Zf3TdZddlZddlZddlZddlmZddlmZm Z m Z m Z ddl m Z ddlmZddlmZmZmZddlddldd Z dd Z dd Zdd Zdd ZdZddZy)z0Miscellaneous utilities - dependent on utils0/1.N)map_coordinates)GEOMETRY_DSET_NAMESgeometry ifgramStack timeseries) coordinate)resample) attributeptimereadfile)*cv |stj}tjj|}tjj |d}t j |d}|dk(rd}nd}tjj |d}gd}t|d rt|jd tfd |Dr%d |d}|dj |z }t|djvr\djvrNtd|n?ttj tj"tj ||zt j$|} d| j'vrdnd} | d} tjj |dd| j)d} t*d} t| d rz'check_loaded_dataset..As9Qq(((9sz$required dataset is missing in file z: z OR r coherencez(WARNING: "coherence" is missing in file Y_FIRSTGEORADAR PROCESSORinputsrz.h5rzrequired dataset "z" is missing in file zinputs/geometry*.h5)rrN)iscedoris)gammaroipaczUnknown InSAR processor: z to locate look up table!z8Input data seems to be geocoded. Lookup file not needed.zinputs/ionStack.h5z0Loaded dataset are processed by InSAR software: z Loaded dataset are in z coordinatesz Interferogram Stack: z Ionosphere Stack: z Geometry File : z Lookup Table File : z3 --------------------------------------------------)osgetcwdpathrjoinr read_template is_file_existropenall ValueErrorrprintFileNotFoundErrorerrnoENOENTstrerrorread_attributekeys capitalizerrget_lookup_fileAttributeError Exceptionrelpath)work_dirrr? template_fileprocmsg_aria stack_filednamesmsgatr coord_type processor geom_filedname lookup_fileion_filers @rcheck_loaded_datasetrNs~ 99;wwx(HGGLL+ABM  ! !- 01H ID v~eh(?@J ?K!+tyQKW  ";'C HHuH %--,Qq111,Qq11)bggooh/xA)M )*\BB ( 55 x( 3RG ( 44 ( 66  c y+x 77c 8tj|} t| |} | j||dd\} }| r"t d|d|t d| d|d\}}|| j||dd\}}t | |||||||| d \}}}|||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 )rLrzinput lat / lon:  / zcorresponding y / x: )NNF)ref_yref_x zero_firstwin_sizeunitmethodr)r r9r geo2radarr4read_timeseries_yx)latlonts_filerLref_latref_lonrUrVrWrXrrGcoordyrrSrTdatesdisdis_stds rread_timeseries_lalores  ! !' *C s 4E ??3 $Qq )DAq !#c#/0 %aSA3/0LE5w81= u-Q738388B6>264:7<>E3 #w rOc t|} | jdtj| jd} t j | } | rtd|d||||dz|dzf} tj|| d} d}|dk7rt|d z }||z ||z ||zdz||zdzf}tj||dj| jd }|d k(r/t j|d } t j|d }n6|d k(r#t j|d } t!|}nt#d||)|||dz|dzf}| tj||dz} |r| | dz} |dk(rn6|dk(r| dz} |dn|dz}n"|dk(r| dz} |dn|dz}nt#d|| | |fS)aE Read time-series of one pixel with input y/x Parameters: y/x - int, row/column number of interest ts_file - string, filename of time-series HDF5 file ref_y/x - int, row/column number of reference pixel zero_first - bool, shift the time-series so that it starts from zero win_size - int, windows size centered at point of interest unit - str, output displacement unit method - str, method to calculate the output displacement and its dispersity Returns: dates - 1D np.ndarray of datetime.datetime objects, i.e. datetime.datetime(2010, 10, 20, 0, 0) dis - 1D np.ndarray of float32, displacement dis_std - 1D np.ndarray of float32, displacement dispersity Frrz input y / x: rRr&)boxNrQmean)axismedianzun-recognized method: mcmgY@mmg@@zun-supported output unit: )rr1r date_list2vectordateListnparrayr4r readintreshapenumDatenanmeannanstd nanmedianmedian_abs_deviationr3)rarr]rSrTrUrVrWrXrrrbrgrcrdbufbox_windis_winref_boxs rrZrZs W CHHuH  " "3<< 0 3E HHUOE aSA3'( a1ac C --S )! ,CG1}(Q,S5!C%3q!C%'2--W5a8@@bQ V **W1-Ciia0G x ,,wQ/C*73G5fX>? ? %q%'2 x}}W'2155 s1v  s{  t !/$w~  u !/$w5dV<== #w rOcR|j}|\}}|\}}t|dt|dctfdt||g||gDs)d} | d|z } | d|z } | ddd z } t | tt j ||z ||z } t j||| t j } t j||| t j } |d k(rT|t j| jtt j| jtf} ntd d dd}||jvr&d|} | d|jz } t | ||j}t|t j| | f|} d}d}d|jvrt|d}t|d}|jddst!|j#||g||gd\}}||zdz }|t j$dz |zz}|t j$dz |zt j&|t j$zdz zz}n t)|}t+|}t j | |z |z| |z |z}t j.| }|| dk7z}i}| ||d <| ||d!<| ||d"<|||d#<||d$<|S#t,$r d }d }d}YzwxYw)%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.ndarray) 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: from mintpy.utils import readfile, utils as ut dem, atr = readfile.read('srtm1.dem.wgs84') txn = transect_yx(dem, atr, [10,15], [100,115]) LENGTHWIDTHc3hK|])\}}d|cxkxrkncxrd|cxkxrknc+yw)rN)rijlengthwidths rrztransect_yx..%s-QCAaq1}u}/Q/Qs/2z-input start/end point is out of data coveragez start_yx: z end_yx:z data size: (z, )dtypenearestr&r'r*)linearcubicquinticz#un-supported interpolation method: z available methods: )ordergTXArlrY_STEPX_STEPUTM_ZONENrg@f@pixelgYXvaluedistance distance_unit)lowerrtr2zipr3rqhypotlinspacefloat32rintastyper:rvstackfloatgetryx2lalopicosrange_ground_resolutionazimuth_ground_resolutionKeyErrorisnan)zrGstart_yxend_yx interpolationy0x0y1x1rFnum_ptsysxsz_lineinterpolate_name2order interp_order earth_radius dist_unity_stepx_steplat0lat1lat_c dist_linemasktransectrrs @@r transect_yxrsP0"'')MHRHRH &CL(9MFE Q32wB;PQ Q= hZ(( 6(## xr%22o"((2b5"R%()G RWBJJ 7B RWBJJ 7B  !2772;%%c*BGGBK,>,>s,CCD "   6 ; ; = =7 GC *+A+F+F+H*IJ JCS/ !-m.A.A.CD  BIIr2h$7|LLICHHJs8}%s8}%wwz4(%c?22B8b"XFqILT4D[B&E beeEkL0 0F beeEkL0266%"%%-:K3LL LF ,S1F.s3F "r'V+r'V+-I HHV  DFcMDHtHHSMtHHSMt HW$T?HZ )H_ O' FFI sLL&%L&ct|}|j|d|dg|d|dg\\}}\}} t||||g|| g|} | S)aExtract 2D matrix (z) value along the line [start_lalo, end_lalo] Parameters: z : (np.ndarray) 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: from mintpy.utils import readfile, utils as ut vel, atr = readfile.read('geo_velocity_msk.h5') txn = transect_yx(vel, atr, [30.0, 110.0], [30.2, 111.3]) rr&)rlalo2yxr) rrG start_laloend_lalorr`rrrrrs r transect_lalorksg. sOE 1 x{'C(21 x{'CEHRhr21cB8b"X}EH OrOcNi}d}g|d<t|D]\}}|d|d}}d|jvrt||||} nt||||} | dxx|z cc<|dk(rA| j D]-\} } t j | t j|| </n5| j D]"\} } t j|| | f|| <$|dj||dd}t j |dt j|d<|S)aExtract 2D matrix (z) value along multiple lines Parameters: z : 2D np.ndarray in size of (l,w) atr : dict, metadata of matrix z lines : list of lines with each line is defined as: [[lat0, lon0], [lat1, lon1]] for geo coordinates [[y0, x0], [y1, x1]] for radar coordinates Returns: transect : (dict) containing 1D matrix: 'X' - 1D np.array for X/column coordinates in float32 'Y' - 1D np.array for Y/row. coordinates in float32 'value' - 1D np.array for z value in float32 'distance' - 1D np.array for distance in float32 rstart_distancer&rrrrh) enumerater:rritemsrqrrr concatenateappend) rrGlinesrrrlinerrsegkeyrs rtransect_linesrs>HN!#H U#24#AwQH  "3 H=Caj(;C J>) 6!iik B U "bjj A  B"iik G U " u/E F  G !")).9!*-b1)2*"$(3C*DBJJ!WH  OrOctd|tj|}td|tj|dd}dtj|vr)td|tj|dd}n_tdtd t j |jt j t|d z}t|}d |jvrtd tdt||}|j|j|jd}|j!||d|d|d|df}|j!||d|d|d|df}t#j$||}|dj'j)dst+|dt+|d} }t|d } t|d} t|d} t|d} | | |zz}| | | zz}t-|| | \}}t-|||\}}||z |z }||z | z }||d <||d<||d<||d<d|d<d|d<t j.||dk(<|j)dr,|t j0dz z}|t j0dz z}|||fS) a Prepare LOS geometry data/info in geo-coordinates. Parameters: geom_file - str, path of geometry file unit - str, rad or deg, output angle unit Returns: inc_angle - 2D np.ndarray, incidence angle in radians / degrees measured from the vertical az_angle - 2D np.ndarray, azimuth angle in radians / degrees measured from the north with anti-clockwise direction as positive atr - dict, metadata in geo-coordinate z3prepare LOS geometry in geo-coordinates from file: zread incidenceAngle from file: incidenceAngle) datasetNamer azimuthAnglezread azimuthAngle from file: z3use the HEADING attribute as the mean heading anglez&convert heading angle to azimuth anglerHEADINGrz2--------------------------------------------------z,geocoding the incidence / heading angles ...)lut_filesrc_filer&r'rQ)src_data)res_objY_UNITdegrrX_FIRSTrrdegreesX_UNITradr)r4r r9rsget_dataset_listrqonesshaperrheading2azimuth_angler:r r1prepare src_box_list run_resampleattrupdate_attribute4radar2geor startswithrt utm2latlonnanr)rJrWrG inc_angleaz_angle head_anglerrgrrNWrrSErlon0rlon1lat_steplon_steps rprepare_geo_los_geometryrs ? { KL  ! !) ,C +I; 78 i5EFqII229== / {;<MM)HK CD 67WWY__BJJ?%IBWW (4 " f  <=I B ""1%(()CF3q6M3q6RUVWRX=rst6 ) ,,;;!!y8zUYY]$NJNFJ@HaH<'ZM$rO