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Commit e613f4b5 authored by jacques Grelet's avatar jacques Grelet
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Merge branch 'master' of /m/git/pirata

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docs/Readme-Python.txt
+ 29
− 2
View file @ e613f4b5
......@@ -13,7 +13,31 @@ L[:-1]
[1, 2, 3]
L[::-1]
[4, 3, 2, 1]
L.method() avec method = append, sort,index,reverse
L.method() avec method = append, sort,index,reverse, extend
We see that extend() is semantically clearer, and that it can run much faster than append(),
when you intend to append each element in an iterable to a list.
If you only have a single element (not in an iterable) to add to the list, use append.
The following two snippets are semantically equivalent:
for item in iterator:
a_list.append(item)
and
a_list.extend(iterator)
The latter may be faster as the loop is implemented in C.
List comprehensions:
------------------------------------------
new_list = [expression for_loop_one_or_more condtions]
numbers = [1, 2, 3, 4]
squares = [n**2 for n in numbers]
print(squares) # Output: [1, 4, 9, 16]
list_a = [1, 2, 3]
square_cube_list = [ [a**2, a**3] for a in list_a]
print(square_cube_list) # Output: [[1, 1], [4, 8], [9, 27]]
Tuples:
-------
......@@ -527,6 +551,9 @@ Successfully installed basemap-1.1.0 pyproj-2.1.2 pyshp-2.1.0
Pour utiliser QT au lieu de Tk
> pip install PySimpleGUIQt
> pip install PySide2
> pip install PyAstronomy
> pip install sciPy
> pip install basemap
Puis remplacer le :
import PySimpleGUI as gs
......@@ -589,4 +616,4 @@ From https://github.com/jgrelet/oceano2python
Merge made by the 'recursive' strategy.
README.md | 2 ++
1 file changed, 2 insertions(+)
create mode 100644 README.md
\ No newline at end of file
create mode 100644 README.md
example/hoff_muller_diagram.py 0 → 100644
+ 69
− 0
View file @ e613f4b5
import netCDF4 as nc
from netCDF4 import Dataset
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as dplt
from pylab import *
import os, sys
mask =
Dataset('/ccc/scratch/cont005/legos/nivertfl/VALIDATION_F01/INPUT_SAISON/HOFF-MULLER/total.nc',
mode='r')
trop =
Dataset('/ccc/scratch/cont005/legos/nivertfl/VALIDATION_F01/INPUT_SAISON/HOFF-MULLER/sst_tropflux_1d_2000-regrid.nc',
mode='r')
mask1 = mask.variables['votemper'][:,0,:,:]
trop1 = trop.variables['sst'][:,:,:]
zbla=np.zeros(shape=(301,1))
zblo=np.zeros(shape=(301,1))
zbla2=np.zeros(shape=(301,366))
zblo2=np.zeros(shape=(301,366))
time = mask.variables['time_counter'][:]
lon = mask.variables['nav_lon'][0,:]
mask1[mask1 == 0] = np.NaN
for y in range(0,365):
for x in range(0,300):
result1= np.nanmean(mask1[y,78:86,x])
zbla[x,:]=result1
zbla3=np.squeeze(zbla)
zbla2[:,y]=zbla3
zbla2=transpose(zbla2)
for y in range(0,365):
for x in range(0,300):
result2= np.nanmean(trop1[y,78:86,x])
zblo[x,:]=result2
zblo3=np.squeeze(zblo)
zblo2[:,y]=zblo3
zblo2=transpose(zblo2)
plt.clf()
units=mask.variables['time_counter'].units
from datetime import datetime
buf=mask.variables['time_centered'][:];
time=list()
time.extend(buf.tolist())
dates=nc.num2date(time,units,'gregorian').tolist()
nt=len(dates)
im1 = plt.figure(figsize=(6, 18))
im1 = plt.contourf(lon,dates,zbla2, np.linspace(23,30,21),
extend='both', cmap=cm.RdBu_r)
plt.colorbar(im1,orientation='horizontal')
im1 = plt.title("Modele annee 2000")
plt.savefig('modele2000.png')
plt.clf()
im2 = plt.figure(figsize=(6, 18))
im2 = plt.contourf(lon,dates,zblo2, np.linspace(23,30,21),
extend='both', cmap=cm.RdBu_r)
plt.colorbar(im2,orientation='horizontal')
im2 = plt.title("TropFlux annee 2000")
plt.savefig('obs2000.png')
example/various_modelisation_plot.py 0 → 100644
+ 300
− 0
View file @ e613f4b5
from netCDF4 import Dataset
import numpy as np
import matplotlib.pyplot as plt
from pylab import *
file1 =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/grid_T_saison.nc'
file2 =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/grid_U_saison.nc'
file3 =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/grid_V_saison.nc'
file4 =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/MYWRF3D_regrid-saison.nc'
trop1 =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/sst_tropflux_1d_2000-regrid-saison.nc'
trop2 =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/taux_tropflux_1d_2000-regrid-saison.nc'
trop3 =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/tauy_tropflux_1d_2000-regrid-saison.nc'
trop4 =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/swr_tropflux_1d_2000-regrid-saison.nc'
trop5 =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/lwr_tropflux_1d_2000-regrid-saison.nc'
pluie1 =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/precip-2000-regrid-saison.nc'
meshmask =
'/ccc/scratch/cont005/legos/nivertfl/TEST_VALIDATION_TROPFLUX/MOYENNE-SAISON/mesh_mask.nc'
mask = Dataset(file1, mode='r')
masku = Dataset(file2, mode='r')
maskv = Dataset(file3, mode='r')
wrf = Dataset(file4, mode='r')
pluie = Dataset(pluie1, mode='r')
meshmask1 = Dataset(meshmask, mode='r')
tropsst= Dataset(trop1, mode='r')
troptaux= Dataset(trop2, mode='r')
troptauy= Dataset(trop3, mode='r')
tropswr= Dataset(trop4, mode='r')
troplwr= Dataset(trop5, mode='r')
lat = mask.variables['nav_lat'][:]
lon = mask.variables['nav_lon'][:]
lat1 = mask.variables['nav_lat'][:,0]
meshmask2 = meshmask1.variables['tmask'][:,0,:,:]
mask1 = mask.variables['votemper'][:,0,:,:]
mask11 = tropsst.variables['sst'][:,:,:]
vari2 = mask.variables['qsr'][:,:,:]
vari22 = tropswr.variables['swr'][:,:,:]
vari31 = wrf.variables['RAIN'][:,:,:]
vari3 = vari31[:,:,:] * 40 * 24
vari33 = pluie.variables['precipitation'][:,:,:]
vari4 = masku.variables['utau'][:,:,:]
vari44 = troptaux.variables['taux'][:,:,:]
vari51 = wrf.variables['GLW'][:,:,:]
vari5 = vari51[:,:,:] * meshmask2[:,:,:]
vari555 = troplwr.variables['lwr'][:,:,:]
mask112 = mask11[:,:,:] + 273.15
vari55 = vari555[:,:,:] +
5.67e-8*(mask112[:,:,:])*(mask112[:,:,:])*(mask112[:,:,:])*(mask112[:,:,:])
vari6 = maskv.variables['vtau'][:,:,:]
vari6[vari6 == 0] = np.NaN
vari66 = troptauy.variables['tauy'][:,:,:]
list1 = ['JFM' , 'AMJ' , 'JAS' , 'OND']
'''Difference modele'''
for x in range(0,4):
print "We're on time %d" % (x)
plt.clf()
result1 = mask1[x,:,:] - mask11[x,:,:]
result2 = vari2[x,:,:] - vari22[x,:,:]
result3 = vari3[x,:,:] - vari33[x,:,:]
result4 = vari4[x,:,:] - vari44[x,:,:]
result5 = vari5[x,:,:] - vari55[x,:,:]
result6 = vari6[x,:,:] - vari66[x,:,:]
fig, cs = plt.subplots(3, 2, figsize=(9, 6))
fig.subplots_adjust(left=0.125, bottom=0.1, right=0.9, top=0.9,
wspace=0.3, hspace=0.3)
im1 = cs[0, 0].contourf(lon,lat,result1, np.linspace(-2.5,2.5,21),
extend='both', cmap=cm.RdBu_r)
cs[0, 0].set_title('Difference VOTEMPER MODELE - OBS Saison ' +
list1[x],fontsize=10)
fig.colorbar(im1, ax=cs[0, 0], orientation='horizontal')
im2 = cs[0, 1].contourf(lon,lat,result2, np.linspace(-100,100,21),
extend='both', cmap=cm.RdBu_r)
cs[0, 1].set_title('Difference QSR MODELE - OBS Saison ' +
list1[x],fontsize=10)
fig.colorbar(im2, ax=cs[0, 1], orientation='horizontal')
im3 = cs[1, 0].contourf(lon,lat,result3, np.linspace(-16,16,21),
extend='both', cmap=cm.RdBu_r)
cs[1, 0].set_title('Difference PRECIP MODELE - OBS Saison ' +
list1[x],fontsize=10)
fig.colorbar(im3, ax=cs[1, 0], orientation='horizontal')
im4 = cs[1, 1].contourf(lon,lat,result4, np.linspace(-0.1,0.1,21),
extend='both', cmap=cm.RdBu_r)
cs[1, 1].set_title('Difference U TAU MODELE - OBS Saison ' +
list1[x],fontsize=10)
fig.colorbar(im4, ax=cs[1, 1], orientation='horizontal', format='%.0e')
im5 = cs[2, 0].contourf(lon,lat,result5, np.linspace(-50,50,21),
extend='both', cmap=cm.RdBu_r)
cs[2, 0].set_title('Difference LW MODELE - OBS Saison ' +
list1[x],fontsize=10)
fig.colorbar(im5, ax=cs[2, 0], orientation='horizontal')
im6 = cs[2, 1].contourf(lon,lat,result6, np.linspace(-0.1,0.1,21),
extend='both', cmap=cm.RdBu_r)
cs[2, 1].set_title('Difference V TAU MODELE - OBS Saison ' +
list1[x],fontsize=10)
fig.colorbar(im6, ax=cs[2, 1], orientation='horizontal')
plt.savefig('all_var_diff_saison_' + list1[x] + '.png')
'''plot modele'''
for x in range(0,4):
print "We're on time %d" % (x)
plt.clf()
result1 = mask1[x,:,:]
result2 = vari2[x,:,:]
result3 = vari3[x,:,:]
result4 = vari4[x,:,:]
result5 = vari5[x,:,:]
result6 = vari6[x,:,:]
fig, cs = plt.subplots(3, 2, figsize=(9, 6))
fig.subplots_adjust(left=0.125, bottom=0.1, right=0.9, top=0.9,
wspace=0.3, hspace=0.3)
im1 = cs[0, 0].contourf(lon,lat,result1, np.linspace(20,30,21),
extend='both', cmap=cm.jet)
cs[0, 0].set_title('VOTEMPER MODELE Saison ' + list1[x],fontsize=10)
fig.colorbar(im1, ax=cs[0, 0], orientation='horizontal')
im2 = cs[0, 1].contourf(lon,lat,result2, np.linspace(100,380,15),
extend='both', cmap=cm.jet)
cs[0, 1].set_title('QSR MODELE Saison ' + list1[x],fontsize=10)
fig.colorbar(im2, ax=cs[0, 1], orientation='horizontal')
im3 = cs[1, 0].contourf(lon,lat,result3, np.linspace(0,20,21),
extend='both', cmap=cm.jet)
cs[1, 0].set_title('PRECIP MODELE Saison ' + list1[x],fontsize=10)
fig.colorbar(im3, ax=cs[1, 0], orientation='horizontal')
im4 = cs[1, 1].contourf(lon,lat,result4,
np.linspace(-0.13,0.05,21), extend='both', cmap=cm.jet)
cs[1, 1].set_title('U TAU MODELE Saison ' + list1[x],fontsize=10)
fig.colorbar(im4, ax=cs[1, 1], orientation='horizontal', format='%.0e')
im5 = cs[2, 0].contourf(lon,lat,result5, np.linspace(300,460,21),
extend='both', cmap=cm.jet)
cs[2, 0].set_title('GLW MODELE Saison ' + list1[x],fontsize=10)
fig.colorbar(im5, ax=cs[2, 0], orientation='horizontal')
im6 = cs[2, 1].contourf(lon,lat,result6,
np.linspace(-0.15,0.13,21), extend='both', cmap=cm.jet)
cs[2, 1].set_title('V TAU MODELE Saison ' + list1[x],fontsize=10)
fig.colorbar(im6, ax=cs[2, 1], orientation='horizontal')
plt.savefig('all_var_modele_saison_' + list1[x] + '.png')
'''plot obs Trop et TRMM'''
for x in range(0,4):
print "We're on time %d" % (x)
plt.clf()
result1 = mask11[x,:,:]
result2 = vari22[x,:,:]
result3 = vari33[x,:,:]
result4 = vari44[x,:,:]
result5 = vari55[x,:,:]
result6 = vari66[x,:,:]
fig, cs = plt.subplots(3, 2, figsize=(9, 6))
fig.subplots_adjust(left=0.125, bottom=0.1, right=0.9, top=0.9,
wspace=0.3, hspace=0.3)
im1 = cs[0, 0].contourf(lon,lat,result1, np.linspace(20,30,21),
extend='both', cmap=cm.jet)
cs[0, 0].set_title('VOTEMPER OBS Saison ' + list1[x],fontsize=10)
fig.colorbar(im1, ax=cs[0, 0], orientation='horizontal')
im2 = cs[0, 1].contourf(lon,lat,result2, np.linspace(100,380,15),
extend='both', cmap=cm.jet)
cs[0, 1].set_title('QSR OBS Saison ' + list1[x],fontsize=10)
fig.colorbar(im2, ax=cs[0, 1], orientation='horizontal')
im3 = cs[1, 0].contourf(lon,lat,result3, np.linspace(0,20,21),
extend='both', cmap=cm.jet)
cs[1, 0].set_title('PRECIP OBS Saison ' + list1[x],fontsize=10)
fig.colorbar(im3, ax=cs[1, 0], orientation='horizontal')
im4 = cs[1, 1].contourf(lon,lat,result4,
np.linspace(-0.13,0.05,21), extend='both', cmap=cm.jet)
cs[1, 1].set_title('U TAU OBS Saison ' + list1[x],fontsize=10)
fig.colorbar(im4, ax=cs[1, 1], orientation='horizontal', format='%.0e')
im5 = cs[2, 0].contourf(lon,lat,result5, np.linspace(300,460,21),
extend='both', cmap=cm.jet)
cs[2, 0].set_title('LW OBS Saison ' + list1[x],fontsize=10)
fig.colorbar(im5, ax=cs[2, 0], orientation='horizontal')
im6 = cs[2, 1].contourf(lon,lat,result6,
np.linspace(-0.15,0.13,21), extend='both', cmap=cm.jet)
cs[2, 1].set_title('V TAU OBS Saison ' + list1[x],fontsize=10)
fig.colorbar(im6, ax=cs[2, 1], orientation='horizontal')
plt.savefig('all_var_obs_saison_' + list1[x] + '.png')
zbla=np.zeros(shape=(165,1))
zbla2=np.zeros(shape=(165,1))
zbla3=np.zeros(shape=(165,1))
zbla4=np.zeros(shape=(165,1))
zbla5=np.zeros(shape=(165,1))
zbla6=np.zeros(shape=(165,1))
zbla7=np.zeros(shape=(165,1))
zbla8=np.zeros(shape=(165,1))
zbla9=np.zeros(shape=(165,1))
zbla10=np.zeros(shape=(165,1))
zbla11=np.zeros(shape=(165,1))
zbla12=np.zeros(shape=(165,1))
mask1[mask1 == 0] = np.NaN
vari2[vari2 == 0] = np.NaN
vari4[vari4 == 0] = np.NaN
vari5[vari5 == 0] = np.NaN
'''Coupe zonale'''
for y in range(0,4):
print "We're on time %d" % (y)
for x in range(0,165):
result1= np.nanmean(mask1[y,x,80:160])
result2= np.nanmean(mask11[y,x,80:160])
zbla[x,:]=result1
zbla2[x,:]=result2
for z in range(0,165):
result3= np.nanmean(vari2[y,z,80:160])
result4= np.nanmean(vari22[y,z,80:160])
zbla3[z,:]=result3
zbla4[z,:]=result4
for ii in range(0,165):
result5= np.nanmean(vari3[y,ii,80:160])
result6= np.nanmean(vari33[y,ii,80:160])
zbla5[ii,:]=result5
zbla6[ii,:]=result6
for jj in range(0,165):
result7= np.nanmean(vari4[y,jj,80:160])
result8= np.nanmean(vari44[y,jj,80:160])
zbla7[jj,:]=result7
zbla8[jj,:]=result8
for zz in range(0,165):
result9= np.nanmean(vari5[y,zz,80:160])
result10= np.nanmean(vari55[y,zz,80:160])
zbla9[zz,:]=result9
zbla10[zz,:]=result10
for hh in range(0,165):
result11= np.nanmean(vari6[y,hh,80:160])
result12= np.nanmean(vari66[y,hh,80:160])
zbla11[hh,:]=result11
zbla12[hh,:]=result12
fig, cs = plt.subplots(3, 2, figsize=(9, 6))
fig.subplots_adjust(left=0.125, bottom=0.1, right=0.9, top=0.9,
wspace=0.3, hspace=0.3)
im1 = cs[0, 0].plot(lat1,zbla)
im1 = cs[0, 0].plot(lat1,zbla2)
cs[0, 0].set_title('Comparaison SST MODELE et OBS Saison ' +
list1[y],fontsize=10)
cs[0, 0].set_ylim([18,30])
cs[0, 0].set_xlim([-20,20])
im2 = cs[0, 1].plot(lat1,zbla3)
im2 = cs[0, 1].plot(lat1,zbla4)
cs[0, 1].set_title('Comparaison QSR MODELE et OBS Saison ' +
list1[y],fontsize=10)
cs[0, 1].set_ylim([100,380])
cs[0, 1].set_xlim([-20,20])
im3 = cs[1, 0].plot(lat1,zbla5)
im3 = cs[1, 0].plot(lat1,zbla6)
cs[1, 0].set_title('Comparaison PRECIP MODELE et OBS Saison ' +
list1[y],fontsize=10)
cs[1, 0].set_ylim([0, 20])
cs[1, 0].set_xlim([-20,20])
im4 = cs[1, 1].plot(lat1,zbla7)
im4 = cs[1, 1].plot(lat1,zbla8)
cs[1, 1].set_title('Comparaison U TAU MODELE et OBS Saison ' +
list1[y],fontsize=10)
cs[1, 1].set_ylim([-0.13,0.05])
cs[1, 1].set_xlim([-20,20])
im5 = cs[2, 0].plot(lat1,zbla9)
im5 = cs[2, 0].plot(lat1,zbla10)
cs[2, 0].set_title('Comparaison LW MODELE et OBS Saison ' +
list1[y],fontsize=10)
cs[2, 0].set_ylim([300,430])
cs[2, 0].set_xlim([-20,20])
im6 = cs[2, 1].plot(lat1,zbla11)
im6 = cs[2, 1].plot(lat1,zbla12)
cs[2, 1].set_title('Comparaison V TAU MODELE et OBS Saison ' +
list1[y],fontsize=10)
cs[2, 1].set_ylim([-0.15,0.13])
cs[2, 1].set_xlim([-20,20])
plt.savefig('coupe_zonale_saison_' + list1[y] + '.png')
oceano.py
+ 96
− 39
View file @ e613f4b5
import argparse
import sys
import myPySimpleGUI as sg
# import PySimpleGUIQt as sg
# import myPySimpleGUI as sg
import PySimpleGUI as sg
import toml
import logging
from file_extractor import FileExtractor
......@@ -14,6 +14,8 @@ import distutils.util as du
typeInstrument = {'CTD': ('cnv', 'CNV'), 'XBT': (
'EDF', 'edf'), 'LADCP': ('lad', 'LAD'), 'TSG': 'COLCOR'}
ti = typeInstrument # an alias
filesBrowsePosition_row = 2
filesBrowsePosition_column = 1
def processArgs():
......@@ -22,45 +24,62 @@ def processArgs():
following ROSCOP codification at the given column, fill arrays, write header file ',
usage='\npython oceano.py data/CTD/cnv/dfr2900[1-3].cnv -i CTD -d\n'
'python oceano.py data/CTD/cnv/dfr2900[1-3].cnv -i CTD -k PRES TEMP PSAL DOX2 DENS\n'
'python oceano.py data/CTDcnv/dfr29*.cnv -d\n'
'python oceano.py data/CTDcnv/dfr29*.cnv -i CTD -d\n'
'python oceano.py data/XBT/T7_0000*.EDF -i XBT -k DEPTH TEMP SVEL\n'
"python oceano.py data/LADCP/*.lad -i LADCP -k DEPTH EWCT NSCT",
'python oceano.py data/LADCP/*.lad - i LADCP - k DEPTH EWCT NSCT\n'
' \n',
epilog='J. Grelet IRD US191 - March 2019')
parser.add_argument('-d', '--debug', help='display debug informations',
action='store_true')
parser.add_argument('--demo', nargs='?', default='CTD',
help='specify the commande line for instrument, eg CTD, XBT, TSG, LADCP (default: %(default)s)')
parser.add_argument('--demo', nargs='?', choices=ti.keys(),
help='specify the commande line for instrument, eg CTD, XBT, TSG, LADCP')
parser.add_argument('-c', '--config', help="toml configuration file, (default: %(default)s)",
default='tests/test.toml')
parser.add_argument('-i', '--instrument', nargs='?', default='CTD',
help='specify the instrument that produce files, eg CTD, XBT, TSG, LADCP (default: %(default)s)')
parser.add_argument('-i', '--instrument', nargs='?', choices=ti.keys(),
help='specify the instrument that produce files, eg CTD, XBT, TSG, LADCP')
parser.add_argument('-k', '--key', nargs='+', default=['PRES', 'TEMP', 'PSAL'],
help='display dictionary for key(s), (default: %(default)s)')
parser.add_argument('-g', '--gui', action='store_true',
help='use GUI interface')
parser.add_argument('files', nargs='*',
help='cnv file(s) to parse, (default: data/cnv/dfr29*.cnv)')
parser.add_argument('files', nargs='*', type=argparse.FileType('r', encoding='ISO-8859-1'),
help='ASCII file(s) to parse')
return parser
# TODOS:
# DEPTH is missing
# file name is not clear at startup
# if no file selected, don't leave the program
def defineGUI():
# get all devices
devices = list(ti.keys())
# change look and feel color scheme
sg.ChangeLookAndFeel('SandyBeach')
frameLayout = {}
# define a frame layout for each instrument (device)
for d in devices:
keys = cfg['split'][d.lower()].keys()
# List comprehensions
frameLayout[d] = [[sg.Checkbox(k, key=k,
tooltip='Select the extract the physical parameter {}'.format(k))] for k in keys]
# define GUI layout
layout = ([[sg.Text('File(s) to read and convert')],
[sg.Multiline(size=(40, 5), key='_IN_'),
sg.Input(key='_HIDDEN_', visible=False,
layout = ([[sg.Text('File(s) to read and convert')], # row 0
[sg.Multiline(size=(40, 5), key='_IN_'), # row 1, col 0
sg.Input(key='_HIDDEN_', visible=False, # row 1, col 1
enable_events=True),
sg.FilesBrowse(key='_HIDDEN_',
tooltip='Choose one or more files',
initial_folder='data/{}'.format(ti[device][0]))],
[sg.Combo(list(ti.keys()), enable_events=True, size=(8, 1),
sg.FilesBrowse(key='_HIDDEN_', initial_folder=None, # row 1, col 2
tooltip='Choose one or more files')],
[sg.Combo(list(ti.keys()), enable_events=True, size=(8, 1), # row 2
key='_COMBO_', tooltip='Select the instrument')],
* [[sg.Checkbox(k, key=k,
tooltip='Select the extract the physical parameter {}'.format(k))] for k in keys],
[sg.OK(), sg.CloseButton('Cancel')]])
# [sg.CloseButton('Run'), sg.CloseButton('Cancel')]])
[sg.Frame(d, frameLayout[d], key='_FRAME_{:s}'.format(d) , visible=True) # row 3
for d in devices],
[sg.OK(), sg.CloseButton('Cancel')]]) # row 4
# [sg.CloseButton('Run'), sg.CloseButton('Cancel')]])
# create a local instance windows used to reload the saved config from file
window = sg.Window('Oceano converter').Layout(layout)
......@@ -69,11 +88,16 @@ def defineGUI():
return window
def updateFilesBrowseCombo(extentions):
e = window.Rows[1][2] # hardcoded
e.FileTypes = [] # init to empty list
def updateFilesBrowseCombo(extentions, x, y):
'''# special function used to update the FilesBrowseCombo with canvas poisition
# instead of key because the same key is assign to shadow input object
'''
e = window.Rows[x][y] # hardcoded
e.FileTypes = [] # init to empty list
for ext in extentions:
e.FileTypes.append(("{} files".format(ext), "*.{}".format(ext)))
e.initial_folder = 'data/{}'.format(extentions[0])
window.Finalize
......@@ -131,8 +155,8 @@ if __name__ == "__main__":
# read config Toml file and get the physical parameter list (Roscop code) for the specified instrument
cfg = toml.load(args.config)
# this the select device from command line !
device = str(args.instrument) # convert one element list to str
keys = cfg['split'][device.lower()].keys()
# test arguements from sys.argv, args is never to None with default option set
if args.gui or len(sys.argv) == 1:
......@@ -140,24 +164,48 @@ if __name__ == "__main__":
# setup the GUI windows Layout
window = defineGUI()
device = window.FindElement('_COMBO_').DefaultValue
updateFilesBrowseCombo(ti[device])
keys = cfg['split'][device.lower()].keys()
# can't update combo with FindElement('_HIDDEN_').Update(), we use this function
# with hardcoded FilesBrowseCombo position
updateFilesBrowseCombo(
ti[device], filesBrowsePosition_column, filesBrowsePosition_row)
# set the rigth frame for device visible, dosn't work
# File "C:\git\python\PySimpleGUI\PySimpleGUI.py", line 2362, in Update
# self.TKFrame.pack()
# AttributeError: 'NoneType' object has no attribute 'pack'
# for d in list(ti.keys()):
# print(d)
# if d == device:
# window.FindElement(
# '_FRAME_{:s}'.format(d)).Update(visible=True)
# main GUI loop
while True:
# display the main windows
event, values = window.Read()
# print(event, values)
print(event, values)
if event is 'Cancel' or event == None:
raise SystemExit("Cancelling: user exit")
if event is 'OK': # end of initialization, process data now
# values['_HIDDEN_'] is a string with files separated by ';' and fileExtractor need a list
files = values['_HIDDEN_'].split(';')
args.files = files
# test if a or more file are selected
if not all(args.files):
sg.Popup("Cancel", "No filename supplied")
# raise SystemExit("Cancelling: no filename supplied")
continue
break
if event is '_COMBO_':
# you have to go into the bowels of the pygi code, to get the instance of the Combo
# by the line and column number of the window to update its "fileType" property.
updateFilesBrowseCombo(ti[values['_COMBO_']])
updateFilesBrowseCombo(
ti[values['_COMBO_']], filesBrowsePosition_column, filesBrowsePosition_row)
# update the Multilines instance from FilesBrowse return
if event is '_HIDDEN_':
......@@ -177,15 +225,6 @@ if __name__ == "__main__":
del new_values[k]
args.key = new_values.keys()
# values['_HIDDEN_'] is a string with files separated by ';' and fileExtractor need a list
files = values['_HIDDEN_'].split(';')
args.files = files
# test if a or more file are selected
if not all(args.files):
sg.Popup("Cancel", "No filename supplied")
raise SystemExit("Cancelling: no filename supplied")
# process of files start here
fe, n, m = process(args, cfg, values['_COMBO_'])
......@@ -200,11 +239,29 @@ if __name__ == "__main__":
# print = sg.Print(size=(80,40))
else:
# demo mode, only in command line
if args.demo != None:
print('demo mode: {}'.format(args.demo))
sys.exit(1)
# test if a or more file are selected
if args.files == []:
print('You need to specify one or more files to process !!!', end='\n\n')
else:
if args.files == []:
print(
'Error, you need to specify one or more files to process !!!', end='\n\n')
parser.print_help(sys.stderr)
sys.exit(1)
else:
files = []
for f in args.files:
files.append(f.name)
args.files = files
if device == 'None':
print(
'Error: missing option -i or --instrument, instrument = {}\n'.format(device))
parser.print_help(sys.stderr)
sys.exit(1)
keys = cfg['split'][device.lower()].keys()
# in command line mode (console)
fe, n, m = process(args, cfg, device)
print("Dimensions: {} x {}".format(m, n))
......
tests/test.toml
+ 7
− 1
View file @ e613f4b5
......@@ -158,4 +158,10 @@ comment = "Extract from .lad files"
[split.ladcp]
DEPTH = 0
EWCT = 1
NSCT = 2
\ No newline at end of file
NSCT = 2
[split.tsg]
DEPTH = 0
SSJT = 1
SSTP = 2
SSPS = 3
\ No newline at end of file
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