def urbansound_analysis(metafile): if not os.path.exists(metafile): raise Exception("Metafile UrbanSound is not found") with open(metafile, "r") as f: data = csv.reader(f) classes = list() duration_hist = list() header = False for line in data: try: duration = str(math.ceil(float(line[3]) - float(line[2]))) duration_hist.append(duration) color = "green" info = str("File: ") + line[0] + str(" class: ") + line[-1] if header: classes.append(line[-1]) else: header = True except: color = "red" info = "File has been passed" print(termcolor.colored(info, color)) analysis.histogram(classes, filename="urbansound_class") analysis.histogram(duration_hist, filename="urabnsound_duration")
def freesound_analysis(search_tokens, output, lim_page_count=1, key=None): lim_page_count = int(lim_page_count) try: client = freesound.FreesoundClient() client.set_token(key, "token") print(termcolor.colored("Authorisation successful ", "green")) except: print(termcolor.colored("Authorisation failed ", "red")) classes = list() for token in search_tokens: try: results = client.text_search(query=token, fields="id,name,previews") output_catalog = os.path.normpath(output) if not os.path.exists(output_catalog): os.makedirs(output_catalog) page_count = int(0) while True: for sound in results: try: classes.append(token) info = "Data has been getter: " + str(sound.name) print(termcolor.colored(info, "green")) except: info = "Data has not been getter: " + str(sound.name) print(termcolor.colored(info, "red")) page_count += 1 if (not results.next) or (lim_page_count == page_count): page_count = 0 break results = results.next_page() except: print(termcolor.colored(" Search is failed ", "red")) analysis.histogram(classes) pass
def audioset_analysis(audioset_file, inputOntology): if not os.path.exists(inputOntology) or not os.path.exists(audioset_file): raise Exception("Can not found file") with open(audioset_file, 'r') as fe: csv_data = csv.reader(fe) sx = list() with open(inputOntology) as f: data = json.load(f) duration_hist = list() for row in csv_data: if row[0][0] == '#': continue classes = row[3:] try: color = "green" tmp_duration = str(float(row[2]) - float(row[1])) info = str("id: ") + str( row[0]) + str(" duration: ") + tmp_duration duration_hist.append(tmp_duration) for cl in classes: for dt in data: cl = str(cl).strip().replace('"', "") if cl == dt['id'] and len(dt['child_ids']) == 0: sx.append(dt['name']) info += str(" ") + str(dt['name']) + str(",") except: color = "red" info = "File has been pass: "******"audioset_class") analysis.pie_chart(duration_hist, textinfo="percent + label", filename="audioset_duration")
QUEUE.close() DB_CONN.close() sys.exit(1) try: CONFS = analysis.statistics(QUEUE, sys.argv[2], sys.argv[3]) manage.print_results(CONFS) except: print(sys.exc_info()) elif COMMAND == "histogram": if len(sys.argv) != 4: print("Usage: " + sys.argv[0] + " histogram <table> <samples>") QUEUE.close() DB_CONN.close() sys.exit(1) try: HISTS = analysis.histogram(QUEUE, sys.argv[2], sys.argv[3]) for hist in HISTS: i = 0 for item in hist: print(i, item) i = i + 1 print("\n\n") except: print(sys.exc_info()) elif COMMAND == "optimizationSpace": if len(sys.argv) != 4: print("Usage: " + sys.argv[0] + " optimizationSpace <table> <samples>") QUEUE.close() DB_CONN.close() sys.exit(1) try:
QUEUE.close() DB_CONN.close() sys.exit(1) try: SCENARIO = "beams = " + sys.argv[3] + " AND sBeams = " + sys.argv[ 4] + " AND subbands = " + sys.argv[ 5] + " AND channels = " + sys.argv[ 6] + " AND zappedChannels = " + sys.argv[ 7] + " AND subSamples = " + sys.argv[ 8] + " AND samples = " + sys.argv[9] FLAGS = [False, False] if "local" in sys.argv: FLAGS[0] = True elif "cache" in sys.argv: FLAGS[1] = False HISTS = analysis.histogram(QUEUE, sys.argv[2], SCENARIO, FLAGS) for hist in HISTS: i = 0 for item in hist: print(i, item) i = i + 1 print("\n\n") except: print(sys.exc_info()) elif COMMAND == "optimizationSpace": if len(sys.argv) < 10 or len(sys.argv) > 11: print( "Usage: " + sys.argv[0] + " optimizationSpace <table> <beams> <sBeams> <subbands> <channels> <zappedChannels> <subSamples> <samples> [local|cache]" ) QUEUE.close()
import analysis #Create historgram analysis.histogram() #Create scatterplot analysis.scatterplot("sepal_length", "sepal_width") analysis.scatterplot("petal_length", "petal_width") analysis.pair_plot() #Create summary.txt analysis.writeToAFile