Merge branch 'main' of https://github.com/SPROOK/InRoomAirFilterScaleUp

Author: HEYBRR

results/Percentage_After_1_Yr_region_MS.csv

@@ -1,23 +1,23 @@
 Region,Percentage after 1 Year
-Australia and New Zealand,38.647544557146354
-Caribbean,9.047952056011187
-Central America,26.255501041024676
-Central Asia,9.243882570450882
-Eastern Africa,0.034724292567159386
-Eastern Asia,47.67567705830016
-Eastern Europe,18.1051137196055
-Melanesia,0.2898233223373184
-Micronesia,1.7609380286706433
-Middle Africa,0.006332446226603382
-Northern Africa,5.408045587566065
-Northern America,102.18382538841222
-Northern Europe,73.93373954835721
-Polynesia,1.1783302550047663
-South America,11.167957520602034
-South-eastern Asia,10.534889709477083
-Southern Africa,14.952272797936514
-Southern Asia,3.739199000746242
-Southern Europe,47.6791128952953
-Western Africa,1.7991069021255401
-Western Asia,16.222458793943577
-Western Europe,98.26477850491979
+Australia and New Zealand,3864.7544557146352
+Caribbean,904.7952056011187
+Central America,2625.5501041024672
+Central Asia,924.3882570450884
+Eastern Africa,3.4724292567159387
+Eastern Asia,4767.567705830016
+Eastern Europe,1810.5113719605502
+Melanesia,28.98233223373183
+Micronesia,176.09380286706434
+Middle Africa,0.6332446226603382
+Northern Africa,540.8045587566064
+Northern America,10218.382538841222
+Northern Europe,7393.373954835721
+Polynesia,117.83302550047662
+South America,1116.7957520602035
+South-eastern Asia,1053.4889709477084
+Southern Africa,1495.2272797936516
+Southern Asia,373.9199000746242
+Southern Europe,4767.911289529529
+Western Africa,179.91069021255402
+Western Asia,1622.2458793943576
+Western Europe,9826.47785049198

results/Scale_up_COALBAG_MS.pkl

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -37,7 +37,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -244,7 +244,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -291,7 +291,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -348,7 +348,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -457,7 +457,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -515,7 +515,7 @@
     "    ]    \n",
     "    if ecw_list[0] == 0:\n",
     "        PERCENT_ECW_data_points = [0] * (Scale_Up_Time_Period_In_Weeks+1)\n",
-    "    else: PERCENT_ECW_data_points = [x/(CADRPP*ecw_list[0]) for x in MAIN_data_points]\n",
+    "    else: PERCENT_ECW_data_points = [100*x/(CADRPP*ecw_list[0]) for x in MAIN_data_points]\n",
     "\n",
     "    scale_up_data_country_MAIN[country.name] = ecw_list + MAIN_data_points\n",
     "    scale_up_data_country_PERCENT_ECW[country.name] = ecw_list + PERCENT_ECW_data_points\n",
@@ -561,10 +561,10 @@
     "for region in UNRegion_list:\n",
     "    ecw_list_region = scale_up_data_region_MAIN[region][:2]\n",
     "    PERCENT_ECW_region_data_points = scale_up_data_region_MAIN[region][2:]\n",
-    "    scale_up_data_region_PERCENT_ECW[region] = ecw_list_region + [x/(CADRPP*ecw_list_region[0]) for x in PERCENT_ECW_region_data_points]\n",
+    "    scale_up_data_region_PERCENT_ECW[region] = ecw_list_region + [100*x/(CADRPP*ecw_list_region[0]) for x in PERCENT_ECW_region_data_points]\n",
     "ecw_list_global = scale_up_data_region_MAIN['Global'][:2]\n",
     "PERCENT_ECW_global_data_points = scale_up_data_region_MAIN['Global'][2:]\n",
-    "scale_up_data_region_PERCENT_ECW[\"Global\"] = ecw_list_global + [x/(CADRPP*ecw_list_global[0]) for x in PERCENT_ECW_global_data_points]\n",
+    "scale_up_data_region_PERCENT_ECW[\"Global\"] = ecw_list_global + [100*x/(CADRPP*ecw_list_global[0]) for x in PERCENT_ECW_global_data_points]\n",
     "\n",
     "## ------- Exporting -------\n",
     "Scale_Up_df_MAIN = pd.DataFrame(scale_up_data_country_MAIN | scale_up_data_region_MAIN).T\n",
@@ -591,7 +591,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -635,7 +635,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [

results/Scale_up_CR_MAN_MS.pkl

@@ -137,7 +137,7 @@
     "\n",
     "    stack_vals = [vals1, vals2, vals3, vals4]\n",
     "    \n",
-    "    labels = ['CR Box Repurposing', 'CR Box Stock', 'Coalbaghouse','CR Box Manufacturing']\n",
+    "    labels = ['CR Box Repurposing', 'CR Box Stock', 'Coal Baghouse','CR Box Manufacturing']\n",
     "    \n",
     "    ax.stackplot(t, *stack_vals, labels=labels, alpha=0.6)\n",
     "    \n",