| from datasets import Dataset |
|
|
|
|
| def only_nan(input:list) -> bool: |
| |
| c_input = [e for e in input if e==e and e!=" "] |
| if len(c_input) > 0: |
| return False |
| else: |
| return True |
|
|
| def shard_ds(ds:Dataset, size=1000) -> list[Dataset]: |
| if len(ds) < 1000: |
| ds_list = [ds] |
| else: |
| ds_list = [] |
| n_s = round(len(ds)/size) |
| indices = [i for i in range(n_s)] |
| for i in indices: |
| data_shard = ds.shard(num_shards=n_s, index = i) |
| ds_list.append(data_shard) |
| |
| return ds_list |
|
|
|
|
| def word_tokenize(text: str) -> list[str]: |
| """ |
| Tokenizes a string into words, splitting on whitespace and punctuation. |
| Example: |
| >>> word_tokenize("Hello, world!") |
| ['Hello', ',', 'world', '!'] |
| >>> word_tokenize("This is a test.") |
| ['This', 'is', 'a', 'test', '.'] |
| >>> word_tokenize("Many spaces between words.") |
| ['Many', 'spaces', 'between', 'words', '.'] |
| """ |
|
|
| punkt = [",", ".", "!", "?", ":", ";", "(", ")", "[", "]", "{", "}", '"', "'"] |
| for p in punkt: |
| text = text.replace(p, f" {p} ") |
| t = text.split() |
| return t |
|
|
| def remove_punkt_and_numbers(tokens:list[str]) -> list[str]: |
| punkt = [",", ".", "!", "?", ":", ";", "(", ")", "[", "]", "{", "}", '"', "'"] |
| tokens = [i.lower() for i in tokens if i not in punkt and i.isalpha()] |
| return tokens |
|
|
|
|
| def count_tokens_and_words(page:Dataset,colname:str,wordlist:list[str])-> Dataset: |
| """returns all token count including numbers and punctuation, |
| as well as relation of dictionary items to all tokens (measures general quality), |
| and relation of dictionary items to only alphabetic words (measures difference between ocr methods) |
| """ |
|
|
| toks = word_tokenize(page[colname]) |
| a_toks = remove_punkt_and_numbers(toks) |
| t_length = len(toks) |
|
|
| punkt = [",", ".", "!", "?", ":", ";", "(", ")", "[", "]", "{", "}", '"', "'"] |
| t_punkt = [i for i in toks if i in punkt] |
| n_punkt = len(t_punkt) |
|
|
| word_c = [i for i in a_toks if i in wordlist] |
| if len(a_toks) == 0: |
| wc_rel = 0.0 |
| wc_a_rel = 0.0 |
| else: |
| wc_rel = round(len(word_c)/len(toks),4) |
| wc_a_rel = round(len(word_c)/len(a_toks),4) |
|
|
| t_name = colname + "_n_tokens" |
| wc_name = colname + "_rel_words" |
| wc_a_name = colname + "_rel_a_words" |
| p_t_name = colname + "_punkt_tokens" |
| a_t_name = colname + "_a_tokens" |
|
|
| page.update({t_name:t_length, |
| wc_name:wc_rel, |
| wc_a_name:wc_a_rel, |
| p_t_name:n_punkt, |
| a_t_name:len(a_toks)}) |
| |
| return page |
|
|
|
|
| def make_year_list(start_year: int, stop_year: int) -> list[str]: |
| """make a list of file names based on years""" |
| year_list = list(range(start_year, stop_year + 1)) |
| year_list = [str(i) for i in year_list] |
| return year_list |
|
|
