ver Dec27th

merged zdy into main

desktop_env/envs/desktop_env.py

@@ -79,6 +79,7 @@ class DesktopEnv(gym.Env):
         self.metric: Metric = getattr(metrics, self.evaluator["func"])
         self.result_getter: Getter = getattr(getters, "get_{:}".format(self.evaluator["result"]["type"]))
         self.expected_getter: Getter = getattr(getters, "get_{:}".format(self.evaluator["expected"]["type"]))
+        self.metric_options: Dict[str, Any] = self.evaluator.get("options", {})
 
         # Initialize emulator and controller
         print("Initializing...")
@@ -165,6 +166,7 @@ class DesktopEnv(gym.Env):
             self.metric: Metric = getattr(metrics, self.evaluator["func"])
             self.result_getter: Getter = getattr(getters, "get_{:}".format(self.evaluator["result"]["type"]))
             self.expected_getter: Getter = getattr(getters, "get_{:}".format(self.evaluator["expected"]["type"]))
+            self.metric_options = self.evaluator.get("options", {})
 
             self.setup_controller.reset_cache_dir(self.cache_dir)
 
@@ -237,7 +239,7 @@ class DesktopEnv(gym.Env):
 
         result = self.result_getter(self, self.evaluator["result"])
         expected = self.expected_getter(self, self.evaluator["expected"])
-        metric: float = self.metric(result, expected)
+        metric: float = self.metric(result, expected, **self.metric_options)
 
         return metric
 

desktop_env/evaluators/metrics/table.py

@@ -1,14 +1,10 @@
 import pandas as pd
-import zipfile
-import lxml.etree
-import lxml.cssselect
-from lxml.etree import _Element
-import xmltodict
 #import pylightxl
 import openpyxl
-from openpyxl import Workbook
+#from openpyxl import Workbook
 from openpyxl.worksheet.worksheet import Worksheet
-from openpyxl.chart._chart import ChartBase
+
+from utils import load_charts, load_sparklines
 
 from typing import Dict, List
 from typing import Any
@@ -20,104 +16,35 @@ def compare_table(actual, expected):
     # Compare the DataFrames
     return 1 if df1.equals(df2) else 0
 
-_xlsx_namespaces = [ ("x14", "http://schemas.microsoft.com/office/spreadsheetml/2009/9/main")
-                   , ("xm", "http://schemas.microsoft.com/office/excel/2006/main")
-                   ]
-_xlsx_ns_mapping = dict(_xlsx_namespaces)
-_xlsx_ns_imapping = dict(map(lambda itm: (itm[1], itm[0]), _xlsx_namespaces))
-_sparklines_selector = lxml.cssselect.CSSSelector("x14|sparkline", namespaces=_xlsx_ns_mapping)
-#print(_sparklines_selector.css)
-def _load_sparklines(xlsx_file: str) -> Dict[str, str]:
-    """
-    This function modifies data_frame in-place
-
-    Args:
-        xlsx_file (str): path to xlsx
-
-    Returns:
-        List[Dict[str, str]]: sparkline definitions in form of
-          {
-            "F3": "Sheet1!C3:E3"
-          }
-    """
-
-    # read xlsx
-    with zipfile.ZipFile(xlsx_file, "r") as z_f:
-        with z_f.open("xl/worksheets/sheet1.xml") as f:
-            sheet1: _Element = lxml.etree.fromstring(f.read())
-            sparklines: List[_Element] = _sparklines_selector(sheet1)
-
-    sparklines_dict: Dict[str, str] = {}
-    for sp_l in sparklines:
-        sparkline_xml: str = lxml.etree.tostring(sp_l, encoding="unicode")
-        sparkline: Dict[str, Dict[str, str]] = xmltodict.parse( sparkline_xml
-                                                              , process_namespaces=True
-                                                              , namespaces=_xlsx_ns_imapping
-                                                              )
-        sparklines_dict[sparkline["x14:sparkline"]["xm:sqref"]] = sparkline["x14:sparkline"]["xm:f"]
-    return sparklines_dict
-
 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)
+    sp1 = load_sparklines(actual)
-    sp2 = _load_sparklines(expected)
+    sp2 = load_sparklines(expected)
     sparkline_metric: bool = sp1 == sp2
     print("Sparkline Metric: {:}".format(sparkline_metric))
 
     return float(normal_content_metric and sparkline_metric)
 
-def _load_charts(xlsx_file: str) -> Dict[str, Any]:
+def compare_with_charts(actual: str, expected: str, **options) -> float:
     """
     Args:
-        xlsx_file (str): path to xlsx
+        actual (str): path to result xlsx
-
+        expected (str): path to gold xlsx
-    Returns:
+        options (Dict[str, List[str]]): dict like {"chart_props": list of str}
-        Dict[str, Any]: information of charts
+          giving the concerned chart properties
     """
 
-    workbook: Workbook = openpyxl.load_workbook(filename=xlsx_file)
-    worksheet: Worksheet = workbook.active
-    charts: List[ChartBase] = worksheet._charts
-
-    chart_set: Dict[str, Any] = {}
-    for ch in charts:
-        series: List[str] = []
-        for ser in ch.series:
-            value_num = ser.val.numRef.f\
-                     if hasattr(ser.val, "numRef") and hasattr(ser.val.numRef, "f")\
-                   else ""
-            value_str = ser.val.strRef.f\
-                     if hasattr(ser.val, "strRef") and hasattr(ser.val.strRef, "f")\
-                   else ""
-            categ_num = ser.cat.numRef.f\
-                     if hasattr(ser.cat, "numRef") and hasattr(ser.cat.numRef, "f")\
-                   else ""
-            categ_str = ser.cat.strRef.f\
-                     if hasattr(ser.cat, "strRef") and hasattr(ser.cat.strRef, "f")\
-                   else ""
-            series.append( "{:},{:},{:},{:}".format( value_num, value_str
-                                                   , categ_num, categ_str
-                                                   )
-                         )
-        series: str = ";".join(series)
-
-        # TODO: maybe more aspects, like chart type
-        info: Dict[str, Any] = {}
-        chart_set[series] = info
-    return chart_set
-
-def compare_with_charts(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))
 
-    charts1 = _load_charts(actual)
+    charts1 = load_charts(actual, **options)
-    charts2 = _load_charts(expected)
+    charts2 = load_charts(expected, **options)
     chart_metric: bool = charts1==charts2
     print("Chart Metric: {:}".format(chart_metric))
 
@@ -202,25 +129,5 @@ if __name__ == '__main__':
     #print(check_sheet_list(path1, rule))
 
     path1 = "../../../../../任务数据/LibreOffice Calc/Create_column_charts_using_statistics_gold.xlsx"
-    #workbook1: Workbook = openpyxl.load_workbook(filename=path1)
-    #worksheet1: Worksheet = workbook1.active
-    #charts: List[ChartBase] = worksheet1._charts
-    #print(len(charts))
-    #print(type(charts[0]))
-#
-    #print(len(charts[0].series))
-    #print(type(charts[0].series[0]))
-    #print(type(charts[0].series[0].val))
-    ##print(charts[0].series[0].val)
-    #print(charts[0].series[0].val.numRef.f)
-#
-    #print(type(charts[0].series[0].cat))
-    ##print(charts[0].series[0].cat)
-    #print(charts[0].series[0].cat.numRef)
-    #print(charts[0].series[0].cat.strRef)
-    #print(charts[0].series[0].cat.strRef.f)
-#
-    #df1 = pd.read_excel(path1)
-    #print(df1)
     path2 = "../../../../../任务数据/LibreOffice Calc/Create_column_charts_using_statistics_gold2.xlsx"
-    print(compare_with_charts(path1, path2))
+    print(compare_with_charts(path1, path2, chart_props=["type", "direction"]))

desktop_env/evaluators/metrics/utils.py

@@ -0,0 +1,161 @@
+import zipfile
+import lxml.etree
+import lxml.cssselect
+from lxml.etree import _Element
+import xmltodict
+import openpyxl
+from openpyxl import Workbook
+from openpyxl.worksheet.worksheet import Worksheet
+from openpyxl.chart._chart import ChartBase
+
+from typing import Dict, List, Set
+from typing import Any
+
+_xlsx_namespaces = [ ("x14", "http://schemas.microsoft.com/office/spreadsheetml/2009/9/main")
+                   , ("xm", "http://schemas.microsoft.com/office/excel/2006/main")
+                   ]
+_xlsx_ns_mapping = dict(_xlsx_namespaces)
+_xlsx_ns_imapping = dict(map(lambda itm: (itm[1], itm[0]), _xlsx_namespaces))
+_sparklines_selector = lxml.cssselect.CSSSelector("x14|sparkline", namespaces=_xlsx_ns_mapping)
+#print(_sparklines_selector.css)
+def load_sparklines(xlsx_file: str) -> Dict[str, str]:
+    """
+    This function modifies data_frame in-place
+
+    Args:
+        xlsx_file (str): path to xlsx
+
+    Returns:
+        List[Dict[str, str]]: sparkline definitions in form of
+          {
+            "F3": "Sheet1!C3:E3"
+          }
+    """
+
+    # read xlsx
+    with zipfile.ZipFile(xlsx_file, "r") as z_f:
+        with z_f.open("xl/worksheets/sheet1.xml") as f:
+            sheet1: _Element = lxml.etree.fromstring(f.read())
+            sparklines: List[_Element] = _sparklines_selector(sheet1)
+
+    sparklines_dict: Dict[str, str] = {}
+    for sp_l in sparklines:
+        sparkline_xml: str = lxml.etree.tostring(sp_l, encoding="unicode")
+        sparkline: Dict[str, Dict[str, str]] = xmltodict.parse( sparkline_xml
+                                                              , process_namespaces=True
+                                                              , namespaces=_xlsx_ns_imapping
+                                                              )
+        sparklines_dict[sparkline["x14:sparkline"]["xm:sqref"]] = sparkline["x14:sparkline"]["xm:f"]
+    return sparklines_dict
+
+# Available Chart Properties:
+# title: str
+# anchor: ["oneCell" | "twoCell" | "absolute", col0, row0, col1, row1]
+# width: number
+# height: number
+# type: "scatterChart" | "lineChart" | "barChart"
+# direction: "bar" (hori) | "col" (vert)
+# xtitle, ytitle, ztitle: str
+def load_charts(xlsx_file: str, **options) -> Dict[str, Any]:
+    """
+    Args:
+        xlsx_file (str): path to xlsx
+        options (Dict[str, List[str]]): dict like {"chart_props": list of str}
+          giving the concerned chart properties
+
+    Returns:
+        Dict[str, Any]: information of charts
+    """
+
+    workbook: Workbook = openpyxl.load_workbook(filename=xlsx_file)
+    worksheet: Worksheet = workbook.active
+    charts: List[ChartBase] = worksheet._charts
+
+    chart_set: Dict[str, Any] = {}
+    chart_props: Set[str] = set(options["chart_props"]) if "chart_props" in options else set()
+    for ch in charts:
+        series: List[str] = []
+        for ser in ch.series:
+            value_num = ser.val.numRef.f\
+                     if hasattr(ser.val, "numRef") and hasattr(ser.val.numRef, "f")\
+                   else ""
+            value_str = ser.val.strRef.f\
+                     if hasattr(ser.val, "strRef") and hasattr(ser.val.strRef, "f")\
+                   else ""
+            categ_num = ser.cat.numRef.f\
+                     if hasattr(ser.cat, "numRef") and hasattr(ser.cat.numRef, "f")\
+                   else ""
+            categ_str = ser.cat.strRef.f\
+                     if hasattr(ser.cat, "strRef") and hasattr(ser.cat.strRef, "f")\
+                   else ""
+            series.append( "{:},{:},{:},{:}".format( value_num, value_str
+                                                   , categ_num, categ_str
+                                                   )
+                         )
+        series: str = ";".join(series)
+
+        # TODO: maybe more aspects, like chart type
+        info: Dict[str, Any] = {}
+
+        if "title" in chart_props:
+            info["title"] = ch.title.tx.rich.p[0].r[0].t
+        if "anchor" in chart_props:
+            info["anchor"] = [ ch.anchor.editAs
+                             , ch.anchor._from.col, ch.anchor.to.row
+                             , ch.anchor.to.col, ch.anchor.to.row
+                             ]
+        if "width" in chart_props:
+            info["width"] = ch.width
+        if "height" in chart_props:
+            info["height"] = ch.height
+        if "type" in chart_props:
+            info["type"] = ch.tagname
+        if "direction" in chart_props:
+            info["direction"] = ch.barDir
+
+        if "xtitle" in chart_props:
+            info["xtitle"] = ch.x_axis.title.tx.rich.p[0].r[0].t
+        if "ytitle" in chart_props:
+            info["ytitle"] = ch.y_axis.title.tx.rich.p[0].r[0].t
+        if "ztitle" in chart_props:
+            info["ztitle"] = ch.z_axis.title.tx.rich.p[0].r[0].t
+        chart_set[series] = info
+    return chart_set
+
+if __name__ == "__main__":
+    path1 = "../../../../../任务数据/LibreOffice Calc/Create_column_charts_using_statistics_gold_line_scatter.xlsx"
+    workbook1: Workbook = openpyxl.load_workbook(filename=path1)
+    worksheet1: Worksheet = workbook1.active
+    charts: List[ChartBase] = worksheet1._charts
+    #print(len(charts))
+    #print(type(charts[0]))
+#
+    #print(len(charts[0].series))
+    #print(type(charts[0].series[0]))
+    #print(type(charts[0].series[0].val))
+    ##print(charts[0].series[0].val)
+    #print(charts[0].series[0].val.numRef.f)
+#
+    #print(type(charts[0].series[0].cat))
+    ##print(charts[0].series[0].cat)
+    #print(charts[0].series[0].cat.numRef)
+    #print(charts[0].series[0].cat.strRef)
+    #print(charts[0].series[0].cat.strRef.f)
+
+    #print(type(charts[0].title.tx.strRef))
+    #print(type(charts[0].title.tx.rich))
+    #print(type(charts[0].title.txPr))
+    #print(len(charts[0].title.tx.rich.p))
+    #print(len(charts[0].title.tx.rich.p[0].r))
+    #print(type(charts[0].title.tx.rich.p[0].r[0]))
+    #print(type(charts[0].title.tx.rich.p[0].r[0].t))
+    #print(charts[0].title.tx.rich.p[0].r[0].t)
+
+    #print(type(charts[0].anchor))
+    #print(charts[0].anchor.editAs)
+    #print(charts[0].anchor._from.col, charts[0].anchor.to.row)
+    #print(charts[0].anchor.to.col, charts[0].anchor.to.row)
+
+    #df1 = pd.read_excel(path1)
+    #print(df1)
+    print(load_charts(path1, chart_props=["title", "xtitle", "ytitle", "type"]))

evaluation_examples/examples/libreoffice_calc/347ef137-7eeb-4c80-a3bb-0951f26a8aff.json

@@ -37,6 +37,12 @@
 			"type": "cloud_file",
 			"path": "https://drive.usercontent.google.com/download?id=1yiTCGZvGccWET9u8K7looD3ybH7PO9gb&export=download&authuser=0&confirm=t&uuid=65f54a6f-bb2e-40c3-8a76-091d785a5aca&at=APZUnTVbeO6maMvzItLvSwdBEZoM:1703595892144",
 			"dest": "Create_column_charts_using_statistics_gold.xlsx"
+		},
+		"options": {
+			"chart_props": [
+				"type",
+				"direction"
+			]
 		}
 	}
 }