def read_eshdf_eig_data(filename, Ef_list):
import numpy as np
from numpy import array, pi
from numpy.linalg import inv
from unit_converter import convert
from hdfreader import read_hdf
from developer import error
def h5int(i):
return array(i, dtype=int)[0]
#end def h5int
h = read_hdf(filename, view=True)
axes = array(h.supercell.primitive_vectors)
kaxes = 2 * pi * inv(axes).T
nk = h5int(h.electrons.number_of_kpoints)
ns = h5int(h.electrons.number_of_spins)
if len(Ef_list) != ns:
msg = 'Ef "%s" must have same length as nspin=%d' % (str(Ef_list), ns)
error(msg)
data = obj()
for k in range(nk):
kp = h.electrons['kpoint_' + str(k)]
for s, Ef in zip(range(ns), Ef_list):
E_fermi = Ef + 1e-8
eig_s = []
path = 'electrons/kpoint_{0}/spin_{1}'.format(k, s)
spin = h.get_path(path)
eig = convert(array(spin.eigenvalues), 'Ha', 'eV')
nst = h5int(spin.number_of_states)
for st in range(nst):
e = eig[st]
if e < E_fermi:
eig_s.append(e)
#end if
#end for
data[k, s] = obj(
kpoint=array(kp.reduced_k),
eig=array(eig_s),
)
#end for
#end for
res = obj(
orbfile=filename,
axes=axes,
kaxes=kaxes,
nkpoints=nk,
nspins=ns,
data=data,
)
return res
def read_eshdf_nofk_data(filename, Ef):
from numpy import array, pi, dot, sqrt, abs, zeros
from numpy.linalg import inv, det
from hdfreader import read_hdf
def h5int(i):
return array(i, dtype=int)[0]
#end def h5int
# Use slightly shifted Fermi energy
E_fermi = Ef + 1e-8
# Open the HDF file w/o loading the arrays into memory (view mode)
vlog('Reading ' + filename)
h = read_hdf(filename, view=True)
# Get the G-vectors in cell coordinates
gvu = array(h.electrons.kpoint_0.gvectors)
# Get the untiled cell axes
axes = array(h.supercell.primitive_vectors)
# Compute the k-space cell axes
kaxes = 2 * pi * inv(axes).T
# Convert G-vectors from cell coordinates to atomic units
gv = dot(gvu, kaxes)
# Get number of kpoints/twists, spins, and G-vectors
nkpoints = h5int(h.electrons.number_of_kpoints)
nspins = h5int(h.electrons.number_of_spins)
ngvecs = len(gv)
# Process the orbital data
data = obj()
for k in range(nkpoints):
vlog('Processing k-point {:>3}'.format(k), n=1, time=True)
kin_k = obj()
eig_k = obj()
k_k = obj()
nk_k = obj()
nelec_k = zeros((nspins, ), dtype=float)
kp = h.electrons['kpoint_' + str(k)]
gvs = dot(array(kp.reduced_k), kaxes)
gvk = gv.copy()
for d in range(3):
gvk[:, d] += gvs[d]
#end for
kinetic = (gvk**2).sum(1) / 2 # Hartree units
for s in range(nspins):
kin_s = []
eig_s = []
k_s = gvk
nk_s = zeros((ngvecs, ), dtype=float)
nelec_s = 0
path = 'electrons/kpoint_{0}/spin_{1}'.format(k, s)
spin = h.get_path(path)
eigs = convert(array(spin.eigenvalues), 'Ha', 'eV')
nstates = h5int(spin.number_of_states)
for st in range(nstates):
eig = eigs[st]
if eig < E_fermi:
stpath = path + '/state_{0}/psi_g'.format(st)
psi = array(h.get_path(stpath))
nk_orb = (psi**2).sum(1)
kin_orb = (kinetic * nk_orb).sum()
nelec_s += nk_orb.sum()
nk_s += nk_orb
kin_s.append(kin_orb)
eig_s.append(eig)
#end if
#end for
data[k, s] = obj(
kpoint=array(kp.reduced_k),
kin=array(kin_s),
eig=array(eig_s),
k=k_s,
nk=nk_s,
ne=nelec_s,
)
#end for
#end for
res = obj(
orbfile=filename,
E_fermi=E_fermi,
axes=axes,
kaxes=kaxes,
nkpoints=nkpoints,
nspins=nspins,
data=data,
)
return res
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import helpers
import hdfreader
from scipy.interpolate import interp1d
#Grid to interpolate to
wacam_heights_a = open('./pickle/heightpickle.obj', 'rb')
wacam_heights = pickle.load(wacam_heights_a)
wacam_heights = np.append(wacam_heights[:-1], np.array(
[0])) * 1000 #Extend the bottom layer to 0km from 0.61km
# ================= O3 ====================
df_o3 = hdfreader.read_hdf('../ndacc', 'O3')
o3_retr_time = hdfreader.find_closest_retrival(df_o3, "200309T7:15:00")
print("Closest O3 retrival", o3_retr_time)
o3_selected_retrival = df_o3.loc[o3_retr_time][
'O3.MIXING.RATIO.VOLUME_ABSORPTION.SOLAR']
o3_altitude = df_o3.loc[o3_retr_time]['ALTITUDE']
o3_pressure = df_o3.loc[o3_retr_time]['PRESSURE_INDEPENDENT']
o3_temperature = df_o3.loc[o3_retr_time]['TEMPERATURE_INDEPENDENT']
#interp_o3_f = interp1d(o3_altitude,o3_selected_retrival,fill_value="extrapolate", kind="linear")
#interp_o3 = interp_o3_f(wacam_heights)
plt.plot(o3_selected_retrival, o3_altitude)
plt.savefig('o3_profile')
def test_read():
import os
import numpy as np
import h5py
from hdfreader import read_hdf
ds = 'string value'
di = 100
df = np.pi
das = np.array(tuple('abcdefghijklmnopqrstuvwxyz'), dtype=bytes)
dai = np.arange(20, dtype=np.int64)
daf = 0.1 * np.arange(20, dtype=np.float64)
path = testing.setup_unit_test_output_directory(
'hdfreader', 'test_read')
def add_datasets(g):
g.create_dataset('sdata', data=das)
g.create_dataset('idata', data=dai)
g.create_dataset('fdata', data=daf)
#end def add_datasets
def add_attrs(g):
g.attrs['sval'] = ds
g.attrs['ival'] = di
g.attrs['fval'] = df
#end def add_attrs
def add_group(g, label=''):
g = g.create_group('group' + str(label))
add_attrs(g)
add_datasets(g)
return g
#end def add_group
testfile = os.path.join(path, 'test.h5')
f = h5py.File(testfile, 'w')
add_datasets(f)
g1 = add_group(f, 1)
g2 = add_group(f, 2)
g11 = add_group(g1, 1)
g12 = add_group(g1, 2)
g21 = add_group(g2, 1)
g22 = add_group(g2, 2)
f.close()
def check_datasets(g):
assert (value_eq(g.sdata, das))
assert (value_eq(g.idata, dai))
assert (value_eq(g.fdata, daf))
#end def check_datasets
def check_groups(g):
assert ('group1' in g)
assert ('group2' in g)
check_datasets(g.group1)
check_datasets(g.group2)
#end def check_groups
h = read_hdf(testfile)
check_datasets(h)
check_groups(h)
check_groups(h.group1)
check_groups(h.group2)
