Example script that produces a comet finder chart
This commit is contained in:
Brandon Rhodes
parent
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Pic 2 32607 27530 27530 27321
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Sex 3 48437 49641 49641 51437 51437 51362
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Sge 4 98337 97365 97365 96757 96757 97365 97365 96837
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Sgr 20 90185 88635 88635 89931 89931 90185 90185 89931 89931 90496 90496 92041 92041 89931 89931 92041 92041 92855 92855 93864 93864 93506 93506 92041 92041 93506 93506 90185 90185 89642 90496 89341 95168 94141 94141 93683 93683 93085 93085 94141
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Tri 3 8796 10064 10064 10670 10670 8796
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UMa 26 58001 57399 57399 54539 54539 50801 50801 50372 50372 50801 50801 54539 54539 57399 57399 55219 55219 55302 59774 54061 54061 53910 53910 58001 58001 59774 59774 62956 62956 65378 65378 67301 54061 46733 46733 48319 48319 46733 46733 41704 41704 48319 48319 53910 53910 48319 48319 46853 46853 44471 44471 44127
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UMi 7 11767 85822 85822 82080 82080 77055 77055 79822 79822 75097 75097 72607 72607 77055
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Vel 8 42913 39953 39953 44816 44816 46651 46651 50191 50191 52727 52727 48774 48774 45941 45941 42913
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Vir 20 60129 58948 58948 57380 57380 57757 57757 60129 60129 61941 61941 63090 63090 63608 63608 63090 63090 61941 61941 64238 64238 65474 65474 64238 64238 61941 61941 66249 66249 68520 68520 72220 72220 68520 68520 66249 66249 69701 69701 71957
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Vol 6 44382 41312 41312 39794 39794 35228 35228 34481 34481 39794 39794 44382
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Vul 1 95771 97886
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@ -0,0 +1,127 @@
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import numpy as np
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import pandas as pd
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from matplotlib import pyplot as plt
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from matplotlib.collections import LineCollection
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from skyfield import api
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from skyfield.api import Star, load, tau
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from skyfield.constants import GM_SUN_Pitjeva_2005_km3_s2 as GM_SUN
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from skyfield.data import hipparcos, mpc, stellarium
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from skyfield.projections import build_stereographic_projection
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# The comet is plotted on several dates `t_comet`. But the stars only
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# need to be drawn once, so we take the middle comet date as the single
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# time `t` we use for everything else.
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ts = load.timescale(builtin=True)
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t_comet = ts.utc(2020, 7, range(17, 27))
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t = t_comet[len(t_comet) // 2] # middle date
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# An ephemeris from the JPL provides Sun and Earth positions.
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eph = load('de421.bsp')
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sun = eph['sun']
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earth = eph['earth']
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# The Minor Planet Center data file provides the comet orbit.
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with load.open(mpc.COMET_URL) as f:
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comets = mpc.load_comets_dataframe(f)
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comets = comets.set_index('designation', drop=False)
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row = comets.loc['C/2020 F3 (NEOWISE)']
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comet = sun + mpc.comet_orbit(row, ts, GM_SUN)
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# The Hipparcos mission provides our star catalog.
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with load.open(hipparcos.URL) as f:
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stars = hipparcos.load_dataframe(f)
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# And the constellation outlines come from Stellarium. We make a list
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# of the stars at which each edge stars, and the star at which each edge
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# ends.
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url = ('https://raw.githubusercontent.com/Stellarium/stellarium/master'
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'/skycultures/western_SnT/constellationship.fab')
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with load.open(url) as f:
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constellations = stellarium.parse_constellations(f)
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edges = [edge for name, edges in constellations for edge in edges]
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edges_star1 = [star1 for star1, star2 in edges]
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edges_star2 = [star2 for star1, star2 in edges]
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# We will center the chart on the comet's middle position.
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center = earth.at(t).observe(comet)
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projection = build_stereographic_projection(center)
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field_of_view_degrees = 45.0
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limiting_magnitude = 7.0
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# Now that we have constructed our projection, compute the x and y
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# coordinates that each star and the comet will have on the plot.
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star_positions = earth.at(t).observe(Star.from_dataframe(stars))
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stars['x'], stars['y'] = projection(star_positions)
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comet_x, comet_y = projection(earth.at(t_comet).observe(comet))
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# Create a True/False mask marking the stars bright enough to be
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# included in our plot. And go ahead and compute how large their
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# markers will be on the plot.
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bright_stars = (stars.magnitude <= limiting_magnitude)
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magnitude = stars['magnitude'][bright_stars]
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marker_size = (0.5 + limiting_magnitude - magnitude) ** 2.0
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# The constellation lines will each begin at the x,y of one star and end
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# at the x,y of another. We have to "rollaxis" the resulting coordinate
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# array into the shape that matplotlib expects.
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xy1 = stars[['x', 'y']].loc[edges_star1].values
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xy2 = stars[['x', 'y']].loc[edges_star2].values
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lines_xy = np.rollaxis(np.array([xy1, xy2]), 1)
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# Time to build the figure!
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fig, ax = plt.subplots(figsize=[9, 9])
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# Draw the constellation lines.
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ax.add_collection(LineCollection(lines_xy, colors='#00f2'))
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# Draw the stars.
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ax.scatter(stars['x'][bright_stars], stars['y'][bright_stars],
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s=marker_size, color='k')
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# Draw the comet positions, and label them with dates.
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comet_color = '#f00'
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offset = 0.002
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ax.plot(comet_x, comet_y, '+', c=comet_color, zorder=3)
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for xi, yi, tstr in zip(comet_x, comet_y, t_comet.utc_strftime('%-m/%d')):
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text = ax.text(xi + offset, yi - offset, tstr, color=comet_color,
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ha='left', va='top', fontsize=9, weight='bold', zorder=-1)
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text.set_alpha(0.5)
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# Finally, title the plot and set some final parameters.
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angle = np.pi - field_of_view_degrees / 360.0 * np.pi
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limit = np.sin(angle) / (1.0 - np.cos(angle))
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ax.set_xlim(-limit, limit)
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ax.set_ylim(-limit, limit)
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ax.xaxis.set_visible(False)
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ax.yaxis.set_visible(False)
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ax.set_aspect(1.0)
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ax.set_title('Comet NEOWISE {} through {}'.format(
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t_comet[0].utc_strftime('%Y %B %d'),
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t_comet[-1].utc_strftime('%Y %B %d'),
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))
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# Save.
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fig.savefig('neowise-finder-chart.png', bbox_inches='tight')
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"""Parse Stellarium data files."""
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def parse_constellations(lines):
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"""Return a list of constellation outlines.
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Each constellation outline is a list of edges, each of which is
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drawn between a pair of specific stars::
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[
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(name, [(star1, star2), (star3, star4), ...]),
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(name, [(star1, star2), (star3, star4), ...]),
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...
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]
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Each name is a 3-letter constellation abbreviation; each star is an
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integer Hipparcos catalog number.
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"""
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constellations = []
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for line in lines:
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line = line.lstrip()
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if line.startswith(b'#'):
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continue
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fields = line.split()
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if not fields:
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continue
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name = fields[0]
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edges = [(int(fields[i]), int(fields[i+1]))
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for i in range(2, len(fields), 2)]
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constellations.append((name.decode('utf-8'), edges))
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return constellations
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@ -6,173 +6,64 @@
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This section of the documentation
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will gradually accumulate example scripts
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for producing images from Skyfield computations.
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For the moment there’s only example so far,
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for plotting the elevation of a satellite over time:
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For now there are two:
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Finder chart for comet NEOWISE
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==============================
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Here is a stand-alone script
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that brings together four different data sources —
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a planetary ephemeris, a comet orbit database, a large star catalog,
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and constellation diagrams —
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to plot the course of Comet NEOWISE across Ursa Major
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over one week of July 2020:
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.. image:: _static/neowise-finder-chart.png
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.. testsetup::
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import matplotlib
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matplotlib.use('Agg') # to avoid “no display name” error on Travis CI
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del matplotlib
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|
||||
.. testcode::
|
||||
import sys
|
||||
sys.path[0:0] = ['../../examples']
|
||||
import comet_neowise_chart
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from matplotlib import pyplot as plt
|
||||
Its code includes many design decisions and presentation tweaks
|
||||
that you will probably want to adjust for your own project.
|
||||
Use the script as a starting point:
|
||||
|
||||
from skyfield import api
|
||||
from skyfield.api import load
|
||||
ts = load.timescale(builtin=True)
|
||||
eph = load('de421.bsp')
|
||||
sun = eph['sun']
|
||||
earth = eph['earth']
|
||||
|
||||
|
||||
# In[3]:
|
||||
|
||||
|
||||
t_comet = ts.utc(2020, 7, range(17, 27))
|
||||
t = t_comet[len(t_comet) // 2] # middle date
|
||||
|
||||
|
||||
# In[4]:
|
||||
|
||||
|
||||
from skyfield.data import mpc
|
||||
|
||||
with load.open(mpc.COMET_URL) as f:
|
||||
comets = mpc.load_comets_dataframe(f)
|
||||
|
||||
comets = comets.set_index('designation', drop=False)
|
||||
row = comets.loc['C/2020 F3 (NEOWISE)']
|
||||
|
||||
|
||||
# In[5]:
|
||||
|
||||
|
||||
from skyfield.constants import GM_SUN_Pitjeva_2005_km3_s2 as GM_SUN
|
||||
|
||||
comet = sun + mpc.comet_orbit(row, ts, GM_SUN)
|
||||
center = earth.at(t).observe(comet)
|
||||
|
||||
|
||||
# In[6]:
|
||||
|
||||
|
||||
from skyfield.api import Star
|
||||
from skyfield.data import hipparcos
|
||||
|
||||
|
||||
# In[53]:
|
||||
|
||||
|
||||
from skyfield.projections import build_stereographic_projection
|
||||
proj = build_stereographic_projection(center)
|
||||
|
||||
|
||||
# In[54]:
|
||||
|
||||
|
||||
with load.open(hipparcos.URL) as f:
|
||||
stars = hipparcos.load_dataframe(f)
|
||||
|
||||
|
||||
# In[55]:
|
||||
|
||||
|
||||
star_positions = earth.at(t).observe(Star.from_dataframe(stars))
|
||||
stars['x'], stars['y'] = proj(star_positions)
|
||||
|
||||
|
||||
# In[56]:
|
||||
|
||||
|
||||
limiting_magnitude = 6.5
|
||||
bright_stars = (stars.magnitude <= limiting_magnitude)
|
||||
|
||||
|
||||
# In[57]:
|
||||
|
||||
|
||||
comet_x, comet_y = proj(earth.at(t_comet).observe(comet))
|
||||
|
||||
|
||||
# In[98]:
|
||||
|
||||
|
||||
# = 'https://raw.githubusercontent.com/Stellarium/stellarium/master/skycultures/western_SnT/constellationship.fab'
|
||||
from skyfield.data.stellarium import parse_constellations
|
||||
|
||||
url = 'https://raw.githubusercontent.com/Stellarium/stellarium/master/skycultures/western_SnT/constellationship.fab'
|
||||
with load.open(url) as f:
|
||||
constellations = parse_constellations(f)
|
||||
|
||||
edges_star1 = [star1 for name, edges in constellations for star1, star2 in edges]
|
||||
edges_star2 = [star2 for name, edges in constellations for star1, star2 in edges]
|
||||
|
||||
np.array([stars['x'].loc[edges_star1], stars['y'].loc[edges_star1]])
|
||||
xy1 = stars[['x', 'y']].loc[edges_star1].values
|
||||
xy2 = stars[['x', 'y']].loc[edges_star2].values
|
||||
lines_xy = np.rollaxis(np.array([xy1, xy2]), 1)
|
||||
|
||||
|
||||
# In[94]:
|
||||
|
||||
|
||||
fig, ax = plt.subplots(figsize=[9, 9])
|
||||
|
||||
from matplotlib.collections import LineCollection
|
||||
from skyfield.api import tau
|
||||
|
||||
field_of_view_degrees = 45.0
|
||||
|
||||
line_collection = LineCollection(lines_xy) #, color=['#0002'] * len(lines_xy))
|
||||
ax.add_collection(line_collection)
|
||||
|
||||
marker_size = (0.5 + limiting_magnitude - stars.magnitude[bright_stars]) ** 2.0
|
||||
ax.scatter(stars['x'][bright_stars], stars['y'][bright_stars], s=marker_size, color='k')
|
||||
#ax.scatter(comet_x, comet_y, s=100, color='b')
|
||||
#comet_color = '#f00'
|
||||
#ax.plot(comet_x, comet_y, '+', c=comet_color, zorder=3)
|
||||
ax.plot(comet_x, comet_y, '+', zorder=3)
|
||||
offset = 0.002
|
||||
for xi, yi, tstr in zip(comet_x, comet_y, t_comet.utc_strftime('%-m/%d')):
|
||||
#text = ax.text(xi + offset, yi - offset, tstr, color=comet_color, ha='left', va='top', fontsize=12,
|
||||
text = ax.text(xi + offset, yi - offset, tstr, ha='left', va='top', fontsize=12,
|
||||
weight='bold')
|
||||
text.set_alpha(0.3)
|
||||
|
||||
ax.set_title('Comet NEOWISE {} through {}'.format(
|
||||
t_comet[0].utc_strftime('%Y %B %d'),
|
||||
t_comet[-1].utc_strftime('%Y %B %d'),
|
||||
))
|
||||
ax.set_aspect(1.0)
|
||||
ax.xaxis.set_visible(False)
|
||||
ax.yaxis.set_visible(False)
|
||||
|
||||
angle = (180.0 - field_of_view_degrees) / 720.0 * tau
|
||||
limit = np.sin(angle) / (1.0 - np.cos(angle))
|
||||
ax.set_xlim(-limit, limit)
|
||||
ax.set_ylim(-limit, limit)
|
||||
|
||||
fig.savefig('neowise-finder-chart.png')
|
||||
|
||||
|
||||
|
||||
.. image:: _static/neowise-finder-chart.png
|
||||
.. include:: ../../examples/comet_neowise_chart.py
|
||||
:literal:
|
||||
|
||||
.. testcleanup::
|
||||
|
||||
import os
|
||||
os.rename('neowise-finder-chart.png', '_static/neowise-finder-chart.png')
|
||||
|
||||
If you choose a different rendering engine
|
||||
instead of the venerable but rather ornery and complicated
|
||||
`matplotlib <https://matplotlib.org/>`_,
|
||||
then of course the plotting calls you make
|
||||
will be completely different.
|
||||
But the basic data loading and filtering will be the same,
|
||||
so hopefully the script will still help get you started
|
||||
in targeting a more modern plotting library.
|
||||
|
||||
Satellite altitude during re-entry
|
||||
==================================
|
||||
|
||||
Here is the decreasing altitude of a satellite as its orbit decayed
|
||||
and it re-entered the atmosphere above the Pacific Ocean:
|
||||
|
||||
.. image:: _static/goce-reentry.png
|
||||
|
||||
The code to produce the diagram
|
||||
using `matplotlib <https://matplotlib.org/>`_,
|
||||
including custom tick marks that are based on the date,
|
||||
is:
|
||||
|
||||
.. testcode::
|
||||
|
||||
from matplotlib import pyplot as plt
|
||||
|
|
@ -228,9 +119,7 @@ Satellite altitude during re-entry
|
|||
|
||||
# Render the plot to a PNG file.
|
||||
|
||||
fig.savefig('goce-reentry.png')
|
||||
|
||||
.. image:: _static/goce-reentry.png
|
||||
fig.savefig('goce-reentry.png', bbox_inches='tight')
|
||||
|
||||
.. testcleanup::
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue