Merge pull request #109 from USEPA/release_v1.1.2

Release v1.1.2

.github/workflows/python-package.yml

@@ -34,11 +34,11 @@ jobs:
         py-version: ['3.9', '3.10', '3.11']
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
 
     # general Python setup
     - name: Set up Python ${{ matrix.py-version }}
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.py-version }}
 
@@ -52,6 +52,7 @@ jobs:
     - name: Install package and dependencies
       run: |
         pip install .
+        pip install bibtexparser # for testing bibliographies via esupy
         
     # - name: Install package and dependencies (Windows)
     #   if: matrix.os == 'windows-latest'

.github/workflows/test_methods.yml

@@ -13,9 +13,9 @@ jobs:
     runs-on: macos-latest
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - name: Set up Python
-      uses: actions/setup-python@v3
+      uses: actions/setup-python@v5
       with:
         python-version: "3.10"
 
@@ -36,7 +36,7 @@ jobs:
 
     - name: Upload files
       if: always()
-      uses: actions/upload-artifact@v3.1.1
+      uses: actions/upload-artifact@v4
       with:
         # Artifact name
         name: lciafmt_methods

format specs/LCIAcompilation.md

@@ -0,0 +1,15 @@
+## LCIA Compilation
+
+Custom methods consisting of indicators from multiple indicators can be created using `lciafmt.generate_lcia_compilation()`. 
+This requires an input `.yaml` file with the following specifications.
+See [compilation.yaml](../tests/compilation.yaml) for an example.
+
+```
+name: # Name given to new method
+rename_indicators: # True or False
+indicators: # Include as many unique indicators as desired as shown
+    Climate change: # The provided indicator name will be used if `rename_indicators` is `True`
+      method: IPCC # Method name from exisiting methods available in LCIAfmt
+      indicator: AR5-100 # Indicator name available within the selected method
+      code: GHG # (optional) code
+```

format specs/LCIAmethod.md

@@ -6,9 +6,9 @@ The flow name fields match those in the fedelemflowlist [FlowList](https://githu
  Index | Field | Type | Required |  Note |
 | ---- | ------ |  ---- | ---------| -----  |
  0 | Method | string | Y | The LCIA method name, e.g. 'Traci 2.1' |
- 1 | Method UUID | string | Y | ID for the method  |
+ 1 | Method UUID | string | N | ID for the method, generated if not supplied  |
  2 | Indicator | string | Y | Name of indicator, e.g. 'Acidification Potential' |
- 3 | Indicator UUID| string | Y | ID for the indicator |
+ 3 | Indicator UUID| string | N | ID for the indicator, generated if not supplied |
  4 | Indicator unit | string | Y | The unit for the indicator, e.g. 'kg CO2 eq' |
  5 | Flowable | string | Y | The flow name, e.g. 'Sulfur dioxide' |
  6 | Flow UUID | string | Y | ID of the flow |
@@ -18,3 +18,4 @@ The flow name fields match those in the fedelemflowlist [FlowList](https://githu
  10 | Location | string | N | Name of the location
  11 | Location UUID | string | N | ID of the location
  12 | Characterization factor | float | Y | LCIA characterization factor
+ 13 | Code | string | N | string abbreviation for indicator

lciafmt/__init__.py

@@ -22,6 +22,7 @@
 import lciafmt.util as util
 import lciafmt.endpoint as ep
 import lciafmt.custom as custom
+from lciafmt.custom import generate_lcia_compilation
 
 
 from enum import Enum
@@ -153,10 +154,11 @@ def map_flows(df: pd.DataFrame, system=None, mapping=None,
     x = mapped[mapped[['Method', 'Indicator', 'Flowable', 'Flow UUID']
                       ].duplicated(keep=False)]
     duplicates = list(set(zip(x.Indicator, x.Flowable)))
-    util.log.warn(f'Identified duplicate factors for {len(duplicates)} '
-                  f'flow/indicator combinations and {len(x)} factors.')
-    util.log.debug(f'{duplicates}')
-    util.log.warn(f'Use collapse_indicators() to drop these duplicates.')
+    if len(duplicates) > 0:
+        util.log.warning(f'Identified duplicate factors for {len(duplicates)} '
+                         f'flow/indicator combinations and {len(x)} factors.')
+        util.log.debug(f'{duplicates}')
+        util.log.warning('Use collapse_indicators() to drop these duplicates.')
     return mapped
 
 

lciafmt/custom.py

@@ -6,8 +6,12 @@
 """
 
 import pandas as pd
+from pathlib import Path
+import yaml
 
+import lciafmt
 from lciafmt.df import lciafmt_cols
+from lciafmt.util import datapath
 
 def get_custom_method(file: str=None, input_df=None):
     """Converts a dataframe or a csv filepath to a dataframe suitable for
@@ -23,3 +27,45 @@ def get_custom_method(file: str=None, input_df=None):
     else:
         raise Exception
 
+
+def generate_lcia_compilation(filename: str,
+                              filepath: Path=None
+                              ) -> pd.DataFrame:
+    """Generates a dataframe consisting of indicators from various LCIA methods
+    based on specs provided in yaml file.
+    """
+    if not filepath:
+        filepath = datapath
+    with open(filepath / filename) as f:
+        build_file = yaml.safe_load(f)
+    build_df = pd.DataFrame(build_file['indicators']).transpose()
+
+    indicator_dict = (build_df.groupby('method')
+                      .apply(lambda x: [y for y in x['indicator']])
+                      .to_dict())
+    name_dict = build_df['indicator'].to_dict()
+    code_dict = {}
+    if 'code' in build_df:
+        code_dict = build_df['code'].to_dict()
+
+    method_list = []
+    for method, indicators in indicator_dict.items():
+        df = lciafmt.get_mapped_method(method_id = method,
+                                       indicators = indicators,
+                                       methods = [method])
+        method_list.append(df)
+
+    df = pd.concat(method_list, ignore_index=True)
+
+    df['category'] = df['Method']
+    df['source_method'] = df['Method']
+    df['Method'] = build_file.get('name')
+    if build_file.get('rename_indicators', False):
+        df['category'] = df['Method']
+        df['source_indicator'] = df['Indicator']
+        df['Indicator'] = df['Indicator'].replace({v: k for k, v in name_dict.items()})
+        if code_dict:
+            df['Code'] = df['Indicator'].map(code_dict)
+
+    return df
+

lciafmt/data/ISO21930-LCIA-US.yaml

@@ -0,0 +1,28 @@
+name: ISO21930-LCIA-US
+version: v0.1
+rename_indicators: True
+indicators:
+    Greenhouse Gases:
+      method: IPCC
+      indicator: AR5-100
+      code: GHG
+
+    Ozone depletion potential:
+      method: TRACI 2.1
+      indicator: Ozone depletion
+      code: ODP
+
+    Eutrophication potential:
+      method: TRACI 2.1
+      indicator: Eutrophication
+      code: EP
+
+    Acidification potential:
+      method: TRACI 2.1
+      indicator: Acidification
+      code: AP
+
+    Photochemical oxidant creation potential:
+      method: TRACI 2.1
+      indicator: Smog formation
+      code: POCP

lciafmt/data/description.yaml

@@ -1,26 +1,27 @@
-description:
-    '[Method][version] is built from LCIA Formatter v[LCIAfmt_version] and flows from the Federal 
-    Elementary Flow List (FEDEFL) v[FEDEFL_version]
-    
+base: >+
+    [Method][version] is built from LCIA Formatter v[LCIAfmt_version] and
+    flows from the Federal Elementary Flow List (FEDEFL) v[FEDEFL_version]
+
+description: >+
     [Method] source file: [url]
     
     Source citation: [citation]
     
-    [Method] flowable and context input files are maintained in the FEDEFL GitHub Repository: 
-    https://github.com/USEPA/Federal-LCA-Commons-Elementary-Flow-List 
+    [Method] flowable and context input files are maintained in the FEDEFL
+    GitHub Repository: https://github.com/USEPA/fedelemflowlist
     
-        
-    The LCIA Formatter (https://github.com/USEPA/LCIAformatter) applies [Method] 
-    characterization factors to flows using the mapping housed in the FEDEFL. 
-    The flowable and context input files for [Method] are used by the LCIA Formatter 
-    to translate the names from the [Method] source file and generate a mapping 
-    file for the FEDEFL. This file contains all of the accepted flowable and context 
+    The LCIA Formatter (https://github.com/USEPA/LCIAformatter) applies [Method]
+    characterization factors to flows using the mapping housed in the FEDEFL.
+    The flowable and context input files for [Method] are used by the LCIA Formatter
+    to translate the names from the [Method] source file and generate a mapping
+    file for the FEDEFL. This file contains all of the accepted flowable and context
     combinations which can be mapped to [Method] characterization factors. It also
     includes target UUID, units, and conversion factors as well as tracking
     who mapped and verified each record and when they were last updated.
-    
-    
-    '
 
-indicator:
-    '[Indicator] is built from LCIA Formatter v[LCIAfmt_version] for use with [Method]'
+indicator: >
+    [Indicator] is built with LCIA Formatter v[LCIAfmt_version] for use with [Method]
+
+source_indicator: >
+    [Indicator] is built with LCIA Formatter v[LCIAfmt_version] based on
+    [source_indicator] in [Method]

lciafmt/data/lcia.bib

@@ -0,0 +1,18 @@
+@article{bare_traci_2011,
+	title = {{TRACI} 2.0: the tool for the reduction and assessment of chemical and other environmental impacts 2.0},
+	volume = {13},
+	pages = {687--696},
+	number = {5},
+	journal = {Clean Technologies and Environmental Policy},
+	author = {Bare, Jane},
+	doi = {10.1007/s10098-010-0338-9},
+	year = {2011}
+}
+
+@article{huijbregts_recipe_2017,
+	title = {{ReCiPe} 2016: A harmonized life cycle impact assessment method at midpoint and endpoint level Report I: Characterization},
+	journaltitle = {International Journal of Life Cycle Assessment},
+	author = {Huijbregts, M. A. J. and Steinmann, Z. J. N. and Elshout, P. M. F. and Stam, G. and Verones, F. and Vieira, M. D. M. and Hollander, A. and Zijp, M. and {van Zelm}, R.},
+	year = {2017},
+	DOI = {10.1007/s11367-016-1246-y}
+}

lciafmt/data/methods.json

@@ -7,6 +7,7 @@
     "mapping": "TRACI2.1",
     "case_insensitivity": "False",
     "url": "https://www.epa.gov/sites/default/files/2015-12/traci_2_1_2014_dec_10_0.xlsx",
+    "bib_id": "bare_traci_2011",
     "citation": "Bare 2012",
     "source_type": "Excel file"
   },
@@ -25,6 +26,7 @@
     "path": "recipe",
     "case_insensitivity": "True",
     "url": "http://www.rivm.nl/sites/default/files/2018-11/ReCiPe2016_CFs_v1.1_20180117.xlsx",
+    "bib_id": "huijbregts_recipe_2017",
     "citation": "Huijbregts 2017",
     "source_type": "Excel file"
   },
@@ -55,6 +57,7 @@
     "id": "IPCC",
     "name": "IPCC",
     "mapping": "IPCC",
+    "detail_note": "Factors are based on those reported in Table 2.14 (AR4), Table 8.A.1 (AR5), and Table 7.SM.7 (AR6).",
     "path": "ipcc",
     "case_insensitivity": "False",
     "url": "https://github.com/USEPA/LCIAformatter/blob/master/lciafmt/data/IPCC_GWP_values.csv",

lciafmt/endpoint.py

@@ -30,7 +30,7 @@ def apply_endpoints(endpoints, matching_fields, download_from_remote=False):
     method = pd.DataFrame()
 
     for e in matching_fields:
-        endpoints[e].fillna("", inplace=True)
+        endpoints[e] = endpoints[e].fillna("")
 
     for m in indicators['Method'].unique():
         method_indicators = indicators[indicators['Method'] == m]

lciafmt/ipcc.py

@@ -9,6 +9,10 @@
 from lciafmt.util import log, datapath
 from lciafmt.df import lciafmt_cols
 
+### IPCC data for each AR were sourced from the following:
+## AR4: Table 2.14 (https://archive.ipcc.ch/publications_and_data/ar4/wg1/en/errataserrata-errata.html#table214)
+## AR5: Table 8.A.1 (https://archive.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter08_FINAL.pdf)
+## AR6: Table 7.SM.7 (https://github.com/IPCC-WG1/Chapter-7/blob/main/data_output/7sm/metrics_supplement_cleaned.csv)
 
 def get() -> pd.DataFrame:
     """Generate a method for IPCC in standard format.