コード例 #1
0
    def test_date2gpswd(self):
        """Test date2gpswd function,
        use date: 2017-5-17, GPS week: 1949, day of week: 3.
        """
        date = datetime.date(2017, 5, 17)
        gpsweek, dayofweek = gnsscal.date2gpswd(date)

        self.assertEqual(gpsweek, 1949)
        self.assertEqual(dayofweek, 3)
        date = datetime.date(1980, 1, 1)
        with self.assertRaises(ValueError):
            gnsscal.date2gpswd(date)
コード例 #2
0
ファイル: EISA.py プロジェクト: nicolasgapa/EISA
def parse(date,
          receiver_name,
          constellations,
          input_folder='',
          output_folder=''):
    # Print a message.
    date = date_type(int(date[:4]), int(date[4:6]), int(date[6:]))

    # Define PRNs.
    PRNs_to_parse = []
    if 'G' in constellations:
        PRNs_to_parse.extend(['G' + str(i) for i in range(1, 33)])
    if 'R' in constellations:
        PRNs_to_parse.extend(['R' + str(i) for i in range(1, 25)])
    if 'E' in constellations:
        PRNs_to_parse.extend(['E' + str(i) for i in range(1, 31)])

    # Define parsing parameters.
    parameters = ParseSettings()
    parameters.binary_dir = input_folder + filesep + receiver_name
    parameters.CSV_dir = output_folder + filesep + receiver_name + filesep + 'CSV_FILES'
    parameters.receiver_name = receiver_name
    parameters.date_range = False
    parameters.start_date = [date.year, date.month, date.day]
    parameters.end_date = [date.year, date.month, date.day]
    parameters.reduced = True
    parameters.raw = False
    parameters.PRNs_to_parse = PRNs_to_parse
    parameters.set_time_range = False

    # Binary dir and file.
    binary_file = str(date2gpswd(date)[0]) + '_' + str(
        date2gpswd(date)[1]) + '_00_' + receiver_name + '.GPS'
    binary_dir = parameters.binary_dir + filesep + str(
        date2gpswd(date)[0]) + filesep + binary_file

    # If the binary file exists, parse.
    if os.path.exists(binary_dir):
        # Print status to command window.
        print(
            "\n---------------------------------------------------------------------"
        )
        print(
            "PART 1: EISA PARSING. Receiver: {}. Date: ({}, {}, {})\n".format(
                receiver_name, date.year, date.month, date.day))

        # Parse.
        run_parsing(parameters, cwd + filesep + "Parsing")
    else:
        print("The following binary file does not exist: {}. Receiver: {}.".
              format(binary_dir, receiver_name))
コード例 #3
0
ファイル: parsing.py プロジェクト: nicolasgapa/EISA
def run_parsing(model, exe_dir):
    # Process the dates. Obtain the names of the binary files.
    start_year, start_month, start_day = model.start_date
    end_year, end_month, end_day = model.end_date
    number_of_days = (date(end_year, end_month, end_day) - date(start_year, start_month, start_day)).days
    if number_of_days < 0:
        print('Error: The selected end date must be after the start date.')
    days = [date(start_year, start_month, start_day) + timedelta(days=i) for i in range(number_of_days + 1)]
    binary_files = [str(date2gpswd(day)[0]) + '_' + str(date2gpswd(day)[1]) + '_00_' + model.receiver_name + '.GPS' for
                    day in days]

    # Parse the binary files.
    for binary_file in binary_files:

        # Parse file.
        success, error = parse_binary_file(binary_file, exe_dir, model)
        if not success:
            print(error)
コード例 #4
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    def __init__(self, dt):
        self.__dt = dt
        self._year = self.__dt.year
        self._month = self.__dt.month
        self._day = self.__dt.day
        self._doy = dt.timetuple().tm_yday

        gpswd = date2gpswd(date(self._year, self._month, self._day))
        self._gpsweek = gpswd[0]
        self._gpsweekday = gpswd[1]
コード例 #5
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def download_corr_files(out_path, base_stn, obs, nav, sevenzip):
    """
    This function downloads the necessary base station and satellite files (broadcast/orbits)
    for correcting raw rinex files using rtkpost.
    """

    # file root name
    name = obs.split('.obs')[0]

    # first we need the year, doy, and GPS week from the observations file
    f = open(out_path + obs, 'r').read()
    print("Downloading correction data for {}".format(obs))
    lines = f.strip().splitlines()
    for l in lines:
        # read from RINEX header
        if l.endswith('TIME OF FIRST OBS'):
            var = l.split()
            yr = var[0]
            # use datetime and gnsscal to convert the date to doy and gps week
            date = datetime.date(int(yr), int(var[1]), int(var[2]))
            doy = str(gnsscal.date2doy(date))
            if not len(doy) == 3:  # add the leading 0 if DOY is < 3 digits
                doy = '0' + doy
            week = str(gnsscal.date2gpswd(date)[0]) + str(
                gnsscal.date2gpswd(date)[1])

    # create a new folder to hold the correction data and move the rinex files into it
    path = out_path + yr + doy + '_' + name + '/'
    if not os.path.exists(path):
        os.mkdir(path)
        shutil.move(out_path + obs, path + obs)
        shutil.move(out_path + nav, path + nav)

    # download the base station observations, broadcast navigation, and satellite orbital clocks
    # NOTE: we log into and out of the FTP server each time to avoid some hang-ups in downloading
    # also this could allow for replacement of the server to different locations for each file

    # connect to the FTP for getting the base station observations
    f = ftp.FTP('igs.ensg.ign.fr')
    try:
        f.login()
        print('logged into ftp')
    except:
        print('hmm couldn\'t connect to base station ftp. no internet?')
        sys.exit()
    # navigate to the directory
    f.cwd('/pub/igs/data/' + yr + '/' + doy + '/')
    # download the base station using the leading identifier and wildcards
    # note we use the 30 second decimated data (*30S* wildcard below), this is
    # available for most sites
    filematch = base_stn + '*30S*.crx.gz'
    for filename in f.nlst(filematch):
        target_file_name = os.path.join(path, os.path.basename(filename))
        with open(target_file_name, 'wb') as fhandle:
            f.retrbinary('RETR %s' % filename, fhandle.write)
            # quit and close server connection
            f.quit()
            f.close()
    #also unzip the file with 7zip
    cmd = '"' + sevenzip + '"' + ' e ' + path + filename + ' -o' + path
    subprocess.call(cmd, shell=False)
    # change the file name and convert to rinex with crnx2rnx
    shutil.move(path + filename.split('.gz')[0],
                path + filename.split('crx')[0] + yr[2:] + 'd')
    cmd = crnx2rnx + ' ' + path + filename.split('crx')[0] + yr[2:] + 'd'
    subprocess.call(cmd, shell=False)
    # final filename
    baseSTN = path + filename.split('crx')[0] + yr[2:] + 'o'

    # grab the broadcast navigation data from the same directory
    f = ftp.FTP('igs.ensg.ign.fr')
    try:
        f.login()
        print('logged into ftp')
    except:
        print('hmm couldn\'t connect to base station ftp. no internet?')
        sys.exit()
    # navigate to the directory
    f.cwd('/pub/igs/data/' + yr + '/' + doy + '/')
    # get the filematch
    filename = 'brdc' + doy + '0.' + yr[2:] + 'n.Z'
    target_file_name = os.path.join(path, os.path.basename(filename))
    with open(target_file_name, 'wb') as fhandle:
        f.retrbinary('RETR %s' % filename, fhandle.write)
        # quit and close server connection
        f.quit()
        f.close()
    # unzip with 7zip
    cmd = '"' + sevenzip + '"' + ' e ' + path + filename + ' -o' + path
    subprocess.call(cmd, shell=False)
    # final filename
    brdc = target_file_name.split('.Z')[0]

    # finally grab the satellite precise orbits from a different directory
    f = ftp.FTP('igs.ensg.ign.fr')
    try:
        f.login()
        print('logged into ftp')
    except:
        print('hmm couldn\'t connect to base station ftp. no internet?')
        sys.exit()
    # navigate to the directory
    f.cwd('/pub/igs/products/' + week[0:4] + '/')
    # we try with the rapid orbits, if they're available
    try:
        filename = 'igr' + week + '.sp3.Z'
        target_file_name = os.path.join(path, os.path.basename(filename))
        with open(target_file_name, 'wb') as fhandle:
            f.retrbinary('RETR %s' % filename, fhandle.write)
    # retry with the ultra-rapid orbits if that didn't work
    except:
        filename = 'igu' + week + '_18.sp3.Z'  # arbitrarily taking the final ultra-rapid file (18:00)
        target_file_name = os.path.join(path, os.path.basename(filename))
        with open(target_file_name, 'wb') as fhandle:
            f.retrbinary('RETR %s' % filename, fhandle.write)
    # unzip with 7zip
    cmd = '"' + sevenzip + '"' + ' e ' + path + filename + ' -o' + path
    subprocess.call(cmd, shell=False)
    # final filename
    orbits = target_file_name.split('.Z')[0]
    # quit and close server connection for good
    f.quit()
    f.close()

    return yr, doy, week, baseSTN, brdc, orbits
コード例 #6
0
ファイル: EISA.py プロジェクト: nicolasgapa/EISA
def ML_event_detection(date,
                       receiver_name,
                       constellations,
                       threshold,
                       location,
                       input_folder='',
                       output_folder=''):
    # Determine the date, CSV dir, and GRAPHS dir.
    year, month, day = date[:4], date[4:6], date[6:]

    binary_dir = input_folder + filesep + receiver_name
    CSV_dir = output_folder + filesep + receiver_name + filesep + 'CSV_FILES'
    graphs_dir = output_folder + filesep + receiver_name + filesep + 'GRAPHS'

    # Define PRNs.
    PRNs_to_process = []
    if 'G' in constellations:
        PRNs_to_process.extend(['G' + str(i) for i in range(1, 33)])
    if 'R' in constellations:
        PRNs_to_process.extend(['R' + str(i) for i in range(1, 25)])
    if 'E' in constellations:
        PRNs_to_process.extend(['E' + str(i) for i in range(1, 31)])

    # Continue only if the path containing the csv files of the corresponding date exists.
    if os.path.exists(CSV_dir + filesep + date):

        # Print status to command window.
        print(
            "\n---------------------------------------------------------------------"
        )
        print("PART 3: EISA ML MODULE. Receiver: {}. Date: ({}, {}, {})\n".
              format(receiver_name, year, month, day))

        # Create S4 Neural Network, and load the weights.
        S4_model = NNModel('S4')
        S4_model.load_weights('ML' + filesep + 's4_scintillation.h5')

        # Create sigma Neural Network, and load the weights.
        sigma_model = NNModel('sigma')
        sigma_model.load_weights('ML' + filesep + 'sigma_scintillation.h5')

        # Identify binary file name.
        day = date_type(int(year), int(month), int(day))
        week_number, week_day_number = int(date2gpswd(day)[0]), int(
            date2gpswd(day)[1])
        binary_file_name = "{}_{}_00_{}.GPS".format(str(week_number),
                                                    str(week_day_number),
                                                    receiver_name)
        binary_file = binary_dir + filesep + str(
            week_number) + filesep + binary_file_name

        # Ionospheric scintillation detection.
        for prn in PRNs_to_process:
            # Files.
            input_file = CSV_dir + filesep + date + filesep + 'REDOBS_{}_{}.csv'.format(
                prn, date)
            output_file = CSV_dir + filesep + date + filesep + r'\ML_Detection\REDOBS_{}_{}_ML'.format(
                prn, date)

            # Convert date to list format (which is the input format for the run_ML function).
            date_list = [date[:4], date[4:6], date[6:]]

            # Directory to the new (ML) plots.
            graphs_output_dir = graphs_dir + filesep + date + filesep + 'ML'

            # Check that the input file exists.
            if not os.path.isfile(input_file):
                continue

            # ML Detection. Use try except, so that the code continues running even in the case of an error.
            try:

                # ML Detection: S4 scintillation.
                print(
                    '\n ----- Ionospheric Scintillation Event Detection (ML Module). Date: {}. PRN: {}. -----'
                    .format(date, prn))
                output_files_s4 = run_ML(input_file,
                                         output_file,
                                         S4_model,
                                         prn,
                                         date_list,
                                         scintillation_type='S4',
                                         save_plot=True,
                                         save_plot_dir=graphs_output_dir +
                                         filesep + 'Amplitude',
                                         threshold=threshold,
                                         location=location)

                # ML Detection: sigma scintillation.
                output_files_sigma = run_ML(input_file,
                                            output_file,
                                            sigma_model,
                                            prn,
                                            date_list,
                                            scintillation_type='sigma',
                                            save_plot=True,
                                            save_plot_dir=graphs_output_dir +
                                            filesep + 'Phase',
                                            threshold=threshold,
                                            location=location)

                # Raw data period processing.
                output_files = output_files_s4 + output_files_sigma
                if output_files:
                    success, msg = parse_file(binary_file,
                                              CSV_dir,
                                              os.getcwd() + filesep +
                                              'parsing', [prn],
                                              week_number,
                                              week_day_number,
                                              reduced_or_raw='raw',
                                              print_header=False)
                    if not success:
                        print(msg)
                # If no output files were generated, print a message.
                else:
                    print(
                        'No scintillation event was found for prn {}.'.format(
                            prn))

            # Print exception if an error is raised.
            except Exception as e:
                print(
                    'Could not process prn {}. The following exception occurred: {}.'
                    .format(prn, e.message))
コード例 #7
0
            d['predicted'] = df_predict_prn['yhat'].values
            d['index'] = df_expect_prn['epoch_time'].values
            dc[column] = d
            original_dataframe[column] = df_expect_prn[column]
            final_dataframe[column] = pd.DataFrame(
                data=df_predict_prn['yhat'].values, columns=['m'])

        elif column == "OMEGA":

            df = pd.DataFrame()
            df['epoch_time'] = df_expect_prn['epoch_time']
            t_len = df_final_prn.shape[0]
            df['OMEGA'] = df_final_prn['OMEGA'][t_len - 1:t_len][t_len -
                                                                 1:t_len]

            prev_week, _ = gnsscal.date2gpswd(
                df_final_prn['epoch_time'][t_len - 1:t_len].dt.date.values[0])
            this_week, _ = gnsscal.date2gpswd(
                df_expect_prn['epoch_time'][0:1].dt.date.values[0])

            if this_week != prev_week:
                hdiff = (24 -
                         df_final_prn['epoch_time'][t_len -
                                                    1:t_len].dt.hour.values[0]
                         ) + df_expect_prn['epoch_time'][:1].dt.hour.values[0]
                df['OMEGA'][:1] = df_final_prn['OMEGA'][
                    t_len - 1:t_len].values[0] - hdiff * 6 * (10**-6) - 0.12
            else:
                hdiff = (24 -
                         df_final_prn['epoch_time'][t_len -
                                                    1:t_len].dt.hour.values[0]
                         ) + df_expect_prn['epoch_time'][:1].dt.hour.values[0]
コード例 #8
0

def Accepter():
    while 1:
        global conn
        if ABS.accept()[0] or PPP.accept()[0] or RTK.accept()[0]:
            conn = {
                'ABS': ABS.accept()[0],
                'PPP': PPP.accept()[0],
                'RTK': RTK.accept()[0]
            }
        eventConnection.set()


today = datetime.date.today()
GPSweek = gnsscal.date2gpswd(today)

# init threads
AccepterConnection = threading.Thread(target=Accepter)
Recivers = threading.Thread(target=Reciver)
RTKOptimization = threading.Thread(target=ReciveRTK)

# start threads
AccepterConnection.start()
Recivers.start()
RTKOptimization.start()


def main():
    time.sleep(10)
    RequestRTK(AproxPos)