Update helper tuto

Author: luseverin

doc/user-guide/climada_engine_unsequa_helper.ipynb

@@ -67,7 +67,7 @@
     "- EN: mutliplicative noise (inhomogeneous)\n",
     "> The value of each exposure point is independently multiplied by a random number sampled uniformly from a distribution with (min, max) = bounds_noise. EN is the value of the seed for  the uniform random number generator.\n",
     "- EL: sample uniformly from exposure list\n",
-    "> From the provided list of exposure is elements are uniformly sampled. For example, LitPop instances with different exponents.\n",
+    "> Uniformly sample one element from the provided list of exposures. For example, LitPop instances with different exponents.\n",
     "\n",
     "\n",
     "If a bounds is None, this parameter is assumed to have no uncertainty."
@@ -201,7 +201,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "802ac379-39a0-476d-b068-36520d03a459",
    "metadata": {
     "ExecuteTime": {
@@ -226,8 +226,8 @@
     "        print(\"\\n Computing litpop for m=%d, n=%d \\n\" % (m, n))\n",
     "        litpop_kwargs[\"exponents\"] = (m, n)\n",
     "        exp = LitPop.from_countries(**litpop_kwargs)\n",
-    "        exp.gdf[\"impf_\" + haz.haz_type] = impf_id\n",
-    "        exp.gdf.drop(\"impf_\", axis=1, inplace=True)\n",
+    "        exp.data[\"impf_\" + haz.haz_type] = impf_id\n",
+    "        exp.data.drop(\"impf_\", axis=1, inplace=True)\n",
     "        if value_unit is not None:\n",
     "            exp.value_unit = value_unit\n",
     "        exp.assign_centroids(haz, **assign_centr_kwargs)\n",
@@ -897,7 +897,7 @@
     "- HF: scale the frequency of all events (homogeneously)\n",
     "> The frequency of all events is multiplied by a number sampled uniformly from a distribution with (min, max) = bounds_freq\n",
     "- HL: sample uniformly from hazard list\n",
-    "> From the provided list of hazard is elements are uniformly sampled. For example, Hazards outputs from dynamical models for different input factors.\n",
+    "> Uniformly sample one element from the provided list of hazards. For example, Hazards outputs from dynamical models for different input factors.\n",
     "\n",
     "If a bounds is None, this parameter is assumed to have no uncertainty."
    ]
@@ -1146,14 +1146,14 @@
    },
    "source": [
     "The following types of uncertainties can be added:\n",
-    "- MDD: scale the mdd (homogeneously)\n",
+    "- MDD: scale the Mean Damage Degree MDD (homogeneously)\n",
     "> The value of mdd at each intensity is multiplied by a number sampled uniformly from a distribution with (min, max) = bounds_mdd\n",
-    "- PAA: scale the paa (homogeneously)\n",
+    "- PAA: scale the Percentage of Affected Assets PAA (homogeneously)\n",
     "> The value of paa at each intensity is multiplied by a number sampled uniformly from a distribution with (min, max) = bounds_paa\n",
     "- IFi: shift the intensity (homogeneously)\n",
     "> The value intensity are all summed with a random number sampled uniformly from a distribution with (min, max) = bounds_int\n",
     "- IL: sample uniformly from impact function set list\n",
-    "> From the provided list of impact function sets elements are uniformly sampled. For example, impact functions obtained from different calibration methods.\n",
+    "> Uniformly sample one element from the provided list of impact function sets. For example, impact functions obtained from different calibration methods.\n",
     "\n",
     "\n",
     "If a bounds is None, this parameter is assumed to have no uncertainty."
@@ -1268,13 +1268,15 @@
     "- EN: mutliplicative noise (inhomogeneous)\n",
     "> The value of each exposure point is independently multiplied by a random number sampled uniformly from a distribution with (min, max) = bounds_noise. EN is the value of the seed for  the uniform random number generator.\n",
     "- EL: sample uniformly from exposure list\n",
-    "> From the provided list of exposure is elements are uniformly sampled. For example, LitPop instances with different exponents.\n",
+    "> Uniformly sample one element from the provided list of exposures. For example, LitPop instances with different exponents.\n",
     "- MDD: scale the mdd (homogeneously)\n",
     "> The value of mdd at each intensity is multiplied by a number sampled uniformly from a distribution with (min, max) = bounds_mdd\n",
     "- PAA: scale the paa (homogeneously)\n",
     "> The value of paa at each intensity is multiplied by a number sampled uniformly from a distribution with (min, max) = bounds_paa\n",
     "- IFi: shift the intensity (homogeneously)\n",
     "> The value intensity are all summed with a random number sampled uniformly from a distribution with (min, max) = bounds_int\n",
+    "- IL: sample uniformly from impact function set list\n",
+    "> Uniformly sample one element from the provided list of impact function sets. For example, impact functions obtained from different calibration methods.\n",
     "\n",
     "\n",
     "If a bounds is None, this parameter is assumed to have no uncertainty."
@@ -1819,15 +1821,15 @@
     "- EN: mutliplicative noise (inhomogeneous)\n",
     "> The value of each exposure point is independently multiplied by a random number sampled uniformly from a distribution with (min, max) = bounds_noise. EN is the value of the seed for  the uniform random number generator.\n",
     "- EL: sample uniformly from exposure list\n",
-    "> From the provided list of exposure is elements are uniformly sampled. For example, LitPop instances with different exponents.\n",
+    "> Uniformly sample one element from the provided list of exposures. For example, LitPop instances with different exponents.\n",
     "- MDD: scale the mdd (homogeneously)\n",
     "> The value of mdd at each intensity is multiplied by a number sampled uniformly from a distribution with (min, max) = bounds_mdd\n",
     "- PAA: scale the paa (homogeneously)\n",
     "> The value of paa at each intensity is multiplied by a number sampled uniformly from a distribution with (min, max) = bounds_paa\n",
     "- IFi: shift the impact function intensity (homogeneously)\n",
     "> The value intensity are all summed with a random number sampled uniformly from a distribution with (min, max) = bounds_impfi\n",
     "- IL: sample uniformly from impact function set list\n",
-    "> From the provided list of impact function sets elements are uniformly sampled. For example, impact functions obtained from different calibration methods.\n",
+    "> Uniformly sample one element from the provided list of impact function sets. For example, impact functions obtained from different calibration methods.\n",
     "\n",
     "\n",
     "If a bounds is None, this parameter is assumed to have no uncertainty."