Work on Project

.pylintrc

@@ -3,4 +3,4 @@ jobs=4 #number of processes to use
 [BASIC]
 good-names=nameOfYourProject #names to be considered ok
 [pre-commit-hook]
-disable=bare-except, import-outside-toplevel, too-many-return-statements, line-too-long, invalid-name, too-many-arguments, dangerous-default-value, too-many-locals, duplicate-code
+disable=bare-except, import-outside-toplevel, too-many-return-statements, line-too-long, invalid-name, too-many-arguments, dangerous-default-value, too-many-locals, duplicate-code, too-many-statements

glacier_flow_tools/profiles.py

@@ -45,8 +45,6 @@
 )
 
 register_colormaps()
-# The standard backend is not thread-safe, but 'agg' works with the dask client.
-matplotlib.use("agg")
 
 
 def extract_profile(
@@ -131,6 +129,7 @@ def extract_profile(
 def plot_profile(
     ds: xr.Dataset,
     result_dir: Path,
+    interactive: bool = False,
     sigma: float = 1.0,
     obs_var: str = "v",
     obs_error_var: str = "v_err",
@@ -160,6 +159,9 @@ def plot_profile(
         The profile dataset to be plotted.
     result_dir : Path
         The directory where the result PDF file will be saved.
+    interactive : bool
+        If False (default), use non-interactive matplotlib backend for plotting.
+        Needed for distributed plottinging.
     sigma : float, optional
         The sigma value to be used for the plot, which determines the width of the Gaussian kernel, by default 1.0.
     obs_var : str, optional
@@ -188,6 +190,13 @@ def plot_profile(
     --------
     >>> plot_profile(ds, result_dir, sigma=1.0, obs_var='v', obs_error_var='v_err', sim_var='velsurf_mag', palette='Paired')
     """
+
+    if interactive:
+        # The standard backend is not thread-safe, but 'agg' works with the dask client.
+        matplotlib.use("agg")
+    else:
+        matplotlib.use("module://matplotlib_inline.backend_inline")
+
     fig = ds.profiles.plot(
         sigma=sigma,
         obs_var=obs_var,
@@ -212,6 +221,7 @@ def plot_glacier(
     surface: xr.DataArray,
     overlay: xr.DataArray,
     result_dir: Union[str, Path],
+    interactive: bool = False,
     cmap: str = "viridis",
     vmin: float = 10,
     vmax: float = 1500,
@@ -235,6 +245,9 @@ def plot_glacier(
         The overlay to be added to the plot.
     result_dir : Union[str, Path]
         The directory where the result PDF file will be saved.
+    interactive : bool
+        If False (default), use non-interactive matplotlib backend for plotting.
+        Needed for distributed plottinging.
     cmap : str, optional
         The colormap to be used for the plot, by default "viridis".
     vmin : float, optional
@@ -252,6 +265,13 @@ def plot_glacier(
     --------
     >>> plot_glacier(profile_series, surface, overlay, '/path/to/result_dir')
     """
+
+    if interactive:
+        # The standard backend is not thread-safe, but 'agg' works with the dask client.
+        matplotlib.use("agg")
+    else:
+        matplotlib.use("module://matplotlib_inline.backend_inline")
+
     plt.rcParams["font.size"] = fontsize
     geom = getattr(profile_series, "geometry")
     geom_centroid = geom.centroid
@@ -1082,6 +1102,7 @@ def extract_profile(
 
     def plot(
         self,
+        interactive: bool = False,
         sigma: float = 1,
         title: Union[str, None] = None,
         obs_var: str = "v",
@@ -1108,6 +1129,9 @@ def plot(
 
         Parameters
         ----------
+        interactive : bool
+            If False (default), use non-interactive matplotlib backend for plotting.
+            Needed for distributed plottinging.
         sigma : float, optional
             The standard deviation of the observations, by default 1.
         title : str or None, optional
@@ -1144,6 +1168,12 @@ def plot(
         >>> plot(sigma=1, title='My Plot', obs_var='v', obs_error_var='v_err', sim_var='velsurf_mag', palette='Paired')
         """
 
+        if interactive:
+            # The standard backend is not thread-safe, but 'agg' works with the dask client.
+            matplotlib.use("agg")
+        else:
+            matplotlib.use("module://matplotlib_inline.backend_inline")
+
         plt.rcParams["font.size"] = fontsize
         n_exps = self._obj["exp_id"].size
         fig = plt.figure(figsize=figsize)

notebooks/Ice Thickness Datasets.ipynb

@@ -45,18 +45,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "profile_resolution = 500  # m"
+    "profile_resolution = 1_000  # m"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1b80a187-b497-42f1-8021-b50925855801",
+   "cell_type": "markdown",
+   "id": "f4fab5e4-ab8e-4da6-9745-656df3bf1719",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "# process_profile will use non-interactive \"Agg\", so we switch back to default\n",
-    "plt.switch_backend('module://matplotlib_inline.backend_inline')"
+    "## Load observed and simulated velocities"
    ]
   },
   {
@@ -77,7 +74,24 @@
     "                           engine=\"h5netcdf\",\n",
     "                           decode_times=False,\n",
     "                           parallel=True\n",
-    "                          )\n",
+    "                          )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fee49e19-8306-4bc2-977a-e78ccbbdcc68",
+   "metadata": {},
+   "source": [
+    "## Load profile shapefile"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "691c1d3c-0b0f-4698-944b-51bf068b8756",
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "profiles_gp = gp.read_file(\"../glacier_flow_tools/data/greenland-flux-gates-5.gpkg\").rename(columns={\"id\": \"profile_id\", \"name\": \"profile_name\"})\n",
     "geom = profiles_gp.segmentize(profile_resolution)\n",
     "profiles_gp = gp.GeoDataFrame(profiles_gp, geometry=geom)\n",
@@ -86,6 +100,14 @@
     "profile_gp = [p for _, p in profiles_gp.iterrows()][1]"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "0620246f-9ec8-410d-bc19-71ef224267ab",
+   "metadata": {},
+   "source": [
+    "## Plot map-plane view of Jakobshavn gate"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -113,14 +135,23 @@
     "                stats_kwargs={\"obs_var\": \"v\", \"sim_var\": \"velsurf_mag\"})"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "d12609f9-76e8-4a23-9c4b-f9965f74e4d0",
+   "metadata": {},
+   "source": [
+    "## Plot profile"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "f6bec873-8faa-48d2-8293-f56ca303ff7e",
    "metadata": {},
    "outputs": [],
    "source": [
-    "jak_profile.profiles.plot(obs_error_var=None)"
+    "jak_profile.profiles.plot(obs_error_var=None, interactive=True, figsize=(8, 8), fontsize=12, \n",
+    "                          obs_kwargs={\"lw\": 2, \"color\": \"k\", \"marker\": \"o\", \"ms\": 5}, sim_kwargs={\"lw\": 2, \"marker\": \"o\", \"ms\": 5})"
    ]
   },
   {