149 lines
4.1 KiB
Python
149 lines
4.1 KiB
Python
#!/bin/env python
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__author__ = 'dongyun.zdy'
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import math
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import numpy as np
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from scipy.optimize import leastsq
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from scipy.optimize import curve_fit
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import sys
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from lmfit import Model
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import getopt
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import os
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#
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# def array_model_form(args):
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# # (
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# # Nelem,
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# # ) = args
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#
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# Telem_ence = 0.00898860
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# Telem_copy = 0.00631888
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#
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# Nelem = args
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#
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# ELEM_PER_PAGE = 1024
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# extend_cnt = math.ceil(math.log(float(Nelem)/ELEM_PER_PAGE, 2))
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# if extend_cnt < 0:
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# extend_cnt = 0
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# copy_cnt = ELEM_PER_PAGE * (math.pow(2, extend_cnt) - 1)
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#
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# total_cost = Telem_ence * Nelem
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# #total_cost += Tmem_alloc * extend_cnt
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# total_cost += Telem_copy * copy_cnt
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#
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# return total_cost
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def array_model_form(args,
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#Tstartup,
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Telem_ence,
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Telem_copy,
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#Tmem_alloc
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):
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# (
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# Nelem,
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# ) = args
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Nelem = args
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ELEM_PER_PAGE = 1024
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extend_cnt = math.ceil(math.log(float(Nelem)/ELEM_PER_PAGE, 2))
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if extend_cnt < 0:
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extend_cnt = 0
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copy_cnt = ELEM_PER_PAGE * (math.pow(2, extend_cnt) - 1)
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total_cost = Telem_ence * Nelem
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#total_cost += Tmem_alloc * extend_cnt
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total_cost += Telem_copy * copy_cnt
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return total_cost
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def material_model_arr(arg_sets,
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# Tstartup,
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Telem_ence,
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Telem_copy,
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#Tmem_alloc
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):
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res = []
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for single_arg_set in arg_sets:
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res.append(array_model_form(single_arg_set,
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# Tstartup,
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Telem_ence,
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Telem_copy,
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#Tmem_alloc
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))
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return np.array(res)
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material_model = Model(material_model_arr)
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# material_model.set_param_hint("Tstartup", min=0.0)
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material_model.set_param_hint("Telem_ence", min=0.0)
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material_model.set_param_hint("Telem_copy", min=0.0)
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#material_model.set_param_hint("Tmem_alloc", min=0.0)
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def extract_info_from_line(line):
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splited = line.split(",")
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line_info = []
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for item in splited:
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line_info.append(float(item))
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return line_info
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if __name__ == '__main__':
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#file_name = "scan_model.res.formal.prep"
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#out_file_name = "scan_model.fit"
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file_name = "array_result_final"
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out_file_name = "array_model"
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if os.path.exists(out_file_name):
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os.remove(out_file_name)
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#sys.argv.extend("-i arr.prep -o arr.model".split(" "))
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output_fit_res = True
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wrong_arg = False
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opts,args = getopt.getopt(sys.argv[1:],"i:o:")
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for op, value in opts:
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if "-i" == op:
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file_name = value
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elif "-o" == op:
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output_fit_res = True
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out_file_name = value
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else:
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wrong_arg = True
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if wrong_arg:
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print "wrong arg"
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sys.exit(1)
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file = open(file_name, "r")
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arg_sets = []
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times = []
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case_params = []
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for line in file:
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if line.startswith('#'):
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continue
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case_param = extract_info_from_line(line)
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case_params.append(case_param)
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arg_sets.append((case_param[0]))
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times.append(case_param[1])
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file.close()
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arg_sets_np = np.array(arg_sets)
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times_np = np.array(times)
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#10, 0.20406430879623488, 0.016618100054245379, 14.0, 4.5, 37.0, -0.005, 0.5, -7.0
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result = material_model.fit(times_np, arg_sets=arg_sets_np,
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# Tstartup=10.0,
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Telem_ence=1.0,
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Telem_copy=1.0,
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#Tmem_alloc=1.0
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)
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# res_line = str(result.best_values["Tstartup"]) + ","
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res_line = str(result.best_values["Telem_ence"]) + ","
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res_line += str(result.best_values["Telem_copy"])# + ","
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#res_line += str(result.best_values["Tmem_alloc"])
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print result.fit_report()
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if output_fit_res:
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out_file = open(out_file_name, "w")
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out_file.write(res_line)
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out_file.close()
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