fig = plt.figure(figsize=(5.61, 8.92 * .35))
matplotlib.rcParams['font.family'] = 'Arial'
plt.rcParams.update({'font.size': 8})
#%% Load data
mat = sio.loadmat('V:\ipasmans\enstrophy_ana.mat',
squeeze_me=True,
struct_as_record=False)
mat = mat['model']
for mat1 in mat:
mat1.t = mat1.t - 366
mat1.slope.t = mat1.slope.t - 366
ttick = np.arange(2392, 2413.01, 3) + plotter.time2num(
datetime.datetime(2005, 1, 1))
#%% Figure
ax = fig.add_subplot(1, 1, 1)
#x
ax.set_xlim(ttick[[0, -1]])
ax.xaxis.set_major_locator(ticker.FixedLocator(ttick))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(1))
ax.xaxis.set_major_formatter(
ticker.FuncFormatter(lambda x, pos: plotter.num2time(x).strftime('%m/%d')))
ax.set_xlabel('2011')
#y
ax.set_ylim(0, 225)
ax.yaxis.set_major_locator(ticker.MultipleLocator(25))
ax.set_ylabel(r'Enstrophy [$\mathrm{m^2 s^{-2}}$]')
import matplotlib.patches as patch
import numpy as np
import scipy.io as sio
import mod_plotter as plotter
import netCDF4
import scipy.io as sio
from datetime import datetime, timedelta
import imp
from matplotlib import animation
from matplotlib import ticker
import seawater as sw
imp.reload(plotter)
tOut = [datetime(2011, 7, 21, 12, 0, 0), datetime(2011, 8, 13, 12, 0, 0)]
tOut = plotter.time2num(tOut)
tOut = np.arange(tOut[0], tOut[1], 2. / 24.)
#%% Read data
mat = []
mat.append(
sio.loadmat('V:/ipasmans/plume_modes.mat',
squeeze_me=True,
struct_as_record=False))
#Adjust times to Python
for mat1 in mat:
mat1['t'] = mat1['t'] - 366.
dateRef = datetime(2005, 1, 1).toordinal()
#%% Load
mat = sio.loadmat('V:/ipasmans/along_glider.mat',
squeeze_me=True,
struct_as_record=False)
#Time to Python
mat['obs'].t = mat['obs'].t - 366
def dateFormatter(x, pos):
date = plotter.num2time(x).strftime('%m/%d')
return date
tLim = plotter.time2num([datetime(2011, 7, 21), datetime(2011, 8, 11)])
#%% Create figure
ax = []
alfabet = ['a)', 'b)', 'c)', 'd)', 'e)']
for iax in np.arange(0, 5):
ax1 = fig.add_subplot(5, 1, iax + 1)
#y
ax1.set_ylim(200, 0)
ax1.yaxis.set_major_locator(ticker.MultipleLocator(50))
ax1.yaxis.set_major_formatter(ticker.StrMethodFormatter('{x:.0f}'))
ax1.set_ylabel('Depth [m]')
#Text
import netCDF4
from os import listdir
import re as re
import mod_plotter as plotter
import datetime
import matplotlib.ticker as ticker
plt.close('all')
fig = plt.figure(figsize=(5.61, 8.92 * .25))
matplotlib.rcParams['font.family'] = 'Arial'
plt.rcParams.update({'font.size': 8, 'axes.linewidth': 1})
#%% Times
tList = []
tList.append(plotter.time2num(datetime.datetime(2011, 7, 9)))
tList.append(plotter.time2num(datetime.datetime(2011, 7, 21)))
tList.append(plotter.time2num(datetime.datetime(2011, 8, 8)))
tList.append(plotter.time2num(datetime.datetime(2011, 8, 11)))
tList.append(plotter.time2num(datetime.datetime(2011, 9, 1)))
tTick = np.arange(tList[0], tList[-1] + .001, 3)
#%%
ax = fig.add_subplot(111)
ax.set_xlim(tList[0], tList[-1])
ax.xaxis.set_major_locator(ticker.FixedLocator(np.take(tList, [0, 1, 2, 4])))
ax.xaxis.set_major_formatter(
ticker.FuncFormatter(lambda x, pos: plotter.num2time(x).strftime('%m/%d')))
import scipy.io as sio
from datetime import datetime, timedelta
import imp
from matplotlib import animation
from matplotlib import ticker
import seawater as sw
imp.reload(plotter)
#%% Figure
plt.rcParams.update({'font.size': 8})
matplotlib.rcParams['font.family'] = 'Arial'
plt.close('all')
fig = plt.figure(figsize=(5.61, 8.92 * .35))
dateRef = plotter.time2num(datetime(2005, 1, 1))
tLim = np.array([2392, 2413]) + dateRef
ax = []
for iax in np.arange(0, 3):
ax1 = fig.add_subplot(1, 3, iax + 1)
#xaxis
ax1.xaxis.set_major_locator(ticker.MultipleLocator(2))
ax1.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:.0f}'))
ax1.set_xlabel('Longitude')
ax1.set_xlim(-129, -123.5)
#yaxis
ax1.set_ylim(0, 60)
ax1.yaxis.set_major_locator(ticker.MultipleLocator(5))
import matplotlib
imp.reload(plotter)
#%% Read data
mat35 = (sio.loadmat('V:/ipasmans/ritz_vectors_exp35.mat',
squeeze_me=True,
struct_as_record=False))
mat36 = (sio.loadmat('V:/ipasmans/ritz_vectors_exp36.mat',
squeeze_me=True,
struct_as_record=False))
mat37 = (sio.loadmat('V:/ipasmans/ritz_vectors_exp37.mat',
squeeze_me=True,
struct_as_record=False))
mat = mat35
t = plotter.time2num(datetime(2011, 7, 24))
plt.close('all')
fig = plt.figure(figsize=(7.4, 8.2))
matplotlib.rcParams['font.family'] = 'Arial'
plt.rcParams.update({'font.size': 8})
#Read grid
grd = plotter.read_grid_rho()
#Obslist
obs = plotter.read_obslist()
#%% Create axes
ax = []
import numpy as np
import scipy.io as sio
import mod_plotter as plotter
import netCDF4
import scipy.io as sio
from datetime import datetime, timedelta
import imp
from matplotlib import animation
from matplotlib import ticker
import seawater as sw
import matplotlib
imp.reload(plotter)
#%%
t = plotter.time2num(datetime(2011, 8, 8))
plt.close('all')
fig = plt.figure(figsize=(5.61, 8.92 * .65))
matplotlib.rcParams['font.family'] = 'Arial'
plt.rcParams.update({'font.size': 8})
#Obslist
obs = plotter.read_obslist()
#Glider location
tLim1 = 3. * int((t - 2) / 3) + np.array([2., 5.])
obsll = [
(lon1, lat1, z1)
for (lon1, lat1, type1, t1,
z1) in zip(obs['lon'], obs['lat'], obs['type'], obs['t'], obs['z'])
if type1 == 6 and tLim1[0] <= t1 <= tLim1[1]
ax1.yaxis.set_major_formatter(ticker.StrMethodFormatter('{x:.0f}'))
ax1.xaxis.set_major_locator(ticker.MultipleLocator(2))
ax1.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:.0f}'))
ax.append(ax1)
return ax
ax = plotAx()
#%% Plot
#
ax1 = ax[0]
t = plotter.time2num(datetime(2011, 7, 21, 12, 0, 0))
it = np.abs(mat['t'] - t) < .1
cplot1 = ax1.contourf(
mat['lon'],
mat['lat'],
np.squeeze(mat['zpot'][1][:, :, it] - mat['zpot'][0][:, :, it]),
levels=[
tick1 for tick1 in np.arange(-.1, .101, .01) if np.abs(tick1) > .001
],
cmap=cmap)
cplot2 = ax1.contour(mat['lon'],
mat['lat'],
np.squeeze(mat['dEpot'][1][:, :, it]),
colors='k',
linewidths=.7,
levels=np.arange(0, 2.01e5, .1e5))
