ds['DENSITY'] = (('N_MEASUREMENTS'), np.full(ds.dims['N_MEASUREMENTS'], np.nan))
+        SA = gsw.SA_from_SP(ds.PSAL, ds.DEPTH, ds.LONGITUDE, ds.LATITUDE)
+        CT = gsw.CT_from_t(SA, ds.TEMP, ds.DEPTH)
+        ds['DENSITY'] = gsw.rho(SA, CT, ds.DEPTH)
+
     denG, profG, depthG = grid2d(ds.PROFILE_NUMBER, ds.DEPTH, ds.DENSITY, p, z)
 
     tempG = tempG[start_prof:end_prof, :]
@@ -523,16 +539,19 @@ def check_temporal_drift(ds: xr.Dataset, var: str, ax: plt.Axes = None, **kw: di
     else:
         fig = plt.gcf()
 
-    ax[0].scatter(mdates.date2num(ds.TIME), ds[var], s=10)
-    ax[0].xaxis.set_major_formatter(DateFormatter('%Y-%m-%d'))
-    ax[0].set(ylim=(np.nanpercentile(ds[var], 0.01), np.nanpercentile(ds[var], 99.99)), ylabel=var)
+    if var not in ds.variables:
+        print(f'{var} does not exist in the dataset. Make sure the spelling is correct or add this variable to your dataset')
+    else:
+        ax[0].scatter(mdates.date2num(ds.TIME), ds[var], s=10)
+        ax[0].xaxis.set_major_formatter(DateFormatter('%Y-%m-%d'))
+        ax[0].set(ylim=(np.nanpercentile(ds[var], 0.01), np.nanpercentile(ds[var], 99.99)), ylabel=var)
 
-    c = ax[1].scatter(ds[var], ds.DEPTH, c=mdates.date2num(ds.TIME), s=10)
-    ax[1].set(xlim=(np.nanpercentile(ds[var], 0.01), np.nanpercentile(ds[var], 99.99)), ylabel='Depth (m)', xlabel=var)
-    ax[1].invert_yaxis()
+        c = ax[1].scatter(ds[var], ds.DEPTH, c=mdates.date2num(ds.TIME), s=10)
+        ax[1].set(xlim=(np.nanpercentile(ds[var], 0.01), np.nanpercentile(ds[var], 99.99)), ylabel='Depth (m)', xlabel=var)
+        ax[1].invert_yaxis()
 
-    [a.grid() for a in ax]
-    plt.colorbar(c, format=DateFormatter('%b %d'))
+        [a.grid() for a in ax]
+        plt.colorbar(c, format=DateFormatter('%b %d'))
     return fig, ax
 
 

diff --git a/notebooks/demo.ipynb b/notebooks/demo.ipynb
@@ -21,7 +21,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7c437da6-c3b3-4c48-b272-ee5b8ac27f69",
+   "id": "fc10d805",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -168,6 +168,7 @@
     "tools.plot_updown_bias(tools.updown_bias(ds, var='DOXY', v_res=1), ax[2],  xlabel='Dissolved Oxygen [mmol m-3]')\n",
     "tools.plot_updown_bias(tools.updown_bias(ds, var='CHLA', v_res=1), ax[3],  xlabel='Chlorophyll [mg m-3]')\n",
     "\n",
+    "\n",
     "ax[0].set_ylabel('Depth [m]')"
    ]
   },
@@ -395,7 +396,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -409,7 +410,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,