#print("Working on a ", platform.system(), platform.release())
+print("Python version ", sys.version)
+print("Pandas version ", pd.__version__)
+print("pyplot ", plt.matplotlib.__version__)
+print("PV_ICE version ", PV_ICE.__version__)
+Python version 3.11.5 | packaged by Anaconda, Inc. | (main, Sep 11 2023, 13:26:23) [MSC v.1916 64 bit (AMD64)] +Pandas version 2.0.3 +pyplot 3.7.2 +PV_ICE version ++
idx_temp = pd.RangeIndex(start=2022,stop=2051,step=1) #create the index
-df_shj_merchanttail = pd.DataFrame(index=idx_temp, columns=['mod_merchanttail'], dtype=float)
+df_shj_merchanttail = pd.DataFrame(index=idx_temp, columns=['mod_merchanttail'], dtype=float)
df_shj_merchanttail.loc[2022] = 0
df_shj_merchanttail.loc[2030] = 0
df_shj_merchanttail.loc[2050] = 0
df_shj_merchanttail.interpolate(inplace=True)
#module collection
-df_shj_modcollect = pd.DataFrame(index=idx_temp, columns=['mod_collect'], dtype=float)
+df_shj_modcollect = pd.DataFrame(index=idx_temp, columns=['mod_collect'], dtype=float)
df_shj_modcollect.loc[2022] = 15
df_shj_modcollect.loc[2030] = 30
df_shj_modcollect.loc[2050] = 75
df_shj_modcollect.interpolate(inplace=True)
#collection
-#sim1.modifyScenario('SHJ', 'mod_EOL_collection_eff', df_shj_modcollect.loc[2022:,'mod_collect'], start_year=2022) #
-df_shj_modremfg = pd.DataFrame(index=idx_temp, columns=['mod_remfg'], dtype=float)
+#sim1.modifyScenario('SHJ', 'mod_EOL_collection_eff', df_shj_modcollect.loc[2022:,'mod_collect'], start_year=2022) #
+df_shj_modremfg = pd.DataFrame(index=idx_temp, columns=['mod_remfg'], dtype=float)
df_shj_modremfg.loc[2022] = 0
df_shj_modremfg.loc[2030] = 0
df_shj_modremfg.loc[2050] = 0
df_shj_modremfg.interpolate(inplace=True)
#module recycling target
-df_shj_modrecycle = pd.DataFrame(index=idx_temp, columns=['mod_recycle'], dtype=float)
+df_shj_modrecycle = pd.DataFrame(index=idx_temp, columns=['mod_recycle'], dtype=float)
df_shj_modrecycle.loc[2022] = 75
df_shj_modrecycle.loc[2030] = 80
df_shj_modrecycle.loc[2050] = 95
@@ -15290,56 +15337,56 @@
idx_temp = pd.RangeIndex(start=2022,stop=2051,step=1) #create the index
-columns = ['mat_MFG_scrap_Recycled','mat_MFG_scrap_Recycling_eff','mat_MFG_scrap_Recycled_into_HQ',
- 'mat_MFG_scrap_Recycled_into_HQ_Reused4MFG','mat_PG3_ReMFG_target','mat_ReMFG_yield',
- 'mat_PG4_Recycling_target','mat_Recycling_yield','mat_EOL_Recycled_into_HQ','mat_EOL_RecycledHQ_Reused4MFG']
+columns = ['mat_MFG_scrap_Recycled','mat_MFG_scrap_Recycling_eff','mat_MFG_scrap_Recycled_into_HQ',
+ 'mat_MFG_scrap_Recycled_into_HQ_Reused4MFG','mat_PG3_ReMFG_target','mat_ReMFG_yield',
+ 'mat_PG4_Recycling_target','mat_Recycling_yield','mat_EOL_Recycled_into_HQ','mat_EOL_RecycledHQ_Reused4MFG']
glassimprovedrecycle = pd.DataFrame(index=idx_temp, columns=columns, dtype=float)
#MFGing Scrap
-glassimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2022] = 80
-glassimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2030] = 100
-glassimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2050] = 100
+glassimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2022] = 80
+glassimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2030] = 100
+glassimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2050] = 100
-glassimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2022] = 50
-glassimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2030] = 80
-glassimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2050] = 90
+glassimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2022] = 50
+glassimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2030] = 80
+glassimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2050] = 90
-glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2022] = 0
-glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2030] = 30
-glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2050] = 75
+glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2022] = 0
+glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2030] = 30
+glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2050] = 75
-glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2022] = 0
-glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2030] = 100
-glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2050] = 100
+glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2022] = 0
+glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2030] = 100
+glassimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2050] = 100
#REMFG
-glassimprovedrecycle['mat_PG3_ReMFG_target'].loc[2022] = 0
-glassimprovedrecycle['mat_PG3_ReMFG_target'].loc[2030] = 50
-glassimprovedrecycle['mat_PG3_ReMFG_target'].loc[2050] = 100
+glassimprovedrecycle['mat_PG3_ReMFG_target'].loc[2022] = 0
+glassimprovedrecycle['mat_PG3_ReMFG_target'].loc[2030] = 50
+glassimprovedrecycle['mat_PG3_ReMFG_target'].loc[2050] = 100
-glassimprovedrecycle['mat_ReMFG_yield'].loc[2022] = 60
-glassimprovedrecycle['mat_ReMFG_yield'].loc[2030] = 80
-glassimprovedrecycle['mat_ReMFG_yield'].loc[2050] = 98
+glassimprovedrecycle['mat_ReMFG_yield'].loc[2022] = 60
+glassimprovedrecycle['mat_ReMFG_yield'].loc[2030] = 80
+glassimprovedrecycle['mat_ReMFG_yield'].loc[2050] = 98
#EoL Recycling
-#glassimprovedrecycle['mat_PG4_Recycling_target'].loc[2022] = 90
-#glassimprovedrecycle['mat_PG4_Recycling_target'].loc[2030] = 100
-#glassimprovedrecycle['mat_PG4_Recycling_target'].loc[2050] = 100
-glassimprovedrecycle['mat_PG4_Recycling_target'] = 100-glassimprovedrecycle['mat_PG3_ReMFG_target']
+#glassimprovedrecycle['mat_PG4_Recycling_target'].loc[2022] = 90
+#glassimprovedrecycle['mat_PG4_Recycling_target'].loc[2030] = 100
+#glassimprovedrecycle['mat_PG4_Recycling_target'].loc[2050] = 100
+glassimprovedrecycle['mat_PG4_Recycling_target'] = 100-glassimprovedrecycle['mat_PG3_ReMFG_target']
-glassimprovedrecycle['mat_Recycling_yield'].loc[2022] = 40
-glassimprovedrecycle['mat_Recycling_yield'].loc[2030] = 60
-glassimprovedrecycle['mat_Recycling_yield'].loc[2050] = 90
+glassimprovedrecycle['mat_Recycling_yield'].loc[2022] = 40
+glassimprovedrecycle['mat_Recycling_yield'].loc[2030] = 60
+glassimprovedrecycle['mat_Recycling_yield'].loc[2050] = 90
-glassimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2022] = 0
-glassimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2030] = 30
-glassimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2050] = 75
+glassimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2022] = 0
+glassimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2030] = 30
+glassimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2050] = 75
-glassimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2022] = 100
-glassimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2030] = 100
-glassimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2050] = 100
+glassimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2022] = 100
+glassimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2030] = 100
+glassimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2050] = 100
glassimprovedrecycle.interpolate()
@@ -15793,54 +15840,54 @@
idx_temp = pd.RangeIndex(start=2022,stop=2051,step=1) #create the index
-columns = ['mat_MFG_scrap_Recycled','mat_MFG_scrap_Recycling_eff','mat_MFG_scrap_Recycled_into_HQ',
- 'mat_MFG_scrap_Recycled_into_HQ_Reused4MFG','mat_PG3_ReMFG_target','mat_ReMFG_yield',
- 'mat_PG4_Recycling_target','mat_Recycling_yield','mat_EOL_Recycled_into_HQ','mat_EOL_RecycledHQ_Reused4MFG']
+columns = ['mat_MFG_scrap_Recycled','mat_MFG_scrap_Recycling_eff','mat_MFG_scrap_Recycled_into_HQ',
+ 'mat_MFG_scrap_Recycled_into_HQ_Reused4MFG','mat_PG3_ReMFG_target','mat_ReMFG_yield',
+ 'mat_PG4_Recycling_target','mat_Recycling_yield','mat_EOL_Recycled_into_HQ','mat_EOL_RecycledHQ_Reused4MFG']
Siimprovedrecycle = pd.DataFrame(index=idx_temp, columns=columns, dtype=float)
#MFGing Scrap
-Siimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2022] = 100
-Siimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2030] = 100
-Siimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2050] = 100
+Siimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2022] = 100
+Siimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2030] = 100
+Siimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2050] = 100
-Siimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2022] = 20
-Siimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2030] = 30
-Siimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2050] = 60
+Siimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2022] = 20
+Siimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2030] = 30
+Siimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2050] = 60
-Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2022] = 0
-Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2030] = 50
-Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2050] = 100
+Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2022] = 0
+Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2030] = 50
+Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2050] = 100
-Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2022] = 100
-Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2030] = 100
-Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2050] = 100
+Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2022] = 100
+Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2030] = 100
+Siimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2050] = 100
#REMFG
-Siimprovedrecycle['mat_PG3_ReMFG_target'].loc[2022] = 0
-Siimprovedrecycle['mat_PG3_ReMFG_target'].loc[2030] = 30
-Siimprovedrecycle['mat_PG3_ReMFG_target'].loc[2050] = 80
+Siimprovedrecycle['mat_PG3_ReMFG_target'].loc[2022] = 0
+Siimprovedrecycle['mat_PG3_ReMFG_target'].loc[2030] = 30
+Siimprovedrecycle['mat_PG3_ReMFG_target'].loc[2050] = 80
-Siimprovedrecycle['mat_ReMFG_yield'].loc[2022] = 0
-Siimprovedrecycle['mat_ReMFG_yield'].loc[2030] = 50
-Siimprovedrecycle['mat_ReMFG_yield'].loc[2050] = 90
+Siimprovedrecycle['mat_ReMFG_yield'].loc[2022] = 0
+Siimprovedrecycle['mat_ReMFG_yield'].loc[2030] = 50
+Siimprovedrecycle['mat_ReMFG_yield'].loc[2050] = 90
#EoL Recycling
-Siimprovedrecycle['mat_PG4_Recycling_target'].loc[2022] = 100
-Siimprovedrecycle['mat_PG4_Recycling_target'].loc[2030] = 50
-Siimprovedrecycle['mat_PG4_Recycling_target'].loc[2050] = 10
+Siimprovedrecycle['mat_PG4_Recycling_target'].loc[2022] = 100
+Siimprovedrecycle['mat_PG4_Recycling_target'].loc[2030] = 50
+Siimprovedrecycle['mat_PG4_Recycling_target'].loc[2050] = 10
-Siimprovedrecycle['mat_Recycling_yield'].loc[2022] = 20
-Siimprovedrecycle['mat_Recycling_yield'].loc[2030] = 30
-Siimprovedrecycle['mat_Recycling_yield'].loc[2050] = 75
+Siimprovedrecycle['mat_Recycling_yield'].loc[2022] = 20
+Siimprovedrecycle['mat_Recycling_yield'].loc[2030] = 30
+Siimprovedrecycle['mat_Recycling_yield'].loc[2050] = 75
-Siimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2022] = 0
-Siimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2030] = 50
-Siimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2050] = 90
+Siimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2022] = 0
+Siimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2030] = 50
+Siimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2050] = 90
-Siimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2022] = 0
-Siimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2030] = 100
-Siimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2050] = 100
+Siimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2022] = 0
+Siimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2030] = 100
+Siimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2050] = 100
Siimprovedrecycle.interpolate()
@@ -16294,54 +16341,54 @@
idx_temp = pd.RangeIndex(start=2022,stop=2051,step=1) #create the index
-columns = ['mat_MFG_scrap_Recycled','mat_MFG_scrap_Recycling_eff','mat_MFG_scrap_Recycled_into_HQ',
- 'mat_MFG_scrap_Recycled_into_HQ_Reused4MFG','mat_PG3_ReMFG_target','mat_ReMFG_yield',
- 'mat_PG4_Recycling_target','mat_Recycling_yield','mat_EOL_Recycled_into_HQ','mat_EOL_RecycledHQ_Reused4MFG']
+columns = ['mat_MFG_scrap_Recycled','mat_MFG_scrap_Recycling_eff','mat_MFG_scrap_Recycled_into_HQ',
+ 'mat_MFG_scrap_Recycled_into_HQ_Reused4MFG','mat_PG3_ReMFG_target','mat_ReMFG_yield',
+ 'mat_PG4_Recycling_target','mat_Recycling_yield','mat_EOL_Recycled_into_HQ','mat_EOL_RecycledHQ_Reused4MFG']
Alimprovedrecycle = pd.DataFrame(index=idx_temp, columns=columns, dtype=float)
#MFGing Scrap
-Alimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2022] = 100
-Alimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2030] = 100
-Alimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2050] = 100
+Alimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2022] = 100
+Alimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2030] = 100
+Alimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2050] = 100
-Alimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2022] = 60
-Alimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2030] = 70
-Alimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2050] = 90
+Alimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2022] = 60
+Alimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2030] = 70
+Alimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2050] = 90
-Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2022] = 100
-Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2030] = 100
-Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2050] = 100
+Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2022] = 100
+Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2030] = 100
+Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2050] = 100
-Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2022] = 100
-Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2030] = 100
-Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2050] = 100
+Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2022] = 100
+Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2030] = 100
+Alimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2050] = 100
#REMFG
-Alimprovedrecycle['mat_PG3_ReMFG_target'].loc[2022] = 0
-Alimprovedrecycle['mat_PG3_ReMFG_target'].loc[2030] = 0
-Alimprovedrecycle['mat_PG3_ReMFG_target'].loc[2050] = 0
+Alimprovedrecycle['mat_PG3_ReMFG_target'].loc[2022] = 0
+Alimprovedrecycle['mat_PG3_ReMFG_target'].loc[2030] = 0
+Alimprovedrecycle['mat_PG3_ReMFG_target'].loc[2050] = 0
-Alimprovedrecycle['mat_ReMFG_yield'].loc[2022] = 0
-Alimprovedrecycle['mat_ReMFG_yield'].loc[2030] = 0
-Alimprovedrecycle['mat_ReMFG_yield'].loc[2050] = 0
+Alimprovedrecycle['mat_ReMFG_yield'].loc[2022] = 0
+Alimprovedrecycle['mat_ReMFG_yield'].loc[2030] = 0
+Alimprovedrecycle['mat_ReMFG_yield'].loc[2050] = 0
#EoL Recycling
-Alimprovedrecycle['mat_PG4_Recycling_target'].loc[2022] = 100
-Alimprovedrecycle['mat_PG4_Recycling_target'].loc[2030] = 100
-Alimprovedrecycle['mat_PG4_Recycling_target'].loc[2050] = 100
+Alimprovedrecycle['mat_PG4_Recycling_target'].loc[2022] = 100
+Alimprovedrecycle['mat_PG4_Recycling_target'].loc[2030] = 100
+Alimprovedrecycle['mat_PG4_Recycling_target'].loc[2050] = 100
-Alimprovedrecycle['mat_Recycling_yield'].loc[2022] = 42
-Alimprovedrecycle['mat_Recycling_yield'].loc[2030] = 75
-Alimprovedrecycle['mat_Recycling_yield'].loc[2050] = 98
+Alimprovedrecycle['mat_Recycling_yield'].loc[2022] = 42
+Alimprovedrecycle['mat_Recycling_yield'].loc[2030] = 75
+Alimprovedrecycle['mat_Recycling_yield'].loc[2050] = 98
-Alimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2022] = 100
-Alimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2030] = 100
-Alimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2050] = 100
+Alimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2022] = 100
+Alimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2030] = 100
+Alimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2050] = 100
-Alimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2022] = 20
-Alimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2030] = 50
-Alimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2050] = 100
+Alimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2022] = 20
+Alimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2030] = 50
+Alimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2050] = 100
Alimprovedrecycle.interpolate()
@@ -16795,54 +16842,54 @@
idx_temp = pd.RangeIndex(start=2022,stop=2051,step=1) #create the index
-columns = ['mat_MFG_scrap_Recycled','mat_MFG_scrap_Recycling_eff','mat_MFG_scrap_Recycled_into_HQ',
- 'mat_MFG_scrap_Recycled_into_HQ_Reused4MFG','mat_PG3_ReMFG_target','mat_ReMFG_yield',
- 'mat_PG4_Recycling_target','mat_Recycling_yield','mat_EOL_Recycled_into_HQ','mat_EOL_RecycledHQ_Reused4MFG']
+columns = ['mat_MFG_scrap_Recycled','mat_MFG_scrap_Recycling_eff','mat_MFG_scrap_Recycled_into_HQ',
+ 'mat_MFG_scrap_Recycled_into_HQ_Reused4MFG','mat_PG3_ReMFG_target','mat_ReMFG_yield',
+ 'mat_PG4_Recycling_target','mat_Recycling_yield','mat_EOL_Recycled_into_HQ','mat_EOL_RecycledHQ_Reused4MFG']
Agimprovedrecycle = pd.DataFrame(index=idx_temp, columns=columns, dtype=float)
#MFGing Scrap
-Agimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2022] = 95
-Agimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2030] = 100
-Agimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2050] = 100
+Agimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2022] = 95
+Agimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2030] = 100
+Agimprovedrecycle['mat_MFG_scrap_Recycled'].loc[2050] = 100
-Agimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2022] = 97
-Agimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2030] = 98
-Agimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2050] = 99
+Agimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2022] = 97
+Agimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2030] = 98
+Agimprovedrecycle['mat_MFG_scrap_Recycling_eff'].loc[2050] = 99
-Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2022] = 100
-Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2030] = 100
-Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2050] = 100
+Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2022] = 100
+Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2030] = 100
+Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ'].loc[2050] = 100
-Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2022] = 16.61
-Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2030] = 30
-Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2050] = 75
+Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2022] = 16.61
+Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2030] = 30
+Agimprovedrecycle['mat_MFG_scrap_Recycled_into_HQ_Reused4MFG'].loc[2050] = 75
#REMFG
-Agimprovedrecycle['mat_PG3_ReMFG_target'].loc[2022] = 0
-Agimprovedrecycle['mat_PG3_ReMFG_target'].loc[2030] = 0
-Agimprovedrecycle['mat_PG3_ReMFG_target'].loc[2050] = 0
+Agimprovedrecycle['mat_PG3_ReMFG_target'].loc[2022] = 0
+Agimprovedrecycle['mat_PG3_ReMFG_target'].loc[2030] = 0
+Agimprovedrecycle['mat_PG3_ReMFG_target'].loc[2050] = 0
-Agimprovedrecycle['mat_ReMFG_yield'].loc[2022] = 0
-Agimprovedrecycle['mat_ReMFG_yield'].loc[2030] = 0
-Agimprovedrecycle['mat_ReMFG_yield'].loc[2050] = 0
+Agimprovedrecycle['mat_ReMFG_yield'].loc[2022] = 0
+Agimprovedrecycle['mat_ReMFG_yield'].loc[2030] = 0
+Agimprovedrecycle['mat_ReMFG_yield'].loc[2050] = 0
#EoL Recycling
-Agimprovedrecycle['mat_PG4_Recycling_target'].loc[2022] = 0
-Agimprovedrecycle['mat_PG4_Recycling_target'].loc[2030] = 100
-Agimprovedrecycle['mat_PG4_Recycling_target'].loc[2050] = 100
+Agimprovedrecycle['mat_PG4_Recycling_target'].loc[2022] = 0
+Agimprovedrecycle['mat_PG4_Recycling_target'].loc[2030] = 100
+Agimprovedrecycle['mat_PG4_Recycling_target'].loc[2050] = 100
-Agimprovedrecycle['mat_Recycling_yield'].loc[2022] = 97
-Agimprovedrecycle['mat_Recycling_yield'].loc[2030] = 98
-Agimprovedrecycle['mat_Recycling_yield'].loc[2050] = 99
+Agimprovedrecycle['mat_Recycling_yield'].loc[2022] = 97
+Agimprovedrecycle['mat_Recycling_yield'].loc[2030] = 98
+Agimprovedrecycle['mat_Recycling_yield'].loc[2050] = 99
-Agimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2022] = 80
-Agimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2030] = 100
-Agimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2050] = 100
+Agimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2022] = 80
+Agimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2030] = 100
+Agimprovedrecycle['mat_EOL_Recycled_into_HQ'].loc[2050] = 100
-Agimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2022] = 16.61
-Agimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2030] = 30
-Agimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2050] = 75
+Agimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2022] = 16.61
+Agimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2030] = 30
+Agimprovedrecycle['mat_EOL_RecycledHQ_Reused4MFG'].loc[2050] = 75
Agimprovedrecycle.interpolate()
@@ -17302,22 +17349,18 @@ Calculations for Project L
-
+
+
-
-In [8]:
-
-
-import PV_ICE
-
+
+
+import PV_ICE
-
-
@@ -17373,7 +17416,7 @@ Calculations for Project L
T50 = pd.Series(range(15,66,1))
T90 = pd.Series(range(18,69,1))
-inputsdf = pd.concat([T50,T90],axis=1, keys=['T50','T90'])
+inputsdf = pd.concat([T50,T90],axis=1, keys=['T50','T90'])
inputsdf
@@ -17695,10 +17738,10 @@ Calculations for Project L
for row in inputsdf.index:
- t50, t90 = inputsdf.loc[row,'T50'], inputsdf.loc[row,'T90']
+ t50, t90 = inputsdf.loc[row,'T50'], inputsdf.loc[row,'T90']
params = PV_ICE.weibull_params({t50: 0.50, t90: 0.90})
- T10 = alphabeta2T10(params['alpha'],params['beta'])
- inputsdf.loc[row,'T10'] = T10
+ T10 = alphabeta2T10(params['alpha'],params['beta'])
+ inputsdf.loc[row,'T10'] = T10
inputsdf
@@ -18089,7 +18132,7 @@ Calculations for Project L
T50 = pd.Series([16,19,20,21,24,25,28,33,40])
T90 = pd.Series([21,23,25,26,29,30,33,38,44])
-inputsdf = pd.concat([T50,T90],axis=1, keys=['T50','T90'])
+inputsdf = pd.concat([T50,T90],axis=1, keys=['T50','T90'])
inputsdf
@@ -18216,10 +18259,10 @@ Calculations for Project L
for row in inputsdf.index:
- t50, t90 = inputsdf.loc[row,'T50'], inputsdf.loc[row,'T90']
+ t50, t90 = inputsdf.loc[row,'T50'], inputsdf.loc[row,'T90']
params = PV_ICE.weibull_params({t50: 0.50, t90: 0.90})
- T10 = alphabeta2T10(params['alpha'],params['beta'])
- inputsdf.loc[row,'T10'] = T10
+ T10 = alphabeta2T10(params['alpha'],params['beta'])
+ inputsdf.loc[row,'T10'] = T10
inputsdf
@@ -18341,7 +18384,7 @@ Calculations for Project L
params = PV_ICE.weibull_params({44.83: 0.50, 49: 0.90})
-T10 = alphabeta2T10(params['alpha'],params['beta'])
+T10 = alphabeta2T10(params['alpha'],params['beta'])
T10
@@ -18486,9 +18529,9 @@ Calculations for Project L
T10 = projectlife
T90 = T10+N
params = PV_ICE.weibull_params({T10: 0.10, T90: 0.90})
- T50 = round(-params['beta']*-np.abs(np.log(0.5))**(1/params['alpha']),2)
+ T50 = round(-params['beta']*-np.abs(np.log(0.5))**(1/params['alpha']),2)
if plot==True:
- plt.plot(PV_ICE.weibull_cdf_vis(params['alpha'],params['beta']))
+ plt.plot(PV_ICE.weibull_cdf_vis(params['alpha'],params['beta']))
return T50,T90
@@ -18566,7 +18609,7 @@ Calculations for Project L
#Mod Project Lifetime
idx_temp = pd.RangeIndex(start=2022,stop=2051,step=1) #create the index
-life = pd.DataFrame(index=idx_temp, columns=['mod_lifetime'], dtype=float)
+life = pd.DataFrame(index=idx_temp, columns=['mod_lifetime'], dtype=float)
life.loc[2022] = 20
#life.loc[2030] =
life.loc[2050] = 32
@@ -18590,9 +18633,9 @@ Calculations for Project L
df_t50t90 = pd.DataFrame()
for row in life.index:
- T50,T90 = projectlife2T50T90(life.loc[row,'mod_lifetime'])
- df_t50t90.loc[row,'T50'] = T50
- df_t50t90.loc[row,'T90'] = T90
+ T50,T90 = projectlife2T50T90(life.loc[row,'mod_lifetime'])
+ df_t50t90.loc[row,'T50'] = T50
+ df_t50t90.loc[row,'T90'] = T90
pd.concat([round(life,0),df_t50t90],axis=1)
@@ -18854,7 +18897,7 @@ Calculations for Project L
#checking T90 from Ab et al 2018
params = PV_ICE.weibull_params({44.83: 0.50, 49: 0.90})
-alphabeta2T10(params['alpha'],params['beta'])
+alphabeta2T10(params['alpha'],params['beta'])
diff --git a/docs/baseline development documentation/(dev) AltInputsGenerationScripts.ipynb b/docs/baseline development documentation/(dev) AltInputsGenerationScripts.ipynb
index 01ff832..bc87fb7 100644
--- a/docs/baseline development documentation/(dev) AltInputsGenerationScripts.ipynb
+++ b/docs/baseline development documentation/(dev) AltInputsGenerationScripts.ipynb
@@ -12,17 +12,40 @@
"import os,sys\n",
"from pathlib import Path\n",
"import matplotlib.pyplot as plt\n",
- "\n",
+ "import PV_ICE\n",
"cwd = os.getcwd() #grabs current working directory\n"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "b36be534-06fa-4ed8-b0a0-cb7cbfc6e600",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Python version 3.11.5 | packaged by Anaconda, Inc. | (main, Sep 11 2023, 13:26:23) [MSC v.1916 64 bit (AMD64)]\n",
+ "Pandas version 2.0.3\n",
+ "pyplot 3.7.2\n",
+ "PV_ICE version \n"
+ ]
+ }
+ ],
+ "source": [
+ "#print(\"Working on a \", platform.system(), platform.release())\n",
+ "print(\"Python version \", sys.version)\n",
+ "print(\"Pandas version \", pd.__version__)\n",
+ "print(\"pyplot \", plt.matplotlib.__version__)\n",
+ "print(\"PV_ICE version \", PV_ICE.__version__)"
+ ]
+ },
{
"cell_type": "code",
"execution_count": 2,
"id": "20abc6b4",
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [
{
"data": {
@@ -377,9 +400,7 @@
"cell_type": "code",
"execution_count": 3,
"id": "4a55a2e3",
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [
{
"data": {
@@ -729,9 +750,7 @@
"cell_type": "code",
"execution_count": 4,
"id": "91400dfb",
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [
{
"data": {
@@ -3295,11 +3314,9 @@
]
},
{
- "cell_type": "code",
- "execution_count": 8,
- "id": "0f828010",
+ "cell_type": "markdown",
+ "id": "f90a3f64-061d-4b4d-9d53-d1658309f80b",
"metadata": {},
- "outputs": [],
"source": [
"import PV_ICE"
]
@@ -4457,9 +4474,7 @@
"cell_type": "code",
"execution_count": 20,
"id": "d7444940",
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [
{
"data": {
@@ -4490,9 +4505,7 @@
"cell_type": "code",
"execution_count": 21,
"id": "93021324",
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [],
"source": [
"#Mod Project Lifetime\n",
@@ -4510,9 +4523,7 @@
"cell_type": "code",
"execution_count": 22,
"id": "a31dcad8",
- "metadata": {
- "scrolled": false
- },
+ "metadata": {},
"outputs": [
{
"data": {
@@ -4833,7 +4844,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.8"
+ "version": "3.11.5"
}
},
"nbformat": 4,
diff --git a/docs/baseline development documentation/(dev) AltInputsGenerationScripts.py b/docs/baseline development documentation/(dev) AltInputsGenerationScripts.py
index 8b502ed..28b590f 100644
--- a/docs/baseline development documentation/(dev) AltInputsGenerationScripts.py
+++ b/docs/baseline development documentation/(dev) AltInputsGenerationScripts.py
@@ -9,10 +9,20 @@
import os,sys
from pathlib import Path
import matplotlib.pyplot as plt
-
+import PV_ICE
cwd = os.getcwd() #grabs current working directory
+# In[3]:
+
+
+#print("Working on a ", platform.system(), platform.release())
+print("Python version ", sys.version)
+print("Pandas version ", pd.__version__)
+print("pyplot ", plt.matplotlib.__version__)
+print("PV_ICE version ", PV_ICE.__version__)
+
+
# In[2]:
@@ -339,11 +349,7 @@
# (ex) TN0 - x years = TM0
# and TN0 = -beta*-np.abs(np.log(1-TN0))^(1/alpha)
-# In[8]:
-
-
-import PV_ICE
-
+# import PV_ICE
# In[9]: