def parse_altitude(cls, distance, unit):
"""
Parse altitude managing units conversion::
>>> Point.parse_altitude(712, 'm')
0.712
>>> Point.parse_altitude(712, 'km')
712.0
>>> Point.parse_altitude(712, 'mi')
1145.852928
:param float distance: Numeric value of altitude.
:param str unit: ``distance`` unit. Supported units
are listed in :meth:`.from_string` doc.
"""
if distance is not None:
distance = float(distance)
CONVERTERS = {
'km': lambda d: d,
'm': lambda d: units.kilometers(meters=d),
'mi': lambda d: units.kilometers(miles=d),
'ft': lambda d: units.kilometers(feet=d),
'nm': lambda d: units.kilometers(nautical=d),
'nmi': lambda d: units.kilometers(nautical=d)
}
try:
return CONVERTERS[unit](distance)
except KeyError:
raise NotImplementedError(
'Bad distance unit specified, valid are: %r' %
CONVERTERS.keys())
else:
return distance
def parse_altitude(cls, distance, unit):
if distance is not None:
distance = float(distance)
CONVERTERS = {
'km': lambda d: d,
'm': lambda d: units.kilometers(meters=d),
'mi': lambda d: units.kilometers(miles=d),
'ft': lambda d: units.kilometers(feet=d),
'nm': lambda d: units.kilometers(nautical=d),
'nmi': lambda d: units.kilometers(nautical=d)
}
return CONVERTERS[unit](distance)
else:
return distance
def parse_altitude(cls, distance, unit):
if distance is not None:
distance = float(distance)
CONVERTERS = {
'km': lambda d: d,
'm': lambda d: units.kilometers(meters=d),
'mi': lambda d: units.kilometers(miles=d),
'ft': lambda d: units.kilometers(feet=d),
'nm': lambda d: units.kilometers(nautical=d),
'nmi': lambda d: units.kilometers(nautical=d)
}
return CONVERTERS[unit](distance)
else:
return distance
def parse_altitude(cls, distance, unit):
if distance is not None:
distance = float(distance)
CONVERTERS = {
'km': lambda d: d,
'm': lambda d: units.kilometers(meters=d),
'mi': lambda d: units.kilometers(miles=d),
'ft': lambda d: units.kilometers(feet=d),
'nm': lambda d: units.kilometers(nautical=d),
'nmi': lambda d: units.kilometers(nautical=d)
}
try:
return CONVERTERS[unit](distance)
except KeyError: # pragma: no cover
raise NotImplementedError(
'Bad distance unit specified, valid are: %r' %
CONVERTERS.keys())
else:
return distance
def parse_altitude(cls, distance, unit):
if distance is not None:
distance = float(distance)
CONVERTERS = {
'km': lambda d: d,
'm': lambda d: units.kilometers(meters=d),
'mi': lambda d: units.kilometers(miles=d),
'ft': lambda d: units.kilometers(feet=d),
'nm': lambda d: units.kilometers(nautical=d),
'nmi': lambda d: units.kilometers(nautical=d)
}
try:
return CONVERTERS[unit](distance)
except KeyError: # pragma: no cover
raise NotImplementedError(
'Bad distance unit specified, valid are: %r' % CONVERTERS.keys()
)
else:
return distance
def __init__(self, *args, **kwargs):
kilometers = kwargs.pop('kilometers', 0)
if len(args) == 1:
# if we only get one argument we assume
# it's a known distance instead of
# calculating it first
kilometers += args[0]
elif len(args) > 1:
for a, b in util.pairwise(args):
kilometers += self.measure(a, b)
kilometers += units.kilometers(**kwargs)
self.__kilometers = kilometers
def __init__(self, *args, **kwargs):
kilometers = kwargs.pop('kilometers', 0)
if len(args) == 1:
# if we only get one argument we assume
# it's a known distance instead of
# calculating it first
kilometers += args[0]
elif len(args) > 1:
for a, b in util.pairwise(args):
kilometers += self.measure(a, b)
kilometers += units.kilometers(**kwargs)
self.__kilometers = kilometers
def __init__(self, *args, **kwargs):
"""
There are 3 ways to create a distance:
- From kilometers::
>>> from geopy.distance import Distance
>>> Distance(1.42)
Distance(1.42)
- From units::
>>> from geopy.distance import Distance
>>> Distance(kilometers=1.42)
Distance(1.42)
>>> Distance(miles=1)
Distance(1.609344)
- From points (for non-abstract distances only),
calculated as a sum of distances between all points::
>>> from geopy.distance import geodesic
>>> geodesic((40, 160), (40.1, 160.1))
Distance(14.003702498106215)
>>> geodesic((40, 160), (40.1, 160.1), (40.2, 160.2))
Distance(27.999954644813478)
"""
kilometers = kwargs.pop('kilometers', 0)
if len(args) == 1:
# if we only get one argument we assume
# it's a known distance instead of
# calculating it first
kilometers += args[0]
elif len(args) > 1:
for a, b in util.pairwise(args):
kilometers += self.measure(a, b)
kilometers += units.kilometers(**kwargs)
self.__kilometers = kilometers
def calculate_surrounding_coords(sample, num_miles):
"""The project asks to address the question "How many [statistic] COVID-19 occurred
within [num_miles] from [US County]?"
My approach was to calculate the surrounding coordinates from the base coordinate within
the user specified num_miles radius and zoom in on that area in Plotly.
Args:
=====
sample (pd.DataFrame): The pandas DataFrame filtered by user-specified county
num_miles (int) : The number of miles between 0 and 1000
Returns:
=======
lat (list): A list that contains the latitude values from NSEW
lon (list): A list that contains the longitude values from NSEW
"""
miles_to_km = kilometers(miles=num_miles)
start = Point(sample["latitude"].values[0], sample["longitude"].values[0])
d = geopy.distance.geodesic()
dest_north = d.destination(start, distance=miles_to_km, bearing=0)
dest_east = d.destination(start, distance=miles_to_km, bearing=90)
dest_south = d.destination(start, distance=miles_to_km, bearing=180)
dest_west = d.destination(start, distance=miles_to_km, bearing=270)
lat = [
dest_north.latitude, dest_east.latitude, dest_south.latitude,
dest_west.latitude
]
lon = [
dest_north.longitude, dest_east.longitude, dest_south.longitude,
dest_west.longitude
]
return lat, lon