Add example with correspondance

examples/08_tracking_manipulation/pet_how_to_use_correspondances.py

@@ -0,0 +1,94 @@
+"""
+Correspondances
+===============
+
+Correspondances is a mechanism to intend to continue tracking with new detection
+
+"""
+
+import logging
+
+# %%
+from matplotlib import pyplot as plt
+from netCDF4 import Dataset
+
+from py_eddy_tracker import start_logger
+from py_eddy_tracker.data import get_remote_demo_sample
+from py_eddy_tracker.featured_tracking.area_tracker import AreaTracker
+
+# In order to hide some warning
+import py_eddy_tracker.observations.observation
+from py_eddy_tracker.tracking import Correspondances
+
+py_eddy_tracker.observations.observation._display_check_warning = False
+
+
+# %%
+def plot_eddy(ed):
+    fig = plt.figure(figsize=(10, 5))
+    ax = fig.add_axes([0.05, 0.03, 0.90, 0.94])
+    ed.plot(ax, ref=-10, marker="x")
+    lc = ed.display_color(ax, field=ed.time, ref=-10, intern=True)
+    plt.colorbar(lc).set_label("Time in Julian days (from 1950/01/01)")
+    ax.set_xlim(4.5, 8), ax.set_ylim(36.8, 38.3)
+    ax.set_aspect("equal")
+    ax.grid()
+
+
+# %%
+# Get remote data, we will keep only 20 first days,
+# `get_remote_demo_sample` function is only to get demo dataset, in your own case give a list of identification filename
+# and don't mix cyclonic and anticyclonic files.
+file_objects = get_remote_demo_sample(
+    "eddies_med_adt_allsat_dt2018/Anticyclonic_2010_2011_2012"
+)[:20]
+
+# %%
+# We run a traking with a tracker which use contour overlap, on 10 first time step
+c_first_run = Correspondances(
+    datasets=file_objects[:10], class_method=AreaTracker, virtual=4
+)
+start_logger().setLevel("INFO")
+c_first_run.track()
+start_logger().setLevel("WARNING")
+with Dataset("correspondances.nc", "w") as h:
+    c_first_run.to_netcdf(h)
+# Next step are done only to build atlas and display it
+c_first_run.prepare_merging()
+
+# We have now an eddy object
+eddies_area_tracker = c_first_run.merge(raw_data=False)
+eddies_area_tracker.virtual[:] = eddies_area_tracker.time == 0
+eddies_area_tracker.filled_by_interpolation(eddies_area_tracker.virtual == 1)
+
+# %%
+# Plot from first ten days
+plot_eddy(eddies_area_tracker)
+
+# %%
+# Restart from previous run
+# -------------------------
+# We give all filenames, the new one and filename from previous run
+c_second_run = Correspondances(
+    datasets=file_objects[:20],
+    # This parameter must be identical in each run
+    class_method=AreaTracker,
+    virtual=4,
+    # Previous saved correspondancs
+    previous_correspondance="correspondances.nc",
+)
+start_logger().setLevel("INFO")
+c_second_run.track()
+start_logger().setLevel("WARNING")
+c_second_run.prepare_merging()
+# We have now another eddy object
+eddies_area_tracker_extend = c_second_run.merge(raw_data=False)
+eddies_area_tracker_extend.virtual[:] = eddies_area_tracker_extend.time == 0
+eddies_area_tracker_extend.filled_by_interpolation(
+    eddies_area_tracker_extend.virtual == 1
+)
+
+
+# %%
+# Plot with time extension
+plot_eddy(eddies_area_tracker_extend)

notebooks/python_module/08_tracking_manipulation/pet_how_to_use_correspondances.ipynb

@@ -0,0 +1,155 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "\n# Correspondances\n\nCorrespondances is a mechanism to intend to continue tracking with new detection\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "import logging"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "from matplotlib import pyplot as plt\nfrom netCDF4 import Dataset\n\nfrom py_eddy_tracker import start_logger\nfrom py_eddy_tracker.data import get_remote_demo_sample\nfrom py_eddy_tracker.featured_tracking.area_tracker import AreaTracker\n\n# In order to hide some warning\nimport py_eddy_tracker.observations.observation\nfrom py_eddy_tracker.tracking import Correspondances\n\npy_eddy_tracker.observations.observation._display_check_warning = False"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "def plot_eddy(ed):\n    fig = plt.figure(figsize=(10, 5))\n    ax = fig.add_axes([0.05, 0.03, 0.90, 0.94])\n    ed.plot(ax, ref=-10, marker=\"x\")\n    lc = ed.display_color(ax, field=ed.time, ref=-10, intern=True)\n    plt.colorbar(lc).set_label(\"Time in Julian days (from 1950/01/01)\")\n    ax.set_xlim(4.5, 8), ax.set_ylim(36.8, 38.3)\n    ax.set_aspect(\"equal\")\n    ax.grid()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Get remote data, we will keep only 20 first days,\n`get_remote_demo_sample` function is only to get demo dataset, in your own case give a list of identification filename\nand don't mix cyclonic and anticyclonic files.\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "file_objects = get_remote_demo_sample(\n    \"eddies_med_adt_allsat_dt2018/Anticyclonic_2010_2011_2012\"\n)[:20]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "We run a traking with a tracker which use contour overlap, on 10 first time step\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "c_first_run = Correspondances(\n    datasets=file_objects[:10], class_method=AreaTracker, virtual=4\n)\nstart_logger().setLevel(\"INFO\")\nc_first_run.track()\nstart_logger().setLevel(\"WARNING\")\nwith Dataset(\"correspondances.nc\", \"w\") as h:\n    c_first_run.to_netcdf(h)\n# Next step are done only to build atlas and display it\nc_first_run.prepare_merging()\n\n# We have now an eddy object\neddies_area_tracker = c_first_run.merge(raw_data=False)\neddies_area_tracker.virtual[:] = eddies_area_tracker.time == 0\neddies_area_tracker.filled_by_interpolation(eddies_area_tracker.virtual == 1)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Plot from first ten days\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "plot_eddy(eddies_area_tracker)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Restart from previous run\nWe give all filenames, the new one and filename from previous run\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "c_second_run = Correspondances(\n    datasets=file_objects[:20],\n    # This parameter must be identical in each run\n    class_method=AreaTracker,\n    virtual=4,\n    # Previous saved correspondancs\n    previous_correspondance=\"correspondances.nc\",\n)\nstart_logger().setLevel(\"INFO\")\nc_second_run.track()\nstart_logger().setLevel(\"WARNING\")\nc_second_run.prepare_merging()\n# We have now another eddy object\neddies_area_tracker_extend = c_second_run.merge(raw_data=False)\neddies_area_tracker_extend.virtual[:] = eddies_area_tracker_extend.time == 0\neddies_area_tracker_extend.filled_by_interpolation(\n    eddies_area_tracker_extend.virtual == 1\n)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Plot with time extension\n\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": false
+      },
+      "outputs": [],
+      "source": [
+        "plot_eddy(eddies_area_tracker_extend)"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.10.10"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

src/py_eddy_tracker/observations/observation.py

@@ -80,6 +80,7 @@
 _software_version_reduced = packaging.version.Version(
     "{v.major}.{v.minor}".format(v=packaging.version.parse(__version__))
 )
+_display_check_warning = True
 
 
 def _check_versions(version):
@@ -90,7 +91,8 @@ def _check_versions(version):
     :param version: string version of software used to create the file. If None, version was not provided
     :type version: str, None
     """
-
+    if not _display_check_warning:
+        return
     file_version = packaging.version.parse(version) if version is not None else None
     if file_version is None or file_version < _software_version_reduced:
         logger.warning(
@@ -774,7 +776,7 @@ def load_file(cls, filename, **kwargs):
             zarr_file = filename_.endswith(end)
         else:
             zarr_file = False
-        logger.info(f"loading file '{filename}'")
+        logger.info(f"loading file '{filename_}'")
         if zarr_file:
             return cls.load_from_zarr(filename, **kwargs)
         else:

src/py_eddy_tracker/tracking.py

@@ -2,11 +2,11 @@
 """
 Class to store link between observations
 """
-
 from datetime import datetime, timedelta
 import json
 import logging
 import platform
+from tarfile import ExFileObject
 
 from netCDF4 import Dataset, default_fillvals
 from numba import njit, types as numba_types
@@ -375,7 +375,10 @@ def track(self):
         # We begin with second file, first one is in previous
         for file_name in self.datasets[first_dataset:]:
             self.swap_dataset(file_name, **kwargs)
-            logger.info("%s match with previous state", file_name)
+            filename_ = (
+                file_name.filename if isinstance(file_name, ExFileObject) else file_name
+            )
+            logger.info("%s match with previous state", filename_)
             logger.debug("%d obs to match", len(self.current_obs))
 
             nb_real_obs = len(self.previous_obs)