o 4iS@sddlmZddlmZddlTddlmZmZddlmZddl m Z ddl m Z ddl mZddlmZddlmZddlmZddlZddlZddlZddlmZddlZddlZdd lmZdd lmZddl Z d d Z!gd Z"dddZ#ddZ$ddZ%dddZ&ddZ'dddZ(dddZ)d d!Z*Gd"d#d#e+Z,Gd$d%d%e-Z.dd&d'Z/d(d)Z0dd+d,Z1de+fd-d.Z2d/d0Z3Gd1d2d2Z4Gd3d4d4e+Z5d5d6Z6d7d8Z7dd:d;Z8dd?d?e+Z:dd@dAZ;dBdCZdHdIZ?ddKdLZ@dMdNZAdOdPZBdQdRZCdSdTZDdUdVZEdWdXZFdYdZZGdd[d\ZHdd]d^ZId_d`ZJddadbZKdcddZLdedfZMdgdhZNddjdkZOddldmZPdndoZQdpdqZRdrdsZSddtduZTddvdwZUGdxdydye+ZVGdzd{d{e+ZWd|d}ZXd~dZYddZZddZ[ddZ\ddZ]dddZ^dddZ_dddZ`ddZaddZbddZcdddZdddZedddZfdddZgddZhdddZidddZjdddZkdddZldddZmdddZndddZoddZpGdddejqZrdddZsddZtddZuddZvddZwddd„ZxddĄZydddƄZzddȄZ{dddʄZ|ddd̄Z}ddd΄Z~ddЄZdd҄Z 9 dddԄZdddքZddd؄ZddڄZdd܄Zdejfdd߄ZdddZ  9dddZddZddZdS()absolute_import)pylab)*)butterfiltfilt)print_)rangeN)Image)glob) namedtuplecCs t|dS)Nr)wherexrB/home/russ/Documents/_GNSS_data/2026/SUMO-343_bench_test/mutils.pyfind r)2zAuto LSQzGNSS LSQzSBAS LSQz RTK Floatz RTK Fixedz WA RTK Floatz WA RTK FixedOmniSTARz CDGPS - ObszAuto KFzDGNSS KFzSBAS KFzCDGPS KF - ObszSBAS+ KFzSBAS/CDPGS+ KF - ObsRTXz XPS CoarsezXPS FinezINS Autoz INS DGNSSzINS RTKzINS SBASzINS RTXzINS GVBSzINS OmnizINS DRGVBSzRTX FastxFillXzRTX Litez RTX Lite L1zRTX Field PointzRTX Fast RAM -??zAuto TNzGNSS TNzSBAS TNz QZSS SLAS LSQz QZSS SLAS KFz INS xFillXCLASzINS CLASHASzINS HASSouthPANz INS SouthPANz BEIDOU PPPzINS BEIDOU PPPzINS SLASBVRSzINS BVRSTcstj|rtdfdd}|d}|d}d|vrcddlm}|d}||}g}d} | dkr=d } nd | } | |vrJ t |Sd |vrW||| jn||| | d 7} q6dd} |d}d} | D]} | }t |dkr| |drn| d 7} qrddl}ddlm}|d}z-| dd d}||j|dkr|sd|d<n|sd|d<|j|fi|j|jddjWS|jjytgYSw)a> filename=text file or viewdat --mat output. [verbose=True - print status info when loading file?] [error_bad_lines=False - pass error_bad_lines to pandas read_csv? Skips lines with errors.] Accepts gzip'd files ending in '.gz' and bzip'd files ending in '.bz2' Returns numpy array with data. z Loading %s...csFdrddl}||Sdrddl}||St|S)N.gzr.bz2)endswithgzipopenbz2BZ2File)fnamemoderr filenamerrmyopenbs     zdoload..myopenrbr)loadmatTdatazdata%ds C librarycSs$zt|WdStyYdSw)NFTfloat ValueError)srrris_string_a_floats   z!doload..is_string_a_floatrN)parse)skiprowsheaderdelim_whitespacez1.3.0skip on_bad_linesFerror_bad_linescoerceerrors)ospath expanduserprintreadscipy.ior*appendT concatenate readlinesstripsplitlenpandaspackaging.versionr3 __version__read_csvapply to_numericvaluesr<EmptyDataErrorarray)r%verboser9r&fbytesr*raw_dall_dcurr_ivar_namer1nlwpd parse_versioncsv_argsrr$rdoloadVsl             r`ccs.|D]}||vr|||}|VqdSN)replacerH) input_streampattern1pattern2linenew_linerrr_substitute_liness  rhc Csddl}ddl}ddl}ddl}ddl}|\}}} } td|| dr9|j|| d||j dd} | j } n"| drDt |d } n| d rP| |d } n | d r[| |d } t | || } z | | j|jd d jWStdYS)zSee doload_sedrNzdoload_sed loading viewdat T)stdouttextcatrtzcatbzcatr:r;)shlex subprocessrJr rr@ startswithPopenrHPIPErkrrh DataFramerNrOrPzeros) infoseprqspr]r rr%pat1pat2cmdrmsubstituted_linesrrr_doload_sed_helps0           r\s+cs2ddl}t|turtttj|}n tdd|D}|durM|ddr,d}n!|ddr6d}n|d d sH|d d rKd }nd }g}|D] } | | |||fqQd} fd d} t |dkr|r|j } | | |} Wdn1swYnt| |} dd| D} t| S)a Used to run "sed" on a file before loading it. 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'nan' values are empty For example: plot( data['GPS_Sec'], data['Platf13_GnssRcv0_R02_D1C-R_Std']) (The files use RINEX encoding for signals) cSrrr-r rrrr2rzload_hud.._is_numberri;Nrr,cSsg|]}|qSr)rG)rw0rrrrPzload_hud..) rrrHrPrCrzipr.itemsrR)r% max_linesrr+ curr_hdrsr prev_hdr_linerr[r\colhdrvalkeyrrrload_hud's:     rcs|durt|Sdt|tfdd|Dr|t|Stdd|Drottt||\}}d}d}|krK|d7}|||d7}|ks;|||d8}|kri||d|}t|tt|S||dSdS) z(Calculate the weighted median of a list.N?csg|]}|kqSrrrjmidpointrrr_rz#weighted_median..cSsg|]}|dkqSrrrrrrrarrr,)mediansumanyargmaxrrr.rI)r+weights sorted_datasorted_weightscumulative_weightbelow_midpoint_indexboundsrrrweighted_medianZs&   rcCslddl}t|d\}}|dd|df}d|vrd}nd}|dd||df}|dd||d f} |dd|d f} tt|} td | d d dd\} } t| | | dd} ||jtt ||d|jtt ||dd|j fdd}t d|d|d|j f|d|d|j ffd}t dd}t d|dt d|dd}| D]s\}}|d}t|sq|d}||} | | d kr| |7} t|s| dkrqt|}|||jftjd }t|rt|}||| |}| |}|}|}|}n ||| }|d!}|d"krqt d#|| | |f|dqWddS1s/wYdS)$zGenerates RefClock.txt for SNPC based on Titan's clock. Titan usually provides a very good clock estimate. titan_dir = directory containing PKFEE_States_RcvClkBias.hud d,k = rec 35:2 from vd2arr() rN/PKFEE_States_RcvClkBias.hudGPS_Sec(SatSysDepRcvClk_Platf00_GnssRcv0_G00_Val%SatSysDepRcvClk_Platf00_GnssRcv0_G00_#SatSysDepRcvClk_Platf00_GnssRcv0_G_ValStdz&CodeRcvBias_Platf00_GnssRcv0_C1C-G_Valrrlowpassbtypegustmethod)index)clkrz,Titan/d start_t = %.1f/%.1f, end_t %.1f/%.1fru"Az RefClock.txtr\z % clk_types 1)filez% 0 0.0g$rrg?.ArY@z%.3f %.1f %.3f %.1f)rJrrdiffrrrvSeriesrrITIMErriterrowsisfiniteintCLKDRIFT GnssConstLIGHT) titan_dirrkr]hClkdClktclkkeyclk_bias clk_sigma code_biasdtbadf SECS_IN_WEEKoutfile last_clk_tcurr_trowiposiclkmydriftmybiasmysigma last_clk_biaslast_clk_sigmarrrgen_titan_ref_clockos^ "0      $r c@s`eZdZdZdddZddZddZd d Zdd dZddZ ddZ dddZ dddZ dS) TitanHudPKFEEz?Load the (measurement) Titan PKFEE HUD files in given directory cCslt|d\|_|_t|d\|_|_t|d\|_|_t|d\|_|_d|_ i|_ i|_ ||_ dS)Nz/PKFEE_FilterRes_GNSS.hudz/PKFEE_States_Amb.hudz/PKFEE_States_RcvSatBias.hudr) rhResdReshAmbdAmbhMPdMPrr amb_medianL1_reduced_ambL1_MP_plus_ambplatf)selfdirnamerrrr__init__s zTitanHudPKFEE.__init__cCs&|D]}t||}|r|SqdS)z)Get HUD header value that matches patternN)rematch)rrpatternhmrrrget_IDs  zTitanHudPKFEE.get_IDcCT|tjkr d|j|fS|tjkrd|j|fS|tjkr$d|j|fStd|)NzPlatf%.2d_.*G%.2d_[PC]1C-G_zPlatf%.2d_.*R%.2d_[PC]1C-R_zPlatf%.2d_.*C%.2d_[PC]1I-C_unknown sat_type %dRTConstRT_SatType_GPSrRT_SatType_GLONASSRT_SatType_BEIDOU_B1GEOPhsr/rsv_idsat_typerrr get_cde_pat    zTitanHudPKFEE.get_cde_patcCr#)NzPlatf%.2d_.*G%.2d_L1C-G_zPlatf%.2d_.*R%.2d_L1C-R_zPlatf%.2d_.*C%.2d_L1I-C_r$r%r*rrr get_phs_patr.zTitanHudPKFEE.get_phs_patTcCs$|||}|tjkrd}n|tjkrd}n|tjkrd}ntd|||j|d}||j|d}|dus>|durCgggfS|jdd|jdf} |jdd|j|f} |jdd|j|f} |r||j |}|j dd|j |f} t t | | } | | } | | | | t | | } | | } nt t | } | | } | | } | | } |d kr tt| }td |d |d d \}}d }t t| |dkD]%}||kr| ||| ||<nt||| ||dd| ||<|d}qt| }t||| ||dd| ||<| | | fS)aReturns code residuals: t, cde_val [m], cde_std [m]. 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If filt_Tc > 0, run low pass filter on cde_res with this time constant. z)CodeRcvBias_Platf00_GnssRcv0_[PC]1C-G_Valz)CodeRcvBias_Platf00_GnssRcv0_[PC]1C-R_Valz)CodeRcvBias_Platf00_GnssRcv0_[PC]1I-C_Valr$rrNrrrrrrMbP?rrr,)r-r&r'r(r)r/r"rrrrrisnanrminrrrrI)rr+r, remove_clkfilt_TcresPatbiasPatid1id2rcde_valcde_stdtclkirrrstart_iend_irrrget_L1_cde_ressL             zTitanHudPKFEE.get_L1_cde_resc Cs|||}||j|d}||j|d}|jdd|jdf}|jdd|j|f}|jdd|j|f}|||fS)z4Returns phase residuals: t, phs_val [m], phs_std [m]rrNr)r/r"rr) rr+r,r6r8r9rphs_valphs_stdrrrget_L1_phs_ress  zTitanHudPKFEE.get_L1_phs_rescCsg}|jD]A}td|}|r|t|dtjftd|}|r1|t|dtjftd|}|rF|t|dtj fqt dd|D}t dd|DS)zRReturns list of all sv IDs (sv_id, RT_SatType) that have PKFEE_States_amb.hud dataz.*?_G([0-9][0-9])_[PL]1r,z.*?_R([0-9][0-9])_[PL]1z.*?_C([0-9][0-9])_[PL]1cSsg|] \}}||dqSr)rsvr,rrrrrz-TitanHudPKFEE.get_amb_svs..cS$g|]}t|dt|dfqSrDrrrrrr$) rrrrCrgroupr&r'r(r)uniquerR)rsv_listrr! svs_combinedrrr get_amb_svs s    zTitanHudPKFEE.get_amb_svsFcCsd|||}||j|d}||j|d}|jdd|jdf}|jdd|j|f}|jdd|j|f} |r]|||\} } } t|| t| \} } }t|| <t| | <||| fS)a"Get all L1 phase multipath: t [s], phs_val [m], phs_std [m]. Look at phs_res to see if data is used. This doesn't include any drift found by the phase AMB states. If only_valid=False -> return all MP data. If True -> set invalid MP data to nan (based on phs_res).PhaseMP_rrNr)r/r"rrrC intersectr2r)rr+r, only_validmpPatr8r9rrArBt2phs_res_i1i2rrr get_L1_phs_MPs zTitanHudPKFEE.get_L1_phs_MPcCsd|||}||j|d}||j|d}|jdd|jdf}|jdd|j|f}|jdd|j|f} |||\} } } |r]t|| t| \} } }t|| <t| | <||| | fS)zGet all L1 code multipath: t [s], cde_val [m], cde_std [m], cde_res [m]. If only_valid=False -> return all MP data. If True -> set invalid MP data to nan (based on cde_res).CodeMP_rrNr)r-r"rrr@rPr2r)rr+r,rQrRr8r9t1r:r;rScde_resrUrVrWrrr get_L1_cde_MP-s zTitanHudPKFEE.get_L1_cde_MPN)r)Tr0F) __name__ __module__ __qualname____doc__rr"r-r/r@rCrNrXr\rrrrrs   1 rcsHeZdZiZejZejZfddZ ddZ ddZ fddZ Z S) rcs>t|tks t|tkrddt|D}tt||dS)NcSsi|]\}}||qSrr)rrZrrrr Lz$dotdict.__init__..)rlisttuplersuperrr)ridict __class__rrrJszdotdict.__init__cCsiSrarrrrr __getstate__Nzdotdict.__getstate__cCsdSrar)rrrrr __setstate__Prlzdotdict.__setstate__cs*tt|||j}||jurt||Sra)rfrget unique_valKeyError)rnameobjrhrr __getattr__Rs zdotdict.__getattr__)r^r_r`rodict __setitem__ __setattr__ __delitem__ __delattr__rrkrmrs __classcell__rrrhrrFs rc Cs|ddl}|\}}}}}|rtd|d|}|jdd|d|g|||dg} z t|d|d d } W| SY| S) Nrz loading... %sz temp%d.matriz--mat=%s-h)cwd/FrS)rrrcallr`) info_listrSrzrTrecoptmydirrZtmpfilerrrr _vd2arr_helpXs "rc Cs|\}}}}}d|vrd|vst|dkrtdtd|d}ddl}t}t|d|||ddg|\}} t|| dkrStd t | td t| d kr}|d } t | d }t ||Wd| S1svwY| S|S)N-d35:2z-d35:19rzcrec opt unacceptable. Current BoostPythonViewdat module only accepts -d35:2 or -d35:19 with no opt.zloading(by boostpython) ... %sr|z --mat_memrzz err_code = z%BoostPythonViewdat.get_vdata() failediHz/tmp.npywb)rI ExceptionrBoostPythonViewdatr=getcwdchdir get_vdatar@rflattenrnpsave) rrTrrrrZrrr>err_codenp_fnamerrr_vd2arr_help_boostpythongs,    rrc sddl}ddl}ddl}ddl} ||}|durg}d|vr%|ddg7}d|vr.|dg7}ti} ti} g} zt|turStj |}tj |}t t |} n t dd |D} t| dkrhtd |t| D]\}}|jd d d }| |||||fqld}d}zztjd}|du}|std|dkrtdddlm}|rtt| nd}||}|t| }Wdn1swYtt|D](}t||tkrt||d}t|||<Wdn1swYqdd |D}WnJtyJ}z=t| dkr0|r0| j }|t!| }Wdn 1s*wYn tfdd| }dd |D}WYd}~nd}~wwt"|}| D]t\}}}}}|d}tj #|rt|dD]R}t$%d|}|rt|&dkrt|'dd| |'d<t$%d|}|rt|&dkr|rt|'d| |'d<qht|'d| |'d<qht| dkrnqQW| D] \}}}}}|(|qn| D] \}}}}}|(|qw|r|| fS|| | fS)a Run viewdat with --mat option. filename=T0x file, or list of files, or glob filename pattern rec='-d27' or '-d29' or '-d35:2' (default -d35:2). Can also pass args here (e.g. '-d27 -s10000 -p1') extra flags: opt=['--return_rec27_fll_meas','--whatever'] (default []) Returns (d,key): d = raw data key = structure with values from any key info generated by '-h' rN-d27--translate_rec35_sub9_to_rec27 --translate_rec35_sub19_to_rec27z-d29z--translate_rec35_sub2_to_rec29cSrrrrrrrrrzvd2arr..z)Failed to find any input files of format z.tmp.)prefixdirrzSkip using BoostPythonViewdat.Fz@Parallel = False, switch back to use default viewdat executable.)Poolr,r'cSrrrrrrrrrcs t|Sra)r)rxr}rrrs zvd2arr..cSrrrrrrrrrz /mat_key.mr2z\s+key.([^ ]+)\s+=\s+(\d+)rz\s+flag.([^ ]+)\s+=\s+(\d+)))tempfileshutilrqrrHrrrr=r>r?rrr rIrrmkdtemprC importlibutil find_specrrrrrrrrloadrrrrErrrgroupsrJrmtree)r%rrr combine_flagsrSrrrqrrflagsrrrZrTrrrBoostPythonViewdat_specfoundrn_cpurdierUkeyfiler[r!rr}rvd2arrs                  rcCsddl}ddl}|j|||jd}g} |j}|dkr n|dur2||dkr,q||d}| dd|Dqt ||d S) a Run command "cmd" and return array with data. If 'prefix_str' is set, then strip from text before converting to an array. For example: cmd='viewdat -d29 -mb filename.T04' vd2arr is faster, but this doesn't need a temporary file and works for more types rNrkTrcSg|]}t|qSrr.rrrrrrzcmd2arr..dtype) rqrrrtrHrurkreadlinerrbrCrR)r} prefix_strrrqrzpiperr[rrrcmd2arrs    rcCs~ddl}ddl}|j|||jd}g} |j}|dkr#t |S|dkr(q|dkr-q|dkr2q|t| d q) z Run command "cmd" and return array with raw lines as UTF-8 encoding. For example: cmd='viewdat -d99 -mb filename.T04' rNrTr s s utf-8) rqrrrtrHrurkrrCrrstripdecoderR)r}rqrzrrr[rrr cmd2arr_raws   rc@s6eZdZdZddZddZddZGdd d Zd S) BinStructaSimplify naming struct.unpack/pack data. Example for a binary file with a byte and one array of 2 U16s: x = BinStruct('flag: viewdat -d16  => r,)rrH)r%rrrrr get_kv_infosrFc Csddl}ddl}|j|d||jd}g}td|d} |j}|dkr,t |S|durM||dkr8q| d d d }|rMd d |D}| |q)z Convert key-value data to an array. Options: key - if set, only return data with this key string convert_float - if set, convert data to float instead of returning strings rNrrrrTrrr, cSrrrrrrrrrzkv_info2arr..) rqrrrtrHrurrkrrrrCrR) r%r convert_floatrqrzrrrr[rrr kv_info2arrs"  rcCs~ddl}dddd|g}|j||jd}g}tdD]#}|j}|d kr+td dStd |}|r "llh" lat/lon is radians, else in degrees is_ref_rad = True -> "ref_llh" lat/lon is radians, else in degrees r,Nrrr) rIrreshapeonescopyrrrrrrr)llhris_radrscale1scale2rrrrrdEdNdUrrrllh2enus(   ""  r%cCs0t||||\}}}t|d|d|dS)aG Convert lat/lon/height to 3D distance. llh = array of lat/lon/height [lat/lon in degrees by default] ref_llh = point or array of lat/lon/height [lat/lon in degrees by default] is_rad = True -> "llh" lat/lon is radians, else in degrees is_ref_rad = True -> "ref_llh" lat/lon is radians, else in degrees r)r%r)rrrrr"r#r$rrr comp_3d_dist'sr&csddlm}dd|vr|ddgd|vr|d|dddd |Dr.trLt}t|d d dkd}|t|fd d gfd d|d|dfD}|fdd|dd D7}|S)a intersect( a, b, c, ..., make_unique=False ) Find values that appear in both a and b, c, d, ... a = array b = array etc. [optional] ret[0] = common values in a,b,c, ... Will be sorted! ret[1] = index into a[] (not sorted) ret[2] = index into b[] (not sorted) etc. [optional] Note that any repeated input values will be in the output too unless you set make_unique=True. If any of c,d,etc. are None, then it won't be used for comparison and ret[3],ret[4],etc. will be []. r)reduceF make_uniquemake_quick_uniquecSs t||dSNT) intersect1d)r[r2rrrrKrzintersect..css|] }|dur|VqdSrar)rr=rrr Kszintersect..Ncs|durgSr$t|t}t|td}d|t|ddd<d||<r@D]}t|dd|kd}d||dd<q(t| d}t t |krUt d|S)NrT) return_indexr,rrz;intersect length mismatch - perhaps there is repeated data?) rRastypeobject zeros_likeboolrKrr in1dnonzerorIr)argr!rr common_arg)commonduplicted_valuesr)r(rr get_arg_idxTs  zintersect..get_arg_idxcg|]}|qSrrrr4r8rrrfrzintersect..r,cr9rrr:r;rrrhrr) functoolsr'rKrediff1dr delete)argskwargsr'rstrretr)r6r7r8r)r(rrP2s(   $rP皙?c Cs|dkr|t|krtt|tg|t|f}nt|}tt|dtt|}|rcddlm}|||d}tt t|d}|dd|} || } t | } | dkr]| t | } ||| | fS||fS)a$Compute CDF (and PDF?) for 'x'. if do_pdf is False: Returns (cx, cy) cx = is just 'x' sorted cy = value from 0 to 1.0 - shows the % of data below corresponding cx if do_pdf is True: Returns (cx, cy, px, py ) cx/cy as above px = X values for PDF (correspond to input 'x' values) py = Y values for PDF (probability) (Modify 'pdf_sm' to get more or less smoothing. Higher pdf_sm=more smoothing.) plot( cx, cy ) to show CDF plot. plot( cx, cy, px, py ) to show CDF and PDF plot. rr,) gaussian_kde) bw_method@@N?) rIsortrEInfaranger. scipy.statsrDrceilmax) rdo_pdfpdf_smpadcxcyrDfit decimate_npxpymax_pyrrrdocdfks     rXc Cs|td|td}}tjtdtjt|t|}||t|}|t|}|t|}|tj|t|} ||| fS)zy lat_deg - latitude in deg lon_deg - longitude in deg alt_m - height in m Returns (x,y,z) - ECEF [m] gf@rG)pirrrrrrr) lat_deglon_degalt_mlatlonRnrrrrrrrrs$   rcCsRd}tjtj}dtj}tj}tjtj}d}d} d} d} d} |dkr'd} nd} t||||}|dkrO|dkr@|d}n| d}d} t|tj} nd|}|t|}||}||}d|}d|}| |}|dkr}||} | | |} n2|dkr||} n)|||}||||||||}|dkr||} n ||} | | |} | d 7} | | }|| }|||||| d|d |||}| |7} | d krt|d ksnq| | }d|}d|}t|d|| | }t||} d||| t||||t||||} |dt | dt | fS)zK x, y, z = ECEF [m] Returns (lat [deg], lon [deg], height [m]) rg@rr0rG{Gz?@Tr,g@gHz>r) rrrrrabsrfabsarctan2rY)rrrrcfoure2e_primeae_primer]r^hgtcountrsignOfZpp_invz_primez_prime_plus_cz_prime_minus_cuvt_mt_m3fmt_m2ptdelta_t one_plus_t2 one_minus_t2rrr conv_ecef_llasp            0  "r}c Csg}|||||||||dt|dd|dd|dd}|d|}|d|} |d|} t|||} | dtjd} | dtjd} | d}t| }t| }t| }t| }|}|}| }|}| |}||}||}| |}||| || |}t|}|||| }|||| || }t||}|dkr|dtj7}||fS)NrGrrr,rr`rb) rCmathrr}rYrrasinatan2) xRXyRXzRXxSVySVzSVdposinv_rdcosxdcosydcoszllar]r^rksinlatcoslatsinloncoslonutzceet1et2nt1nt2utxutysin_eaelev east_dcos north_dcosazirrrcompute_elev_azis@.            rcCs|d|d?d@}|d|d?d@}|d|d?d@}|d|d?d@}d||Add|dd||Add|S)Nrr,rr?r)u16rISIMQSQMrrr _decode_2bsm.s 4rc Cstddttt|dkt|dtttt|dkt|ftddttt|dkt|dtttt|dkt|fdS)NzIS %%%.1f IM %%%.1frrrzQS %%%.1f QM %%%.1f)rrIrrealreimag)cvalrrr _print_stats6s """" rcCsdd|DS)z@ Convert a Maxwell 7/8 U16 logged sample to 4 I/Q pairs cSs&g|]}tddD]}t||q qS)rr)rr)rrr=rrrr@s&z decode_2bu16..r)raw16rrr decode_2bu16<srcCs"ddl}|d|d||S)Nrz<%dHr)rrrA)rTu8lenrrrr _unpack_u16sBsrcCspt|d}|dkr|dd@}||n|dkr'| dd@ }||dt||}t|}|r6t||S)zB Read a raw 2-bit Ettus RF file (or raw Maxwell 6/7 data) r'rr,r)rseekrrr)r%roffsetrSrTrrrrr read_raw2bHs      rcCsjddl}t|d}|d|dd}|d|dd}|d|d d}|d|dd}|d|d d} |d |d d} |||d @} |d@} |d@} |d @rftd |t|ddkrstdtd| | rtd| rtd| rtdt||}| s| rt |ddd}t |d dd}||fSt |ddd}|S)z Read a p16 file rNr'IrHrBr,riz&Unknown bands : 0x%x - incorrect read?1z)Probably will not handle > 2 bands well..zSamp Hz %.1f. Bands:z L1z L2z G1) rrrrArrbinrlrr)r%rrrrThdr_lenhdr_src hdr_encoding hdr_bandshdr_pad hdr_samp_Hzhas_L1has_L2has_G1rL1valL2valrrrread_p16Ys6        rcCs|dd|?d@}|dd|?d@}|dd|?d@}|dd|?d@}d|d||Addd|d||AdS)Nrr,rrrrr)raw32rrrrrrrr _decode_u32zs 4rcsddl}t|d}d}|d|dd}|d|dd}|d|d d}|d|d d} |d |d d} td | d |d|d d} |d|d d} |rf|d 7}| rl|d 7}d\} }||kr|d|d d}|d|d d}|d 7}|dkrd } n |d krd }ntd|||ksvd|d }|||@}|||d|d}|d|||td||| | |fd||d M}g}t|D]fddtd|D}||q|S)z Read a p32 file u8len = # of bytes in file to read offset = # of bytes to skip at startup. Rounded to multiple of 16. rNr'rrrrrr,zr)rrrzUnknown signal type %d<%dIz%%d signals: L1 %d, L2 %d, G1 %d B1 %dc sJg|]!}tddD]}t|d|dd|q qS)r r)rr)rr=rrZrryrrrsJzread_p32..) rrrrAr@tellrrrC)r%rrrrTn_sigrrhdr_L1hdr_L2samp_HzL1_HzL2_Hzhdr_G1hdr_B1hdr_XX_Hzmasku32lenoutrrrrread_p32sN       rcCsDgd}|dd|?d@}|dd|?d@}||d||S)N)r,rrrrrr)rrZlookupInQnrrr_decode_2bit_gss6450srcCs|dd|?d@}|dkr|ddd}n|dd}|dd|?d@}|dkr4|ddd}n|dd}|d |S) Nrrrcrrr,rrrrZrrrrr_decode_4bit_gss6450   rcCs|dd|?d@}|dkr|ddd}n|dd}|dd|?d@}|dkr4|ddd}n|dd}|d|S) Nrrrr,rrrrrr_decode_8bit_gss6450rrr`c%Csddl}ddlm}m}t|d}d}d} d} g} tdD]} |d} | dr-nv|r3t| | d ra| d d  d }| |d }||j |j |j }|||dd8}||} td| }|rt|d}t|d} t|d}|dr|dkr| t|dq|dkr| t|dq| dks|dkrtd|}|dd @}||d|d|dd}|dkr|d|dd}|dkrtddS|d|dd}|rtd||f||krd}nd}|r td|||dkrF|d|dd}|dkr0|d|dd}|dkr=|rs rrz%H:%M:%S %d/%m/%yrdayss[ +([0-9]+), .*?, Bandwidth ([0-9]+) MHz, Freq ([.0-9]+) MHz, Bits ([0-9]+)rrr,z.a.gnsrzUnknown freq/bitsPrizError: unknown syncz start: %x %xz# of signals in file: %dizFound end of syncz end: %x %x g(\u$@rg @izFile offset {}z# of bytes to read {}rrzError: unknown # of bitsrInfo)start_t f_samp_MHzn_bits f_mid_MHz)$rrrrrrrrsr@rstrptimeyearmonthday isoweekday total_secondsrrrrJrrrCr. RuntimeErrorrrrrAformatrrrrcomplexr )%r%n_secs offset_secsrSrrrrTr bandwidth_mhz week_secs f_mid_mhzrUr0date_str utc_start week_startr! signal_numsync_possync1sync2n_sigs f_samp_mhz bytes_per_secrrrr decode_funcn_in_32bsigsr=rrr samp_inforrr read_gss6450s                         "* "rc Cstt||}|dkrt||}t|}d}|rt|}d}td|D]}|ttt||||d||7}|d7}q$||S)z compute averaged FFT d = raw input data flen = # of points for each FFT max_avg = maximum # of averages to perform do_window = set to True if you want to apply a Hamming window (e.g., in case a jammer is present) rrGr,) rrIr3rwhammingrfftshiftrdfft) rflenmax_avg do_windowi_maxdfftwindown_sumsr=rrr do_1d_avg_fftWs  , r!cCs8d||||||}|||}|t|8}|S)Nrb)mean)rFreqLxFreqLyPhaseLxPhaseLyetaatmrrr _calc_atmms  r)c Cs|}ttt||dk}d}|D]}|||dt|||d8<|d}q||dt||d8<|S)Nr1rr,)rrrdrr")rrrnew_vali_jmpr0r=rrrremove_seg_meansss(  r,c Cstj|} tj|} | || |}}t|||||} ||| } tt|}t||| } t|dkrB||| }t|||}ng}t||| } | | |fS)a Compute iono-free stationary pseudorange (MPx) FreqLx = Lx frequency [Hz] PseudoLx = Lx pseudorange [m] PhaseLx = Lx carrier phase [cyc] SlipLx = Lx slip count FreqLy, PseudoLy, PhaseLy, SlipLy = same for Ly If you let PseudoLy == [] then MPLy will be empty too. Returns: (MPLx, atmLx, MPLy) Note: atmLx is twice the iono because it is a correction to "PR - phase" r)rrr)rrr,rI)rr#PseudoLxr%SlipLxr$PseudoLyr&SlipLylp_known WavelengthLx WavelengthLyatmLxMPLxrMPLyrrr iono_free_SR}s        r7c Cst|dd|jf|k|dd|jf|k@|dd|jf|k@|dd|jf|k@|dd|jf|k@}t|dkrEtgtdS|S)a Similar to get_L1L2_idx(), but for any signal type Inputs: d = rec27/35:19 data k = rec27/35:19 key (from vd2arr) sv_id = satellite ID sat_type = satellite type from T0x file Lx_freq = "x"/master frequency (e.g., dRec27L1Band) Lx_trk = "x"/master track type (e.g., dRec27Track_CA) elev_mask_deg = elevation mask [deg] min_seg = minimum # of points in each non-slip segment Returns: i_Lx Nrr) rSVSAT_TYPEELFREQTRACKrIrRr) rrr+r,Lx_freqLx_trk elev_mask_degmin_segi_Lxrrr get_Lx_idxs   rBc Csnt|dd|jf|k|dd|jf|k@|dd|jf|k@|dd|jf|k@|dd|jf|k@} |dkrt|dd|jf|k|dd|jf|k@|dd|jf|k@|dd|jf|k@} t| dkrt|| |jf} t|dd|jf|k|dd|jf|k@|dd|jf|k@|dd|jf|k@|dd|jf| k@} n>tg} n9t|dd|jf|k|dd|jf|k@|dd|jf|k@|dd|jf|k@|dd|jf|k@} t| dkst| dkr tgt dtgt dfSt || |j f|| |j f\} }}| |} | |} dd}|||| | | \} } | | fS)a Similar to get_L1L2_idx(), but for any signal type Inputs: d = rec27/35:19 data k = rec27/35:19 key (from vd2arr) sv_id = satellite ID sat_type = satellite type from T0x file Lx_freq = "x"/master frequency (e.g., dRec27L1Band) Lx_trk = "x"/master track type (e.g., dRec27Track_CA) Ly_freq = "y"/slave frequency (e.g., dRec27L1Band) Ly_trk = "y"/slave track type (e.g., dRec27Track_CA) elev_mask_deg = elevation mask [deg] min_seg = minimum # of points in each non-slip segment Returns: i_Lx, i_Ly -> for input into get_MPx() Nrrc Sstt|||jfdkt|||jfdk@d}|dkrgtdgtt|dkdt|gf}tj|dgt|d}tt|dD]}||||d} } | | |kr_d|j| | <qE||jj }||||}}||fS)zRemove any data with a slip on either frequency. If min_seg > 0, then make sure data segments are at least 'min_seg' points long. rr,F)rT) rrSLIP_CNTrErImarRrrr+) rriLxiLyr@i_noslipi_jump i_noslip_mar=startendrrr remove_slipss4& z"get_LxLy_idx..remove_slips) rr8r9r:r;r<rIrMrRrrPr)rrr+r,r=r>Ly_freqLy_trkr?r@rAi_LytrackrUixiyrLrrr get_LxLy_idxs\  $rSc@s|eZdZdZejejdfejej dfej ej dfej ej dfejejdfejejdfejejdfejejd fiZd d Zd S) get_sat_typez Return the SAT_TYPE_ for the supplied RT_SatType Also returns a system name string get_sat_type(RT_SatType_GPS).SAT_TYPE get_sat_type(RT_SatType_GALILEO).sysstr GPSSBASGALILEOQZSSBEIDOUGLONASSIRNSSXONAcCs$|j|d|_|j|d|_dSr) sat_type_dictr9sysstr)r RT_SatTyperrrr szget_sat_type.__init__N)r^r_r`rar&r' RcvrConst SAT_TYPE_GPSRT_SatType_SBAS SAT_TYPE_SBASRT_SatType_GALILEOSAT_TYPE_GALILEORT_SatType_QZSS SAT_TYPE_QZSSr)SAT_TYPE_BEIDOUr(SAT_TYPE_GLONASSRT_SatType_IRNSSSAT_TYPE_IRNSSRT_SatType_XONA SAT_TYPE_XONAr]rrrrrrTs         rTc@sL eZdZedgdZedgdZieejejej edde j deejej ej edde jd eejej ejed d e jd eejej ejed d e jd eejej ejed de jd eejejejedde jdeejejejedde jdeejejejedde jdeejejejedde jdeejejejedde jdeejejejedde jdeejejejedde jdeejejejedde jdeejejejedde jdeejejejedde j deej!ejej edde j deej!ejejedde jd ieej"ejejed de j#deej"ejejed de j#deej"ejejed de j#deej"ejejed de j#deej"ejejed de j#deej"ejejed de j#deej"ejej$ed!d"e j%d eej"ejej&ed!d#e j%d eej"ejej'ed!d$e j%d eej"ej(ej$ed%d"e j)d eej"ej(ej&ed%d#e j)d eej"ej(ej'ed%d$e j)d eej"ej*ej+ed&d"e j,deej"ej*ej-ed&d#e j,deej"ej*ej.ed&d$e j,deej"ej*ej/ed&d'e j,deej"ej0ej1ed(d"e j2dieej"ej0ej3ed(d#e j2deej"ej0ej4ed(d$e j2deej5ejej ed)de j deej5ejej6ed*de j7deej5ejejed+de jd eej5ejejed+de jd eej5ejejed+de jd eej5ejejed+de jd eej5ejejed+de jd eej5ejejed+de jd eej5ejej8ed,de j9d eej5ej ejed-d e jdeej5ej ejed-d e jdeej5ej ejed-de jdeej5ejejed.de jdeej5ejejed.de jdeej5ejejed.de jdieej5ej0ej:ed/de j;deejed0de j?deejde jUdeejTejVej ed?de jWd eejXejejYed@de jZd eejXejej[edAde j\di Z] dBdCZ^dDS)E get_sub_typeRTSat)SatTypebandrPSatInfo)rIQsubtypeorderzGPS L1CArrzGPS L2Er,zGPS L2CCMCLrCMCLzGPS L5rsrrQzGPS L1CzDP BOC11rzD BOC11zP BOC11zDP MBOCzD MBOCzP MBOCzGPS L1EzSBAS L1zSBAS L5zGAL E1zGAL E5ADPDPzGAL E5Bz GAL E5AltFullzGAL E6z QZSS L1CAz QZSS L1CBzQZSS L1Cz QZSS L1SAIFzQZSS L2CzQZSS L5zQZSS LEXzBDS B1zBDS B1CzBDS B2zBDS B2AzBDS B2Bz BDS B2AcezBDS B3zGLN G1CzGLN G1PzGLN G2CzGLN G2PzGLN G3PDzIRN L5zIRN S1zXON X1zXON X5cCs|||f|jvrR|j|||fd|_|j|||fd|_|j|||fd|_|j|||fd|_|j|||fd|_t|jrP|jd|j7_dSdSd|_d|_d|_d |_d |||f|_dS) Nrrr,r-rz ??? signalz ??? trackcz??? (%d %d %d)) sub_type_dictSUBTYPEsigstrtrkstrrJfullstrrI)rr_ dRec27Band dRec27Trackrrrr}s zget_sub_type.__init__N)_r^r_r`r rorrr&r' dRec27L1BanddRec27Track_CAr` SUBTYPE_L1CA dRec27L2Band dRec27Track_E SUBTYPE_L2EdRec27Track_CMCL SUBTYPE_L2CdRec27Track_CMdRec27Track_CLdRec27L5E5ABanddRec27Track_IQ SUBTYPE_L5 dRec27Track_I dRec27Track_QdRec27Track_BOC_1_1_DP SUBTYPE_L1CdRec27Track_BOC_1_1_DdRec27Track_BOC_1_1_PdRec27Track_BOC_1_1_DP_MBOCdRec27Track_BOC_1_1_D_MBOCdRec27Track_BOC_1_1_P_MBOCdRec27Track_L1E SUBTYPE_L1Erbrd SUBTYPE_E1dRec27Track_BPSK10_PD SUBTYPE_E5AdRec27Track_BPSK10_DdRec27Track_BPSK10_P dRec27E5BBand SUBTYPE_E5BdRec27E5ABCentreBanddRec27Track_AltBOCCompPDSUBTYPE_E5AltBOCdRec27Track_AltBOCCompDdRec27Track_AltBOCCompPdRec27Track_AltBOCNonComp dRec27E6BanddRec27Track_E6_PD SUBTYPE_E6dRec27Track_E6_DdRec27Track_E6_PrfdRec27Track_L1CB SUBTYPE_L1CBdRec27Track_SAIFSUBTYPE_L1SAIFdRec27Track_LEX SUBTYPE_LEXr) dRec27B1BanddRec27Track_B1 SUBTYPE_B1 SUBTYPE_B1CdRec27Track_B2 SUBTYPE_B2 SUBTYPE_B2A SUBTYPE_B2BSUBTYPE_B2AceBOC dRec27B3BanddRec27Track_B3 SUBTYPE_B3r( SUBTYPE_G1C dRec27Track_P SUBTYPE_G1P SUBTYPE_G2C SUBTYPE_G2P dRec27G3BanddRec27Track_G3_PD SUBTYPE_G3dRec27Track_G3_DdRec27Track_G3_Prj SUBTYPE_L5CA dRec27S1Band SUBTYPE_S1CArldRec27Track_X1_PD SUBTYPE_X1dRec27Track_X5_PD SUBTYPE_X5rrrrrrrns8      !"#$%&()*+,-./012345679:;<=>?@ABCDEFGHIZ rncCsiddddddddddddd dd d d d d ddddddd dd dd dddddddddddddddd ddd}||dS)Nrrrrr,rcrrzrr rrr r rr)rrr!rn)rtswitchrrrget_subtype_to_subbandsf      !rcCsddddddd}||dS) NLG1LG2LE5z E6z B1z S )rr,rrzrrzInvalid rt_band!!r)rt_bandrrrrrt_band_to_labels rc Cs(ddddddddd d d d }||d S)NzGPS C/AzL1 & E1z Glonass G1z Beidou B1zGPS L2z Glonass G2zL5 & E5AzG3 & B2z Galileo E6z Beidou B3zS1 C/A) rr,rrrrzrrrrrzInvalid rt_subband!!r) rt_subbandrrrrrt_subband_to_labels rcCsiddddddddd d d d d ddddddddddddddddddd d!d"id#d$d%d&d'd(d)d*d+d,d-d.d/d0d1d2d3d4d5d6d7d8d9d:d;d<d=d>d?d@dAdBdCdDdEdFdG}||dS)HNrunknownrzL1-C/A rz L1C rzz L1E rz L2E rz L2C rzL2-EorCrz L5 rz G1C rz G1P rz G2C rz G2P rz G3 rcz E1 rz E5A rz E5B rzAltBOC rz E6 rzE6 2nd rz B1 rz B2 rz B3 rz B1C rz B2A rz B2B rzAceBOC rz L1CB rzL1SLAS rz LEX rzLEX-L6ErzL5-C/A rzS1-C/A "z X1 #z X5 zL1-SBOCz X5D )$%r) rt_subtyperrrrrt_subtype_to_labels      !"# 'rc Cszt|dd|jf|k|dd|jf|k@}t||ddf|}g}||D]\}}|||t|||jfq)|S)ab Helper function for get_LxLy_idx() Inputs: d = rec27/35:19 data k = rec27/35:19 key (from vd2arr) sv = satellite ID rt_sat_type = satellite type from T0x file Returns: list for all satellite signals: [ (Lx_freq, Lx_trk, label), ... ] (e.g., [(dRec27L1Band, dRec27Track_CA, 'GPS L1'), ...]) N)rr8r9 get_signalsrCrnr) rrrF rt_sat_typer=signalsrxfreqrPrrr sv_to_Lx_infos 0 rc Cst|dd|jf|k|dd|jf|k@}t||ddf|}g}||D]6\}}||D]\} } t|| fttjtjfkrDq1| |krJnq1|| krPq)|||| | t |||j fq)|S)a Helper function for get_LxLy_idx() Inputs: d = rec27/35:19 data k = rec27/35:19 key (from vd2arr) sv = satellite ID rt_sat_type = satellite type from T0x file Returns: list for all satellite signals: [ (Lx_freq, Lx_trk, Ly_freq, Ly_trk, label), ... ] (e.g., [(dRec27L1Band, dRec27Track_CA, dRec27L2Band, dRec27Track_CMCL, 'GPS L1'), ...]) N) rr8r9rrr&rrrCrnr) rrrFrr=rrxrrPfreq2track2rrrsv_to_LxLy_infos0  rc Cs|tjkrt||||tjtjtjd|| S|tjkr+t||||tjtjtjtj|| S|tjkrAt||||tjtjtjtj|| S|tj krVt||||tjtj tj d|| S|tj ks`|tj krt|dd|jf|k|dd|jf|k@}t||ddf||}d\}} t|dkr|D]\} } | tj ks| tjks| tjkr| | }} nqt||||tjtj|| || Std|)a Get index for intersecting GPS L1 and L2E/L2C times (or GLN G1CA and G2CA, or Galileo E1 & E5A, or Beidou B1 & B2) If there is no L2E/L2C data then L2E/L2C is ignored and i_L2E/i_L2C is empty. d = rec27 data k = rec27 key (e.g., from vd2arr) sv_id = satellite ID sat_type = RT_SatType_GPS, or GLONASS, or ... elev_mask_deg = elevation mask [deg] min_seg = minimum # of points in each non-slip segment (otherwise fill in Nan) Returns: (i_L1, i_L2) (i_L2 is for L2C if available, otherwise L2E) rN)rrr,r$)r&r'rSrrrr(rfrrdrrRT_SatType_BEIDOU_ICDPRNsr)rr8r9rrIrrrrr/) rrr+r,r?r@r=rband2r tmp_band2 tmp_track2rrr get_L1L2_idx(s>        0     rcCsLt|dd|jfd|dd|jf}|rdd|DSdd|DS)z d = rec27 data k = rec27 key (e.g., from vd2arr) Return a list of unique satellites in rec27/35:9 [(sv,sat_type), ...] If desc=True, return triplet: [(sv,sat_type,sat_desc),...] NrEcSs4g|]}t|dt|dtt|djfqSrD)rrTr^rrrrr[s4zget_sv_list..cSrGrDrHrrrrr]rI)rKr8r9)rrrsv_clistrrr get_sv_listQs,rc s|dur|j}t|dd|jftd>|dd|jftd>|dd|jftd>}i}|D]4}|d?d@|d?d@}|d@}|rV||t||jf}n||f}|vrf| |q7|g|<q7| D]t |fddd|<qp|S) ak d = rec27 data (from vd2cls or vd2arr) k = None (or rec27 key from vd2arr) desc = False: Return a dictionary of unique signals in rec27/35:9 {sat_type:(freq,track), ...} desc = True: Return a dictionary of unique signals in rec27/35:9 {sat_type:(freq,track,description), ...} where "desription" is something like 'GPS L1CA' Nrrrrcst|d|djSr)rnrJr r,rrr}rczget_signals..)r) rrKr9r.rr;r<rnrrCkeysr) rrrrrrrrP curr_itemrrrr_s*     rc Cst|dd|jf|k|dd|jf|k@|dd|jf|k@|dd|jf|k@} t|dd|jf|k|dd|jf|k@|dd|jf|k@|dd|jf|k@} t|dd|jf|k|dd|jf|k@|dd|jf|k@|dd|jf|k@} t|dd|jf|k|dd|jf|k@|dd|jf|k@|dd|jf|k@} t|| |jf|| |jf|| |jf|| |jf\} }}}}| |} | |} | |} | |} dd}dd}||| ddf|}||| ddf|}||| ddf|}||| ddf|}||||}||| ddf|}||| ddf|}||| ddf|}||| ddf|}||||}| ||fS)a Do a manual zero-baseline double-diff calculation. dr = rover rec27 data kr = rover rec27 key (e.g., from vd2arr) db = base rec27 data kb = base rec27 key (e.g., from vd2arr) ref_sv = reference satellite ID tst_sv = test satellite ID sat_type = satellite type freq = block type (frequency) track = track/signal type Returns: (t, code double diff[m], carrier double diff[cycles]) Note - tries to remove cycle slips from carrier double diff... NcSsT|dd|jf d}tj}|dd|jf|dd|jf|||tjSNr1)CLKBIASr L1_WAVELENGTHRANGEDOPPrrrr wavelengthrrr steer_code6z"do_double_diff..steer_codecSsT|dd|jf d}tj}|dd|jf|dd|jf||tj|Sr )r rr PHASErrrrrr steer_carrrz"do_double_diff..steer_carr)rr8r9r;r<rPr)drkrdbkbref_svtst_svr,rrPibribtirrirtribr1ibt1irr1irt1rr base_ref_code rovr_ref_code base_tst_code rovr_tst_code diff_code base_ref_carr rovr_ref_carr base_tst_carr rovr_tst_carr diff_carrrrrdo_double_diffsP,,,, r-cCsn||jtjkr)||jtjkrtjS||jtjkr&tjtj ||j Stj S||jtj krG||jtjkrDtj tj||j StjS||jtjkr]||jtjkrZtjStjS||jtjkrhtjS||jtjkrstjS||jtjkr~tjS||jtjkrtjS||jtjkrtjS||jtjkrtjS||jtjkrtj S||jtj!krtj"SdSra)#r;r&rr9rlr XONA_L1_FREQr(GLONASS_L1_BASE_FREQGLONASS_L1_FREQ_OFFSETFDMAL1_FREQrGLONASS_L2_BASE_FREQGLONASS_L2_FREQ_OFFSETL2_FREQr XONA_L5_FREQL5_FREQrGALILEO_E5B_FREQUENCYrGALILEO_E5AltBOC_FREQUENCYrGALILEO_E6_FREQUENCYrBEIDOU_B1_FREQUENCYrBEIDOU_B3_FREQUENCY dRec27E1BandBEIDOU_E1_FREQUENCYrGLONASS_L3_FREQUENCYrIRNSS_S1_FREQUENCYrrrrrget_freqs>rBcCsLd|vr|dd|jft|j@|jkS|dd|jftd@dkS)NMEASr)rCr.rdMEAS_LOCK_POINTMEAS1rArrr get_lp_knowns$ rFr0cCs|r |||jf}ng}t|dkst|t|kr%tgtgtgfS|r6|||jf|||jf} n|||jf} |rH| |||jf7} t||dddf|} t||dddf|} | | } | dkr| dkrtd| tt| j tgtgfSt |||j f| | |||j f|||j f| ||||j f|||j ft||ddf|t||ddf|@ \} }}|dkrtt|||j f}td|d|d d \}}t| d krt||| d d } t|d krt|||d d }| ||fS)a\ Compute iono-free stationary pseudorange (MPx) d = rec27/rec35:19 data k = rec27/rec35:19 key (e.g., from vd2arr) i_Lx = best Lx index for satellite - see get_GPS_L1L2_idx or get_LxLy_idx i_Ly = best Ly index for satellite filt_Tc = if > 0, lowpass filter MPx data with this time constant. 15s is OK. do_MPy = if True, return MPy. If False returns []. use_CCFilt = if True use code/carrier filtered PR (need rec 35:19 diagnostic data) Returns: (MPx, atm1, MPy) MPx = Lx code multipath atmx = Lx atmospheric correction MPy = Ly code multipath rNgGz?g)\(?z.get_MPx frequencies are too close - ratio %.3fr`rrrrrrr)r rIrRCCDiffMPHatrBr@rrrr7rrrCrFrrrr)rrrArOr5do_MPy use_CCFiltrm_MPHatrng_Lyrng_Lxfreq_xfreq_y freq_ratioMPxatmxMPyrrrrrrget_MPxs< *   rTcsNtd|fdd}t|}||}||ddd}t||dddS)z Inputs: x = random signal N = # of points to decay over Returns envelope of 'x' based on a forward-backward estimate.. r0csnt|j}t}t|D])\}}t|r|}nt|r|}n||kr.|d|}n|}|||<q |SNr,)rrrrr2)abs_xrenv_outr=rrrr_helper s   z signal_envelope.._helperNr)exprdmaximum)rrrYrVy_fwdy_revrrXrsignal_envelope s  r^cCs$|r ttt|Sttt|S)zQ Return root-mean-square of x If ignore_nan==True, ignore NaN data.. )rnanmeansquarer")r ignore_nanrrrrms2 srbcCs2|dur tdt|}t|||}|t||S)z>Similar to detrend_linear but uses a polynomial of given orderNr)r_rIpolyfitpolyval)rrurmodelrrr detrend_poly= s rgcCsLg}|D]}t|d|k}t|dkr|||dq|dq|S)Nrarr`)rrIrC)rQrRpercentsrrnr=rrrget_cdf_percentsD s  ric stj tj tj tjtjdtdkr+tddddgdddrEt } t d t dt d d t dt rjt } t d t dt } t d t drjt } t d t drt }t d t dt }t d t drt }t d t drt }t d  t dt }t d t drt }t d  t d fd d}|d|dr djdd dr.show_data..r,csrorarprqrrrr, rrrrrr)labelz-xrzAll '%s' len %dzAll '%s' data err (len %d):zCommon '%s' data err (len %d):)2DZ_rz 3D max/rms/std %.1f %.2f %.2fz5 3D 50%%/68%%/90%%/95%%/99%% %.3f %.3f %.3f %.3f %.3fz 2D max/rms/std %.1f %.2f %.2fz5 2D 50%%/68%%/90%%/95%%/99%% %.3f %.3f %.3f %.3f %.3fz" 3D vel max/rms/std %.1f %.2f %.2fz9 3D vel 50%%/68%%/90%%/95%%/99%% %.3f %.3f %.3f %.3f %.3fz" 2D vel max/rms/std %.1f %.2f %.2fz9 2D vel 50%%/68%%/90%%/95%%/99%% %.3f %.3f %.3f %.3f %.3fz fixmode:r)rKz %d=%.1f%%r)rPinsertslicerrVLONVLATVHGTrrdrXr%LATplotNTRKNUSEDrrIrirMrbstdrerKFIXTYPEr)%for_allri_di_ppcommon_irZrrr[dVEdVNdVUv_err_3dv_err_2d v_err_hgtv_cx3v_cy3v_cx2v_cy2v_cxhv_cyhr"r#r$err_3derr_2derr_hgtcx3cy3cx2cy2cxhcyhpercent3percent2rwr=ax2d_cdf ax2d_cdf_vax2d_errax3d_cdf ax3d_cdf_vax3d_erraxTr_1axTr_2 axhgt_cdf axhgt_cdf_v axhgt_errdPP_LATdPP_TIMEdPP_velEdPP_velNdPP_velUdkl_listdo_2ddo_3ddo_hgtdo_trackdo_vel is_staticpp print_allrr show_data s & ,    4         2 z#plt_pospac_truth..show_datarbest)locrz GPS time [s]z 3D error [m]zCommon data CDF probability %z3D velocity error [m/s]z 2D error [m]z2D velocity error [m/s]zHeight error [m]zHeight velocity error [m/s]N) PosPacConstrrrrrrrRrfiguresubplotgrid tight_layout set_titlelegendnumberxlabelylabeltitle)txtrrrrrrrdo_padrf_Trf_3d_errf_3d_cdf f_3d_cdf_vf_2d_errf_2d_cdf f_2d_cdf_v f_hgt_err f_hgt_cdf f_hgt_cdf_vrrrrplt_pospac_truthN s  $ <V                       rrzc Cst||}d}|D]\}}t|dd|jf|k|dd|jf|k@t|dd|jfddddk@}|durGtt|||jf}t|||jf}tt ||k} t | D]P\} } | ddksn| dt |krsd| | <q\t ||| d|jf||| d|jf|dkrd| | <q\t||| d| d|jfd krd| | <q\q\| | dk} t | dkrt d ||f||| |jfq dS) z Look for sudden SNR jumps in data. Must only pass in data from master subchannel. Usage: (d,k) = vd2arr('file.T0x',rec='-d27',opt=['-t']) find_SNR_dips(d,k) NrErrr,rrrg@@z sv %d/%d:) rrr8r9int_rr3rCNOrdrrIr) rrthreshrLrrFr,r=cno_diffijumpriarrr find_SNR_dips' s0  V8&   rr,?r rcKs|durt}|}|jj}|jd||fd|d|}|jj} |jj| d|dkr5d| dgn| ddg} tj | d| d|j |jj } | | } |} |dkrp|| j| j| j| j| jgdS|| j| j| j| j| jgdS) z Put legend on outside of plot. Only tested example: legend_outside() # legend on right See: https://stackoverflow.com/questions/42994338/creating-figure-with-exact-size-and-no-padding-and-legend-outside-the-axes/43001737 Nr,)bbox_to_anchorrbbox_transform)rendererrtrgR@r)gca get_figurer transFigurercanvas get_rendererdraw matplotlib transformsScaledTranslationdpi_scale_transinvertedget_window_extent transformed get_position set_positionx0y0widthheight)axrr direction padpointsr@figotransrrppartrans2tboxbboxrrrlegend_outsideJ s  $ $$roc" Csf|durt|dd|jf}d}d|vr$d}z|jrd}WnYnd}g}t|D]\}} t} |dkr=td} ntd| dd} t|dd|jf| k} t|| |jf}t|| ddf|| }i}t|D] \}\}}|D]}z |||f}d}Wn d}t | ||j }Yt|| |jf|k|| |j f|k@|| |j f|k@}t |dkrqw| |}|r|rt|||jft|jj@dk}nt|||jft|j@dk}n t|||jf}|||jf}t||kd|t||<|d }tt|||jf}t|d }t||kd }t |dkr8t|||jf|t}t||t}n |||jf}|}t|||d d ||d \} |dur]| }||||f<t||||jf||||dd|d| t |7} qwqn| dkrtq,d}!t |dkr|!d|7}!t|!tt t ||tt!dt"|#| | fq,|S)a; Plot tracking & cycle slip info from a T04 file. Example: d,k=vd2arr(filename, rec='-d35:19') plot_tracking(d,k) Inputs: sat_types = list of satellite types to plot, e.g., [0,2] for GPS/GLN title_txt = add extra info on title marker = what marker to use for the cycle slips Returns: [(fig,sat_type),...] NFrCTrrnrl _nolegend_g(\?r1r,z.-) markersizerscolornone)mfcrsrztrack/slip info : )$rKr9kfrrrrr8rrnrr;r<rIrCr.r dMEAS_SLIPSLIP_FLGriscloserdrrrrxrr~ get_colorrryticksrJrrrC)"rr sat_types title_txtmarker combinedFlag is_rec35_19 all_resultsloopr,rrtot_leni_strLsig_list sig_colorssig_nrrPrFrrsr=rWsv_yspacingr expected_dtigapsv_xgapsv_ygaprnrrrr plot_trackingc s      &$   * 1 rc$ CsLddlm}|durt|dd|jf}d|jfd|jfd|jfd|jfd|jfd |j fd |j fd |j fd |j fd |j fd|jfd|jff }|}g}t|D]\} } t|dd|jf| k} t|| ddf|| } t| } | dkrxqPt| dddd| fd\}}| dkr|g}t|| |jf}d}t| D]i\}\}}||}d}t|D]\}\}}t|dd|jf| k|dd|jf|k@|dd|jf|k@|dd|jft|@dk@}|||jf}t|D] \}}||t||<qt|dr t|dni}t|dkrd}|j|||j f||dt|ddd|d|t|7}t|dkrE||t|7<q||7}t|D]\}}t|dd|jf|k|dd|jf| k@|dd|jf|k@|dd|jf|k@}t!t"|||j f}t|t#|dkd} t| dkrt$|||j f| t%}!t$|t&|j'| t%}"n|||j f}!|t&|j'}"|j|!|"dddqNt(| ||j)}#t|dkr|d|#}#|*|#|+t,t||-|t|.d|dkrt/|q|dkr|st0|qP|1|2|| fqPt3||S)aZ Plot RAIM flags for each subchannel/signalfrom a T04 file. Example: d,k=vd2arr(filename, rec='-d35:19 -t') plot_subchan_raim(d,k) Inputs: sat_types = list of satellite types to plot, e.g., [0,2] for GPS/GLN title_txt = add extra info on title show_all = if False(default), hide plots with no RAIM faults. Returns: [(fig,sat_type),...] rCounterNMMWLSKFrVCNAVFFTrSYSEPHNMArDUAL_ANTr,Trg@)rmfigsizer~rrrrrrsr1k.-rr)4 collectionsrrKr9dSV_FLAGS_FAULT_MM_RAIMdSV_FLAGS_FAULT_WLS_RAIMdSV_FLAGS_FAULT_KF_RAIMdSV_FLAGS_FAULT_SBAS_MSGdSV_FLAGS_FAULT_CNAVdSV_FLAGS_FAULT_FFT_CORRdSV_FLAGS_FAULT_RTX_POSdSV_FLAGS_FAULT_SYS_RAIMdSV_FLAGS_FAULT_EPHdSV_FLAGS_FAULT_NMA dSV_FLAGS_FAULT_CNO_DETECT_SPOOFdSV_FLAGS_FAULT_DUAL_ANT_SPOOFrrrrIsubplotsr8r;r< SUBCH_FLAGSr.rrrhasattrrtr~rrdrrrxrrrrnrr set_yticksrJset_yticklabelsrrrrrCr@)$rrrr show_allrraims raims_cntr rr,rr n_signalsraxesrL tot_len_allsig_idxrrPrrrZrsflagr=rsv_posrF plot_argsrrrrrrrrplot_subchan_raim s  2     rGc Csvddlm}|durt|dd|jf}d|jfd|jfd|jfd|jfd|jfd |j fd |j fd |j fd |j fd |j fd|jfd|jff }|}g}t|D]c\} } t} | dkratd} ntd| dd} t|dd|jf| k}t|||jf}t|D]r\}\}}t|dd|jf| k|dd|jft|@dk@}|||jf}t|D] \}}||t||<qt|dkrd}t|||jf||dt|ddd|d| t|7} t|dkr||t|7<q| dkr|stqPt|D]h\}}t|dd|jf|k|dd|jf| k@}tt|||jf}t|t |dkd}t|dkrWt!|||jf|t"}t!|t#|j$|t"}n|||jf}|t#|j$}t||dddqt%| ||d|j&f||d|j'fj(}t|dkr|d|}t)|t*t+t||tt,d| dkrt-|.| | fqPt/||S)a8 Plot RAIM flags from a T04 file. Example: d,k=vd2arr(filename, rec='-d35:19 -t') plot_raim(d,k) Inputs: sat_types = list of satellite types to plot, e.g., [0,2] for GPS/GLN title_txt = add extra info on title show_all = if False(default), hide plots with no RAIM faults. Returns: [(fig,sat_type),...] rrNrrrrVr r!rr"r#r$rr%rnrlrr,rrr(r1r)r*rT)0r+rrKr9r,r-r.r/r0r1r2r3r4r5r6r7rrrrr8SV_FLAGSr.rrrrIr~rrrdrrrxrrrrnr;r<rrrrJrrrCr@)rrrr r=rr>r?r rr,rrrrrLrZrsrDr=rrErFrrrrrrrr plot_raim- s|    : 0  0*  rIc Cst|dd|jf}i}gd|d<gd|d<gd|d<gd|d <gd |d <gd |d <gd|d<gd|d<gd|d<|d|jf}|dd|jfd|dd|jf|}g}t|dkrmtd} nt|dd|jf|dddf\} } } || dd f}t|| |j|jd f|\} } }t | d| d}|df|dffD]\}}t }|D]w}t |}t || |jf|k}dt t|t t| }tt||}|t dt|}t|dkrt|dtt|d}nt|dd|dtt|d}d}z||}WnYt||||d d!||d"qtd#td$|t|d%|td&td'd d(t||q|S))aInputs: d,k = rec 35:2/16 position data & index info truth = an array of secs,lat,lon,height truth points txt = optional string to prepend to all plot titles Generate a height error plot and 2D error plot vs. time. Returns [ fig_height_err, fig_2d_err ] N)r,rrr,r)r,rg333333?r,r,)r,rg333333?r,r)r,r,rr,r)r,rrr,r)rrr,r,r)rr,rr,r)r,rr,r,r)rrrr,r: Height2Drgffffff?rz (points= )z 95% = z{:.3f}z m (points= rrzr)r0 edgecolorrgrszTime [GPS Seconds]z %s Error [m]z %s ErrorTr)r markerscale)rKrWEEKrrIryrPr%r}rrrrr.rrHrdPosTypeStrConstrrscatterrrrrrrrC)rrtruthrunique_fixtypes color_mapping start_weekrall_figsrrUi_trr"r#r$rerr_valerr_namerfixtyper= pos_yielderrTmperr95rsrrrr plot_pos_err sZ         ,  *$ *    r_csd}dd|D}t|dkrddD}|d}|D]}|dq&tD]"}|}t|t|krDq5t||D] \}}|g|qIq5fdd}j d|d S) a From http://matplotlib.org/examples/event_handling/legend_picking.html Given figure, make clicking on legend elements enable/disable lines. Assumes a single legend, so only label lines on a single subplot(). If multiple subplots have the same number of lines as the legend, then clicking will affect all subplots. May want to use "figlegend()" or "legend(bbox_to_anchor=(1.1,1.05))" rcS g|] }t|tjjkr|qSrrrrLegendrrrrr rz+make_legend_interactive..cSr`rrarrrrr rrcsP|j}|D] }| }||q|r|dn|djdS)NrGg?)artist get_visible set_visible set_alpharr)eventleglineoriglinevisrlinedrronpick s     z'make_legend_interactive..onpick pick_eventN) get_axes get_childrenrI get_lines set_pickerrtr setdefaultrCr mpl_connect)rrleg all_leglinesrhlinesrirmrrkrmake_legend_interactive s"     rxc@s6eZdZddZddZddZddZd d d Zd S)VdClscCsDt||}||_||_d|vr|d=t||_|j||S)Nis_data_transposed)rasarrayviewrrTrrupdate)cls input_arrayrrrrrrr__new__ s  z VdCls.__new__cCs:|durdSt|dd|_t|dd|_t|dd|_dS)NrrTr)rrrTr)rrrrrr__array_finalize__ s zVdCls.__array_finalize__cCsH||jvrt|jdkr||j|S|dd|j|fStd|)Nr,z$'VdCls' object has no attribute '%s')rrIrAttributeError)rattrrrrrs s  zVdCls.__getattr__cCs|j||j|dSra)rr}r)rkey_valsrrradd_keys s zVdCls.add_keysFcCst||j|dS)N)r)rr)rrrrrr szVdCls.get_sv_listNr])r^r_r`rrrsrrrrrrry s  rycCs"t||d|d\}}}t|||S)aSame as vd2arr, but output is wrapped together. Needs work, but idea is: d = vd2cls( 'file.T04', '-d35:19' ) print( d.SV ) # instead of "print( d[:,k.SV] )" To access keys, see "d.k" For flags, see "d.f" For keys+flags, see "d.kf" F)rrS)rry)r%rrSrrrDrrrvd2cls s rc Ost|ddkr|d\}}d\}}n|d\}}}}g}g}|D]<}|dur4t|j|k|j|k@} nt|j|k|j|k@|j|k@|j|k@} t|dkrX||j| || q!t|dkryt|} | dd} ddt ||| DS|d|dS) aGrab a satellite from multiple "vd2cls" data sets. Example: md1, md2 = sv_intersect( d1, d2, sv=(14,10) ) # sv=(sv,sat_type) or sv=(sv,sat_type,freq,track) plot( md1.TIME, md1.RANGE ) md1/md2 are just "views" of d1/d2, so they take minimal memoryrFrrNr,cSsg|] \}}}|||qSrr)rrr=rWrrrr5 sz sv_intersect..r) rIrr8r9r<r;rCrrPr) r?r@rFr,rrPtimesidxrr=ridx2rrr sv_intersect s$  ,    rcCsti}d|_d|_d|_d|_d|_d|_d|_d|_d |_ d |_ d |_ d |_ d |_ d|_d|_d|_d|_d|_d|_d|_d|_d|_d|_d|_|S)z2Return indexes for StingerNavPC residuals.txt filerr,rrrrzrrrrrrrrrrcrrrrrrrr)rweekrr8r9rCSTATEpr_availpr_respr_sig clk_bias_typerclk_diff dop_availdop_res clk_driftclk_drift_diffr:usedAZ pos_err_est iono_mode smooth_pr_res cc_filt_cntr1rXrrrsnpc_res_fields: s4rc sddl}ddl}g}|'fddt|D}|D]}|\}}}||||gqWdn1s8wY|j|gddS)zGiven list of T0x files, return DataFrame of: [[start_t, meas_dt,pos_dt],...] See get_ttff() Example: from glob import glob d = get_ttff_all(glob('/mnt/data_drive/TTFF/data/*20190430*.T04')) plot( d.start_t, d.meas_dt ) rNcsg|] }jt|fdqS))r?) apply_asyncget_ttffrrTrrrrd rz get_ttff_all..)rmeas_dtpos_dt)columns)rrJrrrnrCrv) filenamesmpr]rresultsresrrrrrr get_ttff_allX s rc Cstd|d}t|d}td|d}t|d}td|d}t|d}|d rrz - Time tag :rzviewdat -d29,35:2 zWeek :rzt02z viewdat -d27 z TYPE 27: SVzviewdat -d35:19 z TYPE 35:19 SVrr)rrrHr.rr) r%up_secsgps_secspos_secs meas_secsstart_gps_timerrrrrrrk s& rcCsNtd|}z |td|7}WnYz |td|7}W|SY|S)a-Utlility function for parse_load_diags() Calculates the CPU reserve from all of the background tasks Inputs: info - dictionary of the CPU load data extstr - Extension string for each CPU Empty string for CPU0, otherwise 'CPUn' Returns: The CPU reserve zinfo.data.StingerBITzinfo.data.CheetahBackgroundTestzinfo.data.CoreBuildBackground)eval)rxextstrrrrrcalc_cpu_reserve s rc Csddl}ddl}ddl}d|}|dkrd|}|j|||jd}g}g}g}d} |j } | d kr:nA| sD| d rCd} q-| } t | d krQn*t | d } t | ddkre| dkred } || || d|t | dq.|||fS)arParse processor load filename info. Inputs: filename = T04 file (since 5.20) Returns: task_names = name of each task (for quick lookup by 35:258 index) task_cores = core # of each task Example: IDs, names,cores = parse_load_diags_task_names("file.T04") IDs = [0,1,...] names = ['cyg_start','StingerLM',...] cores = [0,0,...] rNzviewdat -d35:259 rz stdbuf -o0 rFTrz Task Names:rr,rrr)rqrrrrrtrHrurkrrrsrrIrrC) r%rqrzrr}rtask_IDs task_names task_coresgot_task_namesr[r\curr_IDrrrparse_load_diags_task_names s:         rc st|\}}}td|d|td}ti}|dddfd|_ti|_|ddddf}t|jddD]Q}||} ||fdd t|D} t t |dd| fdd } d t |dd|f| } | t | d} | |jvrt |j| | dd |j| <q:| |j| <q:t||_t|dkrt|d |_t|d krt|d|_t|dkrt|d|_ti|_t||D] \} |j| <q|S)aParse processor load diagnostic info. Inputs: filename = T04 file (since 5.20) opts = any other viewdat opts (e.g. "-e260000" to end early) Example: d = parse_load_diags("file.T04") plot( d.TIME, d.data.StingerLM ) # plots one line plot( d.TIME, d.data.HTTPDworker ) # plots several lines (d.core.StingerLM, etc. -> core #) (d.RESERVE is an alias for CBT+BIT CPU0) (d.RESERVECPUn is an alias for CBT+BIT CPUn, if present) zviewdat -d35:258 -mb rjrr,Nrr1csg|] \}}|kr|qSrr)r_i_xtcorerrr rz$parse_load_diags..)axisrCPU1rCPU2rCPU3)rrr.rrr+rrrrrrrIrCrRESERVErM RESERVECPU1 RESERVECPU2 RESERVECPU3corer) r%optsIDsrrrrxdtasksr=rcidxdiff_count_sum curr_loadrrrparse_load_diags s6             rcCsddlm}m}ddlm}t|d}|}|ds!td|}|ds.td|td d  }| |d }|j ddddd || d d}d}|| |} | } |t} g} t|D]E\} }| }| ddkrt|d| } |ddkr|dd } qft|D]\}}|drt}nt|}| | || |fqqf| D] }t| || |<q| Wd S1swYd S)a-The UNAVCO "teqc" program can generate raw data if you give it the options "+qc +plot". For example, it may generate some_file.m12 for raw MP12 data. To plot MP12 for GPS SV #10 data you could then do: d = parse_compact3("some_file.m12") plot( d['G10'][:,0], d['G10'][:,1] ) rr) defaultdictr2COMPACT3zNot a COMPACT3 fileGPS_START_TIMEzUnexpected 2nd linezGPS_START_TIME Nz%Y %m %d %H %M %S.%f)hourminutesecond microsecondrrrJrr,z-1S)rrr+rrrrsrrIrrrbrrrdrrHr.rrrCrrR)r%rrrrTrf start_timeweek_roll_time secs_in_weekstart_offset_s curr_offset_sr+curr_svsrr\rrrrrrparse_compact3 sH           $rc CsNd}d}d}d}d}d}d}d} td|} | } | dur no|dkr)| dkr)nf|dkr:| dkr:|dkr:|dkr:nUd| vrR| d} t| t| d}d}nr,,rr)rrrGrHr@rr) r% reportRates serialNumberrxID productNameposRatemeasRategotPosgotMeasgotRXIDr+rftokensrrrgetSerialNumber# sT     rc Csld}d}d}d}td|} |}|dusd|vrnLd|vr2|d} | dd d}n5d |vrD|d} | d}n#d |vrV|d} | d}nd |vrg|d} | d}q|dkrdd ddddddddddd } |} t| d} | | d} t| d} d|| | | f}n|durd||f}nd|||f}|r|d|7}|S) zReturns the firmware version number and date from a T02/T04/DAT file commas are removed from the date in case this is saved in a CSV file. Only part of the data file is processed (up until we get a record 12), so this is pretty quick to execute. rNz viewdat -d12 TzGPS weekz Firmware daterr,rzNavigation processorzRelease targetz Receiver typerrrrzrrrrrrr) JanFebMarAprMayJunJulAugSepOctNovDecrrrz%s %4d-%02d-%02dz%s %sz%s-%s %srj)rrrrHrGrbr)r% numericDate reportProductdateversion subversionrxTyper+rfrmonthLUTFWYearFWMonthFWDayverStrrrrgetFirmwareVersionW sN      rc Cstd|}d}d}d} |}|}|durnN|dkr?t|dkr?|ddkr?|ddkr?t|d }t|d } n+t|d krj|dd krj|d dkrj|ddkrjt|d }t|d}t|d}nq |dkrw|| |||fS|||fS)zReturns the viewdat -d35:2 NTrrWeekrTimerrzrLatrLonrHgtrrrrrrHrIrr.) r% reportTimer+rrrrfrrrrrrgetRefPosition s8              r cCs|td|}g}g} |}|}|durn#t|dkr=|ddkr=|ddkr=t|d }t|d } ||fSq ) z7Returns the time from the first 35:2 position record rTNrrrrrrrzr)r%r+rrrfrrrrgetTime s       r cCsd}d}d}td|td|} |}|dur ||fSd|vr*tdd}n:|dkrEd|vrE|d}td |t|d }n|dkrdd |vrd|d}td |t|d } ||fSq) NFz In getMasksz viewdat -d30 TMASKSz Found Masksz Elevation:rz Found Elevr,PDOPz Found PDOP)r@rrrrHr)r%foundMaskTokenElevMaskPDOPMaskr+rfrrrrgetMasks s0     rcsddlm}m}m} m} j|kdjvrj|kdjv tj dddDjd r>jd d } t t j | d t | d t } t| | kr]| | 8} j d} | d}t\ td d d |d ddtdd\tdd\tgd}tt| }| ||d rtgd}| |dg|gdndtgd}rt\ |ddttj dkrdnd||dt| t| t| d fdd} f d d!}| r)||fd"d#} jd$||j fS)%aPlot FFT rec 35:25 (or rec 35:24) data interactively. antenna_num = 0 or 1 sample_point = 0:default, 1=pre-miti, 2=post-miti spectrogram = show spectrogram? plot_max = plot max FFT data by default? autoscale = autoscale plots? title = plot title Usage: d=vd2cls("file.T04","-d35:25") plot_fft_data( d ) Note: "." and "," keys can be used to step through time. r)SliderButton RadioButtons CheckButtonsSAMP_PT MAX_FREQDATAcSg|]}d|qSz%.1frrrrrrrz!plot_fft_data..rFREQDATArJr?)leftbottom Freq[MHz]zFFT[dB]Tg?r333333?ractive)r`g333333?r r rM)labelsactivesN)rrCg?gQ?z GPS TOW [sec]zFrequency [MHz]g>@rGgN@r)valinitvalstepc s@j}j|k}tt|jj}tddd|j|d|d} | || df rY drY | || dfn  t dtd}d}rt |dd|jj|jjdf}t |dd|jj|jjdf}|d|d tt|dd df|gtt|dd df|g jrt||j\}}j|||dd|jj|jjdfd ||d } d } jD]} | j} | dur| | d } nq| s j| d} |dd|dd jdSdS)Nrr1rrrr,rrainbow)cmapvminvmaxFTr'r) rvalue_selected CENTERFREQargminrdSECrrcBINSIZE set_xdata set_ydata get_statusrrrrelimr3rr FREQDATA_LASTrMset_xlimset_ylimnanminnanmaxr draw_idlemeshgrid pcolormeshr+colorbar update_normal)rU curr_freq_hzd0r=freq_mhzr+r,XYpcm found_cbarrcbcbar) autoscalerax1 center_hz center_labelsr fft_check fft_radio fft_sliderrfig1freq_ifreq_i2has_maxplt_line plt_line2 spectrogramrr update_freqQsP&  &&"   z"plot_fft_data..update_freqcsj}j|k}tt|jj} ||df r<dr< || dfn t dt   dddjdS)Nr'rT)rr-r.r/rdr0rr3r4rrrr5autoscale_viewrr;)rUr@rAr=) rrKrLrrMrNrOrrQrRrSrTrUrr update_timezsz"plot_fft_data..update_timecs@|jdkrjdS|jdkrjdSdS)Nrr)rset_valr)rg)rOr&rron_keys  zplot_fft_data..on_keykey_release_event)!matplotlib.widgetsrrrrANTNUMrrrKr.aroundunwrapr0rYrr8subplots_adjustr set_xlabel set_ylabelrr~rAr/rdrMrr3 on_clicked on_changedrrtr-)r antenna_num sample_pointrVplot_maxrIrrrrrr secs_unwrapr@curr_secraxi_activerax2axtimerWrYr[r)rIrrJrKrLrrMrNrOrrPrQrRrSrTrUrVr&r plot_fft_datasr     &                 ,$)     roc sddlm}j|ktjdddD|r#jdnjdjd}t\tdd d  d  d t gd }t t |}|||d}fdd}||||jt|S)zPlot history of FFT rec 35:25 data interactively. Usage: d = vd2cls("file.T04","-d35:25") plot_history_fft_data( d ) r)rcSrrrrrrrrrz)plot_history_fft_data..rrrgffffff?)rrz Time[secs]Trr!c s|}j|kddf}tddd|jdd|d}t||j\}}dtvr8j |||dddf}t |dd_  d d d j dS) Nrr'r(r1rrG horizontalr orientationT)rr.rcr1r<r0rrGremover=r>r5rXrr;)rsr@rArBrCrDplt_imrrKrLrrrQrrrWs&  "z*plot_history_fft_data..update_freq)r]rr^rKr.rr8rarbrcrrAr/rdrdr-show) rrfdo_maxrr@rkrlrNrWrrurplot_history_fft_datas*            rxcCs|rtjtj|}tj|st|t}t|d|d| dt |}t t dr=| dj dt jd}n | dj dt jjd}|j|dd d S) a<Save current plot as a PNG file. Matplotlib isn't very good at compressing PNG image files. Therefore, use PIL functions to compress a memory version of the file. The compressed images are close to half the size of the Matplotlib generated version. Note: this reduces the image to 256 colors, so in images with gradients or lots of colors you may notice the difference. 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