From bc6e005f091a19b51e0f202db4b78bad23784452 Mon Sep 17 00:00:00 2001 From: kuchenrolle Date: Wed, 31 Jan 2018 15:56:44 +0000 Subject: [PATCH 1/6] add option to set temporary directory --- pyndl/ndl.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/pyndl/ndl.py b/pyndl/ndl.py index cd02ad3..903d5db 100644 --- a/pyndl/ndl.py +++ b/pyndl/ndl.py @@ -56,7 +56,7 @@ def events_from_file(event_path): def ndl(events, alpha, betas, lambda_=1.0, *, method='openmp', weights=None, number_of_threads=8, len_sublists=10, remove_duplicates=None, - verbose=False): + verbose=False, temporary_directory=None): """ Calculate the weights for all_outcomes over all events in event_file given by the files path. @@ -89,6 +89,10 @@ def ndl(events, alpha, betas, lambda_=1.0, *, preferred!) verbose : bool print some output if True. + temporary_directory : str + path to directory to use for storing temporary files created; + if none is provided, the operating system's default will + be used (/tmp on unix) Returns ------- @@ -155,7 +159,7 @@ def ndl(events, alpha, betas, lambda_=1.0, *, beta1, beta2 = betas - with tempfile.TemporaryDirectory(prefix="pyndl") as binary_path: + with tempfile.TemporaryDirectory(prefix="pyndl", dir=temporary_directory) as binary_path: number_events = preprocess.create_binary_event_files(events, binary_path, cue_map, outcome_map, overwrite=True, number_of_processes=number_of_threads, From 73c86d1b9a1924a777a438d12634c55fd4304530 Mon Sep 17 00:00:00 2001 From: kuchenrolle Date: Sat, 10 Feb 2018 17:30:26 +0000 Subject: [PATCH 2/6] change version, add test for providing temporary directory --- pyndl/__init__.py | 2 +- tests/test_ndl.py | 8 ++++++++ 2 files changed, 9 insertions(+), 1 deletion(-) diff --git a/pyndl/__init__.py b/pyndl/__init__.py index 9f4f5c6..026b430 100644 --- a/pyndl/__init__.py +++ b/pyndl/__init__.py @@ -17,7 +17,7 @@ __author__ = ('Konstantin Sering, Marc Weitz, ' 'David-Elias Künstle, Lennard Schneider') __author_email__ = 'konstantin.sering@uni-tuebingen.de' -__version__ = '0.4.0' +__version__ = '0.4.1' __license__ = 'MIT' __description__ = ('Naive discriminative learning implements learning and ' 'classification models based on the Rescorla-Wagner ' diff --git a/tests/test_ndl.py b/tests/test_ndl.py index 57170f8..cff67fa 100644 --- a/tests/test_ndl.py +++ b/tests/test_ndl.py @@ -124,6 +124,9 @@ def test_exceptions(): ndl.ndl(FILE_PATH_SIMPLE, ALPHA, BETAS, remove_duplicates="magic") assert e_info == "remove_duplicates must be None, True or False" + with pytest.raises(FileNotFoundError, match="No such file or directory") as e_info: + ndl.ndl(FILE_PATH_SIMPLE, ALPHA, BETAS, temporary_directory="./magic") + def test_continue_learning_dict(): events_simple = pd.read_csv(FILE_PATH_SIMPLE, sep="\t") @@ -217,6 +220,11 @@ def test_return_values(result_dict_ndl, result_dict_ndl_data_array, result_ndl_t assert isinstance(result_ndl_threading, xr.DataArray) +def test_provide_temporary_directory(): + with tempfile.TemporaryDirectory(dir=TMP_PATH) as temporary_directory: + result = ndl.ndl(FILE_PATH_SIMPLE, ALPHA, BETAS, temporary_directory=temporary_directory) + + # Test internal consistency def test_dict_ndl_vs_ndl_threading(result_dict_ndl, result_ndl_threading): From ab6aa54511f2fe6bbfed8a7476e5207d3eb08e22 Mon Sep 17 00:00:00 2001 From: kuchenrolle Date: Sat, 10 Feb 2018 19:10:13 +0000 Subject: [PATCH 3/6] Revert "change version, add test for providing temporary directory" This reverts commit 73c86d1b9a1924a777a438d12634c55fd4304530. --- pyndl/__init__.py | 2 +- tests/test_ndl.py | 8 -------- 2 files changed, 1 insertion(+), 9 deletions(-) diff --git a/pyndl/__init__.py b/pyndl/__init__.py index 026b430..9f4f5c6 100644 --- a/pyndl/__init__.py +++ b/pyndl/__init__.py @@ -17,7 +17,7 @@ __author__ = ('Konstantin Sering, Marc Weitz, ' 'David-Elias Künstle, Lennard Schneider') __author_email__ = 'konstantin.sering@uni-tuebingen.de' -__version__ = '0.4.1' +__version__ = '0.4.0' __license__ = 'MIT' __description__ = ('Naive discriminative learning implements learning and ' 'classification models based on the Rescorla-Wagner ' diff --git a/tests/test_ndl.py b/tests/test_ndl.py index cff67fa..57170f8 100644 --- a/tests/test_ndl.py +++ b/tests/test_ndl.py @@ -124,9 +124,6 @@ def test_exceptions(): ndl.ndl(FILE_PATH_SIMPLE, ALPHA, BETAS, remove_duplicates="magic") assert e_info == "remove_duplicates must be None, True or False" - with pytest.raises(FileNotFoundError, match="No such file or directory") as e_info: - ndl.ndl(FILE_PATH_SIMPLE, ALPHA, BETAS, temporary_directory="./magic") - def test_continue_learning_dict(): events_simple = pd.read_csv(FILE_PATH_SIMPLE, sep="\t") @@ -220,11 +217,6 @@ def test_return_values(result_dict_ndl, result_dict_ndl_data_array, result_ndl_t assert isinstance(result_ndl_threading, xr.DataArray) -def test_provide_temporary_directory(): - with tempfile.TemporaryDirectory(dir=TMP_PATH) as temporary_directory: - result = ndl.ndl(FILE_PATH_SIMPLE, ALPHA, BETAS, temporary_directory=temporary_directory) - - # Test internal consistency def test_dict_ndl_vs_ndl_threading(result_dict_ndl, result_ndl_threading): From 329e641f09aec0727486d9c63fd0085286ad3ba0 Mon Sep 17 00:00:00 2001 From: kuchenrolle Date: Sat, 10 Feb 2018 19:26:52 +0000 Subject: [PATCH 4/6] change version, add test for providing temporary directory --- pyndl/__init__.py | 2 +- tests/test_ndl.py | 8 ++++++++ 2 files changed, 9 insertions(+), 1 deletion(-) diff --git a/pyndl/__init__.py b/pyndl/__init__.py index 026b430..64a9b96 100644 --- a/pyndl/__init__.py +++ b/pyndl/__init__.py @@ -17,7 +17,7 @@ __author__ = ('Konstantin Sering, Marc Weitz, ' 'David-Elias Künstle, Lennard Schneider') __author_email__ = 'konstantin.sering@uni-tuebingen.de' -__version__ = '0.4.1' +__version__ = '0.4.2' __license__ = 'MIT' __description__ = ('Naive discriminative learning implements learning and ' 'classification models based on the Rescorla-Wagner ' diff --git a/tests/test_ndl.py b/tests/test_ndl.py index 57170f8..95394b3 100644 --- a/tests/test_ndl.py +++ b/tests/test_ndl.py @@ -124,6 +124,9 @@ def test_exceptions(): ndl.ndl(FILE_PATH_SIMPLE, ALPHA, BETAS, remove_duplicates="magic") assert e_info == "remove_duplicates must be None, True or False" + with pytest.raises(FileNotFoundError, match="No such file or directory") as e_info: + ndl.ndl(FILE_PATH_SIMPLE, ALPHA, BETAS, temporary_directory="./magic") + def test_continue_learning_dict(): events_simple = pd.read_csv(FILE_PATH_SIMPLE, sep="\t") @@ -217,6 +220,11 @@ def test_return_values(result_dict_ndl, result_dict_ndl_data_array, result_ndl_t assert isinstance(result_ndl_threading, xr.DataArray) +def test_provide_temporary_directory(): + with tempfile.TemporaryDirectory(dir=TMP_PATH) as temporary_directory: + ndl.ndl(FILE_PATH_SIMPLE, ALPHA, BETAS, temporary_directory=temporary_directory) + + # Test internal consistency def test_dict_ndl_vs_ndl_threading(result_dict_ndl, result_ndl_threading): From 64c70fe29e86435f2135afbfd771d9dbe017cec9 Mon Sep 17 00:00:00 2001 From: kuchenrolle Date: Wed, 14 Feb 2018 14:54:38 +0000 Subject: [PATCH 5/6] remove duplicate outcomes. simplify occurrence generation and processing. --- pyndl/__init__.py | 2 +- pyndl/preprocess.py | 96 ++++++++++++++++----------------------------- 2 files changed, 34 insertions(+), 64 deletions(-) diff --git a/pyndl/__init__.py b/pyndl/__init__.py index 64a9b96..83e4ef2 100644 --- a/pyndl/__init__.py +++ b/pyndl/__init__.py @@ -17,7 +17,7 @@ __author__ = ('Konstantin Sering, Marc Weitz, ' 'David-Elias Künstle, Lennard Schneider') __author_email__ = 'konstantin.sering@uni-tuebingen.de' -__version__ = '0.4.2' +__version__ = '0.4.3' __license__ = 'MIT' __description__ = ('Naive discriminative learning implements learning and ' 'classification models based on the Rescorla-Wagner ' diff --git a/pyndl/preprocess.py b/pyndl/preprocess.py index cc0eabe..2da8345 100644 --- a/pyndl/preprocess.py +++ b/pyndl/preprocess.py @@ -91,36 +91,29 @@ def process_occurrences(occurrences, outfile, *, if True make cues and outcomes per event unique """ - if cue_structure == "bigrams_to_word": - for cues, outcomes in occurrences: - if cues and outcomes: - occurrence = cues + '_' + outcomes - else: # take either - occurrence = cues + outcomes - phrase_string = "#" + re.sub("_", "#", occurrence) + "#" - bigrams = (phrase_string[i:(i + 2)] for i in - range(len(phrase_string) - 2 + 1)) - if not bigrams or not occurrence: - continue - if remove_duplicates: - outfile.write("_".join(set(bigrams)) + "\t" + occurrence + "\n") - else: - outfile.write("_".join(bigrams) + "\t" + occurrence + "\n") - elif cue_structure == "trigrams_to_word": + if cue_structure in ("bigrams_to_word", "trigrams_to_word"): + if cue_structure == "bigrams_to_word": + gram_size = 2 + else: + gram_size = 3 + for cues, outcomes in occurrences: if cues and outcomes: occurrence = cues + '_' + outcomes else: # take either occurrence = cues + outcomes phrase_string = "#" + re.sub("_", "#", occurrence) + "#" - trigrams = (phrase_string[i:(i + 3)] for i in - range(len(phrase_string) - 3 + 1)) - if not trigrams or not occurrence: + n_grams = (phrase_string[i:(i + gram_size)] for i in + range(len(phrase_string) - gram_size + 1)) + if not n_grams or not occurrence: continue if remove_duplicates: - outfile.write("_".join(set(trigrams)) + "\t" + occurrence + "\n") + n_grams = "_".join(set(n_grams)) + occurrence = "_".join(set(occurrence.split("_"))) + outfile.write(n_grams + "\t" + occurrence + "\n") else: - outfile.write("_".join(trigrams) + "\t" + occurrence + "\n") + outfile.write("_".join(n_grams) + "\t" + occurrence + "\n") + elif cue_structure == "word_to_word": for cues, outcomes in occurrences: if not cues: @@ -239,19 +232,16 @@ def gen_occurrences(words): """ if event_structure == 'consecutive_words': occurrences = list() - cur_words = list() - ii = 0 - while True: - if ii < len(words): - cur_words.append(words[ii]) - if ii >= len(words) or ii >= number_of_words: - # remove the first word - cur_words = cur_words[1:] + # can't have more consecutive words than total words + length = min(number_of_words, len(words)) + # slide window over list of words + for ii in range(1 - length, len(words)): + # no consecutive words before first word + start = max(ii, 0) + # no consecutive words after last word + end = min(ii + length, len(words)) # append (cues, outcomes) with empty outcomes - occurrences.append(("_".join(cur_words), '')) - ii += 1 - if not cur_words: - break + occurrences.append(("_".join(words[start:end]), "")) return occurrences # for words = (A, B, C, D); before = 2, after = 1 # make: (B, A), (A_C, B), (A_B_D, C), (B_C, D) @@ -267,7 +257,7 @@ def gen_occurrences(words): return occurrences elif event_structure == 'line': # (cues, outcomes) with empty outcomes - return [('_'.join(words), ''), ] + return [('_'.join(words), '')] def process_line(line): """processes one line of text.""" @@ -288,13 +278,6 @@ def process_words(words): cue_structure=cue_structure, remove_duplicates=remove_duplicates) - def process_context(line): - """called when a context boundary is found.""" - if context_structure == 'document': - # remove document marker - line = context_pattern.sub("", line) - return line - with open(corpus_file, "rt") as corpus: with gzip.open(event_file, "wt") as outfile: outfile.write("cues\toutcomes\n") @@ -313,29 +296,16 @@ def process_context(line): process_words(words) else: if context_pattern.search(line) is not None: - # process the first context - context1, *contexts = context_pattern.split(line) - context1 = process_context(context1) - - if context1.strip(): - context1 = process_line(context1.strip()) - words.extend(gen_words(context1)) - process_words(words) - # process in between contexts - while len(contexts) > 1: - words = [] - context1, *contexts = contexts - context1 = process_context(context1) - if context1.strip(): - context1 = process_line(context1.strip()) - words.extend(gen_words(context1)) + contexts = context_pattern.split(line) + + # process contexts; only extend words on last context + for ii, context in enumerate(contexts): + context = process_line(context.strip()) + words.extend(gen_words(context)) + if ii < len(contexts): process_words(words) - # add last part to next context - context1 = contexts[0] - context1 = process_context(context1) - if context1.strip(): - context1 = process_line(context1.strip()) - words.extend(gen_words(context1)) + words = [] + else: line = process_line(line) words.extend(gen_words(line)) From 51115c68a567f335ba9119c02ba0e8d09d9a3223 Mon Sep 17 00:00:00 2001 From: "Konstantin (Tino) Sering" Date: Thu, 1 Mar 2018 13:29:44 +0100 Subject: [PATCH 6/6] reinserts correction for multiple outcomes back into the code; corrects tests accordingly --- pyndl/preprocess.py | 14 ++++++++------ setup.cfg | 2 +- .../event_file_bigrams_to_word.tab.gz | Bin 43039 -> 42537 bytes .../event_file_trigrams_to_word.tab.gz | Bin 52586 -> 52125 bytes ...nt_file_trigrams_to_word_line_based.tab.gz | Bin 10567 -> 8437 bytes 5 files changed, 9 insertions(+), 7 deletions(-) diff --git a/pyndl/preprocess.py b/pyndl/preprocess.py index d3023ca..b530dfb 100644 --- a/pyndl/preprocess.py +++ b/pyndl/preprocess.py @@ -100,9 +100,9 @@ def ngrams_to_word(occurrences, n_chars, outfile, remove_duplicates=True): if not ngrams or not occurrence: continue if remove_duplicates: - outfile.write("{}\t{}\n".format("_".join(set(ngrams)), occurrence)) - else: - outfile.write("{}\t{}\n".format("_".join(ngrams), occurrence)) + ngrams = set(ngrams) + occurrence = "_".join(set(occurrence.split("_"))) + outfile.write("{}\t{}\n".format("_".join(ngrams), occurrence)) def process_occurrences(occurrences, outfile, *, @@ -270,7 +270,9 @@ def gen_occurrences(words): return occurrences elif event_structure == 'line': # (cues, outcomes) with empty outcomes - return [('_'.join(words), '')] + return [('_'.join(words), ''), ] + else: + raise ValueError('gen_occurrences should be one of {"consecutive_words", "word_to_word", "line"}') def process_line(line): """processes one line of text.""" @@ -312,10 +314,10 @@ def process_words(words): contexts = context_pattern.split(line) # process contexts; only extend words on last context - for ii, context in enumerate(contexts): + for jj, context in enumerate(contexts): context = process_line(context.strip()) words.extend(gen_words(context)) - if ii < len(contexts): + if jj < len(contexts): process_words(words) words = [] diff --git a/setup.cfg b/setup.cfg index dafbe18..b061ab0 100644 --- a/setup.cfg +++ b/setup.cfg @@ -4,7 +4,7 @@ max-line-length = 120 [pylint] max-line-length = 120 -good-names = nn, ii, _ +good-names = nn, ii, _, jj extension-pkg-whitelist=numpy,pyndl.ndl_parallel ignore=pyndl/ndl_parallel disable=E1101 diff --git a/tests/reference/event_file_bigrams_to_word.tab.gz 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