update notebook metadata to select R kernel

b29e11bc · Thibault Hallouin · 75324e21 · b29e11bc
Commit b29e11bc authored 2 years ago by Thibault Hallouin
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with 10 additions and 14 deletions
+10 -14
--- a/evalhyd-r.ipynb
+++ b/evalhyd-r.ipynb
@@ -66,7 +66,7 @@
   "execution_count": null,
   "outputs": [],
   "source": [
-    "# shape: {series: 1, time:4}\n",
+    "# shape: {series: 1, time: 4}\n",
    "prd <- rbind(\n",
    "    c(5.3, 4.2, 5.7, 2.3)\n",
    ")"
@@ -199,21 +199,17 @@
 ],
 "metadata": {
  "kernelspec": {
-   "display_name": "hj-38-nompi",
-   "language": "python",
-   "name": "hj-38-nompi"
+   "name": "ir",
+   "display_name": "R",
+   "language": "R"
  },
  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "name": "R",
+   "codemirror_mode": "r",
+   "pygments_lexer": "r",
+   "mimetype": "text/x-r-source",
+   "file_extension": ".r",
+   "version":"4.2.3"
  }
 },
 "nbformat": 4,

 %% Cell type:markdown id: tags:

 ## `evalhyd-r` demonstration

 %% Cell type:code id: tags:

-``` python
+``` R
 library(evalhyd)
 ```

 %% Cell type:markdown id: tags:

 ### Deterministic evaluation

 %% Cell type:markdown id: tags:

 Define streamflow observations

 %% Cell type:code id: tags:

-``` python
+``` R
 # shape: {1, time: 4}
 obs <- rbind(
    c(4.7, 4.3, 5.5, 2.7)
 )
 ```

 %% Cell type:markdown id: tags:

 Define streamflow predictions

 %% Cell type:code id: tags:

-``` python
-# shape: {series: 1, time:4}
+``` R
+# shape: {series: 1, time: 4}
 prd <- rbind(
    c(5.3, 4.2, 5.7, 2.3)
 )
 ```

 %% Cell type:markdown id: tags:

 Compute Nash-Sutcliffe efficiency

 %% Cell type:code id: tags:

-``` python
+``` R
 # shape: {series: 1, subsets: 1, samples: 1}
 evalhyd::evald(obs, prd, c("NSE"))
 ```

 %% Cell type:markdown id: tags:

 ### Probabilistic evaluation

 %% Cell type:markdown id: tags:

 Define streamflow observations

 %% Cell type:code id: tags:

-``` python
+``` R
 # shape: {sites: 1, time: 5}
 obs <- rbind(
    c(4.7, 4.3, 5.5, 2.7, 4.1)
 )
 ```

 %% Cell type:markdown id: tags:

 Define streamflow predictions

 %% Cell type:code id: tags:

-``` python
+``` R
 # shape: {sites: 1, lead times: 1, members: 3, time: 5}
 prd <- array(
    rbind(c(5.3, 4.2, 5.7, 2.3, 3.1),
          c(4.3, 4.2, 4.7, 4.3, 3.3),
          c(5.3, 5.2, 5.7, 2.3, 3.9)),
    dim = c(1, 1, 3, 5)
 )
 ```

 %% Cell type:markdown id: tags:

 Define streamflow thresholds

 %% Cell type:code id: tags:

-``` python
+``` R
 # shape: {sites: 1, thresholds: 2}
 thr <- rbind(
    c(4., 5.)
 )
 ```

 %% Cell type:markdown id: tags:

 Compute Brier score

 %% Cell type:code id: tags:

-``` python
+``` R
 # shape: {sites: 1, lead times: 1, subsets: 1, samples: 1, thresholds: 2}
 evalhyd::evalp(obs, prd, c("BS"), thr, events="high")
 ```