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Merge pull request #111 from stweil/typos
Fix some typos (found by `codespell` and `typos`)
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commit
dc4565fd2d
4 changed files with 6 additions and 6 deletions
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@ -100,11 +100,11 @@ This generates `summary.html` and `summary.json` in the same `output_folder`.
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If you are summarizing many reports and have used the `--differences` flag while
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generating them, it may be useful to limit the number of differences reported by using
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the `--occurences-threshold` parameter. This will reduce the size of the generated HTML
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the `--occurrences-threshold` parameter. This will reduce the size of the generated HTML
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report, making it easier to open and navigate. Note that the JSON report will still
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contain all differences. Example:
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~~~
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dinglehopper-summarize output_folder/ --occurences-threshold 10
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dinglehopper-summarize output_folder/ --occurrences-threshold 10
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~~~
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### dinglehopper-line-dirs
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@ -329,7 +329,7 @@ def get_attr(te: Any, attr_name: str) -> float:
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"""Extract the attribute for the given name.
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Note: currently only handles numeric values!
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Other or non existend values are encoded as np.nan.
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Other or non existent values are encoded as np.nan.
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"""
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attr_value = te.attrib.get(attr_name)
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try:
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@ -391,7 +391,7 @@
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"\\text{CER} = \\frac{i + s + d}{n}\n",
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"$$\n",
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"\n",
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"where $i$ is the number of inserts, $s$ the number of substitutions, $d$ the number of deletions and $n$ is the number of characters in the reference text. (The text is not super clear about $n$ being the number of characters in the reference text, but it seems appropiate as they *are* clear about this when computing the word error rate.)"
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"where $i$ is the number of inserts, $s$ the number of substitutions, $d$ the number of deletions and $n$ is the number of characters in the reference text. (The text is not super clear about $n$ being the number of characters in the reference text, but it seems appropriate as they *are* clear about this when computing the word error rate.)"
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]
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},
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{
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@ -680,7 +680,7 @@
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" return cat in unwanted_categories or subcat in unwanted_subcategories\n",
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"\n",
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" # We follow Unicode Standard Annex #29 on Unicode Text Segmentation here: Split on word boundaries using\n",
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" # uniseg.wordbreak.words() and ignore all \"words\" that contain only whitespace, punctation \"or similar characters.\"\n",
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" # uniseg.wordbreak.words() and ignore all \"words\" that contain only whitespace, punctuation \"or similar characters.\"\n",
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" for word in uniseg.wordbreak.words(s):\n",
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" if all(unwanted(c) for c in word):\n",
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" pass\n",
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@ -54,7 +54,7 @@ def words(s: str) -> Generator[str, None, None]:
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# We follow Unicode Standard Annex #29 on Unicode Text Segmentation here: Split on
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# word boundaries using uniseg.wordbreak.words() and ignore all "words" that contain
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# only whitespace, punctation "or similar characters."
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# only whitespace, punctuation "or similar characters."
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for word in uniseg.wordbreak.words(s):
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if all(unwanted(c) for c in word):
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pass
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