Update conda environment

environment.yml

@@ -1,50 +1,48 @@
-name: reeds2
+name: reeds
 channels:
-  - defaults
   - conda-forge
 dependencies:
-  - python=3.11
-  - bokeh=3.2
-  - click=8.0
-  - git-lfs=2.13
+  - python=3.14
+  - bokeh=3.9
+  - click=8.3
+  - cmocean=4.0
+  - geopandas=1.1
+  - git-lfs=3.7
   - gitpython=3.1
-  - h5py=3.9
-  - matplotlib=3.7
-  - numpy=1.26
-  - openpyxl=3.0
-  - pandas=2.0
-  - pip=23.2
-  - pytables=3.8
-  - pytest=7.4
-  - requests=2.31
-  - scikit-learn=1.2
-  - scipy=1.11
-  - tqdm=4.65
+  - h5py=3.16
+  - matplotlib=3.10
+  - numpy=2.4
+  - openpyxl=3.1
+  - pandas=3.0
+  - pip=26.1
+  - pulp=2.8
+  - pytables=3.11
+  - pytest=9.0
+  - requests=2.33
+  - scikit-learn=1.8
+  - scipy=1.17
+  - shapely=2.1
+  - tqdm=4.67
   ## vvv The next packages are optional for default settings and may
   ## vvv be excluded if you're having trouble building the environment.
-  - ipykernel=6.25 # for interactive python in VS Code
-  - ipywidgets=8.0 # for jupyter notebooks
-  - mapclassify=2.5 # more mapping tools
+  - fiona=1.10 # for interactive maps
+  - folium=0.20 # for interactive maps
+  - ipykernel=7.2 # for interactive python in VS Code
+  - ipywidgets=8.1 # for jupyter notebooks
+  - mapclassify=2.10 # more mapping tools
   - mscorefonts=0.0 # extra fonts for plotting (only relevant on linux/HPC)
-  - networkx=3.1 # for uncommonly-used network analysis postprocessing
-  - notebook=6.5 # for jupyter notebooks
+  - myst-parser=5.0 # for building documentation
+  - networkx=3.6 # for uncommonly-used network analysis postprocessing
+  - notebook=7.5 # for jupyter notebooks
+  - python-pptx=1.0 # for postprocessing/compare_cases.py
+  - sphinx=9.1 # for building documentation
+  - sphinx_rtd_theme=3.1 # for documentation
+  - sphinxcontrib-bibtex=2.6 # for documentation
   ## ^^^
   - pip:
-    - cmocean==3.0.3
-    - gdxpds==1.4.0
-    - geopandas==0.14.0
-    - pulp==2.7.0
-    - shapely==2.0.1
+    - gamsapi[transfer]==53.5.0
+    - gdxpds==2.0.0
     ## vvv The next packages are optional for default settings and may
     ## vvv be excluded if they cause trouble building the environment.
-    - fiona==1.9.5 # for interactive maps
-    - folium==0.14.0 # for interactive maps
-    - gamspy_base==50.5.0 # for tests on the github runner
-    - myst-parser==2.0.0 # for building documentation
-    - proj==0.2.0 # for plotting maps
-    - pyproj==3.6.1 # for plotting maps
-    - python-pptx==0.6.22 # for postprocessing/compare_cases.py
-    - sphinx_rtd_theme==2.0.0 # for documentation
-    - sphinx==7.2.6 # for building documentation
-    - sphinxcontrib-bibtex==2.6.2 # for documentation
-    ## ^^^
+    - gamspy_base==53.5.0 # for tests on the github runner
+    - highspy==1.14.0 # for future solver flexibility

postprocessing/raw_value_streams.py

@@ -151,7 +151,7 @@ def get_df_jacobian(jacobian_file, var_list=None, con_list=None):
             coeff (float): Coefficient of the variable in the constraint or objective.
     '''
     start = datetime.now()
-    df_A = gdxpds.to_dataframe(jacobian_file, 'A', old_interface=False)
+    df_A = gdxpds.to_dataframe(jacobian_file, 'A')
     for x in ['j','i']:
         #For i (equation) and j (variable) sets, I need to dump to csv to get the Text column, ugh
         x_file =  jacobian_file.replace('.gdx',f'_{x}.csv')

postprocessing/reValue/reValue.py

@@ -85,7 +85,7 @@ def get_prices():
         yrs_less = [y for y in yrs if y < year]
         max_yr = max(yrs_less)
         df_ra = gdxpds.to_dataframe(f'{reeds_run_path}/handoff/reeds_data/ccdata_{max_yr}.gdx',
-            'net_load_2012', old_interface=False)
+            'net_load_2012')
         if int(df_ra['t'][0]) != year:
             raise ValueError(f'RA year ({int(df_ra["t"][0])}) does not match current scenario year ({year})')
         df_ra = df_ra.sort_values('Value', ascending=False)

postprocessing/retail_rate_module/calculate_historical_capex.py

@@ -58,12 +58,10 @@ def get_earliest_cap_costs(inputs_case):
     cost_cap = gdxpds.to_dataframe(
         os.path.join(inputs_case, 'inputs.gdx'),
         'cost_cap',
-        old_interface=False
     )
     cost_cap_energy = gdxpds.to_dataframe(
         os.path.join(inputs_case, 'inputs.gdx'),
         'cost_cap_energy',
-        old_interface=False
     )
     cost_cap = (
         pd.concat([cost_cap, cost_cap_energy])
@@ -83,7 +81,6 @@ def get_earliest_cap_costs(inputs_case):
     cost_cap_mult = gdxpds.to_dataframe(
         os.path.join(inputs_case, 'inputs.gdx'),
         'cost_cap_fin_mult_out',
-        old_interface=False
     )
     cost_cap_mult['t'] = cost_cap_mult['t'].astype(int)
     cost_cap_mult = cost_cap_mult.rename(
@@ -112,7 +109,6 @@ def get_earliest_cap_costs(inputs_case):
     rsc_dat = gdxpds.to_dataframe(
         os.path.join(inputs_case, 'inputs.gdx'),
         'rsc_dat',
-        old_interface=False
     )
     cost_cap_rsc = (
         rsc_dat.loc[~rsc_dat.i.isin(cost_cap_earliest['i'])]

reeds/input_processing/copy_files.py

@@ -337,7 +337,7 @@ def get_regions_and_agglevel(
 
     # Sort hier_sub by r so that "ord(r)" commands in GAMS result in the properly
     # ordered outputs
-    hier_sub['numeric_value'] = hier_sub['r'].str.extract('(\d+)').astype(float)
+    hier_sub['numeric_value'] = hier_sub['r'].str.extract(r'(\d+)').astype(float)
     hier_sub = hier_sub.sort_values(by='numeric_value').drop('numeric_value', axis=1)
 
     # Output the itlgrp files for mixed and county resolution
@@ -455,12 +455,7 @@ def read_banned_tech_file(full_path, filepath, inputs_case, r_county):
                 .apply(list)
                 .apply(sorted)
             )
-            r_all_counties_map = (
-                r_county.groupby('r')
-                ['county']
-                .apply(list)
-                .apply(sorted)
-            )
+            r_all_counties_map = r_county.county.tolist()
             county_ban_regions = list(
                 r_ban_counties_map
                 .loc[(r_ban_counties_map.isin(r_all_counties_map))]
@@ -492,11 +487,8 @@ def read_special_h5file(full_path):
         df.columns = df.columns.str.replace('distpv|','')
     elif filename.startswith('transmission_cost_ac'):
         df = df.reset_index()
-        for col in ['r', 'rr', 'tscbin']:
-            df[col] = df[col].str.decode('utf-8')
     elif filename.startswith('transmission_distance'):
         df = df.stack().rename('miles').reset_index()
-        df['r'] = df['r'].str.decode('utf-8')
 
     return df
 
@@ -900,7 +892,7 @@ def write_scalars(scalars, inputs_case):
     scalars_write = pd.concat([scalars, toadd], axis=0)
 
     # Trim trailing decimal zeros
-    scalars_write.value = scalars_write.value.astype(str).replace('\.0+$', '', regex=True)
+    scalars_write.value = scalars_write.value.astype(str).replace(r'\.0+$', '', regex=True)
     scalars_write.to_csv(os.path.join(inputs_case, 'scalars.csv'), header=False)
 
     # Rewrite the scalar tables as GAMS-readable definition
@@ -1673,7 +1665,7 @@ def main(reeds_path, inputs_case):
 
     # #%% Settings for testing ###
     # reeds_path = reeds.io.reeds_path
-    # inputs_case = os.path.join(reeds_path,'runs','v20260305_itlM0_USA_defaults','inputs_case')
+    # inputs_case = os.path.join(reeds_path,'runs','v20260520_envM0_Pacific','inputs_case')
 
 
     # ---- Set up logger ----

reeds/io.py

@@ -689,23 +689,24 @@ def get_switches(case=None, **kwargs):
             (case if case is not None else reeds_path),
             'reeds', 'resource_adequacy', 'ra_switches.csv',
         )
-        asw = pd.read_csv(fpath_asw, index_col='key')
-        for i, row in asw.iterrows():
+        dfra = pd.read_csv(fpath_asw, index_col='key', dtype='object')
+        ra_switches = {}
+        for key, row in dfra.iterrows():
             if row['dtype'] == 'list':
-                row.value = row.value.split(',')
+                ra_switches[key] = row.value.split(',')
                 try:
-                    row.value = [int(i) for i in row.value]
+                    ra_switches[key] = [int(i) for i in row.value]
                 except ValueError:
                     pass
             elif row['dtype'] == 'boolean':
-                row.value = False if row.value.lower() == 'false' else True
+                ra_switches[key] = False if row.value.lower() == 'false' else True
             elif row['dtype'] == 'str':
-                row.value = str(row.value)
+                ra_switches[key] = str(row.value)
             elif row['dtype'] == 'int':
-                row.value = int(row.value)
+                ra_switches[key] = int(row.value)
             elif row['dtype'] == 'float':
-                row.value = float(row.value)
-        sw = pd.concat([sw, asw.value])
+                ra_switches[key] = float(row.value)
+        sw = pd.concat([sw, pd.Series(ra_switches)])
     except FileNotFoundError:
         print(f"{fpath_asw} not found so leaving out resource adequacy switches")
     ### Add derivative switches
@@ -773,7 +774,7 @@ def get_scalars(case=None, full=False):
     return scalars
 
 
-def read_h5py_file(filename, decode_strings=False):
+def read_h5py_file(filename):
     """Return dataframe object for a h5py file.
 
     This function returns a pandas dataframe of a h5py file. If the file has multiple dataset on it
@@ -821,7 +822,7 @@ def read_h5py_file(filename, decode_strings=False):
             idx_cols.sort()
             for idx_col in idx_cols:
                 df[idx_col] = pd.Series(f[idx_col]).values
-                if str(df[idx_col].dtype).startswith('|S') and decode_strings:
+                if str(df[idx_col].dtype).startswith('|S'):
                     df[idx_col] = df[idx_col].str.decode('utf-8')
             df = df.set_index(idx_cols)
 
@@ -842,7 +843,7 @@ def read_h5py_file(filename, decode_strings=False):
     return df
 
 
-def read_file(filename, parse_timestamps=False, decode_strings=False):
+def read_file(filename, parse_timestamps=False):
     """Return dataframe object of input file for multiple file formats.
 
     This function read multiple file formats for h5 file sand returns a dataframe from the file.
@@ -872,7 +873,7 @@ def read_file(filename, parse_timestamps=False, decode_strings=False):
     # datasets that composes the h5 file. For a single dataset we use pandas (since it is the most
     # convenient) and h5py for the custom h5 file.
     try:
-        df = read_h5py_file(filename, decode_strings=decode_strings)
+        df = read_h5py_file(filename)
     except TypeError:
         df = pd.read_hdf(filename)
 

reeds/resource_adequacy/prep_data.py

@@ -170,7 +170,7 @@ def main(t, casedir, iteration=0):
         ## e.g. "upv_5" -> "upv", "csp2_3" -> "csp"
         techs_vre_simplify = dict(zip(
             techs_vre,
-            [re.sub('\d?_\d+$', '', i) for i in techs_vre]
+            [re.sub(r'\d?_\d+$', '', i) for i in techs_vre]
         ))
 
     try:

runreeds.py

@@ -826,22 +826,19 @@ def setupEnvironment(
 
     #%% Check whether the ReEDS conda environment is activated
     if (not skip_checks) and (
-        ('reeds2' not in os.environ['CONDA_DEFAULT_ENV'].lower())
-        or (not pd.__version__.startswith('2'))
+        ('reeds' not in os.environ['CONDA_DEFAULT_ENV'].lower())
+        or (not pd.__version__.startswith('3'))
     ):
-        print(
+        err = (
             f"Your environment is {os.environ['CONDA_DEFAULT_ENV']} and your pandas "
-            f"version is {pd.__version__}.\nThe default environment is 'reeds2', with\n"
-            "pandas version 2.x, so the python parts of ReEDS are unlikely to work.\n"
+            f"version is {pd.__version__}.\nThe supported environment is 'reeds', with\n"
+            "pandas version 3.x.\n"
             "To build the environment for the first time, run:\n"
             "    `conda env create -f environment.yml`\n"
             "To activate the created environment, run:\n"
-            "    `conda activate reeds2` (or `activate reeds2` on Windows)\n"
-            "Do you want to continue without activating the environment?"
+            "    `conda activate reeds` (or `activate reeds` on Windows)"
         )
-        confirm_env = str(input("Continue? y/[n]: ") or 'n')
-        if confirm_env not in ['y','Y','yes','Yes','YES']:
-            quit()
+        raise ValueError(err)
 
     #%% Load specified case file, infer other settings from cases.csv
     if cases_suffix in ['', 'default']: