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Simulation.py
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Simulation.py
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from RockPyV3.Functions.general import rotate
from Structure.sample import Sample
from scipy.stats import norm
import numpy as np
import matplotlib.pyplot as plt
class Simulation(object):
def __init__(self, parameters=None):
if not parameters: parameters = {}
self.parameters = parameters
class Sim_Thellier(Simulation):
def __init__(self, blocking_params=None, aniso_params=None, errors=None, **options):
if not blocking_params: blocking_params = {}
if not aniso_params: aniso_params = {}
if not errors: errors = {}
super(Sim_Thellier, self).__init__()
default_blocking_params = {'lab_field': 35.0,
'paleo_field': 35.0,
'mean_nrm': 510.0,
'skewness_nrm': -10,
'skewness_ptrm': -10, # - skewed to left
'w_nrm': 50.0,
'w_ptrm': 50.0,
'ptrm_t_diff': 2.0}
default_aniso_params = {'atrm_matrix': np.array([[1, 0., 0.],
[0., 1., 0.],
[0., 0., 1.]]),
'lab_field_direction': np.array([0, 0, 1]),
'paleo_field_direction': np.array([0, 0, 1]),
}
default_errors = {'alignment_error': 0,
'field_error': 0,
'temperature_error': 0}
default_steps = [20.0, 60.0, 100.0, 140.0, 185.0, 225.0, 265.0, 310.0, 350.0, 390.0, 430.0, 475.0, 515.0, 555.0,
600.0, 680.0]
''' OPTIONS '''
for key in default_blocking_params:
if key not in blocking_params:
blocking_params[key] = default_blocking_params[key]
for key in default_aniso_params:
if key not in aniso_params:
aniso_params[key] = default_aniso_params[key]
for key in default_errors:
if key not in errors:
errors[key] = default_errors[key]
# lists = {key: value for key, value in parameters.iteritems() if type(parameters[key]) == list}
self.__dict__.update(blocking_params)
self.__dict__.update(aniso_params)
self.__dict__.update(errors)
self.t_steps = options.get('t_steps', default_steps)
# this are the put in values for plots oven etc. There is no error yet
''' zero field steps '''
self.th_steps = self.t_steps
self.ac_steps = [self.th_steps[i] for i in range(1, len(self.t_steps), 3)]
self.tr_steps = [self.th_steps[i] for i in range(1, len(self.t_steps), 3)]
''' in field steps '''
self.pt_steps = self.t_steps
self.ck_steps = [self.th_steps[i] for i in range(1, len(self.t_steps), 2)]
''' adding temperature error '''
if not self.temperature_error <= 0:
self.th_temps = self.th_steps + np.random.normal(0, self.temperature_error, len(self.th_steps))
self.ac_temps = self.ac_steps + np.random.normal(0, self.temperature_error, len(self.ac_steps))
self.tr_temps = self.tr_steps + np.random.normal(0, self.temperature_error, len(self.tr_steps))
self.pt_temps = self.pt_steps + np.random.normal(0, self.temperature_error, len(self.pt_steps))
self.ck_temps = self.ck_steps + np.random.normal(0, self.temperature_error, len(self.ck_steps))
else: # error cannot be <=0 -> no arror added
self.th_temps = self.th_steps
self.ac_temps = self.ac_steps
self.tr_temps = self.tr_steps
self.pt_temps = self.pt_steps
self.ck_temps = self.ck_steps
''' field errors '''
if not self.field_error <= 0:
self.ptrm_fields = np.random.normal(0, self.field_error, len(self.pt_steps)) + self.lab_field
self.ck_fields = np.random.normal(0, self.field_error, len(self.ck_steps)) + self.lab_field
else:
self.ptrm_fields = np.ones(len(self.pt_steps)) * self.lab_field
self.ck_fields = np.ones(len(self.ck_steps)) * self.lab_field
''' field errors '''
if not self.alignment_error <= 0:
self.ptrm_field_directions = [rotate(xyz=self.lab_field_direction, degree=i) for i in
np.random.normal(0, self.alignment_error, len(self.pt_steps))]
self.ck_field_directions = [rotate(xyz=self.lab_field_direction, degree=i) for i in
np.random.normal(0, self.alignment_error, len(self.ck_steps))]
else:
self.ptrm_field_directions = np.array([self.lab_field_direction for i in range(len(self.pt_steps))])
self.ck_field_directions = np.array([self.lab_field_direction for i in range(len(self.ck_steps))])
''' generate sample and measurements '''
self.sample = Sample(name='Thellier Simulation')
self.sample.add_measurement(mtype='palint', mfile='', machine='simulation')
N = len(self.th_steps) + len(self.ck_steps) + len(self.pt_steps) + len(self.ac_steps) + len(self.tr_steps)
''' TH Steps '''
self.nrm = np.dot(self.atrm_matrix, self.paleo_field_direction) * self.paleo_field
m_nrm, m_ptrm = self.data()
self.th = np.array([self.nrm * m_nrm[np.argmin(abs(i - m_nrm[:, 0])), 1] for i in self.th_temps])
th_m = [np.linalg.norm(i) for i in self.th]
self.th = np.c_[self.th_steps, self.th[:, 0], self.th[:, 1], self.th[:, 2], th_m]
''' PTRM '''
m_ptrm_calc = np.array([m_ptrm[np.argmin(abs(i - m_ptrm[:, 0])), 1] for i in self.pt_temps])
self.ptrm = np.array(
[np.dot(self.atrm_matrix, self.ptrm_field_directions[i]) * self.ptrm_fields[i] * m_ptrm_calc[i]
for i in range(len(self.ptrm_field_directions))])
self.ptrm = np.c_[
self.pt_steps, self.ptrm[:, 0], self.ptrm[:, 1], self.ptrm[:, 2], map(np.linalg.norm, self.ptrm)]
m_ck_calc = np.array([m_ptrm[np.argmin(abs(i - m_ptrm[:, 0])), 1] for i in self.ck_temps])
ck = np.array([np.dot(self.atrm_matrix, self.ck_field_directions[i]) * self.ck_fields[i] * m_ck_calc[i]
for i in range(len(self.ck_field_directions))])
ck = [ck[i] + self.th[j, 1:4] for i in range(len(self.ck_steps)) for j in range(len(self.th_steps))
if self.th_steps[j] == self.ck_steps[i]]
''' SUM '''
self.sum = self.th[:, 1:4] + self.ptrm[:, 1:4]
self.sum = np.c_[self.pt_steps, self.sum[:, 0], self.sum[:, 1], self.sum[:, 2], map(np.linalg.norm, self.sum)]
# self.ptrm = np.array([])
# plt.plot(self.th[:, 0], self.th[:, 4])
# plt.plot(self.ptrm[:, 0], self.ptrm[:, 4])
# plt.plot(self.sum[:, 0], self.sum[:, 4])
# plt.plot([35, 0], [0, 35], '--')
# plt.plot(self.ptrm[:, 4], self.th[:, 4])
# plt.show()
def skew(self, temps, mean=0, w=1, a=0):
t = (temps - mean) / w
return 2 * norm.pdf(t) * norm.cdf(a * t)
def data(self, check=False):
mean_ptrm = self.mean_nrm + self.ptrm_t_diff
t = np.arange(0, 700, 0.1)
p_nrm = self.skew(t, self.mean_nrm, self.w_nrm, self.skewness_nrm)
p_ptrm = self.skew(t, mean_ptrm, self.w_ptrm, self.skewness_ptrm)
p_nrm /= np.sum(p_nrm)
p_ptrm /= np.sum(p_ptrm)
m_nrm = np.array([1 - np.sum(p_nrm[:i]) for i in range(len(t))])
m_ptrm = np.array([np.sum(p_ptrm[:i]) for i in range(len(t))])
if check:
plt.plot(m_nrm)
plt.plot(m_ptrm)
plt.show()
m_nrm = np.c_[t, m_nrm]
m_ptrm = np.c_[t, m_ptrm]
return m_nrm, m_ptrm
# todo outputs a sample object
if __name__ == '__main__':
test = Sim_Thellier(blocking_params={'ptrm_t_diff': 0, 'lab_field': 35.0, 'w_ptrm': 50},
errors={'field_error': 0.0, 'temperature_error': 0.0, 'alignment_error': 0.0},
t_steps=np.arange(0, 700, 50))