動作環境
GeForce GTX 1070 (8GB)
ASRock Z170M Pro4S [Intel Z170chipset]
Ubuntu 14.04 LTS desktop amd64
TensorFlow v0.11
cuDNN v5.1 for Linux
CUDA v8.0
Python 2.7.6
IPython 5.1.0 -- An enhanced Interactive Python.
gcc (Ubuntu 4.8.4-2ubuntu1~14.04.3) 4.8.4
数値光散乱シミュレーションで出力されるチェックポイントファイルの読込みをCで実装した。
http://qiita.com/7of9/items/0fbea38b48cdfe4588dd
これをmatplotlibで読むためにPython実装に変更しようとしている。
参考: C / Python > Cでfwrite()した値をPythonで読込む
v0.1-v0.3: http://qiita.com/7of9/items/68673ac3239532064c28
v0.5
- PEP8対応
- Cと同じ内容まで実装
- read scalars[], xvec[], rvec[], pvec[], vectors[][]
C実装: http://qiita.com/7of9/items/0fbea38b48cdfe4588dd
read_chpoint.py
import numpy as np
import array
import sys
'''
v0.5 Dec. 23, 2016
- read scalars[], xvec[], rvec[], pvec[], vectors[][]
- refactor according to PEP8 (except for E501 line too long for long comment)
- wrap_fromfile() takes [num] arg
v0.4 Dec. 21, 2016
- read from "auxiliary" file [auxfp]
+ add read_auxiliary_info()
v0.3 Dec. 19, 2016
- add wrap_fromfile()
- read [inprodR],[prev_err],[resid_scale]
v0.2 Dec. 19, 2016
- fix bug > read [local_nRows] for "size_t" type
v0.1 Dec. 18, 2016
- read_chpoint_file() > read [ind_m],[local_nRows],[niter],[counter]
'''
def wrap_fromfile(rfp, typecode, num):
res = array.array(typecode)
res.fromfile(rfp, num)
return res
def read_auxiliary_info(auxFilename):
with open(auxFilename, "rb") as auxfp:
sc_N = wrap_fromfile(auxfp, 'i', num=1) # the number of scalars' sizes
sc_sizes = array.array('i') #
sc_sizes.fromfile(auxfp, *sc_N) # '*':unpack list
vec_N = wrap_fromfile(auxfp, 'i', num=1) # the number of vercotrs' sizes
vec_sizes = array.array('i') #
vec_sizes.fromfile(auxfp, *vec_N) # '*':unpack list
return sc_N, sc_sizes, vec_N, vec_sizes
# TODO: 0m > error handling when file is NULL
def read_chpoint_file(chpFilename, auxFilename):
print(chpFilename)
print(auxFilename)
# TODO: 0m > error handling when file is NULL
with open(chpFilename, "rb") as chpfp:
ind_m = wrap_fromfile(chpfp, 'i', num=1) # index of iterative method
print('ind_m:', ind_m)
# number of local rows of decomposition (only real dipoles)
# where L: unsigned long = size_t
local_nRows = wrap_fromfile(chpfp, 'L', num=1)
print('local_nRows:', local_nRows)
niter = wrap_fromfile(chpfp, 'i', num=1) # iteration count
print('niter:', niter)
# number of successive iterations without residual decrease
counter = wrap_fromfile(chpfp, 'i', num=1)
print('counter:', counter)
# used as |r_0|^2 and best squared norm of residual up to some iteration
inprodR = wrap_fromfile(chpfp, 'd', num=1)
print('inprodR:', inprodR)
# previous relative error; used in ProgressReport, initialized in IterativeSolver
prev_err = wrap_fromfile(chpfp, 'd', num=1)
print('prev_err:', prev_err)
# scale to get square of relative error
resid_scale = wrap_fromfile(chpfp, 'd', num=1)
print('resid_scale:', resid_scale) # scale to get square of relative error
# sc_N: the number of scalars' sizes
# sc_sizes:
# vec_N: the number of vercotrs' sizes
# vec_sizes:
sc_N, sc_sizes, vec_N, vec_sizes = read_auxiliary_info(auxFilename)
print('sc_N:', sc_N)
print('sc_sizes', sc_sizes)
print('vec_N:', vec_N)
print('vec_sizes:', vec_sizes)
# scalars[]
scalars = []
for idx in range(sc_N[0]):
if sc_sizes[idx] is 8: # double
scl = wrap_fromfile(chpfp, 'd', num=1)
scalars.append(scl)
elif sc_sizes[idx] is 16: # double complex
scl = wrap_fromfile(chpfp, 'd', num=2)
scalars.append(scl)
for idx in range(sc_N[0]):
print('scalars:', scalars[idx])
# xvec[] : total electric field on the dipoles
# TODO: 0m > replace 'local_nRows[0]' with function?
# TODO: 0m > replace 'vec_N[0]' with function?
# TODO: 0m > define function for read [drel,dimg]??
xvec = [[] for idx in range(local_nRows[0])]
for idx in range(local_nRows[0]):
drel = wrap_fromfile(chpfp, 'd', 1)
dimg = wrap_fromfile(chpfp, 'd', 1)
xvec[idx] = [drel, dimg]
# rvec[] : current residual
rvec = [[] for idx in range(local_nRows[0])]
for idx in range(local_nRows[0]):
drel = wrap_fromfile(chpfp, 'd', 1)
dimg = wrap_fromfile(chpfp, 'd', 1)
rvec[idx] = [drel, dimg]
# pvec[] : polarization of dipoles, also an auxiliary vector in iterative solvers
pvec = [[] for idx in range(local_nRows[0])]
for idx in range(local_nRows[0]):
drel = wrap_fromfile(chpfp, 'd', 1)
dimg = wrap_fromfile(chpfp, 'd', 1)
pvec[idx] = [drel, dimg]
# vectors[] : ???
MAXNUM_VECTORS = 20
vectors = [[] for idx in range(MAXNUM_VECTORS)]
for idx_vecN in range(vec_N[0]):
alist = []
for idx_LnRows in range(local_nRows[0]):
if vec_sizes[idx_vecN] is 16:
drel = wrap_fromfile(chpfp, 'd', 1)
dimg = wrap_fromfile(chpfp, 'd', 1)
alist.append([drel, dimg])
vectors[idx_vecN] = alist
#
for idx in range(3):
print('xvec:',xvec[idx])
print('rvec:',rvec[idx])
print('pvec:',pvec[idx])
print('vectors:',vectors[idx][0])
print('vectors:',vectors[idx][1])
print('vectors:',vectors[idx][2])
argvs = sys.argv
argc = len(argvs)
print argvs
if (argc < 3):
print("ERROR: chpoint file is not specified\r\n")
print(" [cmd] [chpoint file] [auxiliary file]\r\n")
sys.exit()
read_chpoint_file(chpFilename=argvs[1], auxFilename=argvs[2])
Cとの比較
C実行
ind_m:5
local_nRows:27984
niter:209
counter:139
inprodR:4.317
prev_err:0.320
resid_scale:0.020
Python実行
('ind_m:', array('i', [5]))
('local_nRows:', array('L', [27984L]))
('niter:', array('i', [209]))
('counter:', array('i', [139]))
('inprodR:', array('d', [4.317011265934948]))
('prev_err:', array('d', [0.3198525404317458]))
('resid_scale:', array('d', [0.020384616751203153]))
C実行
sc_N:8
sc_sizes[]:8
sc_sizes[]:8
sc_sizes[]:8
sc_sizes[]:8
sc_sizes[]:16
sc_sizes[]:16
sc_sizes[]:16
sc_sizes[]:16
vec_N:3
vec_sizes[]:16
vec_sizes[]:16
vec_sizes[]:16
Python実行
('sc_N:', array('i', [8]))
('sc_sizes', array('i', [8, 8, 8, 8, 16, 16, 16, 16]))
('vec_N:', array('i', [3]))
('vec_sizes:', array('i', [16, 16, 16]))
C実行
xvec:(0.000916,-0.001571), rvec:(-0.002100,0.002827), pvec:(-0.001287,-0.008525)
xvec:(0.032771,0.090957), rvec:(0.004384,-0.023016), pvec:(-0.005860,0.025872)
xvec:(-0.004613,-0.000545), rvec:(0.005385,-0.006732), pvec:(-0.000544,0.022825)
xvec:(-0.000916,0.001571), rvec:(0.002100,-0.002827), pvec:(0.001287,0.008525)
xvec:(0.032771,0.090957), rvec:(0.004384,-0.023016), pvec:(-0.005860,0.025872)
vectors 1:(-0.203491,0.033598), 2:(0.513358,-0.235685), 3:(0.548095,0.061967)
vectors 1:(0.100941,-0.212583), 2:(-0.220141,0.644602), 3:(-0.386403,0.429201)
vectors 1:(-0.000433,0.008886), 2:(0.007084,-0.024328), 3:(0.006453,-0.022867)
Python実行
('xvec:', [array('d', [0.0009161390559393775]), array('d', [-0.001570522583473328])])
('rvec:', [array('d', [-0.0020997633140212722]), array('d', [0.0028267192546817064])])
('pvec:', [array('d', [-0.0012872008298920184]), array('d', [-0.008525276560774427])])
('vectors:', [array('d', [-0.20349115145116184]), array('d', [0.03359754374072836])])
('vectors:', [array('d', [0.5133580879635192]), array('d', [-0.23568549427068541])])
('vectors:', [array('d', [0.548094579220016]), array('d', [0.061967135670311146])])
('xvec:', [array('d', [0.03277106724041005]), array('d', [0.09095666869781775])])
('rvec:', [array('d', [0.004384056712075103]), array('d', [-0.023015736282339546])])
('pvec:', [array('d', [-0.0058598173209674954]), array('d', [0.025872335594481318])])
('vectors:', [array('d', [0.1009411988714421]), array('d', [-0.21258258378933656])])
('vectors:', [array('d', [-0.22014111334002046]), array('d', [0.644601864206821])])
('vectors:', [array('d', [-0.3864030960612225]), array('d', [0.42920073139253534])])
('xvec:', [array('d', [-0.0046125547011494445]), array('d', [-0.00054452849251024])])
('rvec:', [array('d', [0.005384873980389105]), array('d', [-0.0067320912238461586])])
('pvec:', [array('d', [-0.0005437524384725202]), array('d', [0.02282484518076862])])
('vectors:', [array('d', [-0.00043270205801244216]), array('d', [0.008886034848580922])])
('vectors:', [array('d', [0.007084160219588482]), array('d', [-0.02432821023841541])])
('vectors:', [array('d', [0.00645272013550734]), array('d', [-0.022867155594089517])])
本当は違うんだ日記
- read_chpoint_file()の中身が長すぎる問題
- double complexの読込みはDon't repeat yourselfを無視
- 関数にするのが良い方法かで躊躇している
- print時にCと同じ形式で表示しようとして失敗
-
%.4f
をxvec[idx]などに使おうとしたが失敗 - 1年後にはできるようになる
-
今日はmatplotlib表示に挑みたいがどうだろうか。
v0.6 print時に少数桁数を変更
@shiracamus さんにコメントいただいたnp.set_printoptions(precision=6)
を使い、C実装の結果と同じ少数桁数にしました。
code
read_chpoint.py
import numpy as np
import array
import sys
'''
v0.6 Dec. 23, 2016
- try to print fractional part of xvec[] in 4 digits
+ xvec[idx] = np.array([drel, dimg]), also for rvec[], pvec[], vectors[][]
+ add [np.set_printoptions(precision=4)]
v0.5 Dec. 23, 2016
- read scalars[], xvec[], rvec[], pvec[], vectors[][]
- refactor according to PEP8 (except for E501 line too long for long comment)
- wrap_fromfile() takes [num] arg
v0.4 Dec. 21, 2016
- read from "auxiliary" file [auxfp]
+ add read_auxiliary_info()
v0.3 Dec. 19, 2016
- add wrap_fromfile()
- read [inprodR],[prev_err],[resid_scale]
v0.2 Dec. 19, 2016
- fix bug > read [local_nRows] for "size_t" type
v0.1 Dec. 18, 2016
- read_chpoint_file() > read [ind_m],[local_nRows],[niter],[counter]
'''
np.set_printoptions(precision=6)
def wrap_fromfile(rfp, typecode, num):
res = array.array(typecode)
res.fromfile(rfp, num)
return res
def read_auxiliary_info(auxFilename):
with open(auxFilename, "rb") as auxfp:
sc_N = wrap_fromfile(auxfp, 'i', num=1) # the number of scalars' sizes
sc_sizes = array.array('i') #
sc_sizes.fromfile(auxfp, *sc_N) # '*':unpack list
vec_N = wrap_fromfile(auxfp, 'i', num=1) # the number of vercotrs' sizes
vec_sizes = array.array('i') #
vec_sizes.fromfile(auxfp, *vec_N) # '*':unpack list
return sc_N, sc_sizes, vec_N, vec_sizes
# TODO: 0m > error handling when file is NULL
def read_chpoint_file(chpFilename, auxFilename):
print(chpFilename)
print(auxFilename)
# TODO: 0m > error handling when file is NULL
with open(chpFilename, "rb") as chpfp:
ind_m = wrap_fromfile(chpfp, 'i', num=1) # index of iterative method
print('ind_m:', ind_m)
# number of local rows of decomposition (only real dipoles)
# where L: unsigned long = size_t
local_nRows = wrap_fromfile(chpfp, 'L', num=1)
print('local_nRows:', local_nRows)
niter = wrap_fromfile(chpfp, 'i', num=1) # iteration count
print('niter:', niter)
# number of successive iterations without residual decrease
counter = wrap_fromfile(chpfp, 'i', num=1)
print('counter:', counter)
# used as |r_0|^2 and best squared norm of residual up to some iteration
inprodR = wrap_fromfile(chpfp, 'd', num=1)
print('inprodR:', inprodR)
# previous relative error; used in ProgressReport, initialized in IterativeSolver
prev_err = wrap_fromfile(chpfp, 'd', num=1)
print('prev_err:', prev_err)
# scale to get square of relative error
resid_scale = wrap_fromfile(chpfp, 'd', num=1)
print('resid_scale:', resid_scale) # scale to get square of relative error
# sc_N: the number of scalars' sizes
# sc_sizes:
# vec_N: the number of vercotrs' sizes
# vec_sizes:
sc_N, sc_sizes, vec_N, vec_sizes = read_auxiliary_info(auxFilename)
print('sc_N:', sc_N)
print('sc_sizes', sc_sizes)
print('vec_N:', vec_N)
print('vec_sizes:', vec_sizes)
# scalars[]
scalars = []
for idx in range(sc_N[0]):
if sc_sizes[idx] is 8: # double
scl = wrap_fromfile(chpfp, 'd', num=1)
scalars.append(scl)
elif sc_sizes[idx] is 16: # double complex
scl = wrap_fromfile(chpfp, 'd', num=2)
scalars.append(scl)
for idx in range(sc_N[0]):
print('scalars:', scalars[idx])
# xvec[] : total electric field on the dipoles
# TODO: 0m > replace 'local_nRows[0]' with function?
# TODO: 0m > replace 'vec_N[0]' with function?
# TODO: 0m > define function for read [drel,dimg]??
xvec = [[] for idx in range(local_nRows[0])]
for idx in range(local_nRows[0]):
drel = wrap_fromfile(chpfp, 'd', 1)
dimg = wrap_fromfile(chpfp, 'd', 1)
xvec[idx] = np.array([drel, dimg])
# rvec[] : current residual
rvec = [[] for idx in range(local_nRows[0])]
for idx in range(local_nRows[0]):
drel = wrap_fromfile(chpfp, 'd', 1)
dimg = wrap_fromfile(chpfp, 'd', 1)
rvec[idx] = np.array([drel, dimg] )
# pvec[] : polarization of dipoles, also an auxiliary vector in iterative solvers
pvec = [[] for idx in range(local_nRows[0])]
for idx in range(local_nRows[0]):
drel = wrap_fromfile(chpfp, 'd', 1)
dimg = wrap_fromfile(chpfp, 'd', 1)
pvec[idx] = np.array([drel, dimg])
# vectors[] : ???
MAXNUM_VECTORS = 20
vectors = [[] for idx in range(MAXNUM_VECTORS)]
for idx_vecN in range(vec_N[0]):
alist = []
for idx_LnRows in range(local_nRows[0]):
if vec_sizes[idx_vecN] is 16:
drel = wrap_fromfile(chpfp, 'd', 1)
dimg = wrap_fromfile(chpfp, 'd', 1)
alist.append(np.array([drel, dimg]))
vectors[idx_vecN] = alist
#
for idx in range(3):
print('xvec:',np.array_repr(xvec[idx]).replace('\n',''))
print('rvec:',np.array_repr(rvec[idx]).replace('\n',''))
print('pvec:',np.array_repr(pvec[idx]).replace('\n',''))
print('vectors:',np.array_repr(vectors[idx][0]).replace('\n',''))
print('vectors:',np.array_repr(vectors[idx][1]).replace('\n',''))
print('vectors:',np.array_repr(vectors[idx][2]).replace('\n',''))
argvs = sys.argv
argc = len(argvs)
print argvs
if (argc < 3):
print("ERROR: chpoint file is not specified\r\n")
print(" [cmd] [chpoint file] [auxiliary file]\r\n")
sys.exit()
read_chpoint_file(chpFilename=argvs[1], auxFilename=argvs[2])
結果
['read_chpoint.py', 'LN-CHP', 'LN-AUX']
LN-CHP
LN-AUX
('ind_m:', array('i', [5]))
('local_nRows:', array('L', [27984L]))
('niter:', array('i', [209]))
('counter:', array('i', [139]))
('inprodR:', array('d', [4.317011265934948]))
('prev_err:', array('d', [0.3198525404317458]))
('resid_scale:', array('d', [0.020384616751203153]))
('sc_N:', array('i', [8]))
('sc_sizes', array('i', [8, 8, 8, 8, 16, 16, 16, 16]))
('vec_N:', array('i', [3]))
('vec_sizes:', array('i', [16, 16, 16]))
('scalars:', array('d', [26.040533833425627]))
('scalars:', array('d', [21.695179646708983]))
('scalars:', array('d', [0.01879089326833417]))
('scalars:', array('d', [0.01622964090344006]))
('scalars:', array('d', [2.393088070369695, 5.705068471314085]))
('scalars:', array('d', [0.2463390807093872, 0.2808495718014472]))
('scalars:', array('d', [0.8838701376516526, -0.4673547711298418]))
('scalars:', array('d', [0.34430517188699605, -0.9387175013645006]))
('xvec:', 'array([[ 0.000916], [-0.001571]])')
('rvec:', 'array([[-0.0021 ], [ 0.002827]])')
('pvec:', 'array([[-0.001287], [-0.008525]])')
('vectors:', 'array([[-0.203491], [ 0.033598]])')
('vectors:', 'array([[ 0.513358], [-0.235685]])')
('vectors:', 'array([[ 0.548095], [ 0.061967]])')
('xvec:', 'array([[ 0.032771], [ 0.090957]])')
('rvec:', 'array([[ 0.004384], [-0.023016]])')
('pvec:', 'array([[-0.00586 ], [ 0.025872]])')
('vectors:', 'array([[ 0.100941], [-0.212583]])')
('vectors:', 'array([[-0.220141], [ 0.644602]])')
('vectors:', 'array([[-0.386403], [ 0.429201]])')
('xvec:', 'array([[-0.004613], [-0.000545]])')
('rvec:', 'array([[ 0.005385], [-0.006732]])')
('pvec:', 'array([[-0.000544], [ 0.022825]])')
('vectors:', 'array([[-0.000433], [ 0.008886]])')
('vectors:', 'array([[ 0.007084], [-0.024328]])')
('vectors:', 'array([[ 0.006453], [-0.022867]])')
C実装結果と比較しやすくなりました。
情報感謝です。