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update to v5.2?
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maybe better save as other version!
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@temospena
temospena committed Nov 24, 2023
1 parent e962d08 commit 9f30e1e
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48 changes: 29 additions & 19 deletions code/test-code/heat-prep.R
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Original file line number Diff line number Diff line change
Expand Up @@ -253,7 +253,7 @@ HEATbind_aml_PPP = HEATbind
## For Intermodality ---------------------------------------------------------------------------
# RUN THIS AGAIN WHEN API GETS LIVE

Code_Hass = CENARIOS$Code[9:12] #fazer por enquanto só AML e senários 3
Code_Hass = CENARIOS$Code[9:12] #só AML e cenários 3

HEATbind_intermodal_correct = HEAT

Expand Down Expand Up @@ -321,17 +321,21 @@ for (i in Code_Hass){

#car dist is about 20% more than cycling


tripspersondayAML = 2.60
# tripspersondayAML = 0.5 # teste
# webapp_input[["crashdata_used_fatality_rate_bike_ref"]] = 0.5
# webapp_input[["crashdata_used_fatality_rate_bike_cf"]] = 0.5

# HAAS
# # for MER VSL value
# webapp_input = readRDS(url("https://web.tecnico.ulisboa.pt/~rosamfelix/heat/1304_webapp_input.rds"))
# genericdata = readRDS(url("https://web.tecnico.ulisboa.pt/~rosamfelix/heat/1304_generic_data_relevant_with_calc_params.rds"))

# for PPP VSL value
webapp_input = readRDS(url("https://web.tecnico.ulisboa.pt/~rosamfelix/heat/162410_webapp_input.rds"))
genericdata = readRDS(url("https://web.tecnico.ulisboa.pt/~rosamfelix/heat/162410_generic_data_relevant_with_calc_params.rds"))

# webapp_input = readRDS(url("https://web.tecnico.ulisboa.pt/~rosamfelix/heat/162410_webapp_input.rds"))
# genericdata = readRDS(url("https://web.tecnico.ulisboa.pt/~rosamfelix/heat/162410_generic_data_relevant_with_calc_params.rds"))
webapp_input = readRDS(url("https://web.tecnico.ulisboa.pt/~rosamfelix/heat/2023_52_1304_webapp_input.rds"))
genericdata = readRDS(url("https://web.tecnico.ulisboa.pt/~rosamfelix/heat/2023_52_1304_generic_data_relevant_with_calc_params.rds"))


# Assessment intro
Expand All @@ -344,13 +348,14 @@ for (i in Code_Hass){
# webapp_input[["ucc_assessmenttime"]] = 10 # over how many years should the impacts be calculated
# webapp_input[["ucc_pathway"]] = c("pa", "ap", "crash", "carbon") # which impact to be considered?
webapp_input[["ucc_motormodebasic"]] = "car" # modes to be considered. opt in basic categories: c("car", "pt")
# webapp_input[["ucc_trafficcondition"]] = "euromeancongestionurban" # alternatives: "somecongestion", "heavycongestion", "euromeancongestionrural"
## webapp_input[["ucc_trafficcondition"]] = "euromeancongestionurban" # alternatives: "somecongestion", "heavycongestion", "euromeancongestionrural" # já não existe na v5.2

# Active modes data (ref = Reference, cf = Comparison)
# webapp_input[["raw_activemode_bike_ref_source"]] = "model" # alternatives: "scenario" (Hypotetical scenario), "popsurvey" (Population survey), "intercept" (Intercept survey), "counts" (Count data), "model" (Modeled Data), "app" (App-based data)
# webapp_input[["raw_activemode_bike_ref_unit"]] = "modeshare" # alternatives: "min" (Minutes), "hrs" (Hours), "km" (Km), "trips" (Trips), "modeshare" (Mode Share) # other options to select after may show up, depending on the data source
webapp_input[["raw_activemode_bike_ref_modesharepercent"]] = HEAT$Bike_per # percentage of CYCLING trips in the reference scenario
webapp_input[["raw_activemode_bike_ref_alltrips"]] = HEAT$Total # total travel volume of ALL MODES in the reference scenario
# webapp_input[["raw_activemode_bike_ref_alltrips"]] = HEAT$Total # total travel volume of ALL MODES in the reference scenario
webapp_input[["raw_activemode_bike_ref_alltrips"]] = tripspersondayAML # they say is number of trips per person per day
# webapp_input[["raw_activemode_bike_ref_alltripsunit"]] = "trips" # unit of the travel volume. alternatives: "duration" (in minutes), "distance" (in km)
webapp_input[["raw_activemode_bike_ref_tripkm"]] = HEAT$Dist_bike # average length of CYCLING trips for reference scenario
# webapp_input[["raw_activemode_bike_ref_denominator"]] = "person" # type of population the volume data is based on. alternative depending on previous selection:
Expand All @@ -359,7 +364,8 @@ for (i in Code_Hass){
# webapp_input[["raw_activemode_bike_cf_source"]] = "model" # alternatives: "scenario" (Hypotetical scenario), "popsurvey" (Population survey), "intercept" (Intercept survey), "counts" (Count data), "model" (Modeled Data), "app" (App-based data)
# webapp_input[["raw_activemode_bike_cf_unit"]] = "modeshare" # alternatives: "min" (Minutes), "hrs" (Hours), "km" (Km), "trips" (Trips), "modeshare" (Mode Share) # other options to select after may show up, depending on the data source
webapp_input[["raw_activemode_bike_cf_modesharepercent"]] = HEAT$Bike_per_new # percentage of CYCLING trips in the comparison scenario
webapp_input[["raw_activemode_bike_cf_alltrips"]] = HEAT$Total # total travel volume of ALL MODES in the comparison scenario
# webapp_input[["raw_activemode_bike_cf_alltrips"]] = HEAT$Total # total travel volume of ALL MODES in the comparison scenario
webapp_input[["raw_activemode_bike_cf_alltrips"]] = tripspersondayAML # they say is number of trips per person per day
# webapp_input[["raw_activemode_bike_cf_alltripsunit"]] = "trips" # unit of the travel volume. alternatives: "duration" (in minutes), "distance" (in km)
webapp_input[["raw_activemode_bike_cf_tripkm"]] = HEAT$Dist_bike_new # average length of CYCLING trips, for comparison scenario
# webapp_input[["raw_activemode_bike_cf_denominator"]] = "person" # type of population the volume data is based on. alternative depending on previous selection:
Expand All @@ -368,13 +374,15 @@ for (i in Code_Hass){
# Motorized modes data (car, tp // ref, cf)
# webapp_input[["raw_motorizedmode_car_ref_unit"]] = "modeshare" # alternatives: "min" (Minutes), "hrs" (Hours), "km" (Km), "trips" (Trips), "modeshare" (Mode Share) # other options to select after may show up, depending on the data source
webapp_input[["raw_motorizedmode_car_ref_modesharepercent"]] = HEAT$Car_per # percentage of CAR trips in the reference scenario
webapp_input[["raw_motorizedmode_car_ref_alltrips"]] = HEAT$Total # total travel volume of ALL MODES in the reference scenario
# webapp_input[["raw_motorizedmode_car_ref_alltrips"]] = HEAT$Total # total travel volume of ALL MODES in the reference scenario
webapp_input[["raw_motorizedmode_car_ref_alltrips"]] = tripspersondayAML # they say is number of trips per person per day
# webapp_input[["raw_motorizedmode_car_ref_alltripsunit"]] = "trips" # unit of the travel volume. alternatives: "duration" (in minutes), "distance" (in km)
webapp_input[["raw_motorizedmode_car_ref_tripkm"]] = HEAT$Dist_car # average length of CAR trips for reference scenario

# webapp_input[["raw_motorizedmode_car_cf_unit"]] = "modeshare" # alternatives: "min" (Minutes), "hrs" (Hours), "km" (Km), "trips" (Trips), "modeshare" (Mode Share) # other options to select after may show up, depending on the data source
webapp_input[["raw_motorizedmode_car_cf_modesharepercent"]] = HEAT$Car_per_new # percentage of CAR trips in the comparison scenario
webapp_input[["raw_motorizedmode_car_cf_alltrips"]] = HEAT$Total # total travel volume of ALL MODES in the comparison scenario
webapp_input[["raw_motorizedmode_car_cf_alltrips"]] = tripspersondayAML # they say is number of trips per person per day
# webapp_input[["raw_motorizedmode_car_cf_alltripsunit"]] = "trips" # unit of the travel volume. alternatives: "duration" (in minutes), "distance" (in km)
webapp_input[["raw_motorizedmode_car_cf_tripkm"]] = HEAT$Dist_car_new # average length of CAR trips, for comparison scenario

Expand Down Expand Up @@ -427,15 +435,17 @@ for (i in Code_Hass){
from_hass <- unserialize(httr::content(resp, "raw"))

# Check final result value
from_hass$results$moneyperyear = as.numeric(gsub(" ","",from_hass$results$moneyperyear))
from_hass$results$moneytotaldisc = as.numeric(gsub(" ","",from_hass$results$moneytotaldisc))

HEAT = HEAT %>% mutate(Mortality = from_hass$results$impactperyearave[30],
Mortality10 = from_hass$results$impacttotal[30],
CO2eq = from_hass$results$impactperyearaveco2[30],
CO2eq10 = from_hass$results$impacttotalco2[30],
Economic = from_hass$results$moneyperyear[26]-from_hass$results$moneyperyear[27]-from_hass$results$moneyperyear[28]+from_hass$results$moneyperyear[29],
Economic10 = from_hass$results$moneytotaldisc[26]-from_hass$results$moneytotaldisc[27]-from_hass$results$moneytotaldisc[28]+from_hass$results$moneytotaldisc[29]) %>%
# from_hass$results$moneyperyear = as.numeric(gsub(" ","",from_hass$results$moneyperyear)) #not necessary anymore
# from_hass$results$moneytotaldisc = as.numeric(gsub(" ","",from_hass$results$moneytotaldisc))

HEAT = HEAT %>% mutate(Mortality = from_hass$results$impactperyearave[40], #total
Mortality10 = from_hass$results$impacttotal[40], #total
CO2eq = from_hass$results$impactperyearaveco2[40], #total
CO2eq10 = from_hass$results$impacttotalco2[40], #total
Economic = from_hass$results$moneyperyear[36]+from_hass$results$moneyperyear[37]+from_hass$results$moneyperyear[38]+from_hass$results$moneyperyear[39],
Economic10 = from_hass$results$moneytotaldisc[36]+from_hass$results$moneytotaldisc[37]+from_hass$results$moneytotaldisc[38]+from_hass$results$moneytotaldisc[39],
Environmenal_only = from_hass$results$moneyperyear[39], # only the environmental impacts
Environmenal_only = from_hass$results$moneytotaldisc[39]) %>%
mutate(value_newcyc = round(Economic10/Bike_new),
value_newcyc_eur = round(Economic10/Bike_new*usd_to_eur))

Expand All @@ -449,4 +459,4 @@ for (i in Code_Hass){

# HEATbind_intermodal_correct = HEATbind_intermodal_correct[-1,]
# HEATbind_intermodal_correct_PPP = HEATbind_intermodal_correct
saveRDS(HEATbind_intermodal_correct_PPP, "HEAT/HEAT_AML_intermodal_ppp.Rds")
saveRDS(HEATbind_intermodal_correct, "HEAT/HEAT_AML_intermodal_ppp_NEW.Rds")
23 changes: 23 additions & 0 deletions code/test-code/heat-reprex.R
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Original file line number Diff line number Diff line change
@@ -0,0 +1,23 @@
# Heat reprex

# read RDS exported from UI - NEW VERSION
webapp_input = readRDS(url("https://web.tecnico.ulisboa.pt/~rosamfelix/heat/2023b_webapp_input.rds"))
genericdata = readRDS(url("https://web.tecnico.ulisboa.pt/~rosamfelix/heat/2023b_generic_data_relevant_with_calc_params.rds"))

# to get data prepared by "calc_results"
# input data as "json", two inputs - "generic_data_relevant" from previous step
# returned data as "rds"
resp <-
httr::POST("https://api.heatwalkingcycling.org/apiv1/heat_5_0/calc_results?output_format=rds",
httr::set_cookies("user" = Sys.getenv("HEAT_COOKIE")),
body = jsonlite::toJSON(
list("webapp_input" = webapp_input,
"generic_data_relevant" = genericdata)),
encode = "multipart")

# convert to R
from_rds_reprex <- unserialize(httr::content(resp, "raw"))

# Check final result value
from_rds_reprex$results$impactperyearave[40] #mortality per year - should be 119 preventive deaths
from_rds_reprex$results$moneytotaldisc[36]+from_rds_reprex$results$moneytotaldisc[37]+from_rds_reprex$results$moneytotaldisc[38]+from_rds_reprex$results$moneytotaldisc[39]

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