def plot_sat_temp(projection, temp_sparse, temp,
lons, lats, date, plot_filename):
import matplotlib.pyplot as plt
'''Plot temperature on the map'''
fig = plt.figure(1, figsize=(12, 12))
if projection == 'italy':
ax = utils.get_projection(plt, projection, regions=True,
sat=True, background=False,
coastlines=True)
else:
ax = utils.get_projection(plt, projection, regions=False,
sat=True, background=False,
coastlines=True)
utils.add_vals_on_map(ax=ax, projection=projection,
var=temp_sparse, lons=lons, lats=lats)
plt.title('Temperature live | Ultimo aggiornamento %s' % date[0])
utils.add_logo_on_map(
ax=ax, logo='meteoindiretta_logo.png', zoom=0.15, pos=(0.92, 0.1))
utils.add_logo_on_map(
ax=ax, logo='meteonetwork_logo.png', zoom=0.3, pos=(0.15, 0.05))
if projection == 'italy':
utils.add_hist_on_map(ax=ax, var=temp, label='Temperatura [C]')
else:
utils.add_hist_on_map(ax=ax, var=temp, label='Temperatura [C]', loc=2, width="25%")
plt.savefig(plot_filename, dpi=100, bbox_inches='tight')
plt.clf()
def _compute_distance_scores(obs1, obs2, segments1, segments2):
scores = [[] for _ in range(len(segments1))]
base_dist = utils.euclidean_dist(obs1, obs2)
for i, segment1 in enumerate(segments1):
projection1 = utils.get_projection(segment1['endpoints'], obs1)
for segment2 in segments2:
projection2 = utils.get_projection(segment2['endpoints'], obs2)
dist = utils.euclidean_dist(projection1, projection2)
dist_diff = abs(dist - base_dist)
scores[i].append(1.0 / (1.0 + dist_diff))
return scores
def _compute_distance_scores(obs1, obs2, segments1, segments2):
scores = [[] for _ in range(len(segments1))]
base_dist = utils.euclidean_dist(obs1, obs2)
for i, segment1 in enumerate(segments1):
projection1 = utils.get_projection(segment1['endpoints'], obs1)
for segment2 in segments2:
projection2 = utils.get_projection(segment2['endpoints'], obs2)
dist = utils.euclidean_dist(projection1, projection2)
dist_diff = abs(dist - base_dist)
scores[i].append(1.0/(1.0+dist_diff))
return scores
def plot_temperature_max(projection,
plot_type,
temp_sparse,
temp,
lons,
lats,
date,
plot_filename='output.png'):
import matplotlib.pyplot as plt
'''Plot temperature on the map'''
fig = plt.figure(1, figsize=(10, 10))
ax = utils.get_projection(plt, projection, regions=False)
utils.add_vals_on_map(ax=ax,
var=temp_sparse,
projection=projection,
lons=lons,
lats=lats)
plt.title('Temperature massime %s' % date)
utils.add_logo_on_map(ax=plt.gca(),
logo='meteoindiretta_logo.png',
zoom=0.15,
pos=(0.92, 0.1))
utils.add_logo_on_map(ax=plt.gca(),
logo='meteonetwork_logo.png',
zoom=0.3,
pos=(0.15, 0.05))
utils.add_hist_on_map(plt.gca(), temp, label='Temperatura [C]')
plt.savefig(plot_filename, dpi=100, bbox_inches='tight')
plt.clf()
def plot_gust(projection,
gust_sparse,
gust,
lons,
lats,
date,
plot_filename='output.png'):
import matplotlib.pyplot as plt
fig = plt.figure(1, figsize=(10, 10))
ax = utils.get_projection(plt, projection, regions=False)
utils.add_vals_on_map(ax=ax,
var=gust_sparse,
projection=projection,
lons=lons,
lats=lats,
minval=0,
maxval=150,
cmap='gist_stern_r')
plt.title('Raffica massima giornaliera %s' % date)
utils.add_logo_on_map(ax=plt.gca(),
logo='meteoindiretta_logo.png',
zoom=0.15,
pos=(0.92, 0.1))
utils.add_logo_on_map(ax=plt.gca(),
logo='meteonetwork_logo.png',
zoom=0.3,
pos=(0.15, 0.05))
utils.add_hist_on_map(plt.gca(), gust, label='Raffica [kmh/h]')
plt.savefig(plot_filename, dpi=100, bbox_inches='tight')
plt.clf()
def plot_rain(projection,
rain_sparse,
rain,
lons,
lats,
date,
plot_filename='output.png'):
import matplotlib.pyplot as plt
fig = plt.figure(1, figsize=(10, 10))
ax = utils.get_projection(plt, projection, regions=False)
utils.add_vals_on_map(ax=ax,
var=rain_sparse,
projection=projection,
lons=lons,
lats=lats,
minval=0,
maxval=150,
cmap='gist_stern_r')
plt.title('Precipitazioni live | Ultimo aggiornamento %s' % date[0])
utils.add_logo_on_map(ax=ax,
logo='meteoindiretta_logo.png',
zoom=0.15,
pos=(0.92, 0.1))
utils.add_logo_on_map(ax=ax,
logo='meteonetwork_logo.png',
zoom=0.3,
pos=(0.15, 0.05))
utils.add_hist_on_map(ax=ax, var=rain, label='Pioggia giornaliera [mm]')
plt.savefig(plot_filename, dpi=100, bbox_inches='tight')
plt.clf()
def __init__(self, system, code):
# Get the zone constants.
self.const = get_projection(system, code)
if self.const['TYPE'] != 'TM':
raise TypeError('Expected Transverse Mercator, found \'{0}\''.format(self.const['TYPE']))
# Coordinate system constants
a = 6378137.0 # semi-major radius of ellipsoid, meters (WGS84)
# f = 1.0 / 298.257223563 # flattening (WGS84)
f = 1.0 / 298.25722210088 # flattening (GRS80)
e2 = 2.0*f - f*f # first eccentricity squared
e12 = e2 / (1.0 - e2) # second eccentricity squared
n = f / (2.0 - f)
n2 = n * n
n3 = n2 * n
n4 = n3 * n
r = a * (1.0 - n) * (1.0 - n2) * (1.0 + 9.0 * n2 / 4.0 + 225.0 * n4 / 64.0)
# Defining coordinate system constants for the zone
P0 = dms_radians(self.const['P0']) # Latitude of origin, radians (Bb)
M0 = dms_radians(self.const['M0']) # Central meridian, radians (Lo)
X0 = float(self.const['X0']) # False northing of latitude of origin, meters (No)
Y0 = float(self.const['Y0']) # False easting of central meridian, meters (Eo)
K0 = 1.0 - 1.0/float(self.const['SF']) # Grid scale factor assigned to central meridian
# Calculate the derived coordinate system constants.
u2 = -3.0 * n / 2.0 + 9.0 * n3 / 16.0
u4 = 15.0 * n2 / 16.0 - 15.0 * n4 / 32.0
u6 = -35.0 * n3 / 48.0
u8 = 315.0 * n4 / 512.0
u0 = 2.0 * (u2 - 2.0 * u4 + 3.0 * u6 - 4.0 * u8)
u2 = 8.0 * (u4 - 4.0 * u6 + 10.0 * u8)
u4 = 32.0 * (u6 - 6.0 * u8)
u6 = 128.0 * u8
v2 = 3.0 * n / 2.0 - 27.0 * n3 / 32.0
v4 = 21.0 * n2 / 16.0 - 55.0 * n4 / 32.0
v6 = 151.0 * n3 / 96.0
v8 = 1097.0 * n4 / 512.0
v0 = 2.0 * (v2 - 2.0 * v4 + 3.0 * v6 - 4.0 * v8)
v2 = 8.0 * (v4 - 4.0 * v6 + 10.0 * v8)
v4 = 32.0 * (v6 - 6.0 * v8)
v6 = 128.0 * v8
sinp = math.sin(P0)
cosp = math.cos(P0)
cosp2 = cosp * cosp
S0 = K0 * (P0 + sinp * cosp * (u0 + cosp2 * (u2 + cosp2 * (u4 + u6 * cosp2)))) * r
# Save off the locals.
self._locals = [P0, M0, X0, Y0, K0, a, e2, e12, r, u0, u2, u4, u6, v0, v2, v4, v6, S0]
def plot_synoptic(projection,
u,
v,
mslp,
lons,
lats,
date,
plot_filename='output.png'):
import matplotlib.pyplot as plt
fig = plt.figure(1, figsize=(10, 10))
ax = utils.get_projection(plt, projection, regions=False)
utils.add_vals_on_map(ax=ax,
var=mslp,
projection=projection,
lons=lons,
lats=lats,
minval=960,
maxval=1050,
colors=False,
fontsize=8)
utils.add_barbs_on_map(ax=ax,
projection=projection,
u=u,
v=v,
lons=lons,
lats=lats,
magnitude=True)
plt.title('Pressione e venti | Ultimo aggiornamento %s' % date[0])
utils.add_logo_on_map(ax=ax,
logo='meteoindiretta_logo.png',
zoom=0.15,
pos=(0.92, 0.1))
utils.add_logo_on_map(ax=ax,
logo='meteonetwork_logo.png',
zoom=0.3,
pos=(0.15, 0.05))
plt.savefig(plot_filename, dpi=100, bbox_inches='tight')
plt.clf()
def plot_humidity(projection, hum_sparse, hum,
lons, lats, date, plot_filename):
import matplotlib.pyplot as plt
fig = plt.figure(1, figsize=(12, 12))
ax = utils.get_projection(plt, projection, regions=False)
utils.add_vals_on_map(ax=ax, var=hum_sparse, projection=projection,
lons=lons, lats=lats, minval=0, maxval=100, cmap='jet_r')
plt.title('Umidita live | Ultimo aggiornamento %s' % date[0])
utils.add_logo_on_map(
ax=ax, logo='meteoindiretta_logo.png', zoom=0.15, pos=(0.92, 0.1))
utils.add_logo_on_map(
ax=ax, logo='meteonetwork_logo.png', zoom=0.3, pos=(0.15, 0.05))
utils.add_hist_on_map(ax=ax, var=hum, label='Umidita [%]')
plt.savefig(plot_filename, dpi=100, bbox_inches='tight')
plt.clf()
def __init__(self, system, code):
# Get the zone constants.
self.const = get_projection(system, code)
if self.const['TYPE'] != 'LC':
raise TypeError('Expected Lambert, found \'{0}\''.format(self.const['TYPE']))
# Coordinate system constants
# A = 6378206.4 # major radius of ellipsoid, meters (NAD27)
# E = 0.08227185422 # eccentricity of ellipsoid (NAD27)
A = 6378137.0 # major radius of ellipsoid, meters (NAD83)
E = 0.08181922146 # eccentricity of ellipsoid (NAD83)
PI4 = math.pi / 4.0
PI2 = math.pi / 2.0
# Defining coordinate system constants for the zone
P0 = dms_radians(self.const['P0']) # latitude of origin, radians (Bb)
M0 = dms_radians(self.const['M0']) # central meridian, radians (Lo)
X0 = float(self.const['X0']) # False northing of latitude of origin, meters (Nb)
Y0 = float(self.const['Y0']) # False easting of central meridian, meters (Eo)
P1 = dms_radians(self.const['P1']) # latitude of first standard parallel, radians (Bs)
P2 = dms_radians(self.const['P2']) # latitude of second standard parallel, radians (Bn)
# Calculate the derived coordinate system constants.
m1 = math.cos(P1) / math.sqrt(1.0 - math.pow(E * math.sin(P1), 2.0))
m2 = math.cos(P2) / math.sqrt(1.0 - math.pow(E * math.sin(P2), 2.0))
t1 = (math.tan(PI4 - P1 / 2.0)
/ math.pow((1.0 - E * math.sin(P1)) / (1.0 + E * math.sin(P1)), E / 2.0))
t2 = (math.tan(PI4 - P2 / 2.0)
/ math.pow( (1.0 - E * math.sin(P2)) / (1.0 + E * math.sin(P2)), E / 2.0))
t0 = (math.tan(PI4 - P0 / 2.0)
/ math.pow((1.0 - E * math.sin(P0)) / (1.0 + E * math.sin(P0)), E / 2.0))
n = math.log(m1 / m2) / math.log(t1 / t2)
F = m1 / (n * math.pow(t1, n))
rho0 = A * F * math.pow(t0, n)
# Save off the locals.
self._locals = [A, E, PI4, PI2, P0, M0, X0, Y0, P1, P2, m1, m2, t1, t2, t0, n, F, rho0]
def plot_gust(projection, gust_sparse, gust, u, v,
lons, lats, date, plot_filename):
import matplotlib.pyplot as plt
fig = plt.figure(1, figsize=(12, 12))
ax = utils.get_projection(plt, projection, regions=False)
utils.add_vals_on_map(ax=ax, var=gust_sparse, projection=projection,
lons=lons, lats=lats, minval=0, maxval=150, cmap='gist_stern_r', fontsize=10)
utils.add_barbs_on_map(ax=ax, projection=projection, u=u, v=v,
lons=lons, lats=lats)
plt.title('Raffiche live | Ultimo aggiornamento %s' % date[0])
utils.add_logo_on_map(
ax=ax, logo='meteoindiretta_logo.png', zoom=0.15, pos=(0.92, 0.1))
utils.add_logo_on_map(
ax=ax, logo='meteonetwork_logo.png', zoom=0.3, pos=(0.15, 0.05))
utils.add_hist_on_map(ax=ax, var=gust, label='Raffica [km/h]')
plt.savefig(plot_filename, dpi=100, bbox_inches='tight')
plt.clf()
