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ver Dec29thv2

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re-organized functions w.r.t. comparing xlsx with a golden one
This commit is contained in:
David Chang
2023-12-29 21:43:33 +08:00
parent e4fac09945
commit 6f225b2a02
6 changed files with 72 additions and 69 deletions
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2
desktop_env/evaluators/metrics/__init__.py
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@@ -1,2 +1,2 @@
from .table import compare_table, compare_with_sparklines, compare_with_charts
from .table import compare_table
from .table import check_sheet_list, check_xlsx_freeze

111
desktop_env/evaluators/metrics/table.py
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@@ -9,71 +9,62 @@ from typing import Dict, List
from typing import Any
def compare_table(actual, expected):
df1 = pd.read_excel(expected)
df2 = pd.read_excel(actual)
# Compare the DataFrames
return 1 if df1.equals(df2) else 0
def compare_with_sparklines(actual: str, expected: str) -> float:
df1 = pd.read_excel(actual)
df2 = pd.read_excel(expected)
normal_content_metric: bool = df1.equals(df2)
print("Normal Contents Metric: {:}".format(normal_content_metric))
sp1 = load_sparklines(actual)
sp2 = load_sparklines(expected)
sparkline_metric: bool = sp1 == sp2
print("Sparkline Metric: {:}".format(sparkline_metric))
return float(normal_content_metric and sparkline_metric)
def compare_with_charts(actual: str, expected: str, **options) -> float:
def compare_table(actual: str, expected: str, **options) -> float:
"""
Args:
actual (str): path to result xlsx
expected (str): path to gold xlsx
options (Dict[str, List[str]]): dict like {"chart_props": list of str}
giving the concerned chart properties
options (Dict[str, List[str]]): dict like
{
"features": list of str for other features, supports:
* sparkline
* chart
* number_format
"chart_props": list of str, giving the converned chart properties
}
Return:
float: the score
"""
df1 = pd.read_excel(actual)
df2 = pd.read_excel(expected)
normal_content_metric: bool = df1.equals(df2)
print("Normal Contents Metric: {:}".format(normal_content_metric))
df1 = pd.read_excel(expected)
df2 = pd.read_excel(actual)
metric: bool = df1.equals(df2)
print("Normal Contents Metric: {:}".format(metric))
charts1 = load_charts(actual, **options)
charts2 = load_charts(expected, **options)
chart_metric: bool = charts1 == charts2
print("Chart Metric: {:}".format(chart_metric))
features: List[str] = options.get("features", [])
for ftr in features:
workbook1: Workbook = openpyxl.load_workbook(actual)
workbook2: Workbook = openpyxl.load_workbook(expected)
return float(normal_content_metric and chart_metric)
if ftr=="sparkline":
sp1 = load_sparklines(actual)
sp2 = load_sparklines(expected)
new_metric: bool = sp1 == sp2
print("Sparkline Metric: {:}".format(new_metric))
elif ftr=="chart":
charts1 = load_charts(workbook1, **options)
charts2 = load_charts(workbook2, **options)
new_metric: bool = charts1 == charts2
print("Chart Metric: {:}".format(new_metric))
elif ftr=="number_format":
number_formats1: List[str] = [ c.number_format.lower()\
for col in workbook1.active.iter_cols()\
for c in col\
if c.data_type=="n"
]
number_formats2: List[str] = [ c.number_format.lower()\
for col in workbook2.active.iter_cols()\
for c in col\
if c.data_type=="n"
]
new_metric: bool = number_formats1==number_formats2
print("Number Format Metric: {:}".format(new_metric))
else:
raise NotImplementedError("Unsupported xlsx feature: {:}".format(ftr))
metric = metric and new_metric
def compare_with_formats(actual: str, expected: str) -> float:
df1 = pd.read_excel(actual)
df2 = pd.read_excel(expected)
normal_content_metric: bool = df1.equals(df2)
print("Normal Contents Metric: {:}".format(normal_content_metric))
workbook1: Workbook = openpyxl.load_workbook(actual)
number_formats1: List[str] = [ c.number_format.lower()\
for col in workbook1.active.iter_cols()\
for c in col\
if c.data_type=="n"
]
workbook2: Workbook = openpyxl.load_workbook(expected)
number_formats2: List[str] = [ c.number_format.lower()\
for col in workbook2.active.iter_cols()\
for c in col\
if c.data_type=="n"
]
number_format_metric: bool = number_formats1==number_formats2
print("Number Format Metric: {:}".format(number_format_metric))
return float(normal_content_metric & number_format_metric)
return float(metric)
def check_sheet_list(result: str, rules: List[Dict[str, Any]]) -> float:
# workbook: Workbook = openpyxl.load_workbook(filename=result)
@@ -155,9 +146,9 @@ if __name__ == '__main__':
# ]
# print(check_sheet_list(path1, rule))
#path1 = "../../../../../任务数据/LibreOffice Calc/Create_column_charts_using_statistics_gold.xlsx"
#path2 = "../../../../../任务数据/LibreOffice Calc/Create_column_charts_using_statistics_gold2.xlsx"
#print(compare_with_charts(path1, path2, chart_props=["type", "direction"]))
path1 = "../../任务数据/LibreOffice Calc/Create_column_charts_using_statistics_gold.xlsx"
path2 = "../../任务数据/LibreOffice Calc/Create_column_charts_using_statistics_gold2.xlsx"
print(compare_table(path1, path2, features=["chart"], chart_props=["type", "direction"]))
path1 = "../../任务数据/LibreOffice Calc/Represent_in_millions_billions_gold.xlsx"
path2 = "../../任务数据/LibreOffice Calc/Represent_in_millions_billions_gold3.xlsx"
@@ -172,4 +163,4 @@ if __name__ == '__main__':
#print(worksheet1[position])
#print(worksheet1[position].value)
#print(worksheet1[position].number_format)
print(compare_with_formats(path1, path2))
print(compare_table(path1, path2, features=["number_format"]))

8
desktop_env/evaluators/metrics/utils.py
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@@ -56,10 +56,10 @@ def load_sparklines(xlsx_file: str) -> Dict[str, str]:
# type: "scatterChart" | "lineChart" | "barChart"
# direction: "bar" (hori) | "col" (vert)
# xtitle, ytitle, ztitle: str
def load_charts(xlsx_file: str, **options) -> Dict[str, Any]:
def load_charts(xlsx_file: Workbook, **options) -> Dict[str, Any]:
"""
Args:
xlsx_file (str): path to xlsx
xlsx_file (Workbook): concerned excel book
options (Dict[str, List[str]]): dict like {"chart_props": list of str}
giving the concerned chart properties
@@ -67,8 +67,8 @@ def load_charts(xlsx_file: str, **options) -> Dict[str, Any]:
Dict[str, Any]: information of charts
"""
workbook: Workbook = openpyxl.load_workbook(filename=xlsx_file)
worksheet: Worksheet = workbook.active
#workbook: Workbook = openpyxl.load_workbook(filename=xlsx_file)
worksheet: Worksheet = xlsx_file.active
charts: List[ChartBase] = worksheet._charts
chart_set: Dict[str, Any] = {}

7
evaluation_examples/examples/libreoffice_calc/21df9241-f8d7-4509-b7f1-37e501a823f7.json
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@@ -27,7 +27,7 @@
"libreoffice_calc"
],
"evaluator": {
"func": "compare_with_formats",
"func": "compare_table",
"result": {
"type": "vm_file",
"path": "/home/david/Represent_in_millions_billions.xlsx",
@@ -37,6 +37,11 @@
"type": "cloud_file",
"path": "",
"dest": "Represent_in_millions_billions_gold.xlsx"
},
"options": {
"features": [
"number_format"
]
}
}
}

8
evaluation_examples/examples/libreoffice_calc/2bd59342-0664-4ccb-ba87-79379096cc08.json
View File

@@ -26,7 +26,7 @@
"libreoffice calc"
],
"evaluator": {
"func": "compare_with_sparklines",
"func": "compare_table",
"expected": {
"type": "cloud_file",
"path": "https://drive.usercontent.google.com/download?id=1KQJJLVPGtTL_7ArEWvwwbFbJSiA3cgSE&export=download&authuser=0&confirm=t&uuid=6b11c721-caad-439a-b369-4c13c7a485df&at=APZUnTV5-1isKrDKSHV9NeJ6TDeS:1703509054094",
@@ -36,6 +36,10 @@
"type": "vm_file",
"path": "/home/david/OrderId_Month_Chart.xlsx",
"dest": "OrderId_Month_Chart.xlsx"
}
},
"options": {
"features": [
"sparkline"
]
}
}

5
evaluation_examples/examples/libreoffice_calc/347ef137-7eeb-4c80-a3bb-0951f26a8aff.json
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@@ -27,7 +27,7 @@
"libreoffice_calc"
],
"evaluator": {
"func": "compare_with_charts",
"func": "compare_table",
"result": {
"type": "vm_file",
"path": "/home/david/Create_column_charts_using_statistics.xlsx",
@@ -39,6 +39,9 @@
"dest": "Create_column_charts_using_statistics_gold.xlsx"
},
"options": {
"features": [
"chart"
],
"chart_props": [
"type",
"direction"