Added Python support for user-defined stars.
Defined new StateVector methods: Position and Velocity.
Defined division operator: Vector / float.
Bumped version number to 2.1.12.
Made sure all the altitude search functions
verify that the geographic latitude and target altitude
are valid numbers in the range [-90, +90].
Reworked the C version of the code to be clearer:
eliminated goofy ALTDIFF macro, split out max
altitude derivative into its own function MaxAltitudeSlope,
just like the other language implementations do.
Minor rewording of comments in MaxAltitudeSlope functions.
Python InvalidBodyError now includes the invalid body
in the diagnostic message.
This is a whole new algorithm that efficiently finds
all rise/set events, even near the poles.
It uses a recursive bisection search that limits
recursion depth by knowing the maximum possible
|da/dt| = change in altitude with respect to time.
Updated CodeQL config to ignore source templates,
because they are not syntactically valid source code.
Ignore other stuff that is irrelevant to published
code quality.
Made various fixes based on helpful CodeQL analysis.
I ported the NOVAS C 3.1 functions julian_date and cal_date to Python,
and removed the dependence on the standard datetime class for calculating UT.
Now we can create Time objects for a much wider range of year values.
Simplified the julian_date formula in C and C#.
In the Python version, I had to account for a difference
in the way integer division works for negative numbers.
In Python, integer division always rounds down, not toward
zero like it does in C/C#. So I reworked the formulas to
avoid dividing a negative integer (month-14), dividing the
positive quantity (14-month) instead and toggling addition
of the term with subtraction of the term.
I use the reworked (14-month) version in C and C# for consistency.
Also, the formatting of the formula was wacky and didn't make sense,
so now it easier to read and understand.
The Python regex for parsing dates has been expanded to allow
years before 0 and after 9999.
Allow converting Python Time to string for years before 0 and after 9999.
The following Python functions now support searching
in forward or reverse chronological order:
SearchRiseSet
SearchAltitude
SearchHourAngle
Made some minor performance improvements to the
other implementations: return sooner if we
go past time window.
Enhanced the Python function SearchMoonPhase
to allow searching forward in time when the `limitDays`
argument is positive, or backward in time when `limitDays`
is negative.
Added unit test "moon_reverse" to verify this new feature.
GitHub user `hidp123` submitted the following pull request:
https://github.com/cosinekitty/astronomy/pull/240
The problem was I had documentation for the Python enum
`Refraction` where I incorrectly wrote `Refraction.None`
instead of the correct name `Refraction.Airless`.
The fix in the pull request was correct, but it was
applied to generated source code, so it did not correctly
update the template file or the online documentation.
This commit fixes the mistake in all the affected files.
Fixed 3 of the language implementations where I forgot
to make GeoVector return the observation time, not the
backdated time. This is important to preserve existing
behavior.
Corrected a mistake in the explanation of the
C function Astronomy_GravSimInit: the `bodyStates`
parameter is NOT barycentric -- it is relative to the
originBody parameter.
Python had improperly formatted documentation for
Time.FromTerrestrialTime parameter `tt`.
The Python markdown generator `pydown` did not
correctly handle links to compound symbols like
`#GravitySimulator.Update`. It also was trying
to link to `StateVector[]` instead of `StateVector`.
Removed unnecessary and unhelpful documentation
for C# internal class constructors. They do not appear
in the generated markdown documentation anyway.
Other minor wording revisions in the documentation.
The Python version of the GravitySimulator class
is now passing all unit tests. This completes
the initial coding. I still need to review
documentation across all the language implementations.
Finished coding the Python version of the gravity simulator.
No unit tests have been written yet.
Cleaned up documentation in the other languages.
Made some functions static that did not need to be members.
Started implementation of the Python gravity simulator.
Updated the `pydown` markdown generator to include
class constructors `__init__` when they contain docstrings.
It makes more sense to report Jupiter's moons with
individually named structure fields rather than an array.
It reduces the overall code and documentation size,
and outside of unit testing, there are few cases
where iterating over an array of moons is more
lucid than using the names of the moons.
This is a breaking change, but hopefully very few
developers are using this function yet.
Fixing the breakage is very simple.
Also added operator overloads for adding and
subtracting StateVector, just like we already had
for Vector.
Three of the lunar eclipse demos (Python, Java, Kotlin)
provided a less than ideal example of efficient computation.
They were wasting a lunar eclipse search by calculating it
but not printing it. Now after printing exactly 10 lunar
eclipses, stop running immediately.
I made the scripts for testing the demos for
C, C#, JavaScript, and Python follow the improved
pattern used for Java and Kotlin: much smaller
and easier to maintain thanks to bash functions.
I refactored the unit tests for all the demo programs
to follow a different pattern that makes it simpler
to add more demo tests in the future.
The main thing is that correct output and generated
output are now in separate directories `correct` and `test`.
I have moved the test scripts from `test/test` to `./demotest`
in all the langauge demo directories.
This makes it simpler to clean up any stale generated
files before each test run by `rm -f test/*.txt`.
I stumbled across this while making the Java demo tests,
and it was a better solution, so now all the other languages
are consistent with the Java demo tests.
In the C demo tests, I also decided to compile all the
binary executables into a subdirectory `bin` that can
be cleaned out before each run, to make sure there are
no stale executables from an earlier run.
The existing lunar libration functions in the
other languages (C, C#, Python, JavaScript) were
calculating the Moon's ecliptic latitude and longitude
in radians, not degrees as intended. They have been fixed.
Implemented the libration function for Kotlin.
For years before 1582 or years after 3668, the Seasons functions
were unable to find many equinoxes and/or solstices.
The problem was that over time, the Earth's axis precesses
enough that the calendar dates of these events drifts outside
the fixed search ranges I had provided for them.
I expanded the search ranges so all season changes can be found
for a much wider range of years, as verified by unit tests:
C/C++: -2000..9999
C#: 1..9999
JavaScript: -2000..9999
Python: 1..9999
Kotlin: 1..9999
Note: C#, Python, and Kotlin currently do not allow
years values below +1. In fact, I discovered we were not
noticing when an invalid year was passed into the Kotlin code.
I updated that code to throw an exception when the year does
not match what was expected. It is disturbing that the
GregorianCalendar class silently ignores invalid years!
Constricted the search tolerance from 1 second to 0.01
seconds for the seasons search, to ensure more consistent
behavior.
Fixed a bug in the Kotlin search() function's
quadratic interpolation that was causing the convergence
to be slower than it should have been.
Added an InternalError class to explicitly indicate
that an exception occurs due to an internal assertion
failure inside Astronomy Engine. Any InternalError
should be considered a bug in Astronomy Engine, not
a bug in calling code.
Upon reviewing the code for searching moon phases,
I discovered that there was inconsistent behavior
in SearchMoonPhase. It was sometimes returning null,
other times throwing an exception. Because the caller
passes in `limitDays`, it makes sense to simply
return `null` in any case where the search fails.
This is to support callers that intentionally want
to find whether or not a moon phase occurs in a given
small window of time.
Updated internal callers of SearchMoonPhase to throw
an InternalError when they know they should always
find an event.
Internal function FindSeasonChange did not check to
make sure SearchSunLongitude succeeded. There is no
known case where this failure happens, but if it did,
a null AstroTime would have been stored in SeasonsInfo.
It is better to fail early with an explicit InternalError.
Other miscellaneous C# code cleanup.
In the Python code, I found a couple of `raise Error`
that needed to be changed to `raise InternalError`.
While working on the Kotlin implementation, I have
found a few documentation mistakes in the other language
implementations. These have been accumulating in the
`kotlin` branch. I migrated these changes back into
the released code for now, because I don't want to wait
until Kotlin is ready.
Defined consistent __repr__ methods for
Astronomy Engine Python classes.
Each string representation is reversible:
eval(repr(x)) -> x
The main goal is to facilitate interactive
debugging and experimentation for developers
working directly in the Python interpreter.
Fixed documentation mistakes in the following classes:
IlluminationInfo
LunarEclipseInfo
There was already an internal function for calculating
Greenwich Apparent Sidereal Time (GAST). By request,
I have exposed this function for outside users.
Added a minimal unit test to verify the function is
callable and returns the correct result for one case.
This function is already exhaustively tested by unit
tests that verify other functions that already called
this function when it was internal, so minimal testing
is sufficient in this case.
Added the following new functions to all 4 languages:
MassProduct: find the GM product for all Solar System bodies.
LagrangePoint: calculate L1..L5 state vectors for a pair of bodies.
LagrangePointFast: calculate L1..L5 state vectors given
state vectors and GM products of a pair of bodies.
In languages that support it, using hypot(x,y) is a little
easier to read than sqrt(x*x + y*y). Some documentation
(e.g. the man page for the C function) leads me to believe
hypot might also be better behaved than sqrt in some cases.
The JavaScript Math.hypot() is especially nice because it works
for any number of dimensions, so I can use it in 2D and 3D cases.
C only allows 2D usage, as does Python 3.7. Python 3.8 added
support for any number of dimensions, but I don't want to break
compatibility with Python 3.7 just yet. Therefore, in C and Python,
I am only using hypot for 2D cases.
C# does not appear to have any kind of hypot function,
so no changes were made to the C# code.
Thanks to https://github.com/ebraminio for this suggestion.
The phrase "Moon phase" is ambiguous, because sometimes
it means relative ecliptic longitude, other times it means
illuminated fraction. The "moonphase" demos were only
calculating the relative ecliptic longitude, which was
confusing. Now they calculate both.
Changed the documentation for the GeoMoon and GeoMoonState
functions to make it explicit that they calculate coordinates
oriented with respect to the Earth's J2000 equator (EQJ).
This is because I will soon add ecliptic (ECL) counterparts
for the GeoMoon function, to more directly search for ascending
and descending nodes of the Moon.
See this discussion:
https://github.com/cosinekitty/astronomy/issues/150
For the case of calculating a map, where each pixel
on the map represents a different location on the Earth,
it is more efficient to factor out expensive calculation
of sidereal times, assuming the entire map represents
some phenomenon at a single moment in time.
For example, to determine whether the Moon is visible
at different places on the Earth, the following
functions can be calculated across thousands of
different (lat, lon) geographic coordinates around
the world:
ObserverVector
Rotation_EQD_HOR
Before iterating over the map pixels, a program
can call GeoMoon, then convert EQJ coordinates to EQD.
Then by passing the same time value in a loop to
ObserverVector and Rotation_EQD_HOR, the program
can calculate a vector from the observer to the Moon
in EQD coordinates, then convert EQD to HOR.
The z-coordinate of the horizontal coordinates
determines whether the Moon is above or below the
observer's horizon at that point on the Earth.
This calculation pattern performed redundant
sidereal time calculations for each pixel on the map.
I changed the code for all 4 languages to cache
sidereal time so that it only needs to be calculated
once.
In the C version of Astronomy Engine, this resulted
in a speedup factor of about 2.3 in the above use case.
(See the function MapPerformanceTest in generate/ctest.c.)
The code generator was creating slightly different numeric
values for the Pluto state tables and the Jupiter rotation matrix.
I decreased the output precision by one decimal digit.
This should allow the code generator to produce identical
source code on both Linux and macOS.
More work getting MacOS build process to work.
Avoid excessive number of floating point digits of
output in the demo tests, so that insignificant
floating point variations don't cause unit test failures.
I found a mistake in the raytracer's Spheroid class,
thanks to a warning about an unused member variable.
I don't believe it had any effect on the currently
generated images, but it was important to fix it before
I ever do any set operations on Spheroids.
On macOS, there is no 'realpath' command by default.
So I eliminated some more attempts to use 'realpath'
in the demo test scripts.
Renamed the GitHub Actions tests to be consistent:
Astronomy-Engine-Linux
Astronomy-Engine-Macos
The demo tests on Mac OS failed because of very tiny
floating point discrepancies that don't matter.
Changed the output of the "Moon check" so that slight
differences in vector residue no longer fail the unit tests.
The documentation for the Python function `SearchAltitude`
was missing a mention of the `altitude` parameter.
I searched for similar mistakes in Python, C#, and C,
having just completed the same exercise in the JavaScript code.
I also found several places where extraneous newlines
between the parameter documentation caused the Markdown
to be rendered incorrectly.
