def main():
#SETTINGS
best_n_words = 10000
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
settings = Settings.Settings()
results_dir = settings.results_directory + GwData.FOLDER
#TOKENIZE
data = GwData.GwData()
tokenized_docs = WordTokenizer.tokenize(data.documents, min_word_count = 5)
term_freq = TermFrequency.TermFrequency(tokenized_docs)
#NLTK Decision Tree
list_of_dicts = Converter.vector_space_to_dict_list(term_freq.matrix, term_freq.id2Word, Converter.to_binary)
labels = data.causal_per_document
causal_count = sum(labels)
relative_word_frequency = DocumentFrequency.document_frequency_ratio(list_of_dicts, labels, lambda l: l == 1)
condensed_data = extract_best_n_words(relative_word_frequency, best_n_words, list_of_dicts)
labelled_data = zip(condensed_data, labels)
td_size = int(0.75 * len(labelled_data))
training_data = labelled_data[:td_size]
validation_data = labelled_data[td_size:]
dt = nltk.DecisionTreeClassifier.train(training_data)
#RESULTS
classifications = [dt.classify(rcd) for rcd,lbl in validation_data]
results = ResultsHelper.rfp(labels[td_size:], classifications)
results += "Num Words Used : " + str(best_n_words) + "\n"
results += "\n"
error = dt.error(labelled_data)
results += "ERROR: : " + str(error * 100) + "%\n"
results += "\n"
results += "PSEUDOCODE:\n"
results += dt.pseudocode(depth = 1000) + "\n"
print results
#DUMP TO FILE
fName = results_dir + "Causal_Relation_DT.txt"
handle = open(fName, mode = "w+")
handle.write(results)
handle.close()
#binary_matrix = term_freq.binary_matrix()
#decision_tree = tree.DecisionTreeClassifier(criterion = 'entropy')
#decision_tree.fit(binary_matrix, labels)
# Test with CL1 labels
raw_input("Press Enter to quit")
def convert(self, latex_input):
logging.debug(latex_input)
latex_input = self.handle_custom_commands(latex_input)
logging.debug(latex_input)
mathml_string = l2m.latex_to_mathml(latex_input, name_space = True)
print(mathml_string)
#mathml_string = etree.tostring(mathml_tree)
logging.debug(mathml_string)
mathml_tree = etree.fromstring(mathml_string)
omml_tree = self.transform(mathml_tree)
print(self.transform.error_log)
return omml_tree.getroot()
def on_Convert(self, *args):
#Apre la finestra di dialogo con le impostazioni
dlgCon = ConverterDialog(self.mainWindow, self.prefs)
dlgCon.show()
if not dlgCon.response == gtk.RESPONSE_OK:
return
sorgente = "file"
#Carica la lista dei file selezionati
if not bool(int(self.prefs.get_option("save-all-tracks"))):
# Solo i file selezionati
self.selconv = self.Selection(self.FileTable)
else:
# Tutti i file
self.FileTable.tvSelection.select_all()
self.selconv = self.Selection(self.FileTable)
self.FileTable.tvSelection.unselect_all()
if self.selconv:
# Inizializza la coda
request_queue = Queue.Queue()
n = 0
for sel in self.selconv:
n += 1
af = sel[0]
it = sel[1]
# Status bar
if af.get_tag("title") != "Unknown title" and af.get_tag("artist") != "Unknown artist":
self.msg = af.get_tag("artist") + " - " + af.get_tag("title")
elif af.get_uri():
self.msg = af.get_filepath()
self.set_status("Converting " + self.msg + " (file " + str(n) + "/" + str(len(self.selconv)) + ")")
# Riempie la coda caricando le preferenze
request_queue.put([n, sel])
self.init = time.time()
self.progConvert.show()
# Riempita la coda, lancia il thread dell'encoder
self.encoder_thread = Converter(self, self.prefs, sorgente, request_queue)
self.encoder_thread.start()
# Svuota la coda per fermare il thread
for sel in self.selconv:
request_queue.put(None)
self.FileTable.tvSelection.unselect_all()
def download(self):
print "Start downloading " + self.url
#download youtube info
if self.get_youtube_info()==False:
return False
signature = self.download_stream_info["sig"]
url = self.download_stream_info["url"]
download_url = "%s&signature=%s" % (url, signature)
if self.output_file_name=="FF":
dmn = Download( download_url, self.title)
self.output_file_name = self.title
else:
dmn = Download( download_url, self.output_file_name)
dmn.download()
print "\nConverting:\n"
ofile = "result_"+self.output_file_name+"."+self.ofe
print ofile
con = Converter( self.output_file_name, ofile)
con.ffmpeg_converter(self.audio_codec,self.video_codec)
return True
def main():
#SETTINGS
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
settings = Settings.Settings()
results_dir = settings.results_directory + GwData.FOLDER
#TOKENIZE
data = GwData.GwData()
tokenized_docs = WordTokenizer.tokenize(data.documents, min_word_count = 5)
term_freq = TermFrequency.TermFrequency(tokenized_docs)
#tfidf = TfIdf.TfIdf(tokenized_docs)
#NLTK Decision Tree
list_of_dicts = Converter.vector_space_to_dict_list(term_freq.distance_matrix, term_freq.id2Word,
Converter.to_binary)
#list_of_dicts = Converter.vector_space_to_dict_list(tfidf.matrix, tfidf.id2Word)
labels = data.causal_per_document
labelled_data = zip(list_of_dicts, labels)
td_size = int(0.75 * len(labelled_data))
training_data = labelled_data[:td_size]
validation_data = labelled_data[td_size:]
me = nltk.MaxentClassifier.train(training_data, algorithm = "GIS")
#RESULTS
classifications = [me.classify(rcd) for rcd,lbl in validation_data]
results = ResultsHelper.rfp(labels[td_size:], classifications)
print results
#print "EXPLAIN:\n"
#me.explain(condensed_data[0], 100)
#DUMP TO FILE
fName = results_dir + "Causal_Relation_MaxEnt.txt"
handle = open(fName, mode = "w+")
handle.write(results)
handle.close()
#binary_matrix = term_freq.binary_matrix()
#decision_tree = tree.DecisionTreeClassifier(criterion = 'entropy')
#decision_tree.fit(binary_matrix, labels)
# Test with CL1 labels
raw_input("Press Enter to quit")
def appendStats(raw_output, clf, score, k, timeFit, timePredict):
_timeFitLin = clf.time_fit_lin # SS_MSMS
_timeFitGauss = clf.time_fit_gauss # MM:SS
_timeFitOver = clf.time_overhead # MSMS
# _timeTotal = _timeFitLin + _timeFitGauss + _timeFitOver
_timeTotal = timeFit
_score = score
_error = round((1 - _score) * 100, 2)
_timePredict = timePredict ## SS_MSMS
gauss_stat = str(clf.n_gauss) + " (" + str(
round((float(clf.n_gauss) / float(clf.n_gauss + clf.n_lin) * 100), 2)) + "%);"
lin_stat = str(clf.n_lin) + " \t(" + str(
round((float(clf.n_lin) / float(clf.n_gauss + clf.n_lin) * 100), 2)) + "%);"
lin_c = Converter.toPowerOfTen(clf.lin_svc.C) + ";"
gauss_c = Converter.toPowerOfTen(clf.gauss_svc.C) + ";"
gauss_gamma = Converter.toPowerOfTen(clf.gauss_svc.gamma) + ";"
try:
n_gaussSVs = str(clf.gauss_svc.n_support_[0] + clf.gauss_svc.n_support_[1]) + ";"
except AttributeError:
n_gaussSVs = "0;"
# Bring Time data in readable format
# _timeFit = Conversions.secondsToHourMin(_timeTotal)
_timeFitLin = Converter.secondsToSecMilsec(_timeFitLin)
_timeFitGauss = Converter.secondsToMinSec(_timeFitGauss)
_timeFitOver = Converter.secondsToMilsec(_timeFitOver)
_timePredict = Converter.secondsToSecMilsec(_timePredict)
raw_output[0].append(gauss_stat)
raw_output[1].append(lin_stat)
raw_output[2].append(lin_c)
raw_output[3].append(gauss_c)
raw_output[4].append(gauss_gamma)
raw_output[5].append(n_gaussSVs)
raw_output[6].append(str(_timeTotal).replace(".", ",") + "s;")
raw_output[7].append(_timeFitGauss + ";")
raw_output[8].append(_timeFitLin + ";")
raw_output[9].append(_timeFitOver + ";")
raw_output[10].append(_timePredict + ";")
raw_output[11].append(str(_error) + "%;")
raw_output[12].append(str(k) + ";")
return raw_output
def main():
playlist = Playlist("/home/klaxa/Music/test.m3u")
converter = Converter()
converter.encode(playlist.tracks[0])
converter.encode(playlist.tracks[0])
class classXAudioCopy:
# Costruttore della classe classXAudioCopy
def __init__(self):
# Collega il file XML
self.builderXAC = Gtk.Builder()
self.builderXAC.add_from_file(GLADE)
# Collega i segnali
self.builderXAC.connect_signals(self)
# Carica la finestra principale "mainWindow"
self.mainWindow = self.builderXAC.get_object("mainWindow")
self.mainWindow.set_title(WINDOW_TITLE)
self.mainWindow.connect("destroy", lambda on_quit: Gtk.main_quit())
# Carica la statusbar
self.status = self.builderXAC.get_object("statusbar")
# Collega il menu contestuale
self.popupmenu = self.builderXAC.get_object("popupmenu")
# Carica la tabella per la lista dei file (TreeView)
self.FileTable = FileTable(self.builderXAC)
# Visualizza la finestra principale mainWindow
self.mainWindow.show()
self.set_status()
# Toglie il focus al pulsante cmdOpenFile (TODO: scoprire perché ce l'ha)
self.mainWindow.set_focus(None)
# Carica la barra con i tag e la nasconde all'avvio
self.TagBar = TagBar(self.builderXAC)
self.TagBar.hide()
# Aggancia alcuni pulsanti e menu (per renderli sensibili o insensibili)
self.cmdCD = self.builderXAC.get_object("cmdCD")
self.menuCD = self.builderXAC.get_object("menuCD")
self.cmdOpenFile = self.builderXAC.get_object("cmdOpenFile")
self.menuOpenFile = self.builderXAC.get_object("menuOpenFile")
self.cmdOpenFolder = self.builderXAC.get_object("cmdOpenFolder")
self.menuOpenFolder = self.builderXAC.get_object("menuOpenFolder")
self.cmdPlay = self.builderXAC.get_object("cmdPlay")
self.menuPlay = self.builderXAC.get_object("menuPlay")
self.menuPause = self.builderXAC.get_object("menuPause")
self.popPlay = self.builderXAC.get_object("popPlay")
self.popPause = self.builderXAC.get_object("popPause")
self.cmdStop = self.builderXAC.get_object("cmdStop")
self.menuStop = self.builderXAC.get_object("menuStop")
self.popStop = self.builderXAC.get_object("popStop")
self.cmdNext = self.builderXAC.get_object("cmdNext")
self.menuNext = self.builderXAC.get_object("menuNext")
self.cmdPrev = self.builderXAC.get_object("cmdPrev")
self.menuPrev = self.builderXAC.get_object("menuPrev")
self.cmdRewind = self.builderXAC.get_object("cmdRewind")
self.cmdForward = self.builderXAC.get_object("cmdForward")
self.labelTime = self.builderXAC.get_object("labelTime")
self.scaleTime = self.builderXAC.get_object("scaleTime")
self.volumebutton = self.builderXAC.get_object("volumebutton")
self.volumebutton.set_value(0.5)
self.cmdRemove = self.builderXAC.get_object("cmdRemove")
self.menuRemove = self.builderXAC.get_object("menuRemove")
self.cmdPurge = self.builderXAC.get_object("cmdPurge")
self.menuPurge = self.builderXAC.get_object("menuPurge")
self.menuSelectAll = self.builderXAC.get_object("menuSelectAll")
self.menuUnselectAll = self.builderXAC.get_object("menuUnselectAll")
self.cmdRip = self.builderXAC.get_object("cmdRip")
self.menuRip = self.builderXAC.get_object("menuRip")
self.cmdConvert = self.builderXAC.get_object("cmdConvert")
self.menuConvert = self.builderXAC.get_object("menuConvert")
self.menuProperty = self.builderXAC.get_object("menuProperty")
self.menuModify = self.builderXAC.get_object("menuModify")
self.menuPlaylist = self.builderXAC.get_object("menuPlaylist")
self.popProperty = self.builderXAC.get_object("popProperty")
self.popTagger = self.builderXAC.get_object("popTagger")
# Rende insensibili alcuni menu e pulsanti all'avvio
self.set_sensitive(False)
self.cmdRip.set_sensitive(False)
self.cmdConvert.set_sensitive(False)
# Carica la progressbar per la conversione e la nasconde all'avvio
self.progConvert = self.builderXAC.get_object("progressbar")
self.progConvert.hide()
# Crea l'oggetto lista dei file
self.audioFileList = FileList()
# Istanza del player audio
self.player = Player(None, self)
self.player.set_volume(self.volumebutton.get_value())
self.player_bus = self.player.bus
self.player_bus.connect("message::eos", self.on_endPlay)
self.player_bus.connect("message::error", self.on_endError)
# Carica le preferenze
self.prefs = Preferences()
# Funzione che attiva la finestra principale
def main(self):
Gtk.main()
# Funzione che modifica la barra di stato
def set_status(self, text=None):
self.status.show()
con_id = self.status.get_context_id("SB")
if not text:
text = "Ready"
self.mainWindow.set_title(WINDOW_TITLE)
self.status.push(con_id, text)
#print text
while Gtk.events_pending():
Gtk.main_iteration()
# Funzione che rende sensibili/insensibili alcuni menu e pulsanti
def set_sensitive(self, sensitive):
cmd = [
self.cmdPlay,
self.menuPlay,
self.popPlay,
self.menuPause,
self.popPause,
self.cmdNext,
self.menuNext,
self.cmdPrev,
self.menuPrev,
self.cmdRemove,
self.menuRemove,
self.cmdPurge,
self.menuPurge,
self.cmdRewind,
self.cmdForward,
self.cmdConvert,
self.menuConvert,
self.menuSelectAll,
self.menuUnselectAll,
self.menuProperty,
self.menuModify,
self.popProperty,
self.popTagger,
self.menuPlaylist,
self.TagBar
]
if sensitive:
for c in cmd:
c.set_sensitive(True)
elif not sensitive:
for c in cmd:
c.set_sensitive(False)
self.menuRip.set_sensitive(False)
self.cmdRip.set_sensitive(False)
self.cmdStop.set_sensitive(False)
self.menuStop.set_sensitive(False)
self.popStop.set_sensitive(False)
self.scaleTime.set_sensitive(False)
# Evento per l'uscita dal programma
def on_Quit(self, *args):
print "Bye..."
Gtk.main_quit()
# Evento per l"apertura di un file
def on_OpenFile(self, *args):
self.set_status("Adding files...")
# Oggetto di classe FileChooser (False se apre un file)
FC = FileChooser(False)
self.AddFileList(FC)
try:
self.player.stop()
except:
pass
self.cmdPlay.set_stock_id("gtk-media-play")
# Evento per l"apertura di una cartella
def on_OpenFolder(self, *args):
self.set_status("Adding forder...")
# Oggetto di classe FileChooser (True se apre una cartella)
FC = FileChooser(True)
self.AddFileList(FC)
try:
self.player.stop()
except:
pass
self.cmdPlay.set_stock_id("gtk-media-play")
# Evento che apre la finetra informazioni
def on_About(self, *args):
# Oggetto di classe AboutDialog
self.About = AboutDialog()
# Evento che rimuove gli elementi della tabella slezionati
def on_Remove(self, *args):
self.FileTable.remove()
self.on_Stop()
self.cmdPlay.set_stock_id("gtk-media-play")
self.mainWindow.set_title(WINDOW_TITLE)
if len(self.audioFileList.filelist) == 0:
self.set_sensitive(False)
self.cmdConvert.set_sensitive(False)
self.cmdStop.set_sensitive(False)
self.menuStop.set_sensitive(False)
else:
self.set_sensitive(True)
self.cmdConvert.set_sensitive(True)
# Evento che pulisce la tabella
def on_Purge(self, *args):
self.set_status("Purge list...")
self.FileTable.purge()
self.audioFileList.purge()
self.TagBar.purge()
self.TagBar.hide()
self.cmdOpenFile.set_sensitive(True)
self.cmdOpenFolder.set_sensitive(True)
self.set_status()
self.on_Stop()
self.cmdPlay.set_stock_id("gtk-media-play")
self.mainWindow.set_title(WINDOW_TITLE)
self.set_sensitive(False)
self.cmdConvert.set_sensitive(False)
self.cmdRip.set_sensitive(False)
self.progConvert.hide()
# Evento che apre la finestra preferenze
def on_Preferences(self, *args):
dlgPrefs = PreferencesDialog(self.mainWindow, self.prefs)
dlgPrefs.show()
# Evento per la riproduzione di un file
def on_Play(self, *args):
print self.cmdPlay.get_stock_id()
self.cmdStop.set_sensitive(True)
self.menuStop.set_sensitive(True)
self.popStop.set_sensitive(True)
self.scaleTime.set_sensitive(True)
# Se il pulsante indica "play", riproduce la selezione
if self.cmdPlay.get_stock_id() == "gtk-media-play":
# Se il player è pronto, inizia la riproduzione
if self.player.state == "ready":
#Carica la lista dei file selezionati
self.selplay = self.Selection(self.FileTable)
# Riproduce solo il primo file della lista caricata
try:
sel = self.selplay[0]
except IndexError:
sel = None
self.playing_song = sel
if sel:
af = sel[0]
it = sel[1]
if not self.file_exists(af):
return
self.FileTable.tvSelection.unselect_all()
self.FileTable.tvSelection.select_iter(it)
print "Riproduzione di: ", af.get_uri()
self.player.play(af)
if af.get_tag("title") != "Unknown title" and af.get_tag("artist") != "Unknown artist":
msg = af.get_tag("artist") + " - " + af.get_tag("title")
elif af.get_uri():
msg = af.get_filepath()
self.set_status("Playing " + msg)
self.mainWindow.set_title(msg)
self.scaleTime.set_range(0, 1)
self.scaleTime.set_value(0)
# Se è in pausa, riprende la riproduzione
elif self.player.state == "paused":
self.player.carry_on()
if self.player.state == "playing":
self.cmdPlay.set_stock_id("gtk-media-pause")
# Se il pulsante indica "pause", mette in pausa
elif self.cmdPlay.get_stock_id() == "gtk-media-pause":
if self.player.state == "playing":
self.player.pause()
if self.player.state == "paused":
self.cmdPlay.set_stock_id("gtk-media-play")
# Thread per l'avanzamento del tempo di riproduzione
def play_thread(self):
# From http://pygstdocs.berlios.de/pygst-tutorial/seeking.html
print "PLAY_THREAD"
play_thread_id = self.player.play_thread_id
print play_thread_id
print self.player.play_thread_id
Gtk.gdk.threads_enter()
self.labelTime.set_text("00:00 / 00:00")
Gtk.gdk.threads_leave()
while play_thread_id == self.player.play_thread_id:
try:
time.sleep(0.2)
if self.player.duration == -1:
continue
Gtk.gdk.threads_enter()
self.labelTime.set_text("00:00 / " + self.player.duration_str)
Gtk.gdk.threads_leave()
print "OK 1"
break
except:
print "QUERY_IN_CORSO"
pass
time.sleep(0.2)
while play_thread_id == self.player.play_thread_id:
pos_int = self.player.player.query_position(gst.FORMAT_TIME, None)[0]
pos_str = self.player.convert_ns(pos_int)
if play_thread_id == self.player.play_thread_id:
Gtk.gdk.threads_enter()
self.labelTime.set_text(pos_str + " / " + self.player.duration_str)
self.scaleTime.set_value(float(pos_int)/float(self.player.duration))
Gtk.gdk.threads_leave()
time.sleep(0.5)
# Evento che avanza la barra del tempo
def on_adjust_bounds(self, *args):
print "adjust-bound"
self.player.change_position(self.scaleTime.get_value())
# Evento per la modifica del volume
def volume_changed(self, *args):
try:
self.player.set_volume(self.volumebutton.get_value())
except: pass
# Richiamato quando termina la riproduzione di un brano
def on_endPlay(self, player_bus, message):
print "Esecuzione terminata"
self.set_status()
self.mainWindow.set_title(WINDOW_TITLE)
self.cmdStop.set_sensitive(False)
self.menuStop.set_sensitive(False)
self.popStop.set_sensitive(False)
self.scaleTime.set_sensitive(False)
self.labelTime.set_text("00:00 / 00:00")
# Passa al brano successivo
try:
print "Brano successivo"
self.on_Next()
except:
pass
#self.scaleTime.set_value(1)
def on_endError(self, player_bus, message):
err, debug = message.parse_error()
print "Error: %s" % err, debug
self.set_status()
self.mainWindow.set_title(WINDOW_TITLE)
self.cmdStop.set_sensitive(False)
self.menuStop.set_sensitive(False)
self.popStop.set_sensitive(False)
self.scaleTime.set_sensitive(False)
self.labelTime.set_text("00:00 / 00:00")
#self.scaleTime.set_value(0)
# Evento per il menu pausa (serve per distinguere l'azione
# da quello del pulsante play/pause)
def on_menuPause(self, *args):
if self.cmdPlay.get_stock_id() == "gtk-media-pause":
self.on_Play()
# Evento per il menu play (serve per distinguere l'azione
# da quello del pulsante play/pause)
def on_menuPlay(self, *args):
if self.cmdPlay.get_stock_id() == "gtk-media-play":
self.on_Play()
else:
if self.playing_song == self.Selection(self.FileTable):
self.on_Play()
self.on_Play()
else:
self.on_Stop()
self.on_Play()
# Evento per il doppio click su una riga della tabella
# e riproduce la canzone clickata
def on_row_activated(self, *args):
print "RIGA ATTIVATA"
try:
self.player.stop()
self.cmdPlay.set_stock_id("gtk-media-play")
except:
pass
self.on_Play()
# Evento per il click sulla tabella dei file
def on_row_clicked(self, widget, event):
# Apre il menù contestuale
if event.button == 3:
print "TASTO DESTRO"
if self.Selection(self.FileTable):
x = int(event.x)
y = int(event.y)
time = event.time
pthinfo = widget.get_path_at_pos(x, y)
if pthinfo is not None:
path, col, cellx, celly = pthinfo
widget.grab_focus()
widget.set_cursor( path, col, 0)
self.popupmenu.popup( None, None, None, event.button, time)
return True
if event.button == 1:
print "TASTO SINISTRO"
if event.type == Gtk.gdk.BUTTON_PRESS:
print "SINGOLO CLICK"
elif event.type == Gtk.gdk._2BUTTON_PRESS:
print "DOPPIO CLICK"
elif event.type == Gtk.gdk._3BUTTON_PRESS:
print "TRIPLO CLICK"
# Evento per la selezione di una riga della tabella
def on_row_selected(self, *args):
print "RIGA SELEZIONATA"
model, pathlist = self.FileTable.tvSelection.get_selected_rows()
if pathlist:
rowpath = pathlist[0]
it = self.FileTable.listStore.get_iter(rowpath)
for af in self.audioFileList.filelist:
if str(af.pointer) == model.get_string_from_iter(it):
print "SELEZIONATO IL FILE: ", af.get_filepath()
# Evento che ferma la riproduzione
def on_Stop(self, *args):
try:
self.player.stop()
except: pass
self.cmdPlay.set_stock_id("gtk-media-play")
self.set_status()
self.mainWindow.set_title(WINDOW_TITLE)
self.cmdStop.set_sensitive(False)
self.menuStop.set_sensitive(False)
self.popStop.set_sensitive(False)
self.scaleTime.set_value(0)
self.scaleTime.set_sensitive(False)
self.labelTime.set_text("00:00 / 00:00")
# Evento che passa a riprodurre la canzone successiva
def on_Next(self, *args):
model, pathlist = self.FileTable.tvSelection.get_selected_rows()
rowpath = pathlist[0]
self.FileTable.tvSelection.unselect_all()
self.on_Stop()
#self.FileTable.tvSelection.select_path(rowpath)
it = self.FileTable.listStore.get_iter(rowpath)
root_it = self.FileTable.listStore.get_iter_root()
next_it = self.FileTable.listStore.iter_next(it)
if next_it:
self.FileTable.tvSelection.select_iter(next_it)
print "on_Next Successivo"
else:
try:
self.FileTable.tvSelection.select_iter(root_it)
print "on_Next Primo della lista"
except:
pass
self.cmdPlay.set_stock_id("gtk-media-play")
self.labelTime.set_text("00:00 / 00:00")
self.on_Play()
# Evento che passa a riprodurre la canzone precedente
def on_Prev(self, *args):
selection = []
model, pathlist = self.FileTable.tvSelection.get_selected_rows()
rowpath = pathlist[0]
self.FileTable.tvSelection.unselect_all()
self.on_Stop()
prev_pointer = 0
prev_it = None
curr_it = self.FileTable.listStore.get_iter(rowpath)
for af in self.audioFileList.filelist:
if str(af.pointer) == model.get_string_from_iter(curr_it):
prev_pointer = af.pointer - 1
print "af.pointer: ", af.pointer
print "prev_pointer: ", prev_pointer
if prev_pointer > -1:
self.FileTable.tvSelection.select_all()
model, pathlist = self.FileTable.tvSelection.get_selected_rows()
if pathlist:
iterlist = []
for rowpath in pathlist:
try:
iterlist.append(model.get_iter(rowpath))
except ValueError:
pass
for it in iterlist:
if str(prev_pointer) == model.get_string_from_iter(it):
prev_it = it
if prev_it:
self.FileTable.tvSelection.unselect_all()
self.FileTable.tvSelection.select_iter(prev_it)
else:
try:
self.FileTable.tvSelection.select_iter(self.FileTable.listStore.get_iter_root())
except:
pass
self.cmdPlay.set_stock_id("gtk-media-play")
self.labelTime.set_text("00:00 / 00:00")
self.on_Play()
# Evento per l'avanzamento veloce
def on_Forward(self, *args):
self.player.forward()
# Evento per il riavvolgimento veloce
def on_Rewind(self, *args):
self.player.rewind()
# Evento che apre un CD_Audio e carica i tag da freeDB
# se il server è disponibile
def on_CD(self, *args):
self.set_status("Adding Audio CD...")
self.TagBar.purge()
self.CDdata = None
try:
self.audioCD = CDDBReader()
except:
self.set_status("Insert an Audio CD into the drive...")
self.cmdOpenFile.set_sensitive(True)
self.cmdOpenFolder.set_sensitive(True)
self.dlg = WarningDialog(self.mainWindow, NAME + " - Warning", "No disc into the drive. Please insert one...")
return
if self.audioCD.is_audio_cd:
self.audioFileList.purge()
self.FileTable.purge()
self.TagBar.show()
self.cmdPlay.set_stock_id("gtk-media-play")
self.on_Stop()
if self.audioCD.query_status == 409:
self.set_status("No connection to the internet is current available or no server response...")
self.dlg = WarningDialog(self.mainWindow, NAME + " - Warning","No connection to the internet is current available or no server response...")
self.TagBar.entry_tag("Unknow album", "Unknow artist", "Unknow year", "Unknow genre")
for i in range(self.audioCD.disc_id[1]):
n = "%.02d" %(i + 1)
af = AudioFile("cdda://" + n, n)
af.set_tag("track_number", n)
af.set_tag("title", "Track " + n)
#af.frame = self.audioCD.disc_id[i+2]
af.set_filename("Track " + n)
print af.get_tags_as_dict()
self.audioFileList.append(af)
self.set_status("Append " + af.get_filename() + "/" + str(self.audioCD.disc_id[1]))
else:
if type(self.audioCD.query_info).__name__ == "list":
print "E'UNA LISTA"
cds = []
for cd in self.audioCD.query_info:
cds.append([cd["disc_id"], cd["category"], cd["title"]])
self.CDDBSelection = CDDBSelection(self.mainWindow, cds)
selected_cd = int(self.CDDBSelection.selected_cd)
self.audioCD.get_CDDB_tag(self.audioCD.query_status, self.audioCD.query_info[selected_cd])
else:
self.audioCD.get_CDDB_tag(self.audioCD.query_status, self.audioCD.query_info)
self.TagBar.entry_tag(self.audioCD.album, self.audioCD.artist, self.audioCD.year, self.audioCD.cddb_genre)
self.CDdata = {"album": self.audioCD.album,
"artist": self.audioCD.artist,
"year": self.audioCD.year,
"genre": self.audioCD.cddb_genre
}
for song in self.audioCD.song_list:
af = AudioFile("cdda://" + str("%.02d" %(song["track_number"])), song["track_number"])
af.set_tag("track_number", "%.02d" %(song["track_number"]))
af.set_tag("title", song["title"])
af.set_tag("artist", self.audioCD.artist)
af.set_tag("album", self.audioCD.album)
af.set_tag("year", self.audioCD.year)
af.set_tag("genre", self.audioCD.cddb_genre)
af.set_filename("Track " + str("%.02d" %(song["track_number"])))
print af.get_tags_as_dict()
self.audioFileList.append(af)
self.set_status("Append " + af.get_filename() + "/" + str(self.audioCD.disc_id[1]))
# Scrive i file nella tabella
self.FileTable.append(self.audioFileList)
self.set_status()
self.audioCD = None
self.set_sensitive(True)
self.cmdRip.set_sensitive(True)
self.cmdOpenFile.set_sensitive(False)
self.menuOpenFile.set_sensitive(False)
self.cmdOpenFolder.set_sensitive(False)
self.menuOpenFolder.set_sensitive(False)
self.cmdConvert.set_sensitive(False)
self.menuConvert.set_sensitive(False)
else:
self.audioCD = None
return
# Evento che cambia i dati del CD su modifica utente
def on_entry_changed(self, *args):
print "CHANGED"
self.CDdata = {"album": self.TagBar.entryAlbum.get_text(),
"artist": self.TagBar.entryArtist.get_text(),
"year": self.TagBar.entryYear.get_text(),
"genre": self.TagBar.entryGenre.get_text()
}
for af in self.audioFileList.filelist:
af.set_tag("album", self.CDdata["album"])
af.set_tag("artist", self.CDdata["artist"])
af.set_tag("year", self.CDdata["year"])
af.set_tag("genre", self.CDdata["genre"])
self.FileTable.purge()
self.FileTable.append(self.audioFileList)
# Evento che apre la finestra di scelta per il ripping del CD
def on_Rip(self, *args):
try:
from morituri.rip import main as Ripper
except:
self.dlg = WarningDialog(self.mainWindow, NAME + " - Warning",'''Morituri is not available.
Please try 'apt-get install morituri' or
visit http://thomas.apestaart.org/morituri/trac/wiki''')
return
#Apre la finestra di dialogo con le impostazioni
dlgRip = RipDialog(self.mainWindow, self.prefs)
dlgRip.show()
if not dlgRip.response == Gtk.ResponseType.OK:
return
else:
self.set_status("Ripping Audio CD ...")
# Posizione temporanea
import tempfile
tempdir = tempfile.mkdtemp()
# Ripping del CD audio in una directory temporanea
# Argomenti da passare:
# rip_args = ['cd', 'rip', '--output-directory=' + tempdir, '--track-template=%t - %n', '--profile=wav']
# In morituri waveenc non funziona. Bisogna lasciare l'uscita di default in flac
rip_args = ['cd', 'rip', '--output-directory=' + tempdir, '--track-template=%t - %n']
try:
# Avvia l'estrazione
ret = Ripper.main(rip_args)
ret = 0
except:
self.dlg = WarningDialog(self.mainWindow, NAME + " - Warning", "Task exception. Morituri don't work.")
ret = -1
self.set_status()
return
if ret == 0:
self.set_status("Ripping completed...")
# Carica i file da convertire
walk = os.walk(tempdir)
convert_filelist = []
for dirpath, subdir, filenames in walk:
for f in filenames:
if f[-5:] == ".flac":
f = os.path.join(dirpath, f)
convert_filelist.append(AudioFile("file://" + f))
#Carica la lista dei file selezionati
if not bool(int(self.prefs.get_option("save-all-tracks"))):
# Solo i file selezionati
self.selconv = self.Selection(self.FileTable)
else:
# Tutti i file
self.FileTable.tvSelection.select_all()
self.selconv = self.Selection(self.FileTable)
self.FileTable.tvSelection.unselect_all()
if self.selconv:
temp_format = self.prefs.get_option("output-format")
# Inizializza la coda
request_queue = Queue.Queue()
n = 0
for sel in self.selconv:
n += 1
af = sel[0]
it = sel[1]
for convert_file in convert_filelist:
if af.get_tag("track_number") == convert_file.get_filename()[0:2]:
convert_file.set_tags_as_dict(af.get_tags_as_dict())
# Salva non compressi
if not bool(int(self.prefs.get_option("rip-compressed"))) or self.prefs.get_option("output-format") == "wav":
self.prefs.set_option("output-format", "wav")
request_queue.put([n, (convert_file, it)])
self.set_status("Now save uncompressed files...")
elif bool(int(self.prefs.get_option("rip-compressed"))):
request_queue.put([n, (convert_file, it)])
self.set_status("Now save compressed files...")
self.init = time.time()
self.progConvert.show()
# Riempita la coda, lancia il thread dell'encoder
self.encoder_thread = Converter(self, self.prefs, request_queue)
self.encoder_thread.start()
# Svuota la coda per fermare il thread
for sel in self.selconv:
request_queue.put(None)
self.FileTable.tvSelection.unselect_all()
self.set_status("Done...")
# Evento per la conversione dei file audio
def on_Convert(self, *args):
#Apre la finestra di dialogo con le impostazioni
dlgCon = ConverterDialog(self.mainWindow, self.prefs)
dlgCon.show()
if not dlgCon.response == Gtk.ResponseType.OK:
return
#Carica la lista dei file selezionati
if not bool(int(self.prefs.get_option("save-all-tracks"))):
# Solo i file selezionati
self.selconv = self.Selection(self.FileTable)
else:
# Tutti i file
self.FileTable.tvSelection.select_all()
self.selconv = self.Selection(self.FileTable)
self.FileTable.tvSelection.unselect_all()
if self.selconv:
# Inizializza la coda
request_queue = Queue.Queue()
n = 0
for sel in self.selconv:
n += 1
af = sel[0]
it = sel[1]
# Status bar
if af.get_tag("title") != "Unknown title" and af.get_tag("artist") != "Unknown artist":
self.msg = af.get_tag("artist") + " - " + af.get_tag("title")
elif af.get_uri():
self.msg = af.get_filepath()
self.set_status("Converting " + self.msg + " (file " + str(n) + "/" + str(len(self.selconv)) + ")")
# Riempie la coda caricando le preferenze
request_queue.put([n, sel])
self.init = time.time()
self.progConvert.show()
# Riempita la coda, lancia il thread dell'encoder
self.encoder_thread = Converter(self, self.prefs, request_queue)
self.encoder_thread.start()
# Svuota la coda per fermare il thread
for sel in self.selconv:
request_queue.put(None)
self.FileTable.tvSelection.unselect_all()
# Aggiorna la progressbar durante la conversione
def on_ProgressBar(self):
self.progConvert.set_fraction(self.encoder_thread.amount_completed)
if self.encoder_thread.work_complete:
self.progConvert.set_fraction(1)
if self.encoder_thread.queue_complete:
if bool(int(self.prefs.get_option("playlist"))):
self.write_playlist(self.encoder_thread.savepath, self.encoder_thread.playlistname, self.encoder_thread.listsongs)
self.progConvert.set_text("Complete!")
print "Complete!"
self.set_status("Done in " + str(round(time.time() - self.init, 2)) + " seconds")
self.progConvert.set_fraction(1)
else:
self.progConvert.set_text("%d%%" % (self.encoder_thread.amount_completed * 100))
self.set_status("Converting " + self.encoder_thread.msg + \
" (file " + str(self.encoder_thread.n) + "/" + str(len(self.selconv)) + ")" + \
" - " + ("%f" % (round(time.time() - self.init, 2)))[:4] + " seconds")
return not self.encoder_thread.work_complete
# Crea la playlist dei brani convertiti
def write_playlist(self, savepath, playlistname, listsongs):
playlist = open(savepath + "/" + playlistname + ".m3u", "wb")
playlist.writelines(listsongs)
playlist.close()
# Seleziona tutte le righe
def on_SelectAll(self, *args):
self.FileTable.tvSelection.select_all()
# Deseleziona tutte le righe
def on_UnselectAll(self, *args):
self.FileTable.tvSelection.unselect_all()
# Proprietà della canzone
def on_Property(self, *args):
#Carica la lista dei file selezionati
self.selplay = self.Selection(self.FileTable)
# Riproduce solo il primo file della lista caricata
try:
sel = self.selplay[0]
except IndexError:
sel = None
self.playing_song = sel
if sel:
af = sel[0]
it = sel[1]
self.FileTable.tvSelection.unselect_all()
self.FileTable.tvSelection.select_iter(it)
dlgprop = PropertyDialog(self, self.mainWindow, sel)
dlgprop.show()
# Modifica i tag
def on_Tagger(self, *args):
#Carica la lista dei file selezionati
self.selplay = self.Selection(self.FileTable)
# Riproduce solo il primo file della lista caricata
try:
sel = self.selplay[0]
except IndexError:
sel = None
if sel:
af = sel[0]
it = sel[1]
self.FileTable.tvSelection.unselect_all()
self.FileTable.tvSelection.select_iter(it)
dlgtag = TaggerDialog(self, self.mainWindow, sel)
dlgtag.show()
if not dlgtag.response == Gtk.ResponseType.OK:
return
if dlgtag.save_tags:
if dlgtag.save_tags_all:
for af in self.audioFileList.filelist:
af.write_metadata()
if dlgtag.id3v2:
af.write_ID3v2()
else:
selection = self.Selection(self.FileTable)
sel = selection[0]
sel[0].write_metadata()
if dlgtag.id3v2:
sel[0].write_ID3v2()
i = self.audioFileList.filelist.index(sel[0])
self.audioFileList.remove(sel[0].get_uri())
self.audioFileList.filelist.insert(i, AudioFile(sel[0].get_uri()))
elif dlgtag.remove_tags:
if dlgtag.remove_tags_all:
for af in self.audioFileList.filelist:
af.remove_metadata()
else:
selection = self.Selection(self.FileTable)
sel = selection[0]
sel[0].remove_metadata()
i = self.audioFileList.filelist.index(sel[0])
self.audioFileList.remove(sel[0].get_uri())
self.audioFileList.filelist.insert(i, AudioFile(sel[0].get_uri()))
self.FileTable.purge()
self.FileTable.append(self.audioFileList)
# Crea una playlist
def on_Playlist(self, *args):
dlgpl = PlaylistDialog(self, self.mainWindow)
dlgpl.show()
if not dlgpl.response == Gtk.ResponseType.OK:
return
# Restituisce una lista di file audio selezionati
def Selection(self, FileTable):
selection = []
model, pathlist = FileTable.tvSelection.get_selected_rows()
print "pathlist: ", pathlist
if not pathlist:
print "not"
try:
pathlist = [(0,)]
print "pathlist: ", pathlist
except:
pass
if pathlist:
print "pathlist: ", pathlist
iterlist = []
for rowpath in pathlist:
print "rowpath: ", rowpath
try:
iterlist.append(model.get_iter(rowpath))
except ValueError:
pass
print "iterlist: ", iterlist
for it in iterlist:
print "riga da riprodurre", model.get_string_from_iter(it)
for af in self.audioFileList.filelist:
print "af.pointer: ", af.pointer
print "model.get_string_from_iter(iter): ", model.get_string_from_iter(it)
if str(af.pointer) == model.get_string_from_iter(it):
print "sono uguali"
selection.append((af, it))
print "Selection: ", selection
else:
print "non sono uguali"
return selection
# Funzione che apre il selettore file e carica i file scelti
def AddFileList(self, FileChooser):
# Imposta la cartella corrente
try:
if os.path.exists(self.prefs.get_option("last-used-folder")):
FileChooser.set_current_folder(self.prefs.get_option("last-used-folder"))
else:
FileChooser.set_current_folder(os.path.expandvars("$HOME"))
# Eccezione nel caso in cui non sia definita.
# In tal caso la cartella corrente viene settata sulla HOME.
except:
FileChooser.set_current_folder(os.path.expandvars("$HOME"))
# Seleziona la risposta
response = FileChooser.run()
if response == Gtk.ResponseType.OK:
if FileChooser.is_folder:
# Se il percorso restituito è una cartella
# crea una lista con i file audio presenti nella cartella
# e nelle sue sottocartelle.
walk = os.walk(FileChooser.get_current_folder())
# Restituisce una lista con tutti i file
walk_filelist = []
for dirpath, subdir, filenames in walk:
print "dirpath: ", dirpath
print "dirnames: ", subdir
for f in filenames:
f = os.path.join(dirpath, f)
walk_filelist.append(f)
print "listone: ", walk_filelist
# Aggiunge l'uri completo ad ogni file
furi = []
for f in walk_filelist:
for ext in fileext:
if f[-4:] == ext:
furi.append("file://" + str(f))
for l in furi:
print "fpathList: ", l
self.audioFileList.add_list(furi)
else:
# Se il percorso restituito è un file o un elenco di file
filenames = []
print FileChooser.get_filenames()[0]
if FileChooser.get_filenames():
for f in FileChooser.get_filenames():
print "f ", FileChooser.get_filenames()
# Se il percorso restituito è una plaulist "*.m3u"
if f[-4:] == ".m3u":
plist = open(f, "rb").readlines()
for finlist in plist:
if not "#EXT" in finlist:
print re.compile("\n").sub("", finlist)
print "PERCORSO FILE IN PLAYLIST", "file://" + FileChooser.get_current_folder() + "/" + re.compile("\n").sub("", finlist)
filenames.append("file://" + FileChooser.get_current_folder() + "/" + re.compile("\n").sub("", finlist))
else:
filenames.append("file://" + f)
print filenames
self.audioFileList.add_list(filenames)
print "LISTA APPESA ", self.audioFileList.filelist
# Scrive i file nella tabella
self.FileTable.append(self.audioFileList)
elif response == Gtk.ResponseType.CANCEL:
print 'Closed, no files selected'
self.prefs.set_option("last-used-folder", FileChooser.get_current_folder())
FileChooser.hide()
FileChooser.destroy()
self.set_status()
if not self.audioFileList.filelist:
print "LISTA VUOTA"
self.set_sensitive(False)
self.cmdConvert.set_sensitive(False)
else:
self.set_sensitive(True)
self.cmdConvert.set_sensitive(True)
# Funzione che verifica se il file audio esiste
def file_exists(self, af):
if os.path.exists(af.get_filepath()):
return True
elif af.get_uri()[:7] == "cdda://":
return True
else:
dlg = WarningDialog(self.mainWindow, NAME + " - Warning", "The file " + af.get_filepath() + " does not exist in the specified path. Perhaps it was deleted.")
return False
# - zipper (array) - import Converter as C import Post as P import Generator as G import Transform as T m1 = G.cylinder((0, 0, 0), 1, 5, 0., 360., 10., (50, 50, 1)) m1 = C.initVars(m1, 'cellN', 1.) # Set cellN = 2 (interpolated points) to boundary s = T.subzone(m1, (1, m1[3], 1), (m1[2], m1[3], m1[4])) s = C.initVars(s, 'cellN', 2) m1 = T.patch(m1, s, (1, m1[3], 1)) s = T.subzone(m1, (1, 1, 1), (m1[2], 1, m1[4])) s = C.initVars(s, 'cellN', 2) m1 = T.patch(m1, s, (1, 1, 1)) ni = 30 nj = 40 m2 = G.cart((0, 0, 0), (10. / (ni - 1), 10. / (nj - 1), -1), (ni, nj, 1)) m2 = C.initVars(m2, 'cellN', 1.) array = P.zipper([m1, m2], []) C.convertArrays2File([array], 'out.plt')
# One way to import module is using import file name
import Converter
print(Converter.convert("Hello :)"))
# another to import module with specific functions only
from Converter import convert
print(convert("haha :P"))
# - perturbate (array) - import Generator as G import Transform as T import Converter as C a = G.cart((0, 0, 0), (1, 1, 1), (10, 10, 1)) a = T.perturbate(a, 0.1) C.convertArrays2File([a], "out.plt")
# - projectDir (array) - import Geom as D import Converter as C import Generator as G import Transform as T import KCore.test as test # Structure a = D.sphere((0, 0, 0), 1., 20) a = C.initVars(a, 'F', 1) b = G.cart((1.1, -0.1, -0.1), (0.1, 0.1, 0.1), (1, 5, 5)) b = C.initVars(b, 'F', 1) c = T.projectDir([b], [a], (-1., 0, 0), oriented=1) test.testA([a, b] + c, 1) c = T.projectDir([b], [a], (1., 0, 0), oriented=1) test.testA([a, b] + c, 2)
def streamSurf(arrays, b, vector, N=2000, dir=1):
b = Converter.convertArray2Hexa(b)
if (b[3] != 'BAR'): raise TypeError("streamSurf: b must be a BAR.")
coord = b[1]
return post.compStreamSurf(arrays, b, vector, dir, N)
# - patch (array) - import Transform as T import Generator as G import Converter as C import numpy c1 = G.cart((0, 0, 0), (0.01, 0.01, 1), (201, 101, 1)) c2 = G.cart((0, 0, 0), (0.01, 0.01, 1), (51, 81, 1)) c2 = T.rotate(c2, (0, 0, 0), (0, 0, 1), 0.2) c3 = G.cart((0.0, 1., 0), (0.01, 0.01, 1), (101, 1, 1)) c3 = T.rotate(c3, (0, 0, 0), (0, 0, 1), 0.3) # patch a region at given position a = T.patch(c1, c2, position=(1, 1, 1)) # patch some nodes nodes = numpy.arange(20100, 20201, dtype=numpy.int32) b = T.patch(c1, c3, nodes=nodes) C.convertArrays2File([a, b], 'out.plt')
# - reorder -
# Reordonne le bloc selectionne
# 's' sauvegarde le fichier
import Converter as C
import CPlot
import Transform as T
import time
a = C.convertFile2Arrays('fontaine.plt')
CPlot.display(a, mode=1, displayBB=0)
bool = 0
while (bool == 0):
l = -1
CPlot.display(a)
while (l == -1):
l = CPlot.getSelectedZone()
s = CPlot.getKeyboard()
if (s == "s"):
C.convertArrays2File(a, 'out.plt')
import sys
sys.exit()
time.sleep(0.1)
# Reorder suivant le type de zone
z = a[l - 1]
if (len(z) == 5): # structure
ni = z[2]
nj = z[3]
nk = z[4]
if (ni == 1):
# - polyline (array) - import Geom as D import Converter as C a = D.polyline([(0.,0.,0.),(1.,1.,0.),(2.,0.,0.)]) C.convertArrays2File(a, "out.plt")
# - convertFile2Arrays (binary png) -
import Converter as C
a = C.convertFile2Arrays('Data/test.png', 'bin_png')
C.convertArrays2File(a, 'out.plt', 'bin_tp')
# - computeExtraVariable (array) - import Generator as G import Converter as C import Post as P import Transform as T import KCore.test as test a = G.cart((0, 0, 0), (1, 1, 1), (10, 10, 10)) a = C.initVars(a, 'Density', 1.) a = C.initVars(a, 'MomentumX', 1.) a = C.initVars(a, 'MomentumY', 0.) a = C.initVars(a, 'MomentumZ', 0.) a = C.initVars(a, 'EnergyStagnationDensity', 1.) v = P.computeExtraVariable(a, 'Vorticity') m = P.computeExtraVariable(a, 'VorticityMagnitude') q = P.computeExtraVariable(a, 'QCriterion') tau = P.computeExtraVariable(a, 'ShearStress') a = C.node2Center(a) a = C.addVars([a, v, m, q, tau]) test.testA([a], 1) wall = T.subzone(a, (1, 1, 1), (9, 9, 1)) skinFriction = P.computeExtraVariable(wall, 'SkinFriction') wall = C.addVars([wall, skinFriction]) test.testA([wall], 2)
# - setHoleInterpolatedPts (array) -
import Converter as C
import Connector as X
import Generator as G
def sphere(x, y, z):
if x * x + y * y + z * z < 0.5**2: return 0.
else: return 1.
a = G.cart((-1., -1., -1.), (0.1, 0.1, 0.1), (20, 20, 20))
celln = C.node2Center(a)
celln = C.initVars(celln, 'cellN', sphere, ['x', 'y', 'z'])
celln = X.setHoleInterpolatedPoints(celln, depth=1)
C.convertArrays2File([celln], 'out.plt')
# - gapfixer (array) - import Generator as G import Converter as C import Geom as D import KCore.test as test a = D.circle( (0,0,0), 1, N=100 ) a = C.convertArray2Tetra(a); a = G.close(a) b = G.cart((-2.,-2.,0.), (0.1,0.1,1.), (50,50,1)) a1 = G.gapfixer(a, b) test.testA([a1],1) hp = D.point((0.5, 0.5, 0.)) a2 = G.gapfixer(a, b, hp, refine=0) test.testA([a2],2)
# - boolean reorientExternalFaces (array) - import Generator as G import Converter as C import Intersector as XOR a = G.cartHexa((0., 0., 0.), (0.1, 0.1, 0.2), (10, 10, 10)) a = C.convertArray2NGon(a) a = XOR.reorientExternalFaces(a) C.convertArrays2File([a], 'out.plt')
# - integMomentNorm (array) - import Generator as G import Converter as C import Transform as T import Post as P from numpy import * import math res1 = math.pi * 10. res1c = (math.pi - math.pi / 25.) * 10. res2 = 2. res2c = 1.62 # Lit le fichier et le met dans arrays a = G.cylinder((0., 0., 0.), 0.5, 1., 360., 0., 10., (50, 2, 30)) a2 = T.subzone(a, (1, 1, 1), (50, 1, 30)) C.convertArrays2File([a], "new.plt", "bin_tp") # integMoment node2center, nj = 1 ni = a[2] - 1 nj = a[3] - 1 nk = a[4] - 1 dens = ones((1, ni * nj * nk), float64) densa = ['t', dens, ni, nj, nk] res = P.integMomentNorm([a2], [densa], [], (0., 0., 5.)) ## if math.fabs(res[0]-res1) > 1.e-1: ## print "pb in integMomentNodeCenter, nj=1" print(res, res1) del res # integMoment, nj = 1
# - display (array) -
import Generator as G
import CPlot
import Converter as C
def F(x, y):
return x * x + y * y
a = G.cart((0, 0, 0), (1, 1, 1), (18, 28, 1))
a = C.initVars(a, 'F', F, ['x', 'y'])
CPlot.display(a, mode=3, scalarField=0, dim=2, displayIsoLegend=1)
# - center2Node (array) -
import Converter as C
import Generator as G
import KCore.test as test
def F(x, y):
return 2 * x + y
# Non structure TETRA
ni = 30
nj = 40
nk = 12
a = G.cartTetra((0, 0, 0), (10. / (ni - 1), 10. / (nj - 1), 1), (ni, nj, nk))
a = C.initVars(a, 'ro', F, ['x', 'y'])
ac = C.node2Center(a)
an = C.center2Node(ac)
test.testA([an], 1)
# Test sur une liste
ni = 10
nj = 15
nk = 2
b = G.cartTetra((0, 0, 0), (10. / (ni - 1), 10. / (nj - 1), 1), (ni, nj, nk))
b = C.initVars(b, 'ro', F, ['x', 'y'])
bc = C.node2Center(b)
B = C.center2Node([ac, bc])
test.testA(B, 2)
# Non structure TRI
def streamLine(arrays, X0, vector, N=2000, dir=2):
"""Compute a streamline starting from (x0,y0,z0) given
a list of arrays containing 'vector' information.
Usage: streamLine(arrays, (x0,y0,z0), vector, N, dir)"""
# get an (unstructured) array containing all 2D-surface arrays
surf = []
for a in arrays:
elt = 'None'
ni = 2
nj = 2
nk = 2
if (len(a) == 5): # structure
ni = a[2]
nj = a[3]
nk = a[4]
else:
elt = a[3]
mult = (ni - 1) * (nj - 1) * (nk - 1)
add = (ni - 1) * (nj - 1) + (ni - 1) * (nk - 1) + (nj - 1) * (nk - 1)
if ((mult == 0) and (add != 0)) or (elt == 'QUAD') or (elt == 'TRI'):
a = Converter.convertArray2Tetra(a)
surf.append(a)
if surf != []:
try:
import Transform, Generator
except:
raise ImportError(
"streamLine: requires Transform and Generator modules.")
surf = Transform.join(surf)
surf = Generator.close(surf)
# grow 2D arrays
if surf != []:
tol = 1.
inl, modified = growOfEps__(arrays, tol, nlayers=2, planarity=False)
arrays = inl
if (dir == +1):
return post.compStreamLine(arrays, surf, X0, vector, 1., N)
elif (dir == -1):
return post.compStreamLine(arrays, surf, X0, vector, -1., N)
else:
try:
a = post.compStreamLine(arrays, surf, X0, vector, 1., N)
except:
a = 0
try:
b = post.compStreamLine(arrays, surf, X0, vector, -1., N)
except:
b = 0
if (a != 0 and b != 0):
try:
import Transform
except:
return a
b = Transform.reorder(b, (-1, 2, 3))
c = Transform.join(b, a)
return c
elif (b == 0 and a != 0):
return a
elif (a == 0 and b != 0):
return b
else:
raise
# - setDoublyDefinedBC (array) -
import Converter as C
import Connector as X
import Generator as G
a = G.cart((0, 0, 0), (1, 1, 1), (10, 10, 10))
b = G.cart((2.5, 2.5, -2.5), (0.5, 0.5, 0.5), (10, 10, 30))
celln = C.array('cellN', a[2] - 1, a[3] - 1, a[4] - 1)
celln = C.initVars(celln, 'cellN', 1)
indmax = celln[2] * celln[3]
for ind in xrange(indmax):
celln[1][0][ind] = 2
cellnb = C.array('cellN', b[2] - 1, b[3] - 1, b[4] - 1)
cellnb = C.initVars(cellnb, 'cellN', 1)
celln = X.setDoublyDefinedBC(a,
celln, [b], [cellnb], [1, a[2], 1, a[3], 1, 1],
depth=1)
ac = C.node2Center(a)
ac = C.addVars([ac, celln])
C.convertArrays2File([ac], 'out.plt')
def computeIndicatorField(octreeHexa,
indicVal,
nbTargetPts=-1,
bodies=[],
refineFinestLevel=1,
coarsenCoarsestLevel=1):
"""Compute the indicator -1, 0 or 1 for each element of the HEXA octree
with respect to the indicatorValue field located at element centers. The
bodies fix the indicator to 0 in the vicinity of bodies. nbTargetPts
controls the number of points after adaptation.
If refineFinestLevel=1, the finest levels are refined.
If coarsenCoarsestLevel=1, the coarsest levels are coarsened wherever possible.
Returns the indicator field.
Usage: computeIndicatorField(octreeHexa, indicVal, nbTargetPts, bodies, refinestLevel, coarsenCoarsestLevel)"""
try:
import Generator as G
except:
raise ImportError("computeIndicatorField: requires Generator module.")
npts = octreeHexa[1][0].shape[0]
if (nbTargetPts == -1): nbTargetPts = npts
valName = indicVal[0]
nelts = indicVal[2]
indicVal[1] = numpy.absolute(indicVal[1])
indicator = Converter.initVars(indicVal, 'indicator', 0.)
indicator = Converter.extractVars(indicator, ['indicator'])
if bodies != []:
bodies = Converter.convertArray2Tetra(bodies)
indicator = post.enforceIndicatorNearBodies(indicator, octreeHexa,
bodies)
if (refineFinestLevel == 0):
indicator = post.enforceIndicatorForFinestLevel(indicator, octreeHexa)
if (coarsenCoarsestLevel == 1):
indicator = post.enforceIndicatorForCoarsestLevel(
indicator, octreeHexa)
valMin = Converter.getMinValue(indicVal, valName)
epsInf = valMin / 4.
valMax = Converter.getMaxValue(indicVal, valName)
epsSup = valMax * 4.
# calcul de l'indicateur : tous les pts sont raffines (low)
indicator1 = computeIndicatorFieldForBounds(indicator, indicVal,
epsInf / 4., 4. * epsInf)
res = G.adaptOctree(octreeHexa, indicator1)
nptsfin = len(res[1][0])
print 'Number of points for low bound value %g is %d (targetPts=%d)' % (
epsInf, nptsfin, nbTargetPts)
if (nptsfin < nbTargetPts): return indicator1, epsInf / 4., epsInf * 4.
# calcul de l'indicateur : ts les pts sont deraffines
indicator1 = computeIndicatorFieldForBounds(indicator, indicVal, \
epsSup/4., epsSup*4.)
res = G.adaptOctree(octreeHexa, indicator1)
nptsfin = len(res[1][0])
print 'Number of points for high bound value %g is %d (targetPts=%d)' % (
epsSup, nptsfin, nbTargetPts)
if (nptsfin > nbTargetPts):
#print 'Warning: computeIndicator: the number of final points cannot be lower than the target.'
return indicator1, epsSup / 4., epsSup * 4.
# dichotomie
count = 0
Delta = nbTargetPts
diffmax = 1.e-8 * nbTargetPts / max(Delta, 1e-6)
diff = diffmax + 1.
while (count < 100 and Delta > 0.02 * nbTargetPts and diff > diffmax):
eps = 0.5 * (epsInf + epsSup)
#print 'epsInf =', epsInf, ' | epsSup = ', epsSup
indicator1 = computeIndicatorFieldForBounds(indicator, indicVal,
eps / 4., 4. * eps)
res = G.adaptOctree(octreeHexa, indicator1)
nptsfin = len(res[1][0])
if (nptsfin > nbTargetPts): epsInf = eps
else: epsSup = eps
Delta = abs(nbTargetPts - nptsfin)
diffmax = 1.e-8 * nbTargetPts / max(Delta, 1e-6)
diff = abs(epsSup - epsInf)
count += 1
print 'Number of points for bound value %g is %d (targetPts=%d)' % (
eps, nptsfin, nbTargetPts)
return indicator1, eps / 4., eps * 4.
# - convertFile2Arrays (fmt v3d) -
# - convertArrays2File (fmt v3d) -
import Converter as C
# Lit le fichier in.plt dans arrays
arrays = C.convertFile2Arrays("infmt.v3d", "fmt_v3d")
# Sauvegarde la liste au format fmt_v3d
C.convertArrays2File(arrays, "outfmt.v3d", "fmt_v3d")
# - snapSharpEdges (array) - import Generator as G import Converter as C import Geom as D # polylines with sharp angles s = D.polyline([(0.2, 0, 0), (1, 1, 0), (2.5, 1, 0), (0.2, 0, 0)]) # Regular cartesian grid h = 0.1 ni = 30 nj = 20 nk = 1 b = G.cart((-0.5, -0.5, 0), (h, h, 1.), (ni, nj, nk)) b = G.snapSharpEdges(b, [s], h) C.convertArrays2File([b, s], 'out.plt')
# - convexify any concave polygon in the mesh (array) -
import Intersector as XOR
import Converter as C
import KCore.test as test
M1 = C.convertFile2Arrays('boolNG_M1.tp')
M1 = C.convertArray2NGon(M1[0])
M2 = C.convertFile2Arrays('boolNG_M2.tp')
M2 = C.convertArray2NGon(M2[0])
tol = -0.5e-3
m = XOR.booleanMinus(M1, M2, tol, preserve_right=1, solid_right=1, agg_mode=1)
#C.convertArrays2File([m], 'i.plt')
m = XOR.agglomerateNonStarCells(m)
test.testA(m, 1)
#!/usr/bin/env python
# coding: utf-8
r"""bezier (array)"""
import Geom as D
import Converter as C
import Generator as G
# Bezier 1D
pts = D.polyline([(0., 0., 0.), (0., 1., 0.), (2., 1., 0.), (2., 0., 0.),
(4., -1., 0.), (5., 6., 0.)])
# With a specified number of points
a = D.bezier(pts, N=100)
# With a specified point density
b = D.bezier(pts, density=10.)
C.convertArrays2File([pts, a, b], 'out.plt')
# Bezier 2D
ni = 2
nj = 3
a = G.cart((0, 0, 0), (1, 1, 1), (ni, nj, 1))
C.setValue(a, (1, 1, 1), [1., 1., 2.])
C.setValue(a, (1, 2, 1), [1., 2., 4.])
C.setValue(a, (1, 3, 1), [1., 3., 2.])
C.setValue(a, (2, 1, 1), [2., 1., 2.])
C.setValue(a, (2, 2, 1), [2., 2., 5.])
C.setValue(a, (2, 3, 1), [2., 3., 2.])
b = D.bezier(a, density=10.)
C.convertArrays2File([a] + [b], 'out2.plt')
def train():
#SETTINGS
best_n_words = 10000
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
settings = Settings.Settings()
results_dir = settings.results_directory + "Chicago/Files"
#TOKENIZE
xs = SentenceData.SentenceData()
tokenizer = WordTokenizer.WordTokenizer(min_word_count = 5)
tokenized_docs = tokenizer.tokenize(xs.documents)
term_freq = TermFrequency.TermFrequency(tokenized_docs)
#NLTK Decision Tree
list_of_dicts = Converter.vector_space_to_dict_list(term_freq.distance_matrix, term_freq.id2Word, to_binary)
#Number of unique documents
unique_doc_count = len(xs.documents)
for smCode in xs.sm_codes[1:]: # Skip the first (A code)
try:
print "{0} - Processing smCode: {1}".format(str(datetime.datetime.now()), smCode)
labels = xs.labels_for(smCode)
num_docs_for_code = len(xs.sentences_for_code(smCode))
print "#Docs for code: {0}".format(num_docs_for_code)
relative_word_frequency = DocumentFrequency.document_frequency_ratio(list_of_dicts, labels, lambda l: l == 1)
condensed_data = extract_best_n_words(relative_word_frequency, best_n_words, list_of_dicts)
training_data = zip(condensed_data, labels)
dt = nltk.DecisionTreeClassifier.train(training_data)
results = "Num Words Used: " + str(best_n_words) + "\n"
results += smCode + "\n\n"
results += "PSEUDOCODE:\n"
results += dt.pseudocode(depth = 1000) + "\n"
error = dt.error(training_data)
results += "ERROR: " + str(error * 100) + "%\n\n"
pct_docs_for_code = num_docs_for_code / float(unique_doc_count) * 100.0
results += "Docs for code: {0}%\n".format(pct_docs_for_code)
fName = results_dir + smCode + ".txt"
handle = open(fName, mode = "w+")
handle.write(results)
handle.close()
print results
except IOError as e:
print str(e)
#binary_matrix = term_freq.binary_matrix()
#decision_tree = tree.DecisionTreeClassifier(criterion = 'entropy')
#decision_tree.fit(binary_matrix, labels)
# Test with CL1 labels
raw_input("Press Enter to quit")
def on_Rip(self, *args):
try:
from morituri.rip import main as Ripper
except:
self.dlg = WarningDialog(self.mainWindow, NAME + " - Warning",'''Morituri is not available.
Please try 'apt-get install morituri' or
visit http://thomas.apestaart.org/morituri/trac/wiki''')
return
#Apre la finestra di dialogo con le impostazioni
dlgRip = RipDialog(self.mainWindow, self.prefs)
dlgRip.show()
if not dlgRip.response == Gtk.ResponseType.OK:
return
else:
self.set_status("Ripping Audio CD ...")
# Posizione temporanea
import tempfile
tempdir = tempfile.mkdtemp()
# Ripping del CD audio in una directory temporanea
# Argomenti da passare:
# rip_args = ['cd', 'rip', '--output-directory=' + tempdir, '--track-template=%t - %n', '--profile=wav']
# In morituri waveenc non funziona. Bisogna lasciare l'uscita di default in flac
rip_args = ['cd', 'rip', '--output-directory=' + tempdir, '--track-template=%t - %n']
try:
# Avvia l'estrazione
ret = Ripper.main(rip_args)
ret = 0
except:
self.dlg = WarningDialog(self.mainWindow, NAME + " - Warning", "Task exception. Morituri don't work.")
ret = -1
self.set_status()
return
if ret == 0:
self.set_status("Ripping completed...")
# Carica i file da convertire
walk = os.walk(tempdir)
convert_filelist = []
for dirpath, subdir, filenames in walk:
for f in filenames:
if f[-5:] == ".flac":
f = os.path.join(dirpath, f)
convert_filelist.append(AudioFile("file://" + f))
#Carica la lista dei file selezionati
if not bool(int(self.prefs.get_option("save-all-tracks"))):
# Solo i file selezionati
self.selconv = self.Selection(self.FileTable)
else:
# Tutti i file
self.FileTable.tvSelection.select_all()
self.selconv = self.Selection(self.FileTable)
self.FileTable.tvSelection.unselect_all()
if self.selconv:
temp_format = self.prefs.get_option("output-format")
# Inizializza la coda
request_queue = Queue.Queue()
n = 0
for sel in self.selconv:
n += 1
af = sel[0]
it = sel[1]
for convert_file in convert_filelist:
if af.get_tag("track_number") == convert_file.get_filename()[0:2]:
convert_file.set_tags_as_dict(af.get_tags_as_dict())
# Salva non compressi
if not bool(int(self.prefs.get_option("rip-compressed"))) or self.prefs.get_option("output-format") == "wav":
self.prefs.set_option("output-format", "wav")
request_queue.put([n, (convert_file, it)])
self.set_status("Now save uncompressed files...")
elif bool(int(self.prefs.get_option("rip-compressed"))):
request_queue.put([n, (convert_file, it)])
self.set_status("Now save compressed files...")
self.init = time.time()
self.progConvert.show()
# Riempita la coda, lancia il thread dell'encoder
self.encoder_thread = Converter(self, self.prefs, request_queue)
self.encoder_thread.start()
# Svuota la coda per fermare il thread
for sel in self.selconv:
request_queue.put(None)
self.FileTable.tvSelection.unselect_all()
self.set_status("Done...")
# - getInCircleMap (array) - import Geom as D import Generator as G import Converter as C a = D.sphere((0, 0, 0), 1, 50) a = C.convertArray2Tetra(a) n = G.getInCircleMap(a) n = C.center2Node(n) n = C.addVars([a, n]) C.convertArrays2File([n], "out.plt")
def train():
#SETTINGS
cv_folds = 10
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
settings = Settings.Settings()
results_dir = settings.results_directory + GwData.FOLDER
#TOKENIZE
xs = GwData.GwData()
tokenized_docs = WordTokenizer.tokenize(xs.documents, min_word_count = 5)
tfidf = TfIdf.TfIdf(tokenized_docs)
lsa = Lsa.Lsa(tfidf, 300)
#NLTK SVM linear kernel
xs = Converter.vector_space_to_dict_list(lsa.distance_matrix, lsa.id2Word, fn_dict_creator = lambda : defaultdict(float))
total_recall, total_precision, total_f1, total_accuracy = 0.0, 0.0, 0.0, 0.0
all_results = ""
processed_code_count = 0
def create_maxent(xs, ys):
td = zip(xs, ys)
return nltk.MaxentClassifier.train(td, algorithm='GIS', trace = 2, max_iter = 10)
def classify(me, xs):
return me.batch_classify(xs)
#MIN_CODE_COUNT = 5
MIN_CODE_COUNT = 1
codes = [c for c in xs.sm_codes
# Exclude pure vague codes
if c != "v" and
# Exclude doc codes. Need whole doc to classify them
not c.startswith("s")]
for code in codes:
code_count = xs.sm_code_count[code]
if code_count <= MIN_CODE_COUNT:
continue
processed_code_count += 1
labels = xs.labels_for(code)
recall, precision, f1_score, accuracy = cross_validation_score_generic(xs, labels, create_maxent, classify, cv_folds, class_value = 1.0)
results = "Code: {0} Count: {1}, Recall: {2}, Precision: {3}, F1: {4}\n".format(code.ljust(10), code_count, recall, precision, f1_score)
all_results += results
total_recall += recall
total_precision += precision
total_f1 += f1_score
total_accuracy += accuracy
print results,
#num_codes = len(xs.sm_codes)
num_codes = processed_code_count
result = "AGGREGATE\n\t Recall: {0}, Precision: {1}, F1: {2}, Accuracy {3}\n".format(total_recall / num_codes, total_precision / num_codes, total_f1 / num_codes, total_accuracy / num_codes)
all_results += result
print result
#DUMP TO FILE
fName = results_dir + "Code_Classify_MaxEnt.txt"
handle = open(fName, mode = "w+")
handle.write(all_results)
handle.close()
raw_input("Press Enter to quit")
# Variables a calculer
# --------------------
vars = [
'Pressure', 'VelocityX', 'VelocityZ', 'VelocityMagnitude', 'Temperature',
'Entropy', 'Enthalpy', 'Mach', 'ViscosityMolecular', 'PressureStagnation',
'TemperatureStagnation'
]
# test sur un array avec variables conservatives
# ----------------------------------------------
ni = 30
nj = 40
m = G.cart((0, 0, 0), (10. / (ni - 1), 10. / (nj - 1), 1), (ni, nj, 2))
c1 = C.array('ro,rou,rov,row,roE', ni, nj, 2)
c1 = C.initVars(c1, 'ro', 1.5)
c1 = C.initVars(c1, 'rou', 2.)
c1 = C.initVars(c1, 'rov', 3.)
c1 = C.initVars(c1, 'row', 6.)
c1 = C.initVars(c1, 'roE', 1.e5)
a1 = C.addVars([m, c1])
P._computeVariables2(a1, vars, rgp=12.5)
test.testA([a1], 1)
# test sur un array avec variables primitives
# -------------------------------------------
c2 = C.array('ro,u,v,w,T', ni, nj, 2)
c2 = C.initVars(c2, 'ro', 1.)
c2 = C.initVars(c2, 'u', 1.)
# - extractVars (array) - import Generator as G import Converter as C a = G.cart((0,0,0), (1,1,1), (10,10,10)) a = C.initVars(a, 'F=2.') # Var defined by a string r = C.extractVars(a, 'F') # Vars defined by a list r = C.extractVars(a, ['x','y']) C.convertArrays2File(r, 'out.plt')
# - coarsen (array) -
import Post as P
import Converter as C
import Generator as G
import Transform as T
# coarsen all cells of a square
ni = 21
nj = 21
nk = 11
hi = 2. / (ni - 1)
hj = 2. / (nj - 1)
hk = 1. / (nk - 1)
m = G.cart((0., 0., 0.), (hi, hj, hk), (ni, nj, nk))
hi = hi / 2
hj = hj / 2
hk = hk / 2
m2 = G.cart((0., 0., 0.), (hi, hj, hk), (ni, nj, nk))
m2 = T.subzone(m2, (3, 3, 6), (m[2] - 2, m[3] - 2, 6))
m2 = T.translate(m2, (0.75, 0.75, 0.25))
m2 = T.perturbate(m2, 0.51)
tri = G.delaunay(m2)
npts = tri[2].shape[1]
indic = C.array('indic', npts, 1, 1)
indic = C.initVars(indic, 'indic', 1)
sol = P.coarsen(tri, indic, argqual=0.25, tol=1.e6)
C.convertArrays2File([tri, sol], 'out.plt')
# - projectAllDirs (array) - import Geom as D import Converter as C import Generator as G import Transform as T import KCore.test as test # Structure a = D.sphere((0, 0, 0), 1., 20) a = C.initVars(a, 'F', 1) b = G.cart((1.1, -0.1, -0.1), (0.1, 0.1, 0.1), (1, 5, 5)) n = G.getNormalMap(b) n = C.center2Node(n) C._addVars([b, n]) b = C.initVars(b, 'F', 1) c = T.projectAllDirs([b], [a], ['sx', 'sy', 'sz']) test.testA(c, 1) # Non structure a = D.sphere((0, 0, 0), 1., 20) a = C.initVars(a, 'F', 1) b = G.cartTetra((1.1, -0.1, -0.1), (0.1, 0.1, 0.1), (1, 5, 5)) n = G.getNormalMap(b) n = C.center2Node(n) C._addVars([b, n]) b = C.initVars(b, 'F', 1) c = T.projectAllDirs([b], [a], ['sx', 'sy', 'sz']) test.testA(c, 2) a = C.convertArray2Tetra(a) b = G.cartTetra((1.1, -0.1, -0.1), (0.1, 0.1, 0.1), (1, 5, 5))
# - maximizeBlankedCells (array) -
import Converter as C
import Connector as X
import Generator as G
def F(x,y):
if (x+y<1): return 1
else: return 2
Ni = 50; Nj = 50
a = G.cart((0,0,0),(1./(Ni-1),1./(Nj-1),1),(Ni,Nj,1))
a = C.initVars(a, 'cellN', F, ['x','y'])
a = X.maximizeBlankedCells(a, 2)
C.convertArrays2File([a], 'out.plt')
# - polyC1Mesher (array) -
import Converter as C
import Generator.PolyC1 as GP
import Generator as G
import Transform as T
# Read geometry from svg file
a = C.convertFile2Arrays('Data/curve.svg', density=1)[0]
a = T.homothety(a, (0, 0, 0), 0.01)
a = T.reorder(a, (1, 2, 3))
h = 0.2
hp = 0.001
density = 10.
splitCrit = 2.
m = GP.polyC1Mesher(a, h, hp, density, splitCrit)
for i in m[0]:
v = G.getVolumeMap(i)
min = C.getMinValue(v, 'vol')
if min <= 0:
print('negative volume detected.')
C.convertArrays2File(m[0], 'out.plt')
def get_binary_data(self, distance_matrix, id2word):
# Get binary data
return Converter.vector_space_to_dict_list(distance_matrix, id2word, Converter.to_binary)
