예제 #1
0
파일: train.py 프로젝트: zbeloki/elefix
def dataset_avg_elevation_diff(dataset, overlap, savgol_window, polynom=2):

    sqr_elev_diff = 0.0
    elev_diff = 0.0
    for entry in dataset:
        dists = entry['dists']
        alts1 = entry['alts_orig']
        if savgol_window is None:
            alts2 = entry['alts_srtm_raw']
        else:
            alts2 = elefix.set_altitudes(entry['lats'], entry['lons'], True,
                                         savgol_window, polynom)
        entry_elev_diff = track_avg_elevation_diff(dists, alts1, alts2,
                                                   overlap)
        sqr_elev_diff += (entry_elev_diff**2)
        elev_diff += entry_elev_diff

    return (math.sqrt(sqr_elev_diff / len(dataset)),
            (elev_diff / len(dataset)))
예제 #2
0
파일: train.py 프로젝트: zbeloki/elefix
def calculate_acc_deviation(dataset,
                            savgol_window,
                            vertical_threshold=DEFAULT_VERT_THRESHOLD,
                            polynom=2):

    sqr_deviation = 0.0
    deviation = 0.0
    for entry in dataset:
        totaldist = entry['dists'][-1]
        eg_orig = elevation_gain(entry['alts_orig'], totaldist,
                                 DEFAULT_VERT_THRESHOLD)
        if savgol_window is None and vertical_threshold is None:
            eg_srtm = elevation_gain(entry['alts_srtm_raw'], totaldist,
                                     DEFAULT_VERT_THRESHOLD)
        else:
            alts_srtm = elefix.set_altitudes(entry['lats'], entry['lons'],
                                             True, savgol_window, polynom)
            eg_srtm = elevation_gain(alts_srtm, totaldist, vertical_threshold)
        current_deviation = abs(eg_srtm - eg_orig)
        sqr_deviation += (current_deviation**2)
        deviation += current_deviation

    return (math.sqrt(sqr_deviation / len(dataset)),
            (deviation / len(dataset)))
예제 #3
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def main(dataset_dir, window, grade):

    # validate input directory
    if not os.path.isdir(dataset_dir):
        raise ValueError('"dataset_dir" is not a valid directory path')

    # prepare dataset
    # each dataset entry: {'lats', 'lons', 'dists', 'alts_orig', 'alts_srtm_raw'}
    dataset = []
    for fname in os.listdir(dataset_dir):

        # validate file
        _, ext = os.path.splitext(fname)
        fpath = os.path.join(dataset_dir, fname)
        if not os.path.isfile(fpath) or ext not in ['.gpx', '.tcx']:
            continue

        # parse input file
        with open(fpath, 'r') as f:
            track_content = f.read()
            if ext.lower() == '.gpx':
                wpts = elefix.gpx_parse(track_content)
            else:  # ext.lower() == '.tcx'
                wpts = elefix.tcx_parse(track_content)

        # remove waypoints for which the distance to the next one is 0
        i = 0
        while i < len(wpts) - 1:
            if elefix.wpt_distance(wpts[i], wpts[i + 1]) == 0.0:
                del wpts[i]
            else:
                i += 1

        # original latitudes, longitudes and altitudes
        latitudes = [wpt.lat for wpt in wpts]
        longitudes = [wpt.lon for wpt in wpts]
        altitudes = [wpt.alt for wpt in wpts]

        # accumulated distance on each waypoint
        dists = [
            elefix.wpt_distance(wpair[0], wpair[1])
            for wpair in zip(wpts[:-1], wpts[1:])
        ]
        dists_acc = [sum(dists[:i]) for i in range(len(wpts))]

        # SRTM raw altitudes
        alts_srtm_raw = elefix.set_altitudes(latitudes,
                                             longitudes,
                                             smooth=False)

        dataset_entry = {
            'lats': latitudes,
            'lons': longitudes,
            'dists': dists_acc,
            'alts_orig': altitudes,
            'alts_srtm_raw': alts_srtm_raw,
        }
        dataset.append(dataset_entry)

    # SRTM raw altitudes (baseline)
    sqr_avg_acc_dev, avg_acc_dev = calculate_acc_deviation(
        dataset, None, None, None)
    sqr_avg_ele_diff, avg_ele_diff = dataset_avg_elevation_diff(
        dataset, True, None, None)
    print(
        'N\tG\tEGD (quadratic mean)\tEGD (mean)\tAPD (quadratic mean)\tAPD (mean)'
        .format(sqr_avg_acc_dev, avg_acc_dev, sqr_avg_ele_diff, avg_ele_diff))
    print('-\t-\t{:.2f}\t{:.2f}\t{:.2f}\t{:.2f}'.format(
        sqr_avg_acc_dev, avg_acc_dev, sqr_avg_ele_diff, avg_ele_diff))

    # SRTM smoothed altitudes after applying Savitzky-Golay filter
    best_acc = [None, None, 999999,
                None]  # window, sqr_avg_acc_dev, avg_acc_dev
    best_elediff = [None, None, 999999,
                    None]  # window, sqr_avg_ele_diff, avg_ele_diff

    sqr_avg_acc_dev, avg_acc_dev = calculate_acc_deviation(
        dataset, window, DEFAULT_VERT_THRESHOLD, grade)
    sqr_avg_ele_diff, avg_ele_diff = dataset_avg_elevation_diff(
        dataset, True, window, grade)
    print('{}\t{}\t{:.2f}\t{:.2f}\t{:.2f}\t{:.2f}'.format(
        window, grade, sqr_avg_acc_dev, avg_acc_dev, sqr_avg_ele_diff,
        avg_ele_diff))
예제 #4
0
def main(track_fpath, window, grade):

    # validate input
    fname, ext = os.path.splitext(track_fpath)
    if ext.lower() not in ['.gpx', '.tcx']:
        raise ValueError("Input file's format must be GPX or TCX")

    # parse input file
    with open(track_fpath, 'r') as f:
        track_content = f.read()
        if ext.lower() == '.gpx':
            wpts = elefix.gpx_parse(track_content)
        else:  # ext.lower() == '.tcx'
            wpts = elefix.tcx_parse(track_content)

    # remove waypoints for which the distance to the next one is 0
    i = 0
    while i < len(wpts) - 1:
        if elefix.wpt_distance(wpts[i], wpts[i + 1]) == 0.0:
            del wpts[i]
        else:
            i += 1

    # parsed original latitudes, longitudes and altitudes
    latitudes = [wpt.lat for wpt in wpts]
    longitudes = [wpt.lon for wpt in wpts]
    altitudes_orig = [wpt.alt for wpt in wpts]

    # accumulated distance on each waypoint
    dists = [
        elefix.wpt_distance(wpair[0], wpair[1])
        for wpair in zip(wpts[:-1], wpts[1:])
    ]
    dists_acc = [sum(dists[:i]) for i in range(len(wpts))]
    totaldist = dists_acc[-1]

    # original accumulated elevation gain
    eg_orig = elevation_gain(altitudes_orig, totaldist, DEFAULT_VERT_THRESHOLD)

    # SRTM raw altitudes
    altitudes_srtm_raw = elefix.set_altitudes(latitudes,
                                              longitudes,
                                              smooth=False)
    eg_srtm_raw = elevation_gain(altitudes_srtm_raw, totaldist,
                                 DEFAULT_VERT_THRESHOLD)
    diff_srtm_raw = track_avg_elevation_diff(dists_acc, altitudes_orig,
                                             altitudes_srtm_raw, True)

    # SRTM smoothed altitudes
    altitudes_srtm = elefix.set_altitudes(latitudes, longitudes, True, window,
                                          grade)
    eg_srtm = elevation_gain(altitudes_srtm, totaldist, DEFAULT_VERT_THRESHOLD)
    diff_srtm = track_avg_elevation_diff(dists_acc, altitudes_orig,
                                         altitudes_srtm, True)

    # print elevation gain values
    print("Elevation gain (original): {:.2f}".format(eg_orig *
                                                     (totaldist / 1000)))
    print("Elevation gain (SRTM + smoothing): {:.2f}".format(
        eg_srtm * (totaldist / 1000)))
    print("Elevation gain (raw SRTM): {:.2f}".format(eg_srtm_raw *
                                                     (totaldist / 1000)))
    print("Avg elevation diff (SRTM + smoothing): {:.2f}".format(diff_srtm))
    print("Avg elevation diff (raw SRTM): {:.2f}".format(diff_srtm_raw))

    # draw diagram
    wpts = []
    for w in zip(dists_acc, altitudes_orig, altitudes_srtm_raw,
                 altitudes_srtm):
        wpts.append({'dist': w[0], 'type': 'Original', 'alt': w[1]})
        wpts.append({'dist': w[0], 'type': 'SRTM', 'alt': w[2]})
        wpts.append({
            'dist': w[0],
            'type': 'SRTM + Savitzky-Golay',
            'alt': w[3]
        })
    fig = px.line(wpts,
                  x='dist',
                  y='alt',
                  color='type',
                  template='simple_white',
                  labels={
                      'dist': 'Distance',
                      'alt': 'Altitude',
                      'type': 'Data source',
                  })
    fig.update_traces(patch={"line": {
        "color": "blue",
        "width": 1
    }},
                      selector={"legendgroup": "Original"})
    fig.update_traces(patch={"line": {
        "color": "red",
        "width": 1
    }},
                      selector={"legendgroup": "SRTM"})
    fig.update_traces(patch={"line": {
        "color": "green",
        "width": 1
    }},
                      selector={"legendgroup": "SRTM + Savitzky-Golay"})
    fig.show()