Fix/greedy time impute refactoring

config/config.yaml

@@ -118,7 +118,7 @@ imputation:
       utility pv: "land"
   time:
     scenario: "construction" # Options: historical->construction->pre_construction->announced
-    start_year_imputation_method: capacity_profile
+    method: capacity_profile
     lifetime_years:
       # General lifetime assumptions. Adjust as needed!
       bioenergy turbine: 25

workflow/envs/module.linux-64.pin.txt

@@ -47,13 +47,11 @@ https://conda.anaconda.org/conda-forge/linux-64/pydantic-core-2.46.4-py312h868fb
 https://conda.anaconda.org/conda-forge/noarch/annotated-types-0.7.0-pyhd8ed1ab_1.conda#2934f256a8acfe48f6ebb4fce6cde29c
 https://conda.anaconda.org/conda-forge/noarch/pydantic-2.13.4-pyhcf101f3_0.conda#729843edafc0899b3348bd3f19525b9d
 https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda#4c06a92e74452cfa53623a81592e8934
-https://conda.anaconda.org/conda-forge/noarch/pandera-base-0.24.0-pyhd8ed1ab_2.conda#e1c50e117a98e39d297d9290132f032b
-https://conda.anaconda.org/conda-forge/noarch/pytz-2026.2-pyhcf101f3_0.conda#03cb60f505ad3ada0a95277af5faeb1a
-https://conda.anaconda.org/conda-forge/noarch/python-tzdata-2026.2-pyhd8ed1ab_0.conda#f6ad7450fc21e00ecc23812baed6d2e4
+https://conda.anaconda.org/conda-forge/noarch/pandera-base-0.32.1-pyhcf101f3_0.conda#c78daae943cb94e6e6b2eab16e16a18f
 https://conda.anaconda.org/conda-forge/noarch/six-1.17.0-pyhe01879c_1.conda#3339e3b65d58accf4ca4fb8748ab16b3
 https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.9.0.post0-pyhe01879c_2.conda#5b8d21249ff20967101ffa321cab24e8
-https://conda.anaconda.org/conda-forge/linux-64/pandas-2.3.0-py312hf9745cd_0.conda#ac82ac336dbe61106e21fb2e11704459
-https://conda.anaconda.org/conda-forge/noarch/pandera-0.24.0-hd8ed1ab_2.conda#a12a21a89519f0cc224e44da86f5be2c
+https://conda.anaconda.org/conda-forge/linux-64/pandas-3.0.5-py312h8ecdadd_1.conda#85eb29ade84d1bd97be5ec55607efb00
+https://conda.anaconda.org/conda-forge/noarch/pandera-0.32.1-ha00cc4c_0.conda#f6b96a51cda3cf9a068fd748c8155ced
 https://conda.anaconda.org/conda-forge/noarch/xyzservices-2026.3.0-pyhd8ed1ab_0.conda#4487b9c371d0161d54b5c7bbd890c0fc
 https://conda.anaconda.org/conda-forge/linux-64/sqlite-3.53.3-hbc0de68_0.conda#b345ea7f13e4cae9809c69b1d1af2c99
 https://conda.anaconda.org/conda-forge/linux-64/libwebp-base-1.6.0-hd42ef1d_0.conda#aea31d2e5b1091feca96fcfe945c3cf9
@@ -131,7 +129,7 @@ https://conda.anaconda.org/conda-forge/noarch/joblib-1.5.3-pyhd8ed1ab_0.conda#61
 https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.9.0-np2py312h3226591_0.conda#e6e9b5795bb495325c3b4ebd451519aa
 https://conda.anaconda.org/conda-forge/noarch/networkx-3.6.1-pyhcf101f3_0.conda#a2c1eeadae7a309daed9d62c96012a2b
 https://conda.anaconda.org/conda-forge/noarch/mapclassify-2.10.0-pyhd8ed1ab_1.conda#cc293b4cad9909bf66ca117ea90d4631
-https://conda.anaconda.org/conda-forge/noarch/geopandas-base-1.0.1-pyha770c72_3.conda#e8343d1b635bf09dafdd362d7357f395
+https://conda.anaconda.org/conda-forge/noarch/geopandas-base-1.1.4-pyha770c72_0.conda#6e31007c02f361338281bb78c5b84e7c
 https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha55dd90_7.conda#461219d1a5bd61342293efa2c0c90eac
 https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.1.0-pyhd8ed1ab_0.conda#8e6923fc12f1fe8f8c4e5c9f343256ac
 https://conda.anaconda.org/conda-forge/noarch/hpack-4.2.0-pyhd8ed1ab_0.conda#b395909221b9bd1df066e5930e18855b
@@ -146,8 +144,8 @@ https://conda.anaconda.org/conda-forge/linux-64/markupsafe-3.0.3-py312h8a5da7c_1
 https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.6-pyhcf101f3_1.conda#04558c96691bed63104678757beb4f8d
 https://conda.anaconda.org/conda-forge/noarch/branca-0.8.2-pyhd8ed1ab_0.conda#1fcdf88e7a8c296d3df8409bf0690db4
 https://conda.anaconda.org/conda-forge/noarch/folium-0.20.0-pyhd8ed1ab_0.conda#a6997a7dcd6673c0692c61dfeaea14ab
-https://conda.anaconda.org/conda-forge/noarch/geopandas-1.0.1-pyhd8ed1ab_3.conda#1baca589eb35814a392eaad6d152447e
-https://conda.anaconda.org/conda-forge/noarch/pandera-geopandas-0.24.0-hd8ed1ab_2.conda#fb21509f073465506ea994dc4667bf66
+https://conda.anaconda.org/conda-forge/noarch/geopandas-1.1.4-pyhd8ed1ab_0.conda#99d77e0f92f7b0b977f77cfb49c7eaf6
+https://conda.anaconda.org/conda-forge/noarch/pandera-geopandas-0.32.1-h9ad522b_0.conda#b6b27c3f219ce4d01c8ea31d435f263c
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 https://conda.anaconda.org/conda-forge/linux-64/openpyxl-3.1.5-py312h7f6eeab_3.conda#04ab345ef65b88bcbb8ac3d083427bfc
 https://conda.anaconda.org/conda-forge/linux-64/tornado-6.5.7-py312h4c3975b_0.conda#55f526c3fb5302a1ce922612348442e1

workflow/envs/module.osx-arm64.pin.txt

@@ -41,13 +41,11 @@ https://conda.anaconda.org/conda-forge/osx-arm64/pydantic-core-2.46.4-py312hb9d4
 https://conda.anaconda.org/conda-forge/noarch/annotated-types-0.7.0-pyhd8ed1ab_1.conda#2934f256a8acfe48f6ebb4fce6cde29c
 https://conda.anaconda.org/conda-forge/noarch/pydantic-2.13.4-pyhcf101f3_0.conda#729843edafc0899b3348bd3f19525b9d
 https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda#4c06a92e74452cfa53623a81592e8934
-https://conda.anaconda.org/conda-forge/noarch/pandera-base-0.24.0-pyhd8ed1ab_2.conda#e1c50e117a98e39d297d9290132f032b
-https://conda.anaconda.org/conda-forge/noarch/pytz-2026.2-pyhcf101f3_0.conda#03cb60f505ad3ada0a95277af5faeb1a
-https://conda.anaconda.org/conda-forge/noarch/python-tzdata-2026.2-pyhd8ed1ab_0.conda#f6ad7450fc21e00ecc23812baed6d2e4
+https://conda.anaconda.org/conda-forge/noarch/pandera-base-0.32.1-pyhcf101f3_0.conda#c78daae943cb94e6e6b2eab16e16a18f
 https://conda.anaconda.org/conda-forge/noarch/six-1.17.0-pyhe01879c_1.conda#3339e3b65d58accf4ca4fb8748ab16b3
 https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.9.0.post0-pyhe01879c_2.conda#5b8d21249ff20967101ffa321cab24e8
-https://conda.anaconda.org/conda-forge/osx-arm64/pandas-2.3.0-py312hcb1e3ce_0.conda#d95b29a40430115d6aa817f70be5b5b1
-https://conda.anaconda.org/conda-forge/noarch/pandera-0.24.0-hd8ed1ab_2.conda#a12a21a89519f0cc224e44da86f5be2c
+https://conda.anaconda.org/conda-forge/osx-arm64/pandas-3.0.5-py312h6510ced_1.conda#49c93ebce99da3235ba5bd1a24f7153a
+https://conda.anaconda.org/conda-forge/noarch/pandera-0.32.1-ha00cc4c_0.conda#f6b96a51cda3cf9a068fd748c8155ced
 https://conda.anaconda.org/conda-forge/noarch/xyzservices-2026.3.0-pyhd8ed1ab_0.conda#4487b9c371d0161d54b5c7bbd890c0fc
 https://conda.anaconda.org/conda-forge/osx-arm64/sqlite-3.53.3-h85ec8f2_0.conda#b9df2fcb7e9eba945c1c946c438c4586
 https://conda.anaconda.org/conda-forge/osx-arm64/zstd-1.5.7-hbf9d68e_6.conda#ab136e4c34e97f34fb621d2592a393d8
@@ -124,7 +122,7 @@ https://conda.anaconda.org/conda-forge/noarch/joblib-1.5.3-pyhd8ed1ab_0.conda#61
 https://conda.anaconda.org/conda-forge/osx-arm64/scikit-learn-1.9.0-np2py312he5ca3e3_0.conda#b2b777cdad320a08da92bb1f58040bfd
 https://conda.anaconda.org/conda-forge/noarch/networkx-3.6.1-pyhcf101f3_0.conda#a2c1eeadae7a309daed9d62c96012a2b
 https://conda.anaconda.org/conda-forge/noarch/mapclassify-2.10.0-pyhd8ed1ab_1.conda#cc293b4cad9909bf66ca117ea90d4631
-https://conda.anaconda.org/conda-forge/noarch/geopandas-base-1.0.1-pyha770c72_3.conda#e8343d1b635bf09dafdd362d7357f395
+https://conda.anaconda.org/conda-forge/noarch/geopandas-base-1.1.4-pyha770c72_0.conda#6e31007c02f361338281bb78c5b84e7c
 https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha55dd90_7.conda#461219d1a5bd61342293efa2c0c90eac
 https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.1.0-pyhd8ed1ab_0.conda#8e6923fc12f1fe8f8c4e5c9f343256ac
 https://conda.anaconda.org/conda-forge/noarch/hpack-4.2.0-pyhd8ed1ab_0.conda#b395909221b9bd1df066e5930e18855b
@@ -139,8 +137,8 @@ https://conda.anaconda.org/conda-forge/osx-arm64/markupsafe-3.0.3-py312h04c11ed_
 https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.6-pyhcf101f3_1.conda#04558c96691bed63104678757beb4f8d
 https://conda.anaconda.org/conda-forge/noarch/branca-0.8.2-pyhd8ed1ab_0.conda#1fcdf88e7a8c296d3df8409bf0690db4
 https://conda.anaconda.org/conda-forge/noarch/folium-0.20.0-pyhd8ed1ab_0.conda#a6997a7dcd6673c0692c61dfeaea14ab
-https://conda.anaconda.org/conda-forge/noarch/geopandas-1.0.1-pyhd8ed1ab_3.conda#1baca589eb35814a392eaad6d152447e
-https://conda.anaconda.org/conda-forge/noarch/pandera-geopandas-0.24.0-hd8ed1ab_2.conda#fb21509f073465506ea994dc4667bf66
+https://conda.anaconda.org/conda-forge/noarch/geopandas-1.1.4-pyhd8ed1ab_0.conda#99d77e0f92f7b0b977f77cfb49c7eaf6
+https://conda.anaconda.org/conda-forge/noarch/pandera-geopandas-0.32.1-h9ad522b_0.conda#b6b27c3f219ce4d01c8ea31d435f263c
 https://conda.anaconda.org/conda-forge/noarch/et_xmlfile-2.0.0-pyhd8ed1ab_1.conda#71bf9646cbfabf3022c8da4b6b4da737
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workflow/envs/module.win-64.pin.txt

@@ -46,13 +46,12 @@ https://conda.anaconda.org/conda-forge/win-64/pydantic-core-2.46.4-py312hdabe01f
 https://conda.anaconda.org/conda-forge/noarch/annotated-types-0.7.0-pyhd8ed1ab_1.conda#2934f256a8acfe48f6ebb4fce6cde29c
 https://conda.anaconda.org/conda-forge/noarch/pydantic-2.13.4-pyhcf101f3_0.conda#729843edafc0899b3348bd3f19525b9d
 https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda#4c06a92e74452cfa53623a81592e8934
-https://conda.anaconda.org/conda-forge/noarch/pandera-base-0.24.0-pyhd8ed1ab_2.conda#e1c50e117a98e39d297d9290132f032b
-https://conda.anaconda.org/conda-forge/noarch/pytz-2026.2-pyhcf101f3_0.conda#03cb60f505ad3ada0a95277af5faeb1a
+https://conda.anaconda.org/conda-forge/noarch/pandera-base-0.32.1-pyhcf101f3_0.conda#c78daae943cb94e6e6b2eab16e16a18f
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 https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.9.0.post0-pyhe01879c_2.conda#5b8d21249ff20967101ffa321cab24e8
-https://conda.anaconda.org/conda-forge/win-64/pandas-2.3.0-py312h72972c8_0.conda#e2ab2d8cc52281c9ebe19451936802eb
-https://conda.anaconda.org/conda-forge/noarch/pandera-0.24.0-hd8ed1ab_2.conda#a12a21a89519f0cc224e44da86f5be2c
+https://conda.anaconda.org/conda-forge/win-64/pandas-3.0.5-py312h95189c4_1.conda#2eebd79dac0d5cb03209bebf32c87e0a
+https://conda.anaconda.org/conda-forge/noarch/pandera-0.32.1-ha00cc4c_0.conda#f6b96a51cda3cf9a068fd748c8155ced
 https://conda.anaconda.org/conda-forge/noarch/xyzservices-2026.3.0-pyhd8ed1ab_0.conda#4487b9c371d0161d54b5c7bbd890c0fc
 https://conda.anaconda.org/conda-forge/win-64/sqlite-3.53.3-hdb435a2_0.conda#7a28cb97617f0bd6a650b4b88f1f44cb
 https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda#053b84beec00b71ea8ff7a4f84b55207
@@ -122,7 +121,7 @@ https://conda.anaconda.org/conda-forge/noarch/joblib-1.5.3-pyhd8ed1ab_0.conda#61
 https://conda.anaconda.org/conda-forge/win-64/scikit-learn-1.9.0-np2py312hea30aaf_0.conda#0637562978d4231902754645e4c28640
 https://conda.anaconda.org/conda-forge/noarch/networkx-3.6.1-pyhcf101f3_0.conda#a2c1eeadae7a309daed9d62c96012a2b
 https://conda.anaconda.org/conda-forge/noarch/mapclassify-2.10.0-pyhd8ed1ab_1.conda#cc293b4cad9909bf66ca117ea90d4631
-https://conda.anaconda.org/conda-forge/noarch/geopandas-base-1.0.1-pyha770c72_3.conda#e8343d1b635bf09dafdd362d7357f395
+https://conda.anaconda.org/conda-forge/noarch/geopandas-base-1.1.4-pyha770c72_0.conda#6e31007c02f361338281bb78c5b84e7c
 https://conda.anaconda.org/conda-forge/noarch/win_inet_pton-1.1.0-pyh7428d3b_8.conda#46e441ba871f524e2b067929da3051c2
 https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyh09c184e_7.conda#e2fd202833c4a981ce8a65974fe4abd1
 https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.1.0-pyhd8ed1ab_0.conda#8e6923fc12f1fe8f8c4e5c9f343256ac
@@ -138,8 +137,8 @@ https://conda.anaconda.org/conda-forge/win-64/markupsafe-3.0.3-py312h05f76fc_1.c
 https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.6-pyhcf101f3_1.conda#04558c96691bed63104678757beb4f8d
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 https://conda.anaconda.org/conda-forge/noarch/folium-0.20.0-pyhd8ed1ab_0.conda#a6997a7dcd6673c0692c61dfeaea14ab
-https://conda.anaconda.org/conda-forge/noarch/geopandas-1.0.1-pyhd8ed1ab_3.conda#1baca589eb35814a392eaad6d152447e
-https://conda.anaconda.org/conda-forge/noarch/pandera-geopandas-0.24.0-hd8ed1ab_2.conda#fb21509f073465506ea994dc4667bf66
+https://conda.anaconda.org/conda-forge/noarch/geopandas-1.1.4-pyhd8ed1ab_0.conda#99d77e0f92f7b0b977f77cfb49c7eaf6
+https://conda.anaconda.org/conda-forge/noarch/pandera-geopandas-0.32.1-h9ad522b_0.conda#b6b27c3f219ce4d01c8ea31d435f263c
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 https://conda.anaconda.org/conda-forge/win-64/openpyxl-3.1.5-py312h83acffa_3.conda#ff342a314798173eaaf2753a22f044fa
 https://conda.anaconda.org/conda-forge/win-64/tornado-6.5.7-py312he06e257_0.conda#1045d29f787812d3fac1fd80a1339710

workflow/internal/config.schema.yaml

@@ -59,8 +59,8 @@ $defs:
     title: Planned commissioning year windows
     description: |
       Technology- and status-specific year-offset windows used to impute
-      missing commissioning years for planned powerplants. Each window is
-      expressed as [minimum_year_offset, maximum_year_offset] relative to
+      missing commissioning years for planned powerplants.
+      Each window is expressed as [minimum_year_offset, maximum_year_offset) relative to
       the dataset year (inclusive).
     type: object
     additionalProperties:
@@ -460,7 +460,7 @@ properties:
         additionalProperties: false
         required:
           - scenario
-          - start_year_imputation_method
+          - method
           - lifetime_years
           - retirement_delay_years
           - planned_commissioning_year_windows
@@ -483,14 +483,14 @@ properties:
             $ref: "#/$defs/year_map"
           retirement_delay_years:
             $ref: "#/$defs/year_map"
-          start_year_imputation_method:
-            title: Start year imputation method
+          method:
+            title: Time imputation method
             description: |
-              Method used to impute missing start years when backfilling from known
-              end years is not possible.
+              Method used to complete powerplants for which neither a start nor end
+              year is known.
 
-              - 'capacity_profile' assigns missing start years deterministically using
-              capacity-weighted commissioning profiles from annual commissioning statistics.
+              - 'capacity_profile' assigns dates deterministically using capacity-weighted
+              commissioning and retirement profiles from annual capacity statistics.
             type: string
             enum:
               - capacity_profile

workflow/rules/impute.smk

@@ -88,7 +88,7 @@ rule impute_time:
     message:
         "National-level imputation of missing powerplant ages in {wildcards.shapes}-{wildcards.category} dataset."
     script:
-        "../scripts/impute_ages.py"
+        "../scripts/impute_time.py"
 
 
 rule impute_capacity_adjustment:

workflow/scripts/_plots.py

@@ -12,6 +12,7 @@
 from matplotlib import ticker as mticker
 from matplotlib.axes import Axes
 from matplotlib.patches import Patch
+from matplotlib.typing import ColorType
 
 
 def draw_empty(ax: Axes, title: str = "", message="No data available"):
@@ -248,7 +249,7 @@ def get_colour_dict(
     colormap: str,
     *,
     value_range: tuple[float, float] = (0.0, 1.0),
-) -> dict[str, str]:
+) -> dict[str, ColorType]:
     """Return deterministic colours for a collection of source types."""
     sorted_sources = sorted(sources)