%pylab inline

import re
import pandas as pd
from functools import partial
from mpl_toolkits.basemap import Basemap

starsdf = pd.read_csv('./constellations.csv')

starsdf.head()

from functools import wraps

def nan(f):
    '''Function decorator that returns a nan on Exception'''
    
    @wraps(f)
    def wrapped(*args, **kwargs):
        try:
            return f(*args, **kwargs)
        except Exception:
            return np.nan
    
    return wrapped

@nan
def ra2long(ra):
    '''Parse string representing right ascension into a longitudinal angle'''
    
    h, m, s = (float(x) for x in re.match(r'(.*)h\s*(.*)m\s*(.*)s', ra.lower()).groups())

    return 360 * (h / 24 + m / 24 / 60 + s / 24 / 60 / 60)

@nan
def dec2lat(dec):
    '''Parse declination into a latitudinal angle'''
    
    d, m, s = (float(x) for x in re.match(r'(.*)°\s*(.*)′\s*(.*)″', dec.lower()).groups())
    
    return d + np.copysign(m / 60, d)  + np.copysign(s / 3600, d)

# Add these new columns to our DataFrame
starsdf['Latitude'] = starsdf['Declination'].apply(dec2lat)
starsdf['Longitude'] = starsdf['Right Ascension'].apply(ra2long)

starsdf.head()

min_am = 6.5

# DataFrame of visible stars
visdf = starsdf[starsdf['Apparent Magnitude'] <= min_am]

long = visdf.Longitude
lat = visdf.Latitude
ams = ((visdf['Apparent Magnitude'].max() - visdf['Apparent Magnitude'])) / (visdf['Apparent Magnitude'].max() - visdf['Apparent Magnitude'].min())

visdf['Apparent Magnitude'].hist()
plt.show()

# Pull out into data accquisition notebook

constellations = {
    'Name': [],
    'Latitude': [],
    'Longitude': []
}

for c in starsdf['Constellation'].unique():
    constellations['Name'].append(c)
    constellations['Latitude'].append(visdf[visdf['Constellation'] == c].Latitude.median())
    constellations['Longitude'].append(visdf[visdf['Constellation'] == c].Longitude.median())
    
constellationsdf = pd.DataFrame(constellations)

print(constellationsdf.Name.unique())

def long2ra(long, fmtstr='{:.0f}h {:.0f}m {:.2f}s'):
    '''Convert a longitude to a Right Ascension according to fmt'''
    
    m, h = np.modf(long / 360 * 24)
    s, m = np.modf(m * 60)
    s *= 60
    
    return fmtstr.format(h, m, s)

def lat2dec(lat, fmtstr='{:.0f}° {:.0f}\' {:.2f}\"'):
    '''Convert a Latitude to a Declination according to fmt'''
    
    m, d = np.modf(lat)
    s, m = np.modf(m * 60)
    s *= 60
    
    return fmtstr.format(d, m, s)

# Useful for labelling parrallels and meridians
slong2ra = partial(long2ra, fmtstr='{:.0f}h')
slat2dec = partial(lat2dec, fmtstr='{:.0f}°')

print((long2ra(95), slong2ra(95)))
print((lat2dec(50), slong2ra(50)))

fig, (ax1, ax2) = plt.subplots(1, 2)

fig.set_size_inches((15, 15))

map1 = Basemap(projection='npstere', boundinglat=15, lon_0=135, ax=ax1, celestial=True)
map2 = Basemap(projection='spstere', boundinglat=-15, lon_0=135, ax=ax2, celestial=True)

map1.drawmeridians(np.arange(0,360,15), labels=[1, 1, 1, 1],fmt=slong2ra)
map2.drawmeridians(np.arange(0,360,15), labels=[1, 1, 1, 1], fmt=slong2ra)

map1.drawparallels(np.arange(-90,90,15))
map2.drawparallels(np.arange(-90,90,15))

# Plot Stars
map1.scatter(long.values, lat.values, s=ams.values, c='k', latlon=True)
map2.scatter(long.values, lat.values, s=ams.values, c='k', latlon=True)

ax1.set_title('Northern Hemisphere', y=1.05, size=18)
ax2.set_title('Southern Hemisphere', y=1.05, size=18)

# Label Constellations
for _, i in constellationsdf.iterrows():
    xpt, ypt = map1(i.Longitude, i.Latitude)
    ax1.text(xpt, ypt, i.Name, transform=ax1.transData, clip_on=True, color='grey', weight='semibold')
    
    xpt, ypt = map2(i.Longitude, i.Latitude)
    ax2.text(xpt, ypt, i.Name, transform=ax2.transData, clip_on=True, color='grey', weight='semibold')
    
# North Star
polaris_long = starsdf[starsdf.Name == 'Polaris'].Longitude.values[0]
polaris_lat = starsdf[starsdf.Name == 'Polaris'].Latitude.values[0]

p_xpt, p_ypt = map1(polaris_long, polaris_lat)

ax1.plot(p_xpt, p_ypt, 'go')
ax1.text(p_xpt + 4e5, p_ypt + 4e5, 'Polaris\n{}\n{}'.format(long2ra(polaris_long), lat2dec(polaris_lat)),
         size=10, fontdict={'weight':'semibold','color':'g'})

plt.show()

from scipy.spatial import ConvexHull
from matplotlib.path import Path
from matplotlib.patches import PathPatch

# Ursa Minor Asterism created by the stars:
# alpha umi, delta umi, epsilon umi, zeta umi, beta umi, gamma umi, eta umi, zeta umi
um = starsdf[starsdf.Constellation == 'Ursa Minor'].iloc[[0, 6, 3, 5, 1, 2, 9, 5]]

# Plot Sky
plt.gcf().set_size_inches((6, 6))

map1 = Basemap(projection='stere', celestial=True, width=4e6, height=4e6, lat_ts=50,
              lat_0=um.Latitude.mean(), lon_0=135)

map1.drawmeridians(np.arange(0,360,15), labels=[1, 1, 0, 1], fmt=slong2ra, size=14)
map1.drawparallels(np.arange(-90,90,15))

um_xpt, um_ypt = map1(um.Longitude.mean(), um.Latitude.mean())

# Compute convex hull of visible stars in the Ursa Minor Constellation
points = np.array(map1(starsdf[starsdf.Constellation == 'Ursa Minor'].Longitude.values,
                       starsdf[starsdf.Constellation == 'Ursa Minor'].Latitude.values)).T
hull = ConvexHull(points)
points = hull.points[hull.vertices]
path = Path(points, closed=True)
patch = PathPatch(path, facecolor='white', edgecolor='w', lw=20, joinstyle='round')

# Set bg color and highlight constellation
plt.gca().set_axis_bgcolor((.95, .95, 1.))
plt.gca().add_patch(patch)

# Plot Ursa Minor Asterism
map1.plot(um.Longitude.values, um.Latitude.values, 'g-', linewidth=2, latlon=True, zorder=3)

# Plot Stars
map1.scatter(long.values, lat.values, s=20*ams.values, c='k', latlon=True, zorder=4)

# Label Constellations
for _, i in constellationsdf.iterrows():
    xpt, ypt = map1(i.Longitude, i.Latitude)
    plt.gca().text(xpt, ypt, i.Name, clip_on=True, size=24, family='serif')

plt.show()