Coverage for /usr/local/lib/python3.7/dist-packages/pyrocko/dataset/crustdb.py : 50%

# http://pyrocko.org - GPLv3 

# 

# The Pyrocko Developers, 21st Century 

# ---|P------/S----------~Lg---------- 

'''Access to the USGS Global Crustal Database. 

Simple queries and statistical analysis''' 

from __future__ import absolute_import 

import numpy as num 

import copy 

import logging 

from os import path 

from pyrocko.guts import Object, String, Float, Int 

from pyrocko.guts_array import Array 

from pyrocko.cake import LayeredModel, Material 

from pyrocko.plot.cake_plot import my_model_plot, xscaled, yscaled 

from .crustdb_abbr import ageKey, provinceKey, referenceKey, pubYear # noqa 

logger = logging.getLogger('pyrocko.dataset.crustdb') 

THICKNESS_HALFSPACE = 2 

db_url = 'https://mirror.pyrocko.org/gsc20130501.txt' 

km = 1e3 

vel_labels = { 

'vp': '$V_P$', 

'p': '$V_P$', 

'vs': '$V_S$', 

's': '$V_S$', 

} 

class DatabaseError(Exception): 

pass 

class ProfileEmpty(Exception): 

pass 

def _getCanvas(axes): 

import matplotlib.pyplot as plt 

if axes is None: 

fig = plt.figure() 

return fig, fig.gca() 

return axes.figure, axes 

def xoffset_scale(offset, scale, ax): 

from matplotlib.ticker import ScalarFormatter, AutoLocator 

class FormatVelocities(ScalarFormatter): 

@staticmethod 

def __call__(value, pos): 

return u'%.1f' % ((value-offset) * scale) 

class OffsetLocator(AutoLocator): 

def tick_values(self, vmin, vmax): 

return [v + offset for v in 

AutoLocator.tick_values(self, vmin, vmax)] 

ax.get_xaxis().set_major_formatter(FormatVelocities()) 

ax.get_xaxis().set_major_locator(OffsetLocator()) 

class VelocityProfile(Object): 

uid = Int.T( 

optional=True, 

help='Unique ID of measurement') 

lat = Float.T( 

help='Latitude [deg]') 

lon = Float.T( 

help='Longitude [deg]') 

elevation = Float.T( 

default=num.nan, 

help='Elevation [m]') 

vp = Array.T( 

shape=(None, 1), 

help='P Wave velocities [m/s]') 

vs = Array.T( 

shape=(None, 1), 

help='S Wave velocities [m/s]') 

d = Array.T( 

shape=(None, 1), 

help='Interface depth, top [m]') 

h = Array.T( 

shape=(None, 1), 

help='Interface thickness [m]') 

heatflow = Float.T( 

optional=True, 

help='Heatflow [W/m^2]') 

geographical_location = String.T( 

optional=True, 

help='Geographic Location') 

geological_province = String.T( 

optional=True, 

help='Geological Province') 

geological_age = String.T( 

optional=True, 

help='Geological Age') 

measurement_method = Int.T( 

optional=True, 

help='Measurement method') 

publication_reference = String.T( 

optional=True, 

help='Publication Reference') 

publication_year__ = Int.T( 

help='Publication Date') 

def __init__(self, *args, **kwargs): 

Object.__init__(self, *args, **kwargs) 

self.h = num.abs(self.d - num.roll(self.d, -1)) 

self.h[-1] = 0 

self.nlayers = self.h.size 

self.geographical_location = '%s (%s)' % ( 

provinceKey(self.geographical_location), 

self.geographical_location) 

self.vs[self.vs == 0] = num.nan 

self.vp[self.vp == 0] = num.nan 

self._step_vp = num.repeat(self.vp, 2) 

self._step_vs = num.repeat(self.vs, 2) 

self._step_d = num.roll(num.repeat(self.d, 2), -1) 

self._step_d[-1] = self._step_d[-2] + THICKNESS_HALFSPACE 

@property 

def publication_year__(self): 

return pubYear(self.publication_reference) 

def interpolateProfile(self, depths, phase='p', stepped=True): 

'''Get a continuous velocity function at arbitrary depth 

:param depth: Depths to interpolate 

:type depth: :class:`numpy.ndarray` 

:param phase: P or S wave velocity, **p** or **s** 

:type phase: str, optional 

:param stepped: Use a stepped velocity function or gradient 

:type stepped: bool 

:returns: velocities at requested depths 

:rtype: :class:`numpy.ndarray` 

''' 

if phase not in ['s', 'p']: 

raise AttributeError('Phase has to be either \'p\' or \'s\'.') 

if phase == 'p': 

vel = self._step_vp if stepped else self.vp 

elif phase == 's': 

vel = self._step_vs if stepped else self.vs 

d = self._step_d if stepped else self.d 

if vel.size == 0: 

raise ProfileEmpty('Phase %s does not contain velocities' % phase) 

try: 

res = num.interp(depths, d, vel, 

left=num.nan, right=num.nan) 

except ValueError: 

raise ValueError('Could not interpolate velocity profile.') 

return res 

def plot(self, axes=None): 

''' Plot the velocity profile, see :class:`pyrocko.cake`. 

:param axes: Axes to plot into. 

:type axes: :class:`matplotlib.Axes`''' 

import matplotlib.pyplot as plt 

fig, ax = _getCanvas(axes) 

my_model_plot(self.getLayeredModel(), axes=axes) 

ax.set_title('Global Crustal Database\n' 

'Velocity Structure at {p.lat:.4f}N, ' 

' {p.lat:.4f}E (uid {p.uid})'.format(p=self)) 

if axes is None: 

plt.show() 

def getLayeredModel(self): 

''' Get a layered model, see :class:`pyrocko.cake.LayeredModel`. ''' 

def iterLines(): 

for il, m in enumerate(self.iterLayers()): 

yield self.d[il], m, '' 

return LayeredModel.from_scanlines(iterLines()) 

def iterLayers(self): 

''' Iterator returns a :class:`pyrocko.cake.Material` for each layer''' 

for il in range(self.nlayers): 

yield Material(vp=self.vp[il], 

vs=self.vs[il]) 

@property 

def geog_loc_long(self): 

return provinceKey(self.geog_loc) 

@property 

def geol_age_long(self): 

return ageKey(self.geol_age) 

@property 

def has_s(self): 

return num.any(self.vp) 

@property 

def has_p(self): 

return num.any(self.vs) 

def get_weeded(self): 

''' Get weeded representation of layers used in the profile. 

See :func:`pyrocko.cake.get_weeded` for details. 

''' 

weeded = num.zeros((self.nlayers, 4)) 

weeded[:, 0] = self.d 

weeded[:, 1] = self.vp 

weeded[:, 2] = self.vs 

def _csv(self): 

output = '' 

for d in range(len(self.h)): 

output += ('{p.uid}, {p.lat}, {p.lon},' 

' {vp}, {vs}, {h}, {d}, {self.reference}').format( 

p=self, 

vp=self.vs[d], vs=self.vp[d], h=self.h[d], d=self.d[d]) 

return output 

class CrustDB(object): 

''' CrustDB is a container for :class:`VelocityProfile` and provides 

functions for spatial selection, querying, processing and visualising 

data from the Global Crustal Database. 

''' 

def __init__(self, database_file=None, parent=None): 

self.profiles = [] 

self._velocity_matrix_cache = {} 

self.data_matrix = None 

self.name = None 

self.database_file = database_file 

if parent is not None: 

pass 

elif database_file is not None: 

self._read(database_file) 

else: 

self._read(self._getRepositoryDatabase()) 

def __len__(self): 

return len(self.profiles) 

def __setitem__(self, key, value): 

if not isinstance(value, VelocityProfile): 

raise TypeError('Element is not a VelocityProfile') 

self.profiles[key] = value 

def __delitem__(self, key): 

self.profiles.remove(key) 

def __getitem__(self, key): 

return self.profiles[key] 

def __str__(self): 

rstr = "Container contains %d velocity profiles:\n\n" % self.nprofiles 

return rstr 

@property 

def nprofiles(self): 

return len(self.profiles) 

def append(self, value): 

if not isinstance(value, VelocityProfile): 

raise TypeError('Element is not a VelocityProfile') 

self.profiles.append(value) 

def copy(self): 

return copy.deepcopy(self) 

def lats(self): 

return num.array( 

[p.lat for p in self.profiles]) 

def lons(self): 

return num.array( 

[p.lon for p in self.profiles]) 

def _dataMatrix(self): 

if self.data_matrix is not None: 

return self.data_matrix 

self.data_matrix = num.core.records.fromarrays( 

num.vstack([ 

num.concatenate([p.vp for p in self.profiles]), 

num.concatenate([p.vs for p in self.profiles]), 

num.concatenate([p.h for p in self.profiles]), 

num.concatenate([p.d for p in self.profiles]) 

]), 

names='vp, vs, h, d') 

return self.data_matrix 

def velocityMatrix(self, depth_range=(0, 60000.), ddepth=100., phase='p'): 

'''Create a regular sampled velocity matrix 

:param depth_range: Depth range, ``(dmin, dmax)``, 

defaults to ``(0, 6000.)`` 

:type depth_range: tuple 

:param ddepth: Stepping in [m], defaults to ``100.`` 

:type ddepth: float 

:param phase: Phase to calculate ``p`` or ``s``, 

defaults to ``p`` 

:type phase: str 

:returns: Sample depths, veloctiy matrix 

:rtype: tuple, (sample_depth, :class:`numpy.ndarray`) 

''' 

dmin, dmax = depth_range 

uid = '.'.join(map(repr, (dmin, dmax, ddepth, phase))) 

sdepth = num.linspace(dmin, dmax, (dmax - dmin) / ddepth) 

ndepth = sdepth.size 

if uid not in self._velocity_matrix_cache: 

vel_mat = num.empty((self.nprofiles, ndepth)) 

for ip, profile in enumerate(self.profiles): 

vel_mat[ip, :] = profile.interpolateProfile(sdepth, 

phase=phase) 

self._velocity_matrix_cache[uid] = num.ma.masked_invalid(vel_mat) 

return sdepth, self._velocity_matrix_cache[uid] 

def rmsRank(self, ref_profile, depth_range=(0, 3500.), ddepth=100., 

phase='p'): 

'''Correlates ``ref_profile`` to each profile in the database 

:param ref_profile: Reference profile 

:type ref_profile: :class:`VelocityProfile` 

:param depth_range: Depth range in [m], ``(dmin, dmax)``, 

defaults to ``(0, 35000.)`` 

:type depth_range: tuple, optional 

:param ddepth: Stepping in [m], defaults to ``100.`` 

:type ddepth: float 

:param phase: Phase to calculate ``p`` or ``s``, defaults to ``p`` 

:type phase: str 

:returns: RMS factor length of N_profiles 

:rtype: :class:`numpy.ndarray` 

''' 

if not isinstance(ref_profile, VelocityProfile): 

raise ValueError('ref_profile is not a VelocityProfile') 

sdepth, vel_matrix = self.velocityMatrix(depth_range, ddepth, 

phase=phase) 

ref_vel = ref_profile.interpolateProfile(sdepth, phase=phase) 

rms = num.empty(self.nprofiles) 

for p in range(self.nprofiles): 

profile = vel_matrix[p, :] 

rms[p] = num.sqrt(profile**2 - ref_vel**2).sum() / ref_vel.size 

return rms 

def histogram2d(self, depth_range=(0., 60000.), vel_range=None, 

ddepth=100., dvbin=100., ddbin=2000., phase='p'): 

'''Create a 2D Histogram of all the velocity profiles 

Check :func:`numpy.histogram2d` for more information. 

:param depth_range: Depth range in [m], ``(dmin, dmax)``, 

defaults to ``(0., 60000.)`` 

:type depth_range: tuple 

:param vel_range: Depth range, ``(vmin, vmax)``, 

defaults to ``(5500., 8500.)`` 

:type vel_range: tuple 

:param ddepth: Stepping in [km], defaults to ``100.`` 

:type ddepth: float 

:param dvbin: Bin size in velocity dimension [m/s], defaults to 100. 

:type dvbin: float 

:param dvbin: Bin size in depth dimension [m], defaults to 2000. 

:type dvbin: float 

:param phase: Phase to calculate ``p`` or ``s``, defaults to ``p`` 

:type phase: str 

:returns: :func:`numpy.histogram2d` 

:rtype: tuple 

''' 

sdepth, v_mat = self.velocityMatrix(depth_range, ddepth, phase=phase) 

d_vec = num.tile(sdepth, self.nprofiles) 

# Velocity and depth bins 

if vel_range is None: 

vel_range = ((v_mat.min() // 1e2) * 1e2, 

(v_mat.max() // 1e2) * 1e2) 

nvbins = int((vel_range[1] - vel_range[0]) / dvbin) 

ndbins = int((depth_range[1] - depth_range[0]) / ddbin) 

return num.histogram2d(v_mat.flatten(), d_vec, 

range=(vel_range, depth_range), 

bins=[nvbins, ndbins], 

normed=False) 

def meanVelocity(self, depth_range=(0., 60000.), ddepth=100., phase='p'): 

'''Mean velocity profile plus std variation 

:param depth_range: Depth range in [m], ``(dmin, dmax)``, 

defaults to ``(0., 60000.)`` 

:type depth_range: tuple 

:param ddepth: Stepping in [m], defaults to ``100.`` 

:type ddepth: float 

:param phase: Phase to calculate ``p`` or ``s``, defaults to ``p`` 

:type phase: str 

:returns: depth vector, mean velocities, standard deviations 

:rtype: tuple of :class:`numpy.ndarray` 

''' 

sdepth, v_mat = self.velocityMatrix(depth_range, ddepth, phase=phase) 

v_mean = num.ma.mean(v_mat, axis=0) 

v_std = num.ma.std(v_mat, axis=0) 

return sdepth, v_mean.flatten(), v_std.flatten() 

def modeVelocity(self, depth_range=(0., 60000.), ddepth=100., phase='p'): 

'''Mode velocity profile plus std variation 

:param depth_range: Depth range in [m], ``(dmin, dmax)``, 

defaults to ``(0., 60000.)`` 

:type depth_range: tuple 

:param ddepth: Stepping in [m], defaults to ``100.`` 

:type ddepth: float 

:param phase: Phase to calculate ``p`` or ``s``, defaults to ``p`` 

:type phase: str 

:returns: depth vector, mode velocity, number of counts at each depth 

:rtype: tuple of :class:`numpy.ndarray` 

''' 

import scipy.stats 

sdepth, v_mat = self.velocityMatrix(depth_range, ddepth) 

v_mode, v_counts = scipy.stats.mstats.mode(v_mat, axis=0) 

return sdepth, v_mode.flatten(), v_counts.flatten() 

def medianVelocity(self, depth_range=(0., 60000.), ddepth=100., phase='p'): 

'''Median velocity profile plus std variation 

:param depth_range: Depth range in [m], ``(dmin, dmax)``, 

defaults to ``(0., 60000.)`` 

:type depth_range: tuple 

:param ddepth: Stepping in [m], defaults to ``100.`` 

:type ddepth: float 

:param phase: Phase to calculate ``p`` or ``s``, defaults to ``p`` 

:type phase: str 

:returns: depth vector, median velocities, standard deviations 

:rtype: tuple of :class:`numpy.ndarray` 

''' 

sdepth, v_mat = self.velocityMatrix(depth_range, ddepth, phase=phase) 

v_mean = num.ma.median(v_mat, axis=0) 

v_std = num.ma.std(v_mat, axis=0) 

return sdepth, v_mean.flatten(), v_std.flatten() 

def plotHistogram(self, vel_range=None, bins=36, phase='vp', 

axes=None): 

'''Plot 1D histogram of seismic velocities in the container 

:param vel_range: Velocity range, defaults to (5.5, 8.5) 

:type vel_range: tuple, optional 

:param bins: bins, defaults to 30 (see :func:`numpy.histogram`) 

:type bins: int, optional 

:param phase: Property to plot out of ``['vp', 'vs']``, 

defaults to 'vp' 

:type phase: str, optional 

:param figure: Figure to plot in, defaults to None 

:type figure: :class:`matplotlib.Figure`, optional 

''' 

import matplotlib.pyplot as plt 

fig, ax = _getCanvas(axes) 

if phase not in ['vp', 'vs']: 

raise AttributeError('phase has to be either vp or vs') 

data = self._dataMatrix()[phase] 

ax.hist(data, weights=self.data_matrix['h'], 

range=vel_range, bins=bins, 

color='g', alpha=.5) 

ax.text(.95, .95, '%d Profiles' % self.nprofiles, 

transform=ax.transAxes, fontsize=10, 

va='top', ha='right', alpha=.7) 

ax.set_title('Distribution of %s' % vel_labels[phase]) 

ax.set_xlabel('%s [km/s]' % vel_labels[phase]) 

ax.set_ylabel('Cumulative occurrence [N]') 

xscaled(1./km, ax) 

ax.yaxis.grid(alpha=.4) 

if self.name is not None: 

ax.set_title('%s for %s' % (ax.get_title(), self.name)) 

if axes is None: 

plt.show() 

def plot(self, depth_range=(0, 60000.), ddepth=100., ddbin=2000., 

vel_range=None, dvbin=100., 

percent=False, 

plot_mode=True, plot_median=True, plot_mean=False, 

show_cbar=True, 

aspect=.02, 

phase='p', 

axes=None): 

''' Plot a two 2D Histogram of seismic velocities 

:param depth_range: Depth range, ``(dmin, dmax)``, 

defaults to ``(0, 60)`` 

:type depth_range: tuple 

:param vel_range: Velocity range, ``(vmin, vmax)`` 

:type vel_range: tuple 

:param ddepth: Stepping in [m], defaults to ``.1`` 

:type ddepth: float 

:param dvbin: Bin size in velocity dimension [m/s], defaults to .1 

:type dvbin: float 

:param dvbin: Bin size in depth dimension [m], defaults to 2000. 

:type dvbin: float 

:param phase: Phase to calculate ``p`` or ``s``, defaults to ``p`` 

:type phase: str 

:param plot_mode: Plot the Mode 

:type plot_mode: bool 

:param plot_mean: Plot the Mean 

:type plot_mean: bool 

:param plot_median: Plot the Median 

:type plot_median: bool 

:param axes: Axes to plot into, defaults to None 

:type axes: :class:`matplotlib.Axes` 

''' 

import matplotlib.pyplot as plt 

fig, ax = _getCanvas(axes) 

ax = fig.gca() 

if vel_range is not None: 

vmin, vmax = vel_range 

dmin, dmax = depth_range 

vfield, vedg, dedg = self.histogram2d(vel_range=vel_range, 

depth_range=depth_range, 

ddepth=ddepth, dvbin=dvbin, 

ddbin=ddbin, phase=phase) 

vfield /= (ddbin / ddepth) 

if percent: 

vfield /= vfield.sum(axis=1)[num.newaxis, :] 

grid_ext = [vedg[0], vedg[-1], dedg[-1], dedg[0]] 

histogram = ax.imshow(vfield.swapaxes(0, 1), 

interpolation='nearest', 

extent=grid_ext, aspect=aspect) 

if show_cbar: 

cticks = num.unique( 

num.arange(0, vfield.max(), vfield.max() // 10).round()) 

cbar = fig.colorbar(histogram, ticks=cticks, format='%1i', 

orientation='horizontal') 

if percent: 

cbar.set_label('Percent') 

else: 

cbar.set_label('Number of Profiles') 

if plot_mode: 

sdepth, vel_mode, _ = self.modeVelocity(depth_range=depth_range, 

ddepth=ddepth) 

ax.plot(vel_mode[sdepth < dmax] + ddepth/2, 

sdepth[sdepth < dmax], 

alpha=.8, color='w', label='Mode') 

if plot_mean: 

sdepth, vel_mean, _ = self.meanVelocity(depth_range=depth_range, 

ddepth=ddepth) 

ax.plot(vel_mean[sdepth < dmax] + ddepth/2, 

sdepth[sdepth < dmax], 

alpha=.8, color='w', linestyle='--', label='Mean') 

if plot_median: 

sdepth, vel_median, _ = self.medianVelocity( 

depth_range=depth_range, 

ddepth=ddepth) 

ax.plot(vel_median[sdepth < dmax] + ddepth/2, 

sdepth[sdepth < dmax], 

alpha=.8, color='w', linestyle=':', label='Median') 

ax.grid(True, which="both", color="w", linewidth=.8, alpha=.4) 

ax.text(.025, .025, '%d Profiles' % self.nprofiles, 

color='w', alpha=.7, 

transform=ax.transAxes, fontsize=9, va='bottom', ha='left') 

ax.set_title('Crustal Velocity Distribution') 

ax.set_xlabel('%s [km/s]' % vel_labels[phase]) 

ax.set_ylabel('Depth [km]') 

yscaled(1./km, ax) 

xoffset_scale(dvbin/2, 1./km, ax) 

ax.set_xlim(vel_range) 

if self.name is not None: 

ax.set_title('%s for %s' % (ax.get_title(), self.name)) 

if plot_mode or plot_mean or plot_median: 

leg = ax.legend(loc=1, fancybox=True, prop={'size': 10.}) 

leg.get_frame().set_alpha(.6) 

if axes is None: 

plt.show() 

def plotVelocitySurface(self, v_max, d_min=0., d_max=6000., axes=None): 

'''Plot a triangulated a depth surface exceeding velocity''' 

import matplotlib.pyplot as plt 

fig, ax = _getCanvas(axes) 

d = self.exceedVelocity(v_max, d_min, d_max) 

lons = self.lons()[d > 0] 

lats = self.lats()[d > 0] 

d = d[d > 0] 

ax.tricontourf(lats, lons, d) 

if axes is None: 

plt.show() 

def plotMap(self, outfile, **kwargs): 

from pyrocko.plot import gmtpy 

lats = self.lats() 

lons = self.lons() 

s, n, w, e = (lats.min(), lats.max(), lons.min(), lons.max()) 

def darken(c, f=0.7): 

return (c[0]*f, c[1]*f, c[2]*f) 

gmt = gmtpy.GMT() 

gmt.psbasemap(B='40/20', 

J='M0/12', 

R='%f/%f/%f/%f' % (w, e, s, n)) 

gmt.pscoast(R=True, J=True, 

D='i', S='216/242/254', A=10000, 

W='.2p') 

gmt.psxy(R=True, J=True, 

in_columns=[lons, lats], 

S='c2p', G='black') 

gmt.save(outfile) 

def exceedVelocity(self, v_max, d_min=0, d_max=60): 

''' Returns the last depth ``v_max`` has not been exceeded. 

:param v_max: maximal velocity 

:type vmax: float 

:param dz: depth is sampled in dz steps 

:type dz: float 

:param d_max: maximum depth 

:type d_max: int 

:param d_min: minimum depth 

:type d_min: int 

:returns: Lat, Lon, Depth and uid where ``v_max`` is exceeded 

:rtype: list(num.array) 

''' 

self.profile_exceed_velocity = num.empty(len(self.profiles)) 

self.profile_exceed_velocity[:] = num.nan 

for ip, profile in enumerate(self.profiles): 

for il in range(len(profile.d)): 

if profile.d[il] <= d_min\ 

or profile.d[il] >= d_max: 

continue 

if profile.vp[il] < v_max: 

continue 

else: 

self.profile_exceed_velocity[ip] = profile.d[il] 

break 

return self.profile_exceed_velocity 

def selectRegion(self, west, east, south, north): 

'''Select profiles within a region by geographic corner coordinates 

:param west: west corner 

:type west: float 

:param east: east corner 

:type east: float 

:param south: south corner 

:type south: float 

:param north: north corner 

:type north: float 

:returns: Selected profiles 

:rtype: :class:`CrustDB` 

''' 

r_container = self._emptyCopy() 

for profile in self.profiles: 

if profile.lon >= west and profile.lon <= east \ 

and profile.lat <= north and profile.lat >= south: 

r_container.append(profile) 

return r_container 

def selectPolygon(self, poly): 

'''Select profiles within a polygon. 

The algorithm is called the **Ray Casting Method** 

:param poly: Latitude Longitude pairs of the polygon 

:type param: list of :class:`numpy.ndarray` 

:returns: Selected profiles 

:rtype: :class:`CrustDB` 

''' 

r_container = self._emptyCopy() 

for profile in self.profiles: 

x = profile.lon 

y = profile.lat 

inside = False 

p1x, p1y = poly[0] 

for p2x, p2y in poly: 

if y >= min(p1y, p2y): 

if y <= max(p1y, p2y): 

if x <= max(p1x, p2x): 

if p1y != p2y: 

xints = (y - p1y) * (p2x - p1x) / \ 

(p2y - p1y) + p1x 

if p1x == p2x or x <= xints: 

inside = not inside 

p1x, p1y = p2x, p2y 

if inside: 

r_container.append(profile) 

return r_container 

def selectLocation(self, lat, lon, radius=10): 

'''Select profiles at a geographic location within a ``radius``. 

:param lat: Latitude in [deg] 

:type lat: float 

:param lon: Longitude in [deg] 

:type lon: float 

:param radius: Radius in [deg] 

:type radius: float 

:returns: Selected profiles 

:rtype: :class:`CrustDB` 

''' 

r_container = self._emptyCopy() 

logger.info('Selecting location %f, %f (r=%f)...' % (lat, lon, radius)) 

for profile in self.profiles: 

if num.sqrt((lat - profile.lat)**2 + 

(lon - profile.lon)**2) <= radius: 

r_container.append(profile) 

return r_container 

def selectMinLayers(self, nlayers): 

'''Select profiles with more than ``nlayers`` 

:param nlayers: Minimum number of layers 

:type nlayers: int 

:returns: Selected profiles 

:rtype: :class:`CrustDB` 

''' 

r_container = self._emptyCopy() 

logger.info('Selecting minimum %d layers...' % nlayers) 

for profile in self.profiles: 

if profile.nlayers >= nlayers: 

r_container.append(profile) 

return r_container 

def selectMaxLayers(self, nlayers): 

'''Select profiles with more than ``nlayers``. 

:param nlayers: Maximum number of layers 

:type nlayers: int 

:returns: Selected profiles 

:rtype: :class:`CrustDB` 

''' 

r_container = self._emptyCopy() 

logger.info('Selecting maximum %d layers...' % nlayers) 

for profile in self.profiles: 

if profile.nlayers <= nlayers: 

r_container.append(profile) 

return r_container 

def selectMinDepth(self, depth): 

'''Select profiles describing layers deeper than ``depth`` 

:param depth: Minumum depth in [m] 

:type depth: float 

:returns: Selected profiles 

:rtype: :class:`CrustDB` 

''' 

r_container = self._emptyCopy() 

logger.info('Selecting minimum depth %f m...' % depth) 

for profile in self.profiles: 

if profile.d.max() >= depth: 

r_container.append(profile) 

return r_container 

def selectMaxDepth(self, depth): 

'''Select profiles describing layers shallower than ``depth`` 

:param depth: Maximum depth in [m] 

:type depth: float 

:returns: Selected profiles 

:rtype: :class:`CrustDB` 

''' 

r_container = self._emptyCopy() 

logger.info('Selecting maximum depth %f m...' % depth) 

for profile in self.profiles: 

if profile.d.max() <= depth: 

r_container.append(profile) 

return r_container 

def selectVp(self): 

'''Select profiles describing P Wave velocity 

:returns Selected profiles 

:rtype: :class:`CrustDB` 

''' 

r_container = self._emptyCopy() 

logger.info('Selecting profiles providing Vp...') 

for profile in self.profiles: 

if not num.all(num.isnan(profile.vp)): 

r_container.append(profile) 

return r_container 

def selectVs(self): 

'''Select profiles describing P Wave velocity 

:returns: Selected profiles 

:rtype: :class:`CrustDB` 

''' 

r_container = self._emptyCopy() 

logger.info('Selecting profiles providing Vs...') 

for profile in self.profiles: 

if not num.all(num.isnan(profile.vs)): 

r_container.append(profile) 

return r_container 

def _emptyCopy(self): 

r_container = CrustDB(parent=self) 

r_container.name = self.name 

return r_container 

def exportCSV(self, filename=None): 

'''Export a CSV file as specified in the header below