fix it in adv too

docs/notebooks/sdba-advanced.ipynb

@@ -678,11 +678,11 @@
     "from xclim import sdba\n",
     "\n",
     "group = sdba.Grouper(\"time.dayofyear\", window=31)\n",
-    "sim_ad, pth, dP0 = sdba.processing.adapt_freq(\n",
-    "    pr_ref, pr_sim, thresh=\"0.05 mm d-1\", group=group\n",
+    "hist_ad, pth, dP0 = sdba.processing.adapt_freq(\n",
+    "    pr_ref, pr_hist, thresh=\"0.05 mm d-1\", group=group\n",
     ")\n",
     "QM_ad = sdba.EmpiricalQuantileMapping.train(\n",
-    "    pr_ref, sim_ad, nquantiles=15, kind=\"*\", group=group\n",
+    "    pr_ref, hist_ad, nquantiles=15, kind=\"*\", group=group\n",
     ")\n",
     "scen_ad = QM_ad.adjust(pr_sim)\n",
     "\n",
@@ -698,7 +698,7 @@
    "source": [
     "In the figure above, `scen` occasionally has small peaks where `sim` is 0, indicating that there are more \"dry days\" (days with almost no precipitation) in `hist` than in `ref`. The frequency-adaptation [Themeßl et al. (2010)](https://doi.org/10.1007/s10584-011-0224-4) performed in the step above only worked partially.  \n",
     "\n",
-    "The reason for this is the following. The first step above combines precipitations in 365 overlapping blocks of 31 days * Y years, one block for each day of the year. Each block is adapted, and the 16th day-of-year slice (at the center of the block) is assigned to the corresponding day-of-year in the adapted dataset `sim_ad`. As we proceed to the training, we re-form those 31 days * Y years blocks, but this step does not invert the last one: There can still be more zeroes in the simulation than in the reference. \n",
+    "The reason for this is the following. The first step above combines precipitations in 365 overlapping blocks of 31 days * Y years, one block for each day of the year. Each block is adapted, and the 16th day-of-year slice (at the center of the block) is assigned to the corresponding day-of-year in the adapted dataset `hist_ad`. As we proceed to the training, we re-form those 31 days * Y years blocks, but this step does not invert the last one: There can still be more zeroes in the simulation than in the reference. \n",
     "\n",
     "To alleviate this issue, another way of proceeding is to perform a frequency adaptation on the blocks, and then use the same blocks in the training step, as we show below.\n"
    ]
@@ -714,7 +714,7 @@
     "\n",
     "QM_ad = sdba.EmpiricalQuantileMapping.train(\n",
     "    pr_ref,\n",
-    "    sim_ad,\n",
+    "    pr_hist,\n",
     "    nquantiles=15,\n",
     "    kind=\"*\",\n",
     "    group=group,\n",