Open Goldfish63 opened 2 weeks ago
Hello GCAM team, I am new to gcam learning.
While I was running driver_drake(), this error message came out. It seems that it was a bug in module_energy_LA125.hydrogen, right? Really appreciate any help. I have been stuck here for a while.
BTW, I ran the gcam 7.0 on github desktop with https://github.com/JGCRI/gcamdata.git. Thank you!!
Error: target module_energy_LA125.hydrogen failed. diagnose(module_energy_LA125.hydrogen)$error$message: 'arg' should be one of “down”, “up” diagnose(module_energy_LA125.hydrogen)$error$calls: gcamdata:::module_energy_LA125.hydrogen("MAKE", c(energy.H2A_IO_coef_data, energy.H2A_NE_cost_data, energy.H2A_electrolyzer_NEcost_CF, L223.GlobalTechCapital_elec, L223.GlobalTechEff_elec)) coal_chem_costs_scaled %>% complete(nesting(sector.name, subsector.name, technology, minicam.non.energy.input), year = sort(unique(c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)))) %>% arrange(sector.name, subsector.name, technology, minicam.non.energy.input, year) %>% group_by(sector.name, subsector.name, technology, minicam.non.energy.input) %>% mutate(improvement_rate = (1 - improvement_to_2040[year == 2015])^(1/(2040 - 2015)) - 1, min_cost = value[year == 2015] * (1 - max_improvement[year == 2015]), cost = if_else(year <= 2015, val
Hello GCAM team, I am new to gcam learning.
While I was running driver_drake(), this error message came out. It seems that it was a bug in module_energy_LA125.hydrogen, right? Really appreciate any help. I have been stuck here for a while.
BTW, I ran the gcam 7.0 on github desktop with https://github.com/JGCRI/gcamdata.git. Thank you!!
Error: target module_energy_LA125.hydrogen failed. diagnose(module_energy_LA125.hydrogen)$error$message: 'arg' should be one of “down”, “up” diagnose(module_energy_LA125.hydrogen)$error$calls: gcamdata:::module_energy_LA125.hydrogen("MAKE", c(energy.H2A_IO_coef_data, energy.H2A_NE_cost_data, energy.H2A_electrolyzer_NEcost_CF, L223.GlobalTechCapital_elec, L223.GlobalTechEff_elec)) coal_chem_costs_scaled %>% complete(nesting(sector.name, subsector.name, technology, minicam.non.energy.input), year = sort(unique(c(year, MODEL_BASE_YEARS, MODEL_FUTURE_YEARS)))) %>% arrange(sector.name, subsector.name, technology, minicam.non.energy.input, year) %>% group_by(sector.name, subsector.name, technology, minicam.non.energy.input) %>% mutate(improvement_rate = (1 - improvement_to_2040[year == 2015])^(1/(2040 - 2015)) - 1, min_cost = value[year == 2015] * (1 - max_improvement[year == 2015]), cost = if_else(year <= 2015, val