B Qa{>@sddlZddlZddlZddlmZddlmZmZm Z m Z ddl m Z m Z ddlTddlTddlmZdd d ZdddZdddZdddZdddZddZdS)N)map_coordinates)geometryDatasetNamesgeometry ifgramStack timeseries)ptimereadfile)*) coordinate./TFc s*d}|st}tj|}dddg}tj|dg}t|dd}|dk rt|jdd tfd d |Drd |}|d d|7}t |dj krdj krt d |nt tjttjdt|}d|krtj|dg}ntj|dg}t|dd} | dk rZt| jdd td} | j krpt d | | nt tjttjdtj|dg}t|d|d} d|krN| dk r6t| jdd |ddkrtdd} n.|ddkrtdd} ntd |dxF| D]&} | j kr d}td | | q Wnt tjttjdnt d!|r|rntj|n|}| rtj| n| } | rtj| n| } |rt d" |dd|krt d#nt d$t d% |t d& | t d' | |rt d(t d)t d(||| | fS)*a`Check the result of loading data for the following two rules: 1. file existance 2. file attribute readability Parameters: work_dir : string, MintPy working directory print_msg : bool, print out message Returns: True, if all required files and dataset exist; otherwise, ERROR If True, PROCESS, SLC folder could be removed. stack_file : geom_file : lookup_file : Example: work_dir = os.path.expandvars('./FernandinaSenDT128/mintpy') ut.check_loaded_dataset(work_dir) T unwrapPhase rangeOffset azimuthOffsetzinputs/ifgramStack.h5)abspathNF) print_msgc3s|]}|jkVqdS)N) datasetNames).0x)objH/home/centos/operations/rsmas_insar/sources/MintPy/mintpy/utils/utils.py 9sz'check_loaded_dataset..z'required dataset is missing in file {}: z OR coherencez*WARNING: "coherence" is missing in file {}z./inputs/ifgramStack.h5X_FIRSTzinputs/geometryGeo.h5zinputs/geometryRadar.h5rz+required dataset "{}" is missing in file {}z./inputs/geometry*.h5zinputs/geometry*.h5)rr PROCESSOR)isceZdoris)gammaroipaczInSAR processor: {}z8Input data seems to be geocoded. Lookup file not needed.z2Loaded dataset are processed by InSAR software: {}z$Loaded dataset is in GEO coordinatesz&Loaded dataset is in RADAR coordinateszInterferograms Stack: {}zGeometry File : {}zLookup Table File : {}z2--------------------------------------------------zPAll data needed found/loaded/copied. Processed 2-pass InSAR data can be removed.)osgetcwdpathrjoinZ is_file_existropenallformat ValueErrorrprintFileNotFoundErrorerrnoENOENTstrerrorrread_attributekeysrrZget_lookup_fileAttributeError Exceptionrelpath) work_dirrr3 load_completeds_listflist stack_filemsgatr geom_fileZdname lookup_fileZdnamesr)rrcheck_loaded_datasets                 r=rmmeanc  Cst|} t| |d} | ||dd\} }| rRtd||td| |d\}}|dk rz| ||dd\}}t| |||||||| dd \}}}|||fS) a Read time-series of one pixel with input lat/lon Parameters: lat/lon - float, latitude/longitude ts_file - string, filename of time-series HDF5 file lookup_file - string, filename of lookup table file ref_lat/lon - float, latitude/longitude of reference pixel zero_first - bool, shift the time-series so that it starts from zero win_size - int, windows size centered at point of interest unit - str, output displacement unit method - str, method to calculate the output displacement and its dispersity Returns: dates - 1D np.ndarray of datetime.datetime objects, i.e. datetime.datetime(2010, 10, 20, 0, 0) dis - 1D np.ndarray of float32, displacement dis_std - 1D np.ndarray of float32, displacement dispersity )r<rzinput lat / lon: {} / {}zcorresponding y / x: {} / {})NNNF)ref_yref_x zero_firstwin_sizeunitmethodr)rr/r Z geo2radarr*r(read_timeseries_yx)latlonts_filer<ref_latref_lonrCrDrErFrr:coordyrrArBdatesdisdis_stdrrrread_timeseries_lalos$  rRc Cst|} | jddt| jd} t| } | rBtd|||||d|df} t j || dd} d}|dkrt |d}||||||d||df}t j ||dd | j d }|d krtj|dd } tj|dd }n0|d kr tj|dd } t|}ntd ||dk rL|||d|df}| t j ||dd8} |r^| | d8} |dkrjnF|dkr| d9} |d9}n*|dkr| d9} |d9}ntd|| | |fS)aE Read time-series of one pixel with input y/x Parameters: y/x - int, row/column number of interest ts_file - string, filename of time-series HDF5 file ref_y/x - int, row/column number of reference pixel zero_first - bool, shift the time-series so that it starts from zero win_size - int, windows size centered at point of interest unit - str, output displacement unit method - str, method to calculate the output displacement and its dispersity Returns: dates - 1D np.ndarray of datetime.datetime objects, i.e. datetime.datetime(2010, 10, 20, 0, 0) dis - 1D np.ndarray of float32, displacement dis_std - 1D np.ndarray of float32, displacement dispersity F)rrzinput y / x: {} / {}r)boxNr@r?)axismedianzun-recognized method: {}r>cmgY@mmg@@zun-supported output unit: {})rr&rdate_list2vectordateListnparrayr*r(rreadintreshapenumDatenanmeannanstd nanmedianZmedian_abs_deviationr))rNrrJrArBrCrDrErFrrrOrSrPrQbufZbox_winZdis_winZref_boxrrrrGsF    $         rGnearestcsd|}|\}}|\}}t|dt|dtfddt||g||gDsd} | d|7} | d|7} | d7} t| tt||||} tj||| tj d } tj||| tj d } |d kr|t |  tjt |  tjf} nbd d d d}|| krBd|} | d| 7} t| ||}t |t| | f|d} d}d| krt|j||gdd\}}||d}t|dtjd|t|tjd}t|dtjd|}nt|}t|}t| ||| ||}t| }|| dk9}i}| ||d<| ||d<| ||d<|||d<|S) a{Extract 2D matrix (z) value along the line [x0,y0;x1,y1] Link: http://stackoverflow.com/questions/7878398/how-to-extract-an-arbitrary-line-of-values-from-a-numpy-array Parameters: z : (np.array) 2D data matrix atr : (dict) attribute start_yx : (list) y,x coordinate of start point end_yx : (list) y,x coordinate of end point interpolation : str, sampling/interpolation method, including: 'nearest' - nearest neighbour 'linear' - linear spline interpolation (order of 1) 'cubic' - cubic spline interpolation (order of 3) 'quintic' - quintic spline interpolation (order of 5) Returns: transect: (dict) containing 1D matrix: 'X' - 1D np.array for X/column coordinates in float32 'Y' - 1D np.array for Y/row. coordinates in float32 'value' - 1D np.array for z value in float32 'distance' - 1D np.array for distance in float32 Example: transect = transect_yx(dem, demRsc, [10,15], [100,115]) LENGTHWIDTHc3sB|]:\}}d|kokno8d|ko4knVqdS)rNr)rij)lengthwidthrrrsztransect_yx..z-input start/end point is out of data coveragez start_yx: {}z end_yx:{}z data size: ({}, {}))dtypererrr!)linearZcubicZquinticz%un-supported interpolation method: {}z available methods: {})ordergTXAY_FIRSTrN) coord_typeg@X_STEPgf@Y_STEPgYXvaluedistance)lowerr^r'zipr(r)r[hypotlinspacefloat32rintastyper0rvstackr Zyx2lalofloatpicosZrange_ground_resolutionZazimuth_ground_resolutionisnan)zr:Zstart_yxZend_yx interpolationy0x0y1x1r9Znum_ptsysxsZz_lineZinterpolate_name2orderZ interp_order earth_radiusZlat0Zlat1Zlat_cx_stepy_stepZ dist_linemasktransectr)rjrkr transect_yxsT& *   .      rc Cs`t|}|j|d|dgdd\}}|j|d|dgdd\}} t||||g|| g|} | S)zAExtract 2D matrix (z) value along the line [start_lalo, end_lalo]rrH)rprrI)r Zlalo2yxr) rr: start_laloend_lalorrMrrrrrrrr transect_laloIs rc Csi}d}g|d<xtt|D]}||d||d}}d|krXt||||}nt||||}|d|7<|dkrxV|D]\} } tj| tjd|| <qWn,x*|D]\} } t || | f|| <qW|d ||dd}qWtj|dtjd|d<|S)aExtract 2D matrix (z) value along multiple lines Parameters: z : 2D np.ndarray in size of (l,w) atr : dict, metadata of matrix z lines : list of lines with each line is defined as: [[lat0, lon0], [lat1, lon1]] for geo coordinates [[y0, x0], [y1, x1]] for radar coordinates Returns: transect : (dict) containing 1D matrix: 'X' - 1D np.array for X/column coordinates in float32 'Y' - 1D np.array for Y/row. coordinates in float32 'value' - 1D np.array for z value in float32 'distance' - 1D np.array for distance in float32 rstart_distancerrorw)rlrT) rangelenr0rritemsr[r\r| concatenateappend) rr:linesrrrhrrsegkeyrvrrrtransect_linesRs$  r)r TF)NNNTrr>r?T)NNTrr>r?T)re)re)r"r,numpyr[Z scipy.ndimagermintpy.objectsrrrr mintpy.utilsrrZmintpy.utils.utils0Zmintpy.utils.utils1Zmintpy.objects.coordr r=rRrGrrrrrrr s    i ' C W