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2001_NEMURO_avg.py
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2001_NEMURO_avg.py
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#
## 3d_gui.py
## 3D visualization of 2 variables in the Patagonia region
#
import sys, os, random
import matplotlib
import interp # f2py generated fortran wrappers from interpolate.f90
import numpy as np
import math
import re
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
from netCDF4 import Dataset, Variable
from collections import OrderedDict
from datetime import *
from time import *
# Global Variables
global exp_dir, file_list, fhead
global tday_ref, date_ref, date_file_1
global fnum_min, fnum_max
global varnamelist, var_1_combined, var_2_combined
global F1, F2, zr, nt, var_1_name, var_2_name
global it, nt, ii1, jj1, int_i, int_j
global lon_rho, lat_rho, mask_rho, lon_u, lat_u, mask_u, lon_v, lat_v, mask_v
global lon_psi, lat_psi, mask_psi, h
global xi_rho, eta_rho, xi_psi, eta_psi
global xi_u, eta_u, xi_v, eta_v
global lon_1, lon_2, lat_1, lat_2
global mask_rho_nan
global var_1_loaded_from, var_2_loaded_from
## uncomment the below to get information on fortran routines used
#
##############################
# #
# print im.hindices.__doc__ #
# print im.try_range.__doc__ #
# print im.inside.__doc__ #
# #
##############################
##### matplotlibrc settings #####
# tick label size
matplotlib.rc('xtick', labelsize=7)
matplotlib.rc('ytick', labelsize=7)
# title size
matplotlib.rc('axes', titlesize=10)
# font size
matplotlib.rc('font', size=10.0)
##### End matplotlibrc settings #####
class AppForm(QMainWindow):
def __init__(self, parent=None):
'''Function to instantiate the GUI window object and widgets inside
'''
QMainWindow.__init__(self, parent)
self.setWindowTitle('3D Patagonia Model')
### read grid data in from grid file
self.read_grid_data()
### create window widgets
self.create_plot_window()
def create_plot_window(self):
'''Function to create UI
'''
global varnamelist, fhead
self.plot_window = QWidget()
### create two figures
self.dpi = 150
self.fig_1 = Figure((10.0, 10.0), dpi=self.dpi)
self.fig_2 = Figure((10.0, 10.0), dpi=self.dpi)
self.canvas_1 = FigureCanvas(self.fig_1)
self.canvas_2 = FigureCanvas(self.fig_2)
self.canvas_1.setParent(self.plot_window)
self.canvas_2.setParent(self.plot_window)
### create 2 subplots
self.axes_1 = self.fig_1.add_subplot(111)
self.axes_2 = self.fig_2.add_subplot(111)
### GUI controls ###
#### input fields (choose model, date, lon/lat, variables)
self.model_select_label = QLabel('Select Model')
self.model_select = QComboBox(self)
self.model_select.addItem('Select Model')
self.model_select.addItem('Patagonia Surface and Vertical Model')
self.date_start_label = QLabel('Start Date')
self.date_start = QLineEdit('26 Jun 2001')
self.date_start.setMaximumWidth(100)
self.date_end_label = QLabel('End date')
self.date_end = QLineEdit('20 Dec 2001')
self.date_end.setMaximumWidth(100)
self.lon_east_label = QLabel('Lon Limit East')
self.lon_east = QLineEdit('-55')
self.lon_east.setMaximumWidth(100)
self.lon_west_label = QLabel('Lon Limit West')
self.lon_west = QLineEdit('-75')
self.lon_west.setMaximumWidth(100)
self.lat_north_label = QLabel('Lat Limit North')
self.lat_north = QLineEdit('-50')
self.lat_north.setMaximumWidth(100)
self.lat_south_label = QLabel('Lat Limit South')
self.lat_south = QLineEdit('-60')
self.lat_south.setMaximumWidth(100)
self.variable_1_label = QLabel('Variable 1')
self.variable_1 = QComboBox(self)
self.variable_2_label = QLabel('Variable 2')
self.variable_2 = QComboBox(self)
### Populate variable comboBoxes with netcdf variables
varnamelist = self.read_var_data()
self.variable_1.addItem('Choose Variable')
for name in varnamelist:
self.variable_1.addItem(name)
self.variable_1.activated.connect(lambda: self.load_var_1_surf(self.date_start.text(),
self.date_end.text(), self.lon_east.text(),
self.lon_west.text(), self.lat_north.text(),
self.lat_south.text(),self.variable_1.currentText()))
self.variable_2.addItem('Choose Variable')
for name in varnamelist:
self.variable_2.addItem(name)
self.variable_2.activated.connect(lambda: self.load_var_2_surf(self.date_start.text(),
self.date_end.text(), self.lon_east.text(),
self.lon_west.text(), self.lat_north.text(),
self.lat_south.text(),self.variable_2.currentText()))
#### Plot buttons
self.surf_surf = QPushButton('Surface-Surface')
self.surf_surf.setMaximumWidth(120)
self.connect(self.surf_surf, SIGNAL('clicked()'), self.draw_surf_surf)
self.depth_depth = QPushButton('Depth-Depth')
self.depth_depth.setMaximumWidth(120)
self.connect(self.depth_depth, SIGNAL('clicked()'), self.draw_depth_depth)
self.two_plots = QPushButton('Surface-Depth')
self.two_plots.setMaximumWidth(120)
self.connect(self.two_plots, SIGNAL('clicked()'), self.on_draw_2_plots)
#### User-defined section select button
self.select_section = QPushButton('Select Section')
self.select_section.setMaximumWidth(120)
self.connect(self.select_section, SIGNAL('clicked()'), self.on_select_section)
#### Reset button
self.reset_button = QPushButton('Reset')
self.reset_button.setMaximumWidth(100)
self.connect(self.reset_button, SIGNAL('clicked()'), self.on_reset_button)
#### slider
self.slider = QSlider(Qt.Horizontal)
self.slider.setMaximumWidth(1287)
self.slider.sliderMoved.connect(self.slider_moved)
#### play button
self.play_button = QPushButton('Play')
self.play_button.setCheckable(True)
self.play_button.setMaximumWidth(75)
#self.connect(self.play_button, SIGNAL('clicked()'), self.on_play)
self.play_button.clicked[bool].connect(self.on_play)
input_dict = OrderedDict()
input_dict[self.model_select_label] = self.model_select
input_dict[self.date_start_label ] = self.date_start
input_dict[self.date_end_label ] = self.date_end
input_dict[self.lon_east_label ] = self.lon_east
input_dict[self.lon_west_label ] = self.lon_west
input_dict[self.lat_north_label ] = self.lat_north
input_dict[self.lat_south_label ] = self.lat_south
input_dict[self.variable_1_label ] = self.variable_1
input_dict[self.variable_2_label ] = self.variable_2
input_dict[self.surf_surf ] = self.surf_surf
input_dict[self.depth_depth ] = self.depth_depth
input_dict[self.two_plots ] = self.two_plots
input_dict[self.select_section ] = self.select_section
input_dict[self.reset_button ] = self.reset_button
### End GUI controls ###
### Window Layout
hbox = QHBoxLayout()
vbox = QVBoxLayout()
form_layout = QFormLayout()
for i in input_dict:
form_layout.addRow(i, input_dict[i])
hbox.addWidget(self.canvas_1)
hbox.addWidget(self.canvas_2)
hbox.addLayout(form_layout)
vbox.addLayout(hbox)
vbox.addWidget(self.slider)
vbox.addWidget(self.play_button)
self.plot_window.setLayout(vbox)
self.setCentralWidget(self.plot_window)
def load_var_1_surf(self, date_start, date_end, lon_e, lon_w,
lat_n, lat_s, var_1):
'''Function to load the variable chosen in comboBox 1
'''
global file_list
global tday_ref, date_ref, date_file_1, tday
global fnum_min, fnum_max
global varnamelist
global F1, var_1_combined
global it, nt, ii1, jj1, int_i, int_j
global lon_rho, lat_rho, mask_rho, lon_u, lat_u, mask_u, lon_v, lat_v, mask_v
global lon_psi, lat_psi, mask_psi, h
global lon_1, lon_2, lat_1, lat_2
global var_1_loaded_from
print "variable 1:\t" , var_1
print "start date:\t" , date_start
print "end date:\t" , date_end
print "lon east:\t" , lon_e
print "lon west:\t" , lon_w
print "lat north:\t" , lat_n
print "lat south:\t" , lat_s
### ROMS time
self.t_date_start = self.yeardayAK(date_start, date_ref, tday_ref)
self.t_date_end = self.yeardayAK(date_end, date_ref, tday_ref)
Tan = []
Tan.append(self.t_date_start * 3600 * 24)
Tan.append(self.t_date_end * 3600 * 24)
### find indices of files to read from
d0 = self.yeardayAK(date_file_1, date_ref, tday_ref)
d1 = self.yeardayAK(date_start , date_ref, tday_ref) - 1
d2 = self.yeardayAK(date_end , date_ref, tday_ref) + 1
fnum1 = max([math.floor((d1 - d0) / 30), fnum_min])
fnum2 = min([math.floor((d2 - d0) / 30), fnum_max])
### Coordinates of view frame
lon_1 = float(lon_w)
lon_2 = float(lon_e)
lat_1 = float(lat_n)
lat_2 = float(lat_s)
### Get variable to plot
valF = str(var_1) # get name of variable to use
var_1_name = str(var_1)
varlist = np.array(varnamelist[valF])
### get netcdf global attributes
nc = Dataset(file_list[0], mode='r')
### get N, the number of levels
for dim in nc.dimensions:
if dim == 's_rho':
N = str(nc.dimensions[dim])
[N for N in N.split() if N.isdigit()] # get '40' from string
N = int(N)
theta_s = getattr(nc, 'theta_s')
theta_b = getattr(nc, 'theta_b')
Tcline = getattr(nc, 'Tcline' )
hc = getattr(nc, 'hc' )
### set attributes for variables
if valF == 'comb_phyto' or valF == 'comb_zoo':
for n in varnamelist:
if n == 'LPHY':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_1_units = varcheck.units
var_1_combined = var_1_name + ' ' + '(' + var_1_units + ')'
elif valF == 'comb_N':
for n in varnamelist:
if n == 'NO3':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_1_units = varcheck.units
var_1_combined = var_1_name + ' ' + '(' + var_1_units + ')'
elif valF == 'comb_Fe':
for n in varnamelist:
if n == 'FeD':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_1_units = varcheck.units
var_1_combined = var_1_name + ' ' + '(' + var_1_units + ')'
else: # non-combined variable
dimid_2 = varnamelist[str(valF)].dimensions[2]
dimid_3 = varnamelist[str(valF)].dimensions[3]
### combine variable name and units for label in plots
var_1_units = varnamelist[str(valF)].units
var_1_combined = var_1_name + ' ' + '(' + var_1_units + ')'
nc.close()
### Use eta_rho, xi_u, eta_v appropriately for coordinates
if dimid_2 == 'eta_rho' and dimid_3 == 'xi_u':
lon_r = lon_u
lat_r = lat_u
if dimid_2 == 'eta_v' and dimid_3 == 'xi_rho':
lon_r = lon_v
lat_r = lat_v
if dimid_2 == 'eta_rho' and dimid_3 == 'xi_rho':
lon_r = lon_rho
lat_r = lat_rho
ii1 = []
jj1 = []
for idx, val in enumerate(lon_r[0, :]):
if val >= lon_1 and val <= lon_2:
ii1.append(idx)
for idx, val in enumerate(lat_r[:, 0]):
if val <= lat_1 and val >= lat_2:
jj1.append(idx)
i1 = ii1[0]
j1 = jj1[0]
nx = len(ii1)
ny = len(jj1)
start_3D = (i1, j1, N)
count_3D = (nx, ny, 1)
print 'start_3D', start_3D
print 'count_3D', count_3D
F1 = 0 # variable with plotting data contained
print var_1, varnamelist[valF]
### squeeze variables
#### start with combined variables
if var_1 == 'comb_phyto':
vartemp = ('SPHY', 'LPHY')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F1 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
elif var_1 == 'comb_zoo':
vartemp = ('SZOO', 'LZOO', 'PZOO')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F1 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
elif var_1 == 'comb_N':
vartemp = ('NO3', 'NH4', 'PON', 'DON')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F1 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
elif var_1 == 'comb_Fe':
vartemp = ('FeD', 'FeSp', 'FeLp')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F1 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
else: # non-combined variable
vartemp = (valF,)
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
F1 = np.squeeze(a[valF])
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
int_i = int(str(re.search('\d+',str(np.shape(ii1))).group())) # get size of ii1 as int
int_j = int(str(re.search('\d+',str(np.shape(jj1))).group())) # get size of jj1 as int
ii1 = np.reshape(ii1, (int_i,1))
jj1 = np.transpose(np.reshape(jj1, (int_j,1)))
F1 = np.transpose(F1)
self.slider.setRange(0, nt - 1)
var_1_loaded_from = 'load_var_1_surf'
# show the first frame
it = 0
def load_var_2_surf(self, date_start, date_end, lon_e, lon_w,
lat_n, lat_s, var_2):
'''Function to load the variable chosen in comboBox 2
'''
global file_list
global tday_ref, date_ref, date_file_1, tday
global fnum_min, fnum_max
global varnamelist, var_2_combined
global F2, zr, nt, var_2_name
global it, nt, ii1, jj1, int_i, int_j
global lon_rho, lat_rho, mask_rho, lon_u, lat_u, mask_u, lon_v, lat_v, mask_v
global lon_psi, lat_psi, mask_psi, h
global lon_1, lon_2, lat_1, lat_2
global var_2_loaded_from
print "\nvariable 2:\t" , var_2
print "start date:\t" , date_start
print "end date:\t" , date_end
print "lon east:\t" , lon_e
print "lon west:\t" , lon_w
print "lat north:\t" , lat_n
print "lat south:\t" , lat_s
### ROMS time
self.t_date_start = self.yeardayAK(date_start, date_ref, tday_ref)
self.t_date_end = self.yeardayAK(date_end, date_ref, tday_ref)
Tan = []
Tan.append(self.t_date_start * 3600 * 24)
Tan.append(self.t_date_end * 3600 * 24)
### find indices of files to read from
d0 = self.yeardayAK(date_file_1, date_ref, tday_ref)
d1 = self.yeardayAK(date_start , date_ref, tday_ref) - 1
d2 = self.yeardayAK(date_end , date_ref, tday_ref) + 1
fnum1 = max([math.floor((d1 - d0) / 30), fnum_min])
fnum2 = min([math.floor((d2 - d0) / 30), fnum_max])
### Coordinates of view frame
lon_1 = float(lon_w)
lon_2 = float(lon_e)
lat_1 = float(lat_n)
lat_2 = float(lat_s)
### Get variable to plot
valF = str(var_2) # get name of variable to use
var_2_name = str(var_2)
varlist = np.array(varnamelist[valF])
### get netcdf global attributes
nc = Dataset(file_list[0], mode='r')
### get N, the number of levels
for dim in nc.dimensions:
if dim == 's_rho':
N = str(nc.dimensions[dim])
[N for N in N.split() if N.isdigit()] # get '40' from string
N = float(N)
theta_s = getattr(nc, 'theta_s')
theta_b = getattr(nc, 'theta_b')
Tcline = getattr(nc, 'Tcline' )
hc = getattr(nc, 'hc' )
### set attributes for variables
if valF == 'comb_phyto' or valF == 'comb_zoo':
for n in varnamelist:
if n == 'LPHY':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_2_units = varcheck.units
var_2_combined = var_2_name + ' ' + '(' + var_2_units + ')'
elif valF == 'comb_N':
for n in varnamelist:
if n == 'NO3':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_2_units = varcheck.units
var_2_combined = var_2_name + ' ' + '(' + var_2_units + ')'
elif valF == 'comb_Fe':
for n in varnamelist:
if n == 'FeD':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_2_units = varcheck.units
var_2_combined = var_2_name + ' ' + '(' + var_2_units + ')'
else: # non-combined variable
dimid_2 = varnamelist[str(valF)].dimensions[2]
dimid_3 = varnamelist[str(valF)].dimensions[3]
### combine variable name and units for label in plots
var_2_units = varnamelist[str(valF)].units
var_2_combined = var_2_name + ' ' + '(' + var_2_units + ')'
nc.close()
### Use eta_rho, xi_u, eta_v appropriately for coordinates
if dimid_2 == 'eta_rho' and dimid_3 == 'xi_u':
lon_r = lon_u
lat_r = lat_u
if dimid_2 == 'eta_v' and dimid_3 == 'xi_rho':
lon_r = lon_v
lat_r = lat_v
if dimid_2 == 'eta_rho' and dimid_3 == 'xi_rho':
lon_r = lon_rho
lat_r = lat_rho
ii1 = []
jj1 = []
for idx, val in enumerate(lon_r[0, :]):
if val >= lon_1 and val <= lon_2:
ii1.append(idx)
for idx, val in enumerate(lat_r[:, 0]):
if val <= lat_1 and val >= lat_2:
jj1.append(idx)
i1 = ii1[0]
j1 = jj1[0]
nx = len(ii1)
ny = len(jj1)
start_3D = (i1, j1, int(N))
count_3D = (nx, ny, 1)
print 'start_3D', start_3D
print 'count_3D', count_3D
F2 = 0 # variable to contain plotting data
print var_2, varnamelist[valF]
### squeeze variables
#### start with combined variables
if var_2 == 'comb_phyto':
vartemp = ('SPHY', 'LPHY')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F2 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
elif var_2 == 'comb_zoo':
vartemp = ('SZOO', 'LZOO', 'PZOO')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F2 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
elif var_2 == 'comb_N':
vartemp = ('NO3', 'NH4', 'PON', 'DON')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F2 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
elif var_2 == 'comb_Fe':
vartemp = ('FeD', 'FeSp', 'FeLp')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F2 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
else: # non-combined variable
vartemp = (valF,)
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
F2 = np.squeeze(a[valF])
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
int_i = int(str(re.search('\d+',str(np.shape(ii1))).group())) # get size of ii1 as int
int_j = int(str(re.search('\d+',str(np.shape(jj1))).group())) # get size of jj1 as int
ii1 = np.reshape(ii1, (int_i,1))
jj1 = np.transpose(np.reshape(jj1, (int_j,1)))
F2 = np.transpose(F2)
var_2_loaded_from = 'load_var_2_surf'
self.slider.setRange(0, nt - 1)
### show the first frame
it = 0
def load_var_1_depth(self, date_start, date_end, lon_e, lon_w,
lat_n, lat_s, var_1):
'''Function to load the variable chosen in comboBox 1
'''
global file_list
global tday_ref, date_ref, date_file_1, tday
global fnum_min, fnum_max
global varnamelist
global F1, var_1_combined
global it, nt, ii1, jj1, int_i, int_j
global lon_rho, lat_rho, mask_rho, lon_u, lat_u, mask_u, lon_v, lat_v, mask_v
global lon_psi, lat_psi, mask_psi, h
global lon_1, lon_2, lat_1, lat_2
global var_1_loaded_from
print "variable 1:\t" , var_1
print "start date:\t" , date_start
print "end date:\t" , date_end
print "lon east:\t" , lon_e
print "lon west:\t" , lon_w
print "lat north:\t" , lat_n
print "lat south:\t" , lat_s
### ROMS time
self.t_date_start = self.yeardayAK(date_start, date_ref, tday_ref)
self.t_date_end = self.yeardayAK(date_end, date_ref, tday_ref)
Tan = []
Tan.append(self.t_date_start * 3600 * 24)
Tan.append(self.t_date_end * 3600 * 24)
### find indices of files to read from
d0 = self.yeardayAK(date_file_1, date_ref, tday_ref)
d1 = self.yeardayAK(date_start , date_ref, tday_ref) - 1
d2 = self.yeardayAK(date_end , date_ref, tday_ref) + 1
fnum1 = max([math.floor((d1 - d0) / 30), fnum_min])
fnum2 = min([math.floor((d2 - d0) / 30), fnum_max])
### Coordinates of view frame
lon_1 = float(lon_w)
lon_2 = float(lon_e)
lat_1 = float(lat_n)
lat_2 = float(lat_s)
### Get variable to plot
valF = str(var_1) # get name of variable to use
var_1_name = str(var_1)
varlist = np.array(varnamelist[valF])
### get netcdf global attributes
nc = Dataset(file_list[0], mode='r')
### get N, the number of levels
for dim in nc.dimensions:
if dim == 's_rho':
N = str(nc.dimensions[dim])
[N for N in N.split() if N.isdigit()] # get '40' from string
N = int(N)
theta_s = getattr(nc, 'theta_s')
theta_b = getattr(nc, 'theta_b')
Tcline = getattr(nc, 'Tcline' )
hc = getattr(nc, 'hc' )
### set attributes for variables
if valF == 'comb_phyto' or valF == 'comb_zoo':
for n in varnamelist:
if n == 'LPHY':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_1_units = varcheck.units
var_1_combined = var_1_name + ' ' + '(' + var_1_units + ')'
elif valF == 'comb_N':
for n in varnamelist:
if n == 'NO3':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_1_units = varcheck.units
var_1_combined = var_1_name + ' ' + '(' + var_1_units + ')'
elif valF == 'comb_Fe':
for n in varnamelist:
if n == 'FeD':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_1_units = varcheck.units
var_1_combined = var_1_name + ' ' + '(' + var_1_units + ')'
else: # non-combined variable
dimid_2 = varnamelist[str(valF)].dimensions[2]
dimid_3 = varnamelist[str(valF)].dimensions[3]
### combine variable name and units for label in plots
var_1_units = varnamelist[str(valF)].units
var_1_combined = var_1_name + ' ' + '(' + var_1_units + ')'
nc.close()
### Use eta_rho, xi_u, eta_v appropriately for coordinates
if dimid_2 == 'eta_rho' and dimid_3 == 'xi_u':
lon_r = lon_u
lat_r = lat_u
if dimid_2 == 'eta_v' and dimid_3 == 'xi_rho':
lon_r = lon_v
lat_r = lat_v
if dimid_2 == 'eta_rho' and dimid_3 == 'xi_rho':
lon_r = lon_rho
lat_r = lat_rho
ii1 = []
jj1 = []
for idx, val in enumerate(lon_r[0, :]):
if val >= lon_1 and val <= lon_2:
ii1.append(idx)
for idx, val in enumerate(lat_r[:, 0]):
if val <= lat_1 and val >= lat_2:
jj1.append(idx)
i1 = ii1[0]
j1 = jj1[0]
nx = len(ii1)
ny = len(jj1)
# start_3D = (i1, j1, N)
# count_3D = (nx, ny, 1)
start_3D = (i1, j1, 1)
count_3D = (nx, ny, N)
print 'start_3D', start_3D
print 'count_3D', count_3D
int_i = int(str(re.search('\d+',str(np.shape(ii1))).group())) # get size of ii1 as int
int_j = int(str(re.search('\d+',str(np.shape(jj1))).group())) # get size of jj1 as int
ii1 = np.reshape(ii1, (int_i,1))
jj1 = np.transpose(np.reshape(jj1, (int_j,1)))
### set depth variable zr
vartemp = ('zeta',)
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
zeta1 = a['zeta']
zeta1 = np.transpose(zeta1)
Vst = 1
Vtr = 1
for i in range(int(nt)):
ssh = np.squeeze(zeta1[:,:,i])
zr = self.set_depth_(Vtr, Vst, theta_s, theta_b, hc, N, 1, h[jj1,ii1], ssh, 0)
F1 = 0 # variable with plotting data contained
print var_1, varnamelist[valF]
### squeeze variables
#### start with combined variables
if var_1 == 'comb_phyto':
vartemp = ('SPHY', 'LPHY')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F1 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
elif var_1 == 'comb_zoo':
vartemp = ('SZOO', 'LZOO', 'PZOO')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F1 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
elif var_1 == 'comb_N':
vartemp = ('NO3', 'NH4', 'PON', 'DON')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F1 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
elif var_1 == 'comb_Fe':
vartemp = ('FeD', 'FeSp', 'FeLp')
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
for var in a:
Ftemp = np.squeeze(a[var])
F1 += Ftemp
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
else: # non-combined variable
vartemp = (valF,)
scrum_time, a = self.read_his_fastAK(fnum1, fnum2, vartemp,
start_3D, count_3D, Tan)
F1 = np.squeeze(a[valF])
nt = len(scrum_time)
tday = scrum_time / 24 / 3600
F1 = np.transpose(F1)
var_1_loaded_from = 'load_var_1_depth'
self.slider.setRange(0, nt - 1)
# show the first frame
it = 0
def load_var_2_depth(self, date_start, date_end, lon_e, lon_w,
lat_n, lat_s, var_2):
'''Function to load the variable chosen in comboBox 2
'''
global file_list
global tday_ref, date_ref, date_file_1, tday
global fnum_min, fnum_max
global varnamelist, var_2_combined
global F2, zr, nt, var_2_name
global it, nt, ii1, jj1, int_i, int_j
global lon_rho, lat_rho, mask_rho, lon_u, lat_u, mask_u, lon_v, lat_v, mask_v
global lon_psi, lat_psi, mask_psi, h
global lon_1, lon_2, lat_1, lat_2
global var_2_loaded_from
print "\nvariable 2:\t" , var_2
print "start date:\t" , date_start
print "end date:\t" , date_end
print "lon east:\t" , lon_e
print "lon west:\t" , lon_w
print "lat north:\t" , lat_n
print "lat south:\t" , lat_s
### ROMS time
self.t_date_start = self.yeardayAK(date_start, date_ref, tday_ref)
self.t_date_end = self.yeardayAK(date_end, date_ref, tday_ref)
Tan = []
Tan.append(self.t_date_start * 3600 * 24)
Tan.append(self.t_date_end * 3600 * 24)
### find indices of files to read from
d0 = self.yeardayAK(date_file_1, date_ref, tday_ref)
d1 = self.yeardayAK(date_start , date_ref, tday_ref) - 1
d2 = self.yeardayAK(date_end , date_ref, tday_ref) + 1
fnum1 = max([math.floor((d1 - d0) / 30), fnum_min])
fnum2 = min([math.floor((d2 - d0) / 30), fnum_max])
### Coordinates of view frame
lon_1 = float(lon_w)
lon_2 = float(lon_e)
lat_1 = float(lat_n)
lat_2 = float(lat_s)
### Get variable to plot
valF = str(var_2) # get name of variable to use
var_2_name = str(var_2)
varlist = np.array(varnamelist[valF])
### get netcdf global attributes
nc = Dataset(file_list[0], mode='r')
### get N, the number of levels
for dim in nc.dimensions:
if dim == 's_rho':
N = str(nc.dimensions[dim])
[N for N in N.split() if N.isdigit()] # get '40' from string
N = float(N)
theta_s = getattr(nc, 'theta_s')
theta_b = getattr(nc, 'theta_b')
Tcline = getattr(nc, 'Tcline' )
hc = getattr(nc, 'hc' )
### set attributes for variables
if valF == 'comb_phyto' or valF == 'comb_zoo':
for n in varnamelist:
if n == 'LPHY':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_2_units = varcheck.units
var_2_combined = var_2_name + ' ' + '(' + var_2_units + ')'
elif valF == 'comb_N':
for n in varnamelist:
if n == 'NO3':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_2_units = varcheck.units
var_2_combined = var_2_name + ' ' + '(' + var_2_units + ')'
elif valF == 'comb_Fe':
for n in varnamelist:
if n == 'FeD':
varcheck = varnamelist[n]
dimid_2 = varcheck.dimensions[2]
dimid_3 = varcheck.dimensions[3]
### combine variable name and units for label in plots
var_2_units = varcheck.units
var_2_combined = var_2_name + ' ' + '(' + var_2_units + ')'
else: # non-combined variable
dimid_2 = varnamelist[str(valF)].dimensions[2]
dimid_3 = varnamelist[str(valF)].dimensions[3]
### combine variable name and units for label in plots
var_2_units = varnamelist[str(valF)].units
var_2_combined = var_2_name + ' ' + '(' + var_2_units + ')'
nc.close()
### Use eta_rho, xi_u, eta_v appropriately for coordinates
if dimid_2 == 'eta_rho' and dimid_3 == 'xi_u':
lon_r = lon_u
lat_r = lat_u
if dimid_2 == 'eta_v' and dimid_3 == 'xi_rho':
lon_r = lon_v
lat_r = lat_v
if dimid_2 == 'eta_rho' and dimid_3 == 'xi_rho':
lon_r = lon_rho
lat_r = lat_rho
ii1 = []
jj1 = []
for idx, val in enumerate(lon_r[0, :]):
if val >= lon_1 and val <= lon_2:
ii1.append(idx)
for idx, val in enumerate(lat_r[:, 0]):
if val <= lat_1 and val >= lat_2: