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restructured advanced example

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This commit is contained in:
Richard Hartmann 2014-09-15 13:29:36 +02:00
parent 3578bf26cd
commit d0754c29ed
5 changed files with 94 additions and 80 deletions
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35
advanced_example/calculations.py Normal file
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@ -0,0 +1,35 @@
import numpy as np
from scipy.special import gamma as scipy_gamma_func
def alpha_func(tau, eta, Gamma, s):
return eta * (Gamma / (1 + 1j*tau))**(s+1) * scipy_gamma_func(s)
def x_to_g_w(x):
n = len(x) // 3
g_re = x[0*n:1*n]
g_im = x[1*n:2*n]
w = x[2*n:3*n]
return g_re + 1j*g_im, w, n
def alpha_apprx(tau, g, w):
"""
alpha = sum_i g_i * exp(-w_i * tau)
"""
n_tau = len(tau)
tau = tau.reshape((n_tau,1))
res = np.sum(g * np.exp(-w * tau), axis=1)
return res
def alpha_apprx_x(tau, x):
g, w, n = x_to_g_w(x)
g = g.reshape((1,n))
w = w.reshape((1,n))
return alpha_apprx(tau, g, w)
def diff(x, tau, alpha_true, p):
alpha = alpha_apprx_x(tau, x)
rel_diff = np.abs(alpha_true - alpha)/np.abs(alpha_true)
max_diff = np.max(rel_diff)
mean_rel_diff = np.mean(rel_diff)
return p*mean_rel_diff + (1-p)*max_diff

0
example_client.py → advanced_example/client.py
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135
example.py → advanced_example/my_jobmanager_classes.py
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@ -1,56 +1,22 @@
import os, sys
sys.path.append(os.path.abspath("../"))
import jobmanager as jm
import numpy as np
from scipy.special import gamma as scipy_gamma_func
from calculations import diff, alpha_func
from scipy.optimize import minimize
import time
import numpy as np
import matplotlib.pyplot as plt
def alpha_func(tau, eta, Gamma, s):
return eta * (Gamma / (1 + 1j*tau))**(s+1) * scipy_gamma_func(s)
def x_to_g_w(x):
n = len(x) // 3
g_re = x[0*n:1*n]
g_im = x[1*n:2*n]
w = x[2*n:3*n]
return g_re + 1j*g_im, w, n
def alpha_apprx(tau, g, w):
"""
alpha = sum_i g_i * exp(-w_i * tau)
"""
n_tau = len(tau)
tau = tau.reshape((n_tau,1))
res = np.sum(g * np.exp(-w * tau), axis=1)
return res
def alpha_apprx_x(tau, x):
g, w, n = x_to_g_w(x)
g = g.reshape((1,n))
w = w.reshape((1,n))
return alpha_apprx(tau, g, w)
def diff(x, tau, alpha_true, p):
alpha = alpha_apprx_x(tau, x)
rel_diff = np.abs(alpha_true - alpha)/np.abs(alpha_true)
max_diff = np.max(rel_diff)
mean_rel_diff = np.mean(rel_diff)
return p*mean_rel_diff + (1-p)*max_diff
class FitFunc_Client(jm.JobManager_Client):
def __init__(self):
super(FitFunc_Client, self).__init__(ip="localhost",
super(FitFunc_Client, self).__init__(ip="tqo07",
authkey='fit function example',
port = 42524,
nproc = 0,
nice=19,
no_warings=True,
verbose=1)
@staticmethod
def func(args, const_args):
eta, Gamma, s, p, tau_max, tau_n = const_args
@ -71,23 +37,19 @@ class FitFunc_Server(jm.JobManager_Server):
# setup init parameters for the ancestor class
authkey = 'fit function example'
fname_for_final_result_dump = 'FitFunc_final_result'
fname_dump = None
const_args = const_args
port = 42524
verbose = 2
verbose = 1
msg_interval = 1
fname_for_args_dump = 'auto'
fname_for_fail_dump = 'auto'
# init ancestor class
super(FitFunc_Server, self).__init__(authkey=authkey,
fname_for_final_result_dump=fname_for_final_result_dump,
const_args = const_args,
port = port,
verbose = verbose,
msg_interval = msg_interval,
fname_for_args_dump = fname_for_args_dump,
fname_for_fail_dump = fname_for_fail_dump)
const_arg = const_args,
port = port,
verbose = verbose,
msg_interval = msg_interval,
fname_dump = fname_dump)
self.final_result = None
for i in range(num_samples):
@ -104,12 +66,14 @@ class FitFunc_Server(jm.JobManager_Server):
g, w, n = x_to_g_w(x)
if ((self.final_result == None) or
(self.final_result[0] > fun)):
print("\nnew result {}".format(fun))
self.final_result = (fun, g, w)
def process_final_result(self):
print("final Res")
if self.final_result != None:
eta, Gamma, s, p, tau_max, tau_n = self.const_args
eta, Gamma, s, p, tau_max, tau_n = self.const_arg
(fun, g, w) = self.final_result
tau = np.linspace(0, tau_max, tau_n)
@ -125,36 +89,47 @@ class FitFunc_Server(jm.JobManager_Server):
plt.grid()
plt.show()
args = {}
args['eta'] = 1
args['Gamma'] = 1
args['s'] = 0.7
args['p'] = 0.99
args['tau_max'] = 2
args['tau_n'] = 500
args['num_samples'] = 300
args['n'] = 5
args['g_max'] = 10
args['w_max'] = 5
const_args = (args['eta'],
args['Gamma'],
args['s'],
args['p'],
args['tau_max'],
args['tau_n'])
def FitFunc_Server_from_args():
return FitFunc_Server(const_args = const_args,
num_samples = args['num_samples'],
n = args['n'],
g_max = args['g_max'],
w_max = args['w_max'])
if __name__ == "__main__":
debug = False
eta = 1
Gamma = 1
s = 0.7
p = 0.5
tau_max = 2
tau_n = 500
fitfunc_server = FitFunc_Server(const_args=(eta, Gamma, s, p, tau_max, tau_n),
num_samples=500,
n=5,
g_max=100,
w_max=10)
fitfunc_server = FitFunc_Server_from_args()
if debug:
# for debug reasons only
# note the server does not get started, but as the init
# function of the subclass generates the arguments
# we can check if they can be process by the
# clinet's static function func
arg0 = fitfunc_server.job_q.get()
x, fun = FitFunc_Client.func(arg0, const_args=(eta, Gamma, s, p))
print("arg0 :", arg0)
print("x :", x)
print("fmin :", fun)
else:
fitfunc_server.start()
# note the server does not get started, but as the init
# function of the subclass generates the arguments
# we can check if they can be process by the
# clinet's static function func
arg0 = fitfunc_server.job_q.get()
x, fun = FitFunc_Client.func(arg0, const_args=const_args)
print("arg0 :", arg0)
print("x :", x)
print("fmin :", fun)

4
advanced_example/server.py Normal file
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@ -0,0 +1,4 @@
from example import FitFunc_Server_from_args
with FitFunc_Server_from_args() as fitfunc_server:
fitfunc_server.start()

0
simple_example.py → simple_example/simple_example.py
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