-
Notifications
You must be signed in to change notification settings - Fork 92
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Merge pull request #958 from pierce314159/957_mimic_re
Closes #957: Mimic `re` library functionality applied to SegStrings
- Loading branch information
Showing
14 changed files
with
1,296 additions
and
261 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,231 @@ | ||
| from typing import cast | ||
| from arkouda.client import generic_msg | ||
| from arkouda.pdarrayclass import pdarray, create_pdarray | ||
| import json | ||
| from enum import Enum | ||
|
|
||
| MatchType = Enum('MatchType', ['SEARCH', 'MATCH', 'FULLMATCH']) | ||
|
|
||
| class Match: | ||
| def __init__(self, matched: pdarray, starts: pdarray, lengths: pdarray, indices: pdarray, | ||
| parent_bytes_name: str, parent_offsets_name: str, match_type: MatchType, pattern: str): | ||
| self._objtype = type(self).__name__ | ||
| self._parent_bytes_name = parent_bytes_name | ||
| self._parent_offsets_name = parent_offsets_name | ||
| self._match_type = match_type | ||
| self._matched = matched | ||
| self._starts = starts | ||
| self._lengths = lengths | ||
| self._ends = starts + lengths | ||
| self._indices = indices | ||
| self._parent_obj: object = None | ||
| self.re = pattern | ||
|
|
||
| def __str__(self): | ||
| from arkouda.client import pdarrayIterThresh | ||
| if self._matched.size <= pdarrayIterThresh: | ||
| vals = [self.__getitem__(i) for i in range(self._matched.size)] | ||
| else: | ||
| vals = [self.__getitem__(i) for i in range(3)] | ||
| vals.append('... ') | ||
| vals.extend([self.__getitem__(i) for i in range(self._matched.size - 3, self._matched.size)]) | ||
| return f"<ak.{self._objtype} object: {'; '.join(vals)}>" | ||
|
|
||
| def __getitem__(self, item): | ||
| return f"matched={self._matched[item]}, span=({self._starts[self._indices[item]]}, {self._ends[self._indices[item]]})" if self._matched[item] else f"matched={self._matched[item]}" | ||
|
|
||
| def __repr__(self): | ||
| return self.__str__() | ||
|
|
||
| def matched(self) -> pdarray: | ||
| """ | ||
| Returns a boolean array indiciating whether each element matched | ||
| Returns | ||
| ------- | ||
| pdarray, bool | ||
| True for elements that match, False otherwise | ||
| Examples | ||
| -------- | ||
| >>> strings = ak.array(['1_2___', '____', '3', '__4___5____6___7', '']) | ||
| >>> strings.search('_+').matched() | ||
| array([True True False True False]) | ||
| """ | ||
| return self._matched | ||
|
|
||
| def start(self) -> pdarray: | ||
| """ | ||
| Returns the starts of matches | ||
| Returns | ||
| ------- | ||
| pdarray, int64 | ||
| The start positions of matches | ||
| Examples | ||
| -------- | ||
| >>> strings = ak.array(['1_2___', '____', '3', '__4___5____6___7', '']) | ||
| >>> strings.search('_+').start() | ||
| array([1 0 0]) | ||
| """ | ||
| return self._starts | ||
|
|
||
| def end(self) -> pdarray: | ||
| """ | ||
| Returns the ends of matches | ||
| Returns | ||
| ------- | ||
| pdarray, int64 | ||
| The end positions of matches | ||
| Examples | ||
| -------- | ||
| >>> strings = ak.array(['1_2___', '____', '3', '__4___5____6___7', '']) | ||
| >>> strings.search('_+').end() | ||
| array([2 4 2]) | ||
| """ | ||
| return self._ends | ||
|
|
||
| def match_type(self) -> str: | ||
| """ | ||
| Returns the type of the Match object | ||
| Returns | ||
| ------- | ||
| str | ||
| MatchType of the Match object | ||
| Examples | ||
| -------- | ||
| >>> strings = ak.array(['1_2___', '____', '3', '__4___5____6___7', '']) | ||
| >>> strings.search('_+').match_type() | ||
| 'SEARCH' | ||
| """ | ||
| return self._match_type.name | ||
|
|
||
| def find_matches(self, return_match_origins: bool = False): | ||
| """ | ||
| Return all matches as a new Strings object | ||
| Parameters | ||
| ---------- | ||
| return_match_origins: bool | ||
| If True, return a pdarray containing the index of the original string each pattern match is from | ||
| Returns | ||
| ------- | ||
| Strings | ||
| Strings object containing only matches | ||
| pdarray, int64 (optional) | ||
| The index of the original string each pattern match is from | ||
| Raises | ||
| ------ | ||
| RuntimeError | ||
| Raised if there is a server-side error thrown | ||
| Examples | ||
| -------- | ||
| >>> strings = ak.array(['1_2___', '____', '3', '__4___5____6___7', '']) | ||
| >>> strings.search('_+').find_matches(return_match_origins=True) | ||
| (array(['_', '____', '__']), array([0 1 3])) | ||
| """ | ||
| from arkouda.strings import Strings | ||
| cmd = "segmentedFindAll" | ||
| args = "{} {} {} {} {} {} {} {}".format(self._objtype, | ||
| self._parent_offsets_name, | ||
| self._parent_bytes_name, | ||
| self._matched.name, | ||
| self._starts.name, | ||
| self._lengths.name, | ||
| self._indices.name, | ||
| return_match_origins) | ||
| repMsg = cast(str, generic_msg(cmd=cmd, args=args)) | ||
| if return_match_origins: | ||
| arrays = repMsg.split('+', maxsplit=2) | ||
| return Strings(arrays[0], arrays[1]), create_pdarray(arrays[2]) | ||
| else: | ||
| arrays = repMsg.split('+', maxsplit=1) | ||
| return Strings(arrays[0], arrays[1]) | ||
|
|
||
| def group(self, group_num: int = 0, return_group_origins: bool = False): | ||
| """ | ||
| Returns a new Strings containing the capture group corresponding to group_num. For the default, group_num=0, return the full match | ||
| Parameters | ||
| ---------- | ||
| group_num: int | ||
| The index of the capture group to be returned | ||
| return_group_origins: bool | ||
| If True, return a pdarray containing the index of the original string each capture group is from | ||
| Returns | ||
| ------- | ||
| Strings | ||
| Strings object containing only the capture groups corresponding to group_num | ||
| pdarray, int64 (optional) | ||
| The index of the original string each group is from | ||
| Examples | ||
| -------- | ||
| >>> strings = ak.array(["Isaac Newton, physicist", '<--calculus-->', 'Gottfried Leibniz, mathematician']) | ||
| >>> m = strings.search("(\\w+) (\\w+)") | ||
| >>> m.group() | ||
| array(['Isaac Newton', 'Gottfried Leibniz']) | ||
| >>> m.group(1) | ||
| array(['Isaac', 'Gottfried']) | ||
| >>> m.group(2, return_group_origins=True) | ||
| (array(['Newton', 'Leibniz']), array([0 2])) | ||
| """ | ||
| from arkouda.strings import Strings | ||
| from arkouda.client import regexMaxCaptures | ||
| if group_num < 0: | ||
| raise ValueError("group_num cannot be negative") | ||
| if group_num > regexMaxCaptures: | ||
| max_capture_flag = f'-e REGEX_MAX_CAPTURES={group_num}' | ||
| e = f"group_num={group_num} > regexMaxCaptures={regexMaxCaptures}. To run group({group_num}), recompile the server with flag '{max_capture_flag}'" | ||
| raise ValueError(e) | ||
|
|
||
| # We don't cache the locations of groups, find the location info and call findAll | ||
| cmd = "segmentedFindLoc" | ||
| args = "{} {} {} {} {}".format(self._objtype, | ||
| self._parent_offsets_name, | ||
| self._parent_bytes_name, | ||
| group_num, | ||
| json.dumps([self.re])) | ||
| repMsg = cast(str, generic_msg(cmd=cmd, args=args)) | ||
| created_map = json.loads(repMsg) | ||
| global_starts = create_pdarray(created_map["Starts"]) | ||
| global_lengths = create_pdarray(created_map["Lens"]) | ||
| global_indices = create_pdarray(created_map["Indices"]) | ||
| if self._match_type == MatchType.SEARCH: | ||
| matched = create_pdarray(created_map["SearchBool"]) | ||
| indices = create_pdarray(created_map["SearchInd"]) | ||
| elif self._match_type == MatchType.MATCH: | ||
| matched = create_pdarray(created_map["MatchBool"]) | ||
| indices = create_pdarray(created_map["MatchInd"]) | ||
| elif self._match_type == MatchType.FULLMATCH: | ||
| matched = create_pdarray(created_map["FullMatchBool"]) | ||
| indices = create_pdarray(created_map["FullMatchInd"]) | ||
| else: | ||
| raise ValueError(f"{self._match_type} is not a MatchType") | ||
| starts = global_starts[global_indices[matched]] | ||
| lengths = global_lengths[global_indices[matched]] | ||
| cmd = "segmentedFindAll" | ||
| args = "{} {} {} {} {} {} {} {}".format(self._objtype, | ||
| self._parent_offsets_name, | ||
| self._parent_bytes_name, | ||
| matched.name, | ||
| starts.name, | ||
| lengths.name, | ||
| indices.name, | ||
| return_group_origins) | ||
| repMsg = cast(str, generic_msg(cmd=cmd, args=args)) | ||
| if return_group_origins: | ||
| arrays = repMsg.split('+', maxsplit=2) | ||
| return Strings(arrays[0], arrays[1]), create_pdarray(arrays[2]) | ||
| else: | ||
| arrays = repMsg.split('+', maxsplit=1) | ||
| return Strings(arrays[0], arrays[1]) |
Oops, something went wrong.