def levelSelectionMenu():
"""
Fait fonctionner le menu de sélection d'un niveau enregistré.
"""
goInBlack()
levels = IO.getLevels("level")
levelSelected = 0
level = IO.loadLevel(level=levels[0])
game.initSelectionLevel(level)
moveRender(levels, levelSelected, IO.loadLevel)
while not evenement.event["game"] == 'return':
evenement.compute()
ui.logic(evenement.event["tk"])
if evenement.event["game"] == "right":
levelSelected = move(levelSelected, levels, 1, IO.loadLevel)
elif evenement.event["game"] == "left":
levelSelected = move(levelSelected, levels, -1, IO.loadLevel)
elif evenement.event["game"] == "play":
goInBlack()
game.play(levels[levelSelected], "s")
backInBlack(game.initSelectionLevel, [levels[levelSelected]])
moveRender(levels, levelSelected, IO.loadLevel)
elif evenement.event["game"] == "edit":
goInBlack()
editor.editor(levels[levelSelected])
backInBlack(game.initSelectionLevel, [levels[levelSelected]])
moveRender(levels, levelSelected, IO.loadLevel)
game.updateTime()
animation.update()
ui.render(game.getFps())
mise_a_jour()
backInBlack(game.initPlayMenu)
def begin(arg):
print arg
with cd('socialscan'):
ipaddress,personality=str(arg).split(':')
print ipaddress, personality
path=str(ipaddress)+'socialscan.config'
get('socialscan.config',path)
print 'Transferred socialscan.config file from server to localhost for editing'
sharing=editor.getInfo(path)
shandler=scanname.getName(ipaddress)
print sharing
print shandler
editor.editor(shandler,personality,sharing,path)
put(path,'socialscan.config')
def interroplot(path, query):
import corpkit
"""Interrogates path with Tregex query, gets relative frequencies, and plots the top seven results"""
from corpkit import interrogator, editor, plotter
quickstart = interrogator(path, 'words', query)
edited = editor(quickstart.results, '%', quickstart.totals, print_info = False)
plotter(str(path), edited.results)
def __init__(self, name, is_old_project, old_project_file):
self.name = name
self.is_old_project = is_old_project
self.old_project_file = old_project_file
self.editor = editor(self, self.is_old_project, self.old_project_file)
def edit(self, *args, **kwargs):
"""Delete or keep rows by subcorpus or by middle column text.
>>> skipped = conc.edit(skip_entries = r'to_?match')"""
from editor import editor
return editor(self, *args, **kwargs)
def edit(self, *args, **kwargs):
"""Delete or keep rows by subcorpus or by middle column text.
>>> skipped = conc.edit(skip_entries = r'to_?match')"""
from editor import editor
return editor(self, *args, **kwargs)
def default(mapeditor):
# general things
m=editor(mapeditor)
# a wall around the world, suitable for all games.
m.make('wall',type='wall',pos=(-151,-101,village_height),bbox=[1,102,2.5])
m.make('wall',type='wall',pos=(-151,-101,village_height),bbox=[152,1,2.5])
m.make('wall',type='wall',pos=(-151,100,village_height),bbox=[152,1,2.5])
m.make('wall',type='wall',pos=(100,-101,village_height),bbox=[1,102,2.5])
m.make('weather',type='weather',desc='object that describes the weather',
pos=(0,1,0), rain=0.0)
# the gallows
gallows = m.make('gallows', type='gallows', pos=gallows_pos)
# the mayor, who runs the game
mayor=m.make('mayor', type='mayor', pos=(1, 1, village_height))
# the hangman, who lynches the villagers
hangman=m.make('hangman', type='hangman', pos=(5, 5, village_height))
m.learn(hangman,execute)
m.know(hangman,knowledge)
m.own(hangman,gallows)
def edit(self, *args, **kwargs):
"""Edit each value with :func:`~corpkit.interrogation.Interrogation.edit`.
See :func:`~corpkit.interrogation.Interrogation.edit` for possible arguments.
:returns: :class:`corpkit.interrogation.Interrodict`
"""
from editor import editor
return editor(self, *args, **kwargs)
def edit(self, *args, **kwargs):
"""Edit each value with :func:`~corpkit.interrogation.Interrogation.edit`.
See :func:`~corpkit.interrogation.Interrogation.edit` for possible arguments.
:returns: A :class:`corpkit.interrogation.Interrodict`
"""
from editor import editor
return editor(self, *args, **kwargs)
def create_town_buildings(mapeditor):
m = editor(mapeditor)
cfire=m.make('campfire',type='campfire',xyz=(3,9,10))
m.make('fire',type='fire',xyz=(0,0,0),parent=cfire.id)
m.make('mausoleum', type='mausoleum', xyz=(40,40,10))
m.make('mausoleum', type='mausoleum', xyz=(40,-40,10))
m.make('tavern',type='house3',xyz=(-80,-20,town_height),orientation=directions[2])
# tower for the keep
m.make('tower',type='tower',xyz=(-200,-120,30))
def MENU(): # first Menu
import os
from ascci import rabbit
from editor import editor
from keydetect import keydetect
from lwsystem import osuser
from creds import creds
os.system("clear")
print "\x1b[0;31m" + "ducky converter/encoder " + "\x1b[0m" + "by"
CSI = "\x1B["
print " " + CSI + "\x1b[31;5m" + " ------------\n |DuckyTools|\n ------------" + CSI + "0m"
print "(python2.7)"
print("\n")
userChoice = raw_input(
"\nMENU :\n\nWhat do you want ?\n\n1) editor for translat many ducky/P4wnP1 keyboard keys \n2) generate payloads for P4wnP1 A.L.O.A with web client interface \n3) test P4wnP1 with a simple keyboard detect key pressed\n4) Creds\n\n99) exit \n\n>>> "
)
if userChoice == "1":
editor()
elif userChoice == "2":
print "\n"
os.system("clear")
osuser()
elif userChoice == "3":
keydetect()
elif userChoice == "4":
creds()
elif userChoice == "99":
rabbit()
exit()
else:
print "\nan error occurred, please try again\n"
MENU()
def plain(mapeditor):
# general things
m=editor(mapeditor)
world=m.look()
points = { }
for i in range(-6, 7):
for j in range(-6, 7):
points['%ix%i'%(i,j)] = [i, j, 8]
m.set(world.id, terrain={'points' : points})
def plain(mapeditor):
# general things
m = editor(mapeditor)
world = m.look()
points = {}
for i in range(-6, 7):
for j in range(-6, 7):
points['%ix%i' % (i, j)] = [i, j, 8]
m.set(world.id, terrain={'points': points})
def __init__(self, parent=None):
QtGui.QMainWindow.__init__(self, parent)
self.__Dir = os.path.dirname(sys.argv[0])
self.icons = os.path.join(self.__Dir, 'icons/')
self.resize(640, 480)
self.setWindowTitle('PyTe v3')
self.setWindowIcon(QtGui.QIcon(self.icons+'pyte.png'))
self.mainTabWidget = QtGui.QTabWidget(self)
self.mainTabWidget.setTabsClosable(True)
self.mainTabWidget.setMovable(True)
self.setCentralWidget(self.mainTabWidget)
newEditor = editor(self, self)
newTab = self.mainTabWidget.addTab(newEditor, QtGui.QIcon(self.icons+'pyte.png'), "Pyte v3")
self.mainTabWidget.setCurrentIndex(newTab)
self.statusBar()
closeTab = QtGui.QAction(QtGui.QIcon(self.icons+'exit.png'), 'Close Tab', self)
closeTab.setStatusTip('Close Tab')
self.connect(closeTab, QtCore.SIGNAL('triggered()'), self.closetab)
newtab = QtGui.QAction(QtGui.QIcon(self.icons+'add.png'), 'Add Tab', self)
newtab.setStatusTip('Add Tab')
self.connect(newtab,QtCore.SIGNAL('triggered()'), self.codetab)
self.connect(self.mainTabWidget, QtCore.SIGNAL("tabCloseRequested (int)"), self.on_close_tab_requested)
self.connect(self.mainTabWidget, QtCore.SIGNAL("currentChanged (int)"), self.on_tab_change)
menubar = self.menuBar()
file = menubar.addMenu('&File')
file.addAction(newtab)
file.addAction(closeTab)
#if there is a argument passed then try to open it as a file
if (len(sys.argv) > 1):
fn = sys.argv[1]
fileName = str(fn)
try:
self.editor.openArg(fileName)
self.editor.title(fileName)
except:
return
self.setWindowTitle(fileName+" - PyTe v3")
else:
pass
def create_town_buildings(mapeditor):
m = editor(mapeditor)
cfire = m.make('campfire', type='campfire', xyz=(3, 9, 10))
m.make('fire', type='fire', xyz=(0, 0, 0), parent=cfire.id)
m.make('mausoleum', type='mausoleum', xyz=(40, 40, 10))
m.make('mausoleum', type='mausoleum', xyz=(40, -40, 10))
m.make('tavern',
type='house3',
xyz=(-80, -20, town_height),
orientation=directions[2])
# tower for the keep
m.make('tower', type='tower', xyz=(-200, -120, 30))
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.resize(402, 496)
self.centralwidget = QtGui.QWidget(MainWindow)
self.centralwidget.setObjectName("centralwidget")
self.verticalLayout = QtGui.QVBoxLayout(self.centralwidget)
self.verticalLayout.setObjectName("verticalLayout")
self.splitter = QtGui.QSplitter(self.centralwidget)
self.splitter.setOrientation(QtCore.Qt.Vertical)
self.splitter.setObjectName("splitter")
self.list = QtGui.QTreeWidget(self.splitter)
self.list.setTabKeyNavigation(True)
self.list.setAlternatingRowColors(True)
self.list.setItemsExpandable(False)
self.list.setExpandsOnDoubleClick(False)
self.list.setObjectName("list")
self.editor = editor(self.splitter)
self.editor.setObjectName("editor")
self.verticalLayout.addWidget(self.splitter)
MainWindow.setCentralWidget(self.centralwidget)
self.menubar = QtGui.QMenuBar(MainWindow)
self.menubar.setGeometry(QtCore.QRect(0, 0, 402, 25))
self.menubar.setObjectName("menubar")
self.menuMenu = QtGui.QMenu(self.menubar)
self.menuMenu.setObjectName("menuMenu")
MainWindow.setMenuBar(self.menubar)
self.toolBar = QtGui.QToolBar(MainWindow)
self.toolBar.setObjectName("toolBar")
MainWindow.addToolBar(QtCore.Qt.ToolBarArea(QtCore.Qt.TopToolBarArea), self.toolBar)
self.actionDelete_Provider = QtGui.QAction(MainWindow)
self.actionDelete_Provider.setObjectName("actionDelete_Provider")
self.actionNew_Provider = QtGui.QAction(MainWindow)
self.actionNew_Provider.setObjectName("actionNew_Provider")
self.actionEdit_Provider = QtGui.QAction(MainWindow)
self.actionEdit_Provider.setObjectName("actionEdit_Provider")
self.menuMenu.addAction(self.actionNew_Provider)
self.menuMenu.addAction(self.actionDelete_Provider)
self.menuMenu.addAction(self.actionEdit_Provider)
self.menubar.addAction(self.menuMenu.menuAction())
self.toolBar.addAction(self.actionNew_Provider)
self.toolBar.addAction(self.actionDelete_Provider)
self.toolBar.addAction(self.actionEdit_Provider)
self.retranslateUi(MainWindow)
QtCore.QObject.connect(self.list, QtCore.SIGNAL("itemSelectionChanged()"), self.editor.hide)
QtCore.QObject.connect(self.list, QtCore.SIGNAL("itemDoubleClicked(QTreeWidgetItem*,int)"), self.editor.edit)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
def modify_terrain(mapeditor):
# general things
m = editor(mapeditor)
world = m.look()
points = {}
for i in range(-6, 7):
for j in range(-6, 7):
if i >= 5 or j >= 5:
points['%ix%i' % (i, j)] = [i, j, uniform(100, 150)]
elif i <= -5 or j <= -5:
points['%ix%i' % (i, j)] = [i, j, uniform(-30, -10)]
elif (i == 2 or i == 3) and (j == 2 or j == 3):
points['%ix%i' % (i, j)] = [i, j, uniform(20, 25)]
elif i == 4 or j == 4:
points['%ix%i' % (i, j)] = [i, j, uniform(30, 80)]
elif i == -4 or j == -4:
points['%ix%i' % (i, j)] = [i, j, uniform(-5, 5)]
else:
points['%ix%i' % (i, j)] = [
i, j, 1 + uniform(3, 11) * (abs(i) + abs(j))
]
points['-4x-1'] = [-4, -1, 12.4]
points['-4x-2'] = [-4, -2, -8.3]
points['-3x-2'] = [-3, -2, -6.2]
points['-3x-1'] = [-3, -1, -5.3]
points['-2x-1'] = [-2, -1, -4.1]
points['-1x-1'] = [-1, -1, -16.8]
points['0x-1'] = [0, -1, -3.8]
points['-1x0'] = [-1, 0, -2.8]
points['-1x1'] = [-1, 1, -1.8]
points['-1x2'] = [-1, 2, -1.7]
points['0x2'] = [0, 2, -1.6]
points['1x2'] = [1, 2, -1.3]
points['1x3'] = [1, 3, -1.1]
points['1x4'] = [1, 4, -0.6]
points['1x-1'] = [1, -1, 15.8]
points['0x0'] = [0, 0, 12.8]
points['1x0'] = [1, 0, 23.1]
points['0x1'] = [0, 1, 14.2]
points['1x1'] = [1, 1, 19.7]
m.set(world.id, terrain={'points': points})
def modify_terrain(mapeditor):
# general things
m=editor(mapeditor)
world=m.look()
points = { }
for i in range(-6, 7):
for j in range(-6, 7):
if i>=5 or j>=5:
points['%ix%i'%(i,j)] = [i, j, uniform(100, 150)]
elif i<=-5 or j <= -5:
points['%ix%i'%(i,j)] = [i, j, uniform(-30, -10)]
elif (i==2 or i==3) and (j==2 or j==3):
points['%ix%i'%(i,j)] = [i, j, uniform(20, 25)]
elif i==4 or j==4:
points['%ix%i'%(i,j)] = [i, j, uniform(30, 80)]
elif i==-4 or j==-4:
points['%ix%i'%(i,j)] = [i, j, uniform(-5, 5)]
else:
points['%ix%i'%(i,j)] = [i, j, 1+uniform(3, 11)*(abs(i)+abs(j))]
points['-4x-1'] = [-4, -1, 12.4]
points['-4x-2'] = [-4, -2, -8.3]
points['-3x-2'] = [-3, -2, -6.2]
points['-3x-1'] = [-3, -1, -5.3]
points['-2x-1'] = [-2, -1, -4.1]
points['-1x-1'] = [-1, -1, -16.8]
points['0x-1'] = [0, -1, -3.8]
points['-1x0'] = [-1, 0, -2.8]
points['-1x1'] = [-1, 1, -1.8]
points['-1x2'] = [-1, 2, -1.7]
points['0x2'] = [0, 2, -1.6]
points['1x2'] = [1, 2, -1.3]
points['1x3'] = [1, 3, -1.1]
points['1x4'] = [1, 4, -0.6]
points['1x-1'] = [1, -1, 15.8]
points['0x0'] = [0, 0, 12.8]
points['1x0'] = [1, 0, 23.1]
points['0x1'] = [0, 1, 14.2]
points['1x1'] = [1, 1, 19.7]
m.set(world.id, terrain={'points' : points})
def default(mapeditor):
# general things
m = editor(mapeditor)
# a wall around the world, suitable for all games.
m.make('wall',
type='wall',
pos=(-151, -101, village_height),
bbox=[1, 102, 2.5])
m.make('wall',
type='wall',
pos=(-151, -101, village_height),
bbox=[152, 1, 2.5])
m.make('wall',
type='wall',
pos=(-151, 100, village_height),
bbox=[152, 1, 2.5])
m.make('wall',
type='wall',
pos=(100, -101, village_height),
bbox=[1, 102, 2.5])
m.make('weather',
type='weather',
desc='object that describes the weather',
pos=(0, 1, 0),
rain=0.0)
# the gallows
gallows = m.make('gallows', type='gallows', pos=gallows_pos)
# the mayor, who runs the game
mayor = m.make('mayor', type='mayor', pos=(1, 1, village_height))
# the hangman, who lynches the villagers
hangman = m.make('hangman', type='hangman', pos=(5, 5, village_height))
m.learn(hangman, execute)
m.know(hangman, knowledge)
m.own(hangman, gallows)
def multiquery(corpus, query, sort_by = 'total', quicksave = False):
import corpkit
"""Creates a named tuple for a list of named queries to count.
Pass in something like:
[[u'NPs in corpus', r'NP'], [u'VPs in corpus', r'VP']]"""
import collections
import os
import pandas
import pandas as pd
from time import strftime, localtime
from interrogator import interrogator
from editor import editor
if quicksave:
savedir = 'saved_interrogations'
if not quicksave.endswith('.p'):
quicksave = quicksave + '.p'
fullpath = os.path.join(savedir, quicksave)
while os.path.isfile(fullpath):
selection = raw_input("\nSave error: %s already exists in %s.\n\nPick a new name: " % (savename, savedir))
if not selection.endswith('.p'):
selection = selection + '.p'
fullpath = os.path.join(savedir, selection)
results = []
for name, pattern in query:
result = interrogator(corpus, 'count', pattern)
result.totals.name = name # rename count
results.append(result.totals)
results = pd.concat(results, axis = 1)
results = editor(results, sort_by = sort_by, print_info = False, keep_stats = False)
time = strftime("%H:%M:%S", localtime())
print '%s: Finished! %d unique results, %d total.' % (time, len(results.results.columns), results.totals.sum())
if quicksave:
from other import save_result
save_result(results, quicksave)
return results
def edit(self, *args, **kwargs):
"""calls corpkit.editor.editor()"""
from editor import editor
return editor(self, *args, **kwargs)
def main():
from fhbgui import coprscreen, titlescreen, level_select
from editor import editor
G.display.set_caption("Loading")
joycfg.dump_joysticks(verbose=False)
wndicon = G.image.load('tilesets/wndicon32.png')
G.display.set_icon(wndicon)
view = FHBGView()
game = FHBGGame(view)
view.bindings = joycfg.load_bindings(keybindings_filename)
G.display.set_caption("Forehead Block Guy")
quitting = False
if view.bindings == 'reconfigure':
got_preset = joycfg_get_preset()
if got_preset:
from textwrap import TextWrapper
tw = TextWrapper(width=28)
try:
jname = joycfg.joysticks[0].get_name()
except IndexError:
jname = "Keyboard"
bindingsNotice = '\n'.join([
"\nRecommended settings for",
tw.fill(jname),
format_bindings(got_preset), "\nPress Tab to change"
])
view.bindings = got_preset
e = coprscreen(view, bindingsNotice, with_tab=True)
if e & VK_SELECT:
got_preset = None
view.bindings = (got_preset
or joycfg.get_bindings(view.display.get_surface(),
view.font,
action_names,
flipper=view.display))
if not view.bindings:
return
joycfg.save_bindings(keybindings_filename, view.bindings, action_names)
elif not isinstance(view.bindings, list):
view.bindings = [('key', b) for b in default_bindings]
if todoNotice:
e = coprscreen(view, todoNotice)
while not quitting:
selected = titlescreen(view)
if selected < 0:
break
if selected == 1:
bindingsNotice = '\n'.join([
"\nControls:",
format_bindings(view.bindings),
"\nTo change the controls,\npress Tab or Select"
])
e = coprscreen(view, bindingsNotice, with_tab=True)
if e & VK_SELECT:
newbindings = joycfg.get_bindings(view.display.get_surface(),
view.font,
action_names,
flipper=view.display)
view.bindings = newbindings or view.bindings
joycfg.save_bindings(keybindings_filename, view.bindings,
action_names)
read_pads(view) # clear out fire button
continue
elif selected == 2: # practice
ls_level = 0
while True:
e, ls_level = level_select(view, game, ls_level)
if ls_level < 0:
break
game.new_game()
game.pf.sheet = view.metatile_sheet
result = play_level(view, game, game.levels[ls_level])
if result == 'q':
quitting = True
continue
elif selected == 3: # edit
editor(view, game, play_level)
continue
elif selected == 4: # help
e = coprscreen(view, helpScreenText)
continue
result = play_game(view, game)
if result == 'q':
quitting = True
view.close()
def edit(self, *args, **kwargs):
"""Manipulate results of interrogations.
There are a few overall kinds of edit, most of which can be combined into a single function call. It's useful to keep in mind that many are basic wrappers around `pandas` operations---if you're comfortable with `pandas` syntax, it may be faster at times to use its syntax instead.
:Basic mathematical operations:
First, you can do basic maths on results, optionally passing in some data to serve as the denominator. Very commonly, you'll want to get relative frequencies:
:Example:
>>> data = corpus.interrogate({W: r'^t'})
>>> rel = data.edit('%', SELF)
>>> rel.results
.. to that the then ... toilet tolerant tolerate ton
01 18.50 14.65 14.44 6.20 ... 0.00 0.00 0.11 0.00
02 24.10 14.34 13.73 8.80 ... 0.00 0.00 0.00 0.00
03 17.31 18.01 9.97 7.62 ... 0.00 0.00 0.00 0.00
For the operation, there are a number of possible values, each of which is to be passed in as a `str`:
`+`, `-`, `/`, `*`, `%`: self explanatory
`k`: log likelihood (keywords)
`a`: get distance metric
`d`: get percent difference (alternative approach to keywording)
`SELF` is a very useful shorthand denominator. When used, all editing is performed on the data. The totals are then extracted from the edited data, and used as denominator. If this is not the desired behaviour, however, a more specific `interrogation.results` or `interrogation.totals` branch can be used.
In the example above, `SELF` (or `'self'`) is equivalent to:
:Example:
>>> rel = data.edit('%', data.totals)
:Keeping and skipping data:
There are four keyword arguments that can be used to keep or skip rows or columns in the data:
* `just_entries`
* `just_subcorpora`
* `skip_entries`
* `skip_subcorpora`
Each can accept different input types:
* str: treated as regular expression to match
* list:
* of integers: indices to match
* of strings: entries/subcorpora to match
:Example:
>>> data.edit(just_entries = r'^fr',
... skip_entries = ['free', 'freedom'],
... skip_subcorpora = r'[0-9]')
:Merging data:
There are also keyword arguments for merging entries and subcorpora.
* `merge_entries`
* `merge_subcorpora`
These take a `dict`, with the new name as key and the criteria as value. The criteria can be a str (regex) or wordlist.
:Example:
>>> from dictionaries.wordlists import wordlists
>>> mer = {'Articles': ['the', 'an', 'a'], 'Modals': wordlists.modals}
>>> data.edit(merge_entries = mer)
:Sorting:
The `sort_by` keyword argument takes a `str`, which represents the way the result columns should be ordered.
* `increase`: highest to lowest slope value
* `decrease`: lowest to highest slope value
* `turbulent`: most change in y axis values
* `static`: least change in y axis values
* `total/most`: largest number first
* `infreq/least`: smallest number first
* `name`: alphabetically
:Example:
>>> data.edit(sort_by = 'increase')
:Editing entry text:
Column labels, corresponding to individual interrogation results, can also be edited with `replace_names`.
:param replace_names: Edit result names, then merge duplicate entries
:type replace_names: str/dict
If `replace_names` is a string, it is treated as a regex to delete from each name. If `replace_names` is a dict, the value is the regex, and the key is the replacement text:
:Example:
>>> data.edit(replace_names = {r'object': r'[di]obj'})
:Other options:
There are many other miscellaneous options.
:param keep_stats: Keep/drop stats values from dataframe after sorting
:type keep_stats: bool
:param keep_top: After sorting, remove all but the top *keep_top* results
:type keep_top: int
:param just_totals: Sum each column and work with sums
:type just_totals: bool
:param threshold: When using results list as dataframe 2, drop values occurring fewer than n times. If not keywording, you can use:
`'high'`: `denominator total / 2500`
`'medium'`: `denominator total / 5000`
`'low'`: `denominator total / 10000`
If keywording, there are smaller default thresholds
:type threshold: int/bool
:param span_subcorpora: If subcorpora are numerically named, span all from *int* to *int2*, inclusive
:type span_subcorpora: tuple -- `(int, int2)`
:param projection: a to multiply results in subcorpus by n
:type projection: tuple -- `(subcorpus_name, n)`
:param remove_above_p: Delete any result over `p`
:type remove_above_p: bool
:param p: set the p value
:type p: float
:param revert_year: When doing linear regression on years, turn annual subcorpora into 1, 2 ...
:type revert_year: bool
:param print_info: Print stuff to console showing what's being edited
:type print_info: bool
:param spelling: Convert/normalise spelling:
:type spelling: str -- `'US'`/`'UK'`
:param selfdrop: When keywording, try to remove target corpus from reference corpus
:type selfdrop: bool
:param calc_all: When keywording, calculate words that appear in either corpus
:type calc_all: bool
:returns: :class:`corpkit.interrogation.Interrogation`
"""
from editor import editor
return editor(self, *args, **kwargs)
def edit(self, *args, **kwargs):
"""Manipulate results of interrogations.
There are a few overall kinds of edit, most of which can be combined into a single function call. It's useful to keep in mind that many are basic wrappers around `pandas` operations---if you're comfortable with `pandas` syntax, it may be faster at times to use its syntax instead.
:Basic mathematical operations:
First, you can do basic maths on results, optionally passing in some data to serve as the denominator. Very commonly, you'll want to get relative frequencies:
:Example:
>>> data = corpus.interrogate({W: r'^t'})
>>> rel = data.edit('%', SELF)
>>> rel.results
.. to that the then ... toilet tolerant tolerate ton
01 18.50 14.65 14.44 6.20 ... 0.00 0.00 0.11 0.00
02 24.10 14.34 13.73 8.80 ... 0.00 0.00 0.00 0.00
03 17.31 18.01 9.97 7.62 ... 0.00 0.00 0.00 0.00
For the operation, there are a number of possible values, each of which is to be passed in as a `str`:
`+`, `-`, `/`, `*`, `%`: self explanatory
`k`: log likelihood (keywords)
`a`: get distance metric
`d`: get percent difference (alternative approach to keywording)
`SELF` is a very useful shorthand denominator. When used, all editing is performed on the data. The totals are then extracted from the edited data, and used as denominator. If this is not the desired behaviour, however, a more specific `interrogation.results` or `interrogation.totals` branch can be used.
In the example above, `SELF` (or `'self'`) is equivalent to:
:Example:
>>> rel = data.edit('%', data.totals)
:Keeping and skipping data:
There are four keyword arguments that can be used to keep or skip rows or columns in the data:
* `just_entries`
* `just_subcorpora`
* `skip_entries`
* `skip_subcorpora`
Each can accept different input types:
* str: treated as regular expression to match
* list:
* of integers: indices to match
* of strings: entries/subcorpora to match
:Example:
>>> data.edit(just_entries = r'^fr',
... skip_entries = ['free', 'freedom'],
... skip_subcorpora = r'[0-9]')
:Merging data:
There are also keyword arguments for merging entries and subcorpora.
* `merge_entries`
* `merge_subcorpora`
These take a `dict`, with the new name as key and the criteria as value. The criteria can be a str (regex) or wordlist.
:Example:
>>> from dictionaries.wordlists import wordlists
>>> mer = {'Articles': ['the', 'an', 'a'], 'Modals': wordlists.modals}
>>> data.edit(merge_entries = mer)
:Sorting:
The `sort_by` keyword argument takes a `str`, which represents the way the result columns should be ordered.
* `increase`: highest to lowest slope value
* `decrease`: lowest to highest slope value
* `turbulent`: most change in y axis values
* `static`: least change in y axis values
* `total/most`: largest number first
* `infreq/least`: smallest number first
* `name`: alphabetically
:Example:
>>> data.edit(sort_by = 'increase')
:Editing entry text:
Column labels, corresponding to individual interrogation results, can also be edited with `replace_names`.
:param replace_names: Edit result names, then merge duplicate entries
:type replace_names: str/dict
If `replace_names` is a string, it is treated as a regex to delete from each name. If `replace_names` is a dict, the value is the regex, and the key is the replacement text:
:Example:
>>> data.edit(replace_names = {r'object': r'[di]obj'})
:Other options:
There are many other miscellaneous options.
:param keep_stats: Keep/drop stats values from dataframe after sorting
:type keep_stats: bool
:param keep_top: After sorting, remove all but the top *keep_top* results
:type keep_top: int
:param just_totals: Sum each column and work with sums
:type just_totals: bool
:param threshold: When using results list as dataframe 2, drop values occurring fewer than n times. If not keywording, you can use:
`'high'`: `denominator total / 2500`
`'medium'`: `denominator total / 5000`
`'low'`: `denominator total / 10000`
If keywording, there are smaller default thresholds
:type threshold: int/bool
:param span_subcorpora: If subcorpora are numerically named, span all from *int* to *int2*, inclusive
:type span_subcorpora: tuple -- `(int, int2)`
:param projection: a to multiply results in subcorpus by n
:type projection: tuple -- `(subcorpus_name, n)`
:param remove_above_p: Delete any result over `p`
:type remove_above_p: bool
:param p: set the p value
:type p: float
:param revert_year: When doing linear regression on years, turn annual subcorpora into 1, 2 ...
:type revert_year: bool
:param print_info: Print stuff to console showing what's being edited
:type print_info: bool
:param spelling: Convert/normalise spelling:
:type spelling: str -- `'US'`/`'UK'`
:param selfdrop: When keywording, try to remove target corpus from reference corpus
:type selfdrop: bool
:param calc_all: When keywording, calculate words that appear in either corpus
:type calc_all: bool
:returns: :class:`corpkit.interrogation.Interrogation`
"""
from editor import editor
return editor(self, *args, **kwargs)
game.initMenuUI()
while not evenement.event["game"] == 'return':
# ev=donne_evenement()
# if ev[0]!='RAS':
# print(ev)
evenement.compute()
ui.logic(evenement.event["tk"])
#Â home:play
if evenement.event["game"] == 'play':
goInBlack(game.initPlayMenu)
choicePlaystyleMenu()
backInBlack(game.initMenuUI)
#Â home:editor
elif evenement.event["game"] == 'editor':
goInBlack()
editor.editor()
backInBlack(game.initMenuUI)
elif evenement.event["game"] == 'score':
goInBlack()
scoresMenu()
backInBlack(game.initMenuUI)
game.updateTime()
animation.update() # /!\ render.updateAnimations before ui.render
ui.render(game.getFps())
mise_a_jour()
###############################################################################
###############################################################################
def default(mapeditor):
# general things
m = editor(mapeditor)
world = m.look()
points = {}
# terrain
points['-6x-6'] = [-6, -6, 65]
points['-5x-6'] = [-5, -6, 60]
points['-4x-6'] = [-4, -6, -2]
points['-3x-6'] = [-3, -6, -3]
points['-2x-6'] = [-2, -6, -4]
points['-1x-6'] = [-1, -6, -6]
points['0x-6'] = [0, -6, -7]
points['1x-6'] = [1, -6, -8]
points['2x-6'] = [2, -6, -9]
points['3x-6'] = [3, -6, -10]
points['4x-6'] = [4, -6, -12]
points['5x-6'] = [5, -6, -14]
points['6x-6'] = [6, -6, -20]
points['-6x-5'] = [-6, -5, 65.4]
points['-5x-5'] = [-5, -5, 62.1]
points['-4x-5'] = [-4, -5, 4]
points['-3x-5'] = [-3, -5, 3.9]
points['-2x-5'] = [-2, -5, 3.7]
points['-1x-5'] = [-1, -5, 3.8]
points['0x-5'] = [0, -5, 3.6]
points['1x-5'] = [1, -5, 3.2]
points['2x-5'] = [2, -5, 2.5]
points['3x-5'] = [3, -5, 1]
points['4x-5'] = [4, -5, 0]
points['5x-5'] = [5, -5, -3]
points['6x-5'] = [6, -5, -5]
points['-6x-4'] = [-6, -4, 67]
points['-5x-4'] = [-5, -4, 61]
points['-4x-4'] = [-4, -4, 5]
points['-3x-4'] = [-3, -4, 4.9]
points['-2x-4'] = [-2, -4, 4.7]
points['-1x-4'] = [-1, -4, 4.8]
points['0x-4'] = [0, -4, 4.6]
points['1x-4'] = [1, -4, 4.2]
points['2x-4'] = [2, -4, 3.5]
points['3x-4'] = [3, -4, 2]
points['4x-4'] = [4, -4, 1]
points['5x-4'] = [5, -4, 0]
points['6x-4'] = [6, -4, -5]
points['-6x-3'] = [-6, -3, 69]
points['-5x-3'] = [-5, -3, 65]
points['-4x-3'] = [-4, -3, 6]
points['-3x-3'] = [-3, -3, 5.7]
points['-2x-3'] = [-2, -3, 5.6]
points['-1x-3'] = [-1, -3, 5.8]
points['0x-3'] = [0, -3, 5.6]
points['1x-3'] = [1, -3, 5.2]
points['2x-3'] = [2, -3, 4.5]
points['3x-3'] = [3, -3, 4.9]
points['4x-3'] = [4, -3, 4.5]
points['5x-3'] = [5, -3, 3]
points['6x-3'] = [6, -3, 0]
points['-6x-2'] = [-6, -2, 71]
points['-5x-2'] = [-5, -2, 30] # keep
points['-4x-2'] = [-4, -2, 30] # keep
points['-3x-2'] = [-3, -2, 30] # keep
points['-2x-2'] = [-2, -2, -16.8] # center of the lake
points['-1x-2'] = [-1, -2, -3.8] # east side of the lake
points['0x-2'] = [0, -2, 15.8] # east border of the lake
points['1x-2'] = [1, -2, 13]
points['2x-2'] = [2, -2, 10.5]
points['3x-2'] = [3, -2, 7.9]
points['4x-2'] = [4, -2, 6.5]
points['5x-2'] = [5, -2, 5]
points['6x-2'] = [6, -2, -4]
points['-6x-1'] = [-6, -1, 70]
points['-5x-1'] = [-5, -1, 64.6]
points['-4x-1'] = [-4, -1, 30] # keep
points['-3x-1'] = [-3, -1, 30] # keep
points['-2x-1'] = [-2, -1, -2.8] # north part of the lake
points['-1x-1'] = [-1, -1, 12.7] # town
points['0x-1'] = [0, -1, 12.7] # town
points['1x-1'] = [1, -1, 12.5] # town
points['2x-1'] = [2, -1, 14.7]
points['3x-1'] = [3, -1, 15.8]
points['4x-1'] = [4, -1, 11]
points['5x-1'] = [5, -1, 2]
points['6x-1'] = [6, -1, -10]
points['-6x0'] = [-6, 0, 72.4]
points['-5x0'] = [-5, 0, 65.7]
points['-4x0'] = [-4, 0, 30] # keep
points['-3x0'] = [-3, 0, 30] #keep
points['-2x0'] = [-2, 0, 20] # road to the keep (north border of the lake)
points['-1x0'] = [-1, 0, 13.2] # town
points['0x0'] = [0, 0, 12.8] # town
points['1x0'] = [1, 0, 12.5] # town
points['2x0'] = [2, 0, 12]
points['3x0'] = [3, 0, 10.5]
points['4x0'] = [4, 0, 5]
points['5x0'] = [5, 0, 0]
points['6x0'] = [6, 0, -15]
points['-6x1'] = [-6, 1, 75]
points['-5x1'] = [-5, 1, 67.5]
points['-4x1'] = [-4, 1, 15.2]
points['-3x1'] = [-3, 1, 14.6]
points['-2x1'] = [-2, 1, 14.5]
points['-1x1'] = [-1, 1, 13.1] # town
points['0x1'] = [0, 1, 12.9] # town
points['1x1'] = [1, 1, 12.7] # town
points['2x1'] = [2, 1, 12.5]
points['3x1'] = [3, 1, 10.2]
points['4x1'] = [4, 1, 8.9]
points['5x1'] = [5, 1, 4]
points['6x1'] = [6, 1, -9]
points['-6x2'] = [-6, 2, 77]
points['-5x2'] = [-5, 2, 68]
points['-4x2'] = [-4, 2, 13] # mine road
points['-3x2'] = [-3, 2, 55]
points['-2x2'] = [-2, 2, 57.6]
points['-1x2'] = [-1, 2, 14]
points['0x2'] = [0, 2, 20]
points['1x2'] = [1, 2, 14]
points['2x2'] = [2, 2, 22.4]
points['3x2'] = [3, 2, 18]
points['4x2'] = [4, 2, 10.7]
points['5x2'] = [5, 2, 6.4]
points['6x2'] = [6, 2, -4]
points['-6x3'] = [-6, 3, 81.2]
points['-5x3'] = [-5, 3, 66]
points['-4x3'] = [-4, 3, 13.2] # mine road
points['-3x3'] = [-3, 3, 56.4]
points['-2x3'] = [-2, 3, 60]
points['-1x3'] = [-1, 3, 51.1]
points['0x3'] = [0, 3, 19]
points['1x3'] = [1, 3, 25.6]
points['2x3'] = [2, 3, 10]
points['3x3'] = [3, 3, 19.5]
points['4x3'] = [4, 3, 11.3]
points['5x3'] = [5, 3, 7]
points['6x3'] = [6, 3, 0]
points['-6x4'] = [-6, 4, 85]
points['-5x4'] = [-5, 4, 66.7]
points['-4x4'] = [-4, 4, 14.2] # mine road
points['-3x4'] = [-3, 4, 56.4]
points['-2x4'] = [-2, 4, 57]
points['-1x4'] = [-1, 4, 52.5]
points['0x4'] = [0, 4, 31]
points['1x4'] = [1, 4, 15]
points['2x4'] = [2, 4, 26.2]
points['3x4'] = [3, 4, 22.7]
points['4x4'] = [4, 4, 15]
points['5x4'] = [5, 4, 10]
points['6x4'] = [6, 4, -3.5]
points['-6x5'] = [-6, 5, 91]
points['-5x5'] = [-5, 5, 68]
points['-4x5'] = [-4, 5, 65.5]
points['-3x5'] = [-3, 5, 62.2]
points['-2x5'] = [-2, 5, 58]
points['-1x5'] = [-1, 5, 54]
points['0x5'] = [0, 5, 50]
points['1x5'] = [1, 5, 44.4]
points['2x5'] = [2, 5, 45]
points['3x5'] = [3, 5, 38.6]
points['4x5'] = [4, 5, 12]
points['5x5'] = [5, 5, 0]
points['6x5'] = [6, 5, -8.7]
points['-6x6'] = [-6, 6, 100]
points['-5x6'] = [-5, 6, 85]
points['-4x6'] = [-4, 6, 75]
points['-3x6'] = [-3, 6, 70]
points['-2x6'] = [-2, 6, 65]
points['-1x6'] = [-1, 6, 66.7]
points['0x6'] = [0, 6, 65]
points['1x6'] = [1, 6, 64.3]
points['2x6'] = [2, 6, 59.7]
points['3x6'] = [3, 6, 55.3]
points['4x6'] = [4, 6, 46.7]
points['5x6'] = [5, 6, 12]
points['6x6'] = [6, 6, -5.8]
m.set(world.id, terrain={'points': points}, name="moraf")
# a wall around the world
m.make('boundary',
type='boundary',
xyz=(-384, -384, town_height),
bbox=[2, 514, 256])
m.make('boundary',
type='boundary',
xyz=(-384, -384, town_height),
bbox=[514, 2, 256])
m.make('boundary',
type='boundary',
xyz=(-384, 384, town_height),
bbox=[514, 2, 256])
m.make('boundary',
type='boundary',
xyz=(384, -384, town_height),
bbox=[2, 514, 256])
# paths
statue_path_area = {
'points': [[5, 0], [4.33, 2.5], [2.5, 4.33], [0, 5], [-2.5, 4.33],
[-4.33, 2.5], [-5, 0], [-4.33, -2.5], [-2.5, -4.33],
[0, -5.0], [2.5, -4.33], [4.33, -2.5], [5.0, 0]],
'layer':
7
}
m.make('statue path',
type='path',
xyz=(0, 0, town_height),
area=statue_path_area,
bbox=[-5, -5, 0, 5, 5, 1])
town_path_area = {
'points': [[50, 0], [43.30, 25], [25, 43.30], [0, 50], [-25, 43.30],
[-43.30, 25], [-50, 0], [-43.30, -25], [-25, -43.30],
[0, -50], [25, -43.30], [43.30, -25], [50, -0.01],
[60, -0.01], [51.96, -30], [30, -51.96], [0, -60],
[-30, -51.96], [-51.96, -30], [-60, 0], [-51.96, 30],
[-30, 51.96], [0, 60], [30, 51.96], [51.96, 30], [60, 0]],
'layer':
7
}
m.make('town path',
type='path',
xyz=(0, 0, town_height),
area=town_path_area,
bbox=[-38, -62, 0, 169, 154, 1])
m.make('fir', type='fir', xyz=(0, 0, town_height))
m.make('fir', type='fir', xyz=(64, 0, 10))
m.make('fir', type='fir', xyz=(128, 0, 10))
m.make('fir', type='fir', xyz=(192, 0, 10))
m.make('fir', type='fir', xyz=(256, 0, 10))
m.make('fir', type='fir', xyz=(320, 0, 10))
# animals
chickens = []
xbase = 0
ybase = 0
for i in range(0, 10):
xpos = xbase + uniform(-10, 10)
ypos = ybase + uniform(-10, 10)
d = m.make('chicken', type='chicken', xyz=(xpos, ypos, town_height))
chickens.append(d)
m.learn(chickens, chicken_goals)
dog = m.make('toby', type='dog', xyz=(5, 5, town_height))
m.learn(dog, dog_goals)
m.know(dog, tr_knowledge)
m.tell_importance(dog, il.hunt, '>', il.patrol)
m.tell_importance(dog, il.hunt, '>', il.forage)
m.tell_importance(dog, il.forage, '>', il.patrol)
# TEST: calling sub.methods
create_town_buildings(mapeditor)
if ('simulation' in sys.argv): modules.append('simulation')
if ('analysis' in sys.argv): modules.append('analysis')
if ('editor' in sys.argv): modules.append('editor')
if ('speed' in sys.argv): modules.append('speed')
ut.logo()
if len(modules) == 0:
modules = (input(
' Please enter desired modules to run (SIMULATION and/or ANALYSIS or EDITOR): '
).lower()).split()
if ('-input' in sys.argv):
input_file_name = current_dir + '/' + sys.argv[sys.argv.index('-input') +
1]
else:
input_file_name = False
if ('simulation' in modules):
from simulation import simulation
simulation(current_dir, input_file_name)
if ('analysis' in modules):
from analysis import analysis
analysis(current_dir, input_file_name)
if ('editor' in modules):
from editor import editor
editor(current_dir, input_file_name)
if ('speed' in modules):
from simulation import speed_test
speed_test(current_dir, input_file_name)
#! /usr/bin/env python
import sys
import os
try:
__file__
except NameError:
pass
else:
libdir = os.path.abspath(os.path.join(os.path.dirname(__file__), 'lib'))
sys.path.insert(0, libdir)
import editor
editor.editor()
def initeditor(self):
self.editor = editor.editor()
def setupUi(self, MainWindow):
MainWindow.setObjectName(_fromUtf8("MainWindow"))
MainWindow.resize(989, 449)
MainWindow.setWindowTitle(QtGui.QApplication.translate("MainWindow", "Shot Manager", None, QtGui.QApplication.UnicodeUTF8))
icon = QtGui.QIcon()
icon.addPixmap(QtGui.QPixmap(_fromUtf8(":/todo.svg")), QtGui.QIcon.Normal, QtGui.QIcon.Off)
MainWindow.setWindowIcon(icon)
MainWindow.setDocumentMode(False)
self.centralwidget = QtGui.QWidget(MainWindow)
self.centralwidget.setObjectName(_fromUtf8("centralwidget"))
self.verticalLayout_2 = QtGui.QVBoxLayout(self.centralwidget)
self.verticalLayout_2.setMargin(3)
self.verticalLayout_2.setObjectName(_fromUtf8("verticalLayout_2"))
self.splitter = QtGui.QSplitter(self.centralwidget)
self.splitter.setFrameShape(QtGui.QFrame.StyledPanel)
self.splitter.setLineWidth(4)
self.splitter.setOrientation(QtCore.Qt.Horizontal)
self.splitter.setOpaqueResize(False)
self.splitter.setHandleWidth(10)
self.splitter.setChildrenCollapsible(True)
self.splitter.setObjectName(_fromUtf8("splitter"))
self.widget = QtGui.QWidget(self.splitter)
self.widget.setObjectName(_fromUtf8("widget"))
self.verticalLayout_3 = QtGui.QVBoxLayout(self.widget)
self.verticalLayout_3.setMargin(2)
self.verticalLayout_3.setMargin(0)
self.verticalLayout_3.setObjectName(_fromUtf8("verticalLayout_3"))
self.frame = QtGui.QFrame(self.widget)
self.frame.setMaximumSize(QtCore.QSize(16777215, 30))
self.frame.setFrameShape(QtGui.QFrame.Panel)
self.frame.setFrameShadow(QtGui.QFrame.Raised)
self.frame.setLineWidth(1)
self.frame.setMidLineWidth(1)
self.frame.setObjectName(_fromUtf8("frame"))
self.verticalLayout_4 = QtGui.QVBoxLayout(self.frame)
self.verticalLayout_4.setSpacing(1)
self.verticalLayout_4.setMargin(1)
self.verticalLayout_4.setObjectName(_fromUtf8("verticalLayout_4"))
self.gridLayout = QtGui.QGridLayout()
self.gridLayout.setSizeConstraint(QtGui.QLayout.SetDefaultConstraint)
self.gridLayout.setVerticalSpacing(5)
self.gridLayout.setObjectName(_fromUtf8("gridLayout"))
self.ProjectComboBox = QtGui.QComboBox(self.frame)
self.ProjectComboBox.setEditable(False)
self.ProjectComboBox.setFrame(False)
self.ProjectComboBox.setObjectName(_fromUtf8("ProjectComboBox"))
self.gridLayout.addWidget(self.ProjectComboBox, 0, 1, 1, 1)
self.SequComboBox = QtGui.QComboBox(self.frame)
self.SequComboBox.setMaximumSize(QtCore.QSize(748, 16777215))
self.SequComboBox.setObjectName(_fromUtf8("SequComboBox"))
self.gridLayout.addWidget(self.SequComboBox, 0, 4, 1, 1)
self.label = QtGui.QLabel(self.frame)
self.label.setText(QtGui.QApplication.translate("MainWindow", "Select Project", None, QtGui.QApplication.UnicodeUTF8))
self.label.setObjectName(_fromUtf8("label"))
self.gridLayout.addWidget(self.label, 0, 0, 1, 1)
self.label_2 = QtGui.QLabel(self.frame)
self.label_2.setText(QtGui.QApplication.translate("MainWindow", "Select Sequence", None, QtGui.QApplication.UnicodeUTF8))
self.label_2.setObjectName(_fromUtf8("label_2"))
self.gridLayout.addWidget(self.label_2, 0, 3, 1, 1)
self.frame_2 = QtGui.QFrame(self.frame)
self.frame_2.setFrameShape(QtGui.QFrame.StyledPanel)
self.frame_2.setFrameShadow(QtGui.QFrame.Raised)
self.frame_2.setObjectName(_fromUtf8("frame_2"))
self.gridLayout.addWidget(self.frame_2, 0, 5, 1, 1)
spacerItem = QtGui.QSpacerItem(20, 40, QtGui.QSizePolicy.Minimum, QtGui.QSizePolicy.Expanding)
self.gridLayout.addItem(spacerItem, 0, 2, 1, 1)
self.gridLayout.setColumnMinimumWidth(1, 50)
self.gridLayout.setColumnMinimumWidth(4, 50)
self.gridLayout.setColumnMinimumWidth(5, 300)
self.verticalLayout_4.addLayout(self.gridLayout)
self.verticalLayout_3.addWidget(self.frame)
self.list = QtGui.QTreeWidget(self.widget)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.QSizePolicy.Expanding)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.list.sizePolicy().hasHeightForWidth())
self.list.setSizePolicy(sizePolicy)
self.list.setMinimumSize(QtCore.QSize(400, 0))
self.list.setFrameShape(QtGui.QFrame.StyledPanel)
self.list.setFrameShadow(QtGui.QFrame.Plain)
self.list.setLineWidth(0)
self.list.setAutoScroll(False)
self.list.setTabKeyNavigation(False)
self.list.setAlternatingRowColors(True)
self.list.setRootIsDecorated(True)
self.list.setUniformRowHeights(True)
self.list.setAnimated(True)
self.list.setAllColumnsShowFocus(False)
self.list.setWordWrap(True)
self.list.setExpandsOnDoubleClick(False)
self.list.setObjectName(_fromUtf8("list"))
self.list.headerItem().setText(0, QtGui.QApplication.translate("MainWindow", "Shot", None, QtGui.QApplication.UnicodeUTF8))
self.list.headerItem().setText(1, QtGui.QApplication.translate("MainWindow", "In", None, QtGui.QApplication.UnicodeUTF8))
self.list.headerItem().setText(2, QtGui.QApplication.translate("MainWindow", "Out", None, QtGui.QApplication.UnicodeUTF8))
self.list.headerItem().setText(3, QtGui.QApplication.translate("MainWindow", "CutIn", None, QtGui.QApplication.UnicodeUTF8))
self.list.headerItem().setText(4, QtGui.QApplication.translate("MainWindow", "CutOut", None, QtGui.QApplication.UnicodeUTF8))
self.list.headerItem().setText(5, QtGui.QApplication.translate("MainWindow", "Status", None, QtGui.QApplication.UnicodeUTF8))
self.list.header().setCascadingSectionResizes(False)
self.list.header().setDefaultSectionSize(50)
self.list.header().setHighlightSections(True)
self.list.header().setMinimumSectionSize(40)
self.list.header().setStretchLastSection(True)
self.verticalLayout_3.addWidget(self.list)
self.editor = editor(self.splitter)
self.editor.setEnabled(False)
self.editor.setMaximumSize(QtCore.QSize(500, 16777215))
self.editor.setObjectName(_fromUtf8("editor"))
self.verticalLayout_2.addWidget(self.splitter)
MainWindow.setCentralWidget(self.centralwidget)
self.toolBar = QtGui.QToolBar(MainWindow)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Minimum)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.toolBar.sizePolicy().hasHeightForWidth())
self.toolBar.setSizePolicy(sizePolicy)
self.toolBar.setMinimumSize(QtCore.QSize(0, 30))
self.toolBar.setWindowTitle(QtGui.QApplication.translate("MainWindow", "toolBar", None, QtGui.QApplication.UnicodeUTF8))
self.toolBar.setObjectName(_fromUtf8("toolBar"))
MainWindow.addToolBar(QtCore.Qt.TopToolBarArea, self.toolBar)
self.actionDelete_Task = QtGui.QAction(MainWindow)
self.actionDelete_Task.setEnabled(False)
self.actionDelete_Task.setText(QtGui.QApplication.translate("MainWindow", "Delete Shot", None, QtGui.QApplication.UnicodeUTF8))
self.actionDelete_Task.setShortcut(QtGui.QApplication.translate("MainWindow", "Del", None, QtGui.QApplication.UnicodeUTF8))
self.actionDelete_Task.setObjectName(_fromUtf8("actionDelete_Task"))
self.actionNew_Task = QtGui.QAction(MainWindow)
self.actionNew_Task.setEnabled(False)
self.actionNew_Task.setText(QtGui.QApplication.translate("MainWindow", "New Shot", None, QtGui.QApplication.UnicodeUTF8))
self.actionNew_Task.setObjectName(_fromUtf8("actionNew_Task"))
self.actionUpdate_database = QtGui.QAction(MainWindow)
self.actionUpdate_database.setEnabled(False)
self.actionUpdate_database.setText(QtGui.QApplication.translate("MainWindow", "Update Database", None, QtGui.QApplication.UnicodeUTF8))
self.actionUpdate_database.setObjectName(_fromUtf8("actionUpdate_database"))
self.actionEdit = QtGui.QAction(MainWindow)
self.actionEdit.setCheckable(True)
self.actionEdit.setText(QtGui.QApplication.translate("MainWindow", "Edit", None, QtGui.QApplication.UnicodeUTF8))
self.actionEdit.setObjectName(_fromUtf8("actionEdit"))
self.actionNew_Sequence = QtGui.QAction(MainWindow)
self.actionNew_Sequence.setEnabled(False)
self.actionNew_Sequence.setText(QtGui.QApplication.translate("MainWindow", "New Sequence", None, QtGui.QApplication.UnicodeUTF8))
self.actionNew_Sequence.setObjectName(_fromUtf8("actionNew_Sequence"))
self.actionSet_project = QtGui.QAction(MainWindow)
self.actionSet_project.setText(QtGui.QApplication.translate("MainWindow", "set Environment", None, QtGui.QApplication.UnicodeUTF8))
self.actionSet_project.setObjectName(_fromUtf8("actionSet_project"))
self.toolBar.addSeparator()
self.toolBar.addAction(self.actionSet_project)
self.toolBar.addAction(self.actionEdit)
self.toolBar.addSeparator()
self.toolBar.addSeparator()
self.toolBar.addAction(self.actionNew_Sequence)
self.toolBar.addAction(self.actionNew_Task)
self.toolBar.addAction(self.actionUpdate_database)
self.toolBar.addAction(self.actionDelete_Task)
self.toolBar.addSeparator()
self.retranslateUi(MainWindow)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
def edit(self, *args, **kwargs):
from editor import editor
return editor(self, *args, **kwargs)
def default(mapeditor):
# general things
m=editor(mapeditor)
world=m.look()
points = { }
# terrain
points['-6x-6'] = [-6, -6, 65]
points['-5x-6'] = [-5, -6, 60]
points['-4x-6'] = [-4, -6, -2]
points['-3x-6'] = [-3, -6, -3]
points['-2x-6'] = [-2, -6, -4]
points['-1x-6'] = [-1, -6, -6]
points['0x-6'] = [0, -6, -7]
points['1x-6'] = [1, -6, -8]
points['2x-6'] = [2, -6, -9]
points['3x-6'] = [3, -6, -10]
points['4x-6'] = [4, -6, -12]
points['5x-6'] = [5, -6, -14]
points['6x-6'] = [6, -6, -20]
points['-6x-5'] = [-6, -5, 65.4]
points['-5x-5'] = [-5, -5, 62.1]
points['-4x-5'] = [-4, -5, 4]
points['-3x-5'] = [-3, -5, 3.9]
points['-2x-5'] = [-2, -5, 3.7]
points['-1x-5'] = [-1, -5, 3.8]
points['0x-5'] = [0, -5, 3.6]
points['1x-5'] = [1, -5, 3.2]
points['2x-5'] = [2, -5, 2.5]
points['3x-5'] = [3, -5, 1]
points['4x-5'] = [4, -5, 0]
points['5x-5'] = [5, -5, -3]
points['6x-5'] = [6, -5, -5]
points['-6x-4'] = [-6, -4, 67]
points['-5x-4'] = [-5, -4, 61]
points['-4x-4'] = [-4, -4, 5]
points['-3x-4'] = [-3, -4, 4.9]
points['-2x-4'] = [-2, -4, 4.7]
points['-1x-4'] = [-1, -4, 4.8]
points['0x-4'] = [0, -4, 4.6]
points['1x-4'] = [1, -4, 4.2]
points['2x-4'] = [2, -4, 3.5]
points['3x-4'] = [3, -4, 2]
points['4x-4'] = [4, -4, 1]
points['5x-4'] = [5, -4, 0]
points['6x-4'] = [6, -4, -5]
points['-6x-3'] = [-6, -3, 69]
points['-5x-3'] = [-5, -3, 65]
points['-4x-3'] = [-4, -3, 6]
points['-3x-3'] = [-3, -3, 5.7]
points['-2x-3'] = [-2, -3, 5.6]
points['-1x-3'] = [-1, -3, 5.8]
points['0x-3'] = [0, -3, 5.6]
points['1x-3'] = [1, -3, 5.2]
points['2x-3'] = [2, -3, 4.5]
points['3x-3'] = [3, -3, 4.9]
points['4x-3'] = [4, -3, 4.5]
points['5x-3'] = [5, -3, 3]
points['6x-3'] = [6, -3, 0]
points['-6x-2'] = [-6, -2, 71]
points['-5x-2'] = [-5, -2, 30] # keep
points['-4x-2'] = [-4, -2, 30] # keep
points['-3x-2'] = [-3, -2, 30] # keep
points['-2x-2'] = [-2, -2, -16.8] # center of the lake
points['-1x-2'] = [-1, -2, -3.8] # east side of the lake
points['0x-2'] = [0, -2, 15.8] # east border of the lake
points['1x-2'] = [1, -2, 13]
points['2x-2'] = [2, -2, 10.5]
points['3x-2'] = [3, -2, 7.9]
points['4x-2'] = [4, -2, 6.5]
points['5x-2'] = [5, -2, 5]
points['6x-2'] = [6, -2, -4]
points['-6x-1'] = [-6, -1, 70]
points['-5x-1'] = [-5, -1, 64.6]
points['-4x-1'] = [-4, -1, 30] # keep
points['-3x-1'] = [-3, -1, 30] # keep
points['-2x-1'] = [-2, -1, -2.8] # north part of the lake
points['-1x-1'] = [-1, -1, 12.7] # town
points['0x-1'] = [0, -1, 12.7] # town
points['1x-1'] = [1, -1, 12.5] # town
points['2x-1'] = [2, -1, 14.7]
points['3x-1'] = [3, -1, 15.8]
points['4x-1'] = [4, -1, 11]
points['5x-1'] = [5, -1, 2]
points['6x-1'] = [6, -1, -10]
points['-6x0'] = [-6, 0, 72.4]
points['-5x0'] = [-5, 0, 65.7]
points['-4x0'] = [-4, 0, 30] # keep
points['-3x0'] = [-3, 0, 30] #keep
points['-2x0'] = [-2, 0, 20] # road to the keep (north border of the lake)
points['-1x0'] = [-1, 0, 13.2] # town
points['0x0'] = [0, 0, 12.8] # town
points['1x0'] = [1, 0, 12.5] # town
points['2x0'] = [2, 0, 12]
points['3x0'] = [3, 0, 10.5]
points['4x0'] = [4, 0, 5]
points['5x0'] = [5, 0, 0]
points['6x0'] = [6, 0, -15]
points['-6x1'] = [-6, 1, 75]
points['-5x1'] = [-5, 1, 67.5]
points['-4x1'] = [-4, 1, 15.2]
points['-3x1'] = [-3, 1, 14.6]
points['-2x1'] = [-2, 1, 14.5]
points['-1x1'] = [-1, 1, 13.1] # town
points['0x1'] = [0, 1, 12.9] # town
points['1x1'] = [1, 1, 12.7] # town
points['2x1'] = [2, 1, 12.5]
points['3x1'] = [3, 1, 10.2]
points['4x1'] = [4, 1, 8.9]
points['5x1'] = [5, 1, 4]
points['6x1'] = [6, 1, -9]
points['-6x2'] = [-6, 2, 77]
points['-5x2'] = [-5, 2, 68]
points['-4x2'] = [-4, 2, 13] # mine road
points['-3x2'] = [-3, 2, 55]
points['-2x2'] = [-2, 2, 57.6]
points['-1x2'] = [-1, 2, 14]
points['0x2'] = [0, 2, 20]
points['1x2'] = [1, 2, 14]
points['2x2'] = [2, 2, 22.4]
points['3x2'] = [3, 2, 18]
points['4x2'] = [4, 2, 10.7]
points['5x2'] = [5, 2, 6.4]
points['6x2'] = [6, 2, -4]
points['-6x3'] = [-6, 3, 81.2]
points['-5x3'] = [-5, 3, 66]
points['-4x3'] = [-4, 3, 13.2] # mine road
points['-3x3'] = [-3, 3, 56.4]
points['-2x3'] = [-2, 3, 60]
points['-1x3'] = [-1, 3, 51.1]
points['0x3'] = [0, 3, 19]
points['1x3'] = [1, 3, 25.6]
points['2x3'] = [2, 3, 10]
points['3x3'] = [3, 3, 19.5]
points['4x3'] = [4, 3, 11.3]
points['5x3'] = [5, 3, 7]
points['6x3'] = [6, 3, 0]
points['-6x4'] = [-6, 4, 85]
points['-5x4'] = [-5, 4, 66.7]
points['-4x4'] = [-4, 4, 14.2] # mine road
points['-3x4'] = [-3, 4, 56.4]
points['-2x4'] = [-2, 4, 57]
points['-1x4'] = [-1, 4, 52.5]
points['0x4'] = [0, 4, 31]
points['1x4'] = [1, 4, 15]
points['2x4'] = [2, 4, 26.2]
points['3x4'] = [3, 4, 22.7]
points['4x4'] = [4, 4, 15]
points['5x4'] = [5, 4, 10]
points['6x4'] = [6, 4, -3.5]
points['-6x5'] = [-6, 5, 91]
points['-5x5'] = [-5, 5, 68]
points['-4x5'] = [-4, 5, 65.5]
points['-3x5'] = [-3, 5, 62.2]
points['-2x5'] = [-2, 5, 58]
points['-1x5'] = [-1, 5, 54]
points['0x5'] = [0, 5, 50]
points['1x5'] = [1, 5, 44.4]
points['2x5'] = [2, 5, 45]
points['3x5'] = [3, 5, 38.6]
points['4x5'] = [4, 5, 12]
points['5x5'] = [5, 5, 0]
points['6x5'] = [6, 5, -8.7]
points['-6x6'] = [-6, 6, 100]
points['-5x6'] = [-5, 6, 85]
points['-4x6'] = [-4, 6, 75]
points['-3x6'] = [-3, 6, 70]
points['-2x6'] = [-2, 6, 65]
points['-1x6'] = [-1, 6, 66.7]
points['0x6'] = [0, 6, 65]
points['1x6'] = [1, 6, 64.3]
points['2x6'] = [2, 6, 59.7]
points['3x6'] = [3, 6, 55.3]
points['4x6'] = [4, 6, 46.7]
points['5x6'] = [5, 6, 12]
points['6x6'] = [6, 6, -5.8]
m.set(world.id, terrain={'points' : points}, name="moraf")
# a wall around the world
m.make('boundary',type='boundary',xyz=(-384,-384,town_height),bbox=[2,514,256])
m.make('boundary',type='boundary',xyz=(-384,-384,town_height),bbox=[514,2,256])
m.make('boundary',type='boundary',xyz=(-384, 384,town_height),bbox=[514,2,256])
m.make('boundary',type='boundary',xyz=(384,-384,town_height),bbox=[2,514,256])
# paths
statue_path_area={'points' : [ [5,0], [4.33,2.5], [2.5,4.33], [0,5], [-2.5, 4.33], [-4.33,2.5], [-5,0], [-4.33,-2.5], [-2.5,-4.33], [0,-5.0], [2.5,-4.33], [4.33,-2.5], [5.0,0] ], 'layer' : 7}
m.make('statue path',type='path',xyz=(0, 0, town_height), area=statue_path_area,bbox=[-5,-5,0,5,5,1])
town_path_area={'points' : [ [50,0], [43.30,25], [25,43.30], [0,50], [-25, 43.30], [-43.30,25], [-50,0], [-43.30,-25], [-25, -43.30], [0, -50], [25,-43.30], [43.30,-25], [50,-0.01], [60,-0.01], [51.96,-30], [30,-51.96], [0, -60], [-30,-51.96], [-51.96,-30], [-60,0], [-51.96,30], [-30,51.96], [0,60], [30,51.96], [51.96,30], [60,0] ], 'layer' : 7}
m.make('town path',type='path',xyz=(0, 0, town_height), area=town_path_area,bbox=[-38,-62,0,169,154,1])
m.make('fir',type='fir',xyz=(0,0,town_height))
m.make('fir',type='fir',xyz=(64,0,10))
m.make('fir',type='fir',xyz=(128,0,10))
m.make('fir',type='fir',xyz=(192,0,10))
m.make('fir',type='fir',xyz=(256,0,10))
m.make('fir',type='fir',xyz=(320,0,10))
# animals
chickens=[]
xbase = 0;
ybase = 0;
for i in range(0,10):
xpos = xbase + uniform(-10,10)
ypos = ybase + uniform(-10,10)
d=m.make('chicken', type='chicken', xyz=(xpos, ypos, town_height))
chickens.append(d)
m.learn(chickens,chicken_goals)
dog = m.make('toby',type='dog',xyz=(5,5,town_height))
m.learn(dog,dog_goals)
m.know(dog,tr_knowledge)
m.tell_importance(dog,il.hunt,'>',il.patrol)
m.tell_importance(dog,il.hunt,'>',il.forage)
m.tell_importance(dog,il.forage,'>',il.patrol)
# TEST: calling sub.methods
create_town_buildings(mapeditor)
import os
import sys
cwd = os.getcwd()
sys.path.append( cwd + "/lib" )
import dbclient
import crypto
import editor
count = 1
def test( test, result ) :
global count
print( "Test %d : \t%s\t\t - %s" %( count, test, "passed" if result else "failed" ) )
count = count + 1
dbc = dbclient.dbclient( os.getcwd() + "/my_test_database.db" )
cryptographer = crypto.crypto( "baby steps" )
text = "Mary had a little lamb"
cyphertext = cryptographer.encrypt( text )
edit = editor.editor()
test( "database connectivity test", dbc != None )
test( "encryption test", text == cryptographer.decrypt( cyphertext ) )
test( "editor test", "abc\ndef\n" == edit.edit( "abc" ) )
def editor(): # tool editor function
from ascci import rabbit
from editor import editor
from keydetect import keydetect
from lwsystem import osuser
from creds import creds
from menu import MENU
liste = []
os.system("clear")
print ("translate a ducky script keyboard keys into a keyboard keys adapted to the web interface of P4wnP1 A.L.O.A.\n\nput a ducky script keyboard keys and press enter to add another ducky script,\npress" +"\x1b[0;31m" + " CTRL c " + "\x1b[0m" + "when you are finish\n\nESC, GUI r, ENTER, STRING, REM, ALT, CTRL, TAB, LEFT, RIGHT, UP, DOWN, F1, F2, DELETE, CAPSLOCK, NUMLOCK, HOME, END, BREAK \n") #\n\n========================\npress ENTER for continue\n========================\n")
while 1== 1:
try:
liste.append(raw_input("\x1b[0m"+""))
except KeyboardInterrupt:
print("\n")
for l in liste:
if l == "GUI r": # GUI r
print('press(\"GUI r\")') # press("GUI r")
elif l[:3] == "REM": # REM
print "//"+str(l[3:]) # //
elif l[:5] == "DELAY": # DELAY
print "delay("+str(l[6:])+str(")") # delay()
elif l[:6] == "STRING": # STRING
print "type(\""+str(l[7:])+str("\")") # type("")
elif l == "ENTER": # ENTER
print "press(\"ENTER\")" # type("\n") or press("ENTER")
elif l == "SHIFT": # SHIFT
print "press(\"SHIFT\")" # press("SHIFT")
elif l == "ALT": # ALT
print "press(\"ALT\")" # press("ALT")
elif l == "CAPSLOCK": # CAPSLOCK
print "press(\"CAPSLOCK\")" # press("CAPSLOCK")
elif l == "NUMLOCK": # NUMLOCK
print "press(\"NUMLOCK\")" # press("NUMLOCK")
elif l == "HOME": # HOME
print "press(\"HOME\")" # press("HOME")
elif l == "END": # END
print "press(\"END\")" # press("END")
elif l == "CTRL": # CTRL
print "press(\"CTRL\")" # press("CTRL")
elif l == "ESC": # ESC or ESCAPE
print "press(\"ESC\")" # press("ESC")
elif l == "ESCAPE": # ESC or ESCAPE
print "press(\"ESC\")" # press("ESC")
elif l == "TAB": # TAB
print "press(\"TAB\")" # press("TAB")
elif l == "BREAK": # BREAK
print "press(\"BREAK\")" # press("BREAK")
elif l == "DELETE": # DELETE
print "press(\"DELETE\")" # press("DELETE")
elif l == "UP": # UP
print "press(\"UP\")" #press("UP")
elif l == "UPARROW": # UPARROW
print "press(\"UP\")" # press("UP")
elif l == "DOWN": #DOWN
print "press(\"DOWN\")" #press("DOWN")
elif l == "DOWNARROW": # DOWNARROW
print "press(\"DOWN\")" # press("DOWN")
elif l == "RIGHT": # RIGHT
print "press(\"RIGHT\")" # press("RIGHT")
elif l == "RIGHTARROW": # RIGHTARROW
print "press(\"RIGHT\")" # press("RIGHT")
elif l == "LEFTARROW": # LEFTARROW
print "press(\"LEFT\")" # press("LEFT")
elif l == "LEFT": # LEFT
print "press(\"LEFT\")" # press("LEFT")
elif l == "F1": # F1
print "press(\"F1\")" # press("F1")
elif l == "F2": # F2
print "press(\"F2\")"
elif l == "F3": # F3
print "press(\"F3\")"
elif l == "F4": # F4
print "press(\"F4\")"
elif l == "F5": # F5
print "press(\"F5\")"
elif l == "F6": # F6
print "press(\"F6\")"
elif l == "F7": # F7
print "press(\"F7\")"
elif l == "F8": # F8
print "press(\"F8\")"
elif l == "F9": # F9
print "press(\"F9\")"
elif l == "F10": # F10
print "press(\"F10\")"
elif l == "F11": # F11
print "press(\"F11\")"
elif l == "F12": # F12
print "press(\"F12\")"
menu = raw_input("\n\n\nWhat do you want now ?\n\n1) convert another\n2) back to menu\n3) exit\n\n> ") # second menu
if menu == "1":
editor()
elif menu == "2":
os.system("clear")
MENU()
elif menu == "3":
rabbit()
exit()
break
def setupUi(self, MainWindow):
MainWindow.setObjectName(_fromUtf8("MainWindow"))
MainWindow.resize(340, 464)
icon = QtGui.QIcon()
icon.addPixmap(QtGui.QPixmap(_fromUtf8(":/todo.svg")), QtGui.QIcon.Normal, QtGui.QIcon.Off)
MainWindow.setWindowIcon(icon)
self.centralwidget = QtGui.QWidget(MainWindow)
self.centralwidget.setObjectName(_fromUtf8("centralwidget"))
self.verticalLayout = QtGui.QVBoxLayout(self.centralwidget)
self.verticalLayout.setObjectName(_fromUtf8("verticalLayout"))
self.splitter = QtGui.QSplitter(self.centralwidget)
self.splitter.setOrientation(QtCore.Qt.Vertical)
self.splitter.setObjectName(_fromUtf8("splitter"))
self.list = QtGui.QTreeWidget(self.splitter)
self.list.setAlternatingRowColors(True)
self.list.setRootIsDecorated(False)
self.list.setUniformRowHeights(True)
self.list.setAllColumnsShowFocus(True)
self.list.setObjectName(_fromUtf8("list"))
self.editor = editor(self.splitter)
self.editor.setEnabled(True)
self.editor.setObjectName(_fromUtf8("editor"))
self.verticalLayout.addWidget(self.splitter)
MainWindow.setCentralWidget(self.centralwidget)
self.menubar = QtGui.QMenuBar(MainWindow)
self.menubar.setGeometry(QtCore.QRect(0, 0, 340, 27))
self.menubar.setObjectName(_fromUtf8("menubar"))
self.menuTask = QtGui.QMenu(self.menubar)
self.menuTask.setObjectName(_fromUtf8("menuTask"))
MainWindow.setMenuBar(self.menubar)
self.toolBar = QtGui.QToolBar(MainWindow)
self.toolBar.setObjectName(_fromUtf8("toolBar"))
MainWindow.addToolBar(QtCore.Qt.TopToolBarArea, self.toolBar)
self.actionDelete_Task = QtGui.QAction(MainWindow)
self.actionDelete_Task.setEnabled(False)
icon1 = QtGui.QIcon()
icon1.addPixmap(QtGui.QPixmap(_fromUtf8(":/delete.svg")), QtGui.QIcon.Normal, QtGui.QIcon.Off)
self.actionDelete_Task.setIcon(icon1)
self.actionDelete_Task.setObjectName(_fromUtf8("actionDelete_Task"))
self.actionNew_Task = QtGui.QAction(MainWindow)
icon2 = QtGui.QIcon()
icon2.addPixmap(QtGui.QPixmap(_fromUtf8(":/filenew.svg")), QtGui.QIcon.Normal, QtGui.QIcon.Off)
self.actionNew_Task.setIcon(icon2)
self.actionNew_Task.setObjectName(_fromUtf8("actionNew_Task"))
self.actionEdit_Task = QtGui.QAction(MainWindow)
self.actionEdit_Task.setChecked(False)
self.actionEdit_Task.setEnabled(False)
icon3 = QtGui.QIcon()
icon3.addPixmap(QtGui.QPixmap(_fromUtf8(":/edit.svg")), QtGui.QIcon.Normal, QtGui.QIcon.Off)
self.actionEdit_Task.setIcon(icon3)
self.actionEdit_Task.setObjectName(_fromUtf8("actionEdit_Task"))
self.menuTask.addAction(self.actionNew_Task)
self.menuTask.addAction(self.actionEdit_Task)
self.menuTask.addSeparator()
self.menuTask.addAction(self.actionDelete_Task)
self.menubar.addAction(self.menuTask.menuAction())
self.toolBar.addAction(self.actionNew_Task)
self.toolBar.addAction(self.actionEdit_Task)
self.toolBar.addSeparator()
self.toolBar.addAction(self.actionDelete_Task)
self.retranslateUi(MainWindow)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
def editor(interrogation,
operation = None,
denominator = False,
sort_by = False,
keep_stats = False,
keep_top = False,
just_totals = False,
threshold = 'medium',
just_entries = False,
skip_entries = False,
merge_entries = False,
newname = 'combine',
multiple_merge = False,
just_subcorpora = False,
skip_subcorpora = False,
span_subcorpora = False,
merge_subcorpora = False,
new_subcorpus_name = False,
replace_names = False,
projection = False,
remove_above_p = False,
p = 0.05,
revert_year = True,
print_info = True,
spelling = False,
selfdrop = True,
calc_all = True,
**kwargs
):
"""Edit results of interrogations, do keywording, sort, etc.
``just/skip_entries`` and ``just/skip_subcorpora`` can take a few different kinds of input:
* str: treated as regular expression to match
* list:
* of integers: indices to match
* of strings: entries/subcorpora to match
``merge_entries`` and ``merge_subcorpora``, however, are best entered as dicts:
``{newname: criteria, newname2: criteria2}```
where criteria is a string, list, etc.
:param interrogation: Results to edit
:type interrogation: pandas.core.frame.DataFrame
:param operation: Kind of maths to do on inputted lists:
'+', '-', '/', '*', '%': self explanatory
'k': log likelihood (keywords)
'a': get distance metric (for use with interrogator 'a' option)
'd': get percent difference (alternative approach to keywording)
:type operation: str
:param denominator: List of results or totals.
If list of results, for each entry in dataframe 1, locate
entry with same name in dataframe 2, and do maths there
if 'self', do all merging/keeping operations, then use
edited interrogation as denominator
:type denominator: pandas.core.series.Series/pandas.core.frame.DataFrame/dict/'self'
:param sort_by: Calculate slope, stderr, r, p values, then sort by:
increase: highest to lowest slope value
decrease: lowest to highest slope value
turbulent: most change in y axis values
static: least change in y axis values
total/most: largest number first
infreq/least: smallest number first
name: alphabetically
:type sort_by: str
:param keep_stats: Keep/drop stats values from dataframe after sorting
:type keep_stats: bool
:param keep_top: After sorting, remove all but the top *keep_top* results
:type keep_top: int
:param just_totals: Sum each column and work with sums
:type just_totals: bool
:param threshold: When using results list as denominator, drop values occurring
fewer than n times. If not keywording, you can use:
``'high'``: denominator total / 2500
``'medium'``: denominator total / 5000
``'low'``: denominator total / 10000
Note: if keywording, there are smaller default thresholds
:type threshold: int/bool
:param just_entries: Keep matching entries
:type just_entries: see above
:param skip_entries: Skip matching entries
:type skip_entries: see above
:param merge_entries: Merge matching entries
:type merge_entries: see above
:param newname: New name for merged entries
:type newname: str/'combine'
:param just_subcorpora: Keep matching subcorpora
:type just_subcorpora: see above
:param skip_subcorpora: Skip matching subcorpora
:type skip_subcorpora: see above
:param span_subcorpora: If subcorpora are numerically named, span all from *int* to *int2*, inclusive
:type span_subcorpora: tuple -- ``(int, int2)``
:param merge_subcorpora: Merge matching subcorpora
:type merge_subcorpora: see above
:param new_subcorpus_name: Name for merged subcorpora
:type new_subcorpus_name: str/``'combine'``
:param replace_names: Edit result names and then merge duplicate names.
:type replace_names: dict -- ``{criteria: replacement_text}``; str -- a regex to delete from names
:param projection: a to multiply results in subcorpus by n
:type projection: tuple -- ``(subcorpus_name, n)``
:param remove_above_p: Delete any result over p
:type remove_above_p: bool
:param p: set the p value
:type p: float
:param revert_year: when doing linear regression on years, turn annual subcorpora into 1, 2 ...
:type revert_year: bool
:param print_info: Print stuff to console showing what's being edited
:type print_info: bool
:param spelling: Convert/normalise spelling:
:type spelling: str -- ``'US'``/``'UK'``
:param selfdrop: When keywording, try to remove target corpus from reference corpus
:type selfdrop: bool
:param calc_all: When keywording, calculate words that appear in either corpus
:type calc_all: bool
:returns: corpkit.interrogation.Interrogation
"""
# grab arguments, in case we get dict input and have to iterate
locs = locals()
import corpkit
import pandas
import signal
import re
import collections
import pandas as pd
import numpy as np
from pandas import DataFrame, Series
from time import localtime, strftime
try:
get_ipython().getoutput()
except TypeError:
have_ipython = True
except NameError:
have_ipython = False
try:
from IPython.display import display, clear_output
except ImportError:
pass
return_conc = False
from interrogation import Interrodict, Interrogation, Concordance
if interrogation.__class__ == Interrodict:
locs.pop('interrogation', None)
from collections import OrderedDict
outdict = OrderedDict()
from editor import editor
for i, (k, v) in enumerate(interrogation.items()):
# only print the first time around
if i != 0:
locs['print_info'] = False
# if df2 is also a dict, get the relevant entry
if type(denominator) == dict or denominator.__class__ == Interrodict:
#if sorted(set([i.lower() for i in list(dataframe1.keys())])) == \
# sorted(set([i.lower() for i in list(denominator.keys())])):
# locs['denominator'] = denominator[k]
if kwargs.get('denominator_totals'):
locs['denominator'] = denominator[k].totals
else:
locs['denominator'] = denominator[k].results
outdict[k] = editor(v.results, **locs)
if print_info:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print("\n%s: Finished! Output is a dictionary with keys:\n\n '%s'\n" % (thetime, "'\n '".join(sorted(outdict.keys()))))
return Interrodict(outdict)
elif type(interrogation) in [pandas.core.frame.DataFrame, pandas.core.series.Series]:
dataframe1 = interrogation
elif interrogation.__class__ == Interrogation:
#if interrogation.__dict__.get('concordance', None) is not None:
# concordances = interrogation.concordance
branch = kwargs.pop('branch', 'results')
if branch.lower().startswith('r') :
dataframe1 = interrogation.results
elif branch.lower().startswith('t'):
dataframe1 = interrogation.totals
elif branch.lower().startswith('c'):
dataframe1 = interrogation.concordance
return_conc = True
else:
dataframe1 = interrogation.results
elif interrogation.__class__ == Concordance or \
all(x in list(dataframe1.columns) for x in ['l', 'm', 'r']):
return_conc = True
dataframe1 = interrogation
# hope for the best
else:
dataframe1 = interrogation
the_time_started = strftime("%Y-%m-%d %H:%M:%S")
pd.options.mode.chained_assignment = None
pd.set_option('display.float_format', lambda x: '%.2f' % x)
try:
from tests import check_pytex
except ImportError:
from corpkit.tests import check_pytex
if check_pytex():
print_info = False
def combiney(df, df2, operation = '%', threshold = 'medium', prinf = True):
"""mash df and df2 together in appropriate way"""
totals = False
# delete under threshold
if just_totals:
if using_totals:
if not single_totals:
to_drop = list(df2[df2['Combined total'] < threshold].index)
df = df.drop([e for e in to_drop if e in list(df.index)])
if prinf:
to_show = []
[to_show.append(w) for w in to_drop[:5]]
if len(to_drop) > 10:
to_show.append('...')
[to_show.append(w) for w in to_drop[-5:]]
if len(to_drop) > 0:
print('Removing %d entries below threshold:\n %s' % (len(to_drop), '\n '.join(to_show)))
if len(to_drop) > 10:
print('... and %d more ... \n' % (len(to_drop) - len(to_show) + 1))
else:
print('')
else:
denom = df2
else:
denom = list(df2)
if single_totals:
if operation == '%':
totals = df.sum() * 100.0 / float(df.sum().sum())
df = df * 100.0
try:
df = df.div(denom, axis = 0)
except ValueError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print('%s: cannot combine DataFrame 1 and 2: different shapes' % thetime)
elif operation == '+':
try:
df = df.add(denom, axis = 0)
except ValueError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print('%s: cannot combine DataFrame 1 and 2: different shapes' % thetime)
elif operation == '-':
try:
df = df.sub(denom, axis = 0)
except ValueError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print('%s: cannot combine DataFrame 1 and 2: different shapes' % thetime)
elif operation == '*':
totals = df.sum() * float(df.sum().sum())
try:
df = df.mul(denom, axis = 0)
except ValueError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print('%s: cannot combine DataFrame 1 and 2: different shapes' % thetime)
elif operation == '/':
try:
totals = df.sum() / float(df.sum().sum())
df = df.div(denom, axis = 0)
except ValueError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print('%s: cannot combine DataFrame 1 and 2: different shapes' % thetime)
elif operation == 'd':
#df.ix['Combined total'] = df.sum()
#to_drop = to_drop = list(df.T[df.T['Combined total'] < threshold].index)
to_drop = [n for n in list(df.columns) if df[n].sum() < threshold]
df = df.drop([e for e in to_drop if e in list(df.columns)], axis = 1)
#df.drop('Combined total')
if prinf:
to_show = []
[to_show.append(w) for w in to_drop[:5]]
if len(to_drop) > 10:
to_show.append('...')
[to_show.append(w) for w in to_drop[-5:]]
if len(to_drop) > 0:
print('Removing %d entries below threshold:\n %s' % (len(to_drop), '\n '.join(to_show)))
if len(to_drop) > 10:
print('... and %d more ... \n' % (len(to_drop) - len(to_show) + 1))
else:
print('')
# get normalised num in target corpus
norm_in_target = df.div(denom, axis = 0)
# get normalised num in reference corpus, with or without selfdrop
tot_in_ref = df.copy()
for c in list(tot_in_ref.index):
if selfdrop:
tot_in_ref.ix[c] = df.sum() - tot_in_ref.ix[c]
else:
tot_in_ref.ix[c] = df.sum()
norm_in_ref = tot_in_ref.div(df.sum().sum())
df = (norm_in_target - norm_in_ref) / norm_in_ref * 100.0
df = df.replace(float(-100.00), np.nan)
elif operation == 'a':
for c in [c for c in list(df.columns) if int(c) > 1]:
df[c] = df[c] * (1.0 / int(c))
df = df.sum(axis = 1) / df2
elif operation.startswith('c'):
import warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
df = pandas.concat([df, df2], axis = 1)
return df, totals
elif not single_totals:
if not operation.startswith('a'):
# generate totals
if operation == '%':
totals = df.sum() * 100.0 / float(df2.sum().sum())
if operation == '*':
totals = df.sum() * float(df2.sum().sum())
if operation == '/':
totals = df.sum() / float(df2.sum().sum())
if operation.startswith('c'):
# add here the info that merging will not work
# with identical colnames
import warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
d = pd.concat([df.T, df2.T])
# make index nums
d = d.reset_index()
# sum and remove duplicates
d = d.groupby('index').sum()
dx = d.reset_index('index')
dx.index = list(dx['index'])
df = dx.drop('index', axis = 1).T
for index, entry in enumerate(list(df.columns)):
#p.animate(index)
if operation == '%':
try:
df[entry] = df[entry] * 100.0 / df2[entry]
except:
continue
#df.drop(entry, axis = 1, inplace = True)
#df[entry] = maths_done
elif operation == '+':
try:
df[entry] = df[entry] + df2[entry]
except:
continue
elif operation == '-':
try:
df[entry] = df[entry] - df2[entry]
except:
continue
elif operation == '*':
try:
df[entry] = df[entry] * df2[entry]
except:
continue
elif operation == '/':
try:
df[entry] = df[entry] / df2[entry]
except:
continue
else:
for c in [c for c in list(df.columns) if int(c) > 1]:
df[c] = df[c] * (1.0 / int(c))
df = df.sum(axis = 1) / df2.T.sum()
return df, totals
def parse_input(df, the_input):
"""turn whatever has been passed in into list of words that can
be used as pandas indices---maybe a bad way to go about it"""
parsed_input = False
import re
if the_input == 'all':
the_input = r'.*'
if type(the_input) == int:
try:
the_input = str(the_input)
except:
pass
the_input = [the_input]
elif type(the_input) == str or type(the_input) == str:
try:
regex = re.compile(the_input)
parsed_input = [w for w in list(df) if re.search(regex, w)]
return parsed_input
except:
the_input = [the_input]
if type(the_input) == list:
if type(the_input[0]) == int:
parsed_input = [word for index, word in enumerate(list(df)) if index in the_input]
elif type(the_input[0]) == str or type(the_input[0]) == unicode:
try:
parsed_input = [word for word in the_input if word in df.columns]
except AttributeError: # if series
parsed_input = [word for word in the_input if word in df.index]
return parsed_input
def synonymise(df, pos = 'n'):
"""pass a df and a pos and convert df columns to most common synonyms"""
from nltk.corpus import wordnet as wn
#from dictionaries.taxonomies import taxonomies
from collections import Counter
fixed = []
for w in list(df.columns):
try:
syns = []
for syns in wn.synsets(w, pos = pos):
for w in syns:
synonyms.append(w)
top_syn = Counter(syns).most_common(1)[0][0]
fixed.append(top_syn)
except:
fixed.append(w)
df.columns = fixed
return df
def convert_spell(df, convert_to = 'US', print_info = print_info):
"""turn dataframes into us/uk spelling"""
from dictionaries.word_transforms import usa_convert
if print_info:
print('Converting spelling ... \n')
if convert_to == 'UK':
usa_convert = {v: k for k, v in list(usa_convert.items())}
fixed = []
for val in list(df.columns):
try:
fixed.append(usa_convert[val])
except:
fixed.append(val)
df.columns = fixed
return df
def merge_duplicates(df, print_info = print_info):
if print_info:
print('Merging duplicate entries ... \n')
# now we have to merge all duplicates
for dup in df.columns.get_duplicates():
#num_dupes = len(list(df[dup].columns))
temp = df[dup].sum(axis = 1)
#df = df.drop([dup for d in range(num_dupes)], axis = 1)
df = df.drop(dup, axis = 1)
df[dup] = temp
return df
def name_replacer(df, replace_names, print_info = print_info):
"""replace entry names and merge"""
import re
# double or single nest if need be
if type(replace_names) == str:
replace_names = [(replace_names, '')]
if type(replace_names) != dict:
if type(replace_names[0]) == str:
replace_names = [replace_names]
if type(replace_names) == dict:
replace_names = [(v, k) for k, v in list(replace_names.items())]
for to_find, replacement in replace_names:
if print_info:
try:
print('Replacing "%s" with "%s" ...\n' % (to_find, replacement))
except:
print('Deleting "%s" from entry names ...\n' % (to_find))
to_find = re.compile(to_find)
try:
replacement = replacement
except:
replacement = ''
df.columns = [re.sub(to_find, replacement, l) for l in list(df.columns)]
df = merge_duplicates(df, print_info = False)
return df
def just_these_entries(df, parsed_input, prinf = True):
entries = [word for word in list(df) if word not in parsed_input]
if prinf:
print('Keeping %d entries:\n %s' % (len(parsed_input), '\n '.join(parsed_input[:10])))
if len(parsed_input) > 10:
print('... and %d more ... \n' % (len(parsed_input) - 10))
else:
print('')
df = df.drop(entries, axis = 1)
return df
def skip_these_entries(df, parsed_input, prinf = True):
if prinf:
print('Skipping %d entries:\n %s' % (len(parsed_input), '\n '.join(parsed_input[:10])))
if len(parsed_input) > 10:
print('... and %d more ... \n' % (len(parsed_input) - 10))
else:
print('')
df = df.drop(parsed_input, axis = 1)
return df
def newname_getter(df, parsed_input, newname = 'combine', prinf = True, merging_subcorpora = False):
"""makes appropriate name for merged entries"""
if merging_subcorpora:
if newname is False:
newname = 'combine'
if type(newname) == int:
the_newname = list(df.columns)[newname]
elif type(newname) == str:
if newname == 'combine':
if len(parsed_input) <= 3:
the_newname = '/'.join(parsed_input)
elif len(parsed_input) > 3:
the_newname = '/'.join(parsed_input[:3]) + '...'
else:
the_newname = newname
if newname is False:
# revise this code
import operator
sumdict = {}
for item in parsed_input:
summed = sum(list(df[item]))
sumdict[item] = summed
the_newname = max(iter(sumdict.items()), key=operator.itemgetter(1))[0]
if type(the_newname) != str:
the_newname = str(the_newname, errors = 'ignore')
return the_newname
def merge_these_entries(df, parsed_input, the_newname, prinf = True, merging = 'entries'):
# make new entry with sum of parsed input
if len(parsed_input) == 0:
import warnings
warnings.warn('No %s could be automatically merged.\n' % merging)
else:
if prinf:
print('Merging %d %s as "%s":\n %s' % (len(parsed_input), merging, the_newname, '\n '.join(parsed_input[:10])))
if len(parsed_input) > 10:
print('... and %d more ... \n' % (len(parsed_input) - 10))
else:
print('')
# remove old entries
temp = sum([df[i] for i in parsed_input])
if not multiple_merge:
if type(df) == pandas.core.series.Series:
df = df.drop(parsed_input)
else:
df = df.drop(parsed_input, axis = 1)
df[the_newname] = temp
return df
def just_these_subcorpora(df, lst_of_subcorpora, prinf = True):
if type(lst_of_subcorpora[0]) == int:
lst_of_subcorpora = [str(l) for l in lst_of_subcorpora]
good_years = [subcorpus for subcorpus in list(df.index) if subcorpus in lst_of_subcorpora]
if prinf:
print('Keeping %d subcorpora:\n %s' % (len(good_years), '\n '.join(good_years[:10])))
if len(good_years) > 10:
print('... and %d more ... \n' % (len(good_years) - 10))
else:
print('')
df = df.drop([subcorpus for subcorpus in list(df.index) if subcorpus not in good_years], axis = 0)
return df
def skip_these_subcorpora(df, lst_of_subcorpora, prinf = True):
if type(lst_of_subcorpora) == int:
lst_of_subcorpora = [lst_of_subcorpora]
if type(lst_of_subcorpora[0]) == int:
lst_of_subcorpora = [str(l) for l in lst_of_subcorpora]
bad_years = [subcorpus for subcorpus in list(df.index) if subcorpus in lst_of_subcorpora]
if len(bad_years) == 0:
import warnings
warnings.warn('No subcorpora skipped.\n')
else:
if prinf:
print('Skipping %d subcorpora:\n %s' % (len(bad_years), '\n '.join([str(i) for i in bad_years[:10]])))
if len(bad_years) > 10:
print('... and %d more ... \n' % (len(bad_years) - 10))
else:
print('')
df = df.drop([subcorpus for subcorpus in list(df.index) if subcorpus in bad_years], axis = 0)
return df
def span_these_subcorpora(df, lst_of_subcorpora, prinf = True):
"""select only a span of numerical suborpora (first, last)"""
non_totals = [subcorpus for subcorpus in list(df.index)]
good_years = [subcorpus for subcorpus in non_totals if int(subcorpus) >= int(lst_of_subcorpora[0]) and int(subcorpus) <= int(lst_of_subcorpora[-1])]
if len(lst_of_subcorpora) == 0:
import warnings
warnings.warn('Span not identified.\n')
else:
if prinf:
print('Keeping subcorpora:\n %d--%d\n' % (int(lst_of_subcorpora[0]), int(lst_of_subcorpora[-1])))
df = df.drop([subcorpus for subcorpus in list(df.index) if subcorpus not in good_years], axis = 0)
# retotal needed here
return df
def projector(df, list_of_tuples, prinf = True):
"""project abs values"""
if type(list_of_tuples) == list:
tdict = {}
for a, b in list_of_tuples:
tdict[a] = b
list_of_tuples = tdict
for subcorpus, projection_value in list(list_of_tuples.items()):
if type(subcorpus) == int:
subcorpus = str(subcorpus)
df.ix[subcorpus] = df.ix[subcorpus] * projection_value
if prinf:
if type(projection_value) == float:
print('Projection: %s * %s' % (subcorpus, projection_value))
if type(projection_value) == int:
print('Projection: %s * %d' % (subcorpus, projection_value))
if prinf:
print('')
return df
def do_stats(df):
"""do linregress and add to df"""
try:
from scipy.stats import linregress
except ImportError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print('%s: sort type not available in this verion of corpkit.' % thetime)
return False
#from stats.stats import linregress
entries = []
slopes = []
intercepts = []
rs = []
ps = []
stderrs = []
indices = list(df.index)
first_year = list(df.index)[0]
try:
x = [int(y) - int(first_year) for y in indices]
except ValueError:
x = list(range(len(indices)))
statfields = ['slope', 'intercept', 'r', 'p', 'stderr']
for entry in list(df.columns):
entries.append(entry)
y = list(df[entry])
slope, intercept, r, p, stderr = linregress(x, y)
slopes.append(slope)
intercepts.append(intercept)
rs.append(r)
ps.append(p)
stderrs.append(stderr)
sl = pd.DataFrame([slopes, intercepts, rs, ps, stderrs],
index = statfields,
columns = list(df.columns))
df = df.append(sl)
# drop infinites and nans
if operation != 'd':
df = df.replace([np.inf, -np.inf], np.nan)
df = df.fillna(0.0)
return df
def recalc(df, operation = '%'):
statfields = ['slope', 'intercept', 'r', 'p', 'stderr']
"""Add totals to the dataframe1"""
#df.drop('Total', axis = 0, inplace = True)
#df.drop('Total', axis = 1, inplace = True)
try:
df['temp-Total'] = df.drop(statfields).sum(axis = 1)
except:
df['temp-Total'] = df.sum(axis = 1)
df = df.T
try:
df['temp-Total'] = df.drop(statfields).sum(axis = 1)
except:
df['temp-Total'] = df.sum(axis = 1)
df = df.T
return df
def resort(df, sort_by = False, keep_stats = False):
"""sort results, potentially using scipy's linregress"""
# translate options and make sure they are parseable
options = ['total', 'name', 'infreq', 'increase', 'turbulent',
'decrease', 'static', 'most', 'least', 'none', 'p']
if sort_by is True:
sort_by = 'total'
if sort_by == 'most':
sort_by = 'total'
if sort_by == 'least':
sort_by = 'infreq'
if sort_by not in options and sort_by:
raise ValueError("sort_by parameter error: '%s' not recognised. Must be True, False, %s" % (sort_by, ', '.join(options)))
if operation.startswith('k'):
if type(df) == pandas.core.series.Series:
if sort_by == 'total':
df = df.order(ascending = False)
elif sort_by == 'infreq':
df = df.order(ascending = True)
elif sort_by == 'name':
df = df.sort_index()
return df
if just_totals:
if sort_by == 'infreq':
df = df.sort_values(by = 'Combined total', ascending = True, axis = 1)
elif sort_by == 'total':
df = df.sort_values(by = 'Combined total', ascending = False, axis = 1)
elif sort_by == 'name':
df = df.sort_index()
return df
# this is really shitty now that i know how to sort, like in the above
if keep_stats:
df = do_stats(df)
if type(df) == bool:
if df is False:
return False
if sort_by == 'total':
if df1_istotals:
df = df.T
df = recalc(df, operation = operation)
tot = df.ix['temp-Total']
df = df[tot.argsort()[::-1]]
df = df.drop('temp-Total', axis = 0)
df = df.drop('temp-Total', axis = 1)
if df1_istotals:
df = df.T
elif sort_by == 'infreq':
if df1_istotals:
df = df.T
df = recalc(df, operation = operation)
tot = df.ix['temp-Total']
df = df[tot.argsort()]
df = df.drop('temp-Total', axis = 0)
df = df.drop('temp-Total', axis = 1)
if df1_istotals:
df = df.T
elif sort_by == 'name':
# currently case sensitive...
df = df.reindex_axis(sorted(df.columns), axis=1)
elif sort_by == 'p':
df = df.T.sort_values(by='p').T
else:
statfields = ['slope', 'intercept', 'r', 'p', 'stderr']
if not keep_stats:
df = do_stats(df)
if type(df) == bool:
if df is False:
return False
slopes = df.ix['slope']
if sort_by == 'increase':
df = df[slopes.argsort()[::-1]]
elif sort_by == 'decrease':
df = df[slopes.argsort()]
elif sort_by == 'static':
df = df[slopes.abs().argsort()]
elif sort_by == 'turbulent':
df = df[slopes.abs().argsort()[::-1]]
if remove_above_p:
# the easy way to do it!
df = df.T
df = df[df['p'] <= p]
df = df.T
# remove stats field by default
if not keep_stats:
df = df.drop(statfields, axis = 0)
return df
def set_threshold(big_list, threshold, prinf = True, for_keywords = False):
if type(threshold) == str:
if threshold.startswith('l'):
denominator = 10000
if threshold.startswith('m'):
denominator = 5000
if threshold.startswith('h'):
denominator = 2500
if type(big_list) == pandas.core.frame.DataFrame:
tot = big_list.sum().sum()
if type(big_list) == pandas.core.series.Series:
tot = big_list.sum()
the_threshold = float(tot) / float(denominator)
#if for_keywords:
#the_threshold = the_threshold / 2
else:
the_threshold = threshold
if prinf:
print('Threshold: %d\n' % the_threshold)
return the_threshold
# copy dataframe to be very safe
df = dataframe1.copy()
# make cols into strings
try:
df.columns = [str(c) for c in list(df.columns)]
except:
pass
if operation is None:
operation = 'None'
# do concordance work
if return_conc:
if just_entries:
if type(just_entries) == int:
just_entries = [just_entries]
if type(just_entries) == str:
df = df[df['m'].str.contains(just_entries)]
if type(just_entries) == list:
if all(type(e) == str for e in just_entries):
mp = df['m'].map(lambda x: x in just_entries)
df = df[mp]
else:
df = df.ix[just_entries]
if skip_entries:
if type(skip_entries) == int:
skip_entries = [skip_entries]
if type(skip_entries) == str:
df = df[~df['m'].str.contains(skip_entries)]
if type(skip_entries) == list:
if all(type(e) == str for e in skip_entries):
mp = df['m'].map(lambda x: x not in skip_entries)
df = df[mp]
else:
df = df.drop(skip_entries, axis = 0)
if just_subcorpora:
if type(just_subcorpora) == int:
just_subcorpora = [just_subcorpora]
if type(just_subcorpora) == str:
df = df[df['c'].str.contains(just_subcorpora)]
if type(just_subcorpora) == list:
if all(type(e) == str for e in just_subcorpora):
mp = df['c'].map(lambda x: x in just_subcorpora)
df = df[mp]
else:
df = df.ix[just_subcorpora]
if skip_subcorpora:
if type(skip_subcorpora) == int:
skip_subcorpora = [skip_subcorpora]
if type(skip_subcorpora) == str:
df = df[~df['c'].str.contains(skip_subcorpora)]
if type(skip_subcorpora) == list:
if all(type(e) == str for e in skip_subcorpora):
mp = df['c'].map(lambda x: x not in skip_subcorpora)
df = df[mp]
else:
df = df.drop(skip_subcorpora, axis = 0)
return Concordance(df)
if print_info:
print('\n***Processing results***\n========================\n')
df1_istotals = False
if type(df) == pandas.core.series.Series:
df1_istotals = True
df = pandas.DataFrame(df)
# if just a single result
else:
df = pandas.DataFrame(df)
if operation.startswith('k'):
if sort_by is False:
if not df1_istotals:
sort_by = 'turbulent'
if df1_istotals:
df = df.T
# figure out if there's a second list
# copy and remove totals if there is
single_totals = True
using_totals = False
outputmode = False
if denominator.__class__ == Interrogation:
try:
denominator = denominator.results
except AttributeError:
denominator = denominator.totals
if denominator is not False and type(denominator) != str:
df2 = denominator.copy()
using_totals = True
if type(df2) == pandas.core.frame.DataFrame:
if len(df2.columns) > 1:
single_totals = False
else:
df2 = pandas.Series(df2)
if operation == 'd':
df2 = df2.sum(axis = 1)
single_totals = True
elif type(df2) == pandas.core.series.Series:
single_totals = True
#if operation == 'k':
#raise ValueError('Keywording requires a DataFrame for denominator. Use "self"?')
else:
raise ValueError('Denominator not recognised.')
else:
if operation in ['k', 'd', 'a', '%', '/', '*', '-', '+']:
denominator = 'self'
if denominator == 'self':
outputmode = True
if operation.startswith('a') or operation.startswith('A'):
if list(df.columns)[0] != '0' and list(df.columns)[0] != 0:
df = df.T
if using_totals:
if not single_totals:
df2 = df2.T
if projection:
# projection shouldn't do anything when working with '%', remember.
df = projector(df, projection)
if using_totals:
df2 = projector(df2, projection)
if spelling:
df = convert_spell(df, convert_to = spelling)
df = merge_duplicates(df, print_info = False)
if not single_totals:
df2 = convert_spell(df2, convert_to = spelling, print_info = False)
df2 = merge_duplicates(df2, print_info = False)
if not df1_istotals:
sort_by = 'total'
if replace_names:
df = name_replacer(df, replace_names)
df = merge_duplicates(df)
if not single_totals:
df2 = name_replacer(df2, print_info = False)
df2 = merge_duplicates(df2, print_info = False)
if not sort_by:
sort_by = 'total'
# remove old stats if they're there:
statfields = ['slope', 'intercept', 'r', 'p', 'stderr']
try:
df = df.drop(statfields, axis = 0)
except:
pass
if using_totals:
try:
df2 = df2.drop(statfields, axis = 0)
except:
pass
# remove totals and tkinter order
for name, ax in zip(['Total'] * 2 + ['tkintertable-order'] * 2, [0, 1, 0, 1]):
if name == 'Total' and df1_istotals:
continue
try:
df = df.drop(name, axis = ax, errors = 'ignore')
except:
pass
for name, ax in zip(['Total'] * 2 + ['tkintertable-order'] * 2, [0, 1, 0, 1]):
if name == 'Total' and single_totals:
continue
try:
df2 = df2.drop(name, axis = ax, errors = 'ignore')
except:
pass
# merging: make dicts if they aren't already, so we can iterate
if merge_entries:
if type(merge_entries) != list:
if type(merge_entries) == str or type(merge_entries) == str:
merge_entries = {newname: merge_entries}
# for newname, criteria
for name, the_input in sorted(merge_entries.items()):
the_newname = newname_getter(df, parse_input(df, the_input), newname = name, prinf = print_info)
df = merge_these_entries(df, parse_input(df, the_input), the_newname, prinf = print_info)
if not single_totals:
df2 = merge_these_entries(df2, parse_input(df2, the_input), the_newname, prinf = False)
else:
for i in merge_entries:
the_newname = newname_getter(df, parse_input(df, merge_entries), newname = newname, prinf = print_info)
df = merge_these_entries(df, parse_input(df, merge_entries), the_newname, prinf = print_info)
if not single_totals:
df2 = merge_these_entries(df2, parse_input(df2, merge_entries), the_newname, prinf = False)
if merge_subcorpora:
if type(merge_subcorpora) != dict:
if type(merge_subcorpora) == list:
if type(merge_subcorpora[0]) == tuple:
merge_subcorpora = {x: y for x, y in merge_subcorpora}
elif type(merge_subcorpora[0]) == str or type(merge_subcorpora[0]) == str:
merge_subcorpora = {new_subcorpus_name: [x for x in merge_subcorpora]}
elif type(merge_subcorpora[0]) == int:
merge_subcorpora = {new_subcorpus_name: [str(x) for x in merge_subcorpora]}
else:
merge_subcorpora = {new_subcorpus_name: merge_subcorpora}
for name, the_input in sorted(merge_subcorpora.items()):
the_newname = newname_getter(df.T, parse_input(df.T, the_input),
newname = name,
merging_subcorpora = True,
prinf = print_info)
df = merge_these_entries(df.T, parse_input(df.T, the_input), the_newname, merging = 'subcorpora', prinf = print_info).T
if using_totals:
df2 = merge_these_entries(df2.T, parse_input(df2.T, the_input), the_newname, merging = 'subcorpora', prinf = False).T
if just_subcorpora:
df = just_these_subcorpora(df, just_subcorpora, prinf = print_info)
if using_totals:
df2 = just_these_subcorpora(df2, just_subcorpora, prinf = False)
if skip_subcorpora:
df = skip_these_subcorpora(df, skip_subcorpora, prinf = print_info)
if using_totals:
df2 = skip_these_subcorpora(df2, skip_subcorpora, prinf = False)
if span_subcorpora:
df = span_these_subcorpora(df, span_subcorpora, prinf = print_info)
if using_totals:
df2 = span_these_subcorpora(df2, span_subcorpora, prinf = False)
if just_entries:
df = just_these_entries(df, parse_input(df, just_entries), prinf = print_info)
if not single_totals:
df2 = just_these_entries(df2, parse_input(df2, just_entries), prinf = False)
if skip_entries:
df = skip_these_entries(df, parse_input(df, skip_entries), prinf = print_info)
if not single_totals:
df2 = skip_these_entries(df2, parse_input(df2, skip_entries), prinf = False)
# drop infinites and nans
if operation != 'd':
df = df.replace([np.inf, -np.inf], np.nan)
df = df.fillna(0.0)
# make just_totals as dataframe
just_one_total_number = False
if just_totals:
df = pd.DataFrame(df.sum(), columns = ['Combined total'])
if using_totals:
if not single_totals:
df2 = pd.DataFrame(df2.sum(), columns = ['Combined total'])
else:
just_one_total_number = True
df2 = df2.sum()
tots = df.sum(axis = 1)
if using_totals or outputmode:
if not operation.startswith('k'):
the_threshold = 0
# set a threshold if just_totals
if outputmode is True:
df2 = df.T.sum()
if not just_totals:
df2.name = 'Total'
else:
df2.name = 'Combined total'
using_totals = True
single_totals = True
if just_totals:
if not single_totals:
the_threshold = set_threshold(df2, threshold, prinf = print_info)
if operation == 'd':
the_threshold = set_threshold(df2, threshold, prinf = print_info)
df, tots = combiney(df, df2, operation = operation, threshold = the_threshold, prinf = print_info)
# if doing keywording...
if operation.startswith('k'):
from keys import keywords
# allow saved dicts to be df2, etc
try:
if denominator == 'self':
df2 = df.copy()
except TypeError:
pass
if type(denominator) == str:
if denominator != 'self':
df2 = denominator
else:
the_threshold = False
df = keywords(df, df2,
selfdrop = selfdrop,
threshold = threshold,
printstatus = print_info,
editing = True,
calc_all = calc_all,
**kwargs)
# eh?
df = df.T
# drop infinites and nans
if operation != 'd':
df = df.replace([np.inf, -np.inf], np.nan)
df = df.fillna(0.0)
# resort data
if sort_by or keep_stats:
df = resort(df, keep_stats = keep_stats, sort_by = sort_by)
if type(df) == bool:
if df is False:
return 'linregress'
if keep_top:
if not just_totals:
df = df[list(df.columns)[:keep_top]]
else:
df = df.head(keep_top)
if just_totals:
# turn just_totals into series:
df = pd.Series(df['Combined total'], name = 'Combined total')
if df1_istotals:
if operation.startswith('k'):
try:
df = pd.Series(df.ix[dataframe1.name])
df.name = '%s: keyness' % df.name
except:
df = df.iloc[0,:]
df.name = 'keyness' % df.name
# generate totals branch if not percentage results:
# fix me
if df1_istotals or operation.startswith('k'):
if not just_totals:
try:
total = pd.Series(df['Total'], name = 'Total')
except:
pass
total = 'none'
#total = df.copy()
else:
total = 'none'
else:
# might be wrong if using division or something...
try:
total = df.T.sum(axis = 1)
except:
total = 'none'
if type(tots) != pandas.core.frame.DataFrame and type(tots) != pandas.core.series.Series:
total = df.sum(axis = 1)
else:
total = tots
if type(df) == pandas.core.frame.DataFrame:
datatype = df.ix[0].dtype
else:
datatype = df.dtype
# TURN INT COL NAMES INTO STR
try:
df.results.columns = [str(d) for d in list(df.results.columns)]
except:
pass
def add_tkt_index(df):
if type(df) != pandas.core.series.Series:
df = df.T
df = df.drop('tkintertable-order', errors = 'ignore', axis = 0)
df = df.drop('tkintertable-order', errors = 'ignore', axis = 1)
df['tkintertable-order'] = pd.Series([index for index, data in enumerate(list(df.index))], index = list(df.index))
df = df.T
return df
# while tkintertable can't sort rows
try:
from tests import check_t_kinter
except ImportError:
from corpkit.tests import check_t_kinter
tk = check_t_kinter()
if tk:
df = add_tkt_index(df)
if kwargs.get('df1_always_df'):
if type(df) == pandas.core.series.Series:
df = pandas.DataFrame(df)
#outputnames = collections.namedtuple('edited_interrogation', ['query', 'results', 'totals'])
#output = outputnames(the_options, df, total)
# delete non-appearing conc lines
if interrogation.__dict__.get('concordance', None) is None:
lns = None
else:
col_crit = interrogation.concordance['m'].map(lambda x: x in list(df.columns))
ind_crit = interrogation.concordance['c'].map(lambda x: x in list(df.index))
lns = interrogation.concordance[col_crit]
lns = lns.loc[ind_crit]
lns = Concordance(lns)
output = Interrogation(results = df, totals = total, query = locs, concordance = lns)
#print '\nResult (sample)\n'
if print_info:
#if merge_entries or merge_subcorpora or span_subcorpora or just_subcorpora or \
#just_entries or skip_entries or skip_subcorpora or printed_th or projection:
print('***Done!***\n========================\n')
#print df.head().T
#print ''
if operation.startswith('k') or just_totals or df1_istotals:
pd.set_option('display.max_rows', 30)
else:
pd.set_option('display.max_rows', 15)
pd.set_option('display.max_columns', 8)
pd.set_option('max_colwidth',70)
pd.set_option('display.width', 800)
pd.set_option('expand_frame_repr', False)
pd.set_option('display.float_format', lambda x: '%.2f' % x)
return output
def editor(
interrogation,
operation=None,
denominator=False,
sort_by=False,
keep_stats=False,
keep_top=False,
just_totals=False,
threshold="medium",
just_entries=False,
skip_entries=False,
merge_entries=False,
newname="combine",
multiple_merge=False,
just_subcorpora=False,
skip_subcorpora=False,
span_subcorpora=False,
merge_subcorpora=False,
new_subcorpus_name=False,
replace_names=False,
projection=False,
remove_above_p=False,
p=0.05,
revert_year=True,
print_info=True,
spelling=False,
selfdrop=True,
calc_all=True,
**kwargs
):
"""Edit results of interrogations, do keywording, sort, etc.
``just/skip_entries`` and ``just/skip_subcorpora`` can take a few different kinds of input:
* str: treated as regular expression to match
* list:
* of integers: indices to match
* of strings: entries/subcorpora to match
``merge_entries`` and ``merge_subcorpora``, however, are best entered as dicts:
``{newname: criteria, newname2: criteria2}```
where criteria is a string, list, etc.
:param interrogation: Results to edit
:type interrogation: pandas.core.frame.DataFrame
:param operation: Kind of maths to do on inputted lists:
'+', '-', '/', '*', '%': self explanatory
'k': log likelihood (keywords)
'a': get distance metric (for use with interrogator 'a' option)
'd': get percent difference (alternative approach to keywording)
:type operation: str
:param denominator: List of results or totals.
If list of results, for each entry in dataframe 1, locate
entry with same name in dataframe 2, and do maths there
if 'self', do all merging/keeping operations, then use
edited interrogation as denominator
:type denominator: pandas.core.series.Series/pandas.core.frame.DataFrame/dict/'self'
:param sort_by: Calculate slope, stderr, r, p values, then sort by:
increase: highest to lowest slope value
decrease: lowest to highest slope value
turbulent: most change in y axis values
static: least change in y axis values
total/most: largest number first
infreq/least: smallest number first
name: alphabetically
:type sort_by: str
:param keep_stats: Keep/drop stats values from dataframe after sorting
:type keep_stats: bool
:param keep_top: After sorting, remove all but the top *keep_top* results
:type keep_top: int
:param just_totals: Sum each column and work with sums
:type just_totals: bool
:param threshold: When using results list as denominator, drop values occurring
fewer than n times. If not keywording, you can use:
``'high'``: denominator total / 2500
``'medium'``: denominator total / 5000
``'low'``: denominator total / 10000
Note: if keywording, there are smaller default thresholds
:type threshold: int/bool
:param just_entries: Keep matching entries
:type just_entries: see above
:param skip_entries: Skip matching entries
:type skip_entries: see above
:param merge_entries: Merge matching entries
:type merge_entries: see above
:param newname: New name for merged entries
:type newname: str/'combine'
:param just_subcorpora: Keep matching subcorpora
:type just_subcorpora: see above
:param skip_subcorpora: Skip matching subcorpora
:type skip_subcorpora: see above
:param span_subcorpora: If subcorpora are numerically named, span all from *int* to *int2*, inclusive
:type span_subcorpora: tuple -- ``(int, int2)``
:param merge_subcorpora: Merge matching subcorpora
:type merge_subcorpora: see above
:param new_subcorpus_name: Name for merged subcorpora
:type new_subcorpus_name: str/``'combine'``
:param replace_names: Edit result names and then merge duplicate names.
:type replace_names: dict -- ``{criteria: replacement_text}``; str -- a regex to delete from names
:param projection: a to multiply results in subcorpus by n
:type projection: tuple -- ``(subcorpus_name, n)``
:param remove_above_p: Delete any result over p
:type remove_above_p: bool
:param p: set the p value
:type p: float
:param revert_year: when doing linear regression on years, turn annual subcorpora into 1, 2 ...
:type revert_year: bool
:param print_info: Print stuff to console showing what's being edited
:type print_info: bool
:param spelling: Convert/normalise spelling:
:type spelling: str -- ``'US'``/``'UK'``
:param selfdrop: When keywording, try to remove target corpus from reference corpus
:type selfdrop: bool
:param calc_all: When keywording, calculate words that appear in either corpus
:type calc_all: bool
:returns: corpkit.interrogation.Interrogation
"""
# grab arguments, in case we get dict input and have to iterate
locs = locals()
import corpkit
import pandas
import signal
import re
import collections
import pandas as pd
import numpy as np
from pandas import DataFrame, Series
from time import localtime, strftime
try:
get_ipython().getoutput()
except TypeError:
have_ipython = True
except NameError:
have_ipython = False
try:
from IPython.display import display, clear_output
except ImportError:
pass
return_conc = False
from interrogation import Interrodict, Interrogation, Concordance
if interrogation.__class__ == Interrodict:
from collections import OrderedDict
outdict = OrderedDict()
from editor import editor
for i, (k, v) in enumerate(interrogation.items()):
# only print the first time around
if i == 0:
pass
# saved_args['print_info'] = True
else:
locs["print_info"] = False
# if df2 is also a dict, get the relevant entry
if type(denominator) == dict:
if sorted(set([i.lower() for i in list(dataframe1.keys())])) == sorted(
set([i.lower() for i in list(denominator.keys())])
):
locs["denominator"] = denominator[k]
if kwargs.get("use_df2_totals"):
saved_args["denominator"] = denominator[k].totals
outdict[k] = editor(v.results, **saved_args)
if print_info:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print(
"\n%s: Finished! Output is a dictionary with keys:\n\n '%s'\n"
% (thetime, "'\n '".join(sorted(outdict.keys())))
)
return Interrodict(outdict)
elif type(interrogation) in [pandas.core.frame.DataFrame, pandas.core.series.Series]:
dataframe1 = interrogation
elif interrogation.__class__ == Interrogation:
# if interrogation.__dict__.get('concordance', None) is not None:
# concordances = interrogation.concordance
branch = kwargs.pop("branch", "results")
if branch.lower().startswith("r"):
dataframe1 = interrogation.results
elif branch.lower().startswith("t"):
dataframe1 = interrogation.totals
elif branch.lower().startswith("c"):
dataframe1 = interrogation.concordance
return_conc = True
else:
dataframe1 = interrogation.results
elif interrogation.__class__ == Concordance or all(x in list(dataframe1.columns) for x in ["l", "m", "r"]):
return_conc = True
dataframe1 = interrogation
# hope for the best
else:
dataframe1 = interrogation
the_time_started = strftime("%Y-%m-%d %H:%M:%S")
pd.options.mode.chained_assignment = None
pd.set_option("display.float_format", lambda x: "%.2f" % x)
from tests import check_pytex
if check_pytex():
print_info = False
def combiney(df, df2, operation="%", threshold="medium", prinf=True):
"""mash df and df2 together in appropriate way"""
totals = False
# delete under threshold
if just_totals:
if using_totals:
if not single_totals:
to_drop = list(df2[df2["Combined total"] < threshold].index)
df = df.drop([e for e in to_drop if e in list(df.index)])
if prinf:
to_show = []
[to_show.append(w) for w in to_drop[:5]]
if len(to_drop) > 10:
to_show.append("...")
[to_show.append(w) for w in to_drop[-5:]]
if len(to_drop) > 0:
print(
"Removing %d entries below threshold:\n %s" % (len(to_drop), "\n ".join(to_show))
)
if len(to_drop) > 10:
print("... and %d more ... \n" % (len(to_drop) - len(to_show) + 1))
else:
print("")
else:
denom = df2
else:
denom = list(df2)
if single_totals:
if operation == "%":
totals = df.sum() * 100.0 / float(df.sum().sum())
df = df * 100.0
try:
df = df.div(denom, axis=0)
except ValueError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print("%s: cannot combine DataFrame 1 and 2: different shapes" % thetime)
elif operation == "+":
try:
df = df.add(denom, axis=0)
except ValueError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print("%s: cannot combine DataFrame 1 and 2: different shapes" % thetime)
elif operation == "-":
try:
df = df.sub(denom, axis=0)
except ValueError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print("%s: cannot combine DataFrame 1 and 2: different shapes" % thetime)
elif operation == "*":
totals = df.sum() * float(df.sum().sum())
try:
df = df.mul(denom, axis=0)
except ValueError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print("%s: cannot combine DataFrame 1 and 2: different shapes" % thetime)
elif operation == "/":
try:
totals = df.sum() / float(df.sum().sum())
df = df.div(denom, axis=0)
except ValueError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print("%s: cannot combine DataFrame 1 and 2: different shapes" % thetime)
elif operation == "d":
# df.ix['Combined total'] = df.sum()
# to_drop = to_drop = list(df.T[df.T['Combined total'] < threshold].index)
to_drop = [n for n in list(df.columns) if df[n].sum() < threshold]
df = df.drop([e for e in to_drop if e in list(df.columns)], axis=1)
# df.drop('Combined total')
if prinf:
to_show = []
[to_show.append(w) for w in to_drop[:5]]
if len(to_drop) > 10:
to_show.append("...")
[to_show.append(w) for w in to_drop[-5:]]
if len(to_drop) > 0:
print("Removing %d entries below threshold:\n %s" % (len(to_drop), "\n ".join(to_show)))
if len(to_drop) > 10:
print("... and %d more ... \n" % (len(to_drop) - len(to_show) + 1))
else:
print("")
# get normalised num in target corpus
norm_in_target = df.div(denom, axis=0)
# get normalised num in reference corpus, with or without selfdrop
tot_in_ref = df.copy()
for c in list(tot_in_ref.index):
if selfdrop:
tot_in_ref.ix[c] = df.sum() - tot_in_ref.ix[c]
else:
tot_in_ref.ix[c] = df.sum()
norm_in_ref = tot_in_ref.div(df.sum().sum())
df = (norm_in_target - norm_in_ref) / norm_in_ref * 100.0
df = df.replace(float(-100.00), np.nan)
elif operation == "a":
for c in [c for c in list(df.columns) if int(c) > 1]:
df[c] = df[c] * (1.0 / int(c))
df = df.sum(axis=1) / df2
elif operation.startswith("c"):
import warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
df = pandas.concat([df, df2], axis=1)
return df, totals
elif not single_totals:
if not operation.startswith("a"):
# generate totals
if operation == "%":
totals = df.sum() * 100.0 / float(df2.sum().sum())
if operation == "*":
totals = df.sum() * float(df2.sum().sum())
if operation == "/":
totals = df.sum() / float(df2.sum().sum())
if operation.startswith("c"):
# add here the info that merging will not work
# with identical colnames
import warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
d = pd.concat([df.T, df2.T])
# make index nums
d = d.reset_index()
# sum and remove duplicates
d = d.groupby("index").sum()
dx = d.reset_index("index")
dx.index = list(dx["index"])
df = dx.drop("index", axis=1).T
for index, entry in enumerate(list(df.columns)):
# p.animate(index)
if operation == "%":
try:
df[entry] = df[entry] * 100.0 / df2[entry]
except:
continue
# df.drop(entry, axis = 1, inplace = True)
# df[entry] = maths_done
elif operation == "+":
try:
df[entry] = df[entry] + df2[entry]
except:
continue
elif operation == "-":
try:
df[entry] = df[entry] - df2[entry]
except:
continue
elif operation == "*":
try:
df[entry] = df[entry] * df2[entry]
except:
continue
elif operation == "/":
try:
df[entry] = df[entry] / df2[entry]
except:
continue
else:
for c in [c for c in list(df.columns) if int(c) > 1]:
df[c] = df[c] * (1.0 / int(c))
df = df.sum(axis=1) / df2.T.sum()
return df, totals
def parse_input(df, the_input):
"""turn whatever has been passed in into list of words that can
be used as pandas indices---maybe a bad way to go about it"""
# FIX MERGE ERROR HERE
parsed_input = False
import re
if the_input == "all":
the_input = r".*"
if type(the_input) == int:
try:
the_input = str(the_input)
except:
pass
the_input = [the_input]
elif type(the_input) == str or type(the_input) == str:
try:
regex = re.compile(the_input)
parsed_input = [w for w in list(df) if re.search(regex, w)]
return parsed_input
except:
the_input = [the_input]
if type(the_input) == list:
if type(the_input[0]) == int:
parsed_input = [word for index, word in enumerate(list(df)) if index in the_input]
elif type(the_input[0]) == str or type(the_input[0]) == str:
try:
parsed_input = [word for word in the_input if word in df.columns]
except AttributeError: # if series
parsed_input = [word for word in the_input if word in df.index]
return parsed_input
def synonymise(df, pos="n"):
"""pass a df and a pos and convert df columns to most common synonyms"""
from nltk.corpus import wordnet as wn
# from dictionaries.taxonomies import taxonomies
from collections import Counter
fixed = []
for w in list(df.columns):
try:
syns = []
for syns in wn.synsets(w, pos=pos):
for w in syns:
synonyms.append(w)
top_syn = Counter(syns).most_common(1)[0][0]
fixed.append(top_syn)
except:
fixed.append(w)
df.columns = fixed
return df
def convert_spell(df, convert_to="US", print_info=print_info):
"""turn dataframes into us/uk spelling"""
from dictionaries.word_transforms import usa_convert
if print_info:
print("Converting spelling ... \n")
if convert_to == "UK":
usa_convert = {v: k for k, v in list(usa_convert.items())}
fixed = []
for val in list(df.columns):
try:
fixed.append(usa_convert[val])
except:
fixed.append(val)
df.columns = fixed
return df
def merge_duplicates(df, print_info=print_info):
if print_info:
print("Merging duplicate entries ... \n")
# now we have to merge all duplicates
for dup in df.columns.get_duplicates():
# num_dupes = len(list(df[dup].columns))
temp = df[dup].sum(axis=1)
# df = df.drop([dup for d in range(num_dupes)], axis = 1)
df = df.drop(dup, axis=1)
df[dup] = temp
return df
def name_replacer(df, replace_names, print_info=print_info):
"""replace entry names and merge"""
import re
# double or single nest if need be
if type(replace_names) == str:
replace_names = [(replace_names, "")]
if type(replace_names) != dict:
if type(replace_names[0]) == str:
replace_names = [replace_names]
if type(replace_names) == dict:
replace_names = [(v, k) for k, v in list(replace_names.items())]
for to_find, replacement in replace_names:
if print_info:
try:
print('Replacing "%s" with "%s" ...\n' % (to_find, replacement))
except:
print('Deleting "%s" from entry names ...\n' % (to_find))
to_find = re.compile(to_find)
try:
replacement = replacement
except:
replacement = ""
df.columns = [re.sub(to_find, replacement, l) for l in list(df.columns)]
df = merge_duplicates(df, print_info=False)
return df
def just_these_entries(df, parsed_input, prinf=True):
entries = [word for word in list(df) if word not in parsed_input]
if prinf:
print("Keeping %d entries:\n %s" % (len(parsed_input), "\n ".join(parsed_input[:10])))
if len(parsed_input) > 10:
print("... and %d more ... \n" % (len(parsed_input) - 10))
else:
print("")
df = df.drop(entries, axis=1)
return df
def skip_these_entries(df, parsed_input, prinf=True):
if prinf:
print("Skipping %d entries:\n %s" % (len(parsed_input), "\n ".join(parsed_input[:10])))
if len(parsed_input) > 10:
print("... and %d more ... \n" % (len(parsed_input) - 10))
else:
print("")
df = df.drop(parsed_input, axis=1)
return df
def newname_getter(df, parsed_input, newname="combine", prinf=True, merging_subcorpora=False):
"""makes appropriate name for merged entries"""
if merging_subcorpora:
if newname is False:
newname = "combine"
if type(newname) == int:
the_newname = list(df.columns)[newname]
elif type(newname) == str:
if newname == "combine":
if len(parsed_input) <= 3:
the_newname = "/".join(parsed_input)
elif len(parsed_input) > 3:
the_newname = "/".join(parsed_input[:3]) + "..."
else:
the_newname = newname
if newname is False:
# revise this code
import operator
sumdict = {}
for item in parsed_input:
summed = sum(list(df[item]))
sumdict[item] = summed
the_newname = max(iter(sumdict.items()), key=operator.itemgetter(1))[0]
if type(the_newname) != str:
the_newname = str(the_newname, errors="ignore")
return the_newname
def merge_these_entries(df, parsed_input, the_newname, prinf=True, merging="entries"):
# make new entry with sum of parsed input
if len(parsed_input) == 0:
import warnings
warnings.warn("No %s could be automatically merged.\n" % merging)
else:
if prinf:
print(
'Merging %d %s as "%s":\n %s'
% (len(parsed_input), merging, the_newname, "\n ".join(parsed_input[:10]))
)
if len(parsed_input) > 10:
print("... and %d more ... \n" % (len(parsed_input) - 10))
else:
print("")
# remove old entries
temp = sum([df[i] for i in parsed_input])
if not multiple_merge:
if type(df) == pandas.core.series.Series:
df = df.drop(parsed_input)
else:
df = df.drop(parsed_input, axis=1)
df[the_newname] = temp
return df
def just_these_subcorpora(df, lst_of_subcorpora, prinf=True):
if type(lst_of_subcorpora[0]) == int:
lst_of_subcorpora = [str(l) for l in lst_of_subcorpora]
good_years = [subcorpus for subcorpus in list(df.index) if subcorpus in lst_of_subcorpora]
if prinf:
print("Keeping %d subcorpora:\n %s" % (len(good_years), "\n ".join(good_years[:10])))
if len(good_years) > 10:
print("... and %d more ... \n" % (len(good_years) - 10))
else:
print("")
df = df.drop([subcorpus for subcorpus in list(df.index) if subcorpus not in good_years], axis=0)
return df
def skip_these_subcorpora(df, lst_of_subcorpora, prinf=True):
if type(lst_of_subcorpora) == int:
lst_of_subcorpora = [lst_of_subcorpora]
if type(lst_of_subcorpora[0]) == int:
lst_of_subcorpora = [str(l) for l in lst_of_subcorpora]
bad_years = [subcorpus for subcorpus in list(df.index) if subcorpus in lst_of_subcorpora]
if len(bad_years) == 0:
import warnings
warnings.warn("No subcorpora skipped.\n")
else:
if prinf:
print(
"Skipping %d subcorpora:\n %s"
% (len(bad_years), "\n ".join([str(i) for i in bad_years[:10]]))
)
if len(bad_years) > 10:
print("... and %d more ... \n" % (len(bad_years) - 10))
else:
print("")
df = df.drop([subcorpus for subcorpus in list(df.index) if subcorpus in bad_years], axis=0)
return df
def span_these_subcorpora(df, lst_of_subcorpora, prinf=True):
"""select only a span of numerical suborpora (first, last)"""
non_totals = [subcorpus for subcorpus in list(df.index)]
good_years = [
subcorpus
for subcorpus in non_totals
if int(subcorpus) >= int(lst_of_subcorpora[0]) and int(subcorpus) <= int(lst_of_subcorpora[-1])
]
if len(lst_of_subcorpora) == 0:
import warnings
warnings.warn("Span not identified.\n")
else:
if prinf:
print("Keeping subcorpora:\n %d--%d\n" % (int(lst_of_subcorpora[0]), int(lst_of_subcorpora[-1])))
df = df.drop([subcorpus for subcorpus in list(df.index) if subcorpus not in good_years], axis=0)
# retotal needed here
return df
def projector(df, list_of_tuples, prinf=True):
"""project abs values"""
if type(list_of_tuples) == list:
tdict = {}
for a, b in list_of_tuples:
tdict[a] = b
list_of_tuples = tdict
for subcorpus, projection_value in list(list_of_tuples.items()):
if type(subcorpus) == int:
subcorpus = str(subcorpus)
df.ix[subcorpus] = df.ix[subcorpus] * projection_value
if prinf:
if type(projection_value) == float:
print("Projection: %s * %s" % (subcorpus, projection_value))
if type(projection_value) == int:
print("Projection: %s * %d" % (subcorpus, projection_value))
if prinf:
print("")
return df
def do_stats(df):
"""do linregress and add to df"""
try:
from scipy.stats import linregress
except ImportError:
from time import localtime, strftime
thetime = strftime("%H:%M:%S", localtime())
print("%s: sort type not available in this verion of corpkit." % thetime)
return False
# from stats.stats import linregress
entries = []
slopes = []
intercepts = []
rs = []
ps = []
stderrs = []
indices = list(df.index)
first_year = list(df.index)[0]
try:
x = [int(y) - int(first_year) for y in indices]
except ValueError:
x = list(range(len(indices)))
statfields = ["slope", "intercept", "r", "p", "stderr"]
for entry in list(df.columns):
entries.append(entry)
y = list(df[entry])
slope, intercept, r, p, stderr = linregress(x, y)
slopes.append(slope)
intercepts.append(intercept)
rs.append(r)
ps.append(p)
stderrs.append(stderr)
sl = pd.DataFrame([slopes, intercepts, rs, ps, stderrs], index=statfields, columns=list(df.columns))
df = df.append(sl)
# drop infinites and nans
if operation != "d":
df = df.replace([np.inf, -np.inf], np.nan)
df = df.fillna(0.0)
return df
def recalc(df, operation="%"):
statfields = ["slope", "intercept", "r", "p", "stderr"]
"""Add totals to the dataframe1"""
# df.drop('Total', axis = 0, inplace = True)
# df.drop('Total', axis = 1, inplace = True)
try:
df["temp-Total"] = df.drop(statfields).sum(axis=1)
except:
df["temp-Total"] = df.sum(axis=1)
df = df.T
try:
df["temp-Total"] = df.drop(statfields).sum(axis=1)
except:
df["temp-Total"] = df.sum(axis=1)
df = df.T
return df
def resort(df, sort_by=False, keep_stats=False):
"""sort results, potentially using scipy's linregress"""
# translate options and make sure they are parseable
options = [
"total",
"name",
"infreq",
"increase",
"turbulent",
"decrease",
"static",
"most",
"least",
"none",
"p",
]
if sort_by is True:
sort_by = "total"
if sort_by == "most":
sort_by = "total"
if sort_by == "least":
sort_by = "infreq"
if sort_by not in options and sort_by:
raise ValueError(
"sort_by parameter error: '%s' not recognised. Must be True, False, %s" % (sort_by, ", ".join(options))
)
if operation.startswith("k"):
if type(df) == pandas.core.series.Series:
if sort_by == "total":
df = df.order(ascending=False)
elif sort_by == "infreq":
df = df.order(ascending=True)
elif sort_by == "name":
df = df.sort_index()
return df
if just_totals:
if sort_by == "infreq":
df = df.sort_values(by="Combined total", ascending=True, axis=1)
elif sort_by == "total":
df = df.sort_values(by="Combined total", ascending=False, axis=1)
elif sort_by == "name":
df = df.sort_index()
return df
# this is really shitty now that i know how to sort, like in the above
if keep_stats:
df = do_stats(df)
if type(df) == bool:
if df is False:
return False
if sort_by == "total":
if df1_istotals:
df = df.T
df = recalc(df, operation=operation)
tot = df.ix["temp-Total"]
df = df[tot.argsort()[::-1]]
df = df.drop("temp-Total", axis=0)
df = df.drop("temp-Total", axis=1)
if df1_istotals:
df = df.T
elif sort_by == "infreq":
if df1_istotals:
df = df.T
df = recalc(df, operation=operation)
tot = df.ix["temp-Total"]
df = df[tot.argsort()]
df = df.drop("temp-Total", axis=0)
df = df.drop("temp-Total", axis=1)
if df1_istotals:
df = df.T
elif sort_by == "name":
# currently case sensitive...
df = df.reindex_axis(sorted(df.columns), axis=1)
elif sort_by == "p":
df = df.T.sort_values(by="p").T
else:
statfields = ["slope", "intercept", "r", "p", "stderr"]
if not keep_stats:
df = do_stats(df)
if type(df) == bool:
if df is False:
return False
slopes = df.ix["slope"]
if sort_by == "increase":
df = df[slopes.argsort()[::-1]]
elif sort_by == "decrease":
df = df[slopes.argsort()]
elif sort_by == "static":
df = df[slopes.abs().argsort()]
elif sort_by == "turbulent":
df = df[slopes.abs().argsort()[::-1]]
if remove_above_p:
# the easy way to do it!
df = df.T
df = df[df["p"] <= p]
df = df.T
# remove stats field by default
if not keep_stats:
df = df.drop(statfields, axis=0)
return df
def set_threshold(big_list, threshold, prinf=True, for_keywords=False):
if type(threshold) == str:
if threshold.startswith("l"):
denominator = 10000
if threshold.startswith("m"):
denominator = 5000
if threshold.startswith("h"):
denominator = 2500
if type(big_list) == pandas.core.frame.DataFrame:
tot = big_list.sum().sum()
if type(big_list) == pandas.core.series.Series:
tot = big_list.sum()
the_threshold = float(tot) / float(denominator)
# if for_keywords:
# the_threshold = the_threshold / 2
else:
the_threshold = threshold
if prinf:
print("Threshold: %d\n" % the_threshold)
return the_threshold
# copy dataframe to be very safe
df = dataframe1.copy()
# make cols into strings
try:
df.columns = [str(c) for c in list(df.columns)]
except:
pass
if operation is None:
operation = "None"
# do concordance work
if return_conc:
if just_entries:
if type(just_entries) == int:
just_entries = [just_entries]
if type(just_entries) == str:
df = df[df["m"].str.contains(just_entries)]
if type(just_entries) == list:
if all(type(e) == str for e in just_entries):
mp = df["m"].map(lambda x: x in just_entries)
df = df[mp]
else:
df = df.ix[just_entries]
if skip_entries:
if type(skip_entries) == int:
skip_entries = [skip_entries]
if type(skip_entries) == str:
df = df[~df["m"].str.contains(skip_entries)]
if type(skip_entries) == list:
if all(type(e) == str for e in skip_entries):
mp = df["m"].map(lambda x: x not in skip_entries)
df = df[mp]
else:
df = df.drop(skip_entries, axis=0)
if just_subcorpora:
if type(just_subcorpora) == int:
just_subcorpora = [just_subcorpora]
if type(just_subcorpora) == str:
df = df[df["c"].str.contains(just_subcorpora)]
if type(just_subcorpora) == list:
if all(type(e) == str for e in just_subcorpora):
mp = df["c"].map(lambda x: x in just_subcorpora)
df = df[mp]
else:
df = df.ix[just_subcorpora]
if skip_subcorpora:
if type(skip_subcorpora) == int:
skip_subcorpora = [skip_subcorpora]
if type(skip_subcorpora) == str:
df = df[~df["c"].str.contains(skip_subcorpora)]
if type(skip_subcorpora) == list:
if all(type(e) == str for e in skip_subcorpora):
mp = df["c"].map(lambda x: x not in skip_subcorpora)
df = df[mp]
else:
df = df.drop(skip_subcorpora, axis=0)
return Concordance(df)
if print_info:
print("\n***Processing results***\n========================\n")
df1_istotals = False
if type(df) == pandas.core.series.Series:
df1_istotals = True
df = pandas.DataFrame(df)
# if just a single result
else:
df = pandas.DataFrame(df)
if operation.startswith("k"):
if sort_by is False:
if not df1_istotals:
sort_by = "turbulent"
if df1_istotals:
df = df.T
# figure out if there's a second list
# copy and remove totals if there is
single_totals = True
using_totals = False
outputmode = False
if denominator is not False and type(denominator) != str:
df2 = denominator.copy()
using_totals = True
if type(df2) == pandas.core.frame.DataFrame:
if len(df2.columns) > 1:
single_totals = False
else:
df2 = pandas.Series(df2)
if operation == "d":
df2 = df2.sum(axis=1)
single_totals = True
elif type(df2) == pandas.core.series.Series:
single_totals = True
# if operation == 'k':
# raise ValueError('Keywording requires a DataFrame for denominator. Use "self"?')
else:
raise ValueError("Denominator not recognised.")
else:
if operation in ["k", "d", "a", "%", "/", "*", "-", "+"]:
denominator = "self"
if denominator == "self":
outputmode = True
if operation.startswith("a") or operation.startswith("A"):
if list(df.columns)[0] != "0" and list(df.columns)[0] != 0:
df = df.T
if using_totals:
if not single_totals:
df2 = df2.T
if projection:
# projection shouldn't do anything when working with '%', remember.
df = projector(df, projection)
if using_totals:
df2 = projector(df2, projection)
if spelling:
df = convert_spell(df, convert_to=spelling)
df = merge_duplicates(df, print_info=False)
if not single_totals:
df2 = convert_spell(df2, convert_to=spelling, print_info=False)
df2 = merge_duplicates(df2, print_info=False)
if not df1_istotals:
sort_by = "total"
if replace_names:
df = name_replacer(df, replace_names)
df = merge_duplicates(df)
if not single_totals:
df2 = name_replacer(df2, print_info=False)
df2 = merge_duplicates(df2, print_info=False)
if not sort_by:
sort_by = "total"
# remove old stats if they're there:
statfields = ["slope", "intercept", "r", "p", "stderr"]
try:
df = df.drop(statfields, axis=0)
except:
pass
if using_totals:
try:
df2 = df2.drop(statfields, axis=0)
except:
pass
# remove totals and tkinter order
for name, ax in zip(["Total"] * 2 + ["tkintertable-order"] * 2, [0, 1, 0, 1]):
if name == "Total" and df1_istotals:
continue
try:
df = df.drop(name, axis=ax, errors="ignore")
except:
pass
for name, ax in zip(["Total"] * 2 + ["tkintertable-order"] * 2, [0, 1, 0, 1]):
if name == "Total" and single_totals:
continue
try:
df2 = df2.drop(name, axis=ax, errors="ignore")
except:
pass
# merging: make dicts if they aren't already, so we can iterate
if merge_entries:
if type(merge_entries) != list:
if type(merge_entries) == str or type(merge_entries) == str:
merge_entries = {newname: merge_entries}
# for newname, criteria
for name, the_input in sorted(merge_entries.items()):
the_newname = newname_getter(df, parse_input(df, the_input), newname=name, prinf=print_info)
df = merge_these_entries(df, parse_input(df, the_input), the_newname, prinf=print_info)
if not single_totals:
df2 = merge_these_entries(df2, parse_input(df2, the_input), the_newname, prinf=False)
else:
for i in merge_entries:
the_newname = newname_getter(df, parse_input(df, merge_entries), newname=newname, prinf=print_info)
df = merge_these_entries(df, parse_input(df, merge_entries), the_newname, prinf=print_info)
if not single_totals:
df2 = merge_these_entries(df2, parse_input(df2, merge_entries), the_newname, prinf=False)
if merge_subcorpora:
if type(merge_subcorpora) != dict:
if type(merge_subcorpora) == list:
if type(merge_subcorpora[0]) == tuple:
merge_subcorpora = {x: y for x, y in merge_subcorpora}
elif type(merge_subcorpora[0]) == str or type(merge_subcorpora[0]) == str:
merge_subcorpora = {new_subcorpus_name: [x for x in merge_subcorpora]}
elif type(merge_subcorpora[0]) == int:
merge_subcorpora = {new_subcorpus_name: [str(x) for x in merge_subcorpora]}
else:
merge_subcorpora = {new_subcorpus_name: merge_subcorpora}
for name, the_input in sorted(merge_subcorpora.items()):
the_newname = newname_getter(
df.T, parse_input(df.T, the_input), newname=name, merging_subcorpora=True, prinf=print_info
)
df = merge_these_entries(
df.T, parse_input(df.T, the_input), the_newname, merging="subcorpora", prinf=print_info
).T
if using_totals:
df2 = merge_these_entries(
df2.T, parse_input(df2.T, the_input), the_newname, merging="subcorpora", prinf=False
).T
if just_subcorpora:
df = just_these_subcorpora(df, just_subcorpora, prinf=print_info)
if using_totals:
df2 = just_these_subcorpora(df2, just_subcorpora, prinf=False)
if skip_subcorpora:
df = skip_these_subcorpora(df, skip_subcorpora, prinf=print_info)
if using_totals:
df2 = skip_these_subcorpora(df2, skip_subcorpora, prinf=False)
if span_subcorpora:
df = span_these_subcorpora(df, span_subcorpora, prinf=print_info)
if using_totals:
df2 = span_these_subcorpora(df2, span_subcorpora, prinf=False)
if just_entries:
df = just_these_entries(df, parse_input(df, just_entries), prinf=print_info)
if not single_totals:
df2 = just_these_entries(df2, parse_input(df2, just_entries), prinf=False)
if skip_entries:
df = skip_these_entries(df, parse_input(df, skip_entries), prinf=print_info)
if not single_totals:
df2 = skip_these_entries(df2, parse_input(df2, skip_entries), prinf=False)
# drop infinites and nans
if operation != "d":
df = df.replace([np.inf, -np.inf], np.nan)
df = df.fillna(0.0)
# make just_totals as dataframe
just_one_total_number = False
if just_totals:
df = pd.DataFrame(df.sum(), columns=["Combined total"])
if using_totals:
if not single_totals:
df2 = pd.DataFrame(df2.sum(), columns=["Combined total"])
else:
just_one_total_number = True
df2 = df2.sum()
tots = df.sum(axis=1)
if using_totals or outputmode:
if not operation.startswith("k"):
the_threshold = 0
# set a threshold if just_totals
if outputmode is True:
df2 = df.T.sum()
if not just_totals:
df2.name = "Total"
else:
df2.name = "Combined total"
using_totals = True
single_totals = True
if just_totals:
if not single_totals:
the_threshold = set_threshold(df2, threshold, prinf=print_info)
if operation == "d":
the_threshold = set_threshold(df2, threshold, prinf=print_info)
df, tots = combiney(df, df2, operation=operation, threshold=the_threshold, prinf=print_info)
# if doing keywording...
if operation.startswith("k"):
from keys import keywords
# allow saved dicts to be df2, etc
try:
if denominator == "self":
df2 = df.copy()
except TypeError:
pass
if type(denominator) == str:
if denominator != "self":
df2 = denominator
else:
the_threshold = False
df = keywords(
df,
df2,
selfdrop=selfdrop,
threshold=threshold,
printstatus=print_info,
editing=True,
calc_all=calc_all,
**kwargs
)
# eh?
df = df.T
# drop infinites and nans
if operation != "d":
df = df.replace([np.inf, -np.inf], np.nan)
df = df.fillna(0.0)
# resort data
if sort_by or keep_stats:
df = resort(df, keep_stats=keep_stats, sort_by=sort_by)
if type(df) == bool:
if df is False:
return "linregress"
if keep_top:
if not just_totals:
df = df[list(df.columns)[:keep_top]]
else:
df = df.head(keep_top)
if just_totals:
# turn just_totals into series:
df = pd.Series(df["Combined total"], name="Combined total")
if df1_istotals:
if operation.startswith("k"):
try:
df = pd.Series(df.ix[dataframe1.name])
df.name = "%s: keyness" % df.name
except:
df = df.iloc[0, :]
df.name = "keyness" % df.name
# generate totals branch if not percentage results:
# fix me
if df1_istotals or operation.startswith("k"):
if not just_totals:
try:
total = pd.Series(df["Total"], name="Total")
except:
pass
total = "none"
# total = df.copy()
else:
total = "none"
else:
# might be wrong if using division or something...
try:
total = df.T.sum(axis=1)
except:
total = "none"
if type(tots) != pandas.core.frame.DataFrame and type(tots) != pandas.core.series.Series:
total = df.sum(axis=1)
else:
total = tots
if type(df) == pandas.core.frame.DataFrame:
datatype = df.ix[0].dtype
else:
datatype = df.dtype
# TURN INT COL NAMES INTO STR
try:
df.results.columns = [str(d) for d in list(df.results.columns)]
except:
pass
def add_tkt_index(df):
if type(df) != pandas.core.series.Series:
df = df.T
df = df.drop("tkintertable-order", errors="ignore", axis=0)
df = df.drop("tkintertable-order", errors="ignore", axis=1)
df["tkintertable-order"] = pd.Series(
[index for index, data in enumerate(list(df.index))], index=list(df.index)
)
df = df.T
return df
# while tkintertable can't sort rows
from tests import check_t_kinter
tk = check_t_kinter()
if tk:
df = add_tkt_index(df)
if kwargs.get("df1_always_df"):
if type(df) == pandas.core.series.Series:
df = pandas.DataFrame(df)
# outputnames = collections.namedtuple('edited_interrogation', ['query', 'results', 'totals'])
# output = outputnames(the_options, df, total)
# delete non-appearing conc lines
if interrogation.__dict__.get("concordance", None) is None:
lns = None
else:
col_crit = interrogation.concordance["m"].map(lambda x: x in list(df.columns))
ind_crit = interrogation.concordance["c"].map(lambda x: x in list(df.index))
lns = interrogation.concordance[col_crit]
lns = lns.loc[ind_crit]
lns = Concordance(lns)
output = Interrogation(results=df, totals=total, query=locs, concordance=lns)
# print '\nResult (sample)\n'
if print_info:
# if merge_entries or merge_subcorpora or span_subcorpora or just_subcorpora or \
# just_entries or skip_entries or skip_subcorpora or printed_th or projection:
print("***Done!***\n========================\n")
# print df.head().T
# print ''
if operation.startswith("k") or just_totals or df1_istotals:
pd.set_option("display.max_rows", 30)
else:
pd.set_option("display.max_rows", 15)
pd.set_option("display.max_columns", 8)
pd.set_option("max_colwidth", 70)
pd.set_option("display.width", 800)
pd.set_option("expand_frame_repr", False)
pd.set_option("display.float_format", lambda x: "%.2f" % x)
return output
def codetab(self):
newEditor = editor(self, self)
newTab = self.mainTabWidget.addTab(newEditor, QtGui.QIcon(self.icons+'tex.png'), "Code Editor")
self.mainTabWidget.setCurrentIndex(newTab)
self.printChildren(self.mainTabWidget, "")
def default(mapeditor):
# general things
m=editor(mapeditor)
# a wall around the world
m.make('wall',type='wall',xyz=(-151,-101,village_height),bbox=[2,204,5])
m.make('wall',type='wall',xyz=(-151,-101,village_height),bbox=[304,2,5])
m.make('wall',type='wall',xyz=(-151,100,village_height),bbox=[304,2,5])
m.make('wall',type='wall',xyz=(100,-101,village_height),bbox=[2,204,5])
# a camp near the origin
#cfire=m.make('campfire',type='campfire',xyz=(0,4,village_height))
#m.make('fire',type='fire',xyz=(0.7,0.7,0),parent=cfire.id)
#m.make('tent',type='tent',xyz=(-1,8,village_height),bbox=[2.5,2.5,3])
#m.make('lumber',type='lumber',xyz=(-1,3,village_height))
#m.make('lumber',type='lumber',xyz=(-1,2.5,village_height))
cfire=m.make('campfire',type='campfire',xyz=(35,54,village_height))
m.make('fire',type='fire',xyz=(0.7,0.7,0),parent=cfire.id)
cfire=m.make('campfire',type='campfire',xyz=(42,51,village_height))
m.make('fire',type='fire',xyz=(0.7,0.7,0),parent=cfire.id)
cfire=m.make('campfire',type='campfire',xyz=(43,39,village_height))
m.make('fire',type='fire',xyz=(0.7,0.7,0),parent=cfire.id)
m.make('sign_market_w',type='sign_market_w',xyz=(-8.7,-21.2,village_height))
for i in range(0, 20):
m.make('lumber',type='lumber',xyz=(uniform(-100,0),uniform(-100,-80),village_height))
# general
m.make('oak',type='oak',xyz=(-70,-86,village_height), bbox=[1,1,6])
m.make('oak',type='oak',xyz=(-6,-77,village_height), bbox=[1,1,6])
m.make('oak',type='oak',xyz=(-24,-90,village_height), bbox=[1,1,6])
m.make('oak',type='oak',xyz=(-49,-90,village_height), bbox=[1,1,6])
m.make('oak',type='oak',xyz=(-86,-81,village_height), bbox=[1,1,6])
m.make('oak',type='oak',xyz=(-12,-98,village_height), bbox=[1,1,6])
m.make('oak',type='oak',xyz=(-35,-73,village_height), bbox=[1,1,6])
m.make('oak',type='oak',xyz=(-83,-66,village_height), bbox=[1,1,6])
m.make('oak',type='oak',xyz=(-87,-34,village_height), bbox=[1,1,6])
m.make('oak',type='oak',xyz=(-98,-28,village_height), bbox=[1,1,6])
m.make('oak',type='oak',xyz=(-75,31,village_height), bbox=[1,1,6])
m.make('weather',type='weather',desc='object that describes the weather',
xyz=(0,1,0), rain=0.0)
# bones all over the place
for i in range(0, 10):
xpos = uniform(-150,100)
ypos = uniform(-100,100)
m.make('skull', type='skull', xyz=(xpos+uniform(-2,2),ypos+uniform(-2,2),village_height))
m.make('pelvis', type='pelvis', xyz=(xpos+uniform(-2,2),ypos+uniform(-2,2),village_height))
m.make('arm', type='arm', xyz=(xpos+uniform(-2,2),ypos+uniform(-2,2),village_height))
m.make('thigh', type='thigh', xyz=(xpos+uniform(-2,2),ypos+uniform(-2,2),village_height))
m.make('shin', type='shin', xyz=(xpos+uniform(-2,2),ypos+uniform(-2,2),village_height))
m.make('ribcage', type='ribcage', xyz=(xpos+uniform(-2,2),ypos+uniform(-2,2),village_height))
# the lych, who makes bones into skeletons
lych=m.make('lych', type='lych', xyz=(-21, -89, village_height))
m.learn(lych,lych_goals)
m.know(lych,lych_knowledge)
m.tell_importance(lych,il.assemble,'>',il.patrol)
# animals
piglet = m.make('pig', type='pig', xyz=(-31,-16,village_height))
m.learn(piglet,pig_goals)
wolf = m.make('wolf', type='wolf', xyz=(90,-90,village_height))
m.learn(wolf,wolf_goals)
m.know(wolf,wolf_knowledge)
m.tell_importance(wolf,il.forage,'>',il.hunt)
m.tell_importance(wolf,il.forage,'>',il.patrol)
m.tell_importance(wolf,il.hunt,'>',il.patrol)
crab = m.make('crab', type='crab', xyz=(-90,90,village_height))
m.learn(crab,crab_goals)
skeleton = m.make('skeleton', type='skeleton', xyz=(-38,-25,village_height))
#squirrel = m.make('squirrel', type='squirrel', desc='test squirrel',
#xyz=(-32,-115,village_height))
#m.know(squirrel,sknowledge)
#m.learn(squirrel,(il.transport,"transport_something(self,'acorn','forest','stash')"))
# villagers
# Some generic market traders, to operate the market stalls
stall_list = ['mstall_bakery_2_se', 'mstall_beer_1_se',
'mstall_blacksmith_1_sw', 'mstall_blue_1_us',
'mstall_books_2_sw', 'mstall_cheese_2_se',
'mstall_fish_1_se', 'mstall_freshmeat_1_se',
'mstall_fruits_2_se', 'mstall_healer_1_sw',
'mstall_household_1_sw', 'mstall_jewels_1_sw',
'mstall_magic_items_1_sw', 'mstall_milk_2_se',
'mstall_seamstress_1_sw', 'mstall_vegetables_1_se',
'mstall_wine_1_se']
directions = [[0,1,0],[1,0,0],[0,-1,0],[-1,0,0],
[0.7,0.7,0],[0.7,-0.7,0],[-0.7,-0.7,0],[-0.7,0.7,0]]
trader_list = ['merchant', 'maid_brown', 'maid_blond', 'maid_red']
for stall in stall_list:
trader=m.make('trader',type=trader_list[randint(0,3)],
xyz=(uniform(-36,-56),uniform(-7,-17),village_height),
age=probability.fertility_age,face=directions[randint(0,7)])
m.learn(trader,(il.market,"run_shop('"+stall+"','open','dawn')"))
m.learn(trader,(il.market,"run_shop('"+stall+"','closed','evening')"))
#m.make('bstall',type='bstall',xyz=(-41,-5,village_height))
home1_xyz=(90,-90,village_height)
butcher=m.make('Ulad Bargan',type='butcher',desc='the butcher',
xyz=butcher_stall_xyz,age=probability.fertility_age,sex='male')
m.learn(butcher,(il.trade,"trade(self, 'pig', 'cleaver', 'cut', 'ham', 'market','day')"))
m.learn(butcher,(il.buy_livestock,"buy_livestock('pig', 1)"))
m.learn(butcher,(il.market,"run_shop('mstall_freshmeat_1_se','open','dawn')"))
m.learn(butcher,(il.market,"run_shop('mstall_freshmeat_1_se','closed','evening')"))
m.know(butcher,bknowledge)
m.price(butcher,bprices)
cleaver=m.make('cleaver', type='cleaver', desc='cleaver for cutting meat',
place='market', xyz=(-41,-5,village_height))
m.own(butcher,cleaver)
m.learn(butcher,(il.sell,"sell_trade('ham', 'market')"))
coins=[]
for i in range(0, 60):
coins.append(m.make('coin',type='coin',xyz=(0,0,0),parent=butcher.id))
m.own(butcher,coins)
home2_xyz=(80,80,village_height)
merchant=m.make('Dyfed Searae',type='merchant',desc='the pig merchant',
xyz=pig_stall_xyz,age=probability.fertility_age,sex='male',face=[-1,0,0])
merchant2=m.make('Dylan Searae',type='merchant',desc='the pig merchant',
xyz=(-28,2,village_height),age=probability.fertility_age,sex='male',face=[0,-1,0])
merchants=[merchant, merchant2]
sty=m.make('sty',type='sty',xyz=pig_sty_xyz,status=1.0,bbox=[5,5,3])
m.know(merchants,mknowledge)
m.know(merchants,village)
m.price(merchant,mprices)
m.price(merchant2,m2prices)
m.own(merchant,sty)
m.learn(merchant,(il.keep,"keep('pig', 'sty')"))
m.learn(merchant, (il.sell,"sell_trade('pig', 'market', 'morning')"))
m.learn(merchant2,(il.sell,"sell_trade('pig', 'market', 'afternoon')"))
m.learn(merchants,(il.lunch,"meal(self, 'ham','midday', 'inn')"))
m.learn(merchants,(il.sup,"meal(self, 'beer', 'evening', 'inn')"))
piglets=[]
for i in range(0, 6):
piglets.append(m.make('pig',type='pig',xyz=(uniform(0,4),uniform(0,4),village_height),parent=sty.id,face=directions[randint(0,7)]))
m.learn(piglets,pig_goals)
m.own(merchants,piglets)
# Warriors - the more adventurous types
warriors=[]
warrior=m.make('Tom Harrowe', type='guard',xyz=(uniform(-1,14),uniform(-18,-27),village_height),sex='male',face=directions[randint(0,7)])
sword=m.make('sword',type='sword',xyz=(0,0,0), parent=warrior.id)
m.own(warrior,sword)
warriors.append(warrior)
warrior=m.make('Mae Dollor', type='guard',xyz=(uniform(-1,14),uniform(-18,-27),village_height),sex='female',face=directions[randint(0,7)])
sword=m.make('sword',type='sword',xyz=(0,0,0), parent=warrior.id)
m.own(warrior,sword)
warriors.append(warrior)
warrior=m.make('Covan Dubneal',type='guard',xyz=(uniform(-1,14),uniform(-18,-27),village_height),sex='male',face=directions[randint(0,7)])
sword=m.make('sword',type='sword',xyz=(0,0,0), parent=warrior.id)
m.own(warrior,sword)
warriors.append(warrior)
warrior=m.make('Roal Guddon', type='guard',xyz=(uniform(-1,14),uniform(-18,-27),village_height),sex='male',face=directions[randint(0,7)])
sword=m.make('sword',type='sword',xyz=(0,0,0), parent=warrior.id)
m.own(warrior,sword)
warriors.append(warrior)
m.learn(warriors,(il.defend,"defend(self, 'sword', 'skeleton', 10)"))
warrior=m.make('Vonaa Barile',type='archer',xyz=(uniform(-1,14),uniform(-18,-27),village_height),sex='female',face=directions[randint(0,7)])
m.learn(warrior,(il.hunt,"hunt(self, 'bow', 'deer', 10)"))
bow=m.make('bow',type='bow',xyz=(0,0,0), parent=warrior.id)
m.own(warrior,bow)
warriors.append(warrior)
warrior=m.make('Lile Birloc', type='archer',xyz=(-2,-2,village_height),sex='female',face=directions[randint(0,7)])
m.learn(warrior,(il.hunt,"hunt(self, 'bow', 'deer', 10)"))
bow=m.make('bow',type='bow',xyz=(0,0,0), parent=warrior.id)
m.own(warrior,bow)
for i in range(0, 6):
arrow=m.make('arrow',type='arrow',xyz=(0,0,0), parent=warrior.id)
m.own(warrior,arrow)
warriors.append(warrior)
# Warriors all know where stuff is in the village
m.know(warriors,village)
# Warriors enjoy their food and drink
m.learn(warriors,(il.lunch,"meal(self, 'ham','midday', 'inn')"))
m.learn(warriors,(il.sup,"meal(self, 'beer', 'evening', 'inn')"))
m.make('deer',type='deer',xyz=(2,2,village_height))
def _edit(self, *args, **kwargs):
from corpkit import editor
return editor(self, *args, **kwargs)
def textEditor(init=''):
return editor.editor(box=True, inittext=init, win_location=(0, 0))
def default(mapeditor):
# general things
m=editor(mapeditor)
# general
m.make('oak',type='oak',desc='oak tree',
xyz=(-16,-8,forest_height),status=1.0)
m.make('oak',type='oak',desc='oak tree',
xyz=(-7,19,forest_height),status=1.0)
m.make('oak',type='oak',desc='oak tree',
xyz=(3,14,forest_height),status=1.0)
m.make('oak',type='oak',desc='oak tree',
xyz=(12,36,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-15,-166,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-16,-190,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-18,-176,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-23,-155,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-25,-170,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-24,-185,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-30,-158,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-33,-179,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-32,-192,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-38,-159,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-50,-169,forest_height),status=1.0)
# m.make('oak',type='oak',desc='oak tree',xyz=(-43,-182,forest_height),status=1.0)
# animals
for i in range(0, 5):
m.make('skull', type='skull', desc='test skull', xyz=(uniform(-2,2),uniform(-2,2),village_height))
m.make('pelvis', type='pelvis', desc='test pelvis', xyz=(uniform(-2,2),uniform(-2,2),village_height))
m.make('arm', type='arm', desc='test arm', xyz=(uniform(-2,2),uniform(-2,2),village_height))
m.make('thigh', type='thigh', desc='test thigh', xyz=(uniform(-2,2),uniform(-2,2),village_height))
m.make('shin', type='shin', desc='test shin', xyz=(uniform(-2,2),uniform(-2,2),village_height))
m.make('ribcage',type='ribcage',desc='test ribcage',xyz=(uniform(-2,2),uniform(-2,2),village_height))
lych=m.make('lych', type='lych', desc='Source of all evil',
xyz=(2, 3, village_height))
m.learn(lych,(il.assemble,
"assemble(self, 'skeleton', ['skull', 'ribcage', 'arm', 'pelvis', 'thigh', 'shin'])"))
piglet = m.make('pig', type='pig', desc='test piglet',
xyz=(-16,13,village_height))
m.learn(piglet,(il.avoid,"avoid('wolf',10.0)"))
m.learn(piglet,(il.forage,"forage(self, 'acorn')"))
piglet = m.make('pig', type='pig', desc='test piglet',
xyz=(-18,15,village_height))
m.learn(piglet,(il.avoid,"avoid('wolf',10.0)"))
m.learn(piglet,(il.forage,"forage(self, 'acorn')"))
piglet = m.make('pig', type='pig', desc='test piglet',
xyz=(-16,15,village_height))
m.learn(piglet,(il.avoid,"avoid('wolf',10.0)"))
m.learn(piglet,(il.forage,"forage(self, 'acorn')"))
# wolf = m.make('wolf', type='wolf', desc='test wolf',
# xyz=(-10,-10,village_height))
# m.learn(wolf,(il.hunt,"predate(self,'pig',50.0)"))
# m.learn(wolf,wander)
#crab = m.make('crab', type='crab', desc='test crab',
# xyz=(-40,-125,village_height))
#m.learn(crab,wander)
# skeleton = m.make('skeleton', type='skeleton', desc='test skeleton',
# xyz=(-38,-125,village_height))
#squirrel = m.make('squirrel', type='squirrel', desc='test squirrel',
#xyz=(-32,-115,village_height))
#m.know(squirrel,sknowledge)
#m.learn(squirrel,(il.transport,"transport_something(self,'acorn','forest','stash')"))
# farmers
#home1_xyz=(100,-130,village_height)
#butcher=m.make('Bill Brondmore',type='farmer',desc='the butcher',
#xyz=home1_xyz,age=probability.fertility_age,sex='male')
#m.learn(butcher,(il.trade,"trade(self, 'pig', 'cleaver', 'cut', 'sausage', 'market')"))
#m.know(butcher,bknowledge)
#cleaver=m.make('cleaver',desc='cleaver for cutting meat',place='market',
#xyz=home1_xyz,status=1.0)
#m.own(butcher,cleaver)
#home2_xyz=(80,-130,village_height)
#merchant=m.make('Indor Fergman',type='farmer',desc='the pig merchant',
#xyz=home2_xyz,age=probability.fertility_age,sex='female')
#m.know(merchant,bknowledge)
# sty=m.make('sty',desc='A pig sty',xyz=(-27,-2,village_height),status=1.0)
#m.own(merchant,sty)
#m.learn(merchant,(il.keep,"keep('pig', 'sty')"))
#m.learn(merchant,(il.sell,"sell_trade('pig', 'market')"))
#piglet1 = m.make('pig', type='pig', desc='a pig', xyz=(-20,-111,village_height))
#piglet2 = m.make('pig', type='pig', desc='a pig', xyz=(-21,-111,village_height))
#m.learn(piglet1,(il.forage,"forage(self, 'acorn')"))
#m.learn(piglet2,(il.forage,"forage(self, 'acorn')"))
#piglet3 = m.make('pig', type='pig', desc='a pig', xyz=(-21,-110,village_height))
#piglet4 = m.make('pig', type='pig', desc='a pig', xyz=(-20,-109,village_height))
#m.own(merchant,piglet1)
#m.own(merchant,piglet2)
#m.own(merchant,piglet3)
#m.own(merchant,piglet4)
# generated entries
# generated by forge/tools/iso_edit_tools/get_client_entities.pl from agrilan.map
# agrilan.map was created by Pegasus
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-72,85,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-72,81,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-80,81,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-76,71,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-84,71,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-90,69,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-74,67,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-68,65,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-72,65,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-66,61,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(19,55,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-70,55,village_height))
m.make('fern_1_us',type='fern_1_us',desc='a dumb fern_1_us object', xyz=(-84,51,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-75,41,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-97,31,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-87,25,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(83,23,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(79,23,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(75,23,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(59,23,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(56,23,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(53,23,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(49,23,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-95,21,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(49,19,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(35,17,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-79,17,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(49,15,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(31,15,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-95,15,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(35,13,village_height))
m.make('house_deco_1_us',type='house_deco_1_us',desc='a dumb house_deco_1_us object', xyz=(53,11,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(49,11,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(97,7,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-95,6,village_height))
m.make('house_deco_4_us',type='house_deco_4_us',desc='a dumb house_deco_4_us object', xyz=(-38,3,village_height))
m.make('house_deco_4_us',type='house_deco_4_us',desc='a dumb house_deco_4_us object', xyz=(-57,3,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(27,-1,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(-2,-2,village_height))
m.make('fence_study_ta_1',type='fence_study_ta_1',desc='a dumb fence_study_ta_1 object', xyz=(-27,-2,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(13,-3,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(27,-4,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-5,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(13,-5,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(11,-5,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(3,-5,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(1,-5,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(-2,-5,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-6,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-46,-6,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-47,-6,village_height))
m.make('house_deco_1_us',type='house_deco_1_us',desc='a dumb house_deco_1_us object', xyz=(-75,-6,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-97,-6,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(27,-7,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(1,-7,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-7,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-30,-7,village_height))
m.make('jar_ornate_tall_med_1_ta',type='jar_ornate_tall_med_1_ta',desc='a dumb jar_ornate_tall_med_1_ta object', xyz=(-48,-7,village_height))
m.make('maid_brown_sw_kl',type='maid_brown_sw_kl',desc='a dumb maid_brown_sw_kl object', xyz=(-49,-7,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(-2,-8,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-8,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-30,-8,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-34,-8,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-36,-8,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-47,-8,village_height))
m.make('jar_ornate_tall_med_1_ta',type='jar_ornate_tall_med_1_ta',desc='a dumb jar_ornate_tall_med_1_ta object', xyz=(-48,-8,village_height))
m.make('jar_ornate_tall_med_1_ta',type='jar_ornate_tall_med_1_ta',desc='a dumb jar_ornate_tall_med_1_ta object', xyz=(-49,-8,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-9,village_height))
m.make('house_deco_4_us',type='house_deco_4_us',desc='a dumb house_deco_4_us object', xyz=(15,-9,village_height))
m.make('chair_ne_wooden_dbrown_1_us',type='chair_ne_wooden_dbrown_1_us',desc='a dumb chair_ne_wooden_dbrown_1_us object', xyz=(5,-9,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-9,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-34,-9,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-35,-9,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-36,-9,village_height))
m.make('mstall_blue_1_us',type='mstall_blue_1_us',desc='a dumb mstall_blue_1_us object', xyz=(-40,-9,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-41,-9,village_height))
m.make('mstall_blue_1_us',type='mstall_blue_1_us',desc='a dumb mstall_blue_1_us object', xyz=(-45,-9,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-46,-9,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-47,-9,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(27,-10,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-36,-10,village_height))
m.make('maid_red_se_kl',type='maid_red_se_kl',desc='a dumb maid_red_se_kl object', xyz=(-38,-10,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-40,-10,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-41,-10,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-42,-10,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-46,-10,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-47,-10,village_height))
m.make('house_deco_3_us',type='house_deco_3_us',desc='a dumb house_deco_3_us object', xyz=(57,-11,village_height))
m.make('table_ne_wooden_dbrown_1_us',type='table_ne_wooden_dbrown_1_us',desc='a dumb table_ne_wooden_dbrown_1_us object', xyz=(5,-11,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(-2,-11,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-11,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-30,-11,village_height))
m.make('house_deco_3_us',type='house_deco_3_us',desc='a dumb house_deco_3_us object', xyz=(-27,-12,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-12,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-30,-12,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-13,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(27,-13,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-93,-15,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(27,-16,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-17,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(1,-17,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-88,-17,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(-2,-18,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-62,-19,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-63,-19,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-64,-19,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-66,-19,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(27,-20,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-65,-20,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-21,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(-2,-21,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-63,-21,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-65,-21,village_height))
m.make('house_deco_2_us',type='house_deco_2_us',desc='a dumb house_deco_2_us object', xyz=(6,-22,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(27,-23,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(-2,-24,village_height))
m.make('house_deco_3_us',type='house_deco_3_us',desc='a dumb house_deco_3_us object', xyz=(57,-25,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-25,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(-2,-27,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-98,-28,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-29,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-37,-30,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-38,-30,village_height))
m.make('jar_ornate_tall_med_1_ta',type='jar_ornate_tall_med_1_ta',desc='a dumb jar_ornate_tall_med_1_ta object', xyz=(-40,-30,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-53,-30,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-54,-30,village_height))
m.make('house_deco_1_us',type='house_deco_1_us',desc='a dumb house_deco_1_us object', xyz=(-63,-30,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-30,-31,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-36,-31,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-37,-31,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-38,-31,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-39,-31,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-40,-31,village_height))
m.make('jar_ornate_tall_med_1_ta',type='jar_ornate_tall_med_1_ta',desc='a dumb jar_ornate_tall_med_1_ta object', xyz=(-41,-31,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-48,-31,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-54,-31,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-32,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-30,-32,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-37,-32,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-38,-32,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-40,-32,village_height))
m.make('jar_ornate_tall_med_1_ta',type='jar_ornate_tall_med_1_ta',desc='a dumb jar_ornate_tall_med_1_ta object', xyz=(-41,-32,village_height))
m.make('mstall_blue_1_us',type='mstall_blue_1_us',desc='a dumb mstall_blue_1_us object', xyz=(-45,-32,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-46,-32,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-47,-32,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-48,-32,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-33,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-33,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-30,-33,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-31,-33,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-46,-33,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(-48,-33,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-34,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-30,-34,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-31,-34,village_height))
m.make('maid_red_sw_kl',type='maid_red_sw_kl',desc='a dumb maid_red_sw_kl object', xyz=(-42,-34,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-87,-34,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-35,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-30,-35,village_height))
m.make('house_deco_3_us',type='house_deco_3_us',desc='a dumb house_deco_3_us object', xyz=(-27,-36,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(-29,-36,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-37,village_height))
m.make('house_deco_3_us',type='house_deco_3_us',desc='a dumb house_deco_3_us object', xyz=(57,-39,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-41,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-97,-41,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(73,-45,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-45,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(55,-47,village_height))
m.make('box_wood_small_1_ta',type='box_wood_small_1_ta',desc='a dumb box_wood_small_1_ta object', xyz=(55,-49,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-49,village_height))
m.make('house_deco_1_us',type='house_deco_1_us',desc='a dumb house_deco_1_us object', xyz=(-34,-50,village_height))
m.make('house_deco_1_us',type='house_deco_1_us',desc='a dumb house_deco_1_us object', xyz=(-45,-50,village_height))
m.make('house_deco_1_us',type='house_deco_1_us',desc='a dumb house_deco_1_us object', xyz=(-55,-50,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(55,-51,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(53,-51,village_height))
m.make('house_deco_3_us',type='house_deco_3_us',desc='a dumb house_deco_3_us object', xyz=(57,-53,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(53,-53,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-53,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-57,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-61,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(9,-64,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-65,village_height))
m.make('stall_1_ta',type='stall_1_ta',desc='a dumb stall_1_ta object', xyz=(24,-65,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(18,-65,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-98,-66,village_height))
m.make('house_deco_4_us',type='house_deco_4_us',desc='a dumb house_deco_4_us object', xyz=(57,-67,village_height))
m.make('chair_ne_wooden_dbrown_1_us',type='chair_ne_wooden_dbrown_1_us',desc='a dumb chair_ne_wooden_dbrown_1_us object', xyz=(51,-67,village_height))
m.make('chair_ne_wooden_dbrown_1_us',type='chair_ne_wooden_dbrown_1_us',desc='a dumb chair_ne_wooden_dbrown_1_us object', xyz=(49,-67,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-93,-67,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(9,-68,village_height))
m.make('table_ne_wooden_dbrown_1_us',type='table_ne_wooden_dbrown_1_us',desc='a dumb table_ne_wooden_dbrown_1_us object', xyz=(49,-69,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-69,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-97,-69,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(25,-71,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(9,-72,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-67,-72,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(35,-73,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(12,-73,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(25,-75,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-97,-75,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-68,-76,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-90,-77,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-98,-77,village_height))
m.make('stall_1_ta',type='stall_1_ta',desc='a dumb stall_1_ta object', xyz=(16,-79,village_height))
m.make('stall_1_ta',type='stall_1_ta',desc='a dumb stall_1_ta object', xyz=(13,-79,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-97,-80,village_height))
m.make('house_deco_2_us',type='house_deco_2_us',desc='a dumb house_deco_2_us object', xyz=(51,-81,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-86,-81,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(25,-82,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(22,-82,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-21,-82,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-78,-82,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-13,-83,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-85,-83,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-34,-84,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-53,-84,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-93,-84,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-98,-84,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(1,-85,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-75,-85,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(28,-86,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-60,-86,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-70,-86,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-4,-87,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-10,-87,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-28,-87,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-34,-88,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-69,-88,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-98,-88,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(81,-89,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(79,-89,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-28,-89,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-66,-89,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-74,-89,village_height))
m.make('barrel_2_ta',type='barrel_2_ta',desc='a dumb barrel_2_ta object', xyz=(36,-90,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-24,-90,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-49,-90,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-83,-90,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(1,-91,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-12,-91,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-92,-91,village_height))
m.make('stall_1_ta',type='stall_1_ta',desc='a dumb stall_1_ta object', xyz=(38,-92,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(30,-92,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-55,-92,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-98,-92,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(79,-93,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(23,-93,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-62,-93,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-77,-93,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(41,-94,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(12,-94,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(4,-94,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-46,-94,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-60,-94,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-15,-95,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-26,-95,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-89,-95,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-1,-96,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-74,-96,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-94,-96,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(79,-97,village_height))
m.make('house_deco_1_us',type='house_deco_1_us',desc='a dumb house_deco_1_us object', xyz=(67,-97,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(61,-97,village_height))
m.make('roses_flowering_2_us',type='roses_flowering_2_us',desc='a dumb roses_flowering_2_us object', xyz=(57,-97,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(49,-97,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(29,-97,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-22,-97,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-25,-97,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-45,-97,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-89,-97,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-98,-97,village_height))
m.make('stall_1_ta',type='stall_1_ta',desc='a dumb stall_1_ta object', xyz=(12,-98,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(5,-98,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(2,-98,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-3,-98,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-12,-98,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-33,-98,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-36,-98,village_height))
m.make('oak_summer_1_us',type='oak_summer_1_us',desc='a dumb oak_summer_1_us object', xyz=(-41,-98,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-53,-98,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-65,-98,village_height))
m.make('poplar_summer_1_us',type='poplar_summer_1_us',desc='a dumb poplar_summer_1_us object', xyz=(-84,-98,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(45,-99,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-15,-99,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-44,-99,village_height))
m.make('birch_summer_1_us',type='birch_summer_1_us',desc='a dumb birch_summer_1_us object', xyz=(-55,-99,village_height))
def pmultiquery(
path,
option="c",
query="any",
sort_by="total",
quicksave=False,
num_proc="default",
function_filter=False,
just_speakers=False,
root=False,
note=False,
print_info=True,
**kwargs
):
"""Parallel process multiple queries or corpora.
This function is used by interrogator if:
a) path is a list of paths
b) query is a dict of named queries
c) function_filter is iterable
d) just speakers == 'each'
This function needs joblib 0.8.4 or above in order to run properly."""
import collections
import os
import pandas
import pandas as pd
import collections
from collections import namedtuple
from time import strftime, localtime
from interrogator import interrogator
from editor import editor
from other import save_result
try:
from joblib import Parallel, delayed
except:
pass
# raise ValueError('joblib, the module used for multiprocessing, cannot be found. ' \
# 'Install with:\n\n pip install joblib')
import multiprocessing
def best_num_parallel(num_cores, num_queries):
import corpkit
"""decide how many parallel processes to run
the idea, more or less, is to balance the load when possible"""
if num_queries <= num_cores:
return num_queries
if num_queries > num_cores:
if (num_queries / num_cores) == num_cores:
return int(num_cores)
if num_queries % num_cores == 0:
return max([int(num_queries / n) for n in range(2, num_cores) if int(num_queries / n) <= num_cores])
else:
import math
if (float(math.sqrt(num_queries))).is_integer():
square_root = math.sqrt(num_queries)
if square_root <= num_queries / num_cores:
return int(square_root)
return num_cores
num_cores = multiprocessing.cpu_count()
# are we processing multiple queries or corpora?
# find out optimal number of cores to use.
multiple_option = False
multiple_queries = False
multiple_speakers = False
multiple_corpora = False
denom = 1
if hasattr(path, "__iter__"):
multiple_corpora = True
num_cores = best_num_parallel(num_cores, len(path))
denom = len(path)
elif hasattr(query, "__iter__"):
multiple_queries = True
num_cores = best_num_parallel(num_cores, len(query))
denom = len(query)
elif hasattr(function_filter, "__iter__"):
multiple_option = True
num_cores = best_num_parallel(num_cores, len(function_filter.keys()))
denom = len(function_filter.keys())
elif just_speakers:
from corpkit.build import get_speaker_names_from_xml_corpus
multiple_speakers = True
if just_speakers == "each":
just_speakers = get_speaker_names_from_xml_corpus(path)
if len(just_speakers) == 0:
print "No speaker name data found."
return
num_cores = best_num_parallel(num_cores, len(just_speakers))
denom = len(just_speakers)
if num_proc != "default":
num_cores = num_proc
# make sure quicksaves are right type
if quicksave is True:
raise ValueError("quicksave must be string when using pmultiquery.")
# the options that don't change
d = {
"option": option,
#'paralleling': True,
"function": "interrogator",
"root": root,
"note": note,
"denominator": denom,
}
# add kwargs to query
for k, v in kwargs.items():
d[k] = v
# make a list of dicts to pass to interrogator,
# with the iterable unique in every one
ds = []
if multiple_corpora:
path = sorted(path)
for index, p in enumerate(path):
name = os.path.basename(p)
a_dict = dict(d)
a_dict["path"] = p
a_dict["query"] = query
a_dict["outname"] = name
a_dict["just_speakers"] = just_speakers
a_dict["paralleling"] = index
a_dict["printstatus"] = False
ds.append(a_dict)
elif multiple_queries:
for index, (name, q) in enumerate(query.items()):
a_dict = dict(d)
a_dict["path"] = path
a_dict["query"] = q
a_dict["outname"] = name
a_dict["just_speakers"] = just_speakers
a_dict["paralleling"] = index
a_dict["printstatus"] = False
ds.append(a_dict)
elif multiple_option:
for index, (name, q) in enumerate(function_filter.items()):
a_dict = dict(d)
a_dict["path"] = path
a_dict["query"] = query
a_dict["outname"] = name
a_dict["just_speakers"] = just_speakers
a_dict["paralleling"] = index
a_dict["function_filter"] = q
a_dict["printstatus"] = False
ds.append(a_dict)
elif multiple_speakers:
for index, name in enumerate(just_speakers):
a_dict = dict(d)
a_dict["path"] = path
a_dict["query"] = query
a_dict["outname"] = name
a_dict["just_speakers"] = [name]
a_dict["function_filter"] = function_filter
a_dict["paralleling"] = index
a_dict["printstatus"] = False
ds.append(a_dict)
time = strftime("%H:%M:%S", localtime())
if multiple_corpora and not multiple_option:
print (
"\n%s: Beginning %d parallel corpus interrogations:\n %s"
"\n\n Query: '%s'"
"\n Interrogating corpus ... \n" % (time, num_cores, "\n ".join(path), query)
)
elif multiple_queries:
print (
"\n%s: Beginning %d parallel corpus interrogations: %s"
"\n Queries: '%s'"
"\n Interrogating corpus ... \n"
% (time, num_cores, os.path.basename(path), "', '".join(query.values()))
)
elif multiple_option:
print (
"\n%s: Beginning %d parallel corpus interrogations (multiple options): %s"
"\n\n Query: '%s'"
"\n Interrogating corpus ... \n" % (time, num_cores, os.path.basename(path), query)
)
elif multiple_speakers:
print (
"\n%s: Beginning %d parallel corpus interrogations: %s"
"\n\n Query: '%s'"
"\n Interrogating corpus ... \n" % (time, num_cores, os.path.basename(path), query)
)
# run in parallel, get either a list of tuples (non-c option)
# or a dataframe (c option)
# import sys
# reload(sys)
# stdout=sys.stdout
failed = False
# ds = ds[::-1]
if not root:
from blessings import Terminal
terminal = Terminal()
print "\n" * (len(ds) - 2)
for dobj in ds:
linenum = dobj["paralleling"]
with terminal.location(0, terminal.height - (linenum + 1)):
# this is a really bad idea.
thetime = strftime("%H:%M:%S", localtime())
print "%s: [ 0%% (%s) ]" % (thetime, dobj["outname"])
# res = Parallel(n_jobs=num_cores)(delayed(interrogator)(**x) for x in ds)
try:
# ds = sorted(ds, key=lambda k: k['paralleling'], reverse = True)
res = Parallel(n_jobs=num_cores)(delayed(interrogator)(**x) for x in ds)
print "\n\n\n"
except:
failed = True
print "Multiprocessing failed."
raise
try:
res = sorted(res)
except:
failed = True
pass
elif root or failed:
res = []
for index, d in enumerate(ds):
d["startnum"] = (100 / denom) * index
res.append(interrogator(**d))
try:
res = sorted(res)
except:
pass
# multiprocessing way
# from multiprocessing import Process
# from corpkit.interrogator import interrogator
# jobs = []
##for d in ds:
## p = multiprocessing.Process(target=interrogator, kwargs=(**d,))
## jobs.append(p)
## p.start()
## while p.is_alive():
## import time
## time.sleep(2)
## if root:
## root.update()
# result_queue = multiprocessing.Queue()
#
# for d in ds:
# funs = [interrogator(result_queue, **kwargs) for kwargs in ds]
# jobs = [multiprocessing.Process(mc) for mc in funs]
# for job in jobs: job.start()
# for job in jobs: job.join()
# results = [result_queue.get() for mc in funs]
# turn list into dict of results, make query and total branches,
# save and return
if not option.startswith("c"):
out = {}
# print ''
for (name, data), d in zip(res, ds):
for unpicklable in ["note", "root"]:
try:
del d[unpicklable]
except KeyError:
pass
if not option.startswith("k"):
outputnames = collections.namedtuple("interrogation", ["query", "results", "totals"])
try:
stotal = data.sum(axis=1)
stotal.name = u"Total"
except ValueError:
stotal = data.sum()
output = outputnames(d, data, stotal)
else:
outputnames = collections.namedtuple("interrogation", ["query", "results"])
output = outputnames(d, data)
out[name] = output
# could be wrong for unstructured corpora?
if quicksave:
fullpath = os.path.join("saved_interrogations", quicksave)
while os.path.isdir(fullpath):
selection = raw_input(
"\nSave error: %s already exists in %s.\n\nType 'o' to overwrite, or enter a new name: "
% (quicksave, "saved_interrogations")
)
if selection == "o" or selection == "O":
import shutil
shutil.rmtree(fullpath)
else:
import os
fullpath = os.path.join("saved_interrogations", selection)
for k, v in out.items():
save_result(v, k, savedir=fullpath, print_info=False)
time = strftime("%H:%M:%S", localtime())
print "\n%s: %d files saved to %s" % (time, len(out.keys()), fullpath)
time = strftime("%H:%M:%S", localtime())
print "\n\n%s: Finished! Output is a dictionary with keys:\n\n '%s'\n" % (
time,
"'\n '".join(sorted(out.keys())),
)
return out
# make query and total branch, save, return
else:
out = pd.concat(res, axis=1)
out = editor(out, sort_by=sort_by, print_info=False, keep_stats=False)
time = strftime("%H:%M:%S", localtime())
print "\n\n%s: Finished! %d unique results, %d total." % (time, len(out.results.columns), out.totals.sum())
if quicksave:
from other import save_result
save_result(out, quicksave)
return out
help='The path used to access the file to edit (Ex: ~/.bashrc')
parser.add_argument('-p',
nargs='?',
const='',
action='store',
type=str,
help='The prompt string to be used')
def split(word):
return [char for char in word]
args = parser.parse_args()
e = editor(args.file)
p = args.p
if p == 'None':
p = ''
while True:
command = split(input(p))
if command[0] == 'a':
data = []
txt = ""
while txt != "`":
data.append(txt)
txt = input()
data.remove(data[0])
e.append(data)
elif command[0] == 'w':
e.write()
def edit(self, *args, **kwargs):
"""Edit results of interrogations, do keywording, sort, etc.
>>> # rel. frequencies for words without initial capital
>>> rel = data.edit('%', 'self', skip_entries = r'^[A-Z]')
``just/skip_entries`` and ``just/skip_subcorpora`` can take a few different kinds of input:
* str: treated as regular expression to match
* list:
* of integers: indices to match
* of strings: entries/subcorpora to match
``merge_entries`` and ``merge_subcorpora``, however, are best entered as dicts:
``{newname: criteria, newname2: criteria2}```
where criteria is a string, list, etc.
:param operation: Kind of maths to do on inputted lists:
``'+'``, ``'-'``, ``'/'``, ``'*'``, ``'%'``: self explanatory
``'k'``: log likelihood (keywords)
``'a'``: get distance metric
``'d'``: get percent difference (alternative approach to keywording)
:type operation: str
:param denominator: List of results or totals.
If list of results, for each entry in dataframe 1, locate
entry with same name in dataframe 2, and do maths there
if 'self', do all merging/keeping operations, then use
edited dataframe1 as denominator
:type denominator: pandas.Series/pandas.DataFrame/dict/`self`
:param sort_by: Calculate slope, stderr, r, p values, then sort by.
``'increase'``: highest to lowest slope value
``'decrease'``: lowest to highest slope value
``'turbulent'``: most change in y axis values
``'static'``: least change in y axis values
``'total/most'``: largest number first
``'infreq/least'``: smallest number first
``'name'``: alphabetically
:type sort_by: str
:param keep_stats: Keep/drop stats values from dataframe after sorting
:type keep_stats: bool
:param keep_top: After sorting, remove all but the top *keep_top* results
:type keep_top: int
:param just_totals: Sum each column and work with sums
:type just_totals: bool
:param threshold: When using results list as dataframe 2, drop values occurring fewer than n times. If not keywording, you can use:
``'high'``: ``denominator total / 2500``
``'medium'``: ``denominator total / 5000``
``'low'``: ``denominator total / 10000``
If keywording, there are smaller default thresholds
:type threshold: int/bool
:param just_entries: Keep matching entries
:type just_entries: see above
:param skip_entries: Skip matching entries
:type skip_entries: see above
:param merge_entries: Merge matching entries
:type merge_entries: see above
:param newname: New name for merged entries
:type newname: str/``'combine'``
:param just_subcorpora: Keep matching subcorpora
:type just_subcorpora: see above
:param skip_subcorpora: Skip matching subcorpora
:type skip_subcorpora: see above
:param span_subcorpora: If subcorpora are numerically named, span all from *int* to *int2*, inclusive
:type span_subcorpora: tuple -- ``(int, int2)``
:param merge_subcorpora: Merge matching subcorpora
:type merge_subcorpora: see above
:param new_subcorpus_name: Name for merged subcorpora
:type new_subcorpus_name: str/``'combine'``
:param replace_names: Edit result names and then merge duplicate names.
:type replace_names: dict -- ``{criteria: replacement_text}``; str -- a regex to delete from names
:param projection: a to multiply results in subcorpus by n
:type projection: tuple -- ``(subcorpus_name, n)``
:param remove_above_p: Delete any result over ``p``
:type remove_above_p: bool
:param p: set the p value
:type p: float
:param revert_year: When doing linear regression on years, turn annual subcorpora into 1, 2 ...
:type revert_year: bool
:param print_info: Print stuff to console showing what's being edited
:type print_info: bool
:param spelling: Convert/normalise spelling:
:type spelling: str -- ``'US'``/``'UK'``
:param selfdrop: When keywording, try to remove target corpus from reference corpus
:type selfdrop: bool
:param calc_all: When keywording, calculate words that appear in either corpus
:type calc_all: bool
:returns: :class:`corpkit.interrogation.Interrogation`
"""
from editor import editor
return editor(self, *args, **kwargs)
# making sure charcater is in middle of screen g.CORNERPOINT[0] = geo.maximum(player.pos[0] - SCREEN_WIDTH/2, 0) g.CORNERPOINT[1] = geo.maximum(player.pos[1] - SCREEN_HEIGHT/2, 0) scrollx = 0 scrolly = 0 # ---- update shit and draw allGroup ---------------- background = bigmap.subsurface((g.CORNERPOINT[0], g.CORNERPOINT[1], SCREEN_WIDTH, SCREEN_HEIGHT)) screen.blit(background, (0,0)) allGroup.update(seconds) # destroy bodies out of the time step else issues for body in g.TO_DESTROY : _world.DestroyBody(body) g.TO_DESTROY.remove(body) g.TO_DESTROY = [] for timer in g.TIMERS : timer.update(seconds) # take a time step in box2d engine _world.Step(TIME_STEP, 10, 10) gui.update() allGroup.draw(screen) pygame.display.flip() editor.editor(FILEPATH, new = True) main(FILEPATH)
def editfunc(self, *args, **kwargs):
from corpkit import editor
return editor(self, *args, **kwargs)
