Ported conversion to/from galactic coordinates to Python.
Added unit test for new Python code.
Updated documentation for all 4 supported languages.
Fixed mistakes in JavaScript function documentation.
Started work on a Python demo for finding when the moon
reaches relative longitudes with other solar system bodies
that are multiples of 30 degrees. It is not finished yet,
but getting close.
Added operator overloads for the Python Time class so
that times can be compared against each other.
This makes it easier to sort a list of times, for example.
Before making these changes, I had the following discrepancies
between the calculations made by the different programming
language implementations of Astronomy Engine:
C vs C#: 5.55112e-17, worst line number = 6
C vs JS: 2.78533e-12, worst line number = 196936
C vs PY: 1.52767e-12, worst line number = 159834
Now the results are:
Diffing calculations: C vs C#
ctest(Diff): Maximum numeric difference = 5.55112e-17, worst line number = 5
Diffing calculations: C vs JS
ctest(Diff): Maximum numeric difference = 1.02318e-12, worst line number = 133677
Diffing calculations: C vs PY
ctest(Diff): Maximum numeric difference = 5.68434e-14, worst line number = 49066
Diffing calculations: JS vs PY
ctest(Diff): Maximum numeric difference = 1.02318e-12, worst line number = 133677
Here is how I did this:
1. Use new constants HOUR2RAD, RAD2HOUR that directly convert between radians and sidereal hours.
This reduces tiny roundoff errors in the conversions.
2. In VSOP longitude calculations, keep clamping the angular sum to
the range [-2pi, +2pi], to prevent it from accumulating thousands
of radians. This reduces the accumulated error in the final result
before it is fed into trig functions.
The remaining discrepancies are largely because of an "azimuth amplification" effect:
When converting equatorial coordinates to horizontal coordinates, an object near
the zenith (or nadir) has an azimuth that is highly sensitive to the input
equatorial coordinates. A tiny change in right ascension (RA) can cause a much
larger change in azimuth.
I tracked down the RA discrepancy, and it is due to a different behavior
of the atan2 function in C and JavaScript. There are cases where the least
significant decimal digit is off by 1, as if due to a difference of opinion
about rounding policy.
My best thought is to go back and have a more nuanced diffcalc that
applies less strict tests for azimuth values than the other calculated values.
It seems like every other computed quantity is less sensitive, because solar
system bodies tend to stay away from "poles" of other angular coordinate
systems: their ecliptic latitudes and equatorial declinations are usually
reasonably close to zero. Therefore, right ascensions and ecliptic longitudes
are usually insensitive to changes in the cartesian coordinates they
are calculated from.
This change has no effect on client-facing behavior.
It just makes the internal data tables for the array of
constellation appear more compact in C, C#, and Python.
This is what the TypeScript/JavaScript code was already doing.
The demo shows how to correct for light travel
time to render Jupiter's moons as they appear
from the Earth.
Created an addition operator for the Vector
class in the Python code, because it is handy.
Corrected a bug in the string representation
of the Python StateVector class.
Now there are constants for the mean radii of Jupiter's
four major moons available in the C, C#, Python, and JavaScript
versions of Astronomy Engine.
Clarified that these are all mean radii.
Fixed some lingering "//" comments in the C code
(I want to keep ANSI C code as portable as possible.)
To assist software that wants to depict Jupiter and its 4 major moons
as they would appear in a telescope, it is important to know their
physical sizes. I already had constants for Jupiter's equatorial
and polar radii. Here I add constants for the radii of the moons
Io, Europa, Ganymede, and Callisto. They are all nearly spherical,
so a single mean radius value is sufficient.
My pydown.py custom Markdown generator was printing bogus
warnings about unknown symbol types, when it was actually
generating correct documentation for those symbols.
Eliminated the warnings, and improved the output format
for global constant documentation: no more extraneous spaces.
If there really is an undocumented symbol detected, fail the build!
Don't just print a warning that slides up the screen unnoticed.
I am starting the process of implementing calculation
of Jupiter's four largest moons: Io, Europa, Ganymede, Callisto.
This commit just contains constant declarations for the
equatorial, polar, and volumetric mean radii of Jupiter.
The positions of the moons will be related to the center
of Jupiter and be expressed in Jupiter equatorial radius units,
so I felt it would be good to give users a way to convert to
kilometers, which can in turn be converted to AU.
Python docstrings don't work for variables, so I hacked
a special comment format for helping pydown generate Markdown
text for the README.md for the exported constant KM_PER_AU,
or any other constants I may want to expose in the future.
Use a private enumerated type to select which direction
the precession and nutation is to be done:
- from date to J2000
- from J2000 to date
Normalize the order of parameters to be consistent
between precession() and nutation(), and across languages.
Pass in AstroTime instead of a pair of floating point TT
values (one of which had to be 0).
Added TypeScript version of ObserverVector(),
but it has not yet been documented or tested.
Astronomy Engine used to use USNO historical and predictive tables,
along with linear interpolation, to calculate Delta-T values.
The problem with the USNO tables is, they did not work well outside
a few centuries around present day.
Later I replaced with Espenak & Meeus piecewise polynomials
that work over a much larger time span (thousands of years).
I just discovered there were still comments in the code referring
to the USNO models. I updated the ones I could find to reflect
the current truth about how the code works today.
This is technically a breaking change, but only for clients
that use the cartesian coordinates in an ecliptic coordinate
return type. Before now, the coordinates were just separate
floating-point members ex, ey, ez. Now they are a standard
vector type.
The purpose is to allow seamless interfacing with vector
rotation functions, and to be consistent with the equatorial
coordinate types.
Now that equatorial coordinates include both angles
and cartesian coordinates, there is no need for the
VectorFromEquator function. It has been removed
from all four supported languages.
The expression "VectorFromEquator(equ, time)" can be
replaced with "equ.vec" in any calling code.
I'm about to start working on adding a new output
from the Horizon functions. It was a good time to better
document the ideas behind these calculations, before
adding anything new. These are internal comments only
and do not affect generated documentation.
While I was in there, I noticed extra code that was
checking for impossible return values from atan2().
I eliminated these.
I forgot that my build process automatically updates
copyright years when the current year changes.
My Travis CI unit tests verify that there are no local
changes after running all the tests.
That test failed because the update_copyrights.py changed
all the "2019-2020" to "2019-2021".
In all four versions of Astronomy Engine (C, C#, JavaScript, and Python),
starting a search for a full moon near December 19, 2020 would fail.
I added a unit test to all four languages and it failed consistently
across them all.
The root cause: I was too optimistic about how narrow I could make
the window around the approximate moon phase time in the
SearchMoonPhase functions. Finding the exact moon phase time failed
because it was outside this excessively small window around the approximate
time. I increased the window from 1.8 days to 3.0 days.
This should handle all cases with minimal impact on performance.
Now all four of the new unit tests pass.
I believe this wraps up the Python integrator.
It now works in all 4 languages and passes all tests.
Fixed up demo tests to match new output.
Turned on Travis CI checking in this branch again.
To be consistent, when calculating the geocentric position of the Sun,
we do need to correct for light travel time just like we would for any
other object. This reduces the maximum time error for predicting transits
from 25 minutes to 11 minutes.
Also had to disable aberration when calculating moon phases
(longitude from Sun) in order to keep a good fit with test data.
Added global/local solar eclipse functions to topic indexes for
C#, JavaScript, and Python.
Revised wording "eclipse found may be" --> "eclipse may be".
Python:
- Added missing Attributes section in class GlobalSolarEclipseInfo.
- Added classes EclipseEvent, LocalSolarEclipseInfo.
- Added stub functions SearchLocalSolarEclipse, NextLocalSolarEclipse.
In all 4 supported languages, use consistent constant names for
Earth and Moon radii.
Use Moon's equatorial radius for rise/set timing.
Use Moon's mean radius for calculating Moon's umbra radius for
detecting solar eclipses.
Also use Moon's mean radius for determining whether the Earth's shadow
touches the Moon, for finding lunar eclipses.
Use the Moon's polar radius for distinguishing between total
and annular eclipses, with a 14 meter bias (instead of 1420 meters!)
to match Espenak data.
Use consistent unit test error threshold of 0.57 minutes for rise/set.
Updated demo test data for slight changes to rise/set prediction times.
Updated doxygen options to issue an error on any warnings.
Fixed the incorrect function name link that doxygen was warning me about.
There is no need to use absolute value, and it makes the logic
easier for me to understand if I express each of the inequalities
in terms of addition rather than subtraction.
I had to increase certain error tolerances in the unit tests.
Reworked the unit tests to make more sense by waiting until
each language step is done to check against each other.
That way I can run a single language step independently.
Increase type safety by making the enumerated type Body
derive from Enum rather than IntEnum, as recommended by
https://www.python.org/dev/peps/pep-0435/
Fixed places where I was treating Body values as integers.
Now when a Time object is evaluated and represented in
the Python interpreter, it results in a string of the form:
astronomy.Time(ut)
where ut is the numeric representation of the ut field.
This mimics the exact way such a Time value could be constructed.
That is, eval(repr(t)) results in a time value equal to t.
