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https://github.com/Doctorado-ML/benchmark.git
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Add date and color to results list
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11
README.md
11
README.md
@@ -45,3 +45,14 @@ python src/benchmark.py
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# Do benchmark, print report and build excel file with data
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# Do benchmark, print report and build excel file with data
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python src/benchmark.py -x 1
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python src/benchmark.py -x 1
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```
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```
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## List
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```python
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# List of results of given model
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python src/list.py -m ODTE
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# List of results of given model and score
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python src/list.py -m STree -s f1-macro
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# List all results
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python src/list.py
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```
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@@ -1,4 +1,3 @@
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from cgitb import text
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import os
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import os
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import json
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import json
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import abc
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import abc
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@@ -700,7 +699,7 @@ class Summary:
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self.datasets[result] = report.lines
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self.datasets[result] = report.lines
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self.data.append(entry)
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self.data.append(entry)
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def list(self, score=None, model=None) -> None:
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def list_results(self, score=None, model=None) -> None:
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"""Print the list of results"""
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"""Print the list of results"""
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data = self.data.copy()
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data = self.data.copy()
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if score:
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if score:
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@@ -710,14 +709,24 @@ class Summary:
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data = sorted(data, key=lambda x: x["date"], reverse=True)
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data = sorted(data, key=lambda x: x["date"], reverse=True)
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max_file = max(len(x["file"]) for x in data)
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max_file = max(len(x["file"]) for x in data)
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max_title = max(len(x["title"]) for x in data)
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max_title = max(len(x["title"]) for x in data)
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print(f"{'File':{max_file}s} {'Score':7s} {'Title':s}")
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print(TextColor.LINE1, end="")
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print("=" * max_file + " " + "=" * 7 + " " + "=" * max_title)
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print(f"{'Date':10s} {'File':{max_file}s} {'Score':7s} {'Title':s}")
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print(
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"=" * 10
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+ " "
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+ "=" * max_file
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+ " "
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+ "=" * 7
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+ " "
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+ "=" * max_title
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)
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print(
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print(
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"\n".join(
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"\n".join(
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[
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[
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f"{x['file']:{max_file}s} {x['metric']:7.3f} "
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(TextColor.LINE2 if n % 2 == 0 else TextColor.LINE1)
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f"{x['title']}"
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+ f"{x['date']} {x['file']:{max_file}s} "
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for x in data
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f"{x['metric']:7.3f} {x['title']}"
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for n, x in enumerate(data)
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]
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]
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)
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)
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)
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)
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@@ -37,4 +37,4 @@ def parse_arguments():
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data = Summary()
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data = Summary()
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data.acquire()
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data.acquire()
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data.list(score, model)
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data.list_results(score, model)
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