typos

Author: AntSimi

examples/06_grid_manipulation/pet_advect.py

@@ -104,21 +104,21 @@ def update(i_frame, t_step):
 # it could be run backward with `backward=True` option in filament method
 p = g.filament(x, y, "u", "v", **kw_p, filament_size=3)
 fig, txt, l, t = anim_ax(lw=0.5)
-ani = VideoAnimation(fig, update, **kwargs, fargs=(frame_t,))
+_ = VideoAnimation(fig, update, **kwargs, fargs=(frame_t,))
 
 # %%
 # Particle forward
 # ^^^^^^^^^^^^^^^^^
 # Forward advection of particles
 p = g.advect(x, y, "u", "v", **kw_p)
 fig, txt, l, t = anim_ax(ls="", marker=".", markersize=1)
-ani = VideoAnimation(fig, update, **kwargs, fargs=(frame_t,))
+_ = VideoAnimation(fig, update, **kwargs, fargs=(frame_t,))
 
 # %%
 # We get last position and run backward until original position
 p = g.advect(x, y, "u", "v", **kw_p, backward=True)
 fig, txt, l, _ = anim_ax(ls="", marker=".", markersize=1)
-ani = VideoAnimation(fig, update, **kwargs, fargs=(-frame_t,))
+_ = VideoAnimation(fig, update, **kwargs, fargs=(-frame_t,))
 
 # %%
 # Particles stat

examples/06_grid_manipulation/pet_lavd.py

@@ -27,7 +27,7 @@
 import py_eddy_tracker.gui
 from py_eddy_tracker.data import get_path
 from py_eddy_tracker.dataset.grid import RegularGridDataset
-from py_eddy_tracker.observations.network import NetworkObservations
+from py_eddy_tracker.observations.observation import EddiesObservations
 
 
 # %%
@@ -63,8 +63,6 @@ def _repr_html_(self, *args, **kwargs):
             r'width="[0-9]*"\sheight="[0-9]*"', 'width="100%" height="100%"', content
         )
 
-        return
-
     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
@@ -150,7 +148,7 @@ def update(i_frame):
 # pcolorfast will be faster than pcolormesh, we could use pcolorfast due to x and y are regular
 pcolormesh = ax.pcolorfast(x_g_, y_g_, lavd, **kw_vorticity)
 update_axes(ax, pcolormesh)
-ani = VideoAnimation(ax.figure, update, **kw_video)
+_ = VideoAnimation(ax.figure, update, **kw_video)
 
 # %%
 # Final LAVD
@@ -173,8 +171,8 @@ def update(i_frame):
 # Period used for LAVD integration (8 days) is too short for a real use, but choose for example efficiency.
 fig, ax, _ = start_ax()
 mappable = lavd.display(ax, "lavd", **kw_vorticity)
-NetworkObservations.load_file(get_path("Anticyclonic_20160515.nc")).display(
+EddiesObservations.load_file(get_path("Anticyclonic_20160515.nc")).display(
     ax, color="k"
 )
-NetworkObservations.load_file(get_path("Cyclonic_20160515.nc")).display(ax, color="k")
+EddiesObservations.load_file(get_path("Cyclonic_20160515.nc")).display(ax, color="k")
 _ = update_axes(ax, mappable)

notebooks/python_module/06_grid_manipulation/pet_advect.ipynb

@@ -163,7 +163,7 @@
       },
       "outputs": [],
       "source": [
-        "p = g.filament(x, y, \"u\", \"v\", **kw_p, filament_size=3)\nfig, txt, l, t = anim_ax(lw=0.5)\nani = VideoAnimation(fig, update, **kwargs, fargs=(frame_t,))"
+        "p = g.filament(x, y, \"u\", \"v\", **kw_p, filament_size=3)\nfig, txt, l, t = anim_ax(lw=0.5)\n_ = VideoAnimation(fig, update, **kwargs, fargs=(frame_t,))"
       ]
     },
     {
@@ -181,7 +181,7 @@
       },
       "outputs": [],
       "source": [
-        "p = g.advect(x, y, \"u\", \"v\", **kw_p)\nfig, txt, l, t = anim_ax(ls=\"\", marker=\".\", markersize=1)\nani = VideoAnimation(fig, update, **kwargs, fargs=(frame_t,))"
+        "p = g.advect(x, y, \"u\", \"v\", **kw_p)\nfig, txt, l, t = anim_ax(ls=\"\", marker=\".\", markersize=1)\n_ = VideoAnimation(fig, update, **kwargs, fargs=(frame_t,))"
       ]
     },
     {
@@ -199,7 +199,7 @@
       },
       "outputs": [],
       "source": [
-        "p = g.advect(x, y, \"u\", \"v\", **kw_p, backward=True)\nfig, txt, l, _ = anim_ax(ls=\"\", marker=\".\", markersize=1)\nani = VideoAnimation(fig, update, **kwargs, fargs=(-frame_t,))"
+        "p = g.advect(x, y, \"u\", \"v\", **kw_p, backward=True)\nfig, txt, l, _ = anim_ax(ls=\"\", marker=\".\", markersize=1)\n_ = VideoAnimation(fig, update, **kwargs, fargs=(-frame_t,))"
       ]
     },
     {

notebooks/python_module/06_grid_manipulation/pet_lavd.ipynb

@@ -15,7 +15,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n# LAVD experiment\n\nNaive method to reproduce LAVD(Lagrangian-Averaged Vorticity deviation) method with a static velocity field.\nIn the current example we didn't remove a mean vorticity.\n\nMethod are described here:\n\n    - Abernathey, Ryan, and George Haller. \"Transport by Lagrangian Vortices in the Eastern Pacific\",\n    Journal of Physical Oceanography 48, 3 (2018): 667-685, accessed Feb 16, 2021,\n    https://doi.org/10.1175/JPO-D-17-0102.1\n    - `Transport by Coherent Lagrangian Vortices`_,\n    R. Abernathey, Sinha A., Tarshish N., Liu T., Zhang C., Haller G., 2019,\n    Talk a t the Sources and Sinks of Ocean Mesoscale Eddy Energy CLIVAR Workshop\n\n    https://usclivar.org/sites/default/files/meetings/2019/presentations/Aberernathey_CLIVAR.pdf\n"
+        "\n# LAVD experiment\n\nNaive method to reproduce LAVD(Lagrangian-Averaged Vorticity deviation) method with a static velocity field.\nIn the current example we didn't remove a mean vorticity.\n\nMethod are described here:\n\n    - Abernathey, Ryan, and George Haller. \"Transport by Lagrangian Vortices in the Eastern Pacific\",\n      Journal of Physical Oceanography 48, 3 (2018): 667-685, accessed Feb 16, 2021,\n      https://doi.org/10.1175/JPO-D-17-0102.1\n    - `Transport by Coherent Lagrangian Vortices`_,\n      R. Abernathey, Sinha A., Tarshish N., Liu T., Zhang C., Haller G., 2019,\n      Talk a t the Sources and Sinks of Ocean Mesoscale Eddy Energy CLIVAR Workshop\n\n    https://usclivar.org/sites/default/files/meetings/2019/presentations/Aberernathey_CLIVAR.pdf\n"
       ]
     },
     {
@@ -26,7 +26,7 @@
       },
       "outputs": [],
       "source": [
-        "import re\n\nfrom matplotlib import pyplot as plt\nfrom matplotlib.animation import FuncAnimation\nfrom numpy import arange, meshgrid, zeros\n\nimport py_eddy_tracker.gui\nfrom py_eddy_tracker.data import get_path\nfrom py_eddy_tracker.dataset.grid import RegularGridDataset\nfrom py_eddy_tracker.observations.network import NetworkObservations"
+        "import re\n\nfrom matplotlib import pyplot as plt\nfrom matplotlib.animation import FuncAnimation\nfrom numpy import arange, meshgrid, zeros\n\nimport py_eddy_tracker.gui\nfrom py_eddy_tracker.data import get_path\nfrom py_eddy_tracker.dataset.grid import RegularGridDataset\nfrom py_eddy_tracker.observations.observation import EddiesObservations"
       ]
     },
     {
@@ -48,7 +48,7 @@
       },
       "outputs": [],
       "source": [
-        "class VideoAnimation(FuncAnimation):\n    def _repr_html_(self, *args, **kwargs):\n        \"\"\"To get video in html and have a player\"\"\"\n        content = self.to_html5_video()\n        return re.sub(\n            r'width=\"[0-9]*\"\\sheight=\"[0-9]*\"', 'width=\"100%\" height=\"100%\"', content\n        )\n\n        return\n\n    def save(self, *args, **kwargs):\n        if args[0].endswith(\"gif\"):\n            # In this case gif is use to create thumbnail which are not use but consume same time than video\n            # So we create an empty file, to save time\n            with open(args[0], \"w\") as _:\n                pass\n            return\n        return super().save(*args, **kwargs)"
+        "class VideoAnimation(FuncAnimation):\n    def _repr_html_(self, *args, **kwargs):\n        \"\"\"To get video in html and have a player\"\"\"\n        content = self.to_html5_video()\n        return re.sub(\n            r'width=\"[0-9]*\"\\sheight=\"[0-9]*\"', 'width=\"100%\" height=\"100%\"', content\n        )\n\n    def save(self, *args, **kwargs):\n        if args[0].endswith(\"gif\"):\n            # In this case gif is use to create thumbnail which are not use but consume same time than video\n            # So we create an empty file, to save time\n            with open(args[0], \"w\") as _:\n                pass\n            return\n        return super().save(*args, **kwargs)"
       ]
     },
     {
@@ -138,7 +138,7 @@
       },
       "outputs": [],
       "source": [
-        "def update(i_frame):\n    global lavd, i\n    i += 1\n    x, y = particule.__next__()\n    # Interp vorticity on new_position\n    lavd += abs(g.interp(\"vort\", x, y).reshape(original_shape) * 1 / nb_time)\n    txt.set_text(f\"T0 + {i / step_by_day:.2f} days of advection\")\n    pcolormesh.set_array(lavd / i * nb_time)\n    return pcolormesh, txt\n\n\nkw_video = dict(frames=arange(nb_time), interval=1000.0 / step_by_day / 2, blit=True)\nfig, ax, txt = start_ax(dpi=60)\nx_g_, y_g_ = arange(0 - step / 2, 36 + step / 2, step), arange(\n    28 - step / 2, 46 + step / 2, step\n)\n# pcolorfast will be faster than pcolormesh, we could use pcolorfast due to x and y are regular\npcolormesh = ax.pcolorfast(x_g_, y_g_, lavd, **kw_vorticity)\nupdate_axes(ax, pcolormesh)\nani = VideoAnimation(ax.figure, update, **kw_video)"
+        "def update(i_frame):\n    global lavd, i\n    i += 1\n    x, y = particule.__next__()\n    # Interp vorticity on new_position\n    lavd += abs(g.interp(\"vort\", x, y).reshape(original_shape) * 1 / nb_time)\n    txt.set_text(f\"T0 + {i / step_by_day:.2f} days of advection\")\n    pcolormesh.set_array(lavd / i * nb_time)\n    return pcolormesh, txt\n\n\nkw_video = dict(frames=arange(nb_time), interval=1000.0 / step_by_day / 2, blit=True)\nfig, ax, txt = start_ax(dpi=60)\nx_g_, y_g_ = arange(0 - step / 2, 36 + step / 2, step), arange(\n    28 - step / 2, 46 + step / 2, step\n)\n# pcolorfast will be faster than pcolormesh, we could use pcolorfast due to x and y are regular\npcolormesh = ax.pcolorfast(x_g_, y_g_, lavd, **kw_vorticity)\nupdate_axes(ax, pcolormesh)\n_ = VideoAnimation(ax.figure, update, **kw_video)"
       ]
     },
     {
@@ -181,7 +181,7 @@
       },
       "outputs": [],
       "source": [
-        "fig, ax, _ = start_ax()\nmappable = lavd.display(ax, \"lavd\", **kw_vorticity)\nNetworkObservations.load_file(get_path(\"Anticyclonic_20160515.nc\")).display(\n    ax, color=\"k\"\n)\nNetworkObservations.load_file(get_path(\"Cyclonic_20160515.nc\")).display(ax, color=\"k\")\n_ = update_axes(ax, mappable)"
+        "fig, ax, _ = start_ax()\nmappable = lavd.display(ax, \"lavd\", **kw_vorticity)\nEddiesObservations.load_file(get_path(\"Anticyclonic_20160515.nc\")).display(\n    ax, color=\"k\"\n)\nEddiesObservations.load_file(get_path(\"Cyclonic_20160515.nc\")).display(ax, color=\"k\")\n_ = update_axes(ax, mappable)"
       ]
     }
   ],