def __init__(self, msl=None, names=None, **kwargs):
if msl is None:
msl = get_config_value(__name__, 'meansealevel_file')
# msl = _get_option_('meansealevel_file')
if msl is None:
raise MeanSeaLevel("Can't find a default file of mean sea levels")
if isinstance(msl, str): # file
if not os.path.isabs(msl):
msl = os.path.abspath(os.path.join(dirname, '../../../../data', msl))
if not os.path.exists(msl):
raise MeanSeaLevel("File of mean sea levels not found: %s"%msl)
data = []
names = []
xx = [] ; yy = [] ; zz = []
f = open(msl)
for line in f:
name = unicode(line[:29].strip(), 'utf8')
y, x, z = [float(v) for v in line[29:].split()]
names.append(name)
xx.append(x)
yy.append(y)
zz.append(z)
f.close()
msl = (xx, yy, zz)
elif isinstance(msl, MeanSeaLevel): # instance
names = list(msl.names())
kwargs.setdefault('units', 'm')
kwargs.setdefault('long_name', 'Mean sea level')
XYZBathy.__init__(self, msl, **kwargs)
self._names = names
def __init__(self, msl=None, names=None, **kwargs):
if msl is None:
msl = get_config_value(__name__, 'meansealevel_file')
# msl = _get_option_('meansealevel_file')
if msl is None:
raise MeanSeaLevel("Can't find a default file of mean sea levels")
if isinstance(msl, str): # file
if not os.path.isabs(msl):
msl = os.path.abspath(os.path.join(dirname, '../../../../data', msl))
if not os.path.exists(msl):
raise MeanSeaLevel("File of mean sea levels not found: %s"%msl)
data = []
names = []
xx = [] ; yy = [] ; zz = []
f = open(msl)
for line in f:
name = str(line[:29].strip(), 'utf8')
y, x, z = [float(v) for v in line[29:].split()]
names.append(name)
xx.append(x)
yy.append(y)
zz.append(z)
f.close()
msl = (xx, yy, zz)
elif isinstance(msl, MeanSeaLevel): # instance
names = list(msl.names())
kwargs.setdefault('units', 'm')
kwargs.setdefault('long_name', 'Mean sea level')
XYZBathy.__init__(self, msl, **kwargs)
self._names = names
# Creation de fausses bathymetries xyz
# - fonction generatrice
def gene_bathy(xc, yc, xr, yr, n=500, amp=30.):
noise = N.random.random(n)
a = N.random.random(n) * N.pi * 2
r = N.random.random(n)
x = xc + xr * r * N.cos(a)
y = yc + yr * r * N.sin(a)
return N.asarray([
x, y,
N.exp(-(x - xc)**2 / xr**2 - (y - yc)**2 / yr**2) * amp + noise
])
# - creations
xyz1 = XYZBathy(gene_bathy(-5, 48.3, .3, .15)) # top right
xyz2 = XYZBathy(gene_bathy(-5.45, 48.1, .45, .25, n=1000, amp=20),
transp=False) # bot left
# Recuperation de donnees
x = xyz1.x
y = xyz1.y
z = xyz1.z
# Exclusions/selections
xyz1.select([[-5.4, 48.1], [-4.8, 48.1], [-5.1, 48.5]])
xyz1.exclude([-5.2, 48., -5, 48.25])
# Infos
print xyz1.xmin # -> essayer get_xmin avec mask
print xyz1.resol() # -> essayer avec deg=...
xr = .4
yr = .15
noise = N.random.random(n)
a = N.random.random(n) * N.pi * 2
r = N.random.random(n)
x = xc + r * xr * N.cos(a)
y = yc + r * yr * N.sin(a)
bathy = N.asarray([
x, y,
N.exp(-(x - xc)**2 / xr**2 - (y - yc)**2 / yr**2) * 30. + noise
]).transpose()
fbathy = __file__[:-2] + 'xyz'
N.savetxt(fbathy, bathy)
# %% Load XYZ with undersampling
xyz = XYZBathy(fbathy, long_name='My XYZ', rsamp=0.01)
# on aurait pu charger directement :
# >>> xyz = XYZBathy(bathy)
# %% Add a selection zone
# -> triangulaire, par coordonnees [[x1,y1],...]
xyz.select([[-5.4, 48.1], [-4.8, 48.1], [-5.1, 48.5]])
# %% Add an exclusion zone
# -> rectangulaire, par coins [xmin,ymin,xmax,ymax]
xyz.exclude([-5.2, 48., -5, 48.25])
# %% Info
print xyz
# %% Get data
# - fonction generatrice
def gene_bathy(xc, yc, xr, yr, n=500, amp=30.):
noise = N.random.random(n)
a = N.random.random(n) * N.pi * 2
r = N.random.random(n)
x = xc + xr * r * N.cos(a)
y = yc + yr * r * N.sin(a)
return N.asarray([
x, y,
N.exp(-(x - xc)**2 / xr**2 - (y - yc)**2 / yr**2) * amp + noise
])
# - creations
xyz1 = XYZBathy(gene_bathy(-5, 48.3, .3, .15)) # top right
xyz2 = XYZBathy(gene_bathy(-5.45, 48.3, .2, .1, amp=10)) # top left
xyz3 = XYZBathy(gene_bathy(-5.45, 48.1, .45, .25, n=1000, amp=20),
transp=False) # bot left
xyz4 = XYZBathy(gene_bathy(-5., 48.1, .14, .08, n=300)) # bot right
fxyz5 = __file__[:-2] + 'xyz5.xyz'
N.savetxt(fxyz5, gene_bathy(-5.15, 48.2, .2, .1, amp=15).transpose()) # center
# Fusion directe
xyz = xyz1 + xyz2 + xyz3 + xyz4 + fxyz5
# Plot
import pylab as P
P.figure(figsize=(5., 8.5))
P.subplot(311)
from vcmq import N, os, merc, create_grid, resol, map2, P
from vacumm.bathy.bathy import XYZBathy, XYZBathyMerger
# Creation de fausses bathymetries xyz
# - fonction generatrice
def gene_bathy(xc, yc, xr, yr, n=500, amp=30.0):
noise = N.random.random(n)
a = N.random.random(n) * N.pi * 2
r = N.random.random(n)
x = xc + xr * r * N.cos(a)
y = yc + yr * r * N.sin(a)
return N.asarray([x, y, N.exp(-(x - xc) ** 2 / xr ** 2 - (y - yc) ** 2 / yr ** 2) * amp + noise])
# - creations
xyz1 = XYZBathy(gene_bathy(-5, 48.3, 0.3, 0.15)) # top right
xyz2 = XYZBathy(gene_bathy(-5.45, 48.1, 0.45, 0.25, n=1000, amp=20), transp=False) # bot left
# Recuperation de donnees
x = xyz1.x
y = xyz1.y
z = xyz1.z
# Exclusions/selections
xyz1.select([[-5.4, 48.1], [-4.8, 48.1], [-5.1, 48.5]])
xyz1.exclude([-5.2, 48.0, -5, 48.25])
# Infos
print xyz1.xmin # -> essayer get_xmin avec mask
print xyz1.resol() # -> essayer avec deg=...
from vacumm.misc.grid import create_grid, resol from vacumm.misc.plot import map2 # Creation d'une fausse bathymetrie xyz n = 1000 ; xc = -5.1 ; yc = 48.2 ; xr = .4 ; yr = .15 noise = N.random.random(n) a = N.random.random(n)*N.pi*2 r = N.random.random(n) x = xc + r*xr*N.cos(a) y = yc + r*yr*N.sin(a) bathy = N.asarray([x, y, N.exp(-(x-xc)**2/xr**2-(y-yc)**2/yr**2)*30.+noise]).transpose() fbathy = __file__[:-2]+'xyz' N.savetxt(fbathy, bathy) # Chargement dans XYZ avec sous echantillonage xyz = XYZBathy(fbathy, long_name='My XYZ', rsamp=0.01) # on aurait pu charger directement : # >>> xyz = XYZBathy(bathy) # Ajout d'une zone de selection # -> triangulaire, par coordonnees [[x1,y1],...] xyz.select([[-5.4, 48.1], [-4.8, 48.1], [-5.1, 48.5]]) # Ajout d'une zone d'exclusion # -> rectangulaire, par coins [xmin,ymin,xmax,ymax] xyz.exclude([-5.2, 48., -5, 48.25]) # Infos print xyz # Recuperation des valeurs
