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sailboat.py
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sailboat.py
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import requests
from requests.auth import HTTPBasicAuth
import numpy as np
from datetime import datetime, timedelta
import pytz
eastern = pytz.timezone('US/Eastern')
import pandas as pd
from matplotlib import pyplot as plt
import cartopy.crs as ccrs
import cartopy.io.img_tiles as cimgt
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
from cmocean import cm as ccmo
def gen_url(telemetry='min', BB3='min', CI='min', CT='min', O2='min',
date_interval=None, tz='local', limit=1000):
## Returns string for URL ans list of names date type variables requested
## base strings and querry dictionaries
if limit > 30000:
print("WARNING: requesting %i records. \n This will stress navocean's server. Reducing to %i records" % (limit, 10000))
limit = 10000
group_options = {'telemetry': telemetry, 'BB3': BB3, 'CI': CI, 'CT': CT, 'O2': O2}
querry = {
'telemetry' : {
'all': ['GPSTimeStamp', '2CLon', '2CLat', '2CSpeed', '2CTrack', '2CHeading', '2CPitch', '2CRoll',
'2CWindAppSpeed', '2CWindDegOffBow','2CWindTrueSpeed', '2CWindTrueDir', '2CPressureInches', '2CAirTemp'],
'min': ['GPSTimeStamp', '2CLon', '2CLat', '2CTrack', '2CHeading'],
'atmo': ['GPSTimeStamp', '2CLon', '2CLat','2CPressureInches', '2CAirTemp',
'2CWindAppSpeed', '2CWindDegOffBow', '2CWindTrueSpeed', '2CWindTrueDir',]
},
'BB3' : {
'all' : ['2CBB3+%5BTime+UTC%5D', '2CBb%28470%29+%5Bcounts%5D', '2CBb%28532%29+%5Bcounts%5D', '2CBb%28650%29+%5Bcounts%5D', '2CBb%28470%29+%5BNTU%5D', '2CBb%28532%29+%5BNTU%5D', '2CBb%28650%29+%5BNTU%5D'],
'min' : ['2CBb%28470%29+%5BNTU%5D', '2CBb%28532%29+%5BNTU%5D','2CBb%28650%29+%5BNTU%5D']
},
'CI' : {
'all': ['2CCI+%5BTime+UTC%5D', '2CChl.+a+%5Bcounts%5D', '2CCDOM+%5Bcounts%5D', '2CPhycocyanin+%5Bcounts%5D', '2CCDOM+%5BQSU%5D', '2CChl.+a+%5Bppb%5D', '2CPhycocyanin+%5Bppb%5D'],
'min': ['2CCDOM+%5BQSU%5D', '2CChl.+a+%5Bppb%5D', '2CPhycocyanin+%5Bppb%5D']
},
'CT' : {
'all': ['2CCT+%5BTime+UTC%5D', '2CConductivity+%5BmS+cm-1%5D', '2CTemperature+%5Bdeg+C%5D'],
'min': ['2CConductivity+%5BmS+cm-1%5D', '2CTemperature+%5Bdeg+C%5D']
},
'O2' : {
'all': ['2CO2+%5BTime+UTC%5D', '2CO2+Concentration+%5Bmicromolar%5D', '2CO2+Saturation+%5B%25%5D', '2CO2+Temperature+%5Bdeg+C%5D'],
'min': ['2CO2+Concentration+%5Bmicromolar%5D']
}
}
time_dic = {'GPSTimeStamp': 'GPSTimeStamp', '2CBB3+%5BTime+UTC%5D': 'BB3 [Time UTC]', '2CCI+%5BTime+UTC%5D': 'CI [Time UTC]', '2CO2+%5BTime+UTC%5D': 'CT [Time UTC]'}
root_url = 'http://portal.navocean.com/services/nav.php?req=data&id=VELA'
fmtt = 'format=csv&output=file'
limit = 'limit=%i' % limit
token= 'token=5e5c4d86-3fd9-11eb-904e-06ad0ec96835'
# build string for variable request
columns = []
if group_options['telemetry']:
columns.extend(querry['telemetry'][group_options['telemetry']])
if group_options['BB3']:
columns.extend(querry['BB3'][group_options['BB3']])
if group_options['CI']:
columns.extend(querry['CI'][group_options['CI']])
if group_options['CT']:
columns.extend(querry['CT'][group_options['CT']])
if group_options['O2']:
columns.extend(querry['O2'][group_options['O2']])
columns = 'columns='+'%'.join(columns)
# build string for date request
if date_interval:
if tz is 'local':
start = datetime.strptime(date_interval[0], '%Y-%m-%d').astimezone(pytz.timezone('utc')).strftime('%Y-%m-%d+%H')
end = datetime.strptime(date_interval[1], '%Y-%m-%d').astimezone(pytz.timezone('utc')).strftime('%Y-%m-%d+%H')
else:
start = date_interval[0]+'+00'
end = date_interval[1]+'+00'
time = 'start='+start+'%3A00%3A00&end='+end+'%3A00%3A00'
url = '&'.join([root_url, columns, fmtt, time, token]) #, date_vars
else:
url = '&'.join([root_url, columns, fmtt, limit, token])
# get date type variables for parser
date_cols = []
for time_key in time_dic:
if time_key in url:
date_cols.append(time_dic[time_key])
print('Data variables are:', date_cols)
return url, date_cols
def load_csv(path, date_vars=False):
parse_dates = date_vars
date_parser=lambda x: pd.to_datetime(x, errors="coerce")
return pd.read_csv(path, skipinitialspace=True, parse_dates=parse_dates, date_parser=date_parser,
index_col='Id').replace(r'^\s*$', np.nan, regex=True)
def get_data(path, date_vars=['GPSTimeStamp']):
# Output: dataframe:
# Input: either navocean url, or a lists of filenames
# Names of date type variables to parse
if type(path) is str:
if 'http' in path:
request = requests.get(path, auth=HTTPBasicAuth('okeechobee', 'cleanwater'), stream=True)
file = request.raw
else:
file = path
df = load_csv(file, date_vars=date_vars)
elif type(path) is list:
li = []
for f in path:
df = load_csv(f, date_vars=date_vars)
li.append(df)
df = pd.concat(li, axis=0, ignore_index=True)
df['local time'] = df['GPSTimeStamp'].dt.tz_localize('utc').dt.tz_convert(eastern)
return df
def select_times(df, start_date=False, end_date=False):
if start_date:
start_date_val = check_date_frmt(start_date).astimezone(eastern)
df = df[df['local time']>=start_date_val]
if end_date:
end_date_val = check_date_frmt(end_date).astimezone(eastern)
df = df[df['local time']<=end_date_val]
return df
def check_date_frmt(date_str):
try:
date = datetime.strptime(date_str, '%Y-%m-%d')
return date
except:
raise ValueError('date must be string YYYY-mm-dd')
return
def var_names(df):
name_dir = {'time' : 'GPSTimeStamp', 'lon': 'Lon', 'lat': 'Lat',
'speed': 'Speed', 'track': 'Track', 'heading': 'Heading',
'pitch': 'Pitch', 'roll': ' Roll',
'wind speed': 'WindTrueSpeed', 'wind dir': 'WindTrueDir',
'pressure': 'PressureInches', 'air temp': 'AirTemp',
'bb3 time': 'BB3 [Time UTC]',
'bb470 counts': 'Bb(470) [counts]',
'bb532 counts': 'Bb(532) [counts]',
'bb650 counts':'Bb(650) [counts]',
'bb470': 'Bb(470) [NTU]',
'bb532': 'Bb(532) [NTU]',
'bb650': 'Bb(650) [NTU]',
'ci time': 'CI [Time UTC]',
'chla counts': 'Chl. a [counts]',
'cdom counts': 'CDOM [counts]',
'phyco counts': 'Phycocyanin [counts]',
'chla': 'Chl. a [ppb]',
'cdom': 'CDOM [QSU]',
'phyco': 'Phycocyanin [ppb]',
'ct time': 'CT [Time UTC]',
'cond': 'Conductivity [mS cm-1]',
'temp': 'Temperature [deg C]',
'O2 time': 'O2 [Time UTC]',
'O2':'O2 Concentration [micromolar]',
'O2 sat':'O2 Saturation [%]',
'O2 temp': 'O2 Temperature [deg C]',
'local time': 'local time'
}
new_dir = {key: value for key, value in name_dir.items() if value in df.columns}
add = set(df.columns).difference(new_dir.values())
new_dir.update({key: key for key in add})
return new_dir
def check_name(df, name):
variable_to_column_name = var_names(df)
if name in variable_to_column_name.keys():
return variable_to_column_name[name]
else:
return name
def scatter(df, x_var, y_var, z_var='bb470',cmap='jet',
start_date=False, end_date=False, ax=None, **kwargs):
x_name = check_name(df, x_var)
y_name = check_name(df, y_var)
if z_var:
z_name = check_name(df, z_var)
else:
z_name = None
if any([start_date, end_date]):
df = select_times(start_date=start_date, end_date=end_date)
if ax is None:
fig, ax = plt.subplots()
return df.plot.scatter(x_name, y_name, c=z_name, cmap=cmap, ax=ax, **kwargs)
def background(extent = [-81.15, -80.51,26.65, 27.24],
request = cimgt.GoogleTiles(style='satellite'),
ax=None, projection=None, grid=True,):
# Plots lake O background map
out = 0
if request is None:
projection = projection
image = False
else:
projection = request.crs
image = True
if ax is None:
fig = plt.figure(figsize=(10, 10))
ax = plt.axes(projection=projection)
out =+2
ax.set_extent(extent)
if grid:
try:
gl = ax.gridlines(draw_labels=True, alpha=0.2)
gl.top_labels = gl.right_labels = False
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
out =+1
except:
print('Projection does not allow gridlines')
if image:
ax.add_image(request, 10)
if out > 0:
if out == 1:
return gl
if out == 2:
return fig, ax
if out == 3:
return fig, ax, gl
def plot_path(df, var, s=None, start_date=False, end_date=False, ax=None, colorbar=True, **kwargs,):
var_column_name = check_name(df, var)
if s is None:
s = 10
else:
s = df[check_name(df, s)]
if any([start_date, end_date]):
df = select_times(df, start_date=start_date, end_date=end_date)
if ax is None:
fig, ax = background(out=True,)
mapp = ax.scatter(df['Lon'], df['Lat'], c=df[var_column_name],
s = s,
transform=ccrs.PlateCarree(), **kwargs)
if colorbar:
plt.colorbar(mapp, label=var_column_name)
return mapp