def main():
# This is just useful for formatting returned dict
# pp = pprint.PrettyPrinter(indent=2)
# Create instance of Meso object, pass in YOUR token
m = Meso(token='YOUR TOKEN')
# Use to lookup stations, could specify counties or whatever here
# findstationids = m.station_list(state='CO')
# print(findstationids)
# Grab most recent temp (F) ob in last 90 min at each of the below stations
stations = ['kgxy, kccu, kcos, kden, kgjt, kbdu, kpub, klhx, kspd, kdro, ksbs, keeo, kguc, klic, '
'kstk, kals, ktad']
latest = m.latest(stid=stations, within='90', vars='air_temp', units='temp|F')
# create a list to store everything, iterate over the number of objs returned in latest and append
# lat, long, temp, and stid for use later
data = []
[data.append((float(ob['LATITUDE']), float(ob['LONGITUDE']), float(ob['OBSERVATIONS']['air_temp_value_1']['value']),
ob['STID'])) for ob in latest['STATION']]
print(data)
# Create a MapQuest open aerial instance.
map_quest_aerial = cimgt.MapQuestOpenAerial()
# Create a GeoAxes in the tile's projection.
ax = plt.axes(projection=map_quest_aerial.crs)
# Limit the extent of the map to Colorado's borders
ax.set_extent([-102.03, -109.03, 37, 41])
# Add the MapQuest data at zoom level 8.
ax.add_image(map_quest_aerial, 8)
# Plot lat/long pts with below params
for lat, lon, temp, stid in data:
plt.plot(lon, lat, marker='o', color='y', markersize=1,
alpha=0.7, transform=ccrs.Geodetic())
# Transforms for the text func we're about to call
geodetic_transform = ccrs.Geodetic()._as_mpl_transform(ax)
text_transform = offset_copy(geodetic_transform, units='dots', x=0, y=0)
# Plot temp and station id for each of the markers
for lat, lon, temp, stid in data:
plt.text(lon, lat, stid + '\n' + str(round(temp, 1)) + u' \N{DEGREE SIGN}' + 'F',
verticalalignment='center', horizontalalignment='center',
transform=text_transform, fontsize=9,
bbox=dict(facecolor='wheat', alpha=0.5, boxstyle='round'))
plt.title('Current Weather Around Colorado')
plt.show()
"""
@author: joshclark
This script just demonstrates some example usage for the workshop
"""
from MesoPy import Meso
import pprint
# I import Pretty Print to make the returned dictionary look, well, pretty.
pp = pprint.PrettyPrinter(indent=2)
# Instance a Meso object by passing in YOUR api_token
m = Meso(token='YOUR TOKEN')
# Fetches the latest obs for Boulder airport within 30 min of now
latest = m.latest(stid='kbdu', within='30', units='ENGLISH')
pp.pprint(latest)
# Let's format a pretty sentence that tells us the Boulder wx
x = latest['STATION'][0]
st_name = x['NAME']
temp = str(
x['OBSERVATIONS']['air_temp_value_1']['value']) + u'\N{DEGREE SIGN}' + 'F'
wind = str(x['OBSERVATIONS']['wind_speed_value_1']['value']) + ' mph'
result = 'The current weather at ' + st_name + ' is ' + temp + ' with a sustained wind of ' + wind
print(result)
# I import Pretty Print to make the returned dictionary look, well, pretty.
pp = pprint.PrettyPrinter(indent=2)
def main():
# This is just useful for formatting returned dict
# pp = pprint.PrettyPrinter(indent=2)
# Create instance of Meso object, pass in YOUR token
m = Meso(token='YOUR TOKEN')
# Use to lookup stations, could specify counties or whatever here
# findstationids = m.station_list(state='CO')
# print(findstationids)
# Grab most recent temp (F) ob in last 90 min at each of the below stations
stations = [
'kgxy, kccu, kcos, kden, kgjt, kbdu, kpub, klhx, kspd, kdro, ksbs, keeo, kguc, klic, '
'kstk, kals, ktad'
]
latest = m.latest(stid=stations,
within='90',
vars='air_temp',
units='temp|F')
# create a list to store everything, iterate over the number of objs returned in latest and append
# lat, long, temp, and stid for use later
data = []
[
data.append((float(ob['LATITUDE']), float(ob['LONGITUDE']),
float(ob['OBSERVATIONS']['air_temp_value_1']['value']),
ob['STID'])) for ob in latest['STATION']
]
print(data)
# Create a MapQuest open aerial instance.
map_quest_aerial = cimgt.MapQuestOpenAerial()
# Create a GeoAxes in the tile's projection.
ax = plt.axes(projection=map_quest_aerial.crs)
# Limit the extent of the map to Colorado's borders
ax.set_extent([-102.03, -109.03, 37, 41])
# Add the MapQuest data at zoom level 8.
ax.add_image(map_quest_aerial, 8)
# Plot lat/long pts with below params
for lat, lon, temp, stid in data:
plt.plot(lon,
lat,
marker='o',
color='y',
markersize=1,
alpha=0.7,
transform=ccrs.Geodetic())
# Transforms for the text func we're about to call
geodetic_transform = ccrs.Geodetic()._as_mpl_transform(ax)
text_transform = offset_copy(geodetic_transform, units='dots', x=0, y=0)
# Plot temp and station id for each of the markers
for lat, lon, temp, stid in data:
plt.text(lon,
lat,
stid + '\n' + str(round(temp, 1)) + u' \N{DEGREE SIGN}' + 'F',
verticalalignment='center',
horizontalalignment='center',
transform=text_transform,
fontsize=9,
bbox=dict(facecolor='wheat', alpha=0.5, boxstyle='round'))
plt.title('Current Weather Around Colorado')
plt.show()
"""
@author: joshclark
This script just demonstrates some example usage for the workshop
"""
from MesoPy import Meso
import pprint
# I import Pretty Print to make the returned dictionary look, well, pretty.
pp = pprint.PrettyPrinter(indent=2)
# Instance a Meso object by passing in YOUR api_token
m = Meso(token='YOUR TOKEN')
# Fetches the latest obs for Boulder airport within 30 min of now
latest = m.latest(stid='kbdu', within='30', units='ENGLISH')
pp.pprint(latest)
# Let's format a pretty sentence that tells us the Boulder wx
x = latest['STATION'][0]
st_name = x['NAME']
temp = str(x['OBSERVATIONS']['air_temp_value_1']['value']) + u'\N{DEGREE SIGN}' + 'F'
wind = str(x['OBSERVATIONS']['wind_speed_value_1']['value']) + ' mph'
result = 'The current weather at ' + st_name + ' is ' + temp + ' with a sustained wind of ' + wind
print(result)
# I import Pretty Print to make the returned dictionary look, well, pretty.
pp = pprint.PrettyPrinter(indent=2)
# Instance a Meso object by passing in YOUR api_token
def surfacePlot(api):
m = Meso(token=MesoPy_token)
stids = [
'KAIG', 'KATW', 'KASX', 'KDLL', 'KOVS', 'KBUU', 'KCLI', 'KEGV', 'KEAU',
'KFLD', 'KCMY', 'KGRB', 'KHYR', 'KJVL', 'KUNU', 'KENW', 'KLSE', 'KRCX',
'KLNL', 'KLNR', 'KMSN', 'KMTW', 'KMFI', 'KMDZ', 'KLUM', 'KRRL', 'KMKE',
'KMRJ', 'K82C', 'TT278', 'KEFT', 'KRNH', 'KOSH', 'KPBH', 'KPVB',
'KPDC', 'KRHI', 'KBCK', 'LAAW3', 'WUEW3', 'KRPD', 'KEZS', 'KSBM',
'KRZN', 'KSTE', 'KSUE', 'KSUW', 'KY51', 'KRYV', 'KUES', 'KPCZ', 'KAUW',
'KY50', 'KETB', 'KISW', 'KARV', 'GDNW3', 'KRGK', 'AFWW3'
] #stations
latest = m.latest(
stid=stids, within='30', vars='air_temp',
units='temp|F') #gets the latest temps (measured over past 30 minutes)
data = [] #a list with 4 columns: lat, long, temps, stid
for ob in latest['STATION']:
data.append((float(ob['LATITUDE']), float(ob['LONGITUDE']),
float(ob['OBSERVATIONS']['air_temp_value_1']['value']),
ob['STID']))
# Now that we have all the data, we can make the figure
fig = plt.figure(figsize=(10, 10))
plt.style.use('ggplot')
ax = plt.axes(projection=ccrs.Mercator())
ax.set_extent([-86.5, -93.2, 41.75, 47.25])
ax.add_feature(
ShapelyFeature(
Reader("ne_50m_admin_1_states_provinces_lakes.shp").geometries(),
ccrs.PlateCarree(),
facecolor='w',
edgecolor='gray',
linewidth=1.5))
county_shpfile = 'c_05ap16.shp' #wi county shapefile
WI = Reader(county_shpfile).records()
for i in WI:
if i.attributes['STATE'] == 'WI':
ax.add_geometries(i.geometry,
ccrs.PlateCarree(),
facecolor='white',
edgecolor='gray')
roads = cfeature.NaturalEarthFeature(category='cultural',
name='roads',
scale='10m',
facecolor='none')
ax.add_feature(roads, edgecolor='red')
ax.add_feature(
ShapelyFeature(Reader("ne_50m_lakes.shp").geometries(),
ccrs.PlateCarree(),
facecolor='lightblue',
edgecolor='gray',
linewidth=1.5))
for lat, lon, temp, stid in data: #plots a marker for each station
plt.plot(lon,
lat,
marker='o',
color='blue',
markersize=10,
alpha=0.7,
transform=ccrs.PlateCarree())
# Transforms for the text function
transform = ccrs.PlateCarree()._as_mpl_transform(ax)
text_transform = offset_copy(transform, units='dots', x=0, y=0)
# Plot temp for each of the markers
for lat, lon, temp, stid in data:
plt.text(lon,
lat,
str(round(temp, 1)) + u'\N{DEGREE SIGN}' + 'F\n\n',
verticalalignment='center',
horizontalalignment='center',
transform=text_transform,
fontsize=11)
uppertext = """Surface Observations
over Wisconsin, taken
in the last 30 minutes.
Data accessed from
MesoWest and
SynopticLabs.\n"""
lowertext = """See more current surface observations here:
http://mesowest.utah.edu/
http://aos.wisc.edu/weather/wx_obs/Surface.html
Learn how to interpret surface observation symbols here:
http://ww2010.atmos.uiuc.edu/%28Gh%29/guides/maps/sfcobs/home.rxml"""
ax.text(0.015,
0.01,
lowertext,
verticalalignment='bottom',
horizontalalignment='left',
transform=ax.transAxes,
fontsize='10.5',
bbox=dict(facecolor='white', alpha=0.5))
ax.text(0.015,
0.13,
uppertext,
verticalalignment='bottom',
horizontalalignment='left',
transform=ax.transAxes,
fontsize='10.5',
bbox=dict(facecolor='white', alpha=0.5))
plt.title('Current Weather Around Wisconsin', fontsize=14)
plt.savefig('WI_Obs.png', bbox_inches='tight')
#plt.show()
tweet = "What's the weather like around WI? Find out more here: http://aos.wisc.edu/weather/wx_obs/Surface.html"
try:
#print 'WI_Obs.png'
api.update_with_media("WI_Obs.png", status=tweet)
except tweepy.error.TweepError:
print("Twitter error raised")
plt.close('all')
#!/usr/bin/env python3
'''
Copyright © 2018 nick3499@github
Title ⟹ 'Current Weather Conditions: MesoPy (MesoWest API Wrapper)'
Hosted ⟹ https://github.com/nick3499/mesowest_latest_ob
ISC License (ISC) ⟹ https://opensource.org/licenses/ISC
MesoWest Python wrapper ⟹ https://github.com/mesowx/MesoPy
API token required ⟹ https://synopticlabs.org/api/guides/?getstarted
Note: noticed data coming from more than one station, e.g. KILROMEO4, AR794.
'''
from MesoPy import Meso # import `Meso()`
m = Meso(token='xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx') # pass API `token`
lat = m.latest(stid='AR794') # pass station ID, get `latest()` ob JSON data
s = lat['STATION'][0]['STID'] # station ID
s1 = lat['STATION'][0]['NAME'] # station name
ob = lat['STATION'][0]['OBSERVATIONS'] # JSON path prefix for current ob
s2 = ob['precip_accum_24_hour_value_1']['value'] # precip
s2 = "{0:.1f}".format(s2 * .0393700787) # mm to in
s3 = ob['solar_radiation_value_1']['value'] # solar rad
s4 = ob['wind_gust_value_1']['value'] # wind gust
s4 = "{0:.1f}".format(s4 * 1.1507794) # knots to mph
s5 = ob['dew_point_temperature_value_1d']['value'] # dew point
s5 = "{0:.1f}".format((1.8 * s5) + 32.0) # C to F
s6 = ob['wind_cardinal_direction_value_1d']['value'] # wind cardinal dir
s7 = ob['pressure_value_1d']['value'] # baro psi (KILROMEO4)
s7 = "{0:.1f}".format((s7 * 0.029529987507120267) * .01) # inHg to Mb
s8 = ob['wind_direction_value_1']['value'] # wind dir degrees
s9 = ob['sea_level_pressure_value_1d']['value'] # sea level psi (KILROMEO4)
s9 = "{0:.1f}".format((s9 * 0.029529987507120267) * .01) # inHg to Mb
s10 = ob['precip_accum_since_local_midnight_value_1']['value']
def testauth():
badtoken = Meso(token='3030')
badtoken.latest(stid=['kfnl', 'kden', 'ksdf'], within='30')
def surfacePlot(api):
m = Meso(token=MesoPy_token)
stids = ['KAIG', 'KATW', 'KASX', 'KDLL', 'KOVS', 'KBUU', 'KCLI', 'KEGV', 'KEAU', 'KFLD',
'KCMY', 'KGRB', 'KHYR', 'KJVL', 'KUNU', 'KENW', 'KLSE', 'KRCX', 'KLNL', 'KLNR',
'KMSN', 'KMTW', 'KMFI', 'KMDZ', 'KLUM', 'KRRL', 'KMKE', 'KMRJ', 'K82C', 'TT278',
'KEFT', 'KRNH', 'KOSH', 'KPBH', 'KPVB', 'KPDC', 'KRHI', 'KBCK', 'LAAW3', 'WUEW3',
'KRPD', 'KEZS', 'KSBM', 'KRZN', 'KSTE', 'KSUE', 'KSUW', 'KY51', 'KRYV', 'KUES',
'KPCZ', 'KAUW', 'KY50', 'KETB', 'KISW', 'KARV', 'GDNW3', 'KRGK', 'AFWW3'] #stations
latest = m.latest(stid=stids, within='30', vars='air_temp', units='temp|F') #gets the latest temps (measured over past 30 minutes)
data = [] #a list with 4 columns: lat, long, temps, stid
for ob in latest['STATION']:
data.append((float(ob['LATITUDE']), float(ob['LONGITUDE']),
float(ob['OBSERVATIONS']['air_temp_value_1']['value']),ob['STID']))
# Now that we have all the data, we can make the figure
fig = plt.figure(figsize=(10,10))
plt.style.use('ggplot')
ax = plt.axes(projection=ccrs.Mercator())
ax.set_extent([-86.5, -93.2, 41.75, 47.25])
ax.add_feature(ShapelyFeature(Reader("ne_50m_admin_1_states_provinces_lakes.shp").geometries(),
ccrs.PlateCarree(), facecolor = 'w', edgecolor = 'gray', linewidth=1.5))
county_shpfile = 'c_05ap16.shp' #wi county shapefile
WI = Reader(county_shpfile).records()
for i in WI:
if i.attributes['STATE'] == 'WI':
ax.add_geometries(i.geometry, ccrs.PlateCarree(), facecolor='white',edgecolor = 'gray')
roads = cfeature.NaturalEarthFeature(
category='cultural',
name='roads',
scale='10m',
facecolor = 'none')
ax.add_feature(roads, edgecolor='red')
ax.add_feature(ShapelyFeature(Reader("ne_50m_lakes.shp").geometries(),
ccrs.PlateCarree(), facecolor = 'lightblue', edgecolor = 'gray', linewidth=1.5))
for lat, lon, temp, stid in data: #plots a marker for each station
plt.plot(lon, lat, marker='o', color='blue', markersize=10,
alpha=0.7, transform = ccrs.PlateCarree())
# Transforms for the text function
transform = ccrs.PlateCarree()._as_mpl_transform(ax)
text_transform = offset_copy(transform, units='dots', x=0, y=0)
# Plot temp for each of the markers
for lat, lon, temp, stid in data:
plt.text(lon, lat, str(round(temp, 1)) + u'\N{DEGREE SIGN}' + 'F\n\n',
verticalalignment='center', horizontalalignment='center',
transform=text_transform, fontsize=11)
uppertext = """Surface Observations
over Wisconsin, taken
in the last 30 minutes.
Data accessed from
MesoWest and
SynopticLabs.\n"""
lowertext = """See more current surface observations here:
http://mesowest.utah.edu/
http://aos.wisc.edu/weather/wx_obs/Surface.html
Learn how to interpret surface observation symbols here:
http://ww2010.atmos.uiuc.edu/%28Gh%29/guides/maps/sfcobs/home.rxml"""
ax.text(0.015, 0.01, lowertext, verticalalignment = 'bottom', horizontalalignment = 'left',
transform=ax.transAxes, fontsize = '10.5', bbox=dict(facecolor='white', alpha = 0.5))
ax.text(0.015, 0.13, uppertext, verticalalignment = 'bottom', horizontalalignment = 'left',
transform=ax.transAxes, fontsize = '10.5', bbox=dict(facecolor='white', alpha = 0.5))
plt.title('Current Weather Around Wisconsin', fontsize=14)
plt.savefig('WI_Obs.png', bbox_inches = 'tight')
#plt.show()
tweet = "What's the weather like around WI? Find out more here: http://aos.wisc.edu/weather/wx_obs/Surface.html"
try:
#print 'WI_Obs.png'
api.update_with_media("WI_Obs.png", status = tweet)
except tweepy.error.TweepError:
print ("Twitter error raised")
plt.close('all')
def testauth():
badtoken = Meso(token='3030')
badtoken.latest(stid=['kfnl', 'kden', 'ksdf'], within='30')
