Merge branch 'main' of https://github.com/SnowEx/spicy-snow into main

SnowEx · Sep 6, 2023 · 067fed3 · 067fed3
2 parents 8f9de7a + e646a4c
commit 067fed3
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Showing 11 changed files with 574 additions and 382 deletions.
diff --git a/.gitignore b/.gitignore
@@ -162,4 +162,6 @@ scripts/optimize/param_sds
 !/results/site_param_rmses/*.csv
 !/contrib/palomaki/*.csv
 
-*.sqlite
+*.sqlite
+
+*.nfs
diff --git a/SnowEx-Data/.nfs000000013a9d95c700004d8b b/SnowEx-Data/.nfs000000013a9d95c700004d8b
diff --git a/SnowEx-Data/.nfs000000013ac787a900004d8c b/SnowEx-Data/.nfs000000013ac787a900004d8c
diff --git a/contrib/gagliano/wet_snow_testing.ipynb b/contrib/gagliano/wet_snow_testing.ipynb
@@ -96,7 +96,7 @@
     "    ds_name = f.split('stacks/')[-1].split('.')[0]\n",
     "    print(datetime.now(), f' -- starting {ds_name}')\n",
     "\n",
-    "    if Path(f'rmse_out/{ds_name}_wet_flag.nc').is_file():\n",
+    "    if Path(f'rmse_out_with_si/{ds_name}_wet_flag.nc').is_file():\n",
     "        print('This file already exists, continuing.')\n",
     "        continue\n",
     "    \n",
@@ -124,7 +124,7 @@
     "        ds = calc_snow_index(ds)\n",
     "        ds = calc_snow_index_to_snow_depth(ds, C=c, inplace=False)\n",
     "        ds = id_newly_wet_snow(ds,wet_thresh=wst)\n",
-    "        ds = id_wet_negative_si_test(ds)\n",
+    "        ds = id_wet_negative_si(ds,wet_SI_thresh=0) #change to test depending on whether we want neg SI to flag as wet snow\n",
     "        ds = id_newly_frozen_snow(ds,freeze_thresh=-1*wst)\n",
     "        ds = flag_wet_snow(ds)\n",
     "        # Compare snow depths - mask wet snow\n",
@@ -144,9 +144,9 @@
     "        print(f'Frac valid pixels = {mask_wet.sum() /mask.sum():0.2f}')\n",
     "\n",
     "    # After loop, save RMSE results per file\n",
-    "    rmse_wet_flag.to_netcdf(f'rmse_out/{ds_name}_wet_flag.nc')\n",
-    "    rmse_no_flag.to_netcdf(f'rmse_out/{ds_name}_no_flag.nc')\n",
-    "    valid_pixels.to_netcdf(f'rmse_out/{ds_name}_valid_pixels.nc')\n",
+    "    rmse_wet_flag.to_netcdf(f'rmse_out_with_si/{ds_name}_wet_flag.nc')\n",
+    "    rmse_no_flag.to_netcdf(f'rmse_out_with_si/{ds_name}_no_flag.nc')\n",
+    "    valid_pixels.to_netcdf(f'rmse_out_with_si/{ds_name}_valid_pixels.nc')\n",
     "    "
    ]
   },
@@ -156,11 +156,21 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "results = sorted(glob('rmse_out/*.nc'))\n",
+    "with_neg_si_flag_wet_snow = True\n",
+    "\n",
+    "directory = 'rmse_out_with_si'\n",
+    "#directory = 'rmse_out'\n",
+    "\n",
+    "#if with_neg_si_flag_wet_snow == True:\n",
+    "#    directory = 'rmse_out_full_with_si'\n",
+    "#else:\n",
+    "#    directory = 'rmse_out_full'\n",
+    "\n",
+    "results = sorted(glob(f'{directory}/*.nc'))\n",
     "names = []\n",
     "for f in results:\n",
     "    if 'no_flag' in f:\n",
-    "        ds_name = f.split('rmse_out/')[-1]\n",
+    "        ds_name = f.split(f'{directory}/')[-1]\n",
     "        ds_name = ds_name.split('_no')[0]\n",
     "        names.append(ds_name)\n",
     "\n",
@@ -172,19 +182,19 @@
     "for f in results:\n",
     "    if 'wet_flag' in f:\n",
     "        r = xr.open_dataarray(f).load()\n",
-    "        ds_name = f.split('rmse_out/')[-1]\n",
+    "        ds_name = f.split(f'{directory}/')[-1]\n",
     "        ds_name = ds_name.split('_wet')[0]\n",
     "        for ind,val in zip(r.wet_snow_thresh.values,r.values):\n",
     "            thresh_results.loc[ind,ds_name] = val\n",
     "    if 'no_flag' in f:\n",
     "        r = xr.open_dataarray(f).load()\n",
-    "        ds_name = f.split('rmse_out/')[-1]\n",
+    "        ds_name = f.split(f'{directory}/')[-1]\n",
     "        ds_name = ds_name.split('_no')[0]\n",
     "        for ind,val in zip(r.wet_snow_thresh.values,r.values):\n",
     "            no_thresh_results.loc[ind,ds_name] = val\n",
     "    if 'valid' in f:\n",
     "        r = xr.open_dataarray(f).load()\n",
-    "        ds_name = f.split('rmse_out/')[-1]\n",
+    "        ds_name = f.split(f'{directory}/')[-1]\n",
     "        ds_name = ds_name.split('_valid')[0]\n",
     "        for ind,val in zip(r.wet_snow_thresh.values,r.values):\n",
     "            valid_pixels_results.loc[ind,ds_name] = val\n"
@@ -251,7 +261,7 @@
     "    ds_name = f.split('stacks/')[-1].split('.')[0]\n",
     "    print(datetime.now(), f' -- starting {ds_name}')\n",
     "\n",
-    "    if Path(f'rmse_out_full/{ds_name}_wet_flag.nc').is_file():\n",
+    "    if Path(f'rmse_out_full_with_si/{ds_name}_wet_flag.nc').is_file():\n",
     "        print('This file already exists, continuing.')\n",
     "        continue\n",
     "\n",
@@ -280,7 +290,7 @@
     "                    ds = calc_snow_index(ds)\n",
     "                    ds = calc_snow_index_to_snow_depth(ds, C=c, inplace=False)\n",
     "                    ds = id_newly_wet_snow(ds,wet_thresh=wst)\n",
-    "                    ds = id_wet_negative_si_test(ds)\n",
+    "                    ds = id_wet_negative_si(ds) #change to test depdning on whether to remove neg SI = wet snow\n",
     "                    ds = id_newly_frozen_snow(ds,freeze_thresh=-1*wst)\n",
     "                    ds = flag_wet_snow(ds)\n",
     "                    # Compare snow depths - mask wet snow\n",
@@ -300,9 +310,9 @@
     "                    print(f'Frac valid pixels = {mask_wet.sum()/ mask.sum():0.2f}')\n",
     "\n",
     "    # After loop, save RMSE results per file\n",
-    "    rmse_wet_flag.to_netcdf(f'rmse_out_full/{ds_name}_wet_flag.nc')\n",
-    "    rmse_no_flag.to_netcdf(f'rmse_out_full/{ds_name}_no_flag.nc')\n",
-    "    valid_pixels.to_netcdf(f'rmse_out_full/{ds_name}_valid_pixels.nc')\n",
+    "    rmse_wet_flag.to_netcdf(f'rmse_out_full_with_si/{ds_name}_wet_flag.nc')\n",
+    "    rmse_no_flag.to_netcdf(f'rmse_out_full_with_si/{ds_name}_no_flag.nc')\n",
+    "    valid_pixels.to_netcdf(f'rmse_out_full_with_si/{ds_name}_valid_pixels.nc')\n",
     "    "
    ]
   },
@@ -312,11 +322,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "directory = 'rmse_out_full'\n",
+    "directory = 'rmse_out_full_with_si'\n",
+    "\n",
     "which_site = 5\n",
     "\n",
-    "results1 = sorted(glob('rmse_out_full/*wet*.nc'))\n",
-    "results2 = sorted(glob('rmse_out_full/*no*.nc'))\n",
-    "results3 = sorted(glob('rmse_out_full/*valid*.nc'))\n",
+    "results1 = sorted(glob(f'{directory}/*wet*.nc'))\n",
+    "results2 = sorted(glob(f'{directory}/*no*.nc'))\n",
+    "results3 = sorted(glob(f'{directory}/*valid*.nc'))\n",
     "\n",
     "wet_snow = xr.open_dataarray(results1[which_site])\n",
     "all_snow = xr.open_dataarray(results2[which_site])\n",
@@ -345,6 +358,27 @@
     "        plt.tight_layout()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "iles = sorted(glob('spicy_s1_stacks/*.nc'))\n",
+    "\n",
+    "\n",
+    "for f in files:\n",
+    "    ds_name = f.split('stacks/')[-1].split('.')[0]\n",
+    "    print(datetime.now(), f' -- starting {ds_name}')\n",
+    "\n",
+    "    # Open dataset \n",
+    "    ds_ = xr.open_dataset(f).load()\n",
+    "    dataset = ds_[['s1','deltaVV','ims','fcf','lidar-sd']]\n",
+    "    td = abs(pd.to_datetime(dataset.time) - pd.to_datetime(dataset.attrs['lidar-flight-time']))\n",
+    "    closest_ts_idx = np.where(td == td.min())[0][0]\n",
+    "    closest_ts = dataset.time[closest_ts_idx]"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -356,7 +390,7 @@
     "c = 0.55\n",
     "wst = -3\n",
     "\n",
-    "for wst in [-4,-3,-2,-1,0,1,2,3,4]:\n",
+    "for wst in [-4,-3,-2,-1,0]:\n",
     "    ds = calc_delta_cross_ratio(dataset, A=a, inplace=False)\n",
     "    ds = calc_delta_gamma(ds, B=b, inplace=False)\n",
     "    print(f'A={a:0.2f}; B={b:0.2f}; C={c:0.2f}; wst={wst:0.2f}')\n",