diff --git a/inputs/namelist_cmems.bdy b/inputs/namelist_cmems.bdy
index d57ecce8ea03e8bcfd64c4cfc5a43eb144951ce7..2bc9c3aa8818a87126818e53b3019eeb1c742eea 100644
--- a/inputs/namelist_cmems.bdy
+++ b/inputs/namelist_cmems.bdy
@@ -52,7 +52,7 @@
! CMEMS Data Source Configuration
!------------------------------------------------------------------------------
ln_use_cmems = .true.
- ln_download_cmems = .true.
+ ln_download_cmems = .false.
sn_cmems_dir = '/Users/thopri/Projects/PyNEMO/inputs/' ! where to download CMEMS input files (static and variable)
ln_download_static = .false.
ln_subset_static = .false.
@@ -103,7 +103,7 @@
!------------------------------------------------------------------------------
! unstructured open boundaries tidal parameters
!------------------------------------------------------------------------------
- ln_tide = .false. ! =T : produce bdy tidal conditions
+ ln_tide = .true. ! =T : produce bdy tidal conditions
sn_tide_model = 'fes' ! Name of tidal model (fes|tpxo)
clname(1) = 'M2' ! constituent name
clname(2) = 'S2'
diff --git a/pynemo/tide/fes_extract_HC.py b/pynemo/tide/fes_extract_HC.py
index 56508558d3bcef0c73aecca64362c34c2568c3ae..832bdbaab3aefb2d7c272331e3cc03d4cb9afc4c 100644
--- a/pynemo/tide/fes_extract_HC.py
+++ b/pynemo/tide/fes_extract_HC.py
@@ -53,26 +53,20 @@ class HcExtract(object):
lon_resolution = lon_z[1] - lon_z[0]
data_in_km = 0 # added to maintain the reference to matlab tmd code
- # extract example amplitude grid for Z, U and V and change NaNs to 0 (for land) and other values to 1 (for water)
- mask_z = np.array(np.rot90(Dataset(settings['tide_fes']+constituents[0]+'_Z.nc').variables['amplitude'][:]))
- where_are_NaNs = np.isnan(mask_z)
- where_no_NaNs = np.invert(np.isnan(mask_z))
- mask_z[where_no_NaNs] = 1
- mask_z[where_are_NaNs] = 0
+ # extract example amplitude grid for Z, U and V and change NaNs to 1 (for land) and other values to 0 (for water)
+ mask_z = np.ma.MaskedArray.filled(np.flipud(np.rot90(Dataset(settings['tide_fes']+constituents[0]+'_Z.nc').variables['amplitude'][:])))
+ mask_z[mask_z == 18446744073709551616.00000] = 0
+ mask_z[mask_z != 0] = 1
self.mask_dataset[mz_name] = mask_z
- mask_u = np.array(np.rot90(Dataset(settings['tide_fes']+constituents[0]+'_U.nc').variables['Ua'][:]))
- where_are_NaNs = np.isnan(mask_u)
- where_no_NaNs = np.invert(np.isnan(mask_u))
- mask_u[where_no_NaNs] = 1
- mask_u[where_are_NaNs] = 0
+ mask_u = np.ma.MaskedArray.filled(np.flipud(np.rot90(Dataset(settings['tide_fes']+constituents[0]+'_U.nc').variables['Ua'][:])))
+ mask_u[mask_u == 18446744073709551616.00000] = 0
+ mask_u[mask_u != 0] = 1
self.mask_dataset[mu_name] = mask_u
- mask_v = np.array(np.rot90(Dataset(settings['tide_fes']+constituents[0]+'_V.nc').variables['Va'][:]))
- where_are_NaNs = np.isnan(mask_v)
- where_no_NaNs = np.invert(np.isnan(mask_v))
- mask_v[where_no_NaNs] = 1
- mask_v[where_are_NaNs] = 0
+ mask_v = np.ma.MaskedArray.filled(np.flipud(np.rot90(Dataset(settings['tide_fes']+constituents[0]+'_V.nc').variables['Va'][:])))
+ mask_v[mask_v == 18446744073709551616.00000] = 0
+ mask_v[mask_v != 0] = 1
self.mask_dataset[mv_name] = mask_v
@@ -82,8 +76,10 @@ class HcExtract(object):
lat_z = np.array(Dataset(settings['tide_fes'] + constituents[0] + '_Z.nc').variables['lat'][:])
lon_z = np.array(Dataset(settings['tide_fes'] + constituents[0] + '_Z.nc').variables['lon'][:])
for ncon in range(len(constituents)):
- amp = np.array(np.rot90(Dataset(settings['tide_fes']+str(constituents[ncon])+'_Z.nc').variables['amplitude'][:]))
- phase = np.array(np.rot90(Dataset(settings['tide_fes']+constituents[ncon]+'_Z.nc').variables['phase'][:]))
+ amp = np.ma.MaskedArray.filled(np.flipud(np.rot90(Dataset(settings['tide_fes']+str(constituents[ncon])+'_Z.nc').variables['amplitude'][:])))
+ amp[amp == 18446744073709551616.00000] = 0
+ amp = amp/100.00
+ phase = np.ma.MaskedArray.filled(np.flipud(np.rot90(Dataset(settings['tide_fes']+constituents[ncon]+'_Z.nc').variables['phase'][:])))
hRe.append(amp*np.sin(phase))
hIm.append(amp*np.cos(phase))
hRe = np.stack(hRe)
@@ -96,8 +92,10 @@ class HcExtract(object):
lat_u = np.array(Dataset(settings['tide_fes'] + constituents[0] + '_U.nc').variables['lat'][:])
lon_u = np.array(Dataset(settings['tide_fes'] + constituents[0] + '_U.nc').variables['lon'][:])
for ncon in range(len(constituents)):
- amp = np.array(np.rot90(Dataset(settings['tide_fes']+constituents[ncon]+'_U.nc').variables['Ua'][:]))
- phase = np.array(np.rot90(Dataset(settings['tide_fes']+constituents[ncon]+'_U.nc').variables['Ug'][:]))
+ amp = np.ma.MaskedArray.filled(np.flipud(np.rot90(Dataset(settings['tide_fes']+constituents[ncon]+'_U.nc').variables['Ua'][:])))
+ amp[amp == 18446744073709551616.00000] = 0
+ amp = amp/100.00
+ phase = np.ma.MaskedArray.filled(np.flipud(np.rot90(Dataset(settings['tide_fes']+constituents[ncon]+'_U.nc').variables['Ug'][:])))
URe.append(amp*np.sin(phase))
UIm.append(amp*np.cos(phase))
URe = np.stack(URe)
@@ -109,8 +107,10 @@ class HcExtract(object):
lat_v = np.array(Dataset(settings['tide_fes'] + constituents[ncon] + '_V.nc').variables['lat'][:])
lon_v = np.array(Dataset(settings['tide_fes'] + constituents[ncon] + '_V.nc').variables['lon'][:])
for ncon in range(len(constituents)):
- amp = np.array(np.rot90(Dataset(settings['tide_fes']+constituents[ncon]+'_V.nc').variables['Va'][:]))
- phase = np.array(np.rot90(Dataset(settings['tide_fes']+constituents[ncon]+'_V.nc').variables['Vg'][:]))
+ amp = np.ma.MaskedArray.filled(np.flipud(np.rot90(Dataset(settings['tide_fes']+constituents[ncon]+'_V.nc').variables['Va'][:])))
+ amp[amp == 18446744073709551616.00000] = 0
+ amp = amp/100.00
+ phase = np.ma.MaskedArray.filled(np.flipud(np.rot90(Dataset(settings['tide_fes']+constituents[ncon]+'_V.nc').variables['Vg'][:])))
VRe.append(amp*np.sin(phase))
VIm.append(amp*np.cos(phase))
VRe = np.stack(VRe)
diff --git a/test_scripts/bdy_var_plot.py b/test_scripts/bdy_var_plot.py
index be1e8136ca3fe4fc2f585a20e90b59b8f6c4ebcd..0d8bae13693ed78b23ff98bd9a7966f0f71da249 100644
--- a/test_scripts/bdy_var_plot.py
+++ b/test_scripts/bdy_var_plot.py
@@ -61,13 +61,13 @@ def nemo_bdy_order(fname):
id_order[0,] = 0
flag = False
mark = 0
- source_tree = sp.cKDTree(zip(nbi_tmp, nbj_tmp), balanced_tree=False, compact_nodes=False)
+ source_tree = sp.cKDTree(list(zip(nbi_tmp, nbj_tmp)), balanced_tree=False, compact_nodes=False)
# order bdy entries
while count < nbdy[r]:
- nn_dist, nn_id = source_tree.query(zip(nbi_tmp[id_order[count - 1]], nbj_tmp[id_order[count - 1]]),
+ nn_dist, nn_id = source_tree.query(list(zip(nbi_tmp[id_order[count - 1]], nbj_tmp[id_order[count - 1]])),
k=3, distance_upper_bound=2.9)
if np.sum(id_order == nn_id[0, 1]) == 1: # is the nearest point already in the list?
if np.sum(id_order == nn_id[0, 2]) == 1: # is the 2nd nearest point already in the list?
@@ -207,19 +207,19 @@ def plot_bdy(fname, bdy_ind, bdy_dst, bdy_brk, varnam, t, rw):
# create a pseudo bathymetry from the depth data
- bathy = np.zeros_like(coords)
- mbath = np.sum(dta[n].mask == 0, axis=0)
+ #bathy = np.zeros_like(coords)
+ #mbath = np.sum(dta[n].mask == 0, axis=0)
- for i in range(len(coords)):
- bathy[i] = gdepw[mbath[i], i]
+ #for i in range(len(coords)):
+ # bathy[i] = gdepw[mbath[i], i]
- bathy_patch = Polygon(np.vstack((np.hstack((coords[0], coords, coords[-1])),
- np.hstack((np.amax(bathy[:]), bathy, np.amax(bathy[:]))))).T,
- closed=True,
- facecolor=(0.8, 0.8, 0), alpha=0, edgecolor=None)
+ #bathy_patch = Polygon(np.vstack((np.hstack((coords[0], coords, coords[-1])),
+ # np.hstack((np.amax(bathy[:]), bathy, np.amax(bathy[:]))))).T,
+ # closed=True,
+ # facecolor=(0.8, 0.8, 0), alpha=0, edgecolor=None)
# Add patch to axes
- ax[n].add_patch(bathy_patch)
+ #ax[n].add_patch(bathy_patch)
ax[n].set_title('BDY points along section: ' + str(n))
patches = []
colors = []
@@ -248,17 +248,17 @@ def plot_bdy(fname, bdy_ind, bdy_dst, bdy_brk, varnam, t, rw):
# plt.plot(x, y, 'k-', linewidth=0.1)
# plt.plot(coords[i], gdept[k, i], 'k.', markersize=1)
- plt.plot(coords, bathy, '-', color=(0.4, 0, 0))
+ #plt.plot(coords, bathy, '-', color=(0.4, 0, 0))
p = PatchCollection(patches, alpha=0.8, edgecolor='none')
p.set_array(np.array(colors))
ax[n].add_collection(p)
f.colorbar(p, ax=ax[n])
- ax[n].set_ylim((0, np.max(bathy)))
+ #ax[n].set_ylim((0, np.max(bathy)))
ax[n].invert_yaxis()
return f
-fname = '/Users/thopri/Projects/PyNEMO/outputs/NNA_R12_bdyT_y2017m11.nc'
+fname = '/Users/thopri/Projects/PyNEMO/outputs/NNA_R12_bdyT_y2017m01.nc'
print(fname)
ind, dst, brk = nemo_bdy_order(fname)
f = plot_bdy(fname, ind, dst, brk, 'thetao', 0, 0)
diff --git a/test_scripts/test_cmems.py b/test_scripts/test_cmems.py
deleted file mode 100644
index 75362698206ddca2e0a665f6f6b16ea425c3ea53..0000000000000000000000000000000000000000
--- a/test_scripts/test_cmems.py
+++ /dev/null
@@ -1,97 +0,0 @@
-#!/usr/bin/env python2
-# -*- coding: utf-8 -*-
-"""
-Created on Thu Oct 31 15:49:52 2019
-
-Test script to test download CMEMS data function in PyNEMO. To be incorprated
-into profile.py
-
-@author: thopri
-"""
-from pynemo import nemo_bdy_dl_cmems as dl_cmems
-from pynemo import nemo_bdy_setup as setup
-from calendar import monthrange
-import sys
-import time
-import threading
-
-Setup = setup.Setup('/Users/thopri/Projects/PyNEMO/inputs/namelist_cmems.bdy') # default settings file
-settings = Setup.settings
-
-if settings['use_cmems'] == True:
-
- if settings['year_end'] - settings['year_000'] > 0:
- date_min = settings['year_000']+'-01-01'
- date_max = settings['year_end']+'-12-31'
-
- days_mth = monthrange(settings['year_end'],settings['month_end'])
-
- date_min = str(settings['year_000'])+'-'+str(settings['month_000'])+'-01'
-
- date_max = str(settings['year_end'])+'-'+str(settings['month_end'])+'-'+str(days_mth[1])
-
- cmes_config= {
- 'ini_config_template' : settings['cmes_config_template'],
- 'user' : settings['cmes_usr'],
- 'pwd' : settings['cmes_pwd'],
- 'motu_server' : settings['motu_server'],
- 'service_id' : settings['cmes_model'],
- 'product_id' : settings['cmes_product'],
- 'date_min' : date_min,
- 'date_max' : date_max,
- 'latitude_min' : settings['latitude_min'],
- 'latitude_max' : settings['latitude_max'],
- 'longitude_min' : settings['longitude_min'],
- 'longitude_max' : settings['longitude_max'],
- 'depth_min' : settings['depth_min'],
- 'depth_max' : settings['depth_max'],
- 'variable' : settings['cmes_variable'],
- 'src_dir' : settings['src_dir'],
- 'out_name' : settings['cmes_output'],
- 'config_out' : settings['cmes_config']
- }
-
- chk = dl_cmems.chk_motu()
-
- dl = dl_cmems.request_CMEMS(cmes_config)
-
-class progress_bar_loading(threading.Thread):
-
- def run(self):
- global stop
- global kill
- print 'Loading.... ',
- sys.stdout.flush()
- i = 0
- while stop != True:
- if (i%4) == 0:
- sys.stdout.write('\b/')
- elif (i%4) == 1:
- sys.stdout.write('\b-')
- elif (i%4) == 2:
- sys.stdout.write('\b\\')
- elif (i%4) == 3:
- sys.stdout.write('\b|')
-
- sys.stdout.flush()
- time.sleep(0.2)
- i+=1
-
- if kill == True:
- print '\b\b\b\b ABORT!',
- else:
- print '\b\b done!',
-
-
-kill = False
-stop = False
-p = progress_bar_loading()
-p.start()
-
-try:
- #anything you want to run.
- time.sleep(1)
- stop = True
-except KeyboardInterrupt or EOFError:
- kill = True
- stop = True
\ No newline at end of file