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))