Update examples

Author: AntSimi

examples/16_network/pet_atlas.py

@@ -19,6 +19,7 @@
 kw_time = dict(cmap="terrain_r", factor=100.0 / n.nb_days, name="count")
 kw_ratio = dict(cmap=plt.get_cmap("coolwarm_r", 10))
 
+
 # %%
 # Function
 def start_axes(title):

examples/16_network/pet_ioannou_2017_case.py

@@ -26,7 +26,7 @@ def save(self, *args, **kwargs):
         if args[0].endswith("gif"):
             # In this case gif is use to create thumbnail which are not use but consume same time than video
             # So we create an empty file, to save time
-            with open(args[0], "w") as h:
+            with open(args[0], "w") as _:
                 pass
             return
         return super().save(*args, **kwargs)
@@ -132,7 +132,7 @@ def update_axes(ax, mappable=None):
 ax = start_axes("")
 n_copy = close_to_i3.copy()
 n_copy.position_filter(2, 4)
-n_copy.plot(ax)
+n_copy.plot(ax, color_cycle=n_copy.COLORS)
 update_axes(ax)
 
 # %%
@@ -151,12 +151,14 @@ def update_axes(ax, mappable=None):
 for b0, b1 in [
     (datetime(i, 1, 1), datetime(i, 12, 31)) for i in (2004, 2005, 2006, 2007)
 ]:
-    b0_, b1_ = (b0 - datetime(1950, 1, 1)).days - 10, (
-        b1 - datetime(1950, 1, 1)
-    ).days + 10
+    ref, delta = datetime(1950, 1, 1), 20
+    b0_, b1_ = (b0 - ref).days, (b1 - ref).days
     ax = timeline_axes()
-    ax.set_xlim(b0_, b1_)
+    ax.set_xlim(b0_ - delta, b1_ + delta)
     ax.set_ylim(10, 115)
+    ax.axvline(b0_, color="k", lw=1.5, ls="--"), ax.axvline(
+        b1_, color="k", lw=1.5, ls="--"
+    )
     n_copy.display_timeline(
         ax, field="radius_e", method="all", lw=4, markersize=8, factor=1e-3
     )

examples/16_network/pet_relative.py

@@ -166,7 +166,7 @@
 # --------------------
 fig = plt.figure(figsize=(15, 8))
 ax = fig.add_axes([0.04, 0.06, 0.94, 0.88], projection="full_axes")
-close_to_i2.plot(ax)
+close_to_i2.plot(ax, color_cycle=close_to_i2.COLORS)
 ax.set_xlim(-13, 20), ax.set_ylim(-36.5, -20), ax.grid()
 ax = fig.add_axes([0.08, 0.67, 0.55, 0.3])
 _ = close_to_i2.display_timeline(ax, field="latitude")

notebooks/python_module/02_eddy_identification/pet_eddy_detection.ipynb

@@ -170,7 +170,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "Creteria for rejecting a contour\n0. - Accepted (green)\n1. - Rejection for shape error (red)\n2. - Masked value within contour (blue)\n3. - Under or over the pixel limit bounds (black)\n4. - Amplitude criterion (yellow)\n\n"
+        "Criteria for rejecting a contour:\n 0. - Accepted (green)\n 1. - Rejection for shape error (red)\n 2. - Masked value within contour (blue)\n 3. - Under or over the pixel limit bounds (black)\n 4. - Amplitude criterion (yellow)\n\n"
       ]
     },
     {

notebooks/python_module/02_eddy_identification/pet_eddy_detection_gulf_stream.ipynb

@@ -235,7 +235,7 @@
       },
       "outputs": [],
       "source": [
-        "ax = start_axes(\"Eddies detected\")\na.display(ax, color=\"r\", linewidth=0.75, label=\"Anticyclonic ({nb_obs} eddies)\", ref=-10)\nc.display(ax, color=\"b\", linewidth=0.75, label=\"Cyclonic ({nb_obs} eddies)\", ref=-10)\nax.legend()\ngreat_current.display(ax, color=\"k\")\nupdate_axes(ax)"
+        "ax = start_axes(\"Eddies detected\")\na.display(\n    ax, color=\"r\", linewidth=0.75, label=\"Anticyclonic ({nb_obs} eddies)\", ref=-10\n)\nc.display(ax, color=\"b\", linewidth=0.75, label=\"Cyclonic ({nb_obs} eddies)\", ref=-10)\nax.legend()\ngreat_current.display(ax, color=\"k\")\nupdate_axes(ax)"
       ]
     },
     {

notebooks/python_module/02_eddy_identification/pet_filter_and_detection.ipynb

@@ -91,7 +91,7 @@
       },
       "outputs": [],
       "source": [
-        "ax = start_axes(\"Eddies detected over ADT\")\nm = g.display(ax, \"adt\", vmin=-0.15, vmax=0.15)\nmerge_f.display(ax, lw=0.75, label=\"Eddies in the filtered grid ({nb_obs} eddies)\", ref=-10, color=\"k\")\nmerge_t.display(ax, lw=0.75, label=\"Eddies without filter ({nb_obs} eddies)\", ref=-10, color=\"r\")\nax.legend()\nupdate_axes(ax, m)"
+        "ax = start_axes(\"Eddies detected over ADT\")\nm = g.display(ax, \"adt\", vmin=-0.15, vmax=0.15)\nmerge_f.display(\n    ax,\n    lw=0.75,\n    label=\"Eddies in the filtered grid ({nb_obs} eddies)\",\n    ref=-10,\n    color=\"k\",\n)\nmerge_t.display(\n    ax, lw=0.75, label=\"Eddies without filter ({nb_obs} eddies)\", ref=-10, color=\"r\"\n)\nax.legend()\nupdate_axes(ax, m)"
       ]
     },
     {

notebooks/python_module/02_eddy_identification/pet_sla_and_adt.ipynb

@@ -66,7 +66,7 @@
       },
       "outputs": [],
       "source": [
-        "kwargs_a_adt = dict(lw=0.5, label=\"Anticyclonic ADT ({nb_obs} eddies)\", ref=-10, color=\"k\")\nkwargs_c_adt = dict(lw=0.5, label=\"Cyclonic ADT ({nb_obs} eddies)\", ref=-10, color=\"r\")\nkwargs_a_sla = dict(lw=0.5, label=\"Anticyclonic SLA ({nb_obs} eddies)\", ref=-10, color=\"g\")\nkwargs_c_sla = dict(lw=0.5, label=\"Cyclonic SLA ({nb_obs} eddies)\", ref=-10, color=\"b\")"
+        "kwargs_a_adt = dict(\n    lw=0.5, label=\"Anticyclonic ADT ({nb_obs} eddies)\", ref=-10, color=\"k\"\n)\nkwargs_c_adt = dict(lw=0.5, label=\"Cyclonic ADT ({nb_obs} eddies)\", ref=-10, color=\"r\")\nkwargs_a_sla = dict(\n    lw=0.5, label=\"Anticyclonic SLA ({nb_obs} eddies)\", ref=-10, color=\"g\"\n)\nkwargs_c_sla = dict(lw=0.5, label=\"Cyclonic SLA ({nb_obs} eddies)\", ref=-10, color=\"b\")"
       ]
     },
     {

notebooks/python_module/08_tracking_manipulation/pet_select_track_across_area.ipynb

@@ -80,7 +80,7 @@
       },
       "outputs": [],
       "source": [
-        "fig = plt.figure(figsize=(12, 5))\nax = fig.add_axes((0.05, 0.05, 0.9, 0.9))\nax.set_xlim(-1, 9)\nax.set_ylim(36, 40)\nax.set_aspect(\"equal\")\nax.grid()\nc.plot(ax, color=\"gray\", lw=0.1, ref=-10, label=\"All tracks ({nb_tracks} tracks)\")\nc_subset.plot(ax, color=\"red\", lw=0.2, ref=-10, label=\"selected tracks ({nb_tracks} tracks)\")\nax.plot(\n    (x0, x0, x1, x1, x0),\n    (y0, y1, y1, y0, y0),\n    color=\"green\",\n    lw=1.5,\n    label=\"Box of selection\",\n)\nax.legend()"
+        "fig = plt.figure(figsize=(12, 5))\nax = fig.add_axes((0.05, 0.05, 0.9, 0.9))\nax.set_xlim(-1, 9)\nax.set_ylim(36, 40)\nax.set_aspect(\"equal\")\nax.grid()\nc.plot(ax, color=\"gray\", lw=0.1, ref=-10, label=\"All tracks ({nb_tracks} tracks)\")\nc_subset.plot(\n    ax, color=\"red\", lw=0.2, ref=-10, label=\"selected tracks ({nb_tracks} tracks)\"\n)\nax.plot(\n    (x0, x0, x1, x1, x0),\n    (y0, y1, y1, y0, y0),\n    color=\"green\",\n    lw=1.5,\n    label=\"Box of selection\",\n)\nax.legend()"
       ]
     }
   ],

notebooks/python_module/10_tracking_diagnostics/pet_center_count.ipynb

@@ -15,7 +15,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n# Count center\n\nDo Geo stat with center and compare with frequency method show: `sphx_glr_python_module_10_tracking_diagnostics_pet_pixel_used.py`\n"
+        "\n# Count center\n\nDo Geo stat with center and compare with frequency method\nshow: `sphx_glr_python_module_10_tracking_diagnostics_pet_pixel_used.py`\n"
       ]
     },
     {

notebooks/python_module/10_tracking_diagnostics/pet_pixel_used.ipynb

@@ -15,7 +15,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n# Count pixel used\n\nDo Geo stat with frequency and compare with center count method: `sphx_glr_python_module_10_tracking_diagnostics_pet_center_count.py`\n"
+        "\n# Count pixel used\n\nDo Geo stat with frequency and compare with center count\nmethod: `sphx_glr_python_module_10_tracking_diagnostics_pet_center_count.py`\n"
       ]
     },
     {