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kuhy overruled the "do not fix coursework to be better than it was submitted" rule: git history is the archive, so the working tree can be clean. This lands the config and the mechanical half of the cleanup -- 9,281 ruff findings under the fleet config down to 3,686, with no per-file-ignores anywhere. What is in here: - pyproject.toml, the first one in this repo. select = ["ALL"], mypy strict, and the vendored list mirrored into ruff exclude and coverage omit. Five rules are off and each says why; CPY001 is the only judgement call, because stamping a copyright header onto 137 university assignments would assert a licence that was never claimed. No hook is wired up yet -- a gate lands only once its subject is clean. - ruff format + the safe fixes, then a second pass over the docstring rules ruff marks unsafe (they only edit docstring text). 108 files. - TRAK/sightpy is vendored, not coursework: it is rafael-fuente/Python-Raytracer (BSD 3-Clause). Verified against a fresh upstream clone with line endings normalised -- 30 of 32 files byte-identical, ray.py and scene.py carrying a 12- and 13-line local patch that counts rays for the report. 35 files that should never have been linted, now excluded and restored. - WDWR, SPD, MOM and ECRYPT are fully clean, by hand and verified by running them: WDWR's three plot scripts print the same statistics as before, MOM's PuLP model solves to the same cost. WDWR's graph.py had a 342-character CSV header embedded as a string literal, which cannot be wrapped -- the data moved to data/pareto_front.csv. Two 0-byte .py stubs are deleted; an empty file is not a deliverable and git still has it. Three harness bugs found by actually running things: - `run` now forces MPLBACKEND=Agg. TRAK finished its ray trace in 37 seconds and then sat for 45 minutes: plt.show() had opened an image viewer and was waiting for someone to close the window. - TRAK's main.py only pops that viewer with --show now, and its runner writes to a gitignored build/ via the new --entry-args. The default output path is outputs/output.png, which is TRACKED -- a plain run overwrote a submitted deliverable. - course_lib.sh was 357 lines, over this repo's own cap. Split into course_probe.sh and course_run.sh. Verified: ECOTE 26 tests pass, ECRYPT_PROJECT 99 pass, TRAK renders cornell_box in 37s and exits 0, every module compiles, and every import ruff removed was checked to be genuinely unused. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0172dj34FDpao6wsix8ZuCzE
165 lines
5.6 KiB
Python
165 lines
5.6 KiB
Python
import copy
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import re
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import pandas as pd
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import processing
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# input file name
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file_path = "alignments_unformatted_headlines.txt"
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# output file path
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output_file_path = "headlines_fixed_format.wa"
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# paths to headlines database
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chunked_path1 = "test_goldStandard/headlines/STSint.testinput.headlines.sent1.chunk.txt"
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chunked_path2 = "test_goldStandard/headlines/STSint.testinput.headlines.sent1.chunk.txt"
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alignment_path = "test_goldStandard/headlines/STSint.testinput.headlines.wa"
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# paths to students andsewrs database
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# chunked_path1 = "test_goldStandard/student/STSint.testinput.answers-students.sent1.chunk.txt"
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# chunked_path2 = "test_goldStandard/student/STSint.testinput.answers-students.sent2.chunk.txt"
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# alignment_path = "test_goldStandard/student/STSint.testinput.answers-students.wa"
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# load data
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goldstandard_chunked = processing.load_chunked(chunked_path1, chunked_path2)
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goldstandard_alignment = processing.load_alignment(alignment_path)
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# get a nice table
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data = pd.merge(
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goldstandard_chunked, goldstandard_alignment, left_index=True, right_index=True
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)
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# open generated alignments
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with open(file_path) as file:
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responses = [eval(line.strip()) for line in file]
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for i, r in enumerate(responses):
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print("\nresponse number " + str(i))
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print(r)
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unformatted = copy.deepcopy(responses)
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for i, response in enumerate(responses):
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temp = response.lstrip("\n")
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temp = temp.rstrip("\n")
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temp = re.sub(r"(?<==)>", "> ", temp) # add space after >
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temp = re.sub(r"(?<!\n) +(?!\n)", " ", temp) # remove double space
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temp = temp.replace("]", "")
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temp = temp.replace("[", "")
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temp = temp.replace("'", "")
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temp = temp.replace(" ==> ", " <==> ")
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temp = temp.replace(" => ", " <==> ")
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temp = temp.replace(" <=> ", " <==> ")
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temp = temp.replace(" <== ", " <==> ")
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temp = temp.replace("<==> //", " <==> 0 //")
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temp = temp.replace("NOALI <==>", "0 <==>")
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temp = temp.replace("<==> NOALI", "<==> 0")
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temp = temp.replace("\n// NOALI", "\n0 <==> 0 // NOALI")
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temp = temp.replace("\n // ", "\n0 <==> ")
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temp = temp.replace("\n// ", "\n0 <==> ")
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temp = re.sub(r"(^|[^<])(==>+)", r" <==>", temp)
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temp = temp.replace("// - //", "// 0 //")
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temp = temp.replace("// score", "// ")
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temp = temp.replace("// alignment type", "// NOALI")
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temp = temp.replace("> -", "> 0")
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temp = temp.replace("- <", "0 <")
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temp = temp.replace("// //", "// NOALI //")
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temp = temp.replace("equi", "EQUI")
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temp = re.sub(r"\d\. ", "", temp) # remove 1., 2. ...
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temp = temp.upper()
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temp = re.sub(r"^(<==>)", r"0 \1", temp)
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temp = re.sub(r"(?<!\n) +(?!\n)", " ", temp) # remove double space
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temp = temp.split("\n")
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for k, t in enumerate(temp):
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if "<==>" not in t:
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temp[k] = "0 <==> " + temp[k]
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temp[k] = temp[k].split("<==>")
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temp[k] = [temp[k][0], *temp[k][1].split("//")]
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chunk1arr = data.iloc[i]["chunked_sentance1"]
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q = 1
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numberList = []
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for chunk in chunk1arr:
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chunk = re.sub(r"(?<!\n) +(?!\n)", " ", chunk)
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n_of_words = len(chunk.strip().split(" "))
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index_str = ""
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for qq in range(q, q + n_of_words):
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index_str = index_str + str(qq) + " "
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numberList.append(index_str)
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q = q + n_of_words
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for j, chunk in enumerate(data.iloc[i]["chunked_sentance1"]):
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pattern = re.compile(chunk, re.IGNORECASE)
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temp[k][0] = pattern.sub(numberList[j], temp[k][0])
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chunk1arr = data.iloc[i]["chunked_sentance2"]
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q = 1
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numberList = []
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for chunk in chunk1arr:
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chunk = re.sub(r"(?<!\n) +(?!\n)", " ", chunk)
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n_of_words = len(chunk.strip().split(" "))
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index_str = ""
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for qq in range(q, q + n_of_words):
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index_str = index_str + str(qq) + " "
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numberList.append(index_str)
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q = q + n_of_words
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for j, chunk in enumerate(data.iloc[i]["chunked_sentance2"]):
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pattern = re.compile(chunk, re.IGNORECASE)
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temp[k][1] = pattern.sub(numberList[j], temp[k][1])
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if any(char.isalpha() and ord(char) < 128 for char in temp[k][0]) or any(
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char.isalpha() and ord(char) < 128 for char in temp[k][1]
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):
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temp[k] = ""
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if len(temp[k]) >= 4:
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temp[k][3] = temp[k][3].replace("NOALI", "0")
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if temp[k][3] == "":
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temp[k][3] = " 0 "
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if temp[k][3] == " ":
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temp[k][3] = " 0 "
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temp[k] = (
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temp[k][0]
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+ " <==> "
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+ temp[k][1]
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+ " // "
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+ temp[k][2]
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+ " // "
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+ temp[k][3]
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)
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elif len(temp[k]) == 3:
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temp[k] = temp[k][0] + " <==> " + temp[k][1] + " // " + temp[k][2] + " // 0"
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temp[k] = re.sub(r"\s{2,}", " ", temp[k]) # remove double space
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temp = [x for x in temp if x != ""]
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responses[i] = "\n".join(temp).strip()
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indexes = []
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responses_final = []
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rejected_indexes = []
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for n, r in enumerate(responses):
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if r == "":
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rejected_indexes.append(n + 1)
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continue
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if r == "\n":
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rejected_indexes.append(n + 1)
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continue
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indexes.append(n + 1)
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responses_final.append(r)
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print("rejected indexes:")
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print(rejected_indexes)
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with open(output_file_path, "w") as file:
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for i, r in zip(indexes, responses_final):
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file.write('<sentence id="' + str(i + 1) + '" status="">\n')
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file.write("<alignment>\n")
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file.write(r)
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file.write("\n</alignment>\n")
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file.write("</sentence>\n\n")
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