hexsha
stringlengths
40
40
repo
stringlengths
7
114
path
stringlengths
4
124
license
listlengths
1
9
language
stringclasses
1 value
identifier
stringlengths
1
71
return_type
stringlengths
1
749
original_string
stringlengths
76
22.7k
original_docstring
stringlengths
16
7.61k
docstring
stringlengths
16
2.47k
docstring_tokens
listlengths
6
477
code
stringlengths
14
10.2k
code_tokens
listlengths
6
996
short_docstring
stringlengths
2
644
short_docstring_tokens
listlengths
1
116
comment
listlengths
1
89
parameters
listlengths
0
64
docstring_params
dict
71d8ce9b4beda07cb1798c46ad84b05919859d18
TrialAndErrror/TnE_Assistant
src/Assistant.py
[ "MIT" ]
Python
perform_action
null
def perform_action(command_action): """ Process command and perform the corresponding action. This is the core decision-making process behind the Assistant. :param command_action: str :return: None """ command_word, phrase = get_first_word_and_phrase_from(command_action) """ Get fi...
Process command and perform the corresponding action. This is the core decision-making process behind the Assistant. :param command_action: str :return: None
Process command and perform the corresponding action. This is the core decision-making process behind the Assistant.
[ "Process", "command", "and", "perform", "the", "corresponding", "action", ".", "This", "is", "the", "core", "decision", "-", "making", "process", "behind", "the", "Assistant", "." ]
def perform_action(command_action): command_word, phrase = get_first_word_and_phrase_from(command_action) chosen_action = determine_command_type(command_word) if chosen_action == 'play': logging.debug(f'Recognized {command_word} as Play; playing {phrase}') play_youtube_video_for(phrase) ...
[ "def", "perform_action", "(", "command_action", ")", ":", "command_word", ",", "phrase", "=", "get_first_word_and_phrase_from", "(", "command_action", ")", "\"\"\"\n Get first word and phrase. \n 'phrase' has had helper words removed and whitespace stripped.\n \n Run the dete...
Process command and perform the corresponding action.
[ "Process", "command", "and", "perform", "the", "corresponding", "action", "." ]
[ "\"\"\"\n Process command and perform the corresponding action.\n This is the core decision-making process behind the Assistant.\n\n :param command_action: str\n :return: None\n \"\"\"", "\"\"\"\n Get first word and phrase. \n 'phrase' has had helper words removed and whitespace stripped.\n ...
[ { "param": "command_action", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "command_action", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": nu...
71d8ce9b4beda07cb1798c46ad84b05919859d18
TrialAndErrror/TnE_Assistant
src/Assistant.py
[ "MIT" ]
Python
determine_command_type
<not_specific>
def determine_command_type(command_word): """ Check Settings to get the list of available commands (or default to these lists if no settings found). By default, the :param command_word: :return: """ default_play_commands = ['play'] default_wiki_commands = ['wiki', 'what', 'who'] def...
Check Settings to get the list of available commands (or default to these lists if no settings found). By default, the :param command_word: :return:
Check Settings to get the list of available commands (or default to these lists if no settings found). By default, the
[ "Check", "Settings", "to", "get", "the", "list", "of", "available", "commands", "(", "or", "default", "to", "these", "lists", "if", "no", "settings", "found", ")", ".", "By", "default", "the" ]
def determine_command_type(command_word): default_play_commands = ['play'] default_wiki_commands = ['wiki', 'what', 'who'] default_search_commands = ['search', 'find', 'google'] default_open_commands = ['open'] chosen_action = 'catchall' actions_list = [ PLAY_SETTINGS.get('Commands', def...
[ "def", "determine_command_type", "(", "command_word", ")", ":", "default_play_commands", "=", "[", "'play'", "]", "default_wiki_commands", "=", "[", "'wiki'", ",", "'what'", ",", "'who'", "]", "default_search_commands", "=", "[", "'search'", ",", "'find'", ",", ...
Check Settings to get the list of available commands (or default to these lists if no settings found).
[ "Check", "Settings", "to", "get", "the", "list", "of", "available", "commands", "(", "or", "default", "to", "these", "lists", "if", "no", "settings", "found", ")", "." ]
[ "\"\"\"\n Check Settings to get the list of available commands (or default to these lists if no settings found).\n\n By default, the\n :param command_word:\n :return:\n \"\"\"", "\"\"\"\n Actions list is a list of all of the options of command words that can trigger that particular action.\n ...
[ { "param": "command_word", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "command_word", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null...
b46707b42d15d184fe856fbf4ce278fd8f2d3fc4
TrialAndErrror/TnE_Assistant
src/Tools/process_command.py
[ "MIT" ]
Python
cut_wake_word_from_command
<not_specific>
def cut_wake_word_from_command(command): """ Removes trigger from command using string split on the command string. Converts command to lowercase. Returns the rest of the command string after removing the trigger. :param trigger: str :param command: str :return: str """ trigger = ...
Removes trigger from command using string split on the command string. Converts command to lowercase. Returns the rest of the command string after removing the trigger. :param trigger: str :param command: str :return: str
Removes trigger from command using string split on the command string. Converts command to lowercase. Returns the rest of the command string after removing the trigger.
[ "Removes", "trigger", "from", "command", "using", "string", "split", "on", "the", "command", "string", ".", "Converts", "command", "to", "lowercase", ".", "Returns", "the", "rest", "of", "the", "command", "string", "after", "removing", "the", "trigger", "." ]
def cut_wake_word_from_command(command): trigger = get_trigger_command() command_action = command.split(f' {trigger} ')[1].lower() logging.debug(f'Trigger command ({trigger}) removed from ({command})') logging.debug(f'Returning {command_action} as command_action') return command_action
[ "def", "cut_wake_word_from_command", "(", "command", ")", ":", "trigger", "=", "get_trigger_command", "(", ")", "command_action", "=", "command", ".", "split", "(", "f' {trigger} '", ")", "[", "1", "]", ".", "lower", "(", ")", "logging", ".", "debug", "(", ...
Removes trigger from command using string split on the command string.
[ "Removes", "trigger", "from", "command", "using", "string", "split", "on", "the", "command", "string", "." ]
[ "\"\"\"\n Removes trigger from command using string split on the command string.\n\n Converts command to lowercase.\n\n Returns the rest of the command string after removing the trigger.\n\n :param trigger: str\n :param command: str\n :return: str\n \"\"\"" ]
[ { "param": "command", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "command", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
b46707b42d15d184fe856fbf4ce278fd8f2d3fc4
TrialAndErrror/TnE_Assistant
src/Tools/process_command.py
[ "MIT" ]
Python
remove_helper_words
<not_specific>
def remove_helper_words(phrase: str): """ Remove helper words from the beginning of param phrase. Removes whitespace before and after removing words. Returns cleaned phrase. This is a part that could use some improvement or a new library integration. :param phrase: str :return: phrase: st...
Remove helper words from the beginning of param phrase. Removes whitespace before and after removing words. Returns cleaned phrase. This is a part that could use some improvement or a new library integration. :param phrase: str :return: phrase: str
Remove helper words from the beginning of param phrase. Removes whitespace before and after removing words. Returns cleaned phrase. This is a part that could use some improvement or a new library integration.
[ "Remove", "helper", "words", "from", "the", "beginning", "of", "param", "phrase", ".", "Removes", "whitespace", "before", "and", "after", "removing", "words", ".", "Returns", "cleaned", "phrase", ".", "This", "is", "a", "part", "that", "could", "use", "some"...
def remove_helper_words(phrase: str): logging.debug(f'Removing helper words and whitespace from ({phrase})') phrase = phrase.strip() for word in ['for ', 'was ', 'were ', 'up ', 'to ', 'is ', 'are', 'the ']: phrase = phrase.replace(word, '', 1) if phrase.startswith(word) else phrase phrase = phr...
[ "def", "remove_helper_words", "(", "phrase", ":", "str", ")", ":", "logging", ".", "debug", "(", "f'Removing helper words and whitespace from ({phrase})'", ")", "phrase", "=", "phrase", ".", "strip", "(", ")", "for", "word", "in", "[", "'for '", ",", "'was '", ...
Remove helper words from the beginning of param phrase.
[ "Remove", "helper", "words", "from", "the", "beginning", "of", "param", "phrase", "." ]
[ "\"\"\"\n Remove helper words from the beginning of param phrase.\n Removes whitespace before and after removing words.\n\n Returns cleaned phrase.\n\n This is a part that could use some improvement or a new library integration.\n\n :param phrase: str\n :return: phrase: str\n \"\"\"" ]
[ { "param": "phrase", "type": "str" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "phrase", "type": "str", "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
b46707b42d15d184fe856fbf4ce278fd8f2d3fc4
TrialAndErrror/TnE_Assistant
src/Tools/process_command.py
[ "MIT" ]
Python
listen_for_commands
<not_specific>
def listen_for_commands(): """ Listen for command; use Google speech detection to extract command; then return command :return: command: str """ with sr.Microphone() as source: print_custom_intro() voice = listener.listen(source) command: str = listener.recognize_goo...
Listen for command; use Google speech detection to extract command; then return command :return: command: str
Listen for command; use Google speech detection to extract command; then return command
[ "Listen", "for", "command", ";", "use", "Google", "speech", "detection", "to", "extract", "command", ";", "then", "return", "command" ]
def listen_for_commands(): with sr.Microphone() as source: print_custom_intro() voice = listener.listen(source) command: str = listener.recognize_google(voice) return command
[ "def", "listen_for_commands", "(", ")", ":", "with", "sr", ".", "Microphone", "(", ")", "as", "source", ":", "print_custom_intro", "(", ")", "voice", "=", "listener", ".", "listen", "(", "source", ")", "command", ":", "str", "=", "listener", ".", "recogn...
Listen for command; use Google speech detection to extract command; then return command
[ "Listen", "for", "command", ";", "use", "Google", "speech", "detection", "to", "extract", "command", ";", "then", "return", "command" ]
[ "\"\"\"\n Listen for command;\n use Google speech detection to extract command;\n then return command\n\n :return: command: str\n \"\"\"" ]
[]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [], "outlier_params": [], "others": [] }
b46d9db3d085964e5b118f75d4b572e1624f0907
TrialAndErrror/TnE_Assistant
src/Actions/Open.py
[ "MIT" ]
Python
open_page_or_file
null
def open_page_or_file(phrase): """ Handles all routes based on the 'Open' first_word. Currently only supports opening custom e-mail link. Allows for custom commands to launch e-mail in the Settings file. Link to E-mail provider also in Settings file :param phrase: str :return: None ""...
Handles all routes based on the 'Open' first_word. Currently only supports opening custom e-mail link. Allows for custom commands to launch e-mail in the Settings file. Link to E-mail provider also in Settings file :param phrase: str :return: None
Handles all routes based on the 'Open' first_word. Currently only supports opening custom e-mail link. Allows for custom commands to launch e-mail in the Settings file. Link to E-mail provider also in Settings file
[ "Handles", "all", "routes", "based", "on", "the", "'", "Open", "'", "first_word", ".", "Currently", "only", "supports", "opening", "custom", "e", "-", "mail", "link", ".", "Allows", "for", "custom", "commands", "to", "launch", "e", "-", "mail", "in", "th...
def open_page_or_file(phrase): default_email_commands = ['mail', 'message'] if phrase in OPEN_SETTINGS.get('Email', default_email_commands): speak(f'Opening Mail') open_mail_link() else: speak(f'I don\'t know how to open {phrase}')
[ "def", "open_page_or_file", "(", "phrase", ")", ":", "default_email_commands", "=", "[", "'mail'", ",", "'message'", "]", "if", "phrase", "in", "OPEN_SETTINGS", ".", "get", "(", "'Email'", ",", "default_email_commands", ")", ":", "speak", "(", "f'Opening Mail'",...
Handles all routes based on the 'Open' first_word.
[ "Handles", "all", "routes", "based", "on", "the", "'", "Open", "'", "first_word", "." ]
[ "\"\"\"\n Handles all routes based on the 'Open' first_word.\n\n Currently only supports opening custom e-mail link.\n\n Allows for custom commands to launch e-mail in the Settings file.\n Link to E-mail provider also in Settings file\n\n :param phrase: str\n :return: None\n \"\"\"" ]
[ { "param": "phrase", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "phrase", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
b46d9db3d085964e5b118f75d4b572e1624f0907
TrialAndErrror/TnE_Assistant
src/Actions/Open.py
[ "MIT" ]
Python
open_mail_link
null
def open_mail_link(): """ Get mail url from Settings file, then open in web browser. Defaults to GMail if nothing provided in settings. :return: None """ default_url = 'https://mail.google.com/mail/u/0/' mail_url = OPEN_SETTINGS.get('Mail URL', default_url) webbrowser.open(mail_url)
Get mail url from Settings file, then open in web browser. Defaults to GMail if nothing provided in settings. :return: None
Get mail url from Settings file, then open in web browser. Defaults to GMail if nothing provided in settings.
[ "Get", "mail", "url", "from", "Settings", "file", "then", "open", "in", "web", "browser", ".", "Defaults", "to", "GMail", "if", "nothing", "provided", "in", "settings", "." ]
def open_mail_link(): default_url = 'https://mail.google.com/mail/u/0/' mail_url = OPEN_SETTINGS.get('Mail URL', default_url) webbrowser.open(mail_url)
[ "def", "open_mail_link", "(", ")", ":", "default_url", "=", "'https://mail.google.com/mail/u/0/'", "mail_url", "=", "OPEN_SETTINGS", ".", "get", "(", "'Mail URL'", ",", "default_url", ")", "webbrowser", ".", "open", "(", "mail_url", ")" ]
Get mail url from Settings file, then open in web browser.
[ "Get", "mail", "url", "from", "Settings", "file", "then", "open", "in", "web", "browser", "." ]
[ "\"\"\"\n Get mail url from Settings file, then open in web browser.\n\n Defaults to GMail if nothing provided in settings.\n :return: None\n \"\"\"" ]
[]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [], "outlier_params": [], "others": [] }
510d1c722161c6edcc22c253703fb7316e782400
TrialAndErrror/TnE_Assistant
src/Actions/Wiki.py
[ "MIT" ]
Python
open_wiki_url
null
def open_wiki_url(phrase: str): """ Capitalize and parse phrase as web-friendly string; open web browser to Wikipedia page for web-friendly string :param phrase: str :return: None """ webbrowser.open(f'https://en.wikipedia.org/wiki/{quote(phrase.capitalize())}')
Capitalize and parse phrase as web-friendly string; open web browser to Wikipedia page for web-friendly string :param phrase: str :return: None
Capitalize and parse phrase as web-friendly string; open web browser to Wikipedia page for web-friendly string
[ "Capitalize", "and", "parse", "phrase", "as", "web", "-", "friendly", "string", ";", "open", "web", "browser", "to", "Wikipedia", "page", "for", "web", "-", "friendly", "string" ]
def open_wiki_url(phrase: str): webbrowser.open(f'https://en.wikipedia.org/wiki/{quote(phrase.capitalize())}')
[ "def", "open_wiki_url", "(", "phrase", ":", "str", ")", ":", "webbrowser", ".", "open", "(", "f'https://en.wikipedia.org/wiki/{quote(phrase.capitalize())}'", ")" ]
Capitalize and parse phrase as web-friendly string; open web browser to Wikipedia page for web-friendly string
[ "Capitalize", "and", "parse", "phrase", "as", "web", "-", "friendly", "string", ";", "open", "web", "browser", "to", "Wikipedia", "page", "for", "web", "-", "friendly", "string" ]
[ "\"\"\"\n Capitalize and parse phrase as web-friendly string;\n open web browser to Wikipedia page for web-friendly string\n\n :param phrase: str\n :return: None\n \"\"\"" ]
[ { "param": "phrase", "type": "str" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "phrase", "type": "str", "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
510d1c722161c6edcc22c253703fb7316e782400
TrialAndErrror/TnE_Assistant
src/Actions/Wiki.py
[ "MIT" ]
Python
read_wiki_summary
null
def read_wiki_summary(phrase, lines_to_read): """ Read specific number of lines from the Summary of phrase on Wikipedia :param phrase: str :param lines_to_read: int :return: None """ response = wikipedia.summary(phrase, lines_to_read) speak(f'Here\'s what I found on Wikipedia for {phras...
Read specific number of lines from the Summary of phrase on Wikipedia :param phrase: str :param lines_to_read: int :return: None
Read specific number of lines from the Summary of phrase on Wikipedia
[ "Read", "specific", "number", "of", "lines", "from", "the", "Summary", "of", "phrase", "on", "Wikipedia" ]
def read_wiki_summary(phrase, lines_to_read): response = wikipedia.summary(phrase, lines_to_read) speak(f'Here\'s what I found on Wikipedia for {phrase}: {response}')
[ "def", "read_wiki_summary", "(", "phrase", ",", "lines_to_read", ")", ":", "response", "=", "wikipedia", ".", "summary", "(", "phrase", ",", "lines_to_read", ")", "speak", "(", "f'Here\\'s what I found on Wikipedia for {phrase}: {response}'", ")" ]
Read specific number of lines from the Summary of phrase on Wikipedia
[ "Read", "specific", "number", "of", "lines", "from", "the", "Summary", "of", "phrase", "on", "Wikipedia" ]
[ "\"\"\"\n Read specific number of lines from the Summary of phrase on Wikipedia\n\n :param phrase: str\n :param lines_to_read: int\n :return: None\n \"\"\"" ]
[ { "param": "phrase", "type": null }, { "param": "lines_to_read", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "phrase", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
510d1c722161c6edcc22c253703fb7316e782400
TrialAndErrror/TnE_Assistant
src/Actions/Wiki.py
[ "MIT" ]
Python
open_wiki_results_for
null
def open_wiki_results_for(phrase): """ Open Wiki URL for phrase; Read Wiki summary aloud based on number of lines specified in Settings. :param phrase: str :return: None """ open_wiki_url(phrase) lines_to_read: int = WIKI_SETTINGS.get('Lines to Read', 1) read_wiki_summary(phrase, l...
Open Wiki URL for phrase; Read Wiki summary aloud based on number of lines specified in Settings. :param phrase: str :return: None
Open Wiki URL for phrase; Read Wiki summary aloud based on number of lines specified in Settings.
[ "Open", "Wiki", "URL", "for", "phrase", ";", "Read", "Wiki", "summary", "aloud", "based", "on", "number", "of", "lines", "specified", "in", "Settings", "." ]
def open_wiki_results_for(phrase): open_wiki_url(phrase) lines_to_read: int = WIKI_SETTINGS.get('Lines to Read', 1) read_wiki_summary(phrase, lines_to_read)
[ "def", "open_wiki_results_for", "(", "phrase", ")", ":", "open_wiki_url", "(", "phrase", ")", "lines_to_read", ":", "int", "=", "WIKI_SETTINGS", ".", "get", "(", "'Lines to Read'", ",", "1", ")", "read_wiki_summary", "(", "phrase", ",", "lines_to_read", ")" ]
Open Wiki URL for phrase; Read Wiki summary aloud based on number of lines specified in Settings.
[ "Open", "Wiki", "URL", "for", "phrase", ";", "Read", "Wiki", "summary", "aloud", "based", "on", "number", "of", "lines", "specified", "in", "Settings", "." ]
[ "\"\"\"\n Open Wiki URL for phrase;\n Read Wiki summary aloud based on number of lines specified in Settings.\n\n :param phrase: str\n :return: None\n \"\"\"" ]
[ { "param": "phrase", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "phrase", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
da3e4205bb37ae0c21d1d31d422c8823d5f40a39
TrialAndErrror/TnE_Assistant
src/Tools/wake_triggers.py
[ "MIT" ]
Python
check_for_wake_word
<not_specific>
def check_for_wake_word(command: str): """ Check if wake word is in param command. :param command: str :return: is_triggered: bool """ wake_word: str = ASSISTANT_SETTINGS.get('Wake Word') logging.debug(f'Searching for wake word ({wake_word}) in command ({command})') wake_word_found = b...
Check if wake word is in param command. :param command: str :return: is_triggered: bool
Check if wake word is in param command.
[ "Check", "if", "wake", "word", "is", "in", "param", "command", "." ]
def check_for_wake_word(command: str): wake_word: str = ASSISTANT_SETTINGS.get('Wake Word') logging.debug(f'Searching for wake word ({wake_word}) in command ({command})') wake_word_found = bool(command.lower().startswith(wake_word.lower())) if wake_word_found: logging.debug(f'Assistant activated...
[ "def", "check_for_wake_word", "(", "command", ":", "str", ")", ":", "wake_word", ":", "str", "=", "ASSISTANT_SETTINGS", ".", "get", "(", "'Wake Word'", ")", "logging", ".", "debug", "(", "f'Searching for wake word ({wake_word}) in command ({command})'", ")", "wake_wor...
Check if wake word is in param command.
[ "Check", "if", "wake", "word", "is", "in", "param", "command", "." ]
[ "\"\"\"\n Check if wake word is in param command.\n\n :param command: str\n :return: is_triggered: bool\n \"\"\"" ]
[ { "param": "command", "type": "str" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "command", "type": "str", "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
204f69399a2a212a16648b7ddd27efd5dcdff9d4
TrialAndErrror/TnE_Assistant
src/Actions/Catchall.py
[ "MIT" ]
Python
do_catchall_action
null
def do_catchall_action(phrase, command_word): """ Log that the trigger word was not recognized, then perform default action. Default: Search :param phrase: str :param command_word: str :return: """ speak(f'The command word was {command_word}, but I don\'t know what that means.') sp...
Log that the trigger word was not recognized, then perform default action. Default: Search :param phrase: str :param command_word: str :return:
Log that the trigger word was not recognized, then perform default action. Default: Search
[ "Log", "that", "the", "trigger", "word", "was", "not", "recognized", "then", "perform", "default", "action", ".", "Default", ":", "Search" ]
def do_catchall_action(phrase, command_word): speak(f'The command word was {command_word}, but I don\'t know what that means.') speak(f'I\'ll try to search Google for {phrase}.') search_web_for(phrase)
[ "def", "do_catchall_action", "(", "phrase", ",", "command_word", ")", ":", "speak", "(", "f'The command word was {command_word}, but I don\\'t know what that means.'", ")", "speak", "(", "f'I\\'ll try to search Google for {phrase}.'", ")", "search_web_for", "(", "phrase", ")" ]
Log that the trigger word was not recognized, then perform default action.
[ "Log", "that", "the", "trigger", "word", "was", "not", "recognized", "then", "perform", "default", "action", "." ]
[ "\"\"\"\n Log that the trigger word was not recognized, then perform default action.\n\n Default: Search\n\n :param phrase: str\n :param command_word: str\n :return:\n \"\"\"" ]
[ { "param": "phrase", "type": null }, { "param": "command_word", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "phrase", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
3c346d9b4de17fb5d27193ee5c55df28a1eb38fc
Dhrumilsoni/Chess_Engine
chesslib/board.py
[ "WTFPL" ]
Python
_finish_move
null
def _finish_move(self, piece, dest, p1, p2): ''' Set next player turn, count moves, log moves, etc. ''' enemy = self.get_enemy(piece.color) if piece.color == 'black': self.fullmove_number += 1 self.halfmove_clock +=1 self.player_turn = enemy ...
Set next player turn, count moves, log moves, etc.
Set next player turn, count moves, log moves, etc.
[ "Set", "next", "player", "turn", "count", "moves", "log", "moves", "etc", "." ]
def _finish_move(self, piece, dest, p1, p2): enemy = self.get_enemy(piece.color) if piece.color == 'black': self.fullmove_number += 1 self.halfmove_clock +=1 self.player_turn = enemy abbr = piece.abbriviation if abbr == 'P': abbr = '' s...
[ "def", "_finish_move", "(", "self", ",", "piece", ",", "dest", ",", "p1", ",", "p2", ")", ":", "enemy", "=", "self", ".", "get_enemy", "(", "piece", ".", "color", ")", "if", "piece", ".", "color", "==", "'black'", ":", "self", ".", "fullmove_number",...
Set next player turn, count moves, log moves, etc.
[ "Set", "next", "player", "turn", "count", "moves", "log", "moves", "etc", "." ]
[ "'''\n Set next player turn, count moves, log moves, etc.\n '''", "# Pawn has no letter", "# Pawn resets halfmove_clock", "# No capturing", "# Capturing", "# Capturing resets halfmove_clock" ]
[ { "param": "self", "type": null }, { "param": "piece", "type": null }, { "param": "dest", "type": null }, { "param": "p1", "type": null }, { "param": "p2", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "piece", "type": null, "docstring": null, "docstring_tokens": ...
3c346d9b4de17fb5d27193ee5c55df28a1eb38fc
Dhrumilsoni/Chess_Engine
chesslib/board.py
[ "WTFPL" ]
Python
occupied
<not_specific>
def occupied(self, color): ''' Return a list of coordinates occupied by `color` ''' result = [] if(color not in ("black", "white")): raise InvalidColor for coord in self: if self[coord].color == color: result.append(coord) return r...
Return a list of coordinates occupied by `color`
Return a list of coordinates occupied by `color`
[ "Return", "a", "list", "of", "coordinates", "occupied", "by", "`", "color", "`" ]
def occupied(self, color): result = [] if(color not in ("black", "white")): raise InvalidColor for coord in self: if self[coord].color == color: result.append(coord) return result
[ "def", "occupied", "(", "self", ",", "color", ")", ":", "result", "=", "[", "]", "if", "(", "color", "not", "in", "(", "\"black\"", ",", "\"white\"", ")", ")", ":", "raise", "InvalidColor", "for", "coord", "in", "self", ":", "if", "self", "[", "coo...
Return a list of coordinates occupied by `color`
[ "Return", "a", "list", "of", "coordinates", "occupied", "by", "`", "color", "`" ]
[ "'''\n Return a list of coordinates occupied by `color`\n '''" ]
[ { "param": "self", "type": null }, { "param": "color", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "color", "type": null, "docstring": null, "docstring_tokens": ...
9b8ed33c31a92c35f0ac07d1b5a8adeb51aa43dd
Dhrumilsoni/Chess_Engine
chesslib/gui_tkinter.py
[ "WTFPL" ]
Python
addpiece
null
def addpiece(self, name, image, row=0, column=0): # print "addpiece" '''Add a piece to the playing board''' self.canvas.create_image(0, 0, image=image, tags=(name, "piece"), anchor="c") self.placepiece(name, row, column)
Add a piece to the playing board
Add a piece to the playing board
[ "Add", "a", "piece", "to", "the", "playing", "board" ]
def addpiece(self, name, image, row=0, column=0): self.canvas.create_image(0, 0, image=image, tags=(name, "piece"), anchor="c") self.placepiece(name, row, column)
[ "def", "addpiece", "(", "self", ",", "name", ",", "image", ",", "row", "=", "0", ",", "column", "=", "0", ")", ":", "self", ".", "canvas", ".", "create_image", "(", "0", ",", "0", ",", "image", "=", "image", ",", "tags", "=", "(", "name", ",", ...
Add a piece to the playing board
[ "Add", "a", "piece", "to", "the", "playing", "board" ]
[ "# print \"addpiece\"", "'''Add a piece to the playing board'''" ]
[ { "param": "self", "type": null }, { "param": "name", "type": null }, { "param": "image", "type": null }, { "param": "row", "type": null }, { "param": "column", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "name", "type": null, "docstring": null, "docstring_tokens": [...
5fde0397ac04c1034ad4cc9498ebe9a635fffff5
tobiascr/chess
game.py
[ "MIT" ]
Python
insufficient_material
<not_specific>
def insufficient_material(self): """Return true if and only if the position is king vs king or king vs king and light piece.""" FEN_fields = self.FEN_string.split(" ") board = FEN_fields[0] pieces = "" for c in board: if c in "pnbrqkPNBRQK": pi...
Return true if and only if the position is king vs king or king vs king and light piece.
Return true if and only if the position is king vs king or king vs king and light piece.
[ "Return", "true", "if", "and", "only", "if", "the", "position", "is", "king", "vs", "king", "or", "king", "vs", "king", "and", "light", "piece", "." ]
def insufficient_material(self): FEN_fields = self.FEN_string.split(" ") board = FEN_fields[0] pieces = "" for c in board: if c in "pnbrqkPNBRQK": pieces += c if len(pieces) > 3: return False for c in "prqPRQ": if c in p...
[ "def", "insufficient_material", "(", "self", ")", ":", "FEN_fields", "=", "self", ".", "FEN_string", ".", "split", "(", "\" \"", ")", "board", "=", "FEN_fields", "[", "0", "]", "pieces", "=", "\"\"", "for", "c", "in", "board", ":", "if", "c", "in", "...
Return true if and only if the position is king vs king or king vs king and light piece.
[ "Return", "true", "if", "and", "only", "if", "the", "position", "is", "king", "vs", "king", "or", "king", "vs", "king", "and", "light", "piece", "." ]
[ "\"\"\"Return true if and only if the position is king vs king or\n king vs king and light piece.\"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
5fde0397ac04c1034ad4cc9498ebe9a635fffff5
tobiascr/chess
game.py
[ "MIT" ]
Python
threefold_repetition
<not_specific>
def threefold_repetition(self): """Return True if and only if the current position has occured 2 times earlier. Positions are considered the same if the same player has the move, pieces of the same kind and color occupy the same squares, and the possible moves of all the pieces of both p...
Return True if and only if the current position has occured 2 times earlier. Positions are considered the same if the same player has the move, pieces of the same kind and color occupy the same squares, and the possible moves of all the pieces of both players are the same. This is the ca...
Return True if and only if the current position has occured 2 times earlier. Positions are considered the same if the same player has the move, pieces of the same kind and color occupy the same squares, and the possible moves of all the pieces of both players are the same. This is the case if the FEN strings of the pos...
[ "Return", "True", "if", "and", "only", "if", "the", "current", "position", "has", "occured", "2", "times", "earlier", ".", "Positions", "are", "considered", "the", "same", "if", "the", "same", "player", "has", "the", "move", "pieces", "of", "the", "same", ...
def threefold_repetition(self): FEN_fields = self.FEN_string.split(" ") partial_FEN_string = " ".join([FEN_fields[n] for n in range(4)]) repeat = 0 for FEN_string in self.FEN_string_history: if partial_FEN_string in FEN_string: repeat += 1 return repea...
[ "def", "threefold_repetition", "(", "self", ")", ":", "FEN_fields", "=", "self", ".", "FEN_string", ".", "split", "(", "\" \"", ")", "partial_FEN_string", "=", "\" \"", ".", "join", "(", "[", "FEN_fields", "[", "n", "]", "for", "n", "in", "range", "(", ...
Return True if and only if the current position has occured 2 times earlier.
[ "Return", "True", "if", "and", "only", "if", "the", "current", "position", "has", "occured", "2", "times", "earlier", "." ]
[ "\"\"\"Return True if and only if the current position has occured 2 times\n earlier. Positions are considered the same if the same player has the move,\n pieces of the same kind and color occupy the same squares, and the\n possible moves of all the pieces of both players are the same.\n ...
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
5fde0397ac04c1034ad4cc9498ebe9a635fffff5
tobiascr/chess
game.py
[ "MIT" ]
Python
possible_draw_by_50_move_rule
<not_specific>
def possible_draw_by_50_move_rule(self): """Return True if and only if 50 moves have been made by each player without capturing or pushing a pawn.""" FEN_fields = self.FEN_string.split(" ") if len(FEN_fields) <= 4: return False else: return int(FEN_fields[...
Return True if and only if 50 moves have been made by each player without capturing or pushing a pawn.
Return True if and only if 50 moves have been made by each player without capturing or pushing a pawn.
[ "Return", "True", "if", "and", "only", "if", "50", "moves", "have", "been", "made", "by", "each", "player", "without", "capturing", "or", "pushing", "a", "pawn", "." ]
def possible_draw_by_50_move_rule(self): FEN_fields = self.FEN_string.split(" ") if len(FEN_fields) <= 4: return False else: return int(FEN_fields[4]) >= 100
[ "def", "possible_draw_by_50_move_rule", "(", "self", ")", ":", "FEN_fields", "=", "self", ".", "FEN_string", ".", "split", "(", "\" \"", ")", "if", "len", "(", "FEN_fields", ")", "<=", "4", ":", "return", "False", "else", ":", "return", "int", "(", "FEN_...
Return True if and only if 50 moves have been made by each player without capturing or pushing a pawn.
[ "Return", "True", "if", "and", "only", "if", "50", "moves", "have", "been", "made", "by", "each", "player", "without", "capturing", "or", "pushing", "a", "pawn", "." ]
[ "\"\"\"Return True if and only if 50 moves have been made by each player\n without capturing or pushing a pawn.\"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
5fde0397ac04c1034ad4cc9498ebe9a635fffff5
tobiascr/chess
game.py
[ "MIT" ]
Python
FEN_string_board_part
<not_specific>
def FEN_string_board_part(self): """Use the data in this class to produce the part of a FEN string that describe the placement of the pieces.""" def convert_to_FEN_row(row): FEN_row = "" empty_position_count = 0 for value in row: if value == No...
Use the data in this class to produce the part of a FEN string that describe the placement of the pieces.
Use the data in this class to produce the part of a FEN string that describe the placement of the pieces.
[ "Use", "the", "data", "in", "this", "class", "to", "produce", "the", "part", "of", "a", "FEN", "string", "that", "describe", "the", "placement", "of", "the", "pieces", "." ]
def FEN_string_board_part(self): def convert_to_FEN_row(row): FEN_row = "" empty_position_count = 0 for value in row: if value == None: empty_position_count += 1 else: if empty_position_count > 0: ...
[ "def", "FEN_string_board_part", "(", "self", ")", ":", "def", "convert_to_FEN_row", "(", "row", ")", ":", "FEN_row", "=", "\"\"", "empty_position_count", "=", "0", "for", "value", "in", "row", ":", "if", "value", "==", "None", ":", "empty_position_count", "+...
Use the data in this class to produce the part of a FEN string that describe the placement of the pieces.
[ "Use", "the", "data", "in", "this", "class", "to", "produce", "the", "part", "of", "a", "FEN", "string", "that", "describe", "the", "placement", "of", "the", "pieces", "." ]
[ "\"\"\"Use the data in this class to produce the part of a FEN string\n that describe the placement of the pieces.\"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
computer_move_UCI
<not_specific>
def computer_move_UCI(FEN_string): """Return a move that is computed by the engine. The move is returned in the UCI format. """ game_state = GameState(FEN_string) move = computer_move(game_state) return move.UCI_move_format_string()
Return a move that is computed by the engine. The move is returned in the UCI format.
Return a move that is computed by the engine. The move is returned in the UCI format.
[ "Return", "a", "move", "that", "is", "computed", "by", "the", "engine", ".", "The", "move", "is", "returned", "in", "the", "UCI", "format", "." ]
def computer_move_UCI(FEN_string): game_state = GameState(FEN_string) move = computer_move(game_state) return move.UCI_move_format_string()
[ "def", "computer_move_UCI", "(", "FEN_string", ")", ":", "game_state", "=", "GameState", "(", "FEN_string", ")", "move", "=", "computer_move", "(", "game_state", ")", "return", "move", ".", "UCI_move_format_string", "(", ")" ]
Return a move that is computed by the engine.
[ "Return", "a", "move", "that", "is", "computed", "by", "the", "engine", "." ]
[ "\"\"\"Return a move that is computed by the engine. The move is returned in the UCI format.\n \"\"\"" ]
[ { "param": "FEN_string", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "FEN_string", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
UCI_move_format_string
<not_specific>
def UCI_move_format_string(self): """Return the move in the UCI move format. For example like: "e2e4", "e7e5", "e1g1" (white short castling), "e7e8q" (for promotion), "c5b6" (en passant). """ if len(self.change_list) == 2: # The position where the move starts is not e...
Return the move in the UCI move format. For example like: "e2e4", "e7e5", "e1g1" (white short castling), "e7e8q" (for promotion), "c5b6" (en passant).
Return the move in the UCI move format.
[ "Return", "the", "move", "in", "the", "UCI", "move", "format", "." ]
def UCI_move_format_string(self): if len(self.change_list) == 2: if self.change_list[0][1] != None: from_triple = self.change_list[0] to_triple = self.change_list[1] else: from_triple = self.change_list[1] to_triple = self.c...
[ "def", "UCI_move_format_string", "(", "self", ")", ":", "if", "len", "(", "self", ".", "change_list", ")", "==", "2", ":", "if", "self", ".", "change_list", "[", "0", "]", "[", "1", "]", "!=", "None", ":", "from_triple", "=", "self", ".", "change_lis...
Return the move in the UCI move format.
[ "Return", "the", "move", "in", "the", "UCI", "move", "format", "." ]
[ "\"\"\"Return the move in the UCI move format. For example like:\n \"e2e4\", \"e7e5\", \"e1g1\" (white short castling), \"e7e8q\" (for promotion),\n \"c5b6\" (en passant).\n \"\"\"", "# The position where the move starts is not empty before the change.", "# If promotion.", "# En passants....
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
possible_moves
<not_specific>
def possible_moves(self, game_state, from_position): """Return all moves except from castlings that this king can make if it's located at from_position, including putting itself into check and capturing the opponents king. """ capture_move_list = [] non_capture_move_list ...
Return all moves except from castlings that this king can make if it's located at from_position, including putting itself into check and capturing the opponents king.
Return all moves except from castlings that this king can make if it's located at from_position, including putting itself into check and capturing the opponents king.
[ "Return", "all", "moves", "except", "from", "castlings", "that", "this", "king", "can", "make", "if", "it", "'", "s", "located", "at", "from_position", "including", "putting", "itself", "into", "check", "and", "capturing", "the", "opponents", "king", "." ]
def possible_moves(self, game_state, from_position): capture_move_list = [] non_capture_move_list = [] for to_position in self.possible_moves_dict[from_position]: piece = game_state.board[to_position] if piece: if piece.white != self.white: ...
[ "def", "possible_moves", "(", "self", ",", "game_state", ",", "from_position", ")", ":", "capture_move_list", "=", "[", "]", "non_capture_move_list", "=", "[", "]", "for", "to_position", "in", "self", ".", "possible_moves_dict", "[", "from_position", "]", ":", ...
Return all moves except from castlings that this king can make if it's located at from_position, including putting itself into check and capturing the opponents king.
[ "Return", "all", "moves", "except", "from", "castlings", "that", "this", "king", "can", "make", "if", "it", "'", "s", "located", "at", "from_position", "including", "putting", "itself", "into", "check", "and", "capturing", "the", "opponents", "king", "." ]
[ "\"\"\"Return all moves except from castlings that this king can make if it's\n located at from_position, including putting itself into check and capturing the\n opponents king.\n \"\"\"", "# If there is an opposite color piece on the target square.", "# If the is no piece on the target squ...
[ { "param": "self", "type": null }, { "param": "game_state", "type": null }, { "param": "from_position", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "game_state", "type": null, "docstring": null, "docstring_toke...
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
possible_moves
<not_specific>
def possible_moves(self, game_state, from_position): """Return all moves that this piece can make if it's located at from_position.""" return (Rook.possible_moves(self, game_state, from_position)[0] + Bishop.possible_moves(self, game_state, from_position)[0], Rook.possibl...
Return all moves that this piece can make if it's located at from_position.
Return all moves that this piece can make if it's located at from_position.
[ "Return", "all", "moves", "that", "this", "piece", "can", "make", "if", "it", "'", "s", "located", "at", "from_position", "." ]
def possible_moves(self, game_state, from_position): return (Rook.possible_moves(self, game_state, from_position)[0] + Bishop.possible_moves(self, game_state, from_position)[0], Rook.possible_moves(self, game_state, from_position)[1] + Bishop.possible_moves(self, ...
[ "def", "possible_moves", "(", "self", ",", "game_state", ",", "from_position", ")", ":", "return", "(", "Rook", ".", "possible_moves", "(", "self", ",", "game_state", ",", "from_position", ")", "[", "0", "]", "+", "Bishop", ".", "possible_moves", "(", "sel...
Return all moves that this piece can make if it's located at from_position.
[ "Return", "all", "moves", "that", "this", "piece", "can", "make", "if", "it", "'", "s", "located", "at", "from_position", "." ]
[ "\"\"\"Return all moves that this piece can make if it's located at from_position.\"\"\"" ]
[ { "param": "self", "type": null }, { "param": "game_state", "type": null }, { "param": "from_position", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "game_state", "type": null, "docstring": null, "docstring_toke...
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
possible_moves
<not_specific>
def possible_moves(self, game_state, from_position): """Return all moves except for castlings that this piece can make if it's located at from_position.""" capture_move_list = [] non_capture_move_list = [] # Moves up. for to_position in range(from_position + 8, 64, 8): ...
Return all moves except for castlings that this piece can make if it's located at from_position.
Return all moves except for castlings that this piece can make if it's located at from_position.
[ "Return", "all", "moves", "except", "for", "castlings", "that", "this", "piece", "can", "make", "if", "it", "'", "s", "located", "at", "from_position", "." ]
def possible_moves(self, game_state, from_position): capture_move_list = [] non_capture_move_list = [] for to_position in range(from_position + 8, 64, 8): piece = game_state.board[to_position] if piece: if piece.white != self.white: mov...
[ "def", "possible_moves", "(", "self", ",", "game_state", ",", "from_position", ")", ":", "capture_move_list", "=", "[", "]", "non_capture_move_list", "=", "[", "]", "for", "to_position", "in", "range", "(", "from_position", "+", "8", ",", "64", ",", "8", "...
Return all moves except for castlings that this piece can make if it's located at from_position.
[ "Return", "all", "moves", "except", "for", "castlings", "that", "this", "piece", "can", "make", "if", "it", "'", "s", "located", "at", "from_position", "." ]
[ "\"\"\"Return all moves except for castlings that this piece can make if it's\n located at from_position.\"\"\"", "# Moves up.", "# If capture.", "# Moves down.", "# If capture.", "# Moves right.", "# If capture.", "# Moves left.", "# If capture." ]
[ { "param": "self", "type": null }, { "param": "game_state", "type": null }, { "param": "from_position", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "game_state", "type": null, "docstring": null, "docstring_toke...
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
possible_moves
<not_specific>
def possible_moves(self, game_state, from_position): """Return all moves this piece can make if it's located at from_position""" # Row and column for the position. [from_r, from_c] = [from_position // 8, from_position % 8] capture_move_list = [] non_capture_move_list = [] ...
Return all moves this piece can make if it's located at from_position
Return all moves this piece can make if it's located at from_position
[ "Return", "all", "moves", "this", "piece", "can", "make", "if", "it", "'", "s", "located", "at", "from_position" ]
def possible_moves(self, game_state, from_position): [from_r, from_c] = [from_position // 8, from_position % 8] capture_move_list = [] non_capture_move_list = [] r = from_r + 1 c = from_c + 1 while r < 8 and c < 8: to_position = r * 8 + c piece = g...
[ "def", "possible_moves", "(", "self", ",", "game_state", ",", "from_position", ")", ":", "[", "from_r", ",", "from_c", "]", "=", "[", "from_position", "//", "8", ",", "from_position", "%", "8", "]", "capture_move_list", "=", "[", "]", "non_capture_move_list"...
Return all moves this piece can make if it's located at from_position
[ "Return", "all", "moves", "this", "piece", "can", "make", "if", "it", "'", "s", "located", "at", "from_position" ]
[ "\"\"\"Return all moves this piece can make if it's located at from_position\"\"\"", "# Row and column for the position.", "# Moves up right.", "# If capture.", "# Moves up left.", "# If capture.", "# Moves down right.", "# If capture.", "# Moves down left.", "# If capture." ]
[ { "param": "self", "type": null }, { "param": "game_state", "type": null }, { "param": "from_position", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "game_state", "type": null, "docstring": null, "docstring_toke...
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
pseudo_legal_moves_no_castlings
<not_specific>
def pseudo_legal_moves_no_castlings(self): """Return a list of Move-objects corresponding to all possible pseudo-legal moves in this position, except for castlings and promotion to other pieces than queens. The moves are sorted in such a way that the capture moves are preceding the non c...
Return a list of Move-objects corresponding to all possible pseudo-legal moves in this position, except for castlings and promotion to other pieces than queens. The moves are sorted in such a way that the capture moves are preceding the non capture moves.
Return a list of Move-objects corresponding to all possible pseudo-legal moves in this position, except for castlings and promotion to other pieces than queens. The moves are sorted in such a way that the capture moves are preceding the non capture moves.
[ "Return", "a", "list", "of", "Move", "-", "objects", "corresponding", "to", "all", "possible", "pseudo", "-", "legal", "moves", "in", "this", "position", "except", "for", "castlings", "and", "promotion", "to", "other", "pieces", "than", "queens", ".", "The",...
def pseudo_legal_moves_no_castlings(self): capture_move_list = [] non_capture_move_list = [] for position in range(64): piece = self.board[position] if piece: if piece.white == self.white_to_play: (c_move_list, non_c_move_list) = piece....
[ "def", "pseudo_legal_moves_no_castlings", "(", "self", ")", ":", "capture_move_list", "=", "[", "]", "non_capture_move_list", "=", "[", "]", "for", "position", "in", "range", "(", "64", ")", ":", "piece", "=", "self", ".", "board", "[", "position", "]", "i...
Return a list of Move-objects corresponding to all possible pseudo-legal moves in this position, except for castlings and promotion to other pieces than queens.
[ "Return", "a", "list", "of", "Move", "-", "objects", "corresponding", "to", "all", "possible", "pseudo", "-", "legal", "moves", "in", "this", "position", "except", "for", "castlings", "and", "promotion", "to", "other", "pieces", "than", "queens", "." ]
[ "\"\"\"Return a list of Move-objects corresponding to all possible pseudo-legal moves\n in this position, except for castlings and promotion to other pieces than\n queens. The moves are sorted in such a way that the capture moves are preceding\n the non capture moves.\"\"\"", "# If there is a...
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
legal_moves_no_castlings
<not_specific>
def legal_moves_no_castlings(self): """Return a list of Move-objects corresponding to all possible legal moves in this position, except for castlings and promotion to other pieces than queens.""" move_list = [] moves = self.pseudo_legal_moves_no_castlings() for move in mo...
Return a list of Move-objects corresponding to all possible legal moves in this position, except for castlings and promotion to other pieces than queens.
Return a list of Move-objects corresponding to all possible legal moves in this position, except for castlings and promotion to other pieces than queens.
[ "Return", "a", "list", "of", "Move", "-", "objects", "corresponding", "to", "all", "possible", "legal", "moves", "in", "this", "position", "except", "for", "castlings", "and", "promotion", "to", "other", "pieces", "than", "queens", "." ]
def legal_moves_no_castlings(self): move_list = [] moves = self.pseudo_legal_moves_no_castlings() for move in moves: self.make_move(move) if abs(minimax(self, 1)) < 500: move_list.append(move) self.undo_move(move) return move_list
[ "def", "legal_moves_no_castlings", "(", "self", ")", ":", "move_list", "=", "[", "]", "moves", "=", "self", ".", "pseudo_legal_moves_no_castlings", "(", ")", "for", "move", "in", "moves", ":", "self", ".", "make_move", "(", "move", ")", "if", "abs", "(", ...
Return a list of Move-objects corresponding to all possible legal moves in this position, except for castlings and promotion to other pieces than queens.
[ "Return", "a", "list", "of", "Move", "-", "objects", "corresponding", "to", "all", "possible", "legal", "moves", "in", "this", "position", "except", "for", "castlings", "and", "promotion", "to", "other", "pieces", "than", "queens", "." ]
[ "\"\"\"Return a list of Move-objects corresponding to all possible legal moves\n in this position, except for castlings and promotion to other pieces than\n queens.\"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
castlings
<not_specific>
def castlings(self): """Return a list of Move-objects corresponding to all possible castlings in this position. It is assumed that no moves have been made to the game state for while using this method.""" move_list = [] if self.castling_kingside_possible(): if self.wh...
Return a list of Move-objects corresponding to all possible castlings in this position. It is assumed that no moves have been made to the game state for while using this method.
Return a list of Move-objects corresponding to all possible castlings in this position. It is assumed that no moves have been made to the game state for while using this method.
[ "Return", "a", "list", "of", "Move", "-", "objects", "corresponding", "to", "all", "possible", "castlings", "in", "this", "position", ".", "It", "is", "assumed", "that", "no", "moves", "have", "been", "made", "to", "the", "game", "state", "for", "while", ...
def castlings(self): move_list = [] if self.castling_kingside_possible(): if self.white_to_play: king = self.board[4] rook = self.board[7] move = Move() move.add_change(4, king, None) move.add_change(5, None, roo...
[ "def", "castlings", "(", "self", ")", ":", "move_list", "=", "[", "]", "if", "self", ".", "castling_kingside_possible", "(", ")", ":", "if", "self", ".", "white_to_play", ":", "king", "=", "self", ".", "board", "[", "4", "]", "rook", "=", "self", "."...
Return a list of Move-objects corresponding to all possible castlings in this position.
[ "Return", "a", "list", "of", "Move", "-", "objects", "corresponding", "to", "all", "possible", "castlings", "in", "this", "position", "." ]
[ "\"\"\"Return a list of Move-objects corresponding to all possible castlings\n in this position. It is assumed that no moves have been made to the game state\n for while using this method.\"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
make_move
null
def make_move(self, move): """Make a change to the game_state described by the Move instance move. The value of the game state is also updated. """ for triple in move.change_list: self.board[triple[0]] = triple[2] if triple[1]: self.value -= triple...
Make a change to the game_state described by the Move instance move. The value of the game state is also updated.
Make a change to the game_state described by the Move instance move. The value of the game state is also updated.
[ "Make", "a", "change", "to", "the", "game_state", "described", "by", "the", "Move", "instance", "move", ".", "The", "value", "of", "the", "game", "state", "is", "also", "updated", "." ]
def make_move(self, move): for triple in move.change_list: self.board[triple[0]] = triple[2] if triple[1]: self.value -= triple[1].value if triple[2]: self.value += triple[2].value self.en_passant_target_square_history.append(self.en_pa...
[ "def", "make_move", "(", "self", ",", "move", ")", ":", "for", "triple", "in", "move", ".", "change_list", ":", "self", ".", "board", "[", "triple", "[", "0", "]", "]", "=", "triple", "[", "2", "]", "if", "triple", "[", "1", "]", ":", "self", "...
Make a change to the game_state described by the Move instance move.
[ "Make", "a", "change", "to", "the", "game_state", "described", "by", "the", "Move", "instance", "move", "." ]
[ "\"\"\"Make a change to the game_state described by the Move instance move.\n The value of the game state is also updated.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "move", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "move", "type": null, "docstring": null, "docstring_tokens": [...
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
undo_move
null
def undo_move(self, move): """Make a change to the game_state that undo the move described by the Move instance move. The value of the game state is also updated. """ for triple in move.change_list: self.board[triple[0]] = triple[1] if triple[1]: s...
Make a change to the game_state that undo the move described by the Move instance move. The value of the game state is also updated.
Make a change to the game_state that undo the move described by the Move instance move. The value of the game state is also updated.
[ "Make", "a", "change", "to", "the", "game_state", "that", "undo", "the", "move", "described", "by", "the", "Move", "instance", "move", ".", "The", "value", "of", "the", "game", "state", "is", "also", "updated", "." ]
def undo_move(self, move): for triple in move.change_list: self.board[triple[0]] = triple[1] if triple[1]: self.value += triple[1].value if triple[2]: self.value -= triple[2].value self.en_passant_target_square = self.en_passant_target_...
[ "def", "undo_move", "(", "self", ",", "move", ")", ":", "for", "triple", "in", "move", ".", "change_list", ":", "self", ".", "board", "[", "triple", "[", "0", "]", "]", "=", "triple", "[", "1", "]", "if", "triple", "[", "1", "]", ":", "self", "...
Make a change to the game_state that undo the move described by the Move instance move.
[ "Make", "a", "change", "to", "the", "game_state", "that", "undo", "the", "move", "described", "by", "the", "Move", "instance", "move", "." ]
[ "\"\"\"Make a change to the game_state that undo the move described by the\n Move instance move. The value of the game state is also updated.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "move", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "move", "type": null, "docstring": null, "docstring_tokens": [...
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
check
<not_specific>
def check(self): """Return True if the king of the player in turn is in check and False if not. """ nullmove = Move() self.make_move(nullmove) result = abs(minimax(self, 1)) > 500 self.undo_move(nullmove) return result
Return True if the king of the player in turn is in check and False if not.
Return True if the king of the player in turn is in check and False if not.
[ "Return", "True", "if", "the", "king", "of", "the", "player", "in", "turn", "is", "in", "check", "and", "False", "if", "not", "." ]
def check(self): nullmove = Move() self.make_move(nullmove) result = abs(minimax(self, 1)) > 500 self.undo_move(nullmove) return result
[ "def", "check", "(", "self", ")", ":", "nullmove", "=", "Move", "(", ")", "self", ".", "make_move", "(", "nullmove", ")", "result", "=", "abs", "(", "minimax", "(", "self", ",", "1", ")", ")", ">", "500", "self", ".", "undo_move", "(", "nullmove", ...
Return True if the king of the player in turn is in check and False if not.
[ "Return", "True", "if", "the", "king", "of", "the", "player", "in", "turn", "is", "in", "check", "and", "False", "if", "not", "." ]
[ "\"\"\"Return True if the king of the player in turn is in check and\n False if not.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
castling_kingside_possible
<not_specific>
def castling_kingside_possible(self): """Return True if the player in turn can make kingside castling and False if not. This function is assumed to only be used if no moves have been made to the game_state object, since castling rights may not valid then. """ if self.chec...
Return True if the player in turn can make kingside castling and False if not. This function is assumed to only be used if no moves have been made to the game_state object, since castling rights may not valid then.
Return True if the player in turn can make kingside castling and False if not. This function is assumed to only be used if no moves have been made to the game_state object, since castling rights may not valid then.
[ "Return", "True", "if", "the", "player", "in", "turn", "can", "make", "kingside", "castling", "and", "False", "if", "not", ".", "This", "function", "is", "assumed", "to", "only", "be", "used", "if", "no", "moves", "have", "been", "made", "to", "the", "...
def castling_kingside_possible(self): if self.check(): return False if self.white_to_play: if "K" in self.castling_possibilities: if self.board[5] == self.board[6] == None: king = self.board[4] move = Move() ...
[ "def", "castling_kingside_possible", "(", "self", ")", ":", "if", "self", ".", "check", "(", ")", ":", "return", "False", "if", "self", ".", "white_to_play", ":", "if", "\"K\"", "in", "self", ".", "castling_possibilities", ":", "if", "self", ".", "board", ...
Return True if the player in turn can make kingside castling and False if not.
[ "Return", "True", "if", "the", "player", "in", "turn", "can", "make", "kingside", "castling", "and", "False", "if", "not", "." ]
[ "\"\"\"Return True if the player in turn can make kingside castling\n and False if not. This function is assumed to only be used if no moves\n have been made to the game_state object, since castling rights may not\n valid then.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
castling_queenside_possible
<not_specific>
def castling_queenside_possible(self): """Return True if the player in turn can make queenside castling and False if not. This function is assumed to only be used if no moves have been made to the game_state object, since castling rights may not valid then.""" if self.check(): ...
Return True if the player in turn can make queenside castling and False if not. This function is assumed to only be used if no moves have been made to the game_state object, since castling rights may not valid then.
Return True if the player in turn can make queenside castling and False if not. This function is assumed to only be used if no moves have been made to the game_state object, since castling rights may not valid then.
[ "Return", "True", "if", "the", "player", "in", "turn", "can", "make", "queenside", "castling", "and", "False", "if", "not", ".", "This", "function", "is", "assumed", "to", "only", "be", "used", "if", "no", "moves", "have", "been", "made", "to", "the", ...
def castling_queenside_possible(self): if self.check(): return False if self.white_to_play: if "Q" in self.castling_possibilities: if self.board[1] == self.board[2] == self.board[3] == None: king = self.board[4] move = Move(...
[ "def", "castling_queenside_possible", "(", "self", ")", ":", "if", "self", ".", "check", "(", ")", ":", "return", "False", "if", "self", ".", "white_to_play", ":", "if", "\"Q\"", "in", "self", ".", "castling_possibilities", ":", "if", "self", ".", "board",...
Return True if the player in turn can make queenside castling and False if not.
[ "Return", "True", "if", "the", "player", "in", "turn", "can", "make", "queenside", "castling", "and", "False", "if", "not", "." ]
[ "\"\"\"Return True if the player in turn can make queenside castling\n and False if not. This function is assumed to only be used if no moves\n have been made to the game_state object, since castling rights may not\n valid then.\"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
minimax
<not_specific>
def minimax(game_state, depth): """This function uses the minimax algorithm to analyze a game state. White is the maximizing player and black the minimizing. """ # If max depth is reached or if king is captured. if depth == 0 or abs(game_state.value) > 500: return game_state.value # Tes...
This function uses the minimax algorithm to analyze a game state. White is the maximizing player and black the minimizing.
This function uses the minimax algorithm to analyze a game state. White is the maximizing player and black the minimizing.
[ "This", "function", "uses", "the", "minimax", "algorithm", "to", "analyze", "a", "game", "state", ".", "White", "is", "the", "maximizing", "player", "and", "black", "the", "minimizing", "." ]
def minimax(game_state, depth): if depth == 0 or abs(game_state.value) > 500: return game_state.value moves = game_state.pseudo_legal_moves_no_castlings() value_list = [] if moves == []: return 0 for move in moves: game_state.make_move(move) value_list.append(minimax(...
[ "def", "minimax", "(", "game_state", ",", "depth", ")", ":", "if", "depth", "==", "0", "or", "abs", "(", "game_state", ".", "value", ")", ">", "500", ":", "return", "game_state", ".", "value", "moves", "=", "game_state", ".", "pseudo_legal_moves_no_castlin...
This function uses the minimax algorithm to analyze a game state.
[ "This", "function", "uses", "the", "minimax", "algorithm", "to", "analyze", "a", "game", "state", "." ]
[ "\"\"\"This function uses the minimax algorithm to analyze a game state.\n White is the maximizing player and black the minimizing.\n \"\"\"", "# If max depth is reached or if king is captured.", "# Test child nodes.", "# If no moves were found.", "# If maximizing player.", "# If minimizing player."...
[ { "param": "game_state", "type": null }, { "param": "depth", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "game_state", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "depth", "type": null, "docstring": null, "docstring_tok...
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
negamax
<not_specific>
def negamax(game_state, depth, alpha, beta): """Compute a value of game_state. The value is seen from the perspective of the player in turn. A favorable position for that player is given a positive value. """ #global node_counter #node_counter += 1 # If max depth is reached or if king is captu...
Compute a value of game_state. The value is seen from the perspective of the player in turn. A favorable position for that player is given a positive value.
Compute a value of game_state. The value is seen from the perspective of the player in turn. A favorable position for that player is given a positive value.
[ "Compute", "a", "value", "of", "game_state", ".", "The", "value", "is", "seen", "from", "the", "perspective", "of", "the", "player", "in", "turn", ".", "A", "favorable", "position", "for", "that", "player", "is", "given", "a", "positive", "value", "." ]
def negamax(game_state, depth, alpha, beta): if depth == 0 or abs(game_state.value) > 500: if game_state.white_to_play: return game_state.value else: return -game_state.value moves = game_state.pseudo_legal_moves_no_castlings() value_list = [] if moves == []: ...
[ "def", "negamax", "(", "game_state", ",", "depth", ",", "alpha", ",", "beta", ")", ":", "if", "depth", "==", "0", "or", "abs", "(", "game_state", ".", "value", ")", ">", "500", ":", "if", "game_state", ".", "white_to_play", ":", "return", "game_state",...
Compute a value of game_state.
[ "Compute", "a", "value", "of", "game_state", "." ]
[ "\"\"\"Compute a value of game_state. The value is seen from the perspective of the\n player in turn. A favorable position for that player is given a positive value.\n \"\"\"", "#global node_counter", "#node_counter += 1", "# If max depth is reached or if king is captured.", "# Test child nodes.", "...
[ { "param": "game_state", "type": null }, { "param": "depth", "type": null }, { "param": "alpha", "type": null }, { "param": "beta", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "game_state", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "depth", "type": null, "docstring": null, "docstring_tok...
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
convert_position_to_engine_format
<not_specific>
def convert_position_to_engine_format(position): """Convert conventional position format to engine format. position can be for example "a1". For example "a1" is converted to 0. """ return "abcdefgh".find(position[0]) + (int(position[1]) - 1) * 8
Convert conventional position format to engine format. position can be for example "a1". For example "a1" is converted to 0.
Convert conventional position format to engine format. position can be for example "a1". For example "a1" is converted to 0.
[ "Convert", "conventional", "position", "format", "to", "engine", "format", ".", "position", "can", "be", "for", "example", "\"", "a1", "\"", ".", "For", "example", "\"", "a1", "\"", "is", "converted", "to", "0", "." ]
def convert_position_to_engine_format(position): return "abcdefgh".find(position[0]) + (int(position[1]) - 1) * 8
[ "def", "convert_position_to_engine_format", "(", "position", ")", ":", "return", "\"abcdefgh\"", ".", "find", "(", "position", "[", "0", "]", ")", "+", "(", "int", "(", "position", "[", "1", "]", ")", "-", "1", ")", "*", "8" ]
Convert conventional position format to engine format.
[ "Convert", "conventional", "position", "format", "to", "engine", "format", "." ]
[ "\"\"\"Convert conventional position format to engine format.\n position can be for example \"a1\". For example \"a1\" is converted to 0.\n \"\"\"" ]
[ { "param": "position", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "position", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
convert_position_to_conventional_format
<not_specific>
def convert_position_to_conventional_format(position): """Convert engine position format to conventional format. position can be an integer from 0 to 63. For example 0 is converted to "a1". """ [r, c] = [position // 8 + 1, position % 8] return "abcdefgh"[c] + str(r)
Convert engine position format to conventional format. position can be an integer from 0 to 63. For example 0 is converted to "a1".
Convert engine position format to conventional format. position can be an integer from 0 to 63. For example 0 is converted to "a1".
[ "Convert", "engine", "position", "format", "to", "conventional", "format", ".", "position", "can", "be", "an", "integer", "from", "0", "to", "63", ".", "For", "example", "0", "is", "converted", "to", "\"", "a1", "\"", "." ]
def convert_position_to_conventional_format(position): [r, c] = [position // 8 + 1, position % 8] return "abcdefgh"[c] + str(r)
[ "def", "convert_position_to_conventional_format", "(", "position", ")", ":", "[", "r", ",", "c", "]", "=", "[", "position", "//", "8", "+", "1", ",", "position", "%", "8", "]", "return", "\"abcdefgh\"", "[", "c", "]", "+", "str", "(", "r", ")" ]
Convert engine position format to conventional format.
[ "Convert", "engine", "position", "format", "to", "conventional", "format", "." ]
[ "\"\"\"Convert engine position format to conventional format.\n position can be an integer from 0 to 63. For example 0 is converted to \"a1\".\n \"\"\"" ]
[ { "param": "position", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "position", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6076811a884e2b208b811424dd7adf513aa3fa83
tobiascr/chess
engine.py
[ "MIT" ]
Python
computer_move
<not_specific>
def computer_move(game_state): """Return a move that is computed with the minimax algorithm. This function is assumed to only be used if no moves have been made to the game_state object, since castling rights may not valid then.""" global node_counter node_counter = 0 moves = game_state.le...
Return a move that is computed with the minimax algorithm. This function is assumed to only be used if no moves have been made to the game_state object, since castling rights may not valid then.
Return a move that is computed with the minimax algorithm. This function is assumed to only be used if no moves have been made to the game_state object, since castling rights may not valid then.
[ "Return", "a", "move", "that", "is", "computed", "with", "the", "minimax", "algorithm", ".", "This", "function", "is", "assumed", "to", "only", "be", "used", "if", "no", "moves", "have", "been", "made", "to", "the", "game_state", "object", "since", "castli...
def computer_move(game_state): global node_counter node_counter = 0 moves = game_state.legal_moves_no_castlings() + game_state.castlings() number_of_pieces = 0 for s in range(64): if game_state.board[s] != None: number_of_pieces += 1 if number_of_pieces > 15: depth = ...
[ "def", "computer_move", "(", "game_state", ")", ":", "global", "node_counter", "node_counter", "=", "0", "moves", "=", "game_state", ".", "legal_moves_no_castlings", "(", ")", "+", "game_state", ".", "castlings", "(", ")", "number_of_pieces", "=", "0", "for", ...
Return a move that is computed with the minimax algorithm.
[ "Return", "a", "move", "that", "is", "computed", "with", "the", "minimax", "algorithm", "." ]
[ "\"\"\"Return a move that is computed with the minimax algorithm.\n This function is assumed to only be used if no moves\n have been made to the game_state object, since castling rights may not\n valid then.\"\"\"", "# The move order is randomized in order to make opening move", "# selection more natur...
[ { "param": "game_state", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "game_state", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
df422f66e0e4fdc8145032278935ef89104f9c20
moisesejimenezg/traffic_sign_classifier
src/layers.py
[ "MIT" ]
Python
linear_network
<not_specific>
def linear_network(x_in: int, in_dim: int, out_dim: int, mu_in=mu, sigma_in=sigma): """ Create a linear network layer with the input parameters provided. """ W = tf.Variable( tf.truncated_normal(shape=(in_dim, out_dim), mean=mu_in, stddev=sigma_in) ) B = tf.Variable(tf.zeros(shape=(1, ou...
Create a linear network layer with the input parameters provided.
Create a linear network layer with the input parameters provided.
[ "Create", "a", "linear", "network", "layer", "with", "the", "input", "parameters", "provided", "." ]
def linear_network(x_in: int, in_dim: int, out_dim: int, mu_in=mu, sigma_in=sigma): W = tf.Variable( tf.truncated_normal(shape=(in_dim, out_dim), mean=mu_in, stddev=sigma_in) ) B = tf.Variable(tf.zeros(shape=(1, out_dim))) y_out = tf.matmul(x_in, W) + B return y_out
[ "def", "linear_network", "(", "x_in", ":", "int", ",", "in_dim", ":", "int", ",", "out_dim", ":", "int", ",", "mu_in", "=", "mu", ",", "sigma_in", "=", "sigma", ")", ":", "W", "=", "tf", ".", "Variable", "(", "tf", ".", "truncated_normal", "(", "sh...
Create a linear network layer with the input parameters provided.
[ "Create", "a", "linear", "network", "layer", "with", "the", "input", "parameters", "provided", "." ]
[ "\"\"\"\n Create a linear network layer with the input parameters provided.\n \"\"\"" ]
[ { "param": "x_in", "type": "int" }, { "param": "in_dim", "type": "int" }, { "param": "out_dim", "type": "int" }, { "param": "mu_in", "type": null }, { "param": "sigma_in", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "x_in", "type": "int", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "in_dim", "type": "int", "docstring": null, "docstring_tokens...
df422f66e0e4fdc8145032278935ef89104f9c20
moisesejimenezg/traffic_sign_classifier
src/layers.py
[ "MIT" ]
Python
convolutional_network
<not_specific>
def convolutional_network( x_in: int, in_h_w: int, in_depth: int, filter_h_w: int, out_depth: int ): """ Create a convolutional network layer with the input parameters provided. """ out_h_w = (in_h_w - filter_h_w) + 1 # no padding, stride = 1 W = tf.Variable( tf.truncated_normal( ...
Create a convolutional network layer with the input parameters provided.
Create a convolutional network layer with the input parameters provided.
[ "Create", "a", "convolutional", "network", "layer", "with", "the", "input", "parameters", "provided", "." ]
def convolutional_network( x_in: int, in_h_w: int, in_depth: int, filter_h_w: int, out_depth: int ): out_h_w = (in_h_w - filter_h_w) + 1 W = tf.Variable( tf.truncated_normal( shape=(filter_h_w, filter_h_w, in_depth, out_depth), mean=mu, stddev=sigma ) ) B = tf.Variable(...
[ "def", "convolutional_network", "(", "x_in", ":", "int", ",", "in_h_w", ":", "int", ",", "in_depth", ":", "int", ",", "filter_h_w", ":", "int", ",", "out_depth", ":", "int", ")", ":", "out_h_w", "=", "(", "in_h_w", "-", "filter_h_w", ")", "+", "1", "...
Create a convolutional network layer with the input parameters provided.
[ "Create", "a", "convolutional", "network", "layer", "with", "the", "input", "parameters", "provided", "." ]
[ "\"\"\"\n Create a convolutional network layer with the input parameters provided.\n \"\"\"", "# no padding, stride = 1" ]
[ { "param": "x_in", "type": "int" }, { "param": "in_h_w", "type": "int" }, { "param": "in_depth", "type": "int" }, { "param": "filter_h_w", "type": "int" }, { "param": "out_depth", "type": "int" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "x_in", "type": "int", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "in_h_w", "type": "int", "docstring": null, "docstring_tokens...
20856dac91c1b9c08935540b13ec4b6b4437e837
moisesejimenezg/traffic_sign_classifier
src/lenet.py
[ "MIT" ]
Python
network
<not_specific>
def network( x: tf.placeholder, grayscale: bool, normalize: bool, low_keep_prob: float, high_keep_prob: float, ): """ Multilayer network to classify traffic sign images. @param x: input images @param grayscale: whether the images should be converted to grayscale @param normalize:...
Multilayer network to classify traffic sign images. @param x: input images @param grayscale: whether the images should be converted to grayscale @param normalize: whether the converted images should be normalized @param low_keep_prob: a lower probability of keeping values for the dropout regulariza...
Multilayer network to classify traffic sign images.
[ "Multilayer", "network", "to", "classify", "traffic", "sign", "images", "." ]
def network( x: tf.placeholder, grayscale: bool, normalize: bool, low_keep_prob: float, high_keep_prob: float, ): depth = 3 if grayscale: x = tf.image.rgb_to_grayscale(x) depth = 1 if normalize: x = ly.normalize_grayscale(x) layer_1 = ly.convolutional_...
[ "def", "network", "(", "x", ":", "tf", ".", "placeholder", ",", "grayscale", ":", "bool", ",", "normalize", ":", "bool", ",", "low_keep_prob", ":", "float", ",", "high_keep_prob", ":", "float", ",", ")", ":", "depth", "=", "3", "if", "grayscale", ":", ...
Multilayer network to classify traffic sign images.
[ "Multilayer", "network", "to", "classify", "traffic", "sign", "images", "." ]
[ "\"\"\"\n Multilayer network to classify traffic sign images.\n @param x: input images\n @param grayscale: whether the images should be converted to grayscale\n @param normalize: whether the converted images should be normalized\n @param low_keep_prob: a lower probability of keeping values for the dr...
[ { "param": "x", "type": "tf.placeholder" }, { "param": "grayscale", "type": "bool" }, { "param": "normalize", "type": "bool" }, { "param": "low_keep_prob", "type": "float" }, { "param": "high_keep_prob", "type": "float" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "x", "type": "tf.placeholder", "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": false }, { "identifier": "grayscale", "type": "bool", "docstr...
e0f16fca2579b9784de152e49688ba6036bd85af
chinghwayu/python-pytest-cases
pytest_cases/common_pytest.py
[ "BSD-3-Clause" ]
Python
is_fixture
<not_specific>
def is_fixture(fixture_fun # type: Any ): """ Returns True if the provided function is a fixture :param fixture_fun: :return: """ try: fixture_fun._pytestfixturefunction # noqa return True except AttributeError: # not a fixture ? return False
Returns True if the provided function is a fixture :param fixture_fun: :return:
Returns True if the provided function is a fixture
[ "Returns", "True", "if", "the", "provided", "function", "is", "a", "fixture" ]
def is_fixture(fixture_fun ): try: fixture_fun._pytestfixturefunction return True except AttributeError: return False
[ "def", "is_fixture", "(", "fixture_fun", ")", ":", "try", ":", "fixture_fun", ".", "_pytestfixturefunction", "return", "True", "except", "AttributeError", ":", "return", "False" ]
Returns True if the provided function is a fixture
[ "Returns", "True", "if", "the", "provided", "function", "is", "a", "fixture" ]
[ "# type: Any", "\"\"\"\n Returns True if the provided function is a fixture\n\n :param fixture_fun:\n :return:\n \"\"\"", "# noqa", "# not a fixture ?" ]
[ { "param": "fixture_fun", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "fixture_fun", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null,...
e0f16fca2579b9784de152e49688ba6036bd85af
chinghwayu/python-pytest-cases
pytest_cases/common_pytest.py
[ "BSD-3-Clause" ]
Python
safe_isclass
<not_specific>
def safe_isclass(obj # type: object ): # type: (...) -> bool """Ignore any exception via isinstance on Python 3.""" try: return isclass(obj) except Exception: # noqa return False
Ignore any exception via isinstance on Python 3.
Ignore any exception via isinstance on Python 3.
[ "Ignore", "any", "exception", "via", "isinstance", "on", "Python", "3", "." ]
def safe_isclass(obj ): try: return isclass(obj) except Exception: return False
[ "def", "safe_isclass", "(", "obj", ")", ":", "try", ":", "return", "isclass", "(", "obj", ")", "except", "Exception", ":", "return", "False" ]
Ignore any exception via isinstance on Python 3.
[ "Ignore", "any", "exception", "via", "isinstance", "on", "Python", "3", "." ]
[ "# type: object", "# type: (...) -> bool", "\"\"\"Ignore any exception via isinstance on Python 3.\"\"\"", "# noqa" ]
[ { "param": "obj", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "obj", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
e0f16fca2579b9784de152e49688ba6036bd85af
chinghwayu/python-pytest-cases
pytest_cases/common_pytest.py
[ "BSD-3-Clause" ]
Python
assert_is_fixture
null
def assert_is_fixture(fixture_fun # type: Any ): """ Raises a ValueError if the provided fixture function is not a fixture. :param fixture_fun: :return: """ if not is_fixture(fixture_fun): raise ValueError("The provided fixture function does not seem to be a fixtu...
Raises a ValueError if the provided fixture function is not a fixture. :param fixture_fun: :return:
Raises a ValueError if the provided fixture function is not a fixture.
[ "Raises", "a", "ValueError", "if", "the", "provided", "fixture", "function", "is", "not", "a", "fixture", "." ]
def assert_is_fixture(fixture_fun ): if not is_fixture(fixture_fun): raise ValueError("The provided fixture function does not seem to be a fixture: %s. Did you properly decorate " "it ?" % fixture_fun)
[ "def", "assert_is_fixture", "(", "fixture_fun", ")", ":", "if", "not", "is_fixture", "(", "fixture_fun", ")", ":", "raise", "ValueError", "(", "\"The provided fixture function does not seem to be a fixture: %s. Did you properly decorate \"", "\"it ?\"", "%", "fixture_fun", ")...
Raises a ValueError if the provided fixture function is not a fixture.
[ "Raises", "a", "ValueError", "if", "the", "provided", "fixture", "function", "is", "not", "a", "fixture", "." ]
[ "# type: Any", "\"\"\"\n Raises a ValueError if the provided fixture function is not a fixture.\n\n :param fixture_fun:\n :return:\n \"\"\"" ]
[ { "param": "fixture_fun", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "fixture_fun", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null,...
e0f16fca2579b9784de152e49688ba6036bd85af
chinghwayu/python-pytest-cases
pytest_cases/common_pytest.py
[ "BSD-3-Clause" ]
Python
combine_ids
<not_specific>
def combine_ids(paramid_tuples): """ Receives a list of tuples containing ids for each parameterset. Returns the final ids, that are obtained by joining the various param ids by '-' for each test node :param paramid_tuples: :return: """ # return ['-'.join(pid for pid in testid) for test...
Receives a list of tuples containing ids for each parameterset. Returns the final ids, that are obtained by joining the various param ids by '-' for each test node :param paramid_tuples: :return:
Receives a list of tuples containing ids for each parameterset. Returns the final ids, that are obtained by joining the various param ids by '-' for each test node
[ "Receives", "a", "list", "of", "tuples", "containing", "ids", "for", "each", "parameterset", ".", "Returns", "the", "final", "ids", "that", "are", "obtained", "by", "joining", "the", "various", "param", "ids", "by", "'", "-", "'", "for", "each", "test", ...
def combine_ids(paramid_tuples): return ['-'.join(pid for pid in testid) for testid in paramid_tuples]
[ "def", "combine_ids", "(", "paramid_tuples", ")", ":", "return", "[", "'-'", ".", "join", "(", "pid", "for", "pid", "in", "testid", ")", "for", "testid", "in", "paramid_tuples", "]" ]
Receives a list of tuples containing ids for each parameterset.
[ "Receives", "a", "list", "of", "tuples", "containing", "ids", "for", "each", "parameterset", "." ]
[ "\"\"\"\n Receives a list of tuples containing ids for each parameterset.\n Returns the final ids, that are obtained by joining the various param ids by '-' for each test node\n\n :param paramid_tuples:\n :return:\n \"\"\"", "#" ]
[ { "param": "paramid_tuples", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "paramid_tuples", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": nu...
e0f16fca2579b9784de152e49688ba6036bd85af
chinghwayu/python-pytest-cases
pytest_cases/common_pytest.py
[ "BSD-3-Clause" ]
Python
analyze_parameter_set
<not_specific>
def analyze_parameter_set(pmark=None, argnames=None, argvalues=None, ids=None, check_nb=True): """ analyzes a parameter set passed either as a pmark or as distinct (argnames, argvalues, ids) to extract/construct the various ids, marks, and values See also pytest.Metafunc.parametrize method, that ca...
analyzes a parameter set passed either as a pmark or as distinct (argnames, argvalues, ids) to extract/construct the various ids, marks, and values See also pytest.Metafunc.parametrize method, that calls in particular pytest.ParameterSet._for_parametrize and _pytest.python._idvalset :param pm...
analyzes a parameter set passed either as a pmark or as distinct (argnames, argvalues, ids) to extract/construct the various ids, marks, and values
[ "analyzes", "a", "parameter", "set", "passed", "either", "as", "a", "pmark", "or", "as", "distinct", "(", "argnames", "argvalues", "ids", ")", "to", "extract", "/", "construct", "the", "various", "ids", "marks", "and", "values" ]
def analyze_parameter_set(pmark=None, argnames=None, argvalues=None, ids=None, check_nb=True): if pmark is not None: if any(a is not None for a in (argnames, argvalues, ids)): raise ValueError("Either provide a pmark OR the details") argnames = pmark.param_names argvalues = pmark...
[ "def", "analyze_parameter_set", "(", "pmark", "=", "None", ",", "argnames", "=", "None", ",", "argvalues", "=", "None", ",", "ids", "=", "None", ",", "check_nb", "=", "True", ")", ":", "if", "pmark", "is", "not", "None", ":", "if", "any", "(", "a", ...
analyzes a parameter set passed either as a pmark or as distinct (argnames, argvalues, ids) to extract/construct the various ids, marks, and values
[ "analyzes", "a", "parameter", "set", "passed", "either", "as", "a", "pmark", "or", "as", "distinct", "(", "argnames", "argvalues", "ids", ")", "to", "extract", "/", "construct", "the", "various", "ids", "marks", "and", "values" ]
[ "\"\"\"\n analyzes a parameter set passed either as a pmark or as distinct\n (argnames, argvalues, ids) to extract/construct the various ids, marks, and\n values\n\n See also pytest.Metafunc.parametrize method, that calls in particular\n pytest.ParameterSet._for_parametrize and _pytest.python._idvals...
[ { "param": "pmark", "type": null }, { "param": "argnames", "type": null }, { "param": "argvalues", "type": null }, { "param": "ids", "type": null }, { "param": "check_nb", "type": null } ]
{ "returns": [ { "docstring": "ids, marks, values", "docstring_tokens": [ "ids", "marks", "values" ], "type": null } ], "raises": [], "params": [ { "identifier": "pmark", "type": null, "docstring": null, "docstring_tokens": [ ...
e0f16fca2579b9784de152e49688ba6036bd85af
chinghwayu/python-pytest-cases
pytest_cases/common_pytest.py
[ "BSD-3-Clause" ]
Python
ParameterSet
<not_specific>
def ParameterSet(values, id, # noqa marks): """ Dummy function (not a class) used only by parametrize_plus """ if id is not None: raise ValueError("This should not happen as `pytest.param` does not exist in pytest 2") # smart unpack is requ...
Dummy function (not a class) used only by parametrize_plus
Dummy function (not a class) used only by parametrize_plus
[ "Dummy", "function", "(", "not", "a", "class", ")", "used", "only", "by", "parametrize_plus" ]
def ParameterSet(values, id, marks): if id is not None: raise ValueError("This should not happen as `pytest.param` does not exist in pytest 2") val = values[0] if len(values) == 1 else values nbmarks = len(marks) if nbmarks == 0: ...
[ "def", "ParameterSet", "(", "values", ",", "id", ",", "marks", ")", ":", "if", "id", "is", "not", "None", ":", "raise", "ValueError", "(", "\"This should not happen as `pytest.param` does not exist in pytest 2\"", ")", "val", "=", "values", "[", "0", "]", "if", ...
Dummy function (not a class) used only by parametrize_plus
[ "Dummy", "function", "(", "not", "a", "class", ")", "used", "only", "by", "parametrize_plus" ]
[ "# noqa", "\"\"\" Dummy function (not a class) used only by parametrize_plus \"\"\"", "# smart unpack is required for compatibility", "# decorate with the MarkDecorator" ]
[ { "param": "values", "type": null }, { "param": "id", "type": null }, { "param": "marks", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "values", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "id", "type": null, "docstring": null, "docstring_tokens": [...
e0f16fca2579b9784de152e49688ba6036bd85af
chinghwayu/python-pytest-cases
pytest_cases/common_pytest.py
[ "BSD-3-Clause" ]
Python
mini_idval
<not_specific>
def mini_idval( val, # type: object argname, # type: str idx, # type: int ): """ A simplified version of idval where idfn, item and config do not need to be passed. :param val: :param argname: :param idx: :return: """ return _idval(val=val, argname=arg...
A simplified version of idval where idfn, item and config do not need to be passed. :param val: :param argname: :param idx: :return:
A simplified version of idval where idfn, item and config do not need to be passed.
[ "A", "simplified", "version", "of", "idval", "where", "idfn", "item", "and", "config", "do", "not", "need", "to", "be", "passed", "." ]
def mini_idval( val, argname, idx, ): return _idval(val=val, argname=argname, idx=idx, **_idval_kwargs)
[ "def", "mini_idval", "(", "val", ",", "argname", ",", "idx", ",", ")", ":", "return", "_idval", "(", "val", "=", "val", ",", "argname", "=", "argname", ",", "idx", "=", "idx", ",", "**", "_idval_kwargs", ")" ]
A simplified version of idval where idfn, item and config do not need to be passed.
[ "A", "simplified", "version", "of", "idval", "where", "idfn", "item", "and", "config", "do", "not", "need", "to", "be", "passed", "." ]
[ "# type: object", "# type: str", "# type: int", "\"\"\"\n A simplified version of idval where idfn, item and config do not need to be passed.\n\n :param val:\n :param argname:\n :param idx:\n :return:\n \"\"\"" ]
[ { "param": "val", "type": null }, { "param": "argname", "type": null }, { "param": "idx", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "val", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "...
e0f16fca2579b9784de152e49688ba6036bd85af
chinghwayu/python-pytest-cases
pytest_cases/common_pytest.py
[ "BSD-3-Clause" ]
Python
num_mock_patch_args
<not_specific>
def num_mock_patch_args(function): """ return number of arguments used up by mock arguments (if any) """ patchings = getattr(function, "patchings", None) if not patchings: return 0 mock_sentinel = getattr(sys.modules.get("mock"), "DEFAULT", object()) ut_mock_sentinel...
return number of arguments used up by mock arguments (if any)
return number of arguments used up by mock arguments (if any)
[ "return", "number", "of", "arguments", "used", "up", "by", "mock", "arguments", "(", "if", "any", ")" ]
def num_mock_patch_args(function): patchings = getattr(function, "patchings", None) if not patchings: return 0 mock_sentinel = getattr(sys.modules.get("mock"), "DEFAULT", object()) ut_mock_sentinel = getattr(sys.modules.get("unittest.mock"), "DEFAULT", object()) retur...
[ "def", "num_mock_patch_args", "(", "function", ")", ":", "patchings", "=", "getattr", "(", "function", ",", "\"patchings\"", ",", "None", ")", "if", "not", "patchings", ":", "return", "0", "mock_sentinel", "=", "getattr", "(", "sys", ".", "modules", ".", "...
return number of arguments used up by mock arguments (if any)
[ "return", "number", "of", "arguments", "used", "up", "by", "mock", "arguments", "(", "if", "any", ")" ]
[ "\"\"\" return number of arguments used up by mock arguments (if any) \"\"\"" ]
[ { "param": "function", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "function", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
e0f16fca2579b9784de152e49688ba6036bd85af
chinghwayu/python-pytest-cases
pytest_cases/common_pytest.py
[ "BSD-3-Clause" ]
Python
cart_product_pytest
<not_specific>
def cart_product_pytest(argnames, argvalues): """ - do NOT use `itertools.product` as it fails to handle MarkDecorators - we also unpack tuples associated with several argnames ("a,b") if needed - we also propagate marks :param argnames: :param argvalues: :return: """ # transform...
- do NOT use `itertools.product` as it fails to handle MarkDecorators - we also unpack tuples associated with several argnames ("a,b") if needed - we also propagate marks :param argnames: :param argvalues: :return:
do NOT use `itertools.product` as it fails to handle MarkDecorators we also unpack tuples associated with several argnames ("a,b") if needed we also propagate marks
[ "do", "NOT", "use", "`", "itertools", ".", "product", "`", "as", "it", "fails", "to", "handle", "MarkDecorators", "we", "also", "unpack", "tuples", "associated", "with", "several", "argnames", "(", "\"", "a", "b", "\"", ")", "if", "needed", "we", "also",...
def cart_product_pytest(argnames, argvalues): argnames_lists = [get_param_argnames_as_list(_argnames) if len(_argnames) > 0 else [] for _argnames in argnames] argvalues_prod = _cart_product_pytest(argnames_lists, argvalues) argnames_list = [n for nlist in argnames_lists for n in nlist] argvalues_prod = ...
[ "def", "cart_product_pytest", "(", "argnames", ",", "argvalues", ")", ":", "argnames_lists", "=", "[", "get_param_argnames_as_list", "(", "_argnames", ")", "if", "len", "(", "_argnames", ")", ">", "0", "else", "[", "]", "for", "_argnames", "in", "argnames", ...
do NOT use `itertools.product` as it fails to handle MarkDecorators we also unpack tuples associated with several argnames ("a,b") if needed we also propagate marks
[ "do", "NOT", "use", "`", "itertools", ".", "product", "`", "as", "it", "fails", "to", "handle", "MarkDecorators", "we", "also", "unpack", "tuples", "associated", "with", "several", "argnames", "(", "\"", "a", "b", "\"", ")", "if", "needed", "we", "also",...
[ "\"\"\"\n - do NOT use `itertools.product` as it fails to handle MarkDecorators\n - we also unpack tuples associated with several argnames (\"a,b\") if needed\n - we also propagate marks\n\n :param argnames:\n :param argvalues:\n :return:\n \"\"\"", "# transform argnames into a list of lis...
[ { "param": "argnames", "type": null }, { "param": "argvalues", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "argnames", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
7ea54afc6a940c580f2f407dca31f64d154365e8
chinghwayu/python-pytest-cases
pytest_cases/fixture_parametrize_plus.py
[ "BSD-3-Clause" ]
Python
_fixture_product
<not_specific>
def _fixture_product(caller_module, name, # type: str fixtures_or_values, fixture_positions, scope="function", # type: str ids=None, # type: Union[Callable, List[str]] ...
Internal implementation for fixture products created by pytest parametrize plus. :param caller_module: :param name: :param fixtures_or_values: :param fixture_positions: :param idstyle: :param scope: :param ids: :param unpack_into: :param autouse: :param kwargs: :return:...
Internal implementation for fixture products created by pytest parametrize plus.
[ "Internal", "implementation", "for", "fixture", "products", "created", "by", "pytest", "parametrize", "plus", "." ]
def _fixture_product(caller_module, name, fixtures_or_values, fixture_positions, scope="function", ids=None, unpack_into=None, autouse=Fa...
[ "def", "_fixture_product", "(", "caller_module", ",", "name", ",", "fixtures_or_values", ",", "fixture_positions", ",", "scope", "=", "\"function\"", ",", "ids", "=", "None", ",", "unpack_into", "=", "None", ",", "autouse", "=", "False", ",", "hook", "=", "N...
Internal implementation for fixture products created by pytest parametrize plus.
[ "Internal", "implementation", "for", "fixture", "products", "created", "by", "pytest", "parametrize", "plus", "." ]
[ "# type: str", "# type: str", "# type: Union[Callable, List[str]]", "# type: Iterable[str]", "# type: bool", "# type: Callable[[Callable], Callable]", "# type: Callable", "\"\"\"\n Internal implementation for fixture products created by pytest parametrize plus.\n\n :param caller_module:\n :pa...
[ { "param": "caller_module", "type": null }, { "param": "name", "type": null }, { "param": "fixtures_or_values", "type": null }, { "param": "fixture_positions", "type": null }, { "param": "scope", "type": null }, { "param": "ids", "type": null }, ...
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "caller_module", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": nul...
7ea54afc6a940c580f2f407dca31f64d154365e8
chinghwayu/python-pytest-cases
pytest_cases/fixture_parametrize_plus.py
[ "BSD-3-Clause" ]
Python
parametrize_plus
<not_specific>
def parametrize_plus(argnames=None, # type: str argvalues=None, # type: Iterable[Any] indirect=False, # type: bool ids=None, # type: Union[Callable, List[str]] idstyle='explicit', # type: str ...
Equivalent to `@pytest.mark.parametrize` but also supports (1) new alternate style for argnames/argvalues. One can also use `**args` to pass additional `{argnames: argvalues}` in the same parametrization call. This can be handy in combination with `idgen` to master the whole id template associated wit...
Equivalent to `@pytest.mark.parametrize` but also supports (1) new alternate style for argnames/argvalues. One can also use `**args` to pass additional `{argnames: argvalues}` in the same parametrization call. This can be handy in combination with `idgen` to master the whole id template associated with several paramete...
[ "Equivalent", "to", "`", "@pytest", ".", "mark", ".", "parametrize", "`", "but", "also", "supports", "(", "1", ")", "new", "alternate", "style", "for", "argnames", "/", "argvalues", ".", "One", "can", "also", "use", "`", "**", "args", "`", "to", "pass"...
def parametrize_plus(argnames=None, argvalues=None, indirect=False, ids=None, idstyle='explicit', idgen=_IDGEN, scope=None, ...
[ "def", "parametrize_plus", "(", "argnames", "=", "None", ",", "argvalues", "=", "None", ",", "indirect", "=", "False", ",", "ids", "=", "None", ",", "idstyle", "=", "'explicit'", ",", "idgen", "=", "_IDGEN", ",", "scope", "=", "None", ",", "hook", "=",...
Equivalent to `@pytest.mark.parametrize` but also supports (1) new alternate style for argnames/argvalues.
[ "Equivalent", "to", "`", "@pytest", ".", "mark", ".", "parametrize", "`", "but", "also", "supports", "(", "1", ")", "new", "alternate", "style", "for", "argnames", "/", "argvalues", "." ]
[ "# type: str", "# type: Iterable[Any]", "# type: bool", "# type: Union[Callable, List[str]]", "# type: str", "# type: Union[str, Callable]", "# type: str", "# type: Callable[[Callable], Callable]", "# type: bool", "\"\"\"\n Equivalent to `@pytest.mark.parametrize` but also supports\n\n (1) n...
[ { "param": "argnames", "type": null }, { "param": "argvalues", "type": null }, { "param": "indirect", "type": null }, { "param": "ids", "type": null }, { "param": "idstyle", "type": null }, { "param": "idgen", "type": null }, { "param": "sc...
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "argnames", "type": null, "docstring": "same as in pytest.mark.parametrize", "docstring_tokens": [ "same", ...
7ea54afc6a940c580f2f407dca31f64d154365e8
chinghwayu/python-pytest-cases
pytest_cases/fixture_parametrize_plus.py
[ "BSD-3-Clause" ]
Python
_create_params_alt
<not_specific>
def _create_params_alt(test_func_name, union_name, from_i, to_i, hook): # noqa """ Routine that will be used to create a parameter fixture for argvalues between prev_i and i""" # check if this is about a single value or several values single_param_val = (to_i == from_i + 1) ...
Routine that will be used to create a parameter fixture for argvalues between prev_i and i
Routine that will be used to create a parameter fixture for argvalues between prev_i and i
[ "Routine", "that", "will", "be", "used", "to", "create", "a", "parameter", "fixture", "for", "argvalues", "between", "prev_i", "and", "i" ]
def _create_params_alt(test_func_name, union_name, from_i, to_i, hook): single_param_val = (to_i == from_i + 1) if single_param_val: i = from_i p_fix_name = "%s_%s_P%s" % (test_func_name, param_names_str, i) p_fix_name = check_name_available(ca...
[ "def", "_create_params_alt", "(", "test_func_name", ",", "union_name", ",", "from_i", ",", "to_i", ",", "hook", ")", ":", "single_param_val", "=", "(", "to_i", "==", "from_i", "+", "1", ")", "if", "single_param_val", ":", "i", "=", "from_i", "p_fix_name", ...
Routine that will be used to create a parameter fixture for argvalues between prev_i and i
[ "Routine", "that", "will", "be", "used", "to", "create", "a", "parameter", "fixture", "for", "argvalues", "between", "prev_i", "and", "i" ]
[ "# noqa", "\"\"\" Routine that will be used to create a parameter fixture for argvalues between prev_i and i\"\"\"", "# check if this is about a single value or several values", "# noqa", "# Create a unique fixture name", "# Create the fixture that will return the unique parameter value (\"auto-simplify\"...
[ { "param": "test_func_name", "type": null }, { "param": "union_name", "type": null }, { "param": "from_i", "type": null }, { "param": "to_i", "type": null }, { "param": "hook", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "test_func_name", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "union_name", "type": null, "docstring": null, "docs...
7ea54afc6a940c580f2f407dca31f64d154365e8
chinghwayu/python-pytest-cases
pytest_cases/fixture_parametrize_plus.py
[ "BSD-3-Clause" ]
Python
parametrize_plus_decorate
<not_specific>
def parametrize_plus_decorate(test_func): """ A decorator that wraps the test function so that instead of receiving the parameter names, it receives the new fixture. All other decorations are unchanged. :param test_func: :return: """ t...
A decorator that wraps the test function so that instead of receiving the parameter names, it receives the new fixture. All other decorations are unchanged. :param test_func: :return:
A decorator that wraps the test function so that instead of receiving the parameter names, it receives the new fixture. All other decorations are unchanged.
[ "A", "decorator", "that", "wraps", "the", "test", "function", "so", "that", "instead", "of", "receiving", "the", "parameter", "names", "it", "receives", "the", "new", "fixture", ".", "All", "other", "decorations", "are", "unchanged", "." ]
def parametrize_plus_decorate(test_func): test_func_name = test_func.__name__ try: if len(ids) != len(argvalues): raise ValueError("Explicit list of `ids` provided has a different length (%s) than the number of " "parameter...
[ "def", "parametrize_plus_decorate", "(", "test_func", ")", ":", "test_func_name", "=", "test_func", ".", "__name__", "try", ":", "if", "len", "(", "ids", ")", "!=", "len", "(", "argvalues", ")", ":", "raise", "ValueError", "(", "\"Explicit list of `ids` provided...
A decorator that wraps the test function so that instead of receiving the parameter names, it receives the new fixture.
[ "A", "decorator", "that", "wraps", "the", "test", "function", "so", "that", "instead", "of", "receiving", "the", "parameter", "names", "it", "receives", "the", "new", "fixture", "." ]
[ "\"\"\"\n A decorator that wraps the test function so that instead of receiving the parameter names, it receives the\n new fixture. All other decorations are unchanged.\n\n :param test_func:\n :return:\n \"\"\"", "# Are there explicit ids provided ?", "# fi...
[ { "param": "test_func", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "test_func", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
7ea54afc6a940c580f2f407dca31f64d154365e8
chinghwayu/python-pytest-cases
pytest_cases/fixture_parametrize_plus.py
[ "BSD-3-Clause" ]
Python
_process_argvalues
<not_specific>
def _process_argvalues(argnames, marked_argvalues, nb_params): """Internal method to use in _pytest_parametrize_plus Processes the provided marked_argvalues (possibly marked with pytest.param) and returns p_ids, p_marks, argvalues (not marked with pytest.param), fixture_indices Note: `marked_argvalues...
Internal method to use in _pytest_parametrize_plus Processes the provided marked_argvalues (possibly marked with pytest.param) and returns p_ids, p_marks, argvalues (not marked with pytest.param), fixture_indices Note: `marked_argvalues` is modified in the process if a `lazy_value` is found with a custom ...
Internal method to use in _pytest_parametrize_plus Processes the provided marked_argvalues (possibly marked with pytest.param) and returns p_ids, p_marks, argvalues (not marked with pytest.param), fixture_indices `marked_argvalues` is modified in the process if a `lazy_value` is found with a custom id or marks.
[ "Internal", "method", "to", "use", "in", "_pytest_parametrize_plus", "Processes", "the", "provided", "marked_argvalues", "(", "possibly", "marked", "with", "pytest", ".", "param", ")", "and", "returns", "p_ids", "p_marks", "argvalues", "(", "not", "marked", "with"...
def _process_argvalues(argnames, marked_argvalues, nb_params): p_ids, p_marks, argvalues = extract_parameterset_info(argnames, marked_argvalues, check_nb=False) fixture_indices = [] if nb_params == 1: for i, v in enumerate(argvalues): if is_lazy_value(v): _mks = v.get_mar...
[ "def", "_process_argvalues", "(", "argnames", ",", "marked_argvalues", ",", "nb_params", ")", ":", "p_ids", ",", "p_marks", ",", "argvalues", "=", "extract_parameterset_info", "(", "argnames", ",", "marked_argvalues", ",", "check_nb", "=", "False", ")", "fixture_i...
Internal method to use in _pytest_parametrize_plus Processes the provided marked_argvalues (possibly marked with pytest.param) and returns p_ids, p_marks, argvalues (not marked with pytest.param), fixture_indices
[ "Internal", "method", "to", "use", "in", "_pytest_parametrize_plus", "Processes", "the", "provided", "marked_argvalues", "(", "possibly", "marked", "with", "pytest", ".", "param", ")", "and", "returns", "p_ids", "p_marks", "argvalues", "(", "not", "marked", "with"...
[ "\"\"\"Internal method to use in _pytest_parametrize_plus\n\n Processes the provided marked_argvalues (possibly marked with pytest.param) and returns\n p_ids, p_marks, argvalues (not marked with pytest.param), fixture_indices\n\n Note: `marked_argvalues` is modified in the process if a `lazy_value` is foun...
[ { "param": "argnames", "type": null }, { "param": "marked_argvalues", "type": null }, { "param": "nb_params", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "argnames", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, ...
ab7434daee3f5d52f82bc375044d0ccce35ac6ab
chinghwayu/python-pytest-cases
pytest_cases/case_funcs_new.py
[ "BSD-3-Clause" ]
Python
matches_tag_query
<not_specific>
def matches_tag_query(case_fun, has_tag=None, # type: Union[str, Iterable[str]] filter=None, # type: Union[Callable[[Iterable[Any]], bool], Iterable[Callable[[Iterable[Any]], bool]]] # noqa ): """ Returns True if the case function is selected...
Returns True if the case function is selected by the query: - if `has_tag` contains one or several tags, they should ALL be present in the tags set on `case_fun` (`case_fun._pytestcase.tags`) - if `filter` contains one or several filter callables, they are all called in sequence and the c...
if `filter` contains one or several filter callables, they are all called in sequence and the case_fun is only selected if ALL of them return a True truth value
[ "if", "`", "filter", "`", "contains", "one", "or", "several", "filter", "callables", "they", "are", "all", "called", "in", "sequence", "and", "the", "case_fun", "is", "only", "selected", "if", "ALL", "of", "them", "return", "a", "True", "truth", "value" ]
def matches_tag_query(case_fun, has_tag=None, filter=None, ): selected = True if has_tag is not None: selected = selected and CaseInfo.get_from(case_fun).matches_tag_query(has_tag) if filter is not None: if not isinstance...
[ "def", "matches_tag_query", "(", "case_fun", ",", "has_tag", "=", "None", ",", "filter", "=", "None", ",", ")", ":", "selected", "=", "True", "if", "has_tag", "is", "not", "None", ":", "selected", "=", "selected", "and", "CaseInfo", ".", "get_from", "(",...
Returns True if the case function is selected by the query: if `has_tag` contains one or several tags, they should ALL be present in the tags set on `case_fun` (`case_fun._pytestcase.tags`)
[ "Returns", "True", "if", "the", "case", "function", "is", "selected", "by", "the", "query", ":", "if", "`", "has_tag", "`", "contains", "one", "or", "several", "tags", "they", "should", "ALL", "be", "present", "in", "the", "tags", "set", "on", "`", "ca...
[ "# type: Union[str, Iterable[str]]", "# type: Union[Callable[[Iterable[Any]], bool], Iterable[Callable[[Iterable[Any]], bool]]] # noqa", "\"\"\"\n Returns True if the case function is selected by the query:\n\n - if `has_tag` contains one or several tags, they should ALL be present in the tags\n s...
[ { "param": "case_fun", "type": null }, { "param": "has_tag", "type": null }, { "param": "filter", "type": null } ]
{ "returns": [ { "docstring": "True if the case_fun is selected by the query.", "docstring_tokens": [ "True", "if", "the", "case_fun", "is", "selected", "by", "the", "query", "." ], "type": null } ], "r...
ab7434daee3f5d52f82bc375044d0ccce35ac6ab
chinghwayu/python-pytest-cases
pytest_cases/case_funcs_new.py
[ "BSD-3-Clause" ]
Python
case
<not_specific>
def case(id=None, # type: str # noqa tags=None, # type: Union[Any, Iterable[Any]] marks=(), # type: Union[MarkDecorator, Iterable[MarkDecorator]] case_func=DECORATED # noqa ): """ Optional decorator for case functions so as to customize some...
Optional decorator for case functions so as to customize some information. ```python @case(id='hey') def case_hi(): return 1 ``` :param id: the custom pytest id that should be used when this case is active. Replaces the deprecated `@case_name` decorator from v1. If no id is pr...
Optional decorator for case functions so as to customize some information.
[ "Optional", "decorator", "for", "case", "functions", "so", "as", "to", "customize", "some", "information", "." ]
def case(id=None, tags=None, marks=(), case_func=DECORATED ): case_info = CaseInfo(id, marks, tags) case_info.attach_to(case_func) return case_func
[ "def", "case", "(", "id", "=", "None", ",", "tags", "=", "None", ",", "marks", "=", "(", ")", ",", "case_func", "=", "DECORATED", ")", ":", "case_info", "=", "CaseInfo", "(", "id", ",", "marks", ",", "tags", ")", "case_info", ".", "attach_to", "(",...
Optional decorator for case functions so as to customize some information.
[ "Optional", "decorator", "for", "case", "functions", "so", "as", "to", "customize", "some", "information", "." ]
[ "# type: str # noqa", "# type: Union[Any, Iterable[Any]]", "# type: Union[MarkDecorator, Iterable[MarkDecorator]]", "# noqa", "\"\"\"\n Optional decorator for case functions so as to customize some information.\n\n ```python\n @case(id='hey')\n def case_hi():\n return 1\n ```\n\n :...
[ { "param": "id", "type": null }, { "param": "tags", "type": null }, { "param": "marks", "type": null }, { "param": "case_func", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "id", "type": null, "docstring": "the custom pytest id that should be used when this case is active. Replaces the deprecat...
0757457b7be5da92371a9fdb26b80a3972256725
zachjweiner/pystella
pystella/multigrid/transfer.py
[ "MIT" ]
Python
RestrictionBase
<not_specific>
def RestrictionBase(coefs, StencilKernel, halo_shape, **kwargs): """ A base function for generating a restriction kernel. :arg coefs: The coefficients representing the restriction formula. Follows the convention of :func:`pystella.derivs.centered_diff` (since the restriction is applie...
A base function for generating a restriction kernel. :arg coefs: The coefficients representing the restriction formula. Follows the convention of :func:`pystella.derivs.centered_diff` (since the restriction is applied recursively in each dimension). :arg StencilKernel: The stencil ...
A base function for generating a restriction kernel.
[ "A", "base", "function", "for", "generating", "a", "restriction", "kernel", "." ]
def RestrictionBase(coefs, StencilKernel, halo_shape, **kwargs): lsize = kwargs.pop("lsize", (4, 4, 4)) for N in ["Nx", "Ny", "Nz"]: _ = kwargs.pop(N, None) restrict_coefs = {} for a, c_a in coefs.items(): for b, c_b in coefs.items(): for c, c_c in coefs.items(): ...
[ "def", "RestrictionBase", "(", "coefs", ",", "StencilKernel", ",", "halo_shape", ",", "**", "kwargs", ")", ":", "lsize", "=", "kwargs", ".", "pop", "(", "\"lsize\"", ",", "(", "4", ",", "4", ",", "4", ")", ")", "for", "N", "in", "[", "\"Nx\"", ",",...
A base function for generating a restriction kernel.
[ "A", "base", "function", "for", "generating", "a", "restriction", "kernel", "." ]
[ "\"\"\"\r\n A base function for generating a restriction kernel.\r\n\r\n :arg coefs: The coefficients representing the restriction formula.\r\n Follows the convention of :func:`pystella.derivs.centered_diff`\r\n (since the restriction is applied recursively in each dimension).\r\n\r\n :arg St...
[ { "param": "coefs", "type": null }, { "param": "StencilKernel", "type": null }, { "param": "halo_shape", "type": null } ]
{ "returns": [ { "docstring": "An instance of ``StencilKernel`` which executes the requested\nrestriction.", "docstring_tokens": [ "An", "instance", "of", "`", "`", "StencilKernel", "`", "`", "which", "executes", "...
0757457b7be5da92371a9fdb26b80a3972256725
zachjweiner/pystella
pystella/multigrid/transfer.py
[ "MIT" ]
Python
FullWeighting
<not_specific>
def FullWeighting(StencilKernel=Stencil, **kwargs): """ Creates a full-weighting restriction kernel, which restricts in input array :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the coarse grid by applying .. math:: f^{(2 h)}_i = \\frac{1}{4} f^{(h)}_...
Creates a full-weighting restriction kernel, which restricts in input array :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the coarse grid by applying .. math:: f^{(2 h)}_i = \\frac{1}{4} f^{(h)}_{2 i - 1} + \\frac{1}{2} f^{(h)}_{2 i} ...
Creates a full-weighting restriction kernel, which restricts in input array
[ "Creates", "a", "full", "-", "weighting", "restriction", "kernel", "which", "restricts", "in", "input", "array" ]
def FullWeighting(StencilKernel=Stencil, **kwargs): from pymbolic.primitives import Quotient coefs = {-1: Quotient(1, 4), 0: Quotient(1, 2), 1: Quotient(1, 4)} return RestrictionBase(coefs, StencilKernel, **kwargs)
[ "def", "FullWeighting", "(", "StencilKernel", "=", "Stencil", ",", "**", "kwargs", ")", ":", "from", "pymbolic", ".", "primitives", "import", "Quotient", "coefs", "=", "{", "-", "1", ":", "Quotient", "(", "1", ",", "4", ")", ",", "0", ":", "Quotient", ...
Creates a full-weighting restriction kernel, which restricts in input array
[ "Creates", "a", "full", "-", "weighting", "restriction", "kernel", "which", "restricts", "in", "input", "array" ]
[ "\"\"\"\r\n Creates a full-weighting restriction kernel, which restricts in input array\r\n :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the\r\n coarse grid by applying\r\n\r\n .. math::\r\n\r\n f^{(2 h)}_i\r\n = \\\\frac{1}{4} f^{(h)}_{2 i - 1}\r\n + \\\\...
[ { "param": "StencilKernel", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "StencilKernel", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [ { "identifier": "math", "docstring": "`...
0757457b7be5da92371a9fdb26b80a3972256725
zachjweiner/pystella
pystella/multigrid/transfer.py
[ "MIT" ]
Python
Injection
<not_specific>
def Injection(StencilKernel=ElementWiseMap, **kwargs): """ Creates an injection kernel, which restricts in input array :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the coarse grid by direct injection: .. math:: f^{(2 h)}_{i, j ,k} = f^{(h)}_{2 i, 2 j...
Creates an injection kernel, which restricts in input array :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the coarse grid by direct injection: .. math:: f^{(2 h)}_{i, j ,k} = f^{(h)}_{2 i, 2 j, 2 k} See :class:`transfer.RestrictionBase`.
Creates an injection kernel, which restricts in input array
[ "Creates", "an", "injection", "kernel", "which", "restricts", "in", "input", "array" ]
def Injection(StencilKernel=ElementWiseMap, **kwargs): coefs = {0: 1} return RestrictionBase(coefs, StencilKernel, **kwargs)
[ "def", "Injection", "(", "StencilKernel", "=", "ElementWiseMap", ",", "**", "kwargs", ")", ":", "coefs", "=", "{", "0", ":", "1", "}", "return", "RestrictionBase", "(", "coefs", ",", "StencilKernel", ",", "**", "kwargs", ")" ]
Creates an injection kernel, which restricts in input array
[ "Creates", "an", "injection", "kernel", "which", "restricts", "in", "input", "array" ]
[ "\"\"\"\r\n Creates an injection kernel, which restricts in input array\r\n :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the\r\n coarse grid by direct injection:\r\n\r\n .. math::\r\n\r\n f^{(2 h)}_{i, j ,k}\r\n = f^{(h)}_{2 i, 2 j, 2 k}\r\n\r\n See :class:`transf...
[ { "param": "StencilKernel", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "StencilKernel", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [ { "identifier": "math", "docstring": "`...
0757457b7be5da92371a9fdb26b80a3972256725
zachjweiner/pystella
pystella/multigrid/transfer.py
[ "MIT" ]
Python
InterpolationBase
<not_specific>
def InterpolationBase(even_coefs, odd_coefs, StencilKernel, halo_shape, **kwargs): """ A base function for generating a restriction kernel. :arg even_coefs: The coefficients representing the interpolation formula for gridpoints on the coarse and fine grid which coincide in space. Foll...
A base function for generating a restriction kernel. :arg even_coefs: The coefficients representing the interpolation formula for gridpoints on the coarse and fine grid which coincide in space. Follows the convention of :func:`pystella.derivs.centered_diff` (since the restriction...
A base function for generating a restriction kernel.
[ "A", "base", "function", "for", "generating", "a", "restriction", "kernel", "." ]
def InterpolationBase(even_coefs, odd_coefs, StencilKernel, halo_shape, **kwargs): from pymbolic import parse, var i, j, k = parse("i, j, k") f1 = Field("f1", offset="h") tmp_insns = {} tmp = var("tmp") import itertools for parity in tuple(itertools.product((0, 1), (0, 1), (0, 1))): ...
[ "def", "InterpolationBase", "(", "even_coefs", ",", "odd_coefs", ",", "StencilKernel", ",", "halo_shape", ",", "**", "kwargs", ")", ":", "from", "pymbolic", "import", "parse", ",", "var", "i", ",", "j", ",", "k", "=", "parse", "(", "\"i, j, k\"", ")", "f...
A base function for generating a restriction kernel.
[ "A", "base", "function", "for", "generating", "a", "restriction", "kernel", "." ]
[ "\"\"\"\r\n A base function for generating a restriction kernel.\r\n\r\n :arg even_coefs: The coefficients representing the interpolation formula\r\n for gridpoints on the coarse and fine grid which coincide in space.\r\n Follows the convention of :func:`pystella.derivs.centered_diff`\r\n ...
[ { "param": "even_coefs", "type": null }, { "param": "odd_coefs", "type": null }, { "param": "StencilKernel", "type": null }, { "param": "halo_shape", "type": null } ]
{ "returns": [ { "docstring": "An instance of ``StencilKernel`` which executes the requested\ninterpolation.", "docstring_tokens": [ "An", "instance", "of", "`", "`", "StencilKernel", "`", "`", "which", "executes", ...
0757457b7be5da92371a9fdb26b80a3972256725
zachjweiner/pystella
pystella/multigrid/transfer.py
[ "MIT" ]
Python
LinearInterpolation
<not_specific>
def LinearInterpolation(StencilKernel=Stencil, **kwargs): """ Creates an linear interpolation kernel, which interpolates in input array :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the coarse grid via .. math:: f^{(h)}_{2 i} &= f^{(2 h)}_{i} ...
Creates an linear interpolation kernel, which interpolates in input array :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the coarse grid via .. math:: f^{(h)}_{2 i} &= f^{(2 h)}_{i} f^{(h)}_{2 i + 1} &= \\frac{1}{2} f^{(2 h)}_{i} + \\fr...
Creates an linear interpolation kernel, which interpolates in input array
[ "Creates", "an", "linear", "interpolation", "kernel", "which", "interpolates", "in", "input", "array" ]
def LinearInterpolation(StencilKernel=Stencil, **kwargs): from pymbolic.primitives import Quotient odd_coefs = {-1: Quotient(1, 2), 1: Quotient(1, 2)} even_coefs = {0: 1} return InterpolationBase(even_coefs, odd_coefs, StencilKernel, **kwargs)
[ "def", "LinearInterpolation", "(", "StencilKernel", "=", "Stencil", ",", "**", "kwargs", ")", ":", "from", "pymbolic", ".", "primitives", "import", "Quotient", "odd_coefs", "=", "{", "-", "1", ":", "Quotient", "(", "1", ",", "2", ")", ",", "1", ":", "Q...
Creates an linear interpolation kernel, which interpolates in input array
[ "Creates", "an", "linear", "interpolation", "kernel", "which", "interpolates", "in", "input", "array" ]
[ "\"\"\"\r\n Creates an linear interpolation kernel, which interpolates in input array\r\n :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the\r\n coarse grid via\r\n\r\n .. math::\r\n\r\n f^{(h)}_{2 i}\r\n &= f^{(2 h)}_{i}\r\n\r\n f^{(h)}_{2 i + 1}\r\n &= ...
[ { "param": "StencilKernel", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "StencilKernel", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [ { "identifier": "math", "docstring": "`...
0757457b7be5da92371a9fdb26b80a3972256725
zachjweiner/pystella
pystella/multigrid/transfer.py
[ "MIT" ]
Python
CubicInterpolation
<not_specific>
def CubicInterpolation(StencilKernel=Stencil, **kwargs): """ Creates an cubic interpolation kernel, which interpolates in input array :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the coarse grid via .. math:: f^{(h)}_{2 i} &= f^{(2 h)}_{i} ...
Creates an cubic interpolation kernel, which interpolates in input array :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the coarse grid via .. math:: f^{(h)}_{2 i} &= f^{(2 h)}_{i} f^{(h)}_{2 i + 1} &= - \\frac{1}{16} f^{(2 h)}_{i - 1} ...
Creates an cubic interpolation kernel, which interpolates in input array
[ "Creates", "an", "cubic", "interpolation", "kernel", "which", "interpolates", "in", "input", "array" ]
def CubicInterpolation(StencilKernel=Stencil, **kwargs): if kwargs.get("halo_shape", 0) < 2: raise ValueError("CubicInterpolation requires padding >= 2") from pymbolic.primitives import Quotient odd_coefs = {-3: Quotient(-1, 16), -1: Quotient(9, 16), 1: Quotient(9, 16), 3: Quotient(...
[ "def", "CubicInterpolation", "(", "StencilKernel", "=", "Stencil", ",", "**", "kwargs", ")", ":", "if", "kwargs", ".", "get", "(", "\"halo_shape\"", ",", "0", ")", "<", "2", ":", "raise", "ValueError", "(", "\"CubicInterpolation requires padding >= 2\"", ")", ...
Creates an cubic interpolation kernel, which interpolates in input array
[ "Creates", "an", "cubic", "interpolation", "kernel", "which", "interpolates", "in", "input", "array" ]
[ "\"\"\"\r\n Creates an cubic interpolation kernel, which interpolates in input array\r\n :math:`f^{(h)}` on the fine grid into an array :math:`f^{(2 h)}` on the\r\n coarse grid via\r\n\r\n .. math::\r\n\r\n f^{(h)}_{2 i}\r\n &= f^{(2 h)}_{i}\r\n\r\n f^{(h)}_{2 i + 1}\r\n &= -...
[ { "param": "StencilKernel", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "StencilKernel", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [ { "identifier": "math", "docstring": "`...
46c229ed222c98cb727ba27dccbfd3e831bb211c
zachjweiner/pystella
pystella/fourier/projectors.py
[ "MIT" ]
Python
pol_to_vec
<not_specific>
def pol_to_vec(self, queue, plus, minus, vector): """ Projects the plus and minus polarizations of a vector field onto its vector components. :arg queue: A :class:`pyopencl.CommandQueue`. :arg plus: The array containing the momentum-space field of the plus p...
Projects the plus and minus polarizations of a vector field onto its vector components. :arg queue: A :class:`pyopencl.CommandQueue`. :arg plus: The array containing the momentum-space field of the plus polarization. :arg minus: The array containing the ...
Projects the plus and minus polarizations of a vector field onto its vector components.
[ "Projects", "the", "plus", "and", "minus", "polarizations", "of", "a", "vector", "field", "onto", "its", "vector", "components", "." ]
def pol_to_vec(self, queue, plus, minus, vector): evt, _ = self.pol_to_vec_knl(queue, **self.eff_mom, vector=vector, plus=plus, minus=minus) return evt
[ "def", "pol_to_vec", "(", "self", ",", "queue", ",", "plus", ",", "minus", ",", "vector", ")", ":", "evt", ",", "_", "=", "self", ".", "pol_to_vec_knl", "(", "queue", ",", "**", "self", ".", "eff_mom", ",", "vector", "=", "vector", ",", "plus", "="...
Projects the plus and minus polarizations of a vector field onto its vector components.
[ "Projects", "the", "plus", "and", "minus", "polarizations", "of", "a", "vector", "field", "onto", "its", "vector", "components", "." ]
[ "\"\"\"\r\n Projects the plus and minus polarizations of a vector field onto its\r\n vector components.\r\n\r\n :arg queue: A :class:`pyopencl.CommandQueue`.\r\n\r\n :arg plus: The array containing the\r\n momentum-space field of the plus polarization.\r\n\r\n :arg minu...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "plus", "type": null }, { "param": "minus", "type": null }, { "param": "vector", "type": null } ]
{ "returns": [ { "docstring": "The :class:`pyopencl.Event` associated with the kernel invocation.", "docstring_tokens": [ "The", ":", "class", ":", "`", "pyopencl", ".", "Event", "`", "associated", "with", ...
46c229ed222c98cb727ba27dccbfd3e831bb211c
zachjweiner/pystella
pystella/fourier/projectors.py
[ "MIT" ]
Python
vec_to_pol
<not_specific>
def vec_to_pol(self, queue, plus, minus, vector): """ Projects the components of a vector field onto the basis of plus and minus polarizations. :arg queue: A :class:`pyopencl.CommandQueue`. :arg plus: The array into which will be stored the momentum-space fi...
Projects the components of a vector field onto the basis of plus and minus polarizations. :arg queue: A :class:`pyopencl.CommandQueue`. :arg plus: The array into which will be stored the momentum-space field of the plus polarization. :arg minus: The array...
Projects the components of a vector field onto the basis of plus and minus polarizations.
[ "Projects", "the", "components", "of", "a", "vector", "field", "onto", "the", "basis", "of", "plus", "and", "minus", "polarizations", "." ]
def vec_to_pol(self, queue, plus, minus, vector): evt, _ = self.vec_to_pol_knl(queue, **self.eff_mom, vector=vector, plus=plus, minus=minus) return evt
[ "def", "vec_to_pol", "(", "self", ",", "queue", ",", "plus", ",", "minus", ",", "vector", ")", ":", "evt", ",", "_", "=", "self", ".", "vec_to_pol_knl", "(", "queue", ",", "**", "self", ".", "eff_mom", ",", "vector", "=", "vector", ",", "plus", "="...
Projects the components of a vector field onto the basis of plus and minus polarizations.
[ "Projects", "the", "components", "of", "a", "vector", "field", "onto", "the", "basis", "of", "plus", "and", "minus", "polarizations", "." ]
[ "\"\"\"\r\n Projects the components of a vector field onto the basis of plus and\r\n minus polarizations.\r\n\r\n :arg queue: A :class:`pyopencl.CommandQueue`.\r\n\r\n :arg plus: The array into which will be stored the\r\n momentum-space field of the plus polarization.\r\n\r\n...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "plus", "type": null }, { "param": "minus", "type": null }, { "param": "vector", "type": null } ]
{ "returns": [ { "docstring": "The :class:`pyopencl.Event` associated with the kernel invocation.", "docstring_tokens": [ "The", ":", "class", ":", "`", "pyopencl", ".", "Event", "`", "associated", "with", ...
46c229ed222c98cb727ba27dccbfd3e831bb211c
zachjweiner/pystella
pystella/fourier/projectors.py
[ "MIT" ]
Python
decompose_vector
<not_specific>
def decompose_vector(self, queue, vector, plus, minus, lng, *, times_abs_k=False): """ Decomposes a vector field into its two transverse polarizations and longitudinal component. :arg queue: A :class:`pyopencl.CommandQueue`. :arg vector: The arr...
Decomposes a vector field into its two transverse polarizations and longitudinal component. :arg queue: A :class:`pyopencl.CommandQueue`. :arg vector: The array whose polarization components will be computed. Must have shape ``(3,)+k_shape``, where ``k_...
Decomposes a vector field into its two transverse polarizations and longitudinal component.
[ "Decomposes", "a", "vector", "field", "into", "its", "two", "transverse", "polarizations", "and", "longitudinal", "component", "." ]
def decompose_vector(self, queue, vector, plus, minus, lng, *, times_abs_k=False): if not times_abs_k: evt, _ = self.vec_decomp_knl( queue, **self.eff_mom, lng=lng, vector=vector, plus=plus, minus=minus ) else: ...
[ "def", "decompose_vector", "(", "self", ",", "queue", ",", "vector", ",", "plus", ",", "minus", ",", "lng", ",", "*", ",", "times_abs_k", "=", "False", ")", ":", "if", "not", "times_abs_k", ":", "evt", ",", "_", "=", "self", ".", "vec_decomp_knl", "(...
Decomposes a vector field into its two transverse polarizations and longitudinal component.
[ "Decomposes", "a", "vector", "field", "into", "its", "two", "transverse", "polarizations", "and", "longitudinal", "component", "." ]
[ "\"\"\"\r\n Decomposes a vector field into its two transverse polarizations and\r\n longitudinal component.\r\n\r\n :arg queue: A :class:`pyopencl.CommandQueue`.\r\n\r\n :arg vector: The array whose polarization\r\n components will be computed.\r\n Must have shape `...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "vector", "type": null }, { "param": "plus", "type": null }, { "param": "minus", "type": null }, { "param": "lng", "type": null }, { "param": "times_abs_k", ...
{ "returns": [ { "docstring": "The :class:`pyopencl.Event` associated with the kernel invocation.", "docstring_tokens": [ "The", ":", "class", ":", "`", "pyopencl", ".", "Event", "`", "associated", "with", ...
46c229ed222c98cb727ba27dccbfd3e831bb211c
zachjweiner/pystella
pystella/fourier/projectors.py
[ "MIT" ]
Python
transverse_traceless
<not_specific>
def transverse_traceless(self, queue, hij, hij_TT=None): """ Projects a tensor field to be transverse and traceless. :arg queue: A :class:`pyopencl.CommandQueue`. :arg hij: The array containing the momentum-space tensor field to be projected. Must have s...
Projects a tensor field to be transverse and traceless. :arg queue: A :class:`pyopencl.CommandQueue`. :arg hij: The array containing the momentum-space tensor field to be projected. Must have shape ``(6,)+k_shape``, where ``k_shape`` is the shape of...
Projects a tensor field to be transverse and traceless.
[ "Projects", "a", "tensor", "field", "to", "be", "transverse", "and", "traceless", "." ]
def transverse_traceless(self, queue, hij, hij_TT=None): if hij_TT is None: hij_TT = hij evt, _ = self.tt_knl(queue, hij=hij, hij_TT=hij_TT, **self.eff_mom) return evt
[ "def", "transverse_traceless", "(", "self", ",", "queue", ",", "hij", ",", "hij_TT", "=", "None", ")", ":", "if", "hij_TT", "is", "None", ":", "hij_TT", "=", "hij", "evt", ",", "_", "=", "self", ".", "tt_knl", "(", "queue", ",", "hij", "=", "hij", ...
Projects a tensor field to be transverse and traceless.
[ "Projects", "a", "tensor", "field", "to", "be", "transverse", "and", "traceless", "." ]
[ "\"\"\"\r\n Projects a tensor field to be transverse and traceless.\r\n\r\n :arg queue: A :class:`pyopencl.CommandQueue`.\r\n\r\n :arg hij: The array containing the\r\n momentum-space tensor field to be projected.\r\n Must have shape ``(6,)+k_shape``, where\r\n ...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "hij", "type": null }, { "param": "hij_TT", "type": null } ]
{ "returns": [ { "docstring": "The :class:`pyopencl.Event` associated with the kernel invocation.", "docstring_tokens": [ "The", ":", "class", ":", "`", "pyopencl", ".", "Event", "`", "associated", "with", ...
46c229ed222c98cb727ba27dccbfd3e831bb211c
zachjweiner/pystella
pystella/fourier/projectors.py
[ "MIT" ]
Python
tensor_to_pol
<not_specific>
def tensor_to_pol(self, queue, plus, minus, hij): """ Projects the components of a rank-2 tensor field onto the basis of plus and minus polarizations. :arg queue: A :class:`pyopencl.CommandQueue`. :arg plus: The array into which will be stored the momentum-s...
Projects the components of a rank-2 tensor field onto the basis of plus and minus polarizations. :arg queue: A :class:`pyopencl.CommandQueue`. :arg plus: The array into which will be stored the momentum-space field of the plus polarization. :arg minus: Th...
Projects the components of a rank-2 tensor field onto the basis of plus and minus polarizations.
[ "Projects", "the", "components", "of", "a", "rank", "-", "2", "tensor", "field", "onto", "the", "basis", "of", "plus", "and", "minus", "polarizations", "." ]
def tensor_to_pol(self, queue, plus, minus, hij): evt, _ = self.tensor_to_pol_knl(queue, **self.eff_mom, hij=hij, plus=plus, minus=minus) return evt
[ "def", "tensor_to_pol", "(", "self", ",", "queue", ",", "plus", ",", "minus", ",", "hij", ")", ":", "evt", ",", "_", "=", "self", ".", "tensor_to_pol_knl", "(", "queue", ",", "**", "self", ".", "eff_mom", ",", "hij", "=", "hij", ",", "plus", "=", ...
Projects the components of a rank-2 tensor field onto the basis of plus and minus polarizations.
[ "Projects", "the", "components", "of", "a", "rank", "-", "2", "tensor", "field", "onto", "the", "basis", "of", "plus", "and", "minus", "polarizations", "." ]
[ "\"\"\"\r\n Projects the components of a rank-2 tensor field onto the basis of plus and\r\n minus polarizations.\r\n\r\n :arg queue: A :class:`pyopencl.CommandQueue`.\r\n\r\n :arg plus: The array into which will be stored the\r\n momentum-space field of the plus polarization.\...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "plus", "type": null }, { "param": "minus", "type": null }, { "param": "hij", "type": null } ]
{ "returns": [ { "docstring": "The :class:`pyopencl.Event` associated with the kernel invocation.", "docstring_tokens": [ "The", ":", "class", ":", "`", "pyopencl", ".", "Event", "`", "associated", "with", ...
46c229ed222c98cb727ba27dccbfd3e831bb211c
zachjweiner/pystella
pystella/fourier/projectors.py
[ "MIT" ]
Python
pol_to_tensor
<not_specific>
def pol_to_tensor(self, queue, plus, minus, hij): """ Projects the plus and minus polarizations of a rank-2 tensor field onto its tensor components. :arg queue: A :class:`pyopencl.CommandQueue`. :arg plus: The array into which will be stored the momentum-spa...
Projects the plus and minus polarizations of a rank-2 tensor field onto its tensor components. :arg queue: A :class:`pyopencl.CommandQueue`. :arg plus: The array into which will be stored the momentum-space field of the plus polarization. :arg minus: The ...
Projects the plus and minus polarizations of a rank-2 tensor field onto its tensor components.
[ "Projects", "the", "plus", "and", "minus", "polarizations", "of", "a", "rank", "-", "2", "tensor", "field", "onto", "its", "tensor", "components", "." ]
def pol_to_tensor(self, queue, plus, minus, hij): evt, _ = self.pol_to_tensor_knl(queue, **self.eff_mom, hij=hij, plus=plus, minus=minus) return evt
[ "def", "pol_to_tensor", "(", "self", ",", "queue", ",", "plus", ",", "minus", ",", "hij", ")", ":", "evt", ",", "_", "=", "self", ".", "pol_to_tensor_knl", "(", "queue", ",", "**", "self", ".", "eff_mom", ",", "hij", "=", "hij", ",", "plus", "=", ...
Projects the plus and minus polarizations of a rank-2 tensor field onto its tensor components.
[ "Projects", "the", "plus", "and", "minus", "polarizations", "of", "a", "rank", "-", "2", "tensor", "field", "onto", "its", "tensor", "components", "." ]
[ "\"\"\"\r\n Projects the plus and minus polarizations of a rank-2 tensor field onto its\r\n tensor components.\r\n\r\n :arg queue: A :class:`pyopencl.CommandQueue`.\r\n\r\n :arg plus: The array into which will be stored the\r\n momentum-space field of the plus polarization.\r\...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "plus", "type": null }, { "param": "minus", "type": null }, { "param": "hij", "type": null } ]
{ "returns": [ { "docstring": "The :class:`pyopencl.Event` associated with the kernel invocation.", "docstring_tokens": [ "The", ":", "class", ":", "`", "pyopencl", ".", "Event", "`", "associated", "with", ...
f90352419cf011537879d1ad4c80bbb1ce4f9775
zachjweiner/pystella
pystella/fourier/derivs.py
[ "MIT" ]
Python
divergence
<not_specific>
def divergence(self, queue, vec, div, allocator=None): """ Computes the divergence of the input ``vec``. Provides the same interface as :meth:`pystella.FiniteDifferencer.divergence`, while additionally accepting the following arguments: :arg allocator: A :mod:`pyopencl` ...
Computes the divergence of the input ``vec``. Provides the same interface as :meth:`pystella.FiniteDifferencer.divergence`, while additionally accepting the following arguments: :arg allocator: A :mod:`pyopencl` allocator used to allocate temporary arrays, i.e., mos...
Computes the divergence of the input ``vec``. Provides the same interface as
[ "Computes", "the", "divergence", "of", "the", "input", "`", "`", "vec", "`", "`", ".", "Provides", "the", "same", "interface", "as" ]
def divergence(self, queue, vec, div, allocator=None): from itertools import product slices = list(product(*[range(n) for n in vec.shape[:-4]])) for s in slices: arguments = {"queue": queue, **self.momenta, "allocator": allocator} fk = self.fft.dft(vec[s][0]) ...
[ "def", "divergence", "(", "self", ",", "queue", ",", "vec", ",", "div", ",", "allocator", "=", "None", ")", ":", "from", "itertools", "import", "product", "slices", "=", "list", "(", "product", "(", "*", "[", "range", "(", "n", ")", "for", "n", "in...
Computes the divergence of the input ``vec``.
[ "Computes", "the", "divergence", "of", "the", "input", "`", "`", "vec", "`", "`", "." ]
[ "\"\"\"\n Computes the divergence of the input ``vec``.\n Provides the same interface as\n :meth:`pystella.FiniteDifferencer.divergence`, while additionally accepting\n the following arguments:\n\n :arg allocator: A :mod:`pyopencl` allocator used to allocate temporary\n ...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "vec", "type": null }, { "param": "div", "type": null }, { "param": "allocator", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "queue", "type": null, "docstring": null, "docstring_tokens": ...
bf05a43c06190b1af3885b87e79e7f0674752081
zachjweiner/pystella
pystella/derivs.py
[ "MIT" ]
Python
expand_stencil
<not_specific>
def expand_stencil(f, coefs): """ Expands a stencil over a field. :arg f: A :class:`~pystella.Field`. :arg coefs: A :class:`dict` whose values are the coefficients of the stencil at an offset given by the key. The keys must be 3-:class:`tuple`\\ s, and the values may be :mod:`p...
Expands a stencil over a field. :arg f: A :class:`~pystella.Field`. :arg coefs: A :class:`dict` whose values are the coefficients of the stencil at an offset given by the key. The keys must be 3-:class:`tuple`\\ s, and the values may be :mod:`pymbolic` expressions or constants. ...
Expands a stencil over a field.
[ "Expands", "a", "stencil", "over", "a", "field", "." ]
def expand_stencil(f, coefs): return sum([c * shift_fields(f, shift=offset) for offset, c in coefs.items()])
[ "def", "expand_stencil", "(", "f", ",", "coefs", ")", ":", "return", "sum", "(", "[", "c", "*", "shift_fields", "(", "f", ",", "shift", "=", "offset", ")", "for", "offset", ",", "c", "in", "coefs", ".", "items", "(", ")", "]", ")" ]
Expands a stencil over a field.
[ "Expands", "a", "stencil", "over", "a", "field", "." ]
[ "\"\"\"\r\n Expands a stencil over a field.\r\n\r\n :arg f: A :class:`~pystella.Field`.\r\n\r\n :arg coefs: A :class:`dict` whose values are the coefficients of the stencil\r\n at an offset given by the key. The keys must be 3-:class:`tuple`\\\\ s, and the\r\n values may be :mod:`pymbolic` ex...
[ { "param": "f", "type": null }, { "param": "coefs", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "f", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": null }, { "identifier": "coefs", "type": null, "docstring": "A :class:`di...
bf05a43c06190b1af3885b87e79e7f0674752081
zachjweiner/pystella
pystella/derivs.py
[ "MIT" ]
Python
centered_diff
<not_specific>
def centered_diff(f, coefs, direction, order): """ A convenience wrapper to :func:`expand_stencil` for computing centered differences. By assuming the symmetry of the stencil (which has parity given by the parity of ``order``), no redundant coefficients need to be supplied. Further, by supplyin...
A convenience wrapper to :func:`expand_stencil` for computing centered differences. By assuming the symmetry of the stencil (which has parity given by the parity of ``order``), no redundant coefficients need to be supplied. Further, by supplying the ``direction`` parameter, the input offset (the ke...
A convenience wrapper to :func:`expand_stencil` for computing centered differences. By assuming the symmetry of the stencil (which has parity given by the parity of ``order``), no redundant coefficients need to be supplied.
[ "A", "convenience", "wrapper", "to", ":", "func", ":", "`", "expand_stencil", "`", "for", "computing", "centered", "differences", ".", "By", "assuming", "the", "symmetry", "of", "the", "stencil", "(", "which", "has", "parity", "given", "by", "the", "parity",...
def centered_diff(f, coefs, direction, order): all_coefs = {} for s, c in coefs.items(): offset = [0, 0, 0] if s != 0 or order % 2 == 0: offset[direction-1] = s all_coefs[tuple(offset)] = c if s != 0: offset[direction-1] = - s all_coefs[tup...
[ "def", "centered_diff", "(", "f", ",", "coefs", ",", "direction", ",", "order", ")", ":", "all_coefs", "=", "{", "}", "for", "s", ",", "c", "in", "coefs", ".", "items", "(", ")", ":", "offset", "=", "[", "0", ",", "0", ",", "0", "]", "if", "s...
A convenience wrapper to :func:`expand_stencil` for computing centered differences.
[ "A", "convenience", "wrapper", "to", ":", "func", ":", "`", "expand_stencil", "`", "for", "computing", "centered", "differences", "." ]
[ "\"\"\"\r\n A convenience wrapper to :func:`expand_stencil` for computing centered\r\n differences. By assuming the symmetry of the stencil (which has parity given\r\n by the parity of ``order``), no redundant coefficients need to be supplied.\r\n Further, by supplying the ``direction`` parameter, the i...
[ { "param": "f", "type": null }, { "param": "coefs", "type": null }, { "param": "direction", "type": null }, { "param": "order", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "f", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": null }, { "identifier": "coefs", "type": null, "docstring": "A :class:`di...
d95da801becce664632c401beceed55e273f0d2f
zachjweiner/pystella
pystella/fourier/spectra.py
[ "MIT" ]
Python
polarization
<not_specific>
def polarization(self, vector, projector, queue=None, k_power=3, allocator=None): """ Computes the power spectra of the plus and minus polarizations of a vector field. :arg vector: The array containing the position-space vector field whose power spectrum is to be compu...
Computes the power spectra of the plus and minus polarizations of a vector field. :arg vector: The array containing the position-space vector field whose power spectrum is to be computed. If ``vector`` has more than four axes, all the outer axes are l...
Computes the power spectra of the plus and minus polarizations of a vector field.
[ "Computes", "the", "power", "spectra", "of", "the", "plus", "and", "minus", "polarizations", "of", "a", "vector", "field", "." ]
def polarization(self, vector, projector, queue=None, k_power=3, allocator=None): queue = queue or vector.queue vec_k = cla.empty(queue, (3,)+self.kshape, self.cdtype, allocator=None) plus = vec_k[0] minus = vec_k[1] outer_shape = vector.shape[:-4] from itertools import p...
[ "def", "polarization", "(", "self", ",", "vector", ",", "projector", ",", "queue", "=", "None", ",", "k_power", "=", "3", ",", "allocator", "=", "None", ")", ":", "queue", "=", "queue", "or", "vector", ".", "queue", "vec_k", "=", "cla", ".", "empty",...
Computes the power spectra of the plus and minus polarizations of a vector field.
[ "Computes", "the", "power", "spectra", "of", "the", "plus", "and", "minus", "polarizations", "of", "a", "vector", "field", "." ]
[ "\"\"\"\r\n Computes the power spectra of the plus and minus polarizations of a vector\r\n field.\r\n\r\n :arg vector: The array containing the position-space vector field\r\n whose power spectrum is to be computed.\r\n If ``vector`` has more than four axes, all the outer ...
[ { "param": "self", "type": null }, { "param": "vector", "type": null }, { "param": "projector", "type": null }, { "param": "queue", "type": null }, { "param": "k_power", "type": null }, { "param": "allocator", "type": null } ]
{ "returns": [ { "docstring": "A :class:`numpy.ndarray` containing the polarization spectra\nwith shape ``vector.shape[:-4]+(2, num_bins)``.", "docstring_tokens": [ "A", ":", "class", ":", "`", "numpy", ".", "ndarray", "`", ...
d95da801becce664632c401beceed55e273f0d2f
zachjweiner/pystella
pystella/fourier/spectra.py
[ "MIT" ]
Python
vector_decomposition
<not_specific>
def vector_decomposition(self, vector, projector, queue=None, k_power=3, allocator=None): """ Computes the power spectra of the plus and minus polarizations and longitudinal component of a vector field. :arg vector: The array containing the position-sp...
Computes the power spectra of the plus and minus polarizations and longitudinal component of a vector field. :arg vector: The array containing the position-space vector field whose power spectrum is to be computed. If ``vector`` has more than four axes, all the ou...
Computes the power spectra of the plus and minus polarizations and longitudinal component of a vector field.
[ "Computes", "the", "power", "spectra", "of", "the", "plus", "and", "minus", "polarizations", "and", "longitudinal", "component", "of", "a", "vector", "field", "." ]
def vector_decomposition(self, vector, projector, queue=None, k_power=3, allocator=None): queue = queue or vector.queue vec_k = cla.empty(queue, (3,)+self.kshape, self.cdtype, allocator=None) plus = vec_k[0] minus = vec_k[1] lng = vec_k[2] out...
[ "def", "vector_decomposition", "(", "self", ",", "vector", ",", "projector", ",", "queue", "=", "None", ",", "k_power", "=", "3", ",", "allocator", "=", "None", ")", ":", "queue", "=", "queue", "or", "vector", ".", "queue", "vec_k", "=", "cla", ".", ...
Computes the power spectra of the plus and minus polarizations and longitudinal component of a vector field.
[ "Computes", "the", "power", "spectra", "of", "the", "plus", "and", "minus", "polarizations", "and", "longitudinal", "component", "of", "a", "vector", "field", "." ]
[ "\"\"\"\r\n Computes the power spectra of the plus and minus polarizations and\r\n longitudinal component of a vector field.\r\n\r\n :arg vector: The array containing the position-space vector field\r\n whose power spectrum is to be computed.\r\n If ``vector`` has more tha...
[ { "param": "self", "type": null }, { "param": "vector", "type": null }, { "param": "projector", "type": null }, { "param": "queue", "type": null }, { "param": "k_power", "type": null }, { "param": "allocator", "type": null } ]
{ "returns": [ { "docstring": "A :class:`numpy.ndarray` containing the polarization and\nlongitudinal spectra with shape ``vector.shape[:-4]+(3, num_bins)``.", "docstring_tokens": [ "A", ":", "class", ":", "`", "numpy", ".", "ndarray", ...
d95da801becce664632c401beceed55e273f0d2f
zachjweiner/pystella
pystella/fourier/spectra.py
[ "MIT" ]
Python
gw_polarization
<not_specific>
def gw_polarization(self, hij, projector, hubble, queue=None, k_power=3, allocator=None): """ Computes the polarization components of the present gravitational wave power spectrum. .. math:: \\Delta_{h_\\lambda}^2(k) = \\frac{1}{...
Computes the polarization components of the present gravitational wave power spectrum. .. math:: \\Delta_{h_\\lambda}^2(k) = \\frac{1}{24 \\pi^{2} \\mathcal{H}^{2}} \\frac{1}{V} \\int \\mathrm{d} \\Omega \\, \\l...
Computes the polarization components of the present gravitational wave power spectrum.
[ "Computes", "the", "polarization", "components", "of", "the", "present", "gravitational", "wave", "power", "spectrum", "." ]
def gw_polarization(self, hij, projector, hubble, queue=None, k_power=3, allocator=None): queue = queue or hij.queue hij_k = cla.empty(queue, (6,)+self.kshape, self.cdtype, allocator=None) plus = hij_k[0] minus = hij_k[1] for mu in range(6): se...
[ "def", "gw_polarization", "(", "self", ",", "hij", ",", "projector", ",", "hubble", ",", "queue", "=", "None", ",", "k_power", "=", "3", ",", "allocator", "=", "None", ")", ":", "queue", "=", "queue", "or", "hij", ".", "queue", "hij_k", "=", "cla", ...
Computes the polarization components of the present gravitational wave power spectrum.
[ "Computes", "the", "polarization", "components", "of", "the", "present", "gravitational", "wave", "power", "spectrum", "." ]
[ "\"\"\"\r\n Computes the polarization components of the present gravitational wave\r\n power spectrum.\r\n\r\n .. math::\r\n\r\n \\\\Delta_{h_\\\\lambda}^2(k)\r\n = \\\\frac{1}{24 \\\\pi^{2} \\\\mathcal{H}^{2}}\r\n \\\\frac{1}{V}\r\n \\\\int \...
[ { "param": "self", "type": null }, { "param": "hij", "type": null }, { "param": "projector", "type": null }, { "param": "hubble", "type": null }, { "param": "queue", "type": null }, { "param": "k_power", "type": null }, { "param": "allocato...
{ "returns": [ { "docstring": "A :class:`numpy.ndarray` containing\n:math:`\\\\Delta_{h_\\\\lambda}^2(k)` with shape ``(2, num_bins)``.\n\n", "docstring_tokens": [ "A", ":", "class", ":", "`", "numpy", ".", "ndarray", "`", ...
a398594b6957b5517ca1ea7eb407828a425cdc3c
zachjweiner/pystella
pystella/field/__init__.py
[ "MIT" ]
Python
index_fields
<not_specific>
def index_fields(expr, prepend_with=None): """ Appends subscripts to :class:`Field` instances in an expression, turning them into ordinary :class:`pymbolic.primitives.Subscript`\\ s. See the documentation of :class:`Field` for examples. :arg expr: The expression(s) to be mapped. :arg prepe...
Appends subscripts to :class:`Field` instances in an expression, turning them into ordinary :class:`pymbolic.primitives.Subscript`\\ s. See the documentation of :class:`Field` for examples. :arg expr: The expression(s) to be mapped. :arg prepend_with: A :class:`tuple` of indices to prepend to...
Appends subscripts to :class:`Field` instances in an expression, turning them into ordinary
[ "Appends", "subscripts", "to", ":", "class", ":", "`", "Field", "`", "instances", "in", "an", "expression", "turning", "them", "into", "ordinary" ]
def index_fields(expr, prepend_with=None): return IndexMapper()(expr, prepend_with=prepend_with)
[ "def", "index_fields", "(", "expr", ",", "prepend_with", "=", "None", ")", ":", "return", "IndexMapper", "(", ")", "(", "expr", ",", "prepend_with", "=", "prepend_with", ")" ]
Appends subscripts to :class:`Field` instances in an expression, turning them into ordinary
[ "Appends", "subscripts", "to", ":", "class", ":", "`", "Field", "`", "instances", "in", "an", "expression", "turning", "them", "into", "ordinary" ]
[ "\"\"\"\n Appends subscripts to :class:`Field`\n instances in an expression, turning them into ordinary\n :class:`pymbolic.primitives.Subscript`\\\\ s.\n See the documentation of :class:`Field` for examples.\n\n :arg expr: The expression(s) to be mapped.\n\n :arg prepend_with: A :class:`tuple` of ...
[ { "param": "expr", "type": null }, { "param": "prepend_with", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "expr", "type": null, "docstring": "The expression(s) to be mapped.", "docstring_tokens": [ "The", "expression", "(", "s", ")", "to", "be", "mapped", "." ...
54bb285bfb72dced4f3b3bafdcaa7c403a102569
zachjweiner/pystella
pystella/multigrid/__init__.py
[ "MIT" ]
Python
transfer_down
null
def transfer_down(self, queue, i): """ Transfers all arrays from a fine to the next-coarser level. :arg queue: A :class:`pyopencl.CommandQueue`. :arg i: The level from to transfer to. """ for key, f1 in self.unknowns[i-1].items(): f2 = self.unknow...
Transfers all arrays from a fine to the next-coarser level. :arg queue: A :class:`pyopencl.CommandQueue`. :arg i: The level from to transfer to.
Transfers all arrays from a fine to the next-coarser level.
[ "Transfers", "all", "arrays", "from", "a", "fine", "to", "the", "next", "-", "coarser", "level", "." ]
def transfer_down(self, queue, i): for key, f1 in self.unknowns[i-1].items(): f2 = self.unknowns[i][key] self.restrict(queue, f1=f1, f2=f2) self.decomp[i].share_halos(queue, f2) self.solver.residual(queue, **self.resid_args[i-1]) for key, r1 in self.resid[i-1]...
[ "def", "transfer_down", "(", "self", ",", "queue", ",", "i", ")", ":", "for", "key", ",", "f1", "in", "self", ".", "unknowns", "[", "i", "-", "1", "]", ".", "items", "(", ")", ":", "f2", "=", "self", ".", "unknowns", "[", "i", "]", "[", "key"...
Transfers all arrays from a fine to the next-coarser level.
[ "Transfers", "all", "arrays", "from", "a", "fine", "to", "the", "next", "-", "coarser", "level", "." ]
[ "\"\"\"\r\n Transfers all arrays from a fine to the next-coarser level.\r\n\r\n :arg queue: A :class:`pyopencl.CommandQueue`.\r\n\r\n :arg i: The level from to transfer to.\r\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "i", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "queue", "type": null, "docstring": null, "docstring_tokens": ...
54bb285bfb72dced4f3b3bafdcaa7c403a102569
zachjweiner/pystella
pystella/multigrid/__init__.py
[ "MIT" ]
Python
transfer_up
null
def transfer_up(self, queue, i): """ Transfers all arrays from a coarse to the next-finer level. :arg queue: A :class:`pyopencl.CommandQueue`. :arg i: The level from to transfer to. """ for k, f1 in self.unknowns[i].items(): f2 = self.unknowns[i+1...
Transfers all arrays from a coarse to the next-finer level. :arg queue: A :class:`pyopencl.CommandQueue`. :arg i: The level from to transfer to.
Transfers all arrays from a coarse to the next-finer level.
[ "Transfers", "all", "arrays", "from", "a", "coarse", "to", "the", "next", "-", "finer", "level", "." ]
def transfer_up(self, queue, i): for k, f1 in self.unknowns[i].items(): f2 = self.unknowns[i+1][k] self.restrict_and_correct(queue, f1=f1, f2=f2) self.decomp[i+1].share_halos(queue, f2) self.interpolate_and_correct(queue, f1=f1, f2=f2) self.decomp[i].s...
[ "def", "transfer_up", "(", "self", ",", "queue", ",", "i", ")", ":", "for", "k", ",", "f1", "in", "self", ".", "unknowns", "[", "i", "]", ".", "items", "(", ")", ":", "f2", "=", "self", ".", "unknowns", "[", "i", "+", "1", "]", "[", "k", "]...
Transfers all arrays from a coarse to the next-finer level.
[ "Transfers", "all", "arrays", "from", "a", "coarse", "to", "the", "next", "-", "finer", "level", "." ]
[ "\"\"\"\r\n Transfers all arrays from a coarse to the next-finer level.\r\n\r\n :arg queue: A :class:`pyopencl.CommandQueue`.\r\n\r\n :arg i: The level from to transfer to.\r\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "i", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "queue", "type": null, "docstring": null, "docstring_tokens": ...
54bb285bfb72dced4f3b3bafdcaa7c403a102569
zachjweiner/pystella
pystella/multigrid/__init__.py
[ "MIT" ]
Python
smooth
<not_specific>
def smooth(self, queue, i, nu): """ Invokes the relaxation solver, computing the error before and after. :arg queue: A :class:`pyopencl.CommandQueue`. :arg i: On which level to perform the smoothing. :arg nu: The number of smoothing iterations to perform. :r...
Invokes the relaxation solver, computing the error before and after. :arg queue: A :class:`pyopencl.CommandQueue`. :arg i: On which level to perform the smoothing. :arg nu: The number of smoothing iterations to perform. :returns: A list containing the errors before ...
Invokes the relaxation solver, computing the error before and after.
[ "Invokes", "the", "relaxation", "solver", "computing", "the", "error", "before", "and", "after", "." ]
def smooth(self, queue, i, nu): errs1 = self.solver.get_error(queue, **self.resid_args[i]) self.solver(self.decomp[i], queue, iterations=nu, **self.smooth_args[i]) errs2 = self.solver.get_error(queue, **self.resid_args[i]) return [(i, errs1), (i, errs2)]
[ "def", "smooth", "(", "self", ",", "queue", ",", "i", ",", "nu", ")", ":", "errs1", "=", "self", ".", "solver", ".", "get_error", "(", "queue", ",", "**", "self", ".", "resid_args", "[", "i", "]", ")", "self", ".", "solver", "(", "self", ".", "...
Invokes the relaxation solver, computing the error before and after.
[ "Invokes", "the", "relaxation", "solver", "computing", "the", "error", "before", "and", "after", "." ]
[ "\"\"\"\r\n Invokes the relaxation solver, computing the error before and after.\r\n\r\n :arg queue: A :class:`pyopencl.CommandQueue`.\r\n\r\n :arg i: On which level to perform the smoothing.\r\n\r\n :arg nu: The number of smoothing iterations to perform.\r\n\r\n :returns: A list ...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "i", "type": null }, { "param": "nu", "type": null } ]
{ "returns": [ { "docstring": "A list containing the errors before and after of the form\n``[(i, error_before), (i, error_after)]``.", "docstring_tokens": [ "A", "list", "containing", "the", "errors", "before", "and", "after", "of...
b01eae5ffdab7b64545153c571c4146485c4a9d0
zachjweiner/pystella
pystella/fourier/rayleigh.py
[ "MIT" ]
Python
generate
<not_specific>
def generate(self, queue, random=True, field_ps=lambda kmag: 1/2/kmag, norm=1, window=lambda kmag: 1.): """ Generate a 3-D array of Fourier modes with a given power spectrum and random phases. :arg queue: A :class:`pyopencl.CommandQueue`. :arg random: W...
Generate a 3-D array of Fourier modes with a given power spectrum and random phases. :arg queue: A :class:`pyopencl.CommandQueue`. :arg random: Whether to randomly sample the Rayleigh distribution of mode amplitudes. Defaults to *True*. :arg ...
Generate a 3-D array of Fourier modes with a given power spectrum and random phases.
[ "Generate", "a", "3", "-", "D", "array", "of", "Fourier", "modes", "with", "a", "given", "power", "spectrum", "and", "random", "phases", "." ]
def generate(self, queue, random=True, field_ps=lambda kmag: 1/2/kmag, norm=1, window=lambda kmag: 1.): amplitude_sq = norm / self.volume rands = self.rng.uniform(queue, (2,)+self.kmags.shape, self.rdtype) if not random: rands[0] = np.exp(-1) f_power = (ampli...
[ "def", "generate", "(", "self", ",", "queue", ",", "random", "=", "True", ",", "field_ps", "=", "lambda", "kmag", ":", "1", "/", "2", "/", "kmag", ",", "norm", "=", "1", ",", "window", "=", "lambda", "kmag", ":", "1.", ")", ":", "amplitude_sq", "...
Generate a 3-D array of Fourier modes with a given power spectrum and random phases.
[ "Generate", "a", "3", "-", "D", "array", "of", "Fourier", "modes", "with", "a", "given", "power", "spectrum", "and", "random", "phases", "." ]
[ "\"\"\"\r\n Generate a 3-D array of Fourier modes with a given power spectrum and\r\n random phases.\r\n\r\n :arg queue: A :class:`pyopencl.CommandQueue`.\r\n\r\n :arg random: Whether to randomly sample the Rayleigh distribution\r\n of mode amplitudes.\r\n Defaults ...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "random", "type": null }, { "param": "field_ps", "type": null }, { "param": "norm", "type": null }, { "param": "window", "type": null } ]
{ "returns": [ { "docstring": "An :class:`numpy.ndarray` containing the generated Fourier modes\nof the field.", "docstring_tokens": [ "An", ":", "class", ":", "`", "numpy", ".", "ndarray", "`", "containing", "the"...
b01eae5ffdab7b64545153c571c4146485c4a9d0
zachjweiner/pystella
pystella/fourier/rayleigh.py
[ "MIT" ]
Python
init_field
null
def init_field(self, fx, queue=None, **kwargs): """ A wrapper which calls :meth:`generate` to initialize a field in Fourier space and returns its inverse Fourier transform. :arg fx: The array in which the field will be stored. The following keyword arguments are recogniz...
A wrapper which calls :meth:`generate` to initialize a field in Fourier space and returns its inverse Fourier transform. :arg fx: The array in which the field will be stored. The following keyword arguments are recognized: :arg queue: A :class:`pyopencl.CommandQueue`....
A wrapper which calls :meth:`generate` to initialize a field in Fourier space and returns its inverse Fourier transform.
[ "A", "wrapper", "which", "calls", ":", "meth", ":", "`", "generate", "`", "to", "initialize", "a", "field", "in", "Fourier", "space", "and", "returns", "its", "inverse", "Fourier", "transform", "." ]
def init_field(self, fx, queue=None, **kwargs): queue = queue or fx.queue fk = self.generate(queue, **kwargs) self.fft.idft(fk, fx)
[ "def", "init_field", "(", "self", ",", "fx", ",", "queue", "=", "None", ",", "**", "kwargs", ")", ":", "queue", "=", "queue", "or", "fx", ".", "queue", "fk", "=", "self", ".", "generate", "(", "queue", ",", "**", "kwargs", ")", "self", ".", "fft"...
A wrapper which calls :meth:`generate` to initialize a field in Fourier space and returns its inverse Fourier transform.
[ "A", "wrapper", "which", "calls", ":", "meth", ":", "`", "generate", "`", "to", "initialize", "a", "field", "in", "Fourier", "space", "and", "returns", "its", "inverse", "Fourier", "transform", "." ]
[ "\"\"\"\r\n A wrapper which calls :meth:`generate` to initialize a field\r\n in Fourier space and returns its inverse Fourier transform.\r\n\r\n :arg fx: The array in which the field will be stored.\r\n\r\n The following keyword arguments are recognized:\r\n\r\n :arg queue: A :cla...
[ { "param": "self", "type": null }, { "param": "fx", "type": null }, { "param": "queue", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "fx", "type": null, "docstring": "The array in which the field will ...
b01eae5ffdab7b64545153c571c4146485c4a9d0
zachjweiner/pystella
pystella/fourier/rayleigh.py
[ "MIT" ]
Python
init_transverse_vector
null
def init_transverse_vector(self, projector, vector, queue=None, **kwargs): """ A wrapper which calls :meth:`generate` to initialize a transverse three-vector field in Fourier space and returns its inverse Fourier transform. Each component will have the same power spectrum. ...
A wrapper which calls :meth:`generate` to initialize a transverse three-vector field in Fourier space and returns its inverse Fourier transform. Each component will have the same power spectrum. :arg projector: A :class:`Projector` used to project out longitu...
A wrapper which calls :meth:`generate` to initialize a transverse three-vector field in Fourier space and returns its inverse Fourier transform. Each component will have the same power spectrum.
[ "A", "wrapper", "which", "calls", ":", "meth", ":", "`", "generate", "`", "to", "initialize", "a", "transverse", "three", "-", "vector", "field", "in", "Fourier", "space", "and", "returns", "its", "inverse", "Fourier", "transform", ".", "Each", "component", ...
def init_transverse_vector(self, projector, vector, queue=None, **kwargs): queue = queue or vector.queue vector_k = cla.empty(queue, (3,)+self.fft.shape(True), self.cdtype) for mu in range(3): fk = self.generate(queue, **kwargs) vector_k[mu].set(fk) projector.tran...
[ "def", "init_transverse_vector", "(", "self", ",", "projector", ",", "vector", ",", "queue", "=", "None", ",", "**", "kwargs", ")", ":", "queue", "=", "queue", "or", "vector", ".", "queue", "vector_k", "=", "cla", ".", "empty", "(", "queue", ",", "(", ...
A wrapper which calls :meth:`generate` to initialize a transverse three-vector field in Fourier space and returns its inverse Fourier transform.
[ "A", "wrapper", "which", "calls", ":", "meth", ":", "`", "generate", "`", "to", "initialize", "a", "transverse", "three", "-", "vector", "field", "in", "Fourier", "space", "and", "returns", "its", "inverse", "Fourier", "transform", "." ]
[ "\"\"\"\r\n A wrapper which calls :meth:`generate` to initialize a transverse\r\n three-vector field in Fourier space and returns its inverse Fourier\r\n transform.\r\n Each component will have the same power spectrum.\r\n\r\n :arg projector: A :class:`Projector` used to project o...
[ { "param": "self", "type": null }, { "param": "projector", "type": null }, { "param": "vector", "type": null }, { "param": "queue", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "projector", "type": null, "docstring": "A :class:`Projector` used t...
b01eae5ffdab7b64545153c571c4146485c4a9d0
zachjweiner/pystella
pystella/fourier/rayleigh.py
[ "MIT" ]
Python
init_vector_from_pol
null
def init_vector_from_pol(self, projector, vector, plus_ps, minus_ps, queue=None, **kwargs): """ A wrapper which calls :meth:`generate` to initialize a transverse three-vector field in Fourier space and returns its inverse Fourier transform. In c...
A wrapper which calls :meth:`generate` to initialize a transverse three-vector field in Fourier space and returns its inverse Fourier transform. In contrast to :meth:`init_transverse_vector`, modes are generated for the plus and minus polarizations of the vector field, from...
A wrapper which calls :meth:`generate` to initialize a transverse three-vector field in Fourier space and returns its inverse Fourier transform. In contrast to :meth:`init_transverse_vector`, modes are generated for the plus and minus polarizations of the vector field, from which the vector field itself is constructed.
[ "A", "wrapper", "which", "calls", ":", "meth", ":", "`", "generate", "`", "to", "initialize", "a", "transverse", "three", "-", "vector", "field", "in", "Fourier", "space", "and", "returns", "its", "inverse", "Fourier", "transform", ".", "In", "contrast", "...
def init_vector_from_pol(self, projector, vector, plus_ps, minus_ps, queue=None, **kwargs): queue = queue or vector.queue fk = self.generate(queue, field_ps=plus_ps, **kwargs) plus_k = cla.to_device(queue, fk) fk = self.generate(queue, field_ps=minus_ps, **kw...
[ "def", "init_vector_from_pol", "(", "self", ",", "projector", ",", "vector", ",", "plus_ps", ",", "minus_ps", ",", "queue", "=", "None", ",", "**", "kwargs", ")", ":", "queue", "=", "queue", "or", "vector", ".", "queue", "fk", "=", "self", ".", "genera...
A wrapper which calls :meth:`generate` to initialize a transverse three-vector field in Fourier space and returns its inverse Fourier transform.
[ "A", "wrapper", "which", "calls", ":", "meth", ":", "`", "generate", "`", "to", "initialize", "a", "transverse", "three", "-", "vector", "field", "in", "Fourier", "space", "and", "returns", "its", "inverse", "Fourier", "transform", "." ]
[ "\"\"\"\r\n A wrapper which calls :meth:`generate` to initialize a transverse\r\n three-vector field in Fourier space and returns its inverse Fourier\r\n transform.\r\n In contrast to :meth:`init_transverse_vector`, modes are generated\r\n for the plus and minus polarizations of t...
[ { "param": "self", "type": null }, { "param": "projector", "type": null }, { "param": "vector", "type": null }, { "param": "plus_ps", "type": null }, { "param": "minus_ps", "type": null }, { "param": "queue", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "projector", "type": null, "docstring": "A :class:`Projector` used t...
b01eae5ffdab7b64545153c571c4146485c4a9d0
zachjweiner/pystella
pystella/fourier/rayleigh.py
[ "MIT" ]
Python
generate_WKB
<not_specific>
def generate_WKB(self, queue, random=True, field_ps=lambda wk: 1/2/wk, norm=1, omega_k=lambda kmag: kmag, hubble=0., window=lambda kmag: 1.): """ Generate a 3-D array of Fourier modes with a given power spectrum and random phas...
Generate a 3-D array of Fourier modes with a given power spectrum and random phases, along with that of its time derivative according to the WKB approximation (for Klein-Gordon fields in conformal FLRW spacetime). Arguments match those of :meth:`generate`, with the follow...
Generate a 3-D array of Fourier modes with a given power spectrum and random phases, along with that of its time derivative according to the WKB approximation (for Klein-Gordon fields in conformal FLRW spacetime). Arguments match those of :meth:`generate`, with the following exceptions/additions.
[ "Generate", "a", "3", "-", "D", "array", "of", "Fourier", "modes", "with", "a", "given", "power", "spectrum", "and", "random", "phases", "along", "with", "that", "of", "its", "time", "derivative", "according", "to", "the", "WKB", "approximation", "(", "for...
def generate_WKB(self, queue, random=True, field_ps=lambda wk: 1/2/wk, norm=1, omega_k=lambda kmag: kmag, hubble=0., window=lambda kmag: 1.): amplitude_sq = norm / self.volume kshape = self.kmags.shape rands = self.rng.uniform(queue,...
[ "def", "generate_WKB", "(", "self", ",", "queue", ",", "random", "=", "True", ",", "field_ps", "=", "lambda", "wk", ":", "1", "/", "2", "/", "wk", ",", "norm", "=", "1", ",", "omega_k", "=", "lambda", "kmag", ":", "kmag", ",", "hubble", "=", "0."...
Generate a 3-D array of Fourier modes with a given power spectrum and random phases, along with that of its time derivative according to the WKB approximation (for Klein-Gordon fields in conformal FLRW spacetime).
[ "Generate", "a", "3", "-", "D", "array", "of", "Fourier", "modes", "with", "a", "given", "power", "spectrum", "and", "random", "phases", "along", "with", "that", "of", "its", "time", "derivative", "according", "to", "the", "WKB", "approximation", "(", "for...
[ "\"\"\"\r\n Generate a 3-D array of Fourier modes with a given power spectrum and\r\n random phases, along with that of its time derivative\r\n according to the WKB approximation (for Klein-Gordon fields in\r\n conformal FLRW spacetime).\r\n\r\n Arguments match those of :meth:`gen...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "random", "type": null }, { "param": "field_ps", "type": null }, { "param": "norm", "type": null }, { "param": "omega_k", "type": null }, { "param": "hubble",...
{ "returns": [ { "docstring": "A tuple ``(fk, dfk)`` containing the generated Fourier modes\nof the field and its time derivative.", "docstring_tokens": [ "A", "tuple", "`", "`", "(", "fk", "dfk", ")", "`", "`", "c...
b01eae5ffdab7b64545153c571c4146485c4a9d0
zachjweiner/pystella
pystella/fourier/rayleigh.py
[ "MIT" ]
Python
init_WKB_fields
null
def init_WKB_fields(self, fx, dfx, queue=None, **kwargs): """ A wrapper which calls :meth:`generate_WKB` to initialize a field and its time derivative in Fourier space and inverse Fourier transform the results. :arg fx: The array in which the field will be stored. ...
A wrapper which calls :meth:`generate_WKB` to initialize a field and its time derivative in Fourier space and inverse Fourier transform the results. :arg fx: The array in which the field will be stored. :arg dfx: The array in which the field's time derivative will ...
A wrapper which calls :meth:`generate_WKB` to initialize a field and its time derivative in Fourier space and inverse Fourier transform the results.
[ "A", "wrapper", "which", "calls", ":", "meth", ":", "`", "generate_WKB", "`", "to", "initialize", "a", "field", "and", "its", "time", "derivative", "in", "Fourier", "space", "and", "inverse", "Fourier", "transform", "the", "results", "." ]
def init_WKB_fields(self, fx, dfx, queue=None, **kwargs): queue = queue or fx.queue fk, dfk = self.generate_WKB(queue, **kwargs) self.fft.idft(fk, fx) self.fft.idft(dfk, dfx)
[ "def", "init_WKB_fields", "(", "self", ",", "fx", ",", "dfx", ",", "queue", "=", "None", ",", "**", "kwargs", ")", ":", "queue", "=", "queue", "or", "fx", ".", "queue", "fk", ",", "dfk", "=", "self", ".", "generate_WKB", "(", "queue", ",", "**", ...
A wrapper which calls :meth:`generate_WKB` to initialize a field and its time derivative in Fourier space and inverse Fourier transform the results.
[ "A", "wrapper", "which", "calls", ":", "meth", ":", "`", "generate_WKB", "`", "to", "initialize", "a", "field", "and", "its", "time", "derivative", "in", "Fourier", "space", "and", "inverse", "Fourier", "transform", "the", "results", "." ]
[ "\"\"\"\r\n A wrapper which calls :meth:`generate_WKB` to initialize a field and\r\n its time derivative in Fourier space and inverse Fourier transform\r\n the results.\r\n\r\n :arg fx: The array in which the field will be stored.\r\n\r\n :arg dfx: The array in which the field's t...
[ { "param": "self", "type": null }, { "param": "fx", "type": null }, { "param": "dfx", "type": null }, { "param": "queue", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "fx", "type": null, "docstring": "The array in which the field will ...
e99fb4d2e2e57292dfbfe876a35ce3f271f66b20
zachjweiner/pystella
pystella/fourier/dft.py
[ "MIT" ]
Python
dft
<not_specific>
def dft(self, fx=None, fk=None, **kwargs): """ Computes the forward Fourier transform. :arg fx: The array to be transformed. Can be a :class:`pyopencl.array.Array` with or without halo padding (which will be removed by :meth:`pystella.DomainDecompositi...
Computes the forward Fourier transform. :arg fx: The array to be transformed. Can be a :class:`pyopencl.array.Array` with or without halo padding (which will be removed by :meth:`pystella.DomainDecomposition.remove_halos` if needed) or a :class:`n...
Computes the forward Fourier transform.
[ "Computes", "the", "forward", "Fourier", "transform", "." ]
def dft(self, fx=None, fk=None, **kwargs): if fx is not None: if fx.shape != self.shape(False): if isinstance(fx, cla.Array): queue = fx.queue elif isinstance(self.fx, cla.Array): queue = self.fx.queue else: ...
[ "def", "dft", "(", "self", ",", "fx", "=", "None", ",", "fk", "=", "None", ",", "**", "kwargs", ")", ":", "if", "fx", "is", "not", "None", ":", "if", "fx", ".", "shape", "!=", "self", ".", "shape", "(", "False", ")", ":", "if", "isinstance", ...
Computes the forward Fourier transform.
[ "Computes", "the", "forward", "Fourier", "transform", "." ]
[ "\"\"\"\r\n Computes the forward Fourier transform.\r\n\r\n :arg fx: The array to be transformed.\r\n Can be a :class:`pyopencl.array.Array` with or without halo padding\r\n (which will be removed by\r\n :meth:`pystella.DomainDecomposition.remove_halos`\r\n ...
[ { "param": "self", "type": null }, { "param": "fx", "type": null }, { "param": "fk", "type": null } ]
{ "returns": [ { "docstring": "The forward Fourier transform of ``fx``.\nEither ``fk`` if supplied or :attr:`fk`.\n\nAny remaining keyword arguments are passed to :meth:`forward_transform`.\n\n:\nIf you need the result of multiple Fourier transforms at once, you must\neither supply an ``fk`` array or copy t...
e99fb4d2e2e57292dfbfe876a35ce3f271f66b20
zachjweiner/pystella
pystella/fourier/dft.py
[ "MIT" ]
Python
idft
<not_specific>
def idft(self, fk=None, fx=None, **kwargs): """ Computes the backward Fourier transform. :arg fk: The array to be transformed. Can be a :class:`pyopencl.array.Array` or a :class:`numpy.ndarray`. Arrays are copied as necessary. Defaults to *None*, in wh...
Computes the backward Fourier transform. :arg fk: The array to be transformed. Can be a :class:`pyopencl.array.Array` or a :class:`numpy.ndarray`. Arrays are copied as necessary. Defaults to *None*, in which case :attr:`fk` (attached to the transf...
Computes the backward Fourier transform.
[ "Computes", "the", "backward", "Fourier", "transform", "." ]
def idft(self, fk=None, fx=None, **kwargs): if fk is not None: if not isinstance(fk, type(self.fk)): _fk = _transfer_array(self.fk, fk) else: _fk = fk else: _fk = self.fk if fx is not None: if fx.shape == self.shape(...
[ "def", "idft", "(", "self", ",", "fk", "=", "None", ",", "fx", "=", "None", ",", "**", "kwargs", ")", ":", "if", "fk", "is", "not", "None", ":", "if", "not", "isinstance", "(", "fk", ",", "type", "(", "self", ".", "fk", ")", ")", ":", "_fk", ...
Computes the backward Fourier transform.
[ "Computes", "the", "backward", "Fourier", "transform", "." ]
[ "\"\"\"\r\n Computes the backward Fourier transform.\r\n\r\n :arg fk: The array to be transformed.\r\n Can be a :class:`pyopencl.array.Array` or a :class:`numpy.ndarray`.\r\n Arrays are copied as necessary.\r\n Defaults to *None*, in which case :attr:`fk` (attached\r\n...
[ { "param": "self", "type": null }, { "param": "fk", "type": null }, { "param": "fx", "type": null } ]
{ "returns": [ { "docstring": "The forward Fourier transform of ``fx``.\nEither ``fk`` if supplied or :attr:`fk`.\n\nAny remaining keyword arguments are passed to :meth:`backward_transform`.\n\n:\nIf you need the result of multiple Fourier transforms at once, you must\neither supply an ``fx`` array or copy ...
e99fb4d2e2e57292dfbfe876a35ce3f271f66b20
zachjweiner/pystella
pystella/fourier/dft.py
[ "MIT" ]
Python
zero_corner_modes
<not_specific>
def zero_corner_modes(self, array, only_imag=False): """ Zeros the "corner" modes (modes where each component of its integral wavenumber is either zero or the Nyquist along that axis) of ``array`` (or just the imaginary part). :arg array: The array to operate on. ...
Zeros the "corner" modes (modes where each component of its integral wavenumber is either zero or the Nyquist along that axis) of ``array`` (or just the imaginary part). :arg array: The array to operate on. May be a :class:`pyopencl.array.Array` or a :class:`numpy.nda...
Zeros the "corner" modes (modes where each component of its integral wavenumber is either zero or the Nyquist along that axis) of ``array`` (or just the imaginary part).
[ "Zeros", "the", "\"", "corner", "\"", "modes", "(", "modes", "where", "each", "component", "of", "its", "integral", "wavenumber", "is", "either", "zero", "or", "the", "Nyquist", "along", "that", "axis", ")", "of", "`", "`", "array", "`", "`", "(", "or"...
def zero_corner_modes(self, array, only_imag=False): sub_k = list(x.get().astype("int") for x in self.sub_k.values()) shape = self.grid_shape where_to_zero = [] for mu in range(3): kk = sub_k[mu] where_0 = np.argwhere(abs(kk) == 0).reshape(-1) where_N2...
[ "def", "zero_corner_modes", "(", "self", ",", "array", ",", "only_imag", "=", "False", ")", ":", "sub_k", "=", "list", "(", "x", ".", "get", "(", ")", ".", "astype", "(", "\"int\"", ")", "for", "x", "in", "self", ".", "sub_k", ".", "values", "(", ...
Zeros the "corner" modes (modes where each component of its integral wavenumber is either zero or the Nyquist along that axis) of ``array`` (or just the imaginary part).
[ "Zeros", "the", "\"", "corner", "\"", "modes", "(", "modes", "where", "each", "component", "of", "its", "integral", "wavenumber", "is", "either", "zero", "or", "the", "Nyquist", "along", "that", "axis", ")", "of", "`", "`", "array", "`", "`", "(", "or"...
[ "\"\"\"\r\n Zeros the \"corner\" modes (modes where each component of its\r\n integral wavenumber is either zero or the Nyquist along\r\n that axis) of ``array`` (or just the imaginary part).\r\n\r\n :arg array: The array to operate on.\r\n May be a :class:`pyopencl.array.Arra...
[ { "param": "self", "type": null }, { "param": "array", "type": null }, { "param": "only_imag", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "array", "type": null, "docstring": "The array to operate on.\nMay b...
398df17b04743449d579daa3c06fcfa7ee97555b
zachjweiner/pystella
pystella/decomp.py
[ "MIT" ]
Python
share_halos
null
def share_halos(self, queue, fx): """ Communicates halo data across all axes, imposing periodic boundary conditions. :arg queue: The :class:`pyopencl.CommandQueue` to enqueue kernels and copies. :arg fx: The :class:`pyopencl.array.Array` whose halo elements are to be ...
Communicates halo data across all axes, imposing periodic boundary conditions. :arg queue: The :class:`pyopencl.CommandQueue` to enqueue kernels and copies. :arg fx: The :class:`pyopencl.array.Array` whose halo elements are to be synchronized across ranks. ...
Communicates halo data across all axes, imposing periodic boundary conditions.
[ "Communicates", "halo", "data", "across", "all", "axes", "imposing", "periodic", "boundary", "conditions", "." ]
def share_halos(self, queue, fx): h = self.halo_shape rank_shape = tuple(ni - 2 * hi for ni, hi in zip(fx.shape, h)) if h[2] > 0: if self.proc_shape[2] == 1: evt, _ = self.pack_unpack_z_knl(queue, arr=fx) else: raise NotImplementedError("do...
[ "def", "share_halos", "(", "self", ",", "queue", ",", "fx", ")", ":", "h", "=", "self", ".", "halo_shape", "rank_shape", "=", "tuple", "(", "ni", "-", "2", "*", "hi", "for", "ni", ",", "hi", "in", "zip", "(", "fx", ".", "shape", ",", "h", ")", ...
Communicates halo data across all axes, imposing periodic boundary conditions.
[ "Communicates", "halo", "data", "across", "all", "axes", "imposing", "periodic", "boundary", "conditions", "." ]
[ "\"\"\"\r\n Communicates halo data across all axes, imposing periodic boundary\r\n conditions.\r\n\r\n :arg queue: The :class:`pyopencl.CommandQueue` to enqueue kernels and copies.\r\n\r\n :arg fx: The :class:`pyopencl.array.Array` whose halo elements are to be\r\n synchronize...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "fx", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "queue", "type": null, "docstring": "The :class:`pyopencl.CommandQue...
398df17b04743449d579daa3c06fcfa7ee97555b
zachjweiner/pystella
pystella/decomp.py
[ "MIT" ]
Python
remove_halos
null
def remove_halos(self, queue, in_array, out_array): """ Removes the halo padding from an array. The only restriction on the shapes of the three-dimensional input arrays is that the shape of ``in_array`` is larger than that of ``out_array`` by ``2*halo_shape`` along each ax...
Removes the halo padding from an array. The only restriction on the shapes of the three-dimensional input arrays is that the shape of ``in_array`` is larger than that of ``out_array`` by ``2*halo_shape`` along each axis. :arg queue: The :class:`pyopencl.CommandQueue` to...
Removes the halo padding from an array.
[ "Removes", "the", "halo", "padding", "from", "an", "array", "." ]
def remove_halos(self, queue, in_array, out_array): dtype = out_array.dtype if in_array.dtype != dtype: raise ValueError("in_array and out_array have different dtypes") cl_in = isinstance(in_array, cla.Array) cl_out = isinstance(out_array, cla.Array) np_in = isinstanc...
[ "def", "remove_halos", "(", "self", ",", "queue", ",", "in_array", ",", "out_array", ")", ":", "dtype", "=", "out_array", ".", "dtype", "if", "in_array", ".", "dtype", "!=", "dtype", ":", "raise", "ValueError", "(", "\"in_array and out_array have different dtype...
Removes the halo padding from an array.
[ "Removes", "the", "halo", "padding", "from", "an", "array", "." ]
[ "\"\"\"\r\n Removes the halo padding from an array.\r\n\r\n The only restriction on the shapes of the three-dimensional input arrays\r\n is that the shape of ``in_array`` is larger than that of ``out_array``\r\n by ``2*halo_shape`` along each axis.\r\n\r\n :arg queue: The :class:`...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "in_array", "type": null }, { "param": "out_array", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "queue", "type": null, "docstring": "The :class:`pyopencl.CommandQue...
398df17b04743449d579daa3c06fcfa7ee97555b
zachjweiner/pystella
pystella/decomp.py
[ "MIT" ]
Python
gather_array
null
def gather_array(self, queue, in_array, out_array, root): """ Gathers the subdomains of an array from each rank into a single array of the entire grid, removing halo padding from ``in_array``. :arg queue: The :class:`pyopencl.CommandQueue` to enqueue kernels and copies. ...
Gathers the subdomains of an array from each rank into a single array of the entire grid, removing halo padding from ``in_array``. :arg queue: The :class:`pyopencl.CommandQueue` to enqueue kernels and copies. :arg in_array: The subarrays to be gathered. May be eithe...
Gathers the subdomains of an array from each rank into a single array of the entire grid, removing halo padding from ``in_array``.
[ "Gathers", "the", "subdomains", "of", "an", "array", "from", "each", "rank", "into", "a", "single", "array", "of", "the", "entire", "grid", "removing", "halo", "padding", "from", "`", "`", "in_array", "`", "`", "." ]
def gather_array(self, queue, in_array, out_array, root): h = self.halo_shape dtype = None if self.rank != root else out_array.dtype dtype = self.bcast(dtype, root=root) if in_array.dtype != dtype: raise ValueError("in_array and out_array have different dtypes") cl_in...
[ "def", "gather_array", "(", "self", ",", "queue", ",", "in_array", ",", "out_array", ",", "root", ")", ":", "h", "=", "self", ".", "halo_shape", "dtype", "=", "None", "if", "self", ".", "rank", "!=", "root", "else", "out_array", ".", "dtype", "dtype", ...
Gathers the subdomains of an array from each rank into a single array of the entire grid, removing halo padding from ``in_array``.
[ "Gathers", "the", "subdomains", "of", "an", "array", "from", "each", "rank", "into", "a", "single", "array", "of", "the", "entire", "grid", "removing", "halo", "padding", "from", "`", "`", "in_array", "`", "`", "." ]
[ "\"\"\"\r\n Gathers the subdomains of an array from each rank into a single array\r\n of the entire grid, removing halo padding from ``in_array``.\r\n\r\n :arg queue: The :class:`pyopencl.CommandQueue` to enqueue kernels and copies.\r\n\r\n :arg in_array: The subarrays to be gathered.\r\...
[ { "param": "self", "type": null }, { "param": "queue", "type": null }, { "param": "in_array", "type": null }, { "param": "out_array", "type": null }, { "param": "root", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "queue", "type": null, "docstring": "The :class:`pyopencl.CommandQue...
6a82ca38d501a4c9cce768a7b815e5f1f140593e
zachjweiner/pystella
pystella/__init__.py
[ "MIT" ]
Python
choose_device_and_make_context
<not_specific>
def choose_device_and_make_context(platform_choice=None, device_choice=None): """ A wrapper that chooses a device and creates a :class:`pyopencl.Context` on a particular device. :arg platform_choice: An integer or string specifying which :class:`pyopencl.Platform` to choose. Defa...
A wrapper that chooses a device and creates a :class:`pyopencl.Context` on a particular device. :arg platform_choice: An integer or string specifying which :class:`pyopencl.Platform` to choose. Defaults to *None*, in which case the environment variables ``PYOPENCL_CTX`` or `...
A wrapper that chooses a device and creates a :class:`pyopencl.Context` on a particular device.
[ "A", "wrapper", "that", "chooses", "a", "device", "and", "creates", "a", ":", "class", ":", "`", "pyopencl", ".", "Context", "`", "on", "a", "particular", "device", "." ]
def choose_device_and_make_context(platform_choice=None, device_choice=None): import pyopencl as cl if platform_choice is None: import os if "PYOPENCL_CTX" in os.environ: ctx_spec = os.environ["PYOPENCL_CTX"] platform_choice = ctx_spec.split(":")[0] else: plat...
[ "def", "choose_device_and_make_context", "(", "platform_choice", "=", "None", ",", "device_choice", "=", "None", ")", ":", "import", "pyopencl", "as", "cl", "if", "platform_choice", "is", "None", ":", "import", "os", "if", "\"PYOPENCL_CTX\"", "in", "os", ".", ...
A wrapper that chooses a device and creates a :class:`pyopencl.Context` on a particular device.
[ "A", "wrapper", "that", "chooses", "a", "device", "and", "creates", "a", ":", "class", ":", "`", "pyopencl", ".", "Context", "`", "on", "a", "particular", "device", "." ]
[ "\"\"\"\r\n A wrapper that chooses a device and creates a :class:`pyopencl.Context` on\r\n a particular device.\r\n\r\n :arg platform_choice: An integer or string specifying which\r\n :class:`pyopencl.Platform` to choose.\r\n Defaults to *None*, in which case the environment variables\r\n ...
[ { "param": "platform_choice", "type": null }, { "param": "device_choice", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "platform_choice", "type": null, "docstring": "An integer or string specifying which\n:class:`pyopencl.Platform` to choose...
22cd5c5514ff7586fece21c733c4f61051000e07
zachjweiner/pystella
pystella/expansion.py
[ "MIT" ]
Python
step
null
def step(self, stage, energy, pressure, dt): """ Executes one stage of the time stepper. :arg stage: Which stage of the integrator to call. :arg energy: The current energy density, :math:`\\bar{\\rho}`. :arg pressure: The current pressure, :math:`\\bar{P}`. ...
Executes one stage of the time stepper. :arg stage: Which stage of the integrator to call. :arg energy: The current energy density, :math:`\\bar{\\rho}`. :arg pressure: The current pressure, :math:`\\bar{P}`. :arg dt: The timestep to take.
Executes one stage of the time stepper.
[ "Executes", "one", "stage", "of", "the", "time", "stepper", "." ]
def step(self, stage, energy, pressure, dt): arg_dict = dict(a=self.a, adot=self.adot, dt=dt, energy=energy, pressure=pressure) self.stepper(stage, **arg_dict) self.hubble[()] = self.adot / self.a
[ "def", "step", "(", "self", ",", "stage", ",", "energy", ",", "pressure", ",", "dt", ")", ":", "arg_dict", "=", "dict", "(", "a", "=", "self", ".", "a", ",", "adot", "=", "self", ".", "adot", ",", "dt", "=", "dt", ",", "energy", "=", "energy", ...
Executes one stage of the time stepper.
[ "Executes", "one", "stage", "of", "the", "time", "stepper", "." ]
[ "\"\"\"\r\n Executes one stage of the time stepper.\r\n\r\n :arg stage: Which stage of the integrator to call.\r\n\r\n :arg energy: The current energy density, :math:`\\\\bar{\\\\rho}`.\r\n\r\n :arg pressure: The current pressure, :math:`\\\\bar{P}`.\r\n\r\n :arg dt: The timestep ...
[ { "param": "self", "type": null }, { "param": "stage", "type": null }, { "param": "energy", "type": null }, { "param": "pressure", "type": null }, { "param": "dt", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "stage", "type": null, "docstring": "Which stage of the integrator t...
22cd5c5514ff7586fece21c733c4f61051000e07
zachjweiner/pystella
pystella/expansion.py
[ "MIT" ]
Python
constraint
<not_specific>
def constraint(self, energy): """ A dimensionless measure of the satisfaction of the first Friedmann equation (as a constraint on the evolution), equal to .. math:: \\left\\vert \\frac{1}{\\mathcal{H}} \\sqrt{\\frac{8 \\pi a^2}{3 m_\\mathrm{pl}^2} \\rho}...
A dimensionless measure of the satisfaction of the first Friedmann equation (as a constraint on the evolution), equal to .. math:: \\left\\vert \\frac{1}{\\mathcal{H}} \\sqrt{\\frac{8 \\pi a^2}{3 m_\\mathrm{pl}^2} \\rho} - 1 \\right\\vert ...
A dimensionless measure of the satisfaction of the first Friedmann equation (as a constraint on the evolution), equal to
[ "A", "dimensionless", "measure", "of", "the", "satisfaction", "of", "the", "first", "Friedmann", "equation", "(", "as", "a", "constraint", "on", "the", "evolution", ")", "equal", "to" ]
def constraint(self, energy): return np.abs(self.adot_friedmann_1(self.a[0], energy) / self.adot[0] - 1)
[ "def", "constraint", "(", "self", ",", "energy", ")", ":", "return", "np", ".", "abs", "(", "self", ".", "adot_friedmann_1", "(", "self", ".", "a", "[", "0", "]", ",", "energy", ")", "/", "self", ".", "adot", "[", "0", "]", "-", "1", ")" ]
A dimensionless measure of the satisfaction of the first Friedmann equation (as a constraint on the evolution), equal to
[ "A", "dimensionless", "measure", "of", "the", "satisfaction", "of", "the", "first", "Friedmann", "equation", "(", "as", "a", "constraint", "on", "the", "evolution", ")", "equal", "to" ]
[ "\"\"\"\r\n A dimensionless measure of the satisfaction of the first Friedmann equation\r\n (as a constraint on the evolution), equal to\r\n\r\n .. math::\r\n\r\n \\\\left\\\\vert \\\\frac{1}{\\\\mathcal{H}}\r\n \\\\sqrt{\\\\frac{8 \\\\pi a^2}{3 m_\\\\mathrm{pl}^2} \\\\rho...
[ { "param": "self", "type": null }, { "param": "energy", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "energy", "type": null, "docstring": "The current energy density, :m...
de170daf548a2db7fd968e97044478d69f73ecb6
chihming/LibMultiLabel
libmultilabel/model.py
[ "MIT" ]
Python
configure_optimizers
<not_specific>
def configure_optimizers(self): """Initialize an optimizer for the free parameters of the network. """ parameters = [p for p in self.parameters() if p.requires_grad] optimizer_name = self.optimizer if optimizer_name == 'sgd': optimizer = optim.SGD(parameters, self.lea...
Initialize an optimizer for the free parameters of the network.
Initialize an optimizer for the free parameters of the network.
[ "Initialize", "an", "optimizer", "for", "the", "free", "parameters", "of", "the", "network", "." ]
def configure_optimizers(self): parameters = [p for p in self.parameters() if p.requires_grad] optimizer_name = self.optimizer if optimizer_name == 'sgd': optimizer = optim.SGD(parameters, self.learning_rate, momentum=self.momentum, ...
[ "def", "configure_optimizers", "(", "self", ")", ":", "parameters", "=", "[", "p", "for", "p", "in", "self", ".", "parameters", "(", ")", "if", "p", ".", "requires_grad", "]", "optimizer_name", "=", "self", ".", "optimizer", "if", "optimizer_name", "==", ...
Initialize an optimizer for the free parameters of the network.
[ "Initialize", "an", "optimizer", "for", "the", "free", "parameters", "of", "the", "network", "." ]
[ "\"\"\"Initialize an optimizer for the free parameters of the network.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
de170daf548a2db7fd968e97044478d69f73ecb6
chihming/LibMultiLabel
libmultilabel/model.py
[ "MIT" ]
Python
shared_step
<not_specific>
def shared_step(self, batch): """Return loss and predicted logits of the network. Args: batch (dict): A batch of text and label. Returns: loss (Tensor): Binary cross-entropy between target and predict logits. pred_logits (Tensor): The predict logits (batch_s...
Return loss and predicted logits of the network. Args: batch (dict): A batch of text and label. Returns: loss (Tensor): Binary cross-entropy between target and predict logits. pred_logits (Tensor): The predict logits (batch_size, num_classes).
Return loss and predicted logits of the network.
[ "Return", "loss", "and", "predicted", "logits", "of", "the", "network", "." ]
def shared_step(self, batch): target_labels = batch['label'] outputs = self.network(batch['text']) pred_logits = outputs['logits'] loss = F.binary_cross_entropy_with_logits(pred_logits, target_labels.float()) return loss, pred_logits
[ "def", "shared_step", "(", "self", ",", "batch", ")", ":", "target_labels", "=", "batch", "[", "'label'", "]", "outputs", "=", "self", ".", "network", "(", "batch", "[", "'text'", "]", ")", "pred_logits", "=", "outputs", "[", "'logits'", "]", "loss", "...
Return loss and predicted logits of the network.
[ "Return", "loss", "and", "predicted", "logits", "of", "the", "network", "." ]
[ "\"\"\"Return loss and predicted logits of the network.\n\n Args:\n batch (dict): A batch of text and label.\n\n Returns:\n loss (Tensor): Binary cross-entropy between target and predict logits.\n pred_logits (Tensor): The predict logits (batch_size, num_classes).\n ...
[ { "param": "self", "type": null }, { "param": "batch", "type": null } ]
{ "returns": [ { "docstring": "loss (Tensor): Binary cross-entropy between target and predict logits.\npred_logits (Tensor): The predict logits (batch_size, num_classes).", "docstring_tokens": [ "loss", "(", "Tensor", ")", ":", "Binary", "cross",...
de170daf548a2db7fd968e97044478d69f73ecb6
chihming/LibMultiLabel
libmultilabel/model.py
[ "MIT" ]
Python
print
null
def print(self, *args, **kwargs): """Prints only from process 0 and not in silent mode. Use this in any distributed mode to log only once.""" if not self.silent: # print() in LightningModule to print only from process 0 super().print(*args, **kwargs)
Prints only from process 0 and not in silent mode. Use this in any distributed mode to log only once.
Prints only from process 0 and not in silent mode. Use this in any distributed mode to log only once.
[ "Prints", "only", "from", "process", "0", "and", "not", "in", "silent", "mode", ".", "Use", "this", "in", "any", "distributed", "mode", "to", "log", "only", "once", "." ]
def print(self, *args, **kwargs): if not self.silent: super().print(*args, **kwargs)
[ "def", "print", "(", "self", ",", "*", "args", ",", "**", "kwargs", ")", ":", "if", "not", "self", ".", "silent", ":", "super", "(", ")", ".", "print", "(", "*", "args", ",", "**", "kwargs", ")" ]
Prints only from process 0 and not in silent mode.
[ "Prints", "only", "from", "process", "0", "and", "not", "in", "silent", "mode", "." ]
[ "\"\"\"Prints only from process 0 and not in silent mode. Use this in any\n distributed mode to log only once.\"\"\"", "# print() in LightningModule to print only from process 0" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
8375fc13234092af4190e338351a6ab991d4d3ab
chihming/LibMultiLabel
libmultilabel/linear/linear.py
[ "MIT" ]
Python
train_1vsrest
<not_specific>
def train_1vsrest(y: sparse.csr_matrix, x: sparse.csr_matrix, options: str): """ Trains a linear model for multiabel data using a one-vs-all strategy. Returns the model. y is a 0/1 matrix with dimensions number of instances * number of classes. x is a matrix with dimensions number of instances * n...
Trains a linear model for multiabel data using a one-vs-all strategy. Returns the model. y is a 0/1 matrix with dimensions number of instances * number of classes. x is a matrix with dimensions number of instances * number of features. options is the option string passed to liblinear.
Trains a linear model for multiabel data using a one-vs-all strategy. Returns the model. y is a 0/1 matrix with dimensions number of instances * number of classes. x is a matrix with dimensions number of instances * number of features. options is the option string passed to liblinear.
[ "Trains", "a", "linear", "model", "for", "multiabel", "data", "using", "a", "one", "-", "vs", "-", "all", "strategy", ".", "Returns", "the", "model", ".", "y", "is", "a", "0", "/", "1", "matrix", "with", "dimensions", "number", "of", "instances", "*", ...
def train_1vsrest(y: sparse.csr_matrix, x: sparse.csr_matrix, options: str): if options.find('-R') != -1: raise ValueError('-R is not supported') bias = -1. if options.find('-B') != -1: options_split = options.split() i = options_split.index('-B') bias = float(options_split[i...
[ "def", "train_1vsrest", "(", "y", ":", "sparse", ".", "csr_matrix", ",", "x", ":", "sparse", ".", "csr_matrix", ",", "options", ":", "str", ")", ":", "if", "options", ".", "find", "(", "'-R'", ")", "!=", "-", "1", ":", "raise", "ValueError", "(", "...
Trains a linear model for multiabel data using a one-vs-all strategy.
[ "Trains", "a", "linear", "model", "for", "multiabel", "data", "using", "a", "one", "-", "vs", "-", "all", "strategy", "." ]
[ "\"\"\"\n Trains a linear model for multiabel data using a one-vs-all strategy.\n\n Returns the model.\n\n y is a 0/1 matrix with dimensions number of instances * number of classes.\n x is a matrix with dimensions number of instances * number of features.\n options is the option string passed to libl...
[ { "param": "y", "type": "sparse.csr_matrix" }, { "param": "x", "type": "sparse.csr_matrix" }, { "param": "options", "type": "str" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "y", "type": "sparse.csr_matrix", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "x", "type": "sparse.csr_matrix", "docstring": null, ...
8375fc13234092af4190e338351a6ab991d4d3ab
chihming/LibMultiLabel
libmultilabel/linear/linear.py
[ "MIT" ]
Python
predict_values
np.ndarray
def predict_values(model, x: sparse.csr_matrix) -> np.ndarray: """ Calculates the decision values associated with x. Returns a matrix with dimension number of instances * number of classes. x is a matrix with dimension number of instances * number of features. """ bias = model['-B'] bias_c...
Calculates the decision values associated with x. Returns a matrix with dimension number of instances * number of classes. x is a matrix with dimension number of instances * number of features.
Calculates the decision values associated with x. Returns a matrix with dimension number of instances * number of classes. x is a matrix with dimension number of instances * number of features.
[ "Calculates", "the", "decision", "values", "associated", "with", "x", ".", "Returns", "a", "matrix", "with", "dimension", "number", "of", "instances", "*", "number", "of", "classes", ".", "x", "is", "a", "matrix", "with", "dimension", "number", "of", "instan...
def predict_values(model, x: sparse.csr_matrix) -> np.ndarray: bias = model['-B'] bias_col = np.full((x.shape[0], 1 if bias > 0 else 0), bias) nr_feature = model['weights'].shape[0] nr_feature -= 1 if bias > 0 else 0 if x.shape[1] < nr_feature: x = sparse.hstack([ x, ...
[ "def", "predict_values", "(", "model", ",", "x", ":", "sparse", ".", "csr_matrix", ")", "->", "np", ".", "ndarray", ":", "bias", "=", "model", "[", "'-B'", "]", "bias_col", "=", "np", ".", "full", "(", "(", "x", ".", "shape", "[", "0", "]", ",", ...
Calculates the decision values associated with x.
[ "Calculates", "the", "decision", "values", "associated", "with", "x", "." ]
[ "\"\"\"\n Calculates the decision values associated with x.\n\n Returns a matrix with dimension number of instances * number of classes.\n\n x is a matrix with dimension number of instances * number of features.\n \"\"\"" ]
[ { "param": "model", "type": null }, { "param": "x", "type": "sparse.csr_matrix" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "model", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "x", "type": "sparse.csr_matrix", "docstring": null, "docstri...
c1850e4358d5062e1410e2b177e4c0a55918534c
chihming/LibMultiLabel
libmultilabel/utils.py
[ "MIT" ]
Python
dump_log
null
def dump_log(log_path, metrics=None, split=None, config=None): """Write log including config and the evaluation scores. Args: log_path(str): path to log path metrics (dict): metric and scores in dictionary format, defaults to None split (str): val or test, defaults to None confi...
Write log including config and the evaluation scores. Args: log_path(str): path to log path metrics (dict): metric and scores in dictionary format, defaults to None split (str): val or test, defaults to None config (dict): config to save, defaults to None
Write log including config and the evaluation scores.
[ "Write", "log", "including", "config", "and", "the", "evaluation", "scores", "." ]
def dump_log(log_path, metrics=None, split=None, config=None): os.makedirs(os.path.dirname(log_path), exist_ok=True) if os.path.isfile(log_path): with open(log_path) as fp: result = json.load(fp) else: result = dict() if config: config_to_save = copy.deepcopy(dict(con...
[ "def", "dump_log", "(", "log_path", ",", "metrics", "=", "None", ",", "split", "=", "None", ",", "config", "=", "None", ")", ":", "os", ".", "makedirs", "(", "os", ".", "path", ".", "dirname", "(", "log_path", ")", ",", "exist_ok", "=", "True", ")"...
Write log including config and the evaluation scores.
[ "Write", "log", "including", "config", "and", "the", "evaluation", "scores", "." ]
[ "\"\"\"Write log including config and the evaluation scores.\n\n Args:\n log_path(str): path to log path\n metrics (dict): metric and scores in dictionary format, defaults to None\n split (str): val or test, defaults to None\n config (dict): config to save, defaults to None\n \"\"\...
[ { "param": "log_path", "type": null }, { "param": "metrics", "type": null }, { "param": "split", "type": null }, { "param": "config", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "log_path", "type": null, "docstring": "path to log path", "docstring_tokens": [ "path", "to", "log", "path" ], "default": null, "is_optional": false }, { "identif...