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Add universal saving/loading functions based on h5 format #165

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78b3b71
Added functions to save/load to/from h5 files, with example script
cowalz Apr 7, 2025
7c5d0ca
fixed small error in jupyter file
cowalz Apr 7, 2025
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554 changes: 554 additions & 0 deletions example.ipynb
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146 changes: 146 additions & 0 deletions example.py
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# %%
import udkm1Dsim as ud
import matplotlib.pyplot as plt
import numpy as np
import time

import example_materials.sap as sap_gen
import example_materials.Nb as Nb_gen
import example_materials.TbFe2_110 as TbFe2_110
import example_materials.Al as Al_gen
u = ud.u # import pint units

# %%
# import 1TM data for various materials (constants, unit cell, ...)
sap = sap_gen.sap_1TM()
Nb = Nb_gen.Nb_1TM()
TbFe2 = TbFe2_110.TbFe2_110_1TM()
Al = Al_gen.Al_1TM()

# %%
nAl = 20 # in 0.1nm steps
nTbFe2 = 200 # in 0.1nm steps
nNb = 500 # in 0.1nm steps
nSap = 1200 # in 0.1nm steps
num_unit_cell = [nAl, nTbFe2, nNb, nSap]


fluenz_sim = [6] * u.mJ / u.cm**2 # Pump Puls Parameter
puls_width = [0.15] * u.ps
pump_delay = [0] * u.ps
multi_abs = True # absorption: lambert-beer vs. multilayer (better model)
init_temp = 300
heat_diff = True
delays = np.r_[-2:20:0.1] * u.ps # untersuchte Zeitskala

sample_name = 'TbFe30 Sample'
layers = ['Al', 'TbFe2', 'Nb', 'sap'] # define layers material
sample_dic = {'Al': Al, 'TbFe2': TbFe2, 'Nb': Nb, 'sap': sap}
properties = {'Al': {'C': Al.prop['heat_capacity']},
'TbFe2': {'C': TbFe2.prop['heat_capacity']},
'Nb': {'C': Nb.prop['heat_capacity']},
'sap': {'C': sap.prop['heat_capacity']}}


for l in range(len(layers)): # add parameters dictionary for the unit cell of each layer
prop_aml = {}
prop_aml['a_axis'] = sample_dic[layers[l]].prop['a_axis']
prop_aml['b_axis'] = sample_dic[layers[l]].prop['b_axis']
prop_aml['sound_vel'] = sample_dic[layers[l]].prop['sound_vel']
prop_aml['lin_therm_exp'] = sample_dic[layers[l]].prop['lin_therm_exp']
prop_aml['heat_capacity'] = sample_dic[layers[l]].prop['heat_capacity']
prop_aml['therm_cond'] = sample_dic[layers[l]].prop['therm_cond']
prop_aml['opt_pen_depth'] = sample_dic[layers[l]].prop['opt_pen_depth']
prop_aml['opt_ref_index'] = sample_dic[layers[l]].prop['opt_ref_index']
prop_aml['phonon_damping'] = sample_dic[layers[l]].prop['phonon_damping']
properties[layers[l]]['amorphous_layer'] = ud.AmorphousLayer(
layers[l], layers[l], 0.1 * u.nm, sample_dic[layers[l]].prop['density'], **prop_aml)

S = ud.Structure(sample_name) # create empty sample (structure)
for l in range(len(layers)): # add all previously specified layers to the structure
S.add_sub_structure(properties[layers[l]]['amorphous_layer'], num_unit_cell[l])
S.visualize() # plot the structure diagram
print(S) # print structure information

_, _, distances = S.get_distances_of_layers()

# %%
''' Determine the optical absorption from the excitation conditions '''

h = ud.Heat(S, True) # wärme initialisieren, dann anregung simulieren
h.excitation = {'fluence': fluenz_sim, 'delay_pump': pump_delay, 'pulse_width': puls_width, 'backside': False,
'multilayer_absorption': multi_abs, 'wavelength': 800 * u.nm, 'theta': 90 * u.deg}

dAdzLB = h.get_Lambert_Beer_absorption_profile()
dAdz, _, _, _ = h.get_multilayers_absorption_profile()

# %%
'''Plot the absorption profile'''

plt.figure()
plt.plot(distances.to('nm'), dAdz * 1e-9 * 1e2, label=r'Multilayer')
plt.plot(distances.to('nm'), dAdzLB * 1e-9 * 1e2, label=r'Lambert-Beer')
plt.xlim(0, 100)
plt.legend()
plt.xlabel('Distance (nm)')
plt.ylabel('Differnetial Absorption (%)')
plt.title('Laser Absorption Profile')
plt.show()

# %%
''' Get Temperature Map from the absorption profile including heat diffusion '''


h.save_data = False
h.disp_messages = True
# h.ode_options = {'max_step':1e-11}
# h.progress_bar = True
h.heat_diffusion = heat_diff
h.boundary_conditions = {'top_type': 'isolator', 'bottom_type': 'isolator'}

Init_temp = init_temp

print(h)

temp_map, delta_temp_map = h.get_temp_map(delays, Init_temp)
# %% temp maps plotten für e- und ph
plt.figure(figsize=[6, 5])
plt.subplot(1, 1, 1)
plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map[:, :],
shading='auto', cmap='RdBu_r', vmin=np.min(temp_map[:, :]), vmax=np.max(temp_map[:, :]))
plt.colorbar()
plt.xlim(0, 100)
plt.xlabel('Distance (nm)')
plt.ylabel('Delay (ps)')
plt.title('Phonon')
plt.tight_layout()
plt.show()

# %%
''' Get the picosecond strain dynamics from the Temperature Map '''

pnum = ud.PhononNum(S, True)
pnum.disp_messages = True
# pnum.progress_bar = True
pnum.save_data = False
strain_map = pnum.get_strain_map(delays, temp_map, delta_temp_map)

# %% und plotten
plt.figure(figsize=[6, 0.68 * 6], dpi=300)
plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, 1e3 * strain_map, shading='auto',
cmap='seismic', vmin=-1 * np.max(1e3 * strain_map), vmax=1 * np.max(1e3 * strain_map))
plt.colorbar()
plt.xlim(0, 100)
# plt.ylim(-2, 0)
plt.xlabel('Distance (nm)')
plt.ylabel('Delay (ps)')
plt.title(r'Strain Map ($10^{-3}$)')
plt.tight_layout()
plt.show()

# %%
ud.helpers.save_to_h5('example_data.h5', delays, distances, S, abs_profile=dAdz,
temp_map=temp_map, strain_map=strain_map)

# %%
ud.helpers.read_from_h5('example_data.h5')
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34 changes: 34 additions & 0 deletions example_materials/Al.py
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# -*- coding: utf-8 -*-
"""
Created on Sat Oct 9 09:44:23 2021

@author: matte
"""

import numpy as np
import udkm1Dsim as ud
u = ud.u


class Al_1TM:
def __init__(self):

self.Al = ud.Atom('Al')

self.prop = {}
self.prop['crystal_struc'] = 'fcc'
self.prop['c_axis'] = 1*u.angstrom # periodictable.com -- fcc geometry: 3.524*np.sqrt(3)/3
self.prop['a_axis'] = 1*u.angstrom # adjust density
self.prop['b_axis'] = 1*u.angstrom # adjust density

self.prop['density'] = 2700*u.kg/(u.m**3)
self.prop['deb_wal_fac'] = 0*u.m**2

self.prop['sound_vel'] = 5.1*u.nm/u.ps # calculated -- np.sqrt(c33/density)
self.prop['phonon_damping'] = 0*u.kg/u.s

self.prop['lin_therm_exp'] = 23.1e-6 # calculated: exp_c_axis*(1+2*c_13/c_33)
self.prop['heat_capacity'] = 897*u.J/(u.kg * u.K) # ph: 10.1016/0022-3697(81)90174-8
self.prop['therm_cond'] = 235*u.W/(u.m * u.K) # 10.1016/S0301-0104(99)00330-4
self.prop['opt_pen_depth'] = np.inf*u.nm # (800nm) estimation
self.prop['opt_ref_index'] = 0.49 + 4.84j # (800nm, thick film) Werner, J. Phys. Chem. Ref. Data 38 (2009)
53 changes: 53 additions & 0 deletions example_materials/Nb.py
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# -*- coding: utf-8 -*-
"""
Created on Sat Oct 9 09:44:23 2021

@author: matte
"""

import numpy as np
import udkm1Dsim as ud
u = ud.u


class Nb_1TM:
def __init__(self):

self.Nb = ud.Atom('Nb')

self.prop = {}
#self.prop['crystal_struc'] = 'fcc'
self.prop['c_axis'] = 4.667*u.angstrom # periodictable.com -- fcc geometry: 3.524*np.sqrt(3)/3
self.prop['a_axis'] = 4.667*u.angstrom # adjust density
self.prop['b_axis'] = 3.3*u.angstrom # adjust density
#self.prop['molar_mass'] = 58.69*u.g
self.prop['density'] = 8580*u.kg/(u.m**3)
self.prop['deb_wal_fac'] = 0*u.m**2
#self.prop['elastic_c11'] = 327e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
#self.prop['elastic_c12'] = 128e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
#self.prop['elastic_c13'] = 103e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
#self.prop['elastic_c22'] = 327e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
#self.prop['elastic_c23'] = 103e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
#self.prop['elastic_c33'] = 351e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
self.prop['sound_vel'] = 5.160*u.nm/u.ps # calculated -- np.sqrt(c33/density)
self.prop['phonon_damping'] = 0*u.kg/u.s
#self.prop['exp_c_axis'] = 12.7e-6 # calculated: Grun*heat_cap*dens/(c_13+c_23+c_33)
#self.prop['exp_a_axis'] = 12.7e-6 # calculated: Grun*heat_cap*dens/(c_13+c_23+c_33)
#self.prop['exp_b_axis'] = 12.7e-6 # calculated: Grun*heat_cap*dens/(c_13+c_23+c_33)
self.prop['lin_therm_exp'] = 6.89e-6 # calculated: exp_c_axis*(1+2*c_13/c_33)
#self.prop['Grun_c_axis'] = 1.8 # 10.1063/1.2902170
#self.prop['Grun_a_axis'] = 1.8 # 10.1063/1.2902170
#self.prop['Grun_b_axis'] = 1.8 # 10.1063/1.2902170
self.prop['heat_capacity'] = 260*u.J/(u.kg * u.K) # ph: 10.1016/0022-3697(81)90174-8
self.prop['therm_cond'] = 53.3*u.W/(u.m * u.K) # 10.1016/S0301-0104(99)00330-4
self.prop['opt_pen_depth'] = np.inf*u.nm # (800nm) estimation
self.prop['opt_ref_index'] = 2.3344 + 3.2409j # (800nm, thick film) Werner, J. Phys. Chem. Ref. Data 38 (2009)
#self.prop['opt_ref_index_per_strain'] = 0+0j

def createUnitCell(self, name, caxis, prop):
Nb = ud.UnitCell(name, 'Nb', caxis, **prop)
Nb.add_atom(self.Nb,0)
Nb.add_atom(self.Nb,0)
Nb.add_atom(self.Nb,0.5)
Nb.add_atom(self.Nb,0.5)
return Nb
114 changes: 114 additions & 0 deletions example_materials/TbFe.py
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# -*- coding: utf-8 -*-
"""
Created on Sat Oct 9 09:44:23 2021

@author: matte
"""

import numpy as np
import udkm1Dsim as ud
u = ud.u


class TbFe_1TM:
def __init__(self):

self.Tb = ud.Atom('Tb')
self.Fe = ud.Atom('Fe')

self.prop = {}
#self.prop['crystal_struc'] = 'fcc'
self.prop['c_axis'] = 7.347*np.sqrt(2)*u.angstrom # periodictable.com -- fcc geometry: 3.524*np.sqrt(3)/3
self.prop['a_axis'] = 7.347*u.angstrom # adjust density
self.prop['b_axis'] = 7.347*np.sqrt(2)*u.angstrom # adjust density
#self.prop['molar_mass'] = 58.69*u.g
self.prop['density'] = 9170*u.kg/(u.m**3)
self.prop['deb_wal_fac'] = 4.5*1e9*u.angstrom**2
#self.prop['elastic_c11'] = 327e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
#self.prop['elastic_c12'] = 128e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
#self.prop['elastic_c13'] = 103e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
#self.prop['elastic_c22'] = 327e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
#self.prop['elastic_c23'] = 103e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
#self.prop['elastic_c33'] = 351e9*u.kg/(u.m*u.s**2) # 10.1063/1.1702218: c11=253, c12=152, c44=124
self.prop['sound_vel'] = 3.94*u.nm/u.ps # calculated -- np.sqrt(c33/density)
self.prop['phonon_damping'] = 0*u.kg/u.s
#self.prop['exp_c_axis'] = 12.7e-6 # calculated: Grun*heat_cap*dens/(c_13+c_23+c_33)
#self.prop['exp_a_axis'] = 12.7e-6 # calculated: Grun*heat_cap*dens/(c_13+c_23+c_33)
#self.prop['exp_b_axis'] = 12.7e-6 # calculated: Grun*heat_cap*dens/(c_13+c_23+c_33)
self.prop['lin_therm_exp'] = 23.75e-6 # calculated: exp_c_axis*(1+2*c_13/c_33)
#self.prop['Grun_c_axis'] = 1.8 # 10.1063/1.2902170
#self.prop['Grun_a_axis'] = 1.8 # 10.1063/1.2902170
#self.prop['Grun_b_axis'] = 1.8 # 10.1063/1.2902170
self.prop['heat_capacity'] = 330*u.J/(u.kg * u.K) # ph: 10.1016/0022-3697(81)90174-8
self.prop['therm_cond'] = 5*u.W/(u.m * u.K) # 10.1016/S0301-0104(99)00330-4
self.prop['opt_pen_depth'] = 18*u.nm # (800nm) estimation
self.prop['opt_ref_index'] = 2.2361 + 4.472j # (800nm, thick film) Werner, J. Phys. Chem. Ref. Data 38 (2009)
#self.prop['opt_ref_index_per_strain'] = 0+0j

def createUnitCell(self, name, caxis, prop):
TbFe = ud.UnitCell(name, 'TbFe', caxis, **prop)
#TbFe2 along 110:
pos=0
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)

pos=0.125
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)

pos=0.25
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)

pos=0.375
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)

pos=0.5
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)

pos=0.625
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)

pos=0.75
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Tb,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)

pos=0.875
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
TbFe.add_atom(self.Fe,pos)
return TbFe
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