import scipy.optimize as op
import gsw
import os
from scipy.interpolate import griddata
from scipy.integrate import cumtrapz
import scipy.signal as sig
import sandwell
import emapex
import plotting_functions as pf
try:
print("Floats {} and {} exist!.".format(E76.floatID, E77.floatID))
except NameError:
E76 = emapex.load(4976)
E77 = emapex.load(4977)
plot_dir = '../figures/large_wave_analysis'
ftype = 'png'
bwr = plt.get_cmap('bwr')
bwr1 = mcolors.LinearSegmentedColormap.from_list(name='red_white_blue',
colors=[(0, 0, 1),
(1, 1, 1),
(1, 0, 0)],
N=40)
def my_savefig(fid, fname):
fname = str(fid) + '_' + fname
fname = os.path.join(plot_dir, fname) + '.' + ftype
fsdir = '../figures/all_fit_specs'
if not os.path.exists(fsdir):
os.makedirs(fsdir)
psdir = '../processed_data/'
if not os.path.exists(psdir):
os.makedirs(psdir)
# Universal figure font size.
matplotlib.rc('font', **{'size': 8})
parser = argparse.ArgumentParser(description='Run w fitting on a float.')
parser.add_argument('--floatID', type=int, help='EM-APEX float ID number')
args = parser.parse_args()
Float = emapex.load(args.floatID,
apply_w=False,
apply_strain=False,
apply_iso=False,
verbose=False)
# %% Test
# Ballast information provided to me by James Girton was contain in a matlab
# file called float_ballast.m. I have converted it into a dictionary and
# converted the unit of mass (last two columns) to kg from g.
ballast_info = {
1632: [1, 1000., 5.102, 34.878, 31., 2.72e-6, 1.156, 27.885, 0.],
1633: [1, 1000., 5.102, 34.878, 31., 2.72e-6, 1.156, 28.008, 0.],
1634: [1, 1000., 5.102, 34.878, 31., 2.72e-6, 1.156, 27.948, 0.],
1635: [1, 1000., 5.102, 34.878, 31., 2.72e-6, 1.156, 27.964, 0.],
1636: [1, 1000., 5.102, 34.878, 31., 2.72e-6, 1.156, 27.948, 0.],
3304: [1, 1500., 3.0, 34.6, 16., 3.67e-6, 1.156, 26.988, 0.],
# Figure save path.
sdir = os.path.join('..', 'figures', 'vertical_velocity_analysis')
if not os.path.exists(sdir):
os.makedirs(sdir)
# Universal figure font size.
matplotlib.rc('font', **{'size': 9})
###############################################################################
try:
print("Floats {} and {} exist!".format(E76.floatID, E77.floatID))
except NameError:
E76 = emapex.load(4976, apply_w=False)
E77 = emapex.load(4977, apply_w=False)
# %% ##########################################################################
#cf_key = 'diffsq'
#params0 = np.array([3e-2, 5e-2, 3e-6, 4e+2, 1e-6, 16., 27.179])
#fixed = [None, None, None, None, None, None, None]
#wfi = vvf.fitter(E76, params0, fixed, model=model, profiles='all',
# cf_key=cf_key)
#E76.apply_w_model(wfi)
#vvf.assess_w_fit(E76, str(E76.floatID))
#print(E76.__wfi.p)
#
#cf_key = 'diffsq'
#params0 = np.array([3e-2, 5e-2, 3e-6, 4e+2, 1e-6, 16., 27.179])
om = gw.omega(N, k, m, l, f)
p = gw.phi(x, y, z, t, phi_0, k, l, m, om, U=U, V=V, phase_0=phase_0)
return pscale*p
def full_model(params, data):
return np.hstack((u_model(params, data),
v_model(params, data),
w_model(params, data),
b_model(params, data),
p_model(params, data)))
Float = emapex.load(args.floatID)
Float.calculate_pressure_perturbation()
time, z = Float.get_timeseries([args.hpid], 'z')
timeef, U = Float.get_timeseries([args.hpid], 'U_abs')
__, V = Float.get_timeseries([args.hpid], 'V_abs')
__, W = Float.get_timeseries([args.hpid], 'Ww')
__, B = Float.get_timeseries([args.hpid], 'b')
__, N2 = Float.get_timeseries([args.hpid], 'N2_ref')
__, x = Float.get_timeseries([args.hpid], 'x_ctd')
__, y = Float.get_timeseries([args.hpid], 'y_ctd')
__, PP = Float.get_timeseries([args.hpid], 'Pprime')
# Correct for sign error in pp for downward profiles with large aspect
# ratio. w is proxy for aspect.
if (np.max(np.abs(W)) > 0.05) and (args.hpid % 2 != 0.):