Merge 808e192 into 67d806c

.zenodo.json

@@ -28,6 +28,11 @@
       "name": "Braun, Marco",
       "affiliation": "Ouranos",
       "orcid": "0000-0001-5061-3217"
+    },
+    {
+      "name": "Dupuis, Éric",
+      "affiliation": "Ouranos, Montréal, Québec, Canada",
+      "orcid": "0000-0001-7976-4596"
     }
   ],
   "keywords": [

AUTHORS.rst

@@ -20,3 +20,4 @@ Contributors
 
 * Gabriel Rondeau-Genesse <rondeau-genesse.gabriel@ouranos.ca> `@RondeauG <https://github.com/RondeauG>`_
 * Marco Braun <Braun.Marco@ouranos.ca> `@vindelico <https://github.com/vindelico>`_
+* Éric Dupuis <dupuis.eric@ouranos.ca> `@coxipi <https://github.com/coxipi>`_

CHANGELOG.rst

@@ -4,7 +4,7 @@ Changelog
 
 0.4.0 (unreleased)
 ------------------
-Contributors to this version: Trevor James Smith (:user:`Zeitsperre`), Marco Braun (:user:`vindelico`), Pascal Bourgault (:user:`aulemahal`), Sarah-Claude Bourdeau-Goulet (:user:`Sarahclaude`)
+Contributors to this version: Trevor James Smith (:user:`Zeitsperre`), Marco Braun (:user:`vindelico`), Pascal Bourgault (:user:`aulemahal`), Sarah-Claude Bourdeau-Goulet (:user:`Sarahclaude`), Éric Dupuis (:user:`coxipi`)
 
 New features and enhancements
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -13,13 +13,16 @@ New features and enhancements
 * Added style sheet ``transparent.mplstyle`` (:issue:`183`, :pull:`185`)
 * Fix ``NaN`` issues, extreme values in sizes legend and added edgecolors in ``fg.matplotlib.scattermap``  (:pull:`184`).
 * New function ``fg.data`` for fetching package data and defined `matplotlib` style definitions. (:pull:`211`).
+* ``fg.taylordiagram`` can now accept datasets with many dimensions (not only `taylor_params`), provided that they all share the same `ref_std` (e.g. normalized taylor diagrams)  (:pull:`214`).
+* A new optional way to organize points in a `fg.taylordiagram`  with  `colors_key`, `markers_key`  : DataArrays with a common dimension value or a common attrtibute are grouped with the same color/marker (:pull:`214`).
 
 Breaking changes
 ^^^^^^^^^^^^^^^^
 * `figanos` no longer supports Python 3.8. (:pull:`210`).
 * `figanos` now uses a `'src' layout <https://packaging.python.org/en/latest/discussions/src-layout-vs-flat-layout>`_ for the package. (:pull:`210`).
 * `cartopy` has been pinned above v0.23.0 due to a licensing issue. (:pull:`210`).
 * `twine` and `wheel` have been removed from the `dev` requirements. (:pull:`210`).
+* ``fg.taylordiagram`` returns a tuple of `(fig, floating_ax, legend)` instead of only `floating_ax`. (:pull:`214`).
 
 Internal changes
 ^^^^^^^^^^^^^^^^

docs/notebooks/figanos_docs.ipynb

@@ -1009,23 +1009,61 @@
    "source": [
     "da_ref = ds_time['tx_max_p50']\n",
     "\n",
+    "# Toy data with same mean as `da_ref` & modify deviations with trigonometric functions\n",
+    "homogenous_ref_mean = xr.full_like(da_ref, da_ref.mean(dim=\"time\"))\n",
+    "simd = {}\n",
+    "for i, f_trig in enumerate([np.cos, lambda x: np.cos(x)**2, np.tan]):\n",
+    "    da = homogenous_ref_mean + f_trig(da_ref.values)\n",
+    "    da.attrs[\"units\"] = da_ref.attrs[\"units\"]\n",
+    "    simd[f\"model{i}\"] = sdba.measures.taylordiagram(sim=da, ref=da_ref)\n",
     "\n",
-    "rands = np.arange(15)\n",
-    "sims = {}\n",
-    "for rand in rands:\n",
-    "    name = \"model\" + str(rand)\n",
-    "    da = xr.DataArray(data=np.random.rand(13)*20+290+rand,\n",
-    "                      dims={'time': da_ref.time.values})\n",
-    "    da.attrs[\"units\"] = da_ref.units\n",
+    "fg.taylordiagram(simd, std_range=(0, 1.3), contours=5, contours_kw={'colors': 'green'}, plot_kw={'reference': {'marker':'*'}})\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "63",
+   "metadata": {},
+   "source": [
+    "### Normalized taylor diagram\n",
     "\n",
-    "    sims[name] = sdba.measures.taylordiagram(da, da_ref)\n",
+    "If we normalize the standard deviation of our measures, many Taylor diagrams with difference references can be combined in a single plot. In the following example, we have datasets with two variables (`tasmax, pr`) and three location coordinates. For each location (3) and variable (2), a Taylordiagram measure is computed. Each set of correlation and standard deviation is then plotted. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "64",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_ref = xc.testing.open_dataset(\"sdba/ahccd_1950-2013.nc\")\n",
+    "ds_sim = xc.testing.open_dataset(\"sdba/nrcan_1950-2013.nc\")\n",
+    "for v in ds.data_vars: \n",
+    "    ds_sim[v] = xc.core.units.convert_units_to(ds_sim[v], ds_ref[v], context=\"hydro\")\n",
+    "\n",
+    "# Here, we have three locations, two variables. We stack variables to convert from\n",
+    "# a Dataset to a DataArray.\n",
+    "da_ref = sdba.stack_variables(ds_ref)\n",
+    "da_sim = sdba.stack_variables(ds_sim)\n",
+    "\n",
+    "# Each location/variable will have its own set of taylor parameters\n",
+    "out = sdba.measures.taylordiagram(ref=da_ref, sim=da_sim, dim=\"time\")\n",
+    "\n",
+    "# If we normalize the taylor diagrams, they can be compared on the same plot\n",
+    "out[{\"taylor_param\":[0,1]}] = out[{\"taylor_param\":[0,1]}]/out[{\"taylor_param\":0}]\n",
     "\n",
-    "fg.taylordiagram(sims, std_range=(0, 1.3), contours=5, contours_kw={'colors': 'green'}, plot_kw={'reference': {'marker':'*'}})\n"
+    "# The `markers_key` and `colors_key` are used to separate between two different features. \n",
+    "# Here, the type of marker is used to distinguish between locations, and the color \n",
+    "# distinguishes between variables. If those parameters are not specified, then each \n",
+    "# pair (location, multivar)  has simply its own color.\n",
+    "# NB: Negatives correlations are not plotted\n",
+    "fg.taylordiagram(out, markers_key=\"location\", colors_key=\"multivar\")\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "63",
+   "id": "65",
    "metadata": {},
    "source": [
     "## Partition plots\n",
@@ -1045,7 +1083,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "64",
+   "id": "66",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1095,7 +1133,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "65",
+   "id": "67",
    "metadata": {},
    "source": [
     "Compute uncertainties with xclim and use `fractional_uncertainty` to have the right format to plot."
@@ -1104,7 +1142,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "66",
+   "id": "68",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1140,7 +1178,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "67",
+   "id": "69",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1160,7 +1198,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "68",
+   "id": "70",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -1178,7 +1216,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

docs/notebooks/figanos_multiplots.ipynb

@@ -367,7 +367,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,