Other Stuff (Python) |
Table of ContentsOther Stuff (Python) Overview Note About HTML Links References Tutorials Required Readings The Permuted Index SpiceyPy API Documentation Kernels Used SpiceyPy Modules Used NAIF Documentation Required Reading and Users Guides HTML format documentation Library Source Code Documentation API Documentation Text kernels Text kernel format Lesson 1: Kernel Management with the Kernel Subsystem Task Statement Learning Goals Code Solution First, create a meta text kernel: Now the solution source code: Run the code example Lesson 2: The Kernel Pool Task Statement Learning Goals Code Solution Run the code example Related Routines Lesson 3: Coordinate Conversions Task Statement Learning Goals Code Solution Run the code example Related Routines Lesson 4: Advanced Time Manipulation Routines Task Statement Learning Goals Code Solution Run the code example Lesson 5: Error Handling Task Statement Learning Goals Code Solution Run the code example Lesson 6: Windows, and Cells Programming task Learning Goals Code Solution Run the code example Related Routines Lesson 7: Utility and Constants Routines Task Statement Learning Goals Code Solution Run the code example Task Statement Code Solution Run the code example Related Routines Other Stuff (Python)
The extensive scope of the SpiceyPy system's functionality includes features the average user may not expect or appreciate, features NAIF refers to as "Other Stuff." This workbook includes a set of lessons to introduce the beginning to moderate user to such features. The lessons provide a brief description to several related sets of routines, associated reference documents, a programming task designed to teach the use of the routines, and an example solution to the programming problem. Overview
Note About HTML Links
In order for the links to be resolved, if not done already by installing the lessons package under the Toolkit's ``doc/html'' directory, create a subdirectory called ``lessons'' under the ``doc/html'' directory of the ``cspice/'' tree and copy this document to that subdirectory before loading it into a Web browser. References
Of these documents, the ``Tutorials'' contains the highest level descriptions with the least number of details while the ``Required Reading'' documents contain much more detailed specifications. The most complete specifications are provided in the ``API Documentation''. Tutorials
Name Lesson steps/functions it describes ---------------- ----------------------------------------------- concepts Concepts of space geometry and time intro_to_kernels Using kernels, meta-kernels time Time systems, conversions and formats lsk_and_sclk LSK and SCLK derived_quant "high-level" observation geometry computations other_functions Intro to some SPICE "low level" computations exceptions built-in mechanism for trapping/handling errorsThese tutorials are available from the NAIF server at JPL:
https://naif.jpl.nasa.gov/naif/tutorials.html Required Readings
Name Lesson steps/functions that it describes --------------- ----------------------------------------- cells.req The SPICE cell data type error.req The SPICE error handling system kernel.req Loading SPICE kernels time.req Time conversion windows.req The SPICE window data type The Permuted Index
This text document provides a simple mechanism by which users can discover which SpiceyPy functions perform functions of interest, as well as the names of the source files that contain these functions.
SpiceyPy API Documentation
For example, the Python help function
>>> import spiceypy >>> help(spiceypy.str2et)describes of the str2et function's parameters, while the document
cspice/doc/html/cspice/str2et_c.htmldescribes extensively the str2et functionality. Kernels Used
# FILE NAME TYPE DESCRIPTION -- ------------ ---- ------------------------------------------------ 1 naif0008.tls LSK Generic LSK 2 de405s.bsp SPK Planet Ephemeris SPK 3 pck00008.tpc PCK Generic PCKThese SPICE kernels are included in the lesson package. SpiceyPy Modules Used
CHAPTER EXERCISE FUNCTIONS NON-VOID KERNELS ------- --------- --------------- --------------- ---------- 1 kpool spiceypy.furnsh spiceypy.ktotal 1-3 spiceypy.unload spiceypy.kdata spiceypy.kclear 2 kervar spiceypy.furnsh spiceypy.gnpool 1-3 spiceypy.kclear spiceypy.dtpool spiceypy.gdpool spiceypy.gcpool 3 coord spiceypy.furnsh spiceypy.dpr 1-3 spiceypy.kclear spiceypy.str2et spiceypy.bodvrd spiceypy.spkpos spiceypy.recrad spiceypy.reclat spiceypy.recsph spiceypy.recgeo 4 xtic spiceypy.furnsh spiceypy.str2et 1 spiceypy.tsetyr spiceypy.timout spiceypy.kclear spiceypy.tpictr spiceypy.jyear 5 aderr spiceypy.furnsh spiceypy.spkezr 1-3 spiceypy.kclear 6 win spiceypy.furnsh spiceypy.str2et 1-3 spiceypy.wninsd spiceypy.wnvald spiceypy.kclear spiceypy.wnintd spiceypy.card spiceypy.wnfetd spiceypy.et2utc spiceypy.wnsumd 7 units spiceypy.tkvrsn spiceypy.convrt xconst spiceypy.spd spiceypy.dpr spiceypy.rpd spiceypy.clight spiceypy.j2100 spiceypy.j2000 spiceypy.tyear spiceypy.halfpiUse the Python built-in help system on the various functions listed above for the API parameters' description, and refer to the headers of their corresponding CSPICE versions for detailed interface specifications. NAIF Documentation
Required Reading and Users Guides
abcorr.req cells.req ck.req daf.req das.req dla.req dsk.req ek.req ellipses.req error.req frames.req gf.req kernel.req naif_ids.req pck.req planes.req problems.req rotation.req scanning.req sclk.req sets.req spc.req spk.req symbols.req time.req windows.reqNAIF Users Guides (*.ug) describe the proper use of particular SpiceyPy tools:
brief.ug chronos.ug ckbrief.ug commnt.ug convert.ug dskbrief.ug dskexp.ug frmdiff.ug inspekt.ug mkdsk.ug mkspk.ug msopck.ug simple.ug spacit.ug spkdiff.ug spkmerge.ug states.ug subpt.ug tictoc.ug tobin.ug toxfr.ug version.ugThese text documents exist in the 'doc' directory of the main CSPICE Toolkit directory:
../cspice/doc/ HTML format documentation
../cspice/doc/html/index.html Library Source Code Documentation
A header consists of several marked sections:
API Documentation
https://spiceypy.readthedocs.io/en/master/index.htmlEach API documentation page is in large part copied from the ``Abstract'' and ``Brief_I/O'' sections of the corresponding CSPICE function documentation. Each API page includes a link to the API documentation for the CSPICE routine called by the SpiceyPy interface. This SpiceyPy API documentation (the same information as in the website but without hyperlinks) is also available from the Python built-in help system:
>>> help ( spiceypy.str2et ) Help on function str2et in module spiceypy.spiceypy: str2et(*args, **kwargs) Convert a string representing an epoch to a double precision value representing the number of TDB seconds past the J2000 epoch corresponding to the input epoch. ... :param time: A string representing an epoch. :type time: str :return: The equivalent value in seconds past J2000, TDB. :rtype: floatIn order to have offline access to the documentation it is recommended to have the CSPICE Toolkit installed locally. The CSPICE package includes the CSPICE Reference Guide, an index of all CSPICE wrapper APIs with hyperlinks to API specific documentation. Each API documentation page includes cross-links to any other wrapper API mentioned in the document and links to the wrapper source code.
...cspice/doc/html/cspice/index.html Text kernels
The subsystem uses two tags:
\begintextand
\begindatato mark information blocks within the text kernel. The \begintext tag specifies all text following the tag as comment information to be ignored by the subsystem. Things to know:
\begintext ... commentary information on the data assignments ... \begindata ... data assignments ...
Text kernel format
VAR_NAME_DP = 1.234 VAR_NAME_INT = 1234 VAR_NAME_STR = 'FORBIN'Please note the use of a single quote in string assignments. Vector assignments. Vectors must contain the same type data.
VEC_NAME_DP = ( 1.234 , 45.678 , 901234.5 ) VEC_NAME_INT = ( 1234 , 456 , 789 ) VEC_NAME_STR = ( 'FORBIN', 'FALKEN', 'ROBUR' ) also VEC_NAME_DP = ( 1.234, 45.678, 901234.5 ) VEC_NAME_STR = ( 'FORBIN', 'FALKEN', 'ROBUR' )Time assignments.
TIME_VAL = @31-JAN-2003-12:34:56.798 TIME_VEC = ( @01-DEC-2004, @15-MAR-2004 )The at-sign character '@' indicates a time string. The pool subsystem converts the strings to double precision TDB (a numeric value). Please note, the time strings must not contain embedded blanks. WARNING - a TDB string is not the same as a UTC string. The above examples depict direct assignments via the '=' operator. The kernel pool also permits incremental assignments via the '+=' operator. Please refer to the kernels required reading, kernel.req, for additional information. Lesson 1: Kernel Management with the Kernel SubsystemTask Statement
Learning Goals
This lesson requires creation of a SPICE meta kernel. Code SolutionFirst, create a meta text kernel:
KPL/MK \begindata KERNELS_TO_LOAD = ( 'kernels/spk/de405s.bsp', 'kernels/pck/pck00008.tpc', 'kernels/lsk/naif0008.tls' ) \begintext... or a more generic meta kernel using the PATH_VALUES/PATH_SYMBOLS functionality to declare path names as variables:
KPL/MK Define the paths to the kernel directory. Use the PATH_SYMBOLS as aliases to the paths. The names and contents of the kernels referenced by this meta-kernel are as follows: File Name Description --------------- ------------------------------ naif0008.tls Generic LSK. de405s.bsp Planet Ephemeris SPK. pck00008.tpc Generic PCK. \begindata PATH_VALUES = ( 'kernels/lsk', 'kernels/spk', 'kernels/pck' ) PATH_SYMBOLS = ( 'LSK', 'SPK', 'PCK' ) KERNELS_TO_LOAD = ( '$LSK/naif0008.tls', '$SPK/de405s.bsp', '$PCK/pck00008.tpc' ) \begintext Now the solution source code:
from __future__ import print_function # # Import the CSPICE-Python interface. # import spiceypy def kpool(): # # Assign the path name of the meta kernel to META. # META = 'kpool.tm' # # Load the meta kernel then use KTOTAL to interrogate the SPICE # kernel subsystem. # spiceypy.furnsh( META ) count = spiceypy.ktotal( 'ALL' ); print( 'Kernel count after load: {0}\n'.format(count)) # # Loop over the number of files; interrogate the SPICE system # with spiceypy.kdata for the kernel names and the type. # 'found' returns a boolean indicating whether any kernel files # of the specified type were loaded by the kernel subsystem. # This example ignores checking 'found' as kernels are known # to be loaded. # for i in range(0, count): [ file, type, source, handle] = spiceypy.kdata(i, 'ALL'); print( 'File {0}'.format(file) ) print( 'Type {0}'.format(type) ) print( 'Source {0}\n'.format(source) ) # # Unload one kernel then check the count. # spiceypy.unload( 'kernels/spk/de405s.bsp') count = spiceypy.ktotal( 'ALL' ); # # The subsystem should report one less kernel. # print( 'Kernel count after one unload: {0}'.format(count)) # # Now unload the meta kernel. This action unloads all # files listed in the meta kernel. # spiceypy.unload( META ) # # Check the count; spiceypy should return a count of zero. # count = spiceypy.ktotal( 'ALL'); print( 'Kernel count after meta unload: {0}'.format(count)) # # Done. Unload the kernels. # spiceypy.kclear if __name__ == '__main__': kpool() Run the code example
Then the spiceypy.kdata loop returns the name of each loaded kernel, the type of kernel (SPK, CK, TEXT, etc.) and the source of the kernel - the mechanism that loaded the kernel. The source either identifies a meta kernel, or contains an empty string. An empty source string indicates a direct load of the kernel with a spiceypy.furnsh call.
Kernel count after load: 4 File kpool.tm Type META Source File kernels/lsk/naif0008.tls Type TEXT Source kpool.tm File kernels/spk/de405s.bsp Type SPK Source kpool.tm File kernels/pck/pck00008.tpc Type TEXT Source kpool.tm Kernel count after one unload: 3 Kernel count after meta unload: 0 Lesson 2: The Kernel PoolTask Statement
Learning Goals
For the code examples, use this generic text kernel (kervar.tm) containing PCK-type data, kernels to load, and example time strings:
KPL/MK Name the kernels to load. Use path symbols. The names and contents of the kernels referenced by this meta-kernel are as follows: File Name Description --------------- ------------------------------ naif0008.tls Generic LSK. de405s.bsp Planet Ephemeris SPK. pck00008.tpc Generic PCK. \begindata PATH_VALUES = ('kernels/spk', 'kernels/pck', 'kernels/lsk') PATH_SYMBOLS = ('SPK' , 'PCK' , 'LSK' ) KERNELS_TO_LOAD = ( '$SPK/de405s.bsp', '$PCK/pck00008.tpc', '$LSK/naif0008.tls') \begintext Ring model data. \begindata BODY699_RING1_NAME = 'A Ring' BODY699_RING1 = (122170.0 136780.0 0.1 0.1 0.5) BODY699_RING1_1_NAME = 'Encke Gap' BODY699_RING1_1 = (133405.0 133730.0 0.0 0.0 0.0) BODY699_RING2_NAME = 'Cassini Division' BODY699_RING2 = (117580.0 122170.0 0.0 0.0 0.0) \begintext The kernel pool recognizes values preceded by '@' as time values. When read, the kernel subsystem converts these representations into double precision ephemeris time. Caution: The kernel subsystem interprets the time strings identified by '@' as TDB. The same string passed as input to @STR2ET is processed as UTC. The three expressions stored in the EXAMPLE_TIMES array represent the same epoch. \begindata EXAMPLE_TIMES = ( @APRIL-1-2004-12:34:56.789, @4/1/2004-12:34:56.789, @JD2453097.0242684 ) \begintextThe main references for pool routines are found in the help command, the CSPICE source files or the API documentation for the particular routines. Code Solution
from __future__ import print_function # # Import the CSPICE-Python interface. # import spiceypy from spiceypy.utils.support_types import SpiceyError def kervar(): # # Define the max number of kernel variables # of concern for this examples. # N_ITEMS = 20 # # Load the example kernel containing the kernel variables. # The kernels defined in KERNELS_TO_LOAD load into the # kernel pool with this call. # spiceypy.furnsh( 'kervar.tm' ) # # Initialize the start value. This value indicates # index of the first element to return if a kernel # variable is an array. START = 0 indicates return everything. # START = 1 indicates return everything but the first element. # START = 0 # # Set the template for the variable names to find. Let's # look for all variables containing the string RING. # Define this with the wildcard template '*RING*'. Note: # the template '*RING' would match any variable name # ending with the RING string. # tmplate = '*RING*' # # We're ready to interrogate the kernel pool for the # variables matching the template. spiceypy.gnpool tells us: # # 1. Does the kernel pool contain any variables that # match the template (value of found). # 2. If so, how many variables? # 3. The variable names. (cvals, an array of strings) # try: cvals = spiceypy.gnpool( tmplate, START, N_ITEMS ) print( 'Number variables matching template: {0}'.\ format( len(cvals)) ) except SpiceyError: print( 'No kernel variables matched template.' ) return # # Okay, now we know something about the kernel pool # variables of interest to us. Let's find out more... # for cval in cvals: # # Use spiceypy.dtpool to return the dimension and type, # C (character) or N (numeric), of each pool # variable name in the cvals array. We know the # kernel data exists. # [dim, type] = spiceypy.dtpool( cval ) print( '\n' + cval ) print( ' Number items: {0} Of type: {1}\n'.\ format(dim, type) ) # # Test character equality, 'N' or 'C'. # if type == 'N': # # If 'type' equals 'N', we found a numeric array. # In this case any numeric array will be an array # of double precision numbers ('doubles'). # spiceypy.gdpool retrieves doubles from the # kernel pool. # dvars = spiceypy.gdpool( cval, START, N_ITEMS ) for dvar in dvars: print(' Numeric value: {0:20.6f}'.format(dvar)) elif type == 'C': # # If 'type' equals 'C', we found a string array. # spiceypy.gcpool retrieves string values from the # kernel pool. # cvars = spiceypy.gcpool( cval, START, N_ITEMS ) for cvar in cvars: print(' String value: {0}\n'.format(cvar)) else: # # This block should never execute. # print('Unknown type. Code error.') # # Now look at the time variable EXAMPLE_TIMES. Extract this # value as an array of doubles. # dvars = spiceypy.gdpool( 'EXAMPLE_TIMES', START, N_ITEMS ) print( 'EXAMPLE_TIMES' ) for dvar in dvars: print(' Time value: {0:20.6f}'.format(dvar)) # # Done. Unload the kernels. # spiceypy.kclear if __name__ == '__main__': kervar() Run the code example
The program then loops over the spiceypy.dtpool 6 times, reporting the name of each pool variable, the number of data items assigned to that variable, and the variable type. Within the spiceypy.dtpool loop, a second loop outputs the contents of the data variable using spiceypy.gcpool or spiceypy.gdpool.
Number variables matching template: 6 BODY699_RING1_1 Number items: 5 Of type: N Numeric value: 133405.000000 Numeric value: 133730.000000 Numeric value: 0.000000 Numeric value: 0.000000 Numeric value: 0.000000 BODY699_RING1 Number items: 5 Of type: N Numeric value: 122170.000000 Numeric value: 136780.000000 Numeric value: 0.100000 Numeric value: 0.100000 Numeric value: 0.500000 BODY699_RING2 Number items: 5 Of type: N Numeric value: 117580.000000 Numeric value: 122170.000000 Numeric value: 0.000000 Numeric value: 0.000000 Numeric value: 0.000000 BODY699_RING1_1_NAME Number items: 1 Of type: C String value: Encke Gap BODY699_RING2_NAME Number items: 1 Of type: C String value: Cassini Division BODY699_RING1_NAME Number items: 1 Of type: C String value: A Ring EXAMPLE_TIMES Time value: 134094896.789000 Time value: 134094896.789000 Time value: 134094896.789753Note the final time value differs from the previous values in the final three decimal places despite the intention that all three strings represent the same time. This results from round-off when converting a decimal Julian day representation to the seconds past J2000 ET representation. Related Routines
Lesson 3: Coordinate ConversionsTask Statement
Learning Goals
This lesson presents these coordinate transform routines for rectangular, cylindrical, and spherical systems. Code Solution
from __future__ import print_function from builtins import input import sys # # Import the CSPICE-Python interface. # import spiceypy def coord(): # # Define the inertial and non inertial frame names. # # Initialize variables or set type. All variables # used in a PROMPT construct must be initialized # as strings. # INRFRM = 'J2000' NONFRM = 'IAU_EARTH' r2d = spiceypy.dpr() # # Load the needed kernels using a spiceypy.furnsh call on the # meta kernel. # spiceypy.furnsh( 'coord.tm' ) # # Prompt the user for a time string. Convert the # time string to ephemeris time J2000 (ET). # timstr = input( 'Time of interest: ') et = spiceypy.str2et( timstr ) # # Access the kernel pool data for the triaxial radii of the # Earth, rad[1][0] holds the equatorial radius, rad[1][2] # the polar radius. # rad = spiceypy.bodvrd( 'EARTH', 'RADII', 3 ) # # Calculate the flattening factor for the Earth. # # equatorial_radius - polar_radius # flat = ________________________________ # # equatorial_radius # flat = (rad[1][0] - rad[1][2])/rad[1][0] # # Make the spiceypy.spkpos call to determine the apparent # position of the Moon w.r.t. to the Earth at 'et' in the # inertial frame. # [pos, ltime] = spiceypy.spkpos('MOON', et, INRFRM, 'LT+S','EARTH' ) # # Show the current frame and time. # print( ' Time : {0}'.format(timstr) ) print( ' Inertial Frame: {0}\n'.format(INRFRM) ) # # First convert the position vector # X = pos(1), Y = pos(2), Z = pos(3), to RA/DEC. # [ range, ra, dec ] = spiceypy.recrad( pos ) print(' Range/Ra/Dec' ) print(' Range: {0:20.6f}'.format(range) ) print(' RA : {0:20.6f}'.format(ra * r2d) ) print(' DEC : {0:20.6f}'.format(dec* r2d) ) # # ...latitudinal coordinates... # [ range, lon, lat ] = spiceypy.reclat( pos ) print(' Latitudinal ' ) print(' Rad : {0:20.6f}'.format(range) ) print(' Lon : {0:20.6f}'.format(lon * r2d) ) print(' Lat : {0:20.6f}'.format(lat * r2d) ) # # ...spherical coordinates use the colatitude, # the angle from the Z axis. # [ range, colat, lon ] = spiceypy.recsph( pos ) print( ' Spherical' ) print(' Rad : {0:20.6f}'.format(range) ) print(' Lon : {0:20.6f}'.format(lon * r2d) ) print(' Colat: {0:20.6f}'.format(colat * r2d) ) # # Make the spiceypy.spkpos call to determine the apparent # position of the Moon w.r.t. to the Earth at 'et' in the # non-inertial, body fixed, frame. # [pos, ltime] = spiceypy.spkpos('MOON', et, NONFRM, 'LT+S','EARTH') print() print( ' Non-inertial Frame: {0}'.format(NONFRM) ) # # ...latitudinal coordinates... # [ range, lon, lat ] = spiceypy.reclat( pos ) print(' Latitudinal ' ) print(' Rad : {0:20.6f}'.format(range) ) print(' Lon : {0:20.6f}'.format(lon * r2d) ) print(' Lat : {0:20.6f}'.format(lat * r2d) ) # # ...spherical coordinates use the colatitude, # the angle from the Z axis. # [ range, colat, lon ] = spiceypy.recsph( pos ) print( ' Spherical' ) print(' Rad : {0:20.6f}'.format(range) ) print(' Lon : {0:20.6f}'.format(lon * r2d) ) print(' Colat: {0:20.6f}'.format(colat * r2d) ) # # ...finally, convert the position to geodetic coordinates. # [ lon, lat, range ] = spiceypy.recgeo( pos, rad[1][0], flat ) print( ' Geodetic' ) print(' Rad : {0:20.6f}'.format(range) ) print(' Lon : {0:20.6f}'.format(lon * r2d) ) print(' Lat : {0:20.6f}'.format(lat * r2d) ) print() # # Done. Unload the kernels. # spiceypy.kclear if __name__ == '__main__': coord() Run the code example
Time of interest: Feb 3 2002 TDBExamine the Moon position in the J2000 inertial frame, display the time and frame:
Time : Feb 3 2002 TDB Inertial Frame: J2000Convert the Moon Cartesian coordinates to right ascension declination.
Range/Ra/Dec Range: 369340.815193 RA : 203.643686 DEC : -4.979010Latitudinal. Note the difference in the expressions for longitude and right ascension though they represent a measure of the same quantity. The RA/DEC system measures RA in the interval [0,2Pi). Latitudinal coordinates measures longitude in the interval (-Pi,Pi].
Latitudinal Rad : 369340.815193 Lon : -156.356314 Lat : -4.979010Spherical. Note the difference between the expression of latitude in the Latitudinal system and the corresponding Spherical colatitude. The spherical coordinate system uses the colatitude, the angle measure away from the positive Z axis. Latitude is the angle between the position vector and the x-y (equatorial) plane with positive angle defined as toward the positive Z direction
Spherical Rad : 369340.815193 Lon : -156.356314 Colat: 94.979010The same position look-up in a body fixed (non-inertial) frame, IAU_EARTH.
Non-inertial Frame: IAU_EARTHLatitudinal coordinates return the geocentric latitude.
Latitudinal Rad : 369340.815193 Lon : 70.986950 Lat : -4.989675Spherical.
Spherical Rad : 369340.815193 Lon : 70.986950 Colat: 94.989675Geodetic. The cartographic lat/lon.
Geodetic Rad : 362962.836755 Lon : 70.986950 Lat : -4.990249 Related Routines
Lesson 4: Advanced Time Manipulation RoutinesTask Statement
Learning Goals
Code Solution
from __future__ import print_function # # Import the CSPICE-Python interface. # import spiceypy def xtic(): # # Assign the META variable to the name of the meta-kernel # that contains the LSK kernel and create an arbitrary # time string. # CALSTR = 'Mar 15, 2003 12:34:56.789 AM PST' META = 'xtic.tm' AMBIGSTR = 'Mar 15, 79 12:34:56' T_FORMAT1 = 'Wkd Mon DD HR:MN:SC PDT YYYY ::UTC-7' T_FORMAT2 = 'Wkd Mon DD HR:MN ::UTC-7 YR (JULIAND.##### JDUTC)' # # Load the meta-kernel. # spiceypy.furnsh( META ) print( 'Original time string : {0}'.format(CALSTR) ) # # Convert the time string to the number of ephemeris # seconds past the J2000 epoch. This is the most common # internal time representation used by the CSPICE # system; CSPICE refers to this as ephemeris time (ET). # et = spiceypy.str2et( CALSTR ) print( 'Corresponding ET : {0:20.6f}\n'.format(et) ) # # Make a picture of an output format. Describe a Unix-like # time string then send the picture and the 'et' value through # spiceypy.timout to format and convert the ET representation # of the time string into the form described in # spiceypy.timout. The '::UTC-7' token indicates the time # zone for the `timstr' output - PDT. 'PDT' is part of the # output, but not a time system token. # timstr = spiceypy.timout( et, T_FORMAT1) print( 'Time in string format 1 : {0}'.format(timstr) ) timstr = spiceypy.timout( et, T_FORMAT2) print( 'Time in string format 2 : {0}'.format(timstr) ) # # Why create a picture by hand when spiceypy can do it for # you? Input a string to spiceypy.tpictr with the format of # interest. `ok' returns a boolean indicating whether an # error occurred while parsing the picture string, if so, # an error diagnostic message returns in 'xerror'. In this # example the picture string is known as correct. # pic = '12:34:56.789 P.M. PDT January 1, 2006' [ pictr, ok, xerror] = spiceypy.tpictr(pic) if not bool(ok): print( xerror ) exit timstr = spiceypy.timout( et, pictr) print( 'Time in string format 3 : {0}'.format( timstr ) ) # # Two digit year representations often cause problems due to # the ambiguity of the century. The routine spiceypy.tsetyr # gives the user the ability to set a default range for 2 # digit year representation. SPICE uses 1969AD as the default # start year so the numbers inclusive of 69 to 99 represent # years 1969AD to 1999AD, the numbers inclusive of 00 to 68 # represent years 2000AD to 2068AD. # # The defined time string 'AMBIGSTR' contains a two-digit # year. Since the SPICE base year is 1969, the time subsystem # interprets the string as 1979. # et1 = spiceypy.str2et( AMBIGSTR ) # # Set 1980 as the base year causes SPICE to interpret the # time string's "79" as 2079. # spiceypy.tsetyr( 1980 ) et2 = spiceypy.str2et( AMBIGSTR ) # # Calculate the number of years between the two ET # representations, ~100. # print( 'Years between evaluations: {0:20.6f}'.\ format( (et2 - et1)/spiceypy.jyear())) # # Reset the default year to 1969. # spiceypy.tsetyr( 1969 ) # # Done. Unload the kernels. # spiceypy.kclear if __name__ == '__main__': xtic() Run the code example
Original time string : Mar 15, 2003 12:34:56.789 AM PST Corresponding ET : 100989360.974561 Time in string format 1 : Sat Mar 15 01:34:56 PDT 2003 Time in string format 2 : Sat Mar 15 01:34 03 (2452713.85760 JDUTC) Time in string format 3 : 01:34:56.789 A.M. PDT March 15, 2003 Years between evaluations: 100.000000 Lesson 5: Error HandlingTask Statement
Learning Goals
The SpiceyPy error subsystem differs from CSPICE and SPICELIB packages in that the user cannot alter the state of the error subsystem, rather the user can respond to an error signal using try-except blocks. This block natively receives and processes any SpiceyError exception signaled from SpiceyPy. The user can therefore "catch" an error signal so as to respond in an appropriate manner. Code Solution
from __future__ import print_function from builtins import input # # Import the CSPICE-Python interface. # import spiceypy from spiceypy.utils.support_types import SpiceyError def aderr(): # # Set initial parameters. # SPICETRUE = True SPICEFALSE= False doloop = SPICETRUE # # Load the data we need for state evaluation. # spiceypy.furnsh( 'aderr.tm' ) # # Start our input query loop to the user. # while (doloop): # # For simplicity, we request only one input. # The program calculates the state vector from # Earth to the user specified target 'targ' in the # J2000 frame, at ephemeris time zero, using # aberration correction LT+S (light time plus # stellar aberration). # targ = input( 'Target: ' ) if targ == 'NONE': # # An exit condition. If the user inputs NONE # for a target name, set the loop to stop... # doloop = SPICEFALSE else: # # ...otherwise evaluate the state between the Earth # and the target. Initialize an error handler. # try: # # Perform the state lookup. # [state, ltime] = spiceypy.spkezr(targ, 0., 'J2000', 'LT+S', 'EARTH') # # No error, output the state. # print( 'R : {0:20.6f} {1:20.6f} ' '{2:20.5f}'.format(*state[0:3])) print( 'V : {0:20.6f} {1:20.6f} ' '{2:20.6f}'.format(*state[3:6]) ) print( 'LT: {0:20.6f}\n'.format(float(ltime))) except SpiceyError as err: # # What if spiceypy.spkezr signaled an error? # Then spiceypy signals an error to python. # # Examine the value of 'e' to retrieve the # error message. # print( err ) print( ) # # Done. Unload the kernels. # spiceypy.kclear if __name__ == '__main__': aderr() Run the code example
Target: Moon R : -291584.616595 -266693.402359 -76095.64756 V : 0.643439 -0.666066 -0.301310 LT: 1.342311 Target: Mars R : 234536077.419136 -132584383.595569 -63102685.70619 V : 30.961373 28.932996 13.113031 LT: 923.001080 Target: Pluto barycenter R : -1451304742.838526 -4318174144.406321 -918251433.58736 V : 35.079843 3.053138 -0.036762 LT: 15501.258293 Target: Puck ===================================================================== =========== Toolkit version: CSPICE_N0067 SPICE(SPKINSUFFDATA) -- Insufficient ephemeris data has been loaded to compute the state of 7 15 (PUCK) relative to 0 (SOLAR SYSTEM BARYCENTER) at the ephemeris ep och 2000 JAN 01 12:00:00.000. spkezr_c --> SPKEZR --> SPKEZ --> SPKACS --> SPKAPS --> SPKLTC --> SP KGEO ===================================================================== =========== Target:Perplexing. What happened? The kernel files named in meta.tm did not include ephemeris data for Puck. When the SPK subsystem tried to evaluate Puck's position, the evaluation failed due to lack of data, so an error signaled. The above error signifies an absence of state information at ephemeris time 2000 JAN 01 12:00:00.000 (the requested time, ephemeris time zero). Try another look-up, this time for "Casper"
Target: Casper ===================================================================== =========== Toolkit version: CSPICE_N0067 SPICE(IDCODENOTFOUND) -- The target, 'Casper', is not a recognized name for an ephemeris objec t. The cause of this problem may be that you need an updated version of the SPICE Toolkit. Alternatively you may call SPKEZ directly if yo u know the SPICE ID codes for both 'Casper' and 'EARTH' spkezr_c --> SPKEZR ===================================================================== =========== Target:An easy to understand error. The SPICE system does not contain information on a body named 'Casper.' Another look-up, this time, "Venus".
Target: Venus R : -80970027.540532 -139655772.573898 -53860125.95820 V : 31.166910 -27.001056 -12.316514 LT: 567.655074 Target:The look-up succeeded despite two errors in our run. The SpiceyPy system can respond to error conditions (not system errors) in much the same fashion as languages with catch/throw instructions. Lesson 6: Windows, and CellsProgramming task
Learning Goals
A user should create cells by use of the appropriate SpiceyPy calls. NAIF recommends against manual creation of cells. A 'window' is a type of cell containing ordered, double precision values describing a collection of zero or more intervals. We define an interval, 'i', as all double precision values bounded by and including an ordered pair of numbers,
[ a , b ] i iwhere
a < b i - iThe intervals within a window are both ordered and disjoint. That is, the beginning of each interval is greater than the end of the previous interval:
b < a i i+1A common use of the windows facility is to calculate the intersection set of a number of time intervals. Code Solution
from __future__ import print_function # # Import the CSPICE-Python interface. # import spiceypy def win(): MAXSIZ = 8 # # Define a set of time intervals. For the purposes of this # tutorial program, define time intervals representing # an unobscured line of sight between a ground station # and some body. # los = [ 'Jan 1, 2003 22:15:02', 'Jan 2, 2003 4:43:29', 'Jan 4, 2003 9:55:30', 'Jan 4, 2003 11:26:52', 'Jan 5, 2003 11:09:17', 'Jan 5, 2003 13:00:41', 'Jan 6, 2003 00:08:13', 'Jan 6, 2003 2:18:01' ] # # A second set of intervals representing the times for which # an acceptable phase angle exists between the ground station, # the body and the Sun. # phase = [ 'Jan 2, 2003 00:03:30', 'Jan 2, 2003 19:00:00', 'Jan 3, 2003 8:00:00', 'Jan 3, 2003 9:50:00', 'Jan 5, 2003 12:00:00', 'Jan 5, 2003 12:45:00', 'Jan 6, 2003 00:30:00', 'Jan 6, 2003 23:00:00' ] # # Load our meta kernel for the leapseconds data. # spiceypy.furnsh( 'win.tm' ) # # SPICE windows consist of double precision values; convert # the string time tags defined in the 'los' and 'phase' # arrays to double precision ET. Store the double values # in the 'loswin' and 'phswin' windows. # los_et = spiceypy.str2et( los ) phs_et = spiceypy.str2et( phase ) loswin = spiceypy.stypes.SPICEDOUBLE_CELL( MAXSIZ ) phswin = spiceypy.stypes.SPICEDOUBLE_CELL( MAXSIZ ) for i in range(0, int( MAXSIZ/2 ) ): spiceypy.wninsd( los_et[2*i], los_et[2*i+1], loswin ) spiceypy.wninsd( phs_et[2*i], phs_et[2*i+1], phswin ) spiceypy.wnvald( MAXSIZ, MAXSIZ, loswin ) spiceypy.wnvald( MAXSIZ, MAXSIZ, phswin ) # # The issue for consideration, at what times do line of # sight events coincide with acceptable phase angles? # Perform the set operation AND on loswin, phswin, # (the intersection of the time intervals) # place the results in the window 'sched'. # sched = spiceypy.wnintd( loswin, phswin ) print( 'Number data values in sched : ' '{0:2d}'.format(spiceypy.card(sched)) ) # # Output the results. The number of intervals in 'sched' # is half the number of data points (the cardinality). # print( ' ' ) print( 'Time intervals meeting defined criterion.' ) for i in range( spiceypy.card(sched)//2): # # Extract from the derived 'sched' the values defining the # time intervals. # [left, right ] = spiceypy.wnfetd( sched, i ) # # Convert the ET values to UTC for human comprehension. # utcstr_l = spiceypy.et2utc( left , 'C', 3 ) utcstr_r = spiceypy.et2utc( right, 'C', 3 ) # # Output the UTC string and the corresponding index # for the interval. # print( '{0:2d} {1} {2}'.format(i, utcstr_l, utcstr_r)) # # Summarize the 'sched' window. # [meas, avg, stddev, small, large] = spiceypy.wnsumd( sched ) print( '\nSummary of sched window\n' ) print( 'o Total measure of sched : {0:16.6f}'.format(meas)) print( 'o Average measure of sched : {0:16.6f}'.format(avg)) print( 'o Standard deviation of ' ) print( ' the measures in sched : ' '{0:16.6f}'.format(stddev)) # # The values for small and large refer to the indexes of the # values in the window ('sched'). The shortest interval is # # [ sched.base[ sched.data + small] # sched.base[ sched.data + small +1] ]; # # the longest is # # [ sched.base[ sched.data + large] # sched.base[ sched.data + large +1] ]; # # Output the interval indexes for the shortest and longest # intervals. As Python bases an array index on 0, the interval # index is half the array index. # print( 'o Index of shortest interval: ' '{0:2d}'.format(int(small/2)) ) print( 'o Index of longest interval : ' '{0:2d}'.format(int(large/2)) ) # # Done. Unload the kernels. # spiceypy.kclear if __name__ == '__main__': win() Run the code example
Output the amount of data held in `sched' compared to the maximum possible amount.
Number data values in sched : 6List the time intervals for which a line of sight exists during the time of a proper phase angle.
Time intervals meeting defined criterion. 0 2003 JAN 02 00:03:30.000 2003 JAN 02 04:43:29.000 1 2003 JAN 05 12:00:00.000 2003 JAN 05 12:45:00.000 2 2003 JAN 06 00:30:00.000 2003 JAN 06 02:18:01.000Finally, an analysis of the `sched' data. The measure of an interval [a,b] (a <= b) equals b-a. Real values output in units of seconds.
Summary of sched window o Total measure of sched : 25980.000009 o Average measure of sched : 8660.000003 o Standard deviation of the measures in sched : 5958.550217 o Index of shortest interval: 1 o Index of longest interval : 0 Related Routines
Lesson 7: Utility and Constants RoutinesTask Statement
Learning Goals
SpiceyPy also includes a set of functions that return constant values often used in astrodynamics, time calculations, and geometry. Code Solution
from __future__ import print_function from builtins import input # # Import the CSPICE-Python interface. # import spiceypy def tostan(alias): value = alias # # As a convenience, let's alias a few common terms # to their appropriate counterpart. # if alias == 'meter': # # First, a 'meter' by any other name is a # 'METER' and smells as sweet ... # value = 'METERS' elif (alias == 'klicks') \ or (alias == 'kilometers') \ or (alias =='kilometer'): # # ... 'klicks' and 'KILOMETERS' and 'KILOMETER' # identifies 'KM'.... # value = 'KM' elif alias == 'secs': # # ... 'secs' to 'SECONDS'. # value = 'SECONDS' elif alias == 'miles': # # ... and finally 'miles' to 'STATUTE_MILES'. # Normal people think in statute miles. # Only sailors think in nautical miles - one # minute of arc at the equator. # value = 'STATUTE_MILES' else: pass # # Much better. Now return. If the input matched # none of the aliases, this function did nothing. # return value def units(): # # Display the Toolkit version string with a spiceypy.tkvrsn # call. # vers = spiceypy.tkvrsn( 'TOOLKIT' ) print('\nConvert demo program compiled against CSPICE ' 'Toolkit ' + vers) # # The user first inputs the name of a unit of measure. # Send the name through tostan for de-aliasing. # funits = input( 'From Units : ' ) funits = tostan( funits ) # # Input a double precision value to express in a new # unit format. # fvalue = float(input( 'From Value : ' )) # # Now the user inputs the name of the output units. # Again we send the units name through tostan for # de-aliasing. # tunits = input( 'To Units : ' ) tunits = tostan( tunits ) tvalue = spiceypy.convrt( fvalue, funits, tunits) print( '{0:12.5f} {1}'.format(tvalue, tunits) ) if __name__ == '__main__': units() Run the code example
Convert demo program compiled against CSPICE Toolkit CSPICE_N0067 From Units : klicks From Value : 3 To Units : miles 1.86411 STATUTE_MILESNow we know. Three kilometers equals 1.864 miles. Legend states Pheidippides ran from the Marathon Plain to Athens. The modern marathon race (inspired by this event) spans 26.2 miles. How far in kilometers?
Convert demo program compiled against CSPICE Toolkit CSPICE_N0067 From Units : miles From Value : 26.2 To Units : km 42.16481 km Task Statement
Code Solution
from __future__ import print_function # # Import the CSPICE-Python interface. # import spiceypy def xconst(): # # All the function have the same calling sequence: # # VALUE = function_name() # # some_procedure( function_name() ) # # First a simple example using the seconds per day # constant... # print( 'Number of (S)econds (P)er (D)ay : ' '{0:19.12f}'.format(spiceypy.spd() )) # # ...then show the value of degrees per radian, 180/Pi... # print( 'Number of (D)egrees (P)er (R)adian : ' '{0:19.16f}'.format(spiceypy.dpr() )) # # ...and the inverse, radians per degree, Pi/180. # It is obvious spiceypy.dpr() equals 1.d/spiceypy.rpd(), or # more simply spiceypy.dpr() * spiceypy.rpd() equals 1 # print( 'Number of (R)adians (P)er (D)egree : ' '{0:19.16f}'.format(spiceypy.rpd() )) # # What's the value for the astrophysicist's favorite # physical constant (in a vacuum)? # print( 'Speed of light in KM per second : ' '{0:19.12f}'.format(spiceypy.clight() )) # # How long (in Julian days) from the J2000 epoch to the # J2100 epoch? # print( 'Number of days between epochs J2000') print( ' and J2100 : ' '{0:19.12f}'.format( spiceypy.j2100() - spiceypy.j2000() )) # # Redo the calculation returning seconds... # print( 'Number of seconds between epochs' ) print( ' J2000 and J2100 : ' '{0:19.5f}'.format(spiceypy.spd() * \ (spiceypy.j2100() - spiceypy.j2000() ) )) # # ...then tropical years. # val =(spiceypy.spd()/spiceypy.tyear() ) * \ (spiceypy.j2100()- spiceypy.j2000() ) print( 'Number of tropical years between' ) print( ' epochs J2000 and J2100 : ' '{0:19.12f}'.format(val)) # # Finally, how can I convert a radian value to degrees. # print( 'Number of degrees in Pi/2 radians of arc: ' '{0:19.16f}'.format( spiceypy.halfpi() * spiceypy.dpr() )) # # and degrees to radians. # print( 'Number of radians in 250 degrees of arc : ' '{0:19.16f}'.format(250. * spiceypy.rpd() )) if __name__ == '__main__': xconst() Run the code example
Number of (S)econds (P)er (D)ay : 86400.000000000000 Number of (D)egrees (P)er (R)adian : 57.2957795130823229 Number of (R)adians (P)er (D)egree : 0.0174532925199433 Speed of light in KM per second : 299792.457999999984 Number of days between epochs J2000 and J2100 : 36525.000000000000 Number of seconds between epochs J2000 and J2100 : 3155760000.00000 Number of tropical years between epochs J2000 and J2100 : 100.002135902909 Number of degrees in Pi/2 radians of arc: 90.0000000000000000 Number of radians in 250 degrees of arc : 4.3633231299858242 Related Routines
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