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added missing quote
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@konstantinstadler
konstantinstadler committed Feb 27, 2024
1 parent 9641cf7 commit 4c03648
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Showing 4 changed files with 71 additions and 52 deletions.
2 changes: 1 addition & 1 deletion environment.yml
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Expand Up @@ -5,7 +5,7 @@ channels:
- defaults
dependencies:
# core
- python >= 3.9
- python >= 3.9, < 3.12
- pandas >= 1.5
- pyarrow >= 11
- requests >= 2.18
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10 changes: 8 additions & 2 deletions pymrio/__init__.py
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Expand Up @@ -66,6 +66,12 @@
)
from pymrio.tools.iometadata import MRIOMetaData
from pymrio.tools.ioparser import *
from pymrio.tools.ioutil import build_agg_matrix, build_agg_vec, convert_to_long
from pymrio.tools.ioutil import index_match, index_contains, index_fullmatch
from pymrio.tools.ioutil import (
build_agg_matrix,
build_agg_vec,
convert_to_long,
index_contains,
index_fullmatch,
index_match,
)
from pymrio.version import __version__
2 changes: 1 addition & 1 deletion pymrio/tools/ioutil.py
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@@ -1,4 +1,4 @@
""
"""
Utility function for pymrio
KST 20140502
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109 changes: 61 additions & 48 deletions tests/test_util.py
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Expand Up @@ -5,6 +5,7 @@
import sys
from collections import namedtuple
from unittest.mock import mock_open, patch

import numpy as np
import numpy.testing as npt
import pandas as pd
Expand All @@ -15,19 +16,19 @@
TESTPATH = os.path.dirname(os.path.abspath(__file__))
sys.path.append(os.path.join(TESTPATH, ".."))

from pymrio.tools.ioutil import diagonalize_columns_to_sectors # noqa
from pymrio.tools.ioutil import ( # noqa
build_agg_matrix,
build_agg_vec,
diagonalize_blocks,
find_first_number,
set_block,
sniff_csv_format,
diagonalize_columns_to_sectors, # noqa
filename_from_url,
find_first_number,
index_contains,
index_fullmatch,
index_match,
match_and_convert,
set_block,
sniff_csv_format,
)


Expand Down Expand Up @@ -355,38 +356,40 @@ def test_util_regex():


def test_char_table():
""" Testing the characterization of one table """
"""Testing the characterization of one table"""

to_char = pd.DataFrame(
data=5,
index=pd.MultiIndex.from_product([["em1", "em2"], ["air", "water"]]),
columns=pd.MultiIndex.from_product([["r1", "c1"], ["r2", "c2"]]),
)
to_char.columns.names = ["reg", "sec"]
to_char.index.names = ["em_type", "compart"]
to_char.index.names = ["em_type", "compart"]

# TEST1: with only impact (one index level in the result) , sum over compartments

map_test1 = pd.DataFrame(
columns=["em_type", "compart", "total__em_type", "factor"],
data=[["em.*", "air|water", "total_regex", 2],

["em1", "air", "total_sum", 2],
["em1", "water", "total_sum", 2],
["em2", "air", "total_sum", 2],
["em2", "water", "total_sum", 2],

["em1", "air", "all_air", 0.5],
["em2", "air", "all_air", 0.5]],
data=[
["em.*", "air|water", "total_regex", 2],
["em1", "air", "total_sum", 2],
["em1", "water", "total_sum", 2],
["em2", "air", "total_sum", 2],
["em2", "water", "total_sum", 2],
["em1", "air", "all_air", 0.5],
["em2", "air", "all_air", 0.5],
],
)

# alternative way to calculated the expected result
exp_res1 = pd.DataFrame(
columns = to_char.columns,
index = ["total_regex", "total_sum", "all_air"])
exp_res1.loc['all_air'] = to_char.loc[("em1", "air")] * 0.5 + to_char.loc[("em2", "air")] * 0.5
exp_res1.loc['total_regex'] = (to_char.sum(axis=1) * 2).values
exp_res1.loc['total_sum'] = (to_char.sum(axis=1) * 2).values
columns=to_char.columns, index=["total_regex", "total_sum", "all_air"]
)
exp_res1.loc["all_air"] = (
to_char.loc[("em1", "air")] * 0.5 + to_char.loc[("em2", "air")] * 0.5
)
exp_res1.loc["total_regex"] = (to_char.sum(axis=1) * 2).values
exp_res1.loc["total_sum"] = (to_char.sum(axis=1) * 2).values
exp_res1 = exp_res1.astype(float)
exp_res1.sort_index(inplace=True)

Expand All @@ -404,23 +407,29 @@ def test_char_table():

map_test2 = pd.DataFrame(
columns=["em_type", "compart", "total__em_type", "compart__compart", "factor"],
data=[["em.*", "air|water", "total_regex", "all", 2],
["em1", "air", "total_sum", "all", 2],
["em1", "water", "total_sum", "all", 2],
["em2", "air", "total_sum", "all", 2],
["em2", "water", "total_sum", "all", 2],
["em1", "air", "all_air", "air", 0.5],
["em2", "air", "all_air", "air", 0.5]],
data=[
["em.*", "air|water", "total_regex", "all", 2],
["em1", "air", "total_sum", "all", 2],
["em1", "water", "total_sum", "all", 2],
["em2", "air", "total_sum", "all", 2],
["em2", "water", "total_sum", "all", 2],
["em1", "air", "all_air", "air", 0.5],
["em2", "air", "all_air", "air", 0.5],
],
)

# alternative way to calculated the expected result
exp_res2 = pd.DataFrame(
columns = to_char.columns,
index = pd.MultiIndex.from_tuples(
[("total_regex", "all"), ("total_sum", "all"), ("all_air", "air")]))
exp_res2.loc[('all_air', 'air')] = to_char.loc[("em1", "air")] * 0.5 + to_char.loc[("em2", "air")] * 0.5
exp_res2.loc[('total_regex', 'all')] = (to_char.sum(axis=1) * 2).values
exp_res2.loc[('total_sum', 'all')] = (to_char.sum(axis=1) * 2).values
columns=to_char.columns,
index=pd.MultiIndex.from_tuples(
[("total_regex", "all"), ("total_sum", "all"), ("all_air", "air")]
),
)
exp_res2.loc[("all_air", "air")] = (
to_char.loc[("em1", "air")] * 0.5 + to_char.loc[("em2", "air")] * 0.5
)
exp_res2.loc[("total_regex", "all")] = (to_char.sum(axis=1) * 2).values
exp_res2.loc[("total_sum", "all")] = (to_char.sum(axis=1) * 2).values
exp_res2 = exp_res2.astype(float)
exp_res2.sort_index(inplace=True)

Expand All @@ -437,23 +446,29 @@ def test_char_table():

map_test3 = pd.DataFrame(
columns=["em_type", "compart", "total__em_type", "compart__compart", "factor"],
data=[["em.*", "air|water", "total_regex", "all", 2],
["em1", "air", "total_sum", "all", 2],
["em1", "water", "total_sum", "all", 2],
["em2", "air", "total_sum", "all", 2],
["em2", "water", "total_sum", "all", 2],
["em1", "air", "all_air", "air", 0.5],
["em2", "air", "all_air", "air", 0.5]],
data=[
["em.*", "air|water", "total_regex", "all", 2],
["em1", "air", "total_sum", "all", 2],
["em1", "water", "total_sum", "all", 2],
["em2", "air", "total_sum", "all", 2],
["em2", "water", "total_sum", "all", 2],
["em1", "air", "all_air", "air", 0.5],
["em2", "air", "all_air", "air", 0.5],
],
)

# alternative way to calculated the expected result
exp_res3 = pd.DataFrame(
columns = to_char.columns,
index = pd.MultiIndex.from_tuples(
[("total_regex", "all"), ("total_sum", "all"), ("all_air", "air")]))
exp_res3.loc[('all_air', 'air')] = to_char.loc[("em1", "air")] * 0.5 + to_char.loc[("em2", "air")] * 0.5
exp_res3.loc[('total_regex', 'all')] = (to_char.sum(axis=1) * 2).values
exp_res3.loc[('total_sum', 'all')] = (to_char.sum(axis=1) * 2).values
columns=to_char.columns,
index=pd.MultiIndex.from_tuples(
[("total_regex", "all"), ("total_sum", "all"), ("all_air", "air")]
),
)
exp_res3.loc[("all_air", "air")] = (
to_char.loc[("em1", "air")] * 0.5 + to_char.loc[("em2", "air")] * 0.5
)
exp_res3.loc[("total_regex", "all")] = (to_char.sum(axis=1) * 2).values
exp_res3.loc[("total_sum", "all")] = (to_char.sum(axis=1) * 2).values
exp_res3 = exp_res3.astype(float)
exp_res3.sort_index(inplace=True)

Expand All @@ -464,5 +479,3 @@ def test_char_table():
exp_res3.columns.names = res3.columns.names

pdt.assert_frame_equal(res3, exp_res3)


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