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Remove technology_type column from tools.costs #269

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merged 4 commits into from
Dec 16, 2024
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Remove technology_type column from tools.costs #269

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cf509f6
Remove `technology_type` column from input CSV files
measrainsey Dec 12, 2024
d61e2ec
Remove instances in code that used `technology_type` column
measrainsey Dec 12, 2024
1b61d33
Add #269 to doc/whatsnew
measrainsey Dec 12, 2024
59c4ace
Replace `._append()` with `pd.concat()`
measrainsey Dec 12, 2024
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1 change: 1 addition & 0 deletions doc/whatsnew.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -64,6 +64,7 @@ Investment and fixed costs
- Add `cooling` technology variant/module (:pull:`222`).
- Add functionality to specify cost reduction values and cost reduction scenarios in a module (:issue:`251`, :pull:`255`).
- Fix technology mapping of ammonia CCS technologies in materials module (:pull:`258`).
- Remove unused `technology_type` column from tool (:pull:`269`).

Others
------
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192 changes: 96 additions & 96 deletions message_ix_models/data/costs/energy/cost_reduction.csv
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Original file line number Diff line number Diff line change
@@ -1,96 +1,96 @@
# Cost reduction in 2100,,,,,,
# ,,,,,,
# Units: % ,,,,,,
#,,,,,,
# Data is copied from Sheet1 in https://github.com/iiasa/message_data/blob/dev/data/model/investment_cost/SSP_technology_learning.xlsx,,,,,,
# There are some manually changed assumptions to the original GEA data in the spreadsheet (can be seen in the spreadsheet as marked in yellow),,,,,,
# The initial copied data can be found in gea_reduction_rates.csv,,,,,,
# This file renames the learning rates from GEAL to low and GEAM to medium and GEAH to high,,,,,,
message_technology,technology_type,very_low,low,medium,high,very_high
bio_istig,Biomass,0,0.1,0.3,0.4,0.5
bio_istig_ccs,CCS,0,0.1,0.3,0.4,0.6
bio_ppl,Biomass,0,0.1,0.2,0.3,0.4
bio_ppl_co2scr,CCS,0,0,0,0.3,0.4
biomass_i,Biomass,0,0,0,0,0
c_ppl_co2scr,CCS,0,0,0,0.3,0.4
coal_adv,Coal,0,0.1,0.3,0.5,0.7
coal_adv_ccs,CCS,0,0.1,0.3,0.5,0.7
coal_i,Coal,0,0,0,0,0
coal_ppl,Coal,0,0,0.2,0.5,0.7
coal_ppl_u,Coal,0,0,0,0,0
csp_sm1_ppl,Renewable,0.15,0.3,0.3,0.5,0.7
csp_sm3_ppl,Renewable,0.15,0.3,0.3,0.5,0.7
elec_i,NA,0,0,0,0,0
eth_bio,Biomass,0,0.27,0.27,0.4,0.55
eth_bio_ccs,CCS,0,0.27,0.27,0.4,0.55
eth_i,Biomass,0,0,0,0,0
foil_i,Gas/Oil,0,0,0,0,0
g_ppl_co2scr,CCS,0,0,0,0.3,0.4
gas_cc,Gas/Oil,0.1,0.2,0.29,0.38,0.5
gas_cc_ccs,CCS,0.1,0.2,0.29,0.5,0.7
gas_ct,Gas/Oil,0.1,0.2,0.29,0.38,0.5
gas_i,Gas/Oil,0,0,0,0,0
gas_ppl,Gas/Oil,0.1,0.2,0.29,0.38,0.5
geo_hpl,Renewable,0.1,0.15,0.18,0.25,0.35
geo_ppl,Renewable,0,0.1,0.18,0.25,0.35
h2_bio,Biomass,0,0.25,0.4,0.5,0.7
h2_bio_ccs,CCS,0,0.25,0.4,0.5,0.7
h2_coal,Coal,0,0.25,0.4,0.4,0.5
h2_coal_ccs,CCS,0,0.25,0.4,0.4,0.5
h2_elec,Renewable,0,0,0.1,0.2,0.3
h2_i,NA,0,0,0,0,0
h2_smr,Gas/Oil,0,0.25,0.4,0.5,0.7
h2_smr_ccs,CCS,0,0.25,0.4,0.5,0.7
heat_i,NA,0,0,0,0,0
hp_el_i,Renewable,0.1,0.2,0.5,0.5,0.6
hp_gas_i,Gas/Oil,0.1,0.2,0.4,0.4,0.5
hydro_hc,Renewable,0,0,0,0,0
hydro_lc,Renewable,0,0,0,0,0
igcc,Coal,0,0.1,0.3,0.5,0.7
igcc_ccs,CCS,0,0.1,0.3,0.5,0.7
liq_bio,Biomass,0.15,0.27,0.27,0.4,0.55
liq_bio_ccs,CCS,0.15,0.27,0.27,0.4,0.55
loil_i,Gas/Oil,0,0,0,0,0
meth_coal,Coal,0,0.05,0.1,0.15,0.2
meth_coal_ccs,CCS,0,0.05,0.1,0.15,0.2
meth_i,Coal,0,0,0,0,0
meth_ng,Gas/Oil,0,0.05,0.1,0.15,0.2
meth_ng_ccs,CCS,0,0.05,0.1,0.15,0.2
nuc_hc,Nuclear,0,0,0.15,0.3,0.45
nuc_lc,Nuclear,0,0,0,0,0
solar_i,Renewable,0.1,0.2,0.6,0.9,0.95
solar_pv_I,Renewable,0.15,0.3,0.7,0.9,0.95
solar_pv_RC,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res_hist_2005,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res_hist_2010,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res_hist_2015,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res_hist_2020,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res1,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res2,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res3,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res4,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res5,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res6,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res7,Renewable,0.15,0.3,0.7,0.9,0.95
solar_res8,Renewable,0.15,0.3,0.7,0.9,0.95
solar_th_ppl,Renewable,0.15,0.3,0.3,0.5,0.7
stor_ppl,Renewable,0.15,0.3,0.7,0.9,0.95
syn_liq,Coal,0,0.05,0.1,0.15,0.2
syn_liq_ccs,CCS,0,0.05,0.1,0.15,0.2
wind_ref_hist_2005,Renewable,0.15,0.3,0.53,0.65,0.75
wind_ref_hist_2010,Renewable,0.15,0.3,0.53,0.65,0.75
wind_ref_hist_2015,Renewable,0.15,0.3,0.53,0.65,0.75
wind_ref_hist_2020,Renewable,0.15,0.3,0.53,0.65,0.75
wind_ref1,Renewable,0.15,0.3,0.53,0.65,0.75
wind_ref2,Renewable,0.15,0.3,0.53,0.65,0.75
wind_ref3,Renewable,0.15,0.3,0.53,0.65,0.75
wind_ref4,Renewable,0.15,0.3,0.53,0.65,0.75
wind_ref5,Renewable,0.15,0.3,0.53,0.65,0.75
wind_res_hist_2005,Renewable,0.15,0.3,0.53,0.65,0.75
wind_res_hist_2010,Renewable,0.15,0.3,0.53,0.65,0.75
wind_res_hist_2015,Renewable,0.15,0.3,0.53,0.65,0.75
wind_res_hist_2020,Renewable,0.15,0.3,0.53,0.65,0.75
wind_res1,Renewable,0.15,0.3,0.53,0.65,0.75
wind_res2,Renewable,0.15,0.3,0.53,0.65,0.75
wind_res3,Renewable,0.15,0.3,0.53,0.65,0.75
wind_res4,Renewable,0.15,0.3,0.53,0.65,0.75
# Cost reduction in 2100,,,,,
# ,,,,,
# Units: % ,,,,,
#,,,,,
# Data is copied from Sheet1 in https://github.com/iiasa/message_data/blob/dev/data/model/investment_cost/SSP_technology_learning.xlsx,,,,,
# There are some manually changed assumptions to the original GEA data in the spreadsheet (can be seen in the spreadsheet as marked in yellow),,,,,
# The initial copied data can be found in gea_reduction_rates.csv,,,,,
# This file renames the learning rates from GEAL to low and GEAM to medium and GEAH to high,,,,,
message_technology,very_low,low,medium,high,very_high
bio_istig,0,0.1,0.3,0.4,0.5
bio_istig_ccs,0,0.1,0.3,0.4,0.6
bio_ppl,0,0.1,0.2,0.3,0.4
bio_ppl_co2scr,0,0,0,0.3,0.4
biomass_i,0,0,0,0,0
c_ppl_co2scr,0,0,0,0.3,0.4
coal_adv,0,0.1,0.3,0.5,0.7
coal_adv_ccs,0,0.1,0.3,0.5,0.7
coal_i,0,0,0,0,0
coal_ppl,0,0,0.2,0.5,0.7
coal_ppl_u,0,0,0,0,0
csp_sm1_ppl,0.15,0.3,0.3,0.5,0.7
csp_sm3_ppl,0.15,0.3,0.3,0.5,0.7
elec_i,0,0,0,0,0
eth_bio,0,0.27,0.27,0.4,0.55
eth_bio_ccs,0,0.27,0.27,0.4,0.55
eth_i,0,0,0,0,0
foil_i,0,0,0,0,0
g_ppl_co2scr,0,0,0,0.3,0.4
gas_cc,0.1,0.2,0.29,0.38,0.5
gas_cc_ccs,0.1,0.2,0.29,0.5,0.7
gas_ct,0.1,0.2,0.29,0.38,0.5
gas_i,0,0,0,0,0
gas_ppl,0.1,0.2,0.29,0.38,0.5
geo_hpl,0.1,0.15,0.18,0.25,0.35
geo_ppl,0,0.1,0.18,0.25,0.35
h2_bio,0,0.25,0.4,0.5,0.7
h2_bio_ccs,0,0.25,0.4,0.5,0.7
h2_coal,0,0.25,0.4,0.4,0.5
h2_coal_ccs,0,0.25,0.4,0.4,0.5
h2_elec,0,0,0.1,0.2,0.3
h2_i,0,0,0,0,0
h2_smr,0,0.25,0.4,0.5,0.7
h2_smr_ccs,0,0.25,0.4,0.5,0.7
heat_i,0,0,0,0,0
hp_el_i,0.1,0.2,0.5,0.5,0.6
hp_gas_i,0.1,0.2,0.4,0.4,0.5
hydro_hc,0,0,0,0,0
hydro_lc,0,0,0,0,0
igcc,0,0.1,0.3,0.5,0.7
igcc_ccs,0,0.1,0.3,0.5,0.7
liq_bio,0.15,0.27,0.27,0.4,0.55
liq_bio_ccs,0.15,0.27,0.27,0.4,0.55
loil_i,0,0,0,0,0
meth_coal,0,0.05,0.1,0.15,0.2
meth_coal_ccs,0,0.05,0.1,0.15,0.2
meth_i,0,0,0,0,0
meth_ng,0,0.05,0.1,0.15,0.2
meth_ng_ccs,0,0.05,0.1,0.15,0.2
nuc_hc,0,0,0.15,0.3,0.45
nuc_lc,0,0,0,0,0
solar_i,0.1,0.2,0.6,0.9,0.95
solar_pv_I,0.15,0.3,0.7,0.9,0.95
solar_pv_RC,0.15,0.3,0.7,0.9,0.95
solar_res_hist_2005,0.15,0.3,0.7,0.9,0.95
solar_res_hist_2010,0.15,0.3,0.7,0.9,0.95
solar_res_hist_2015,0.15,0.3,0.7,0.9,0.95
solar_res_hist_2020,0.15,0.3,0.7,0.9,0.95
solar_res1,0.15,0.3,0.7,0.9,0.95
solar_res2,0.15,0.3,0.7,0.9,0.95
solar_res3,0.15,0.3,0.7,0.9,0.95
solar_res4,0.15,0.3,0.7,0.9,0.95
solar_res5,0.15,0.3,0.7,0.9,0.95
solar_res6,0.15,0.3,0.7,0.9,0.95
solar_res7,0.15,0.3,0.7,0.9,0.95
solar_res8,0.15,0.3,0.7,0.9,0.95
solar_th_ppl,0.15,0.3,0.3,0.5,0.7
stor_ppl,0.15,0.3,0.7,0.9,0.95
syn_liq,0,0.05,0.1,0.15,0.2
syn_liq_ccs,0,0.05,0.1,0.15,0.2
wind_ref_hist_2005,0.15,0.3,0.53,0.65,0.75
wind_ref_hist_2010,0.15,0.3,0.53,0.65,0.75
wind_ref_hist_2015,0.15,0.3,0.53,0.65,0.75
wind_ref_hist_2020,0.15,0.3,0.53,0.65,0.75
wind_ref1,0.15,0.3,0.53,0.65,0.75
wind_ref2,0.15,0.3,0.53,0.65,0.75
wind_ref3,0.15,0.3,0.53,0.65,0.75
wind_ref4,0.15,0.3,0.53,0.65,0.75
wind_ref5,0.15,0.3,0.53,0.65,0.75
wind_res_hist_2005,0.15,0.3,0.53,0.65,0.75
wind_res_hist_2010,0.15,0.3,0.53,0.65,0.75
wind_res_hist_2015,0.15,0.3,0.53,0.65,0.75
wind_res_hist_2020,0.15,0.3,0.53,0.65,0.75
wind_res1,0.15,0.3,0.53,0.65,0.75
wind_res2,0.15,0.3,0.53,0.65,0.75
wind_res3,0.15,0.3,0.53,0.65,0.75
wind_res4,0.15,0.3,0.53,0.65,0.75
8 changes: 4 additions & 4 deletions message_ix_models/data/costs/materials/cost_reduction.csv
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# Cost reduction in 2100,,,,,,
# ,,,,,,
# Units: % ,,,,,,
message_technology,technology_type,very_low,low,medium,high,very_high
# Cost reduction in 2100,,,,,
# ,,,,,
# Units: % ,,,,,
message_technology,very_low,low,medium,high,very_high
7 changes: 2 additions & 5 deletions message_ix_models/tools/costs/decay.py
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Expand Up @@ -207,7 +207,6 @@ def _get_module_cost_reduction(
pd.concat([reduction_energy, reduction_energy_no_reduction], ignore_index=True)
.sort_values("message_technology")
.reset_index(drop=True)
.drop(columns=["technology_type"])
)

if module != "energy":
Expand All @@ -225,10 +224,8 @@ def _get_module_cost_reduction(
]

# append scen_red_module to scen_red_energy
reduction_joined = (
reduction_energy._append(reduction_module)
.reset_index(drop=True)
.drop(columns=["technology_type"])
reduction_joined = reduction_energy._append(reduction_module).reset_index(
drop=True
)
else:
reduction_joined = reduction_energy.copy()
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In such cases, I prefer this kind of syntax:

reduction_joined = reduction_energy.copy() if module == "energy" else reduction_energy._append(reduction_module).reset_index(drop=True)

I think this is an improvement as it reduces the number of lines requiring tests and more clearly states that all you do is define reduction_joined, just slightly differently.

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Sorry, but what is ._append() here? I thought pandas deprecated and removed methods like DataFrame.append() in v2.0 (2023), and I don't see this one in the documentation.

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ah interesting - it seems that function may be a "private" function that isn't supported by pandas 🙈 i'll push a commit to switch to using concat or something else like that!

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thanks @glatterf42 for the suggestion!

the if...else statement is actually not on module == "energy" but on if os.path.exists(ffile). if the file exists, then the code reads in the file as a dataframe, deletes some rows in another dataframe, and then concats the two dataframes together as the output. if the file doesn't exist, then the output is just the second dataframe copied over. i thought about condensing the code like you suggested but seems like the if part requires a few more steps? 😅

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Oh, sorry, I misunderstood what was going on. I guess its technically possible to still make this one line, but I don't know if it will be easier to read. Up to you if you want to try this :)

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if it's alright, i would prefer to skip editing this part for this PR and move forward with approving/merging -- thank you! :)

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