Python readfile.read_attribute函数代码示例

def file_operation(fname, operator, operand, out_file=None):
    """Mathmathic operation of file"""

    # Basic Info
    atr = readfile.read_attribute(fname)
    k = atr['FILE_TYPE']
    print('input is '+k+' file: '+fname)
    print('operation: file %s %f' % (operator, operand))

    # default output filename
    if not out_file:
        if operator in ['+', 'plus',  'add',      'addition']:
            suffix = 'plus'
        elif operator in ['-', 'minus', 'substract', 'substraction']:
            suffix = 'minus'
        elif operator in ['*', 'times', 'multiply', 'multiplication']:
            suffix = 'multiply'
        elif operator in ['/', 'obelus', 'divide',   'division']:
            suffix = 'divide'
        elif operator in ['^', 'pow', 'power']:
            suffix = 'pow'
        out_file = '{}_{}{}{}'.format(os.path.splitext(fname)[0], suffix,
                                      str(operand), os.path.splitext(fname)[1])

    atr = readfile.read_attribute(fname)
    dsNames = readfile.get_dataset_list(fname)
    dsDict = {}
    for dsName in dsNames:
        data = readfile.read(fname, datasetName=dsName)[0]
        data = data_operation(data, operator, operand)
        dsDict[dsName] = data
    writefile.write(dsDict, out_file=out_file, metadata=atr, ref_file=fname)
    return out_file

def read_subset_box(inpsDict):
    # Read subset info from template
    inpsDict['box'] = None
    inpsDict['box4geo_lut'] = None
    pix_box, geo_box = subset.read_subset_template2box(inpsDict['template_file'][0])

    # Grab required info to read input geo_box into pix_box
    try:
        lookupFile = [glob.glob(str(inpsDict['mintpy.load.lookupYFile']))[0],
                      glob.glob(str(inpsDict['mintpy.load.lookupXFile']))[0]]
    except:
        lookupFile = None

    try:
        pathKey = [i for i in datasetName2templateKey.values()
                   if i in inpsDict.keys()][0]
        file = glob.glob(str(inpsDict[pathKey]))[0]
        atr = readfile.read_attribute(file)
    except:
        atr = dict()

    geocoded = None
    if 'Y_FIRST' in atr.keys():
        geocoded = True
    else:
        geocoded = False

    # Check conflict
    if geo_box and not geocoded and lookupFile is None:
        geo_box = None
        print(('WARNING: mintpy.subset.lalo is not supported'
               ' if 1) no lookup file AND'
               '    2) radar/unkonwn coded dataset'))
        print('\tignore it and continue.')
    if not geo_box and not pix_box:
        return inpsDict

    # geo_box --> pix_box
    coord = ut.coordinate(atr, lookup_file=lookupFile)
    if geo_box is not None:
        pix_box = coord.bbox_geo2radar(geo_box)
        pix_box = coord.check_box_within_data_coverage(pix_box)
        print('input bounding box of interest in lalo: {}'.format(geo_box))
    print('box to read for datasets in y/x: {}'.format(pix_box))

    # Get box for geocoded lookup table (for gamma/roipac)
    box4geo_lut = None
    if lookupFile is not None:
        atrLut = readfile.read_attribute(lookupFile[0])
        if not geocoded and 'Y_FIRST' in atrLut.keys():
            geo_box = coord.bbox_radar2geo(pix_box)
            box4geo_lut = ut.coordinate(atrLut).bbox_geo2radar(geo_box)
            print('box to read for geocoded lookup file in y/x: {}'.format(box4geo_lut))

    inpsDict['box'] = pix_box
    inpsDict['box4geo_lut'] = box4geo_lut
    return inpsDict

def is_file_exist(file_list, abspath=True):
    """Check if any file in the file list 1) exists and 2) readable
    Parameters: file_list : list of string, file name with/without wildcards
                abspath   : bool, return absolute file name/path or not
    Returns:    file_path : string, found file name/path; None if not.
    """
    try:
        file = get_file_list(file_list, abspath=abspath)[0]
        readfile.read_attribute(file)
    except:
        file = None
    return file

def add_attribute(File, atr_new=dict(), print_msg=False):
    """Add/update input attribute into File
    Parameters: File - string, path/name of file
                atr_new - dict, attributes to be added/updated
                    if value is None, delete the item from input File attributes
    Returns:    File - string, path/name of updated file
    """
    atr = readfile.read_attribute(File)

    # Compare new attributes with exsiting ones
    update = update_attribute_or_not(atr_new, atr)
    if not update:
        print(('All updated (removed) attributes already exists (do not exists)'
               ' and have the same value, skip update.'))
        return File

    # Update attributes
    f = h5py.File(File, 'r+')
    for key, value in iter(atr_new.items()):
        # delete the item is new value is None
        if value == 'None' or value is None:
            try:
                f.attrs.pop(key)
                if print_msg:
                    print('remove {}'.format(key))
            except:
                pass
        else:
            f.attrs[key] = str(value)
            if print_msg:
                print('{} = {}'.format(key, str(value)))
    f.close()
    return File

def get_giant_ifg_list(fnames):
    m_date_list = []
    s_date_list = []
    pbase_list = []

    ext = os.path.splitext(fnames[0])[1]
    if ext == '.h5':
        obj = ifgramStack(fnames[0])
        obj.open()
        m_date_list = obj.mDates[obj.dropIfgram].tolist()
        s_date_list = obj.sDates[obj.dropIfgram].tolist()
        pbase_list = obj.pbaseIfgram[obj.dropIfgram].tolist()

    else:
        ifgramNum = len(fnames)
        print('Number of interferograms: %d' % (ifgramNum))
        for fname in fnames:
            atr = readfile.read_attribute(fname)
            m_date, s_date = ptime.yymmdd(atr['DATE12'].split('-'))
            pbase = (float(atr['P_BASELINE_TOP_HDR']) +
                     float(atr['P_BASELINE_BOTTOM_HDR'])) / 2.
            m_date_list.append(m_date)
            s_date_list.append(s_date)
            pbase_list.append(pbase)
    return m_date_list, s_date_list, pbase_list

    def run_save2google_earth(self, step_name):
        """Save velocity file in geo coordinates into Google Earth raster image."""
        if self.template['mintpy.save.kmz'] is True:
            print('creating Google Earth KMZ file for geocoded velocity file: ...')
            # input
            vel_file = 'velocity.h5'
            atr = readfile.read_attribute(vel_file)
            if 'Y_FIRST' not in atr.keys():
                vel_file = os.path.join(self.workDir, 'geo/geo_velocity.h5')

            # output
            kmz_file = '{}.kmz'.format(os.path.splitext(vel_file)[0])
            scp_args = '{} -o {}'.format(vel_file, kmz_file)
            print('save_kmz.py', scp_args)

            # update mode
            try:
                fbase = os.path.basename(kmz_file)
                kmz_file = [i for i in [fbase, './geo/{}'.format(fbase), './pic/{}'.format(fbase)] 
                            if os.path.isfile(i)][0]
            except:
                kmz_file = None
            if ut.run_or_skip(out_file=kmz_file, in_file=vel_file, check_readable=False) == 'run':
                mintpy.save_kmz.main(scp_args.split())
        else:
            print('save velocity to Google Earth format is OFF.')
        return

    def run_geocode(self, step_name):
        """geocode data files in radar coordinates into ./geo folder."""
        if self.template['mintpy.geocode']:
            ts_file = self.get_timeseries_filename(self.template)[step_name]['input']
            atr = readfile.read_attribute(ts_file)
            if 'Y_FIRST' not in atr.keys():
                # 1. geocode
                out_dir = os.path.join(self.workDir, 'geo')
                if not os.path.isdir(out_dir):
                    os.makedirs(out_dir)
                    print('create directory:', out_dir)

                geom_file, lookup_file = ut.check_loaded_dataset(self.workDir, print_msg=False)[2:4]
                in_files = [geom_file, 'temporalCoherence.h5', ts_file, 'velocity.h5']
                scp_args = '-l {l} -t {t} --outdir {o} --update '.format(l=lookup_file,
                                                                         t=self.templateFile,
                                                                         o=out_dir)
                for in_file in in_files:
                    scp_args += ' {}'.format(in_file)
                print('geocode.py', scp_args)
                mintpy.geocode.main(scp_args.split())

                # 2. generate reliable pixel mask in geo coordinate
                geom_file = os.path.join(out_dir, 'geo_{}'.format(os.path.basename(geom_file)))
                tcoh_file = os.path.join(out_dir, 'geo_temporalCoherence.h5')
                mask_file = os.path.join(out_dir, 'geo_maskTempCoh.h5')
                tcoh_min = self.template['mintpy.networkInversion.minTempCoh']
                scp_args = '{} -m {} -o {} --shadow {}'.format(tcoh_file, tcoh_min, mask_file, geom_file)
                print('generate_mask.py', scp_args)
                if ut.run_or_skip(out_file=mask_file, in_file=tcoh_file) == 'run':
                    mintpy.generate_mask.main(scp_args.split())
        else:
            print('geocoding is OFF')
        return

def prepare_stack(inputDir, filePattern, metadata=dict(), baseline_dict=dict(), update_mode=True):
    print('prepare .rsc file for ', filePattern)
    isce_files = sorted(glob.glob(os.path.join(os.path.abspath(inputDir), '*', filePattern)))
    if len(isce_files) == 0:
        raise FileNotFoundError('no file found in pattern: {}'.format(filePattern))

    # write .rsc file for each interferogram file
    num_file = len(isce_files)
    prog_bar = ptime.progressBar(maxValue=num_file)
    for i in range(num_file):
        isce_file = isce_files[i]
        # prepare metadata for current file
        ifg_metadata = readfile.read_attribute(isce_file, metafile_ext='.xml')
        ifg_metadata.update(metadata)
        dates = os.path.basename(os.path.dirname(isce_file)).split('_')
        ifg_metadata = add_ifgram_metadata(ifg_metadata, dates, baseline_dict)

        # write .rsc file
        rsc_file = isce_file+'.rsc'
        writefile.write_roipac_rsc(ifg_metadata, rsc_file,
                                   update_mode=update_mode,
                                   print_msg=False)
        prog_bar.update(i+1, suffix='{}_{}'.format(dates[0], dates[1]))
    prog_bar.close()
    return

def add_file(fnames, out_file=None):
    """Generate sum of all input files
    Parameters: fnames : list of str, path/name of input files to be added
                out_file : str, optional, path/name of output file
    Returns:    out_file : str, path/name of output file
    Example:    'mask_all.h5' = add_file(['mask_1.h5','mask_2.h5','mask_3.h5'], 'mask_all.h5')
    """
    # Default output file name
    ext = os.path.splitext(fnames[0])[1]
    if not out_file:
        out_file = os.path.splitext(fnames[0])[0]
        for i in range(1, len(fnames)):
            out_file += '_plus_' + os.path.splitext(os.path.basename(fnames[i]))[0]
        out_file += ext

    atr = readfile.read_attribute(fnames[0])
    dsNames = readfile.get_dataset_list(fnames[0])
    dsDict = {}
    for dsName in dsNames:
        print('adding {} ...'.format(dsName))
        data = readfile.read(fnames[0], datasetName=dsName)[0]
        for i in range(1, len(fnames)):
            d = readfile.read(fnames[i], datasetName=dsName)[0]
            data = add_matrix(data, d)
        dsDict[dsName] = data
    writefile.write(dsDict, out_file=out_file, metadata=atr, ref_file=fnames[0])
    return out_file

def main(argv):
    if len(sys.argv) < 3:
        usage()
        sys.exit(1)

    lat = float(argv[0])
    lon = float(argv[1])

    try:
        trans_file = argv[2]
    except:
        trans_file = ut.get_lookup_file()

    try:
        radar_file = argv[3]
    except:
        radar_file = 'inputs/ifgramStack.h5'

    atr_rdr = readfile.read_attribute(radar_file)

    print('input geo coord: lat=%.4f, lon=%.4f' % (lat, lon))

    coord = ut.coordinate(atr_rdr, lookup_file=trans_file)
    y, x = coord.geo2radar(np.array(lat), np.array(lon))[0:2]
    print('corresponding radar coord: y=%d, x=%d' % (y, x))
    return

def multilook_file(infile, lks_y, lks_x, outfile=None):
    lks_y = int(lks_y)
    lks_x = int(lks_x)

    # input file info
    atr = readfile.read_attribute(infile)
    k = atr['FILE_TYPE']
    print('multilooking {} {} file: {}'.format(atr['PROCESSOR'], k, infile))
    print('number of looks in y / azimuth direction: %d' % lks_y)
    print('number of looks in x / range   direction: %d' % lks_x)

    # output file name
    if not outfile:
        if os.getcwd() == os.path.dirname(os.path.abspath(infile)):
            ext = os.path.splitext(infile)[1]
            outfile = os.path.splitext(infile)[0]+'_'+str(lks_y)+'alks_'+str(lks_x)+'rlks'+ext
        else:
            outfile = os.path.basename(infile)
    #print('writing >>> '+outfile)

    # read source data and multilooking
    dsNames = readfile.get_dataset_list(infile)
    maxDigit = max([len(i) for i in dsNames])
    dsDict = dict()
    for dsName in dsNames:
        print('multilooking {d:<{w}} from {f} ...'.format(
            d=dsName, w=maxDigit, f=os.path.basename(infile)))
        data = readfile.read(infile, datasetName=dsName, print_msg=False)[0]
        data = multilook_data(data, lks_y, lks_x)
        dsDict[dsName] = data
    atr = multilook_attribute(atr, lks_y, lks_x)
    writefile.write(dsDict, out_file=outfile, metadata=atr, ref_file=infile)
    return outfile

def read_timeseries_yx(timeseries_file, y, x, ref_yx=None):
    '''Read time-series displacement on point (y,x) from timeseries_file
    Inputs:
        timeseries_file : string, name/path of timeseries hdf5 file
        y/x : int, row/column number of point of interest
    Output:
        dis_ts : list of float, displacement time-series of point of interest
    '''
    atr = readfile.read_attribute(timeseries_file)
    k = atr['FILE_TYPE']
    dis_ts = []

    if k in ['GIANT_TS']:
        h5 = h5py.File(timeseries_file, 'r')
        date_list = [dt.fromordinal(int(i)).strftime('%Y%m%d') for i in h5['dates'][:].tolist()]
        dname = [i for i in ['rawts','recons'] if i in list(h5.keys())][0]
        dis_ts = h5[dname][:,y,x]
        if ref_yx is not None:
            dis_ts = h5[dname][:,ref_yx[0],ref_yx[1]]
        h5.close()
    else:
        box = [x, y, x+1, y+1]
        dis_ts = timeseries(timeseries_file).read(box=box, print_msg=False)
        #date_list = list(h5[k].keys())
        #for date in date_list:
        #    dis = h5[k].get(date)[y,x]
        #    if inps.ref_yx:
        #        dis -= h5[k].get(date)[ref_yx[0], ref_yx[1]]
        #    dis_ts.append(dis)
        #dis_ts = np.array(dis_ts)

    return dis_ts

def _check_inps(inps):
    inps.file = ut.get_file_list(inps.file)
    if not inps.file:
        raise Exception('ERROR: no input file found!')
    elif len(inps.file) > 1:
        inps.outfile = None

    atr = readfile.read_attribute(inps.file[0])
    if 'Y_FIRST' in atr.keys() and inps.radar2geo:
        print('input file is already geocoded')
        print('to resample geocoded files into radar coordinates, use --geo2radar option')
        print('exit without doing anything.')
        sys.exit(0)
    elif 'Y_FIRST' not in atr.keys() and not inps.radar2geo:
        print('input file is already in radar coordinates, exit without doing anything')
        sys.exit(0)

    inps.lookupFile = ut.get_lookup_file(inps.lookupFile)
    if not inps.lookupFile:
        raise FileNotFoundError('No lookup table found! Can not geocode without it.')

    if inps.SNWE:
        inps.SNWE = tuple(inps.SNWE)

    inps.laloStep = [inps.latStep, inps.lonStep]
    if None in inps.laloStep:
        inps.laloStep = None

    inps.nprocs = check_num_processor(inps.nprocs)
    return inps

def timeseries2ifgram(ts_file, ifgram_file, out_file='reconUnwrapIfgram.h5'):
    # read time-series
    atr = readfile.read_attribute(ts_file)
    range2phase = -4.*np.pi / float(atr['WAVELENGTH'])
    print('reading timeseries data from file {} ...'.format(ts_file))
    ts_data = readfile.read(ts_file)[0] * range2phase
    num_date, length, width = ts_data.shape
    ts_data = ts_data.reshape(num_date, -1)

    # reconstruct unwrapPhase
    print('reconstructing the interferograms from timeseries')
    stack_obj = ifgramStack(ifgram_file)
    stack_obj.open(print_msg=False)
    A1 = stack_obj.get_design_matrix4timeseries(stack_obj.get_date12_list(dropIfgram=False))[0]
    num_ifgram = A1.shape[0]
    A0 = -1.*np.ones((num_ifgram, 1))
    A = np.hstack((A0, A1))
    ifgram_est = np.dot(A, ts_data).reshape(num_ifgram, length, width)
    ifgram_est = np.array(ifgram_est, dtype=ts_data.dtype)
    del ts_data

    # write to ifgram file
    dsDict = {}
    dsDict['unwrapPhase'] = ifgram_est
    writefile.write(dsDict, out_file=out_file, ref_file=ifgram_file)
    return ifgram_file

def get_date12_list(fname, dropIfgram=False):
    """Read Date12 info from input file: Pairs.list or multi-group hdf5 file
    Inputs:
        fname       - string, path/name of input multi-group hdf5 file or text file
        dropIfgram  - bool, check the "DROP_IFGRAM" attribute or not for multi-group hdf5 file
    Output:
        date12_list - list of string in YYMMDD-YYMMDD format
    Example:
        date12List = get_date12_list('ifgramStack.h5')
        date12List = get_date12_list('ifgramStack.h5', dropIfgram=True)
        date12List = get_date12_list('Pairs.list')
    """
    date12_list = []
    ext = os.path.splitext(fname)[1].lower()
    if ext == '.h5':
        k = readfile.read_attribute(fname)['FILE_TYPE']
        if k == 'ifgramStack':
            date12_list = ifgramStack(fname).get_date12_list(dropIfgram=dropIfgram)
        else:
            return None
    else:
        txtContent = np.loadtxt(fname, dtype=bytes).astype(str)
        if len(txtContent.shape) == 1:
            txtContent = txtContent.reshape(-1, 1)
        date12_list = [i for i in txtContent[:, 0]]
    date12_list = sorted(date12_list)
    return date12_list