def nn_analysis(self): if not os.path.isfile( self.file.split("/healthy")[0] + "/manual/" + self.file.split(".")[0][-4:] + '.tif'): print( "There's no original mask to compare! Analysis cannot be performed." ) return self.nn_analysis = Analysis() epochs = [25, 50, 75, 100] squared_errors = [] for epoch in epochs: self.epochs = epoch self.nn_train() self.nn_predict() squared_error = self.nn_analysis.mean_squared_error( self.predicted_original, self.predicted) squared_errors.append([epoch, squared_error]) print(squared_errors) file = open('squared_errors.txt', 'a') file.write(self.file) for error in squared_errors: file.write("epoch: " + str(error[0]) + "\t error: " + str(error[1]) + "\n") file.write("\n") file.close()
def test_iter(self): x = [] y = [] self.var_iter_checkbox.set(True) self.pts_transformation.alpha = 2 self.pts_transformation.detectors_amount = 99 self.pts_transformation.width = 180 * 2 self.filter_props.gamma = 2.4 self.filter_props.gauss = 1.0 self.pts_transformation.generate_all_positions(self.input_picture) is_end = False i = 0 while not is_end: self.sinogram, is_end = self.pts_transformation.make_sinogram_iter( self.input_picture) self.display_picture(Image.fromarray(self.sinogram), 'sinogram') self.restored_picture = self.pts_transformation.restore_picture( self.sinogram, len(self.input_picture), self.filter_props) self.display_picture(Image.fromarray(self.restored_picture), 'output') self.root.update_idletasks() mse = Analysis.mean_squared_error(self.input_picture, self.restored_picture) x.append(i) y.append(mse) i += 1 print("Iter =", i, "error =", mse) Analysis.draw_plot(x, y, "Iteracja", "Błąd średniokwadratowy", "iter")
def run_truss_design2(): A = Analysis() c = np.array([[1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0], [0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0], [0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0]]) sx = np.array([[1, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]) sy = np.array([[0, 1, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]) x = np.array([0, 6.5, 13, 20.5, 28, 0, 6.5, 13, 20.5, 28]) y = np.array([0, 0, 0, 0, 0, 6.5, 6.5, 6.5, 6.5, 6.5]) x = x.reshape(1, 10) y = y.reshape(1, 10) l = np.array( [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -50, 0, 0, 0, 0, 0, 0, 0]) l = l.reshape(20, 1) A.set_truss_design(c, sx, sy, x, y, l) A.construct_A_mat() A.print_output() A.print_formatted_per_mem()
def neural_network(self): """This function runs the neural network process for the displayed image""" try: if self.image_object.file_type == ImageType.JPG or self.image_object.file_type == ImageType.PNG: predict = Net.testImage(self.image_object.get_file_path()) if predict == 'normal': prediction = 'Normal' else: prediction = 'COVID-19' if self.analysis is None: self.analysis = Analysis(slices_number=self.image_object.total_slice_number) self.add_result_to_analysis_neural_network(prediction, self.image_object.get_current_slice_number_to_show()) logging.debug('Added neural network result to reports: ') else: prediction = "Network accepts only jpg or png files!" popup = Popup(title='Result', content=Label(text=prediction), size=(400, 400), size_hint=(None, None)) popup.open() except Exception as error: logging.error("Neural network classification: " + str(error)) self._error_popup = ErrorPopup(message=str(error))
def train_evaluate(search_params): hyperparameters = {} pick_kwargs = {} for k in list(search_params.keys()): if k in ['w_dfh', 'w_sharpe', 'w_100d', 'v_100d', 'v_dfh', 'v_rfl']: pick_kwargs[k] = search_params[k] else: hyperparameters[k] = search_params[k] hyperparameters['pick_kwargs'] = pick_kwargs print('------------') print(json.dumps(hyperparameters, indent=2, sort_keys=True)) sim = Sim(neptune=neptune, period='2y', timedelay=100, window=100, timestep=1, budget=5000, stockPicks=5, avoidDowntrends=True, sellAllOnCrash=False, **hyperparameters) stats = sim.run() analysis = Analysis(neptune=neptune, stats=stats, positions=sim.portfolio.holdings, prices=sim.downloader.prices) #analysis.chart() output, advanced_stats, obj_stats = analysis.positionStats() for k in list(obj_stats.keys()): neptune.log_metric(k, obj_stats[k]) print(output) #neptune.log_artifact('data/output_1y.pkl') sharpe = analysis.sharpe() stats = sim.portfolio.summary() if math.isnan(sharpe) or math.isinf(sharpe) or sharpe <= -2 or sharpe >= 5: sharpe = -5 #neptune.log_metric('sharpe', sharpe) #neptune.log_metric('start_value', 5000) #neptune.log_metric('end_value', stats['total_value']) report = { 'hyperparameters': hyperparameters, 'sharpe': sharpe, 'end_value': stats['total_value'], 'gains': (stats['total_value'] - 5000.0) / 5000.0 } neptune.log_text('report', json.dumps(report, indent=2, sort_keys=True)) return sharpe
def nn_confusion(self): self.nn_analysis = Analysis() path = self.file.split(".") name = path[0].split("/")[-1] original = io.imread(Sample.output_path + name + Sample.output_extension, as_grey=True) self.nn_analysis.confusion(self.predicted, original)
def on_analysis(): dateFrom = _getParam('from', '2011') dateTo = _getParam('to', '2018') ccy = _getParam('ccy', 'GBP') analysis = Analysis(dateFrom, dateTo, ccy) results = analysis.YearlySpend() yearTotals = analysis.yearTotals() return (render_template('analysis.html', yearly_spend = results['salary'], reimbursements=results['reimbursements'], expenses=results['expenses'], withholding=results['withholding'], year_totals=yearTotals, date_from=dateFrom, date_to=dateTo, date_range = analysis.DateRange(), ccy=ccy))
def analyze(): b = Budget() b.add(i, t, d, e) b.report() m = Metrics(i, b, e, d, a) m.calculate() m.report() ana = Analysis(p, i, d, b, e, a, m) ana.do_all()
def __init__(self, *args, **kwargs): super(RootWidget, self).__init__(*args, **kwargs) try: self.image_object = CTJpgImage(GUI_FOLDER, START_IMAGE) self.examination_type = ExaminationType.CT # new analysis initialization self.analysis = Analysis(slices_number=self.image_object.total_slice_number) except Exception as error: logging.critical("Init root widget: " + str(error)) self._error_popup = ErrorPopup(message=str(error))
def __init__(self): Analysis.__init__(self) self.data = pd.read_sql(session.query(covidData).__str__(), con=engine) self.data.columns = [ 'SNo', 'ObservationDate', 'Province/State', 'Country/Region', 'Last Update', 'Confirmed', 'Deaths', 'Recovered' ] self.plotOptions = [ "line", "bar", "barh", "hist", "box", "density", "area", "scatter" ]
def main(argv): if len(argv) == 2: attackType = argv[1].strip() else: attackType = "sql" sa = Analysis(7474) query = sa.prepareQueryStatic(attackType) print('the query is ') print(query) result, elapsed_time = sa.runTimedQuery(query) print(result)
def test_simple_crow_score_regression(self): data_set = self.dataImporter.import_all_data( self.test_photos_csv_file_path, self.photos_path) results = Learning.simple_crow_score_regression(data_set, epochs=1, batch_size=2) Analysis.store_raw_result(self.result_path, results) Analysis.process_result(self.result_path)
def use_Analysis(n, k): analysis = Analysis() start = time.time() all_solutions = analysis.get_analysis(n, k) end = time.time() average = (end - start) / (k**n) print("k = " + str(k)) for (key, value) in all_solutions: print(str(key) + ": " + str(value) + "%") print("total time: " + str(end - start)) print("average time: " + str(average)) analysis.visualize(all_solutions, k)
def main(argv): attackType = argv[1].strip() sa = Analysis(7474) query = sa.prepareQueryStatic(attackType) print('the query is ') print(query) result, elapsed_time = sa.runTimedQuery(query) print(result) writeToFile(result, elapsed_time, attackType) result, elapsed_time = sa.runTimedQuery("g.V().includeMap()") writeIncludeMapToFile(result, elapsed_time)
def populate_stats_table(self): self.experimentStatsTable.setRowCount(len(self.experiment.animal_list.keys())) for m, mouse in enumerate(sorted(list(self.experiment.animal_list.keys()))): this_mouse = self.experiment.animal_list[mouse] id = QtWidgets.QTableWidgetItem(this_mouse.id) total_trials = QtWidgets.QTableWidgetItem(str(Analysis.n_trials_performed(this_mouse))) trials_last24h = QtWidgets.QTableWidgetItem(str(Analysis.n_trials_last_24(this_mouse))) self.experimentStatsTable.setItem(m, 0, id) self.experimentStatsTable.setItem(m, 1, total_trials) self.experimentStatsTable.setItem(m, 2, trials_last24h)
class ReportWriter(object): def __init__(self, config, logger): self.analysis = Analysis(config.get_value("SHAREABLE", "trade_log_file_name")) self.outfn = config.get_value("SHAREABLE", "stat_file_name") self.logger = logger def write(self): report_text = "" max_mo_length = len(str(self.analysis.max_markout_period())) max_ticker_length = max([len(x) for x in self.analysis.get_tickers()]) + 2 out_cols = ["Markout Period", "Ticker", "Trade Count", "Return mu", "Return tstat", "Return sharpe"] header = ["{item:>{item_width}}".format(item=col, item_width=len(col)) for col in out_cols] report_text += "\t".join(header) + "\n" for mo_period in self.analysis.get_mo_periods(): for ticker in self.analysis.get_tickers(): out = { 'Markout Period' : mo_period, 'Ticker' : ticker, 'Trade Count' : self.analysis.count(mo_period, ticker), 'Return mu' : "{:0.4f}".format(self.analysis.mean(mo_period, ticker)), 'Return tstat' : "{:0.2f}".format(self.analysis.tstat(mo_period, ticker)), 'Return sharpe' : "{:0.2f}".format(self.analysis.sharpe(mo_period, ticker)) } output = [] for column in out_cols: if column in out: output.append( "{item:>{item_width}}".format(item=out[column], item_width=len(column)) ) report_text += "\t".join(output) + "\n" report_text += "\n" with open(self.outfn, 'w') as f: f.write(report_text) self.logger.info("Report written to " + self.outfn)
def display_group_performance(self): n_longest = 0 all_performance = list() bin_size = int(self.binSizeSpin.value()) for animal_id in self.parent.experiment.animal_list.keys(): animal = self.parent.experiment.animal_list[animal_id] if animal_id != 'default': this_performance = Analysis.binned_performance(animal, bin_size) all_performance.append(this_performance) if len(this_performance) > n_longest: n_longest = len(this_performance) performance_matrix = np.empty((len(self.parent.experiment.animal_list)-1, n_longest)) performance_matrix[:] = np.nan for p, perf in enumerate(all_performance): performance_matrix[p][0:len(perf)] = perf av_performance = np.nanmean(performance_matrix, 0) std_performance = np.nanstd(performance_matrix, 0) self.groupPerformanceView.plotItem.clear() self.groupPerformanceView.plotItem.plot(av_performance) self.groupPerformanceView.plotItem.plot(av_performance + std_performance, pen='m') self.groupPerformanceView.plotItem.plot(av_performance - std_performance, pen='m') # Guide lines self.groupPerformanceView.plotItem.plot(np.ones(len(av_performance)) * 0.5, pen='r') self.groupPerformanceView.plotItem.plot(np.ones(len(av_performance)) * 0.8, pen='g') self.groupPerformanceView.setYRange(-0.1, 1.1)
def __init__(self): """ Initializes a new SMACrossOverDelayed object. @rtype: None """ # Note: Each candlestick represents 1 minute self.crossOverDurationShorter = 15 # SMA duration 1 (SHORTER) self.crossOverDurationLonger = 50 # SMA duration 2 (LONGER) self.baseLongPosition = 600 # base long position size self.baseShortPosition = 600 # base short position size self.crossOverDelayForLongTrades = 3 # number of crossover ticks before executing a long position self.crossOverDelayForShortTrades = 3 # number of crossover ticks before executing a long position self.analyzer = Analysis.getInstance( ) # get the singleton instance of Analysis self.data = Data.getInstance() # get the singleton instance of Data self.smaShorter = None # shorter-term SMA object self.smaShorterList = None # list of shorter-term SMA values self.smaLonger = None # longer-term SMA object self.smaLongerList = None # list of longer-term SMA values self.strategyName = "SMA Crossover(" + str(self.crossOverDurationShorter) + "," + \ str(self.crossOverDurationLonger) + ")" + " D=" + \ str(self.crossOverDelayForLongTrades)
def graph(): if request.method == 'GET': return render_template('Graph.html') elif request.method == 'POST': x = int(request.form['graph']) Analysis(x) #.selection(x) time.sleep(5) return render_template('Images.html')
def test_detectors(self): detectors = np.arange(3, 102, 4) x = [] y = [] self.pts_transformation.alpha = 2 self.pts_transformation.width = 180 * 2 for i in detectors: self.pts_transformation.detectors_amount = i self.refresh() mse = Analysis.mean_squared_error(self.input_picture, self.restored_picture) print("Detectors =", i, "error =", mse) self.root.update_idletasks() x.append(i) y.append(mse) Analysis.draw_plot(x, y, "Liczba detektorów", "Błąd średniokwadratowy", "detectors")
def handle(self): data = self.request.recv(BUF_SIZE) data = data.decode() print(data) analysis_data = Analysis().analysis(data) print(str(analysis_data).encode()) self.request.send(str(analysis_data).encode()) return
def test_width(self): widths = np.arange(5, 181, 5) x = [] y = [] self.pts_transformation.alpha = 2 self.pts_transformation.detectors_amount = 99 for i in widths: self.pts_transformation.width = i * 2 self.refresh() mse = Analysis.mean_squared_error(self.input_picture, self.restored_picture) print("Width =", i, "error =", mse) self.root.update_idletasks() x.append(i) y.append(mse) Analysis.draw_plot(x, y, "Kąt rozwarcia stożka [°]", "Błąd średniokwadratowy", "width")
def test_alpha(self): alphas = np.arange(2, 91, 2) x = [] y = [] self.pts_transformation.detectors_amount = 99 self.pts_transformation.width = 180 * 2 for i in alphas: self.pts_transformation.alpha = i self.refresh() mse = Analysis.mean_squared_error(self.input_picture, self.restored_picture) print("Alpha =", i, "error =", mse) self.root.update_idletasks() x.append(i) y.append(mse) Analysis.draw_plot(x, y, "Kąt α [°]", "Błąd średniokwadratowy", "alpha")
def run_analysis(self, conn): # Analyse each unanalysed object for unanalysed_object in self.unanalysed_shapes: # Start analysis on the new image object analysis = Analysis(unanalysed_object["image"]) # Run each analysis shape = analysis.get_shape() shape_colour = analysis.get_shape_colour() character = analysis.get_character() character_colour = analysis.get_character_colour() character_orientation = analysis.get_character_orientation() # Update occurances dictionaries self.add_shape(shape) self.add_shape_colour(shape_colour) self.add_character(character) self.add_character_colour(character_colour) self.add_character_orientation(character_orientation) # Increment the number of analysed objects self.num_objects += 1 # Reset unanalysed objects list self.unanalysed_shapes = [] # Check if object can be sent to ground if (self.completed): self.send_object_to_ground() # Send analysed ODLC class back to the manager process conn.send(self)
def get_end_results(self): # get optimized pulse and propagation # get and save inter vects self.anly = Analysis(self.sys_para, self.tfs.final_state, self.tfs.ops_weight, self.tfs.unitary_scale, self.tfs.inter_vecs) self.save_data() self.display() if not self.show_plots: self.conv.save_evol(self.anly) self.uks = self.Get_uks() if not self.sys_para.state_transfer: self.Uf = self.anly.get_final_state() else: self.Uf = []
def test_gamma(self): gammas = np.arange(0.2, 4.1, 0.2) x = [] y = [] self.pts_transformation.alpha = 2 self.pts_transformation.detectors_amount = 99 self.pts_transformation.width = 180 * 2 for i in gammas: self.filter_props.gamma = i self.refresh() mse = Analysis.mean_squared_error(self.input_picture, self.restored_picture) print("Gamma =", i, "error =", mse) self.root.update_idletasks() x.append(i) y.append(mse) Analysis.draw_plot(x, y, "Wartość γ", "Błąd średniokwadratowy", "gamma")
def test_gauss(self): gauss = np.arange(0, 3.1, 0.1) x = [] y = [] self.pts_transformation.alpha = 2 self.pts_transformation.detectors_amount = 99 self.pts_transformation.width = 180 * 2 self.filter_props.gamma = 2.4 for i in gauss: self.filter_props.gauss = i self.refresh() mse = Analysis.mean_squared_error(self.input_picture, self.restored_picture) print("Gauss =", i, "error =", mse) self.root.update_idletasks() x.append(i) y.append(mse) Analysis.draw_plot(x, y, "Odchylenie standardowe", "Błąd średniokwadratowy", "gauss")
def add_Menu(self): dd = self.text_doc.textCursor().selectedText() # cursor выделенное start_elem = self.text_doc.textCursor().selectionStart( ) # the number of the first element of the selected text end_elem = self.text_doc.textCursor().selectionEnd( ) # the number of the last element of the selected text self.dialog = NewGroup_Menu(dd, self.data, self.bmks_filename, start_elem, end_elem, self) self.dialog.show()
def generate_result(self, target_function, params): result_path = self.make_result_file_path(params) tensorboard_path = self.make_tensorboard_path(params) os.makedirs(result_path, exist_ok=True) config = self.parameter_space.apply_instantiation(params) performance, raw_analysis = target_function({ **config, "result_path": result_path, "tensorboard_path": tensorboard_path }) Analysis.store_raw_result(result_path, raw_analysis) return performance
def onProfileClicked(self): """ Sets the strategy used in the simulator to the strategy with this profile's strategyIndex. @rtype: None """ analyzer = Analysis.getInstance() analyzer.strategy = self.strategyIndex data = Data.getInstance() data.setDataTimerToReset()
def main(): A = Analysis() c = np.array([[1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0], [0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0], [0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1]]) sx = np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [1, 0, 0]]) sy = np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1], [0, 0, 0], [0, 0, 0], [0, 1, 0]]) x = np.array([0, 4, 8, 12, 12, 8, 4, 0]) y = np.array([4, 8, 8, 4, 0, 4, 4, 0]) x = x.reshape(1, 8) y = y.reshape(1, 8) l = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -25, 0]) l = l.reshape(16, 1) A.set_truss_design(c, sx, sy, x, y, l) # A.mat_load() # print(A.get_x_vect()) # print(A.get_y_vect()) A.construct_A_mat()
class ReportWriter(object): def __init__(self, config, logger): self.analysis = Analysis( config.get_value("SHAREABLE", "trade_log_file_name")) self.outfn = config.get_value("SHAREABLE", "stat_file_name") self.logger = logger def write(self): report_text = "" max_mo_length = len(str(self.analysis.max_markout_period())) max_ticker_length = max([len(x) for x in self.analysis.get_tickers()]) + 2 out_cols = [ "Markout Period", "Ticker", "Trade Count", "Return mu", "Return tstat", "Return sharpe" ] header = [ "{item:>{item_width}}".format(item=col, item_width=len(col)) for col in out_cols ] report_text += "\t".join(header) + "\n" for mo_period in self.analysis.get_mo_periods(): for ticker in self.analysis.get_tickers(): out = { 'Markout Period': mo_period, 'Ticker': ticker, 'Trade Count': self.analysis.count(mo_period, ticker), 'Return mu': "{:0.4f}".format(self.analysis.mean(mo_period, ticker)), 'Return tstat': "{:0.2f}".format(self.analysis.tstat(mo_period, ticker)), 'Return sharpe': "{:0.2f}".format(self.analysis.sharpe(mo_period, ticker)) } output = [] for column in out_cols: if column in out: output.append("{item:>{item_width}}".format( item=out[column], item_width=len(column))) report_text += "\t".join(output) + "\n" report_text += "\n" with open(self.outfn, 'w') as f: f.write(report_text) self.logger.info("Report written to " + self.outfn)
def topics(request): output = '' if (request.GET.has_key('sort')): freqTopics = '' output = request.GET['sort'] time_diff = None #The time difference if output == 'today': time_diff = 1 elif output == 'lastweek': time_diff = 7 else: time_diff = 30 time2 = datetime.datetime.now() time1 = time2 - timedelta(days=time_diff) # freqTopics = Analysis.getFreqTopics(time1, time2, minFreq=10, k=params.maxFreqTopics) freqTopics = Analysis.getFreqTopics(time1, time2, minFreq=0, k=params.maxFreqTopics) time22 = time1 time11 = time22 - timedelta(days=time_diff) # to be used to find the old frequencies of current hot topics print time1 print time2 print time11 print time22 freqTopics = Analysis.getTopicsFrequencyChanges(freqTopics, time11, time22) # find trendings for freq topic sets return render_to_response('ui/topics.html', {'freqTopics' : freqTopics})
else: mode = sys.argv[1] datafiles = sys.argv[2:] if 'full' in mode: sys.setrecursionlimit(500) # watch out! if 'single' in mode: sys.setrecursionlimit(2000) # watch out! try: for datafile in datafiles: instructions = Instructions() parser = Parser(datafile, instructions) analysis = Analysis(instructions) if mode == 'debugnofilter': logging.info("running debug mode with ipython on file %s..." % (datafile)) parser = Parser(datafile, instructions, []) parser.run() ipshell = IPShellEmbed() ipshell() if mode == 'debug': logging.info("running debug mode with ipython on file %s..." % (datafile)) parser.run() ipshell = IPShellEmbed()
def __init__(self, myParent): self.analysis = Analysis() if len(sys.argv)>1 and sys.argv[1] in ["CMD",'cmd','cl']: self.Cmdline() sys.exit() self.myContainer = Frame(myParent,height=200,width=200) self.myContainer.pack() Label(self.myContainer, text="Choose an Element:").pack(anchor=W) self.radio_element = StringVar() element = [ (u"Ozone \u03bcg/m\xb3",'oz'), (u"Particulate < 10 \u03bcg/m\xb3",'p10'), (u"Particulate < 2.5 \u03bcg/m\xb3",'p2'), ] for txt,val in element: Radiobutton(self.myContainer, text=txt, indicatoron = 0, width = 64, padx = 20, variable=self.radio_element, command=self.showText, value=val).pack(anchor=W) self.checkbutton1 = StringVar() self.C1 = Checkbutton(self.myContainer, text="Anand Vihar ",variable = self.checkbutton1,onvalue="AV",offvalue="") self.checkbutton2 = StringVar() self.C2 = Checkbutton(self.myContainer, text="Mandir Marg ",variable = self.checkbutton2,onvalue="MM",offvalue="") self.checkbutton3 = StringVar() self.C3 = Checkbutton(self.myContainer, text="Punjabi Bagh",variable = self.checkbutton3,onvalue="PB",offvalue="") self.checkbutton4 = StringVar() self.C4 = Checkbutton(self.myContainer, text="R.K Puram ",variable = self.checkbutton4,onvalue="RKP",offvalue="") """ #Button initials. self.button1 = Button(self.myContainer,command=self.combine) self.button1["text"]= "Execute" """ Label(self.myContainer, text="\nChoose Location(s):").pack(anchor = W) self.C1.pack(anchor=W) self.C2.pack(anchor=W) self.C3.pack(anchor=W) self.C4.pack(anchor=W) """Select yesterday, last 7 days, last Month , this month""" self.time = None self.time = StringVar() date_options = [ (u"Yesterday",'y'), (u"Last 7 Days",'l7'), (u"This Month",'tm'), (u"Last Month",'lm'), (u"Since Beginning",'now') ] for txt,val in date_options: Radiobutton(self.myContainer, text=txt, indicatoron = 0, width = 64, padx = 20, variable=self.time, command=self.combine, value=val).pack(anchor=W) #Label(self.myContainer, text="\n").pack(anchor = W) """""" """Enter date(optional)""" #Not implemented """""" """Execute Button""" #self.button1.pack() self.text = None self.ozone = None self.particulate = None with open('ozone.txt','r') as f: self.ozone = f.read() with open('particulate.txt','r') as f: self.particulate = f.read()
s = urllib.urlopen(SITE_JR + fileName) if s.getcode() != 200: return lines = s.readlines() print u"%s => %s" % (fileName,catName) ret = "{|class='wikitable sortable'\n" ret += "!Titre!!Nb links!!Nb pages traduites!!tpl !! en page !! de page !! es page !! models !! admisssible \n" for l in lines: ret += "|-\n" ret += l ret +="|-\n" ret+= "|}" p = Page(site, page + "/analysis") p.edit(text = ret, summary=str(len(lines)) + " articles à adopter",bot=True) a = Analysis(site) a.run() YEAR = [2013, 2014, 2015, 2016, 2017] MONTH = [u"janvier", u"février", u"mars", u"avril", u"mai", u"juin", u"juillet", u"août", u"septembre", u"octobre", u"novembre", u"décembre"] # orphelins for y in YEAR: m =1 for mon in MONTH: catName = u"Catégorie:Article orphelin depuis %s %d" %(mon, y) fileName= u"orph_%d-%02d.arch" % (y, m) try: printPageFromFile(catName, fileName) except: print "problem with %s" % catName
class Gui(object): def __init__(self, myParent): self.analysis = Analysis() if len(sys.argv)>1 and sys.argv[1] in ["CMD",'cmd','cl']: self.Cmdline() sys.exit() self.myContainer = Frame(myParent,height=200,width=200) self.myContainer.pack() Label(self.myContainer, text="Choose an Element:").pack(anchor=W) self.radio_element = StringVar() element = [ (u"Ozone \u03bcg/m\xb3",'oz'), (u"Particulate < 10 \u03bcg/m\xb3",'p10'), (u"Particulate < 2.5 \u03bcg/m\xb3",'p2'), ] for txt,val in element: Radiobutton(self.myContainer, text=txt, indicatoron = 0, width = 64, padx = 20, variable=self.radio_element, command=self.showText, value=val).pack(anchor=W) self.checkbutton1 = StringVar() self.C1 = Checkbutton(self.myContainer, text="Anand Vihar ",variable = self.checkbutton1,onvalue="AV",offvalue="") self.checkbutton2 = StringVar() self.C2 = Checkbutton(self.myContainer, text="Mandir Marg ",variable = self.checkbutton2,onvalue="MM",offvalue="") self.checkbutton3 = StringVar() self.C3 = Checkbutton(self.myContainer, text="Punjabi Bagh",variable = self.checkbutton3,onvalue="PB",offvalue="") self.checkbutton4 = StringVar() self.C4 = Checkbutton(self.myContainer, text="R.K Puram ",variable = self.checkbutton4,onvalue="RKP",offvalue="") """ #Button initials. self.button1 = Button(self.myContainer,command=self.combine) self.button1["text"]= "Execute" """ Label(self.myContainer, text="\nChoose Location(s):").pack(anchor = W) self.C1.pack(anchor=W) self.C2.pack(anchor=W) self.C3.pack(anchor=W) self.C4.pack(anchor=W) """Select yesterday, last 7 days, last Month , this month""" self.time = None self.time = StringVar() date_options = [ (u"Yesterday",'y'), (u"Last 7 Days",'l7'), (u"This Month",'tm'), (u"Last Month",'lm'), (u"Since Beginning",'now') ] for txt,val in date_options: Radiobutton(self.myContainer, text=txt, indicatoron = 0, width = 64, padx = 20, variable=self.time, command=self.combine, value=val).pack(anchor=W) #Label(self.myContainer, text="\n").pack(anchor = W) """""" """Enter date(optional)""" #Not implemented """""" """Execute Button""" #self.button1.pack() self.text = None self.ozone = None self.particulate = None with open('ozone.txt','r') as f: self.ozone = f.read() with open('particulate.txt','r') as f: self.particulate = f.read() def combine(self): self.buildCmd() try: self.forget() except: return def forget(self): self.text.destroy() self.text = None def showText(self): """After selecting an element have to select location(s)""" if self.v.get()=="oz" and self.text==None: self.text = Text(self.myContainer,width=67, height=15) self.text.configure(state='normal') self.text.insert('1.0', self.ozone) self.text.configure(state='disabled') self.text.pack() elif (self.v.get()=="p2" or self.v.get()=="p10") and self.text==None: self.text = Text(self.myContainer,width=67, height=15) self.text.configure(state='normal') self.text.insert('1.0', self.particulate) self.text.configure(state='disabled') self.text.pack() def buildCmd(self): interval = self.time.get() if interval=='': interval = 'now' s = "get %s in %s %s %s %s on %s" % (self.radio_element.get(),self.checkbutton1.get(), self.checkbutton2.get(),self.checkbutton3.get(),self.checkbutton4.get(),interval) query = s.split() #print query if len(query)<6 or query[1]=='in': #Need to check for locations missing return if query[0]=='get': self.analysis.get_data(query[1:]) def Cmdline(self): #q = {"date":datetime(2015,04,23,15,10)} #find_data(q)[0] while True: print "" #print "Elements = oz: ozone , p10: particulate < 10 , p2: particulate < 2.5" #print "Location = RK: RK Puram , MM: Mandir Marg , AV: Anand Vihar, PB: Punjabi Bagh" #print "Time = now: Since Beginning , y: Yesterday, l7: Last 7 Days, tm: This Month, lm: Last Month" #print "Quit = q" print "Enter Query-->", try: s = raw_input() if s in ["quit","q",'exit']: break query = s.split() if query[0]=='get': check = self.analysis.get_data(query[1:]) if check==0: print "Error in Query" continue except: continue print "Bye"
pass #print report query = 'Reuters' #time1 = '2012-04-20 00:00:00' #time2 = '2013-04-25 08:00:00' #time11 = '2012-04-25 08:00:00' #time22 = '2013-04-30 00:00:00' time2 = datetime.datetime.now() time1 = time2 - timedelta(days=20) time22 = time1 time11 = time22 - timedelta(days=20) print 'getFreqTopics:' print Analysis.getFreqTopics(time1, time2, minFreq=10, k=0) print '\ngetFreqTopicSets:' print Analysis.getFreqTopicSets(query, time1, time2) print '\ngetTopicFrequency:' print Analysis.getTopicFrequency(query, time1, time2) print '\ngetHotTopics:' topics = Analysis.getHotTopics(10, time1, time2) print topics print '\ngetTopicsFrequencyChanges:' print Analysis.getTopicsFrequencyChanges(topics, time11, time22)
def __init__(self, config, logger): self.analysis = Analysis(config.get_value("SHAREABLE", "trade_log_file_name")) self.outfn = config.get_value("SHAREABLE", "stat_file_name") self.logger = logger
def index(request): freqTopicSets = '' query = '' freqTopics = '' time2 = datetime.datetime.now() time1 = time2 - timedelta(days=1) print('timing: before freqTopics') print(datetime.datetime.now()) freqTopics = Analysis.getFreqTopics(time1, time2, minFreq=0, k=params.maxFreqTopics) time22 = time1 time11 = time22 - timedelta(days=2*params.days) # to be used to find the old frequencies of current hot topics freqTopics = Analysis.getTopicsFrequencyChanges(freqTopics, time11, time22) # find trendings for freq topic sets #pdb.set_trace() how to do debugging #print('timing: after freqTopics') #print(datetime.datetime.now()) #if request.method == 'GET' : # If form is submitted form = searchForm(request.GET) tag = '' linkSets = [] topicSet_linkSets = [] if form.is_valid(): if(request.GET.has_key('input')): print('timing: before getFreqTopicSets') print(datetime.datetime.now()) freqTopicSets = Analysis.getFreqTopicSets(request.GET['input'], time1, time2) print('timing: after getFreqTopicSets') print(datetime.datetime.now()) for topicSet in freqTopicSets: tag_ids = [] links = [] #cuz example topicSet for a query like Microsoft = (['Blog', 'Android'], 4) so make into ['Blog', 'Android', 'Microsoft'] topics = topicSet[0] topics.append(str(request.GET['input'])) for topic in topics: tag = Tag.findByTitle(topic) #findByTitle returns multiple rows representing multiple tags, so the last [0][0] means get the first attribute (ie id) or the first tag in rows #pdb.set_trace() tag_id = tag[0][0] tag_id = str(tag_id).strip('L') #seems like we get id's like '3167L' strip the L tag_ids.append(tag_id) #print("in views.py:") print(topicSet) #pdb.set_trace() #print('====') #print(datetime.datetime.now()) feeditems = feeditem.Feeditem.findByTags(tag_ids, time1, time2) #print(datetime.datetime.now()) for item in feeditems: print item[1] t1 = unicode(unicode(item[1],'utf-8', errors='ignore')) # to ignore non utf-8 chars t2 = unicode(item[3]) links.append((t1,t2)) linkSets.append(copy.copy(links)) topicSet_linkSets = zip(freqTopicSets, linkSets) else: form = searchForm() if(request.GET.has_key('input')): query = request.GET['input'] else: qeury = None return render_to_response('ui/index.html', {'form' : form, 'freqTopicSets':freqTopicSets, 'query': query, 'freqTopics':freqTopics, 'linkSets':linkSets, 'topicSet_linkSets':topicSet_linkSets[::-1] })
def __init__(self): Analysis.__init__(self) self.packetList = []