Environment

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
GNU bash, version 4.3.8(1)-release (x86_64-pc-linux-gnu)

data preparation

$ ./adda -grid 25 -store_int_field -maxiter 3000

Then make the symbolic link for the IntField-Y file into the directory where you will use the following Jupyter code.

code v0.1

Jupyter code.

This code shows single result from InitFieldY for a given index of the Z coordinate value.

displaySingleInitFieldY_170422.ipynb

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
import sys


'''
v0.1 Apr. 22, 2017
   - show one result only
      + add show_single()
      + remove show_group()
=== branched from [displayInitFieldY_170419.ipynb] ===
v0.4 Apr. 20, 2017
   - show [Ex.r], [Ex.i], [Ey.r], [Er.i], [Ez.r], [Ez.i]
v0.3 Apr. 20, 2017
   - display for various [zz] values
   - add show_xymap()
v0.2 Apr. 20, 2017
   - set [PICK_UP_ZZ_VALUE] from zz_unique[]
   - use [ALLOWABLE_DIFF_ZZ]
v0.1 Apr. 19, 2017
   - display Ex.r[] without limiting [PICK_UP_ZZ_VALUE]
'''
# codingrule:PEP8

data = np.genfromtxt('IntField-Y', delimiter=' ')
xs, ys, zs = data[1:, 0], data[1:, 1], data[1:, 2]
Exr, Exi = data[1:, 4], data[2:, 4]
Eyr, Eyi = data[3:, 4], data[4:, 4]
Ezr, Ezi = data[5:, 4], data[6:, 4]

# print(zs)
zz_unique = np.unique(zs)
print(len(zz_unique))
print(zz_unique)
plt_y1 = np.array([])


def show_xymap(pick_up_zz, target):
    SIZE_MAP_X, SIZE_MAP_Y = 30, 30
    MIN_X, MIN_Y = -6, -6  # -6: based on coordinate values
    RANGE_X = 6 - MIN_X  # 6: based on coordinate values
    RANGE_Y = 6 - MIN_Y  # 6: based on coordinate values
    rmap = [[0.0 for yi in range(SIZE_MAP_Y)] for xi in range(SIZE_MAP_X)]

    # instead of [sys.float_info.epsilon], which is 2.22044604925e-16
    ALLOWABLE_DIFF_ZZ = 1.0e-10

    for idx, xyz in enumerate(zip(xs, ys, zs)):
        xx, yy, zz = xyz
        if abs(zz - pick_up_zz) >= ALLOWABLE_DIFF_ZZ:
            continue
        xidx = int(SIZE_MAP_X * (xx - MIN_X) / RANGE_X)
        yidx = int(SIZE_MAP_Y * (yy - MIN_Y) / RANGE_Y)
        #rmap[xidx][yidx] = Exr[idx]
        rmap[xidx][yidx] = target[idx]

    wrkarr = np.array(rmap)
    figmap = np.reshape(wrkarr, (SIZE_MAP_X, SIZE_MAP_Y))
    plt.imshow(figmap, extent=(0, SIZE_MAP_X, 0, SIZE_MAP_Y), cmap=cm.jet)


def show_single(atarget, index):
    show_xymap(zz_unique[index], atarget)
    plt.tight_layout()
    plt.show()

print('Ex.r[12]')
show_group(Exr, 12)

print('Ey.i[16]')
show_group(Eyi, 16)

print('Ez.r[8]')
show_group(Ezr, 8)

result

v0.2 > show colorbar

v0.3 > fix bug for artifacts by map size

displaySingleInitFieldY_170422.ipynb

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
import sys


'''
v0.3 Apr. 22, 2017
   - change display map size from [30,30] to [25,25]
v0.2 Apr. 22, 2017
   - show colorbar
v0.1 Apr. 22, 2017
   - show one result only
      + add show_single()
      + remove show_group()
=== branched from [displayInitFieldY_170419.ipynb] ===
v0.4 Apr. 20, 2017
   - show [Ex.r], [Ex.i], [Ey.r], [Er.i], [Ez.r], [Ez.i]
v0.3 Apr. 20, 2017
   - display for various [zz] values
   - add show_xymap()
v0.2 Apr. 20, 2017
   - set [PICK_UP_ZZ_VALUE] from zz_unique[]
   - use [ALLOWABLE_DIFF_ZZ]
v0.1 Apr. 19, 2017
   - display Ex.r[] without limiting [PICK_UP_ZZ_VALUE]
'''
# codingrule:PEP8

data = np.genfromtxt('IntField-Y', delimiter=' ')
xs, ys, zs = data[1:, 0], data[1:, 1], data[1:, 2]
Exr, Exi = data[1:, 4], data[2:, 4]
Eyr, Eyi = data[3:, 4], data[4:, 4]
Ezr, Ezi = data[5:, 4], data[6:, 4]

# print(zs)
zz_unique = np.unique(zs)
print(len(zz_unique))
print(zz_unique)
plt_y1 = np.array([])


def show_xymap(pick_up_zz, target):
    SIZE_MAP_X, SIZE_MAP_Y = 25, 25
    MIN_X, MIN_Y = -6, -6  # -6: based on coordinate values
    RANGE_X = 6 - MIN_X  # 6: based on coordinate values
    RANGE_Y = 6 - MIN_Y  # 6: based on coordinate values
    rmap = [[0.0 for yi in range(SIZE_MAP_Y)] for xi in range(SIZE_MAP_X)]

    # instead of [sys.float_info.epsilon], which is 2.22044604925e-16
    ALLOWABLE_DIFF_ZZ = 1.0e-10

    for idx, xyz in enumerate(zip(xs, ys, zs)):
        xx, yy, zz = xyz
        if abs(zz - pick_up_zz) >= ALLOWABLE_DIFF_ZZ:
            continue
        xidx = int(SIZE_MAP_X * (xx - MIN_X) / RANGE_X)
        yidx = int(SIZE_MAP_Y * (yy - MIN_Y) / RANGE_Y)
        #rmap[xidx][yidx] = Exr[idx]
        rmap[xidx][yidx] = target[idx]

    wrkarr = np.array(rmap)
    figmap = np.reshape(wrkarr, (SIZE_MAP_X, SIZE_MAP_Y))
    plt.imshow(figmap, extent=(0, SIZE_MAP_X, 0, SIZE_MAP_Y), cmap=cm.jet)
    plt.colorbar()

def show_single(atarget, index):
    show_xymap(zz_unique[index], atarget)
    plt.tight_layout()
    plt.show()

print('Ex.r[12]')
show_group(Exr, 12)

print('Ey.i[16]')
show_group(Eyi, 16)

print('Ez.r[8]')
show_group(Ezr, 8)

v0.4 > fix bug > NameError: name 'show_group' is not defined

displaySingleInitFieldY_170422.ipynb

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
import sys


'''
v0.4 Jun. 03, 2017
    - fix bug > NameError: name 'show_group' is not defined
v0.3 Apr. 22, 2017
   - change display map size from [30,30] to [25,25]
v0.2 Apr. 22, 2017
   - show colorbar
v0.1 Apr. 22, 2017
   - show one result only
      + add show_single()
      + remove show_group()
=== branched from [displayInitFieldY_170419.ipynb] ===
v0.4 Apr. 20, 2017
   - show [Ex.r], [Ex.i], [Ey.r], [Er.i], [Ez.r], [Ez.i]
v0.3 Apr. 20, 2017
   - display for various [zz] values
   - add show_xymap()
v0.2 Apr. 20, 2017
   - set [PICK_UP_ZZ_VALUE] from zz_unique[]
   - use [ALLOWABLE_DIFF_ZZ]
v0.1 Apr. 19, 2017
   - display Ex.r[] without limiting [PICK_UP_ZZ_VALUE]
'''
# codingrule:PEP8

data = np.genfromtxt('IntField-Y', delimiter=' ')
xs, ys, zs = data[1:, 0], data[1:, 1], data[1:, 2]
Exr, Exi = data[1:, 4], data[2:, 4]
Eyr, Eyi = data[3:, 4], data[4:, 4]
Ezr, Ezi = data[5:, 4], data[6:, 4]

# print(zs)
zz_unique = np.unique(zs)
print(len(zz_unique))
print(zz_unique)
plt_y1 = np.array([])


def show_xymap(pick_up_zz, target):
    SIZE_MAP_X, SIZE_MAP_Y = 25, 25
    MIN_X, MIN_Y = -6, -6  # -6: based on coordinate values
    RANGE_X = 6 - MIN_X  # 6: based on coordinate values
    RANGE_Y = 6 - MIN_Y  # 6: based on coordinate values
    rmap = [[0.0 for yi in range(SIZE_MAP_Y)] for xi in range(SIZE_MAP_X)]

    # instead of [sys.float_info.epsilon], which is 2.22044604925e-16
    ALLOWABLE_DIFF_ZZ = 1.0e-10

    for idx, xyz in enumerate(zip(xs, ys, zs)):
        xx, yy, zz = xyz
        if abs(zz - pick_up_zz) >= ALLOWABLE_DIFF_ZZ:
            continue
        xidx = int(SIZE_MAP_X * (xx - MIN_X) / RANGE_X)
        yidx = int(SIZE_MAP_Y * (yy - MIN_Y) / RANGE_Y)
        #rmap[xidx][yidx] = Exr[idx]
        rmap[xidx][yidx] = target[idx]

    wrkarr = np.array(rmap)
    figmap = np.reshape(wrkarr, (SIZE_MAP_X, SIZE_MAP_Y))
    plt.imshow(figmap, extent=(0, SIZE_MAP_X, 0, SIZE_MAP_Y), cmap=cm.jet)
    plt.colorbar()

def show_single(atarget, index):
    show_xymap(zz_unique[index], atarget)
    plt.tight_layout()
    plt.show()

print('Ex.r[12]')
show_single(Exr, 12)

print('Ey.i[16]')
show_single(Eyi, 16)

print('Ez.r[8]')
show_single(Ezr, 8)