Fix: update deprecated scipy.integrate.trapz to trapezoid #243 (#262)

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Author: wietzesuijker

.github/dependabot.yml

@@ -4,7 +4,7 @@ updates:
     directory: "/.devcontainer"
     schedule:
       interval: "daily"
-  - package-ecosystem: "github-actions" 
-    directory: "/.github" 
+  - package-ecosystem: "github-actions"
+    directory: "/.github"
     schedule:
       interval: "monthly"

advanced/apply_ufunc/core-dimensions.ipynb

@@ -336,19 +336,19 @@
    },
    "source": [
     "```{exercise}\n",
-    ":label: trapz\n",
+    ":label: trapezoid\n",
     "\n",
-    "Use `apply_ufunc` to apply `scipy.integrate.trapz` along the `time` axis.\n",
+    "Use `apply_ufunc` to apply `scipy.integrate.trapezoid` along the `time` axis.\n",
     "```\n",
     "\n",
-    "````{solution} trapz\n",
+    "````{solution} trapezoid\n",
     ":class: dropdown\n",
     "\n",
     "```python\n",
     "import scipy as sp\n",
     "import scipy.integrate\n",
     "\n",
-    "xr.apply_ufunc(scipy.integrate.trapz, ds, input_core_dims=[[\"time\"]], kwargs={\"axis\": -1})\n",
+    "xr.apply_ufunc(scipy.integrate.trapezoid, ds, input_core_dims=[[\"time\"]], kwargs={\"axis\": -1})\n",
     "```\n",
     "````"
    ]

advanced/apply_ufunc/dask_apply_ufunc.ipynb

@@ -338,8 +338,8 @@
     "in parallel to each block. This ability can be activated using\n",
     "`dask=\"parallelized\"`. \n",
     "\n",
-    "We will use `scipy.integrate.trapz` as an example of a function that cannot\n",
-    "handle dask arrays and requires a core dimension. If we call `trapz` with a dask\n",
+    "We will use `scipy.integrate.trapezoid` as an example of a function that cannot\n",
+    "handle dask arrays and requires a core dimension. If we call `trapezoid` with a dask\n",
     "array, we get a numpy array back that is, the values have been eagerly computed.\n",
     "This is undesirable behaviour\n"
    ]
@@ -354,7 +354,7 @@
     "import scipy as sp\n",
     "import scipy.integrate\n",
     "\n",
-    "sp.integrate.trapz(\n",
+    "sp.integrate.trapezoid(\n",
     "    ds.air.data, axis=ds.air.get_axis_num(\"lon\")\n",
     ")  # does NOT return a dask array, you should see activity on the dashboard"
    ]
@@ -377,7 +377,7 @@
    "outputs": [],
    "source": [
     "integrated = xr.apply_ufunc(\n",
-    "    sp.integrate.trapz,\n",
+    "    sp.integrate.trapezoid,\n",
     "    ds,\n",
     "    input_core_dims=[[\"lon\"]],\n",
     "    kwargs={\"axis\": -1},\n",
@@ -479,7 +479,7 @@
     "tags": []
    },
    "source": [
-    "The core dimension for `trapz` is `lon`, and there is only one chunk along `lon`. This means that integrating along `lon` is a \"blockwise\" or \"embarrassingly parallel\" operation and `dask=\"parallelized\"` works quite well. \n",
+    "The core dimension for `trapezoid` is `lon`, and there is only one chunk along `lon`. This means that integrating along `lon` is a \"blockwise\" or \"embarrassingly parallel\" operation and `dask=\"parallelized\"` works quite well. \n",
     "\n",
     "```{caution} Question\n",
     "Do you understand why `integrate(ds)` when `ds` has a single chunk along `lon` is a \"embarrassingly parallel\" operation?\n",
@@ -535,7 +535,7 @@
    "source": [
     "def integrate_wrapper(array, **kwargs):\n",
     "    print(f\"received array of type {type(array)}, shape {array.shape}\")\n",
-    "    result = sp.integrate.trapz(array, **kwargs)\n",
+    "    result = sp.integrate.trapezoid(array, **kwargs)\n",
     "    print(f\"received array of type {type(result)}, shape {result.shape}\")\n",
     "    return result\n",
     "\n",
@@ -611,15 +611,15 @@
     "\n",
     "Conceptually, there is a two-way flow of information between various packages when executing `integrated.compute()`:\n",
     "\n",
-    "`xarray.apply_ufunc` ↔ `dask.array.apply_gufunc` ↔ `integrate_wrapper` ↔ `scipy.integrate.trapz` ↔ `ds.air.data`\n",
+    "`xarray.apply_ufunc` ↔ `dask.array.apply_gufunc` ↔ `integrate_wrapper` ↔ `scipy.integrate.trapezoid` ↔ `ds.air.data`\n",
     "\n",
     "\n",
     "When executed\n",
     "\n",
     "1. Xarray loops over all data variables.\n",
     "1. Xarray unwraps the underlying dask array (e.g. `ds.air`) and passes that to dask's `apply_gufunc`.\n",
     "1. `apply_gufunc` calls `integrate_wrapper` on each block of the array.\n",
-    "1. For each block, `integrate_wrapper` calls `scipy.integrate.trapz` and returns one block of the output array.\n",
+    "1. For each block, `integrate_wrapper` calls `scipy.integrate.trapezoid` and returns one block of the output array.\n",
     "1. dask stitches all the output blocks to form the output array.\n",
     "1. `xarray.apply_ufunc` wraps the output array with Xarray metadata to give the final result.\n",
     "\n",