def PlotComparison():
"""Script to compare home-brewed and cartopy plots.
"""
# Note to self: use scipy.ndimage.imread or
# Image.open('image.png').convert('LA') if you need
# to flatten to greyscale
img = plt.imread("./moonmap_small.png")
craters = mkin.ReadSalamuniccarCraterCSV()
mindiam = 100.
crater_sub = craters.loc[(craters["Name"].notnull())
& (craters["Diameter (km)"] > mindiam)]
cx, cy = coord2pix(crater_sub["Long"].as_matrix(),
crater_sub["Lat"].as_matrix(),
[img.shape[1], img.shape[0]])
PlotMoonPic(img, {
"x": cx,
"y": cy
},
borderless=True,
savefig="./test_moonpic.png")
PlotMoonMap(img=img,
craters=craters,
mindiam=mindiam,
projection=ccrs.PlateCarree(central_longitude=0),
savefig="./test_moonmap.png")
def setUp(self):
c1 = mkin.ReadSalamuniccarCraterCSV(filename="./LU78287GT.csv",
sortlat=False)
def match_end(s):
if re.match(r" [A-Z]", s[-2:]):
return True
return False
tocut = c1.loc[c1["Name"].notnull(), "Name"].apply(match_end)
tocut = tocut[tocut].index
c1.drop(tocut, inplace=True)
c1.drop(["ID", "Radius (deg)", "D_range", "p", "Name"],
axis=1,
inplace=True)
c1 = c1[c1["Diameter (km)"] > 20]
c2 = mkin.ReadAlanCraterCSV(filename="./alanalldata.csv",
sortlat=False)
c2.drop(["Unnamed: 0", "Unnamed: 0.1", "tag"], axis=1, inplace=True)
self.c = pd.concat([c1, c2], axis=0, ignore_index=True)
self.c.sort_values(by='Lat', inplace=True)
self.c.reset_index(inplace=True, drop=True)
self.co = mkin.ReadCombinedCraterCSV(dropfeatures=True)
del c1
del c2
def BigCraters():
craters = mkin.ReadSalamuniccarCraterCSV(dropfeatures=True)
big_name_craters = craters[(craters["Name"].notnull()) & \
(craters["Diameter (km)"] > mindiam)].copy()
mkin.CreatePlateCarreeDataSet("./moonmap_small.png",
big_name_craters,
6,
outprefix="out/out")
imagelist = sorted(glob.glob("out/out*.png"))
CheckDataSet(imagelist)
def PlotMoonMap(img="./moonmap_small.png",
craters=False,
projection=ccrs.Mollweide(central_longitude=0),
savefig=False):
"""Cartopy plot of largest named craters (see code comments for references).
Reads in long/lat for crater centroids.
Parameters
----------
img : str or ndarray
Name of file or image file in ndarray form.
craters : bool or pandas.DataFrame
LU78287GT craters. If false, loads from file.
mindiam : float
Minimum crater diameter for inclusion in plot
projection : cartopy.crs projection
Map projection
savefig : str or bool
If true, use as filename. If False, do not save figure.
"""
if type(img) == str:
img = plt.imread(img)
# Load craters table
if not type(craters) == pd.core.frame.DataFrame:
craters = mkin.ReadSalamuniccarCraterCSV()
#big_name_craters = craters[(craters["Name"].notnull()) &
# (craters["Diameter (km)"] > mindiam)]
fig = plt.figure()
# Feeding the projection keyword a ccrs method turns ax into a
# cartopy.mpl.geoaxes.GeoAxes object, which supports coordinate
# system transforms.
ax = fig.add_subplot(1, 1, 1, projection=projection)
# As noted in the Iris projections and annotations example, transform
# specifies a non-display coordinate system for the data points.
ax.imshow(img,
transform=ccrs.PlateCarree(central_longitude=0),
extent=[-180, 180, -90, 90],
origin='upper')
ax.scatter(craters["Long"],
craters["Lat"],
transform=ccrs.PlateCarree(central_longitude=0))
if savefig:
fig.savefig(savefig, dpi=200, edgecolor='w')
def ProminentCrater(cratername="Copernicus r"):
"""Checks if one prominent crater is in the right spot
in split images.
Parameters
----------
cratername : str
Crater name. Try "Copernicus r" or "Tycho r".
"""
craters = mkin.ReadSalamuniccarCraterCSV()
tycho = craters[craters['Name'].str.contains(cratername).fillna(
False)].copy()
CreateDataSet("./moonmap_small.png", tycho, 4, outprefix="out/octr")
imagelist = sorted(glob.glob("out/octr*.png"))
CheckDataSet(imagelist)
' and Head.'))
parser.add_argument('--filter_pairs',
action='store_true',
help=('Leaves only one entry per duplicate pair in'
' output dataframe.'))
parser.add_argument('--to_xlsx',
action='store_true',
help='Outputs xlsx instead of csv.')
args = parser.parse_args()
ctrs_lroc = mkin.ReadLROCCraterCSV(sortlat=False)
ctrs_lroc.drop(["tag"], axis=1, inplace=True)
ctrs_lroc['Dataset'] = 'LROC'
if args.lroclu:
ctrs_lu = mkin.ReadSalamuniccarCraterCSV(sortlat=False,
dropfeatures=False)
ctrs_lu.drop(["Radius (deg)", "D_range", "p", "Name"],
axis=1,
inplace=True)
ctrs_lu = ctrs_lu[ctrs_lu["Diameter (km)"] > 20]
ctrs_lu['Dataset'] = 'LU'
craters = pd.concat([ctrs_lroc, ctrs_lu],
axis=0,
ignore_index=True,
copy=True)
else:
ctrs_head = mkin.ReadHeadCraterCSV(sortlat=False)
ctrs_head['Dataset'] = 'Head'