Manipulating the Pandas DataFrame

The Jupyter notebook for this demo can be found in: - docs/quick_start/demo/op2_pandas_unstack.ipynb - https://github.com/SteveDoyle2/pyNastran/tree/main/docs/quick_start/demo/op2_pandas_unstack.ipynb

This example will use pandas unstack

The unstack method on a DataFrame moves on index level from rows to columns. First let’s read in some data:

import os
import pyNastran
pkg_path = pyNastran.__path__[0]
from pyNastran.op2.op2 import read_op2
import pandas as pd
pd.set_option('precision', 2)

op2_filename = os.path.join(pkg_path, '..', 'models', 'iSat', 'iSat_launch_100Hz.op2')
from pyNastran.op2.op2 import read_op2
isat = read_op2(op2_filename, build_dataframe=True, debug=False, skip_undefined_matrices=True)
INFO: op2_scalar.py:1588 op2_filename = 'c:\\nasa\\m4\\formats\\git\\pynastran\\pyNastran\\..\\models\\iSat\\iSat_launch_100Hz.op2' 
self.cannot apply column_names=['Mode', 'Freq'] to RealStrainEnergyArray: 'QUAD4'
self.cannot apply column_names=['Mode', 'Freq'] to RealStrainEnergyArray: 'TRIA3'
self.cannot apply column_names=['Mode', 'Freq'] to RealStrainEnergyArray: 'HEXA'
self.cannot apply column_names=['Mode', 'Freq'] to RealStrainEnergyArray: 'BAR'
self.cannot apply column_names=['Mode', 'Freq'] to RealStrainEnergyArray: 'BUSH'

cbar = isat.cbar_force[1].data_frame

cbar.head()
Mode 1 2 3 4 5 6 7 8 9 10 ... 24 25 26 27 28 29 30 31 32 33
Freq 8.36 9.51 15.67 20.24 20.31 20.55 21.50 21.71 21.72 28.54 ... 80.08 86.49 88.17 88.48 89.93 94.29 94.37 96.04 98.70 98.89
Eigenvalue 2758.15 3568.63 9689.98 16168.04 16278.16 16679.71 18248.43 18600.70 18632.55 32159.89 ... 253141.17 295300.94 306886.00 309040.66 319267.09 350984.50 351566.19 364166.31 384601.34 386090.47
Radians 52.52 59.74 98.44 127.15 127.59 129.15 135.09 136.38 136.50 179.33 ... 503.13 543.42 553.97 555.91 565.04 592.44 592.93 603.46 620.16 621.36
ElementID Item
3323 bending_moment_a1 -0.16 -0.23 -1.33 -2.32e+00 -1.88 -0.80 -1.34e-03 1.42 1.47 4.65 ... -43.42 63.36 -43.07 -3.35 11.08 -14.38 0.75 29.36 0.49 -4.56
bending_moment_a2 0.19 0.05 0.18 5.58e-03 -0.11 -0.42 -4.19e-03 -1.11 0.10 -1.57 ... -4.50 5.33 1.63 4.86 2.15 0.09 -1.27 -10.58 -0.67 3.48
bending_moment_b1 0.17 0.21 2.01 2.66e+00 1.88 0.73 2.29e-03 -1.38 -1.31 -3.98 ... 34.70 -74.02 35.13 3.54 -15.03 10.97 -0.67 -17.69 -0.63 6.39
bending_moment_b2 -0.19 -0.05 -0.18 -3.54e-03 0.11 0.43 4.18e-03 1.11 -0.10 1.57 ... 4.50 -5.34 -1.62 -4.86 -2.15 -0.08 1.27 10.56 0.67 -3.49
shear1 -0.13 -0.18 -1.33 -1.99e+00 -1.50 -0.61 -1.45e-03 1.12 1.11 3.45 ... -31.25 54.95 -31.28 -2.76 10.44 -10.14 0.57 18.82 0.44 -4.38

5 rows × 33 columns

First I’m going to pull out a small subset to work with

csub = cbar.loc[3323:3324,1:2]
csub
Mode 1 2
Freq 8.36 9.51
Eigenvalue 2758.15 3568.63
Radians 52.52 59.74
ElementID Item
3323 bending_moment_a1 -0.16 -0.23
bending_moment_a2 0.19 0.05
bending_moment_b1 0.17 0.21
bending_moment_b2 -0.19 -0.05
shear1 -0.13 -0.18
shear2 0.15 0.04
axial 0.80 -0.21
torque -0.04 0.06
3324 bending_moment_a1 0.14 0.29
bending_moment_a2 -0.19 -0.05
bending_moment_b1 -0.15 -0.26
bending_moment_b2 0.19 0.05
shear1 0.12 0.22
shear2 -0.15 -0.04
axial -0.80 0.21
torque 0.04 -0.06

I happen to like the way that’s organized, but let’s say that I want the have the item descriptions in columns and the mode ID’s and element numbers in rows. To do that, I’ll first move the element ID’s up to the columns using a .unstack(level=0) and the transpose the result:

csub.unstack(level=0).T
Item axial bending_moment_a1 bending_moment_a2 bending_moment_b1 bending_moment_b2 shear1 shear2 torque
Mode Freq Eigenvalue Radians ElementID
1 8.36 2758.15 52.52 3323 0.80 -0.16 0.19 0.17 -0.19 -0.13 0.15 -0.04
3324 -0.80 0.14 -0.19 -0.15 0.19 0.12 -0.15 0.04
2 9.51 3568.63 59.74 3323 -0.21 -0.23 0.05 0.21 -0.05 -0.18 0.04 0.06
3324 0.21 0.29 -0.05 -0.26 0.05 0.22 -0.04 -0.06

unstack requires unique row indices so I can’t work with CQUAD4 stresses as they’re currently output, but I’ll work with CHEXA stresses. Let’s pull out the first two elements and first two modes:

chs = isat.chexa_stress[1].data_frame.loc[3684:3685,1:2]
chs
Mode 1 2
Freq 8.36 9.51
Eigenvalue 2758.15 3568.63
Radians 52.52 59.74
ElementID NodeID Item
3684 0 oxx 1.22e-12 -3.41e-13
oyy -3.35e-12 -2.27e-13
ozz 1.25e-12 4.55e-13
txy -3.27e-13 1.82e-12
tyz 2.84e-14 3.98e-13
... ... ... ... ...
3685 1037 txz -2.84e-13 -1.82e-12
omax -7.47e-15 2.08e-12
omid -1.15e-13 -2.71e-13
omin -1.00e-12 -1.70e-12
von_mises 9.43e-13 3.30e-12

180 rows × 2 columns

Now I want to put ElementID and the Node ID in the rows along with the Load ID, and have the items in the columns:

cht = chs.unstack(level=[0,1]).T
cht
Item omax omid omin oxx oyy ozz txy txz tyz von_mises
Mode Freq Eigenvalue Radians ElementID NodeID
1 8.36 2758.15 52.52 3684 0 1.48e-12 1.02e-12 -3.38e-12 1.22e-12 -3.35e-12 1.25e-12 -3.27e-13 -2.27e-13 2.84e-14 4.64e-12
55 4.81e-12 1.92e-13 -3.57e-13 4.53e-12 -2.42e-13 3.55e-13 -6.54e-13 -9.30e-13 2.20e-15 4.92e-12
51 2.32e-12 1.49e-13 -1.41e-12 -1.39e-12 2.32e-12 1.35e-13 -1.30e-13 -1.46e-13 7.51e-15 3.25e-12
778 -1.38e-12 -3.27e-12 -6.12e-12 -6.08e-12 -1.38e-12 -3.31e-12 -5.81e-14 -3.41e-13 -1.97e-14 4.14e-12
758 5.79e-12 4.11e-12 7.57e-14 5.68e-12 1.14e-13 4.18e-12 -4.55e-13 -3.41e-13 -3.91e-14 5.09e-12
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
2 9.51 3568.63 59.74 3685 1015 1.19e-12 -9.78e-14 -6.96e-13 3.41e-13 -5.68e-14 1.14e-13 -2.27e-13 -9.09e-13 1.13e-13 1.67e-12
50 4.88e-13 -1.28e-13 -1.21e-12 -3.98e-13 1.14e-13 -5.68e-13 -5.68e-13 -4.90e-13 -2.27e-13 1.49e-12
46 6.22e-13 2.26e-14 -5.87e-13 -2.84e-13 3.41e-13 0.00e+00 4.54e-13 9.59e-14 -2.27e-13 1.05e-12
1031 2.32e-12 -6.90e-13 -1.63e-12 -2.27e-13 -6.82e-13 9.09e-13 4.55e-13 -1.82e-12 -2.27e-13 3.57e-12
1037 2.08e-12 -2.71e-13 -1.70e-12 4.55e-13 -3.41e-13 0.00e+00 -3.98e-13 -1.82e-12 -1.14e-13 3.30e-12

68 rows × 10 columns

Maybe I’d like my rows organized with the modes on the inside. I can do that by swapping levels:

We actually need to get rid of the extra rows using dropna():

cht = cht.dropna()
cht
Item omax omid omin oxx oyy ozz txy txz tyz von_mises
Mode Freq Eigenvalue Radians ElementID NodeID
1 8.36 2758.15 52.52 3684 0 1.48e-12 1.02e-12 -3.38e-12 1.22e-12 -3.35e-12 1.25e-12 -3.27e-13 -2.27e-13 2.84e-14 4.64e-12
55 4.81e-12 1.92e-13 -3.57e-13 4.53e-12 -2.42e-13 3.55e-13 -6.54e-13 -9.30e-13 2.20e-15 4.92e-12
51 2.32e-12 1.49e-13 -1.41e-12 -1.39e-12 2.32e-12 1.35e-13 -1.30e-13 -1.46e-13 7.51e-15 3.25e-12
778 -1.38e-12 -3.27e-12 -6.12e-12 -6.08e-12 -1.38e-12 -3.31e-12 -5.81e-14 -3.41e-13 -1.97e-14 4.14e-12
758 5.79e-12 4.11e-12 7.57e-14 5.68e-12 1.14e-13 4.18e-12 -4.55e-13 -3.41e-13 -3.91e-14 5.09e-12
60 2.88e-12 1.71e-12 -4.27e-12 2.63e-12 1.90e-12 -4.21e-12 -4.26e-13 -6.34e-13 8.53e-14 6.64e-12
56 1.66e-12 -1.65e-12 -5.92e-12 -5.87e-12 1.65e-12 -1.69e-12 -3.07e-13 -4.22e-13 8.53e-14 6.59e-12
880 2.63e-12 2.11e-12 -4.74e-12 -4.72e-12 2.10e-12 2.61e-12 -3.41e-13 0.00e+00 8.53e-14 7.12e-12
952 -8.35e-15 -1.79e-12 -3.00e-12 -1.73e-12 -1.14e-13 -2.96e-12 -4.26e-13 2.27e-13 5.68e-14 2.61e-12
3685 0 5.11e-13 1.44e-13 -5.41e-13 4.97e-13 1.56e-13 -5.40e-13 6.75e-14 -2.84e-14 1.42e-14 9.25e-13
45 8.09e-13 -5.47e-13 -8.09e-13 6.79e-13 -7.89e-13 -4.37e-13 6.39e-14 -4.02e-13 5.15e-14 1.50e-12
41 7.67e-13 -1.49e-13 -4.37e-13 -1.49e-13 7.21e-13 -3.91e-13 1.92e-13 1.14e-13 5.33e-14 1.09e-12
1021 7.75e-13 1.86e-13 -5.38e-13 1.56e-13 1.60e-13 1.07e-13 1.94e-13 -6.25e-13 5.47e-14 1.14e-12
1015 8.67e-13 1.56e-13 -6.65e-13 2.98e-13 1.53e-13 -9.24e-14 2.84e-14 -7.39e-13 4.51e-14 1.33e-12
50 9.64e-13 7.11e-13 -6.57e-14 -3.91e-14 7.11e-13 9.38e-13 -4.26e-14 -1.57e-13 1.42e-14 9.29e-13
46 2.26e-12 7.91e-13 7.55e-14 2.25e-12 7.96e-13 7.82e-14 8.37e-14 -7.01e-14 1.42e-14 1.93e-12
1031 -8.72e-13 -1.24e-12 -1.87e-12 -1.68e-12 -8.81e-13 -1.42e-12 8.53e-14 -2.84e-13 4.26e-14 8.75e-13
1037 -7.47e-15 -1.15e-13 -1.00e-12 -9.95e-14 -1.14e-13 -9.09e-13 -7.11e-15 -2.84e-13 2.84e-14 9.43e-13
2 9.51 3568.63 59.74 3684 0 2.22e-12 -1.06e-13 -2.23e-12 -3.41e-13 -2.27e-13 4.55e-13 1.82e-12 1.14e-12 3.98e-13 3.85e-12
55 3.64e-12 9.55e-13 -1.33e-12 2.33e-12 -5.68e-14 9.95e-13 1.82e-12 4.26e-13 1.12e-12 4.31e-12
51 7.48e-13 -3.94e-13 -1.46e-12 -3.41e-13 5.68e-14 -8.24e-13 1.57e-13 3.85e-13 9.24e-13 1.91e-12
778 1.24e-12 -5.76e-13 -2.37e-12 -2.27e-12 7.96e-13 -2.27e-13 1.25e-13 4.55e-13 7.73e-13 3.13e-12
758 1.03e-12 -1.04e-12 -3.57e-12 -5.68e-13 -2.33e-12 -6.82e-13 1.82e-12 4.55e-13 9.08e-13 3.99e-12
60 1.02e-12 -2.20e-12 -2.85e-12 -1.48e-12 -3.41e-13 -2.22e-12 1.82e-12 2.64e-13 1.14e-13 3.59e-12
56 5.04e-13 -3.52e-13 -2.37e-12 -1.82e-12 -7.96e-13 3.98e-13 -9.10e-13 -3.23e-13 1.14e-13 2.55e-12
880 1.79e-12 6.09e-13 -2.51e-12 1.25e-12 -2.27e-12 9.09e-13 -9.09e-13 -4.55e-13 3.41e-13 3.85e-12
952 1.30e-12 1.93e-13 -2.63e-12 -9.09e-13 -6.82e-13 4.55e-13 1.82e-12 4.55e-13 2.27e-13 3.51e-12
3685 0 1.18e-12 -3.91e-15 -9.47e-13 -1.14e-13 1.14e-13 2.27e-13 4.97e-13 -9.09e-13 -1.71e-13 1.84e-12
45 8.96e-13 -2.21e-13 -1.07e-12 2.27e-13 -5.68e-14 -5.68e-13 -2.84e-13 -6.52e-13 5.54e-13 1.71e-12
41 8.01e-13 -3.97e-13 -8.59e-13 -2.84e-13 0.00e+00 -1.71e-13 -4.62e-13 -6.12e-13 3.56e-13 1.48e-12
1021 9.04e-13 4.58e-13 -3.01e-12 -1.48e-12 5.68e-13 -7.39e-13 4.50e-13 -1.82e-12 9.06e-14 3.71e-12
1015 1.19e-12 -9.78e-14 -6.96e-13 3.41e-13 -5.68e-14 1.14e-13 -2.27e-13 -9.09e-13 1.13e-13 1.67e-12
50 4.88e-13 -1.28e-13 -1.21e-12 -3.98e-13 1.14e-13 -5.68e-13 -5.68e-13 -4.90e-13 -2.27e-13 1.49e-12
46 6.22e-13 2.26e-14 -5.87e-13 -2.84e-13 3.41e-13 0.00e+00 4.54e-13 9.59e-14 -2.27e-13 1.05e-12
1031 2.32e-12 -6.90e-13 -1.63e-12 -2.27e-13 -6.82e-13 9.09e-13 4.55e-13 -1.82e-12 -2.27e-13 3.57e-12
1037 2.08e-12 -2.71e-13 -1.70e-12 4.55e-13 -3.41e-13 0.00e+00 -3.98e-13 -1.82e-12 -1.14e-13 3.30e-12 
# mode, eigr, freq, rad, eids, nids # initial
# nids, eids, eigr, freq, rad, mode # final

cht.swaplevel(0,4).swaplevel(1,5).swaplevel(2,5).swaplevel(4, 5)
Item omax omid omin oxx oyy ozz txy txz tyz von_mises
ElementID NodeID Freq Radians Eigenvalue Mode
3684 0 8.36 52.52 2758.15 1 1.48e-12 1.02e-12 -3.38e-12 1.22e-12 -3.35e-12 1.25e-12 -3.27e-13 -2.27e-13 2.84e-14 4.64e-12
55 8.36 52.52 2758.15 1 4.81e-12 1.92e-13 -3.57e-13 4.53e-12 -2.42e-13 3.55e-13 -6.54e-13 -9.30e-13 2.20e-15 4.92e-12
51 8.36 52.52 2758.15 1 2.32e-12 1.49e-13 -1.41e-12 -1.39e-12 2.32e-12 1.35e-13 -1.30e-13 -1.46e-13 7.51e-15 3.25e-12
778 8.36 52.52 2758.15 1 -1.38e-12 -3.27e-12 -6.12e-12 -6.08e-12 -1.38e-12 -3.31e-12 -5.81e-14 -3.41e-13 -1.97e-14 4.14e-12
758 8.36 52.52 2758.15 1 5.79e-12 4.11e-12 7.57e-14 5.68e-12 1.14e-13 4.18e-12 -4.55e-13 -3.41e-13 -3.91e-14 5.09e-12
60 8.36 52.52 2758.15 1 2.88e-12 1.71e-12 -4.27e-12 2.63e-12 1.90e-12 -4.21e-12 -4.26e-13 -6.34e-13 8.53e-14 6.64e-12
56 8.36 52.52 2758.15 1 1.66e-12 -1.65e-12 -5.92e-12 -5.87e-12 1.65e-12 -1.69e-12 -3.07e-13 -4.22e-13 8.53e-14 6.59e-12
880 8.36 52.52 2758.15 1 2.63e-12 2.11e-12 -4.74e-12 -4.72e-12 2.10e-12 2.61e-12 -3.41e-13 0.00e+00 8.53e-14 7.12e-12
952 8.36 52.52 2758.15 1 -8.35e-15 -1.79e-12 -3.00e-12 -1.73e-12 -1.14e-13 -2.96e-12 -4.26e-13 2.27e-13 5.68e-14 2.61e-12
3685 0 8.36 52.52 2758.15 1 5.11e-13 1.44e-13 -5.41e-13 4.97e-13 1.56e-13 -5.40e-13 6.75e-14 -2.84e-14 1.42e-14 9.25e-13
45 8.36 52.52 2758.15 1 8.09e-13 -5.47e-13 -8.09e-13 6.79e-13 -7.89e-13 -4.37e-13 6.39e-14 -4.02e-13 5.15e-14 1.50e-12
41 8.36 52.52 2758.15 1 7.67e-13 -1.49e-13 -4.37e-13 -1.49e-13 7.21e-13 -3.91e-13 1.92e-13 1.14e-13 5.33e-14 1.09e-12
1021 8.36 52.52 2758.15 1 7.75e-13 1.86e-13 -5.38e-13 1.56e-13 1.60e-13 1.07e-13 1.94e-13 -6.25e-13 5.47e-14 1.14e-12
1015 8.36 52.52 2758.15 1 8.67e-13 1.56e-13 -6.65e-13 2.98e-13 1.53e-13 -9.24e-14 2.84e-14 -7.39e-13 4.51e-14 1.33e-12
50 8.36 52.52 2758.15 1 9.64e-13 7.11e-13 -6.57e-14 -3.91e-14 7.11e-13 9.38e-13 -4.26e-14 -1.57e-13 1.42e-14 9.29e-13
46 8.36 52.52 2758.15 1 2.26e-12 7.91e-13 7.55e-14 2.25e-12 7.96e-13 7.82e-14 8.37e-14 -7.01e-14 1.42e-14 1.93e-12
1031 8.36 52.52 2758.15 1 -8.72e-13 -1.24e-12 -1.87e-12 -1.68e-12 -8.81e-13 -1.42e-12 8.53e-14 -2.84e-13 4.26e-14 8.75e-13
1037 8.36 52.52 2758.15 1 -7.47e-15 -1.15e-13 -1.00e-12 -9.95e-14 -1.14e-13 -9.09e-13 -7.11e-15 -2.84e-13 2.84e-14 9.43e-13
3684 0 9.51 59.74 3568.63 2 2.22e-12 -1.06e-13 -2.23e-12 -3.41e-13 -2.27e-13 4.55e-13 1.82e-12 1.14e-12 3.98e-13 3.85e-12
55 9.51 59.74 3568.63 2 3.64e-12 9.55e-13 -1.33e-12 2.33e-12 -5.68e-14 9.95e-13 1.82e-12 4.26e-13 1.12e-12 4.31e-12
51 9.51 59.74 3568.63 2 7.48e-13 -3.94e-13 -1.46e-12 -3.41e-13 5.68e-14 -8.24e-13 1.57e-13 3.85e-13 9.24e-13 1.91e-12
778 9.51 59.74 3568.63 2 1.24e-12 -5.76e-13 -2.37e-12 -2.27e-12 7.96e-13 -2.27e-13 1.25e-13 4.55e-13 7.73e-13 3.13e-12
758 9.51 59.74 3568.63 2 1.03e-12 -1.04e-12 -3.57e-12 -5.68e-13 -2.33e-12 -6.82e-13 1.82e-12 4.55e-13 9.08e-13 3.99e-12
60 9.51 59.74 3568.63 2 1.02e-12 -2.20e-12 -2.85e-12 -1.48e-12 -3.41e-13 -2.22e-12 1.82e-12 2.64e-13 1.14e-13 3.59e-12
56 9.51 59.74 3568.63 2 5.04e-13 -3.52e-13 -2.37e-12 -1.82e-12 -7.96e-13 3.98e-13 -9.10e-13 -3.23e-13 1.14e-13 2.55e-12
880 9.51 59.74 3568.63 2 1.79e-12 6.09e-13 -2.51e-12 1.25e-12 -2.27e-12 9.09e-13 -9.09e-13 -4.55e-13 3.41e-13 3.85e-12
952 9.51 59.74 3568.63 2 1.30e-12 1.93e-13 -2.63e-12 -9.09e-13 -6.82e-13 4.55e-13 1.82e-12 4.55e-13 2.27e-13 3.51e-12
3685 0 9.51 59.74 3568.63 2 1.18e-12 -3.91e-15 -9.47e-13 -1.14e-13 1.14e-13 2.27e-13 4.97e-13 -9.09e-13 -1.71e-13 1.84e-12
45 9.51 59.74 3568.63 2 8.96e-13 -2.21e-13 -1.07e-12 2.27e-13 -5.68e-14 -5.68e-13 -2.84e-13 -6.52e-13 5.54e-13 1.71e-12
41 9.51 59.74 3568.63 2 8.01e-13 -3.97e-13 -8.59e-13 -2.84e-13 0.00e+00 -1.71e-13 -4.62e-13 -6.12e-13 3.56e-13 1.48e-12
1021 9.51 59.74 3568.63 2 9.04e-13 4.58e-13 -3.01e-12 -1.48e-12 5.68e-13 -7.39e-13 4.50e-13 -1.82e-12 9.06e-14 3.71e-12
1015 9.51 59.74 3568.63 2 1.19e-12 -9.78e-14 -6.96e-13 3.41e-13 -5.68e-14 1.14e-13 -2.27e-13 -9.09e-13 1.13e-13 1.67e-12
50 9.51 59.74 3568.63 2 4.88e-13 -1.28e-13 -1.21e-12 -3.98e-13 1.14e-13 -5.68e-13 -5.68e-13 -4.90e-13 -2.27e-13 1.49e-12
46 9.51 59.74 3568.63 2 6.22e-13 2.26e-14 -5.87e-13 -2.84e-13 3.41e-13 0.00e+00 4.54e-13 9.59e-14 -2.27e-13 1.05e-12
1031 9.51 59.74 3568.63 2 2.32e-12 -6.90e-13 -1.63e-12 -2.27e-13 -6.82e-13 9.09e-13 4.55e-13 -1.82e-12 -2.27e-13 3.57e-12
1037 9.51 59.74 3568.63 2 2.08e-12 -2.71e-13 -1.70e-12 4.55e-13 -3.41e-13 0.00e+00 -3.98e-13 -1.82e-12 -1.14e-13 3.30e-12

Alternatively I can do that by first using reset_index to move all the index columns into data, and then using set_index to define the order of columns I want as my index:

cht.reset_index().set_index(['ElementID','NodeID','Mode','Freq']).sort_index()
Item Eigenvalue Radians omax omid omin oxx oyy ozz txy txz tyz von_mises
ElementID NodeID Mode Freq
3684 0 1 8.36 2758.15 52.52 1.48e-12 1.02e-12 -3.38e-12 1.22e-12 -3.35e-12 1.25e-12 -3.27e-13 -2.27e-13 2.84e-14 4.64e-12
2 9.51 3568.63 59.74 2.22e-12 -1.06e-13 -2.23e-12 -3.41e-13 -2.27e-13 4.55e-13 1.82e-12 1.14e-12 3.98e-13 3.85e-12
51 1 8.36 2758.15 52.52 2.32e-12 1.49e-13 -1.41e-12 -1.39e-12 2.32e-12 1.35e-13 -1.30e-13 -1.46e-13 7.51e-15 3.25e-12
2 9.51 3568.63 59.74 7.48e-13 -3.94e-13 -1.46e-12 -3.41e-13 5.68e-14 -8.24e-13 1.57e-13 3.85e-13 9.24e-13 1.91e-12
55 1 8.36 2758.15 52.52 4.81e-12 1.92e-13 -3.57e-13 4.53e-12 -2.42e-13 3.55e-13 -6.54e-13 -9.30e-13 2.20e-15 4.92e-12
2 9.51 3568.63 59.74 3.64e-12 9.55e-13 -1.33e-12 2.33e-12 -5.68e-14 9.95e-13 1.82e-12 4.26e-13 1.12e-12 4.31e-12
56 1 8.36 2758.15 52.52 1.66e-12 -1.65e-12 -5.92e-12 -5.87e-12 1.65e-12 -1.69e-12 -3.07e-13 -4.22e-13 8.53e-14 6.59e-12
2 9.51 3568.63 59.74 5.04e-13 -3.52e-13 -2.37e-12 -1.82e-12 -7.96e-13 3.98e-13 -9.10e-13 -3.23e-13 1.14e-13 2.55e-12
60 1 8.36 2758.15 52.52 2.88e-12 1.71e-12 -4.27e-12 2.63e-12 1.90e-12 -4.21e-12 -4.26e-13 -6.34e-13 8.53e-14 6.64e-12
2 9.51 3568.63 59.74 1.02e-12 -2.20e-12 -2.85e-12 -1.48e-12 -3.41e-13 -2.22e-12 1.82e-12 2.64e-13 1.14e-13 3.59e-12
758 1 8.36 2758.15 52.52 5.79e-12 4.11e-12 7.57e-14 5.68e-12 1.14e-13 4.18e-12 -4.55e-13 -3.41e-13 -3.91e-14 5.09e-12
2 9.51 3568.63 59.74 1.03e-12 -1.04e-12 -3.57e-12 -5.68e-13 -2.33e-12 -6.82e-13 1.82e-12 4.55e-13 9.08e-13 3.99e-12
778 1 8.36 2758.15 52.52 -1.38e-12 -3.27e-12 -6.12e-12 -6.08e-12 -1.38e-12 -3.31e-12 -5.81e-14 -3.41e-13 -1.97e-14 4.14e-12
2 9.51 3568.63 59.74 1.24e-12 -5.76e-13 -2.37e-12 -2.27e-12 7.96e-13 -2.27e-13 1.25e-13 4.55e-13 7.73e-13 3.13e-12
880 1 8.36 2758.15 52.52 2.63e-12 2.11e-12 -4.74e-12 -4.72e-12 2.10e-12 2.61e-12 -3.41e-13 0.00e+00 8.53e-14 7.12e-12
2 9.51 3568.63 59.74 1.79e-12 6.09e-13 -2.51e-12 1.25e-12 -2.27e-12 9.09e-13 -9.09e-13 -4.55e-13 3.41e-13 3.85e-12
952 1 8.36 2758.15 52.52 -8.35e-15 -1.79e-12 -3.00e-12 -1.73e-12 -1.14e-13 -2.96e-12 -4.26e-13 2.27e-13 5.68e-14 2.61e-12
2 9.51 3568.63 59.74 1.30e-12 1.93e-13 -2.63e-12 -9.09e-13 -6.82e-13 4.55e-13 1.82e-12 4.55e-13 2.27e-13 3.51e-12
3685 0 1 8.36 2758.15 52.52 5.11e-13 1.44e-13 -5.41e-13 4.97e-13 1.56e-13 -5.40e-13 6.75e-14 -2.84e-14 1.42e-14 9.25e-13
2 9.51 3568.63 59.74 1.18e-12 -3.91e-15 -9.47e-13 -1.14e-13 1.14e-13 2.27e-13 4.97e-13 -9.09e-13 -1.71e-13 1.84e-12
41 1 8.36 2758.15 52.52 7.67e-13 -1.49e-13 -4.37e-13 -1.49e-13 7.21e-13 -3.91e-13 1.92e-13 1.14e-13 5.33e-14 1.09e-12
2 9.51 3568.63 59.74 8.01e-13 -3.97e-13 -8.59e-13 -2.84e-13 0.00e+00 -1.71e-13 -4.62e-13 -6.12e-13 3.56e-13 1.48e-12
45 1 8.36 2758.15 52.52 8.09e-13 -5.47e-13 -8.09e-13 6.79e-13 -7.89e-13 -4.37e-13 6.39e-14 -4.02e-13 5.15e-14 1.50e-12
2 9.51 3568.63 59.74 8.96e-13 -2.21e-13 -1.07e-12 2.27e-13 -5.68e-14 -5.68e-13 -2.84e-13 -6.52e-13 5.54e-13 1.71e-12
46 1 8.36 2758.15 52.52 2.26e-12 7.91e-13 7.55e-14 2.25e-12 7.96e-13 7.82e-14 8.37e-14 -7.01e-14 1.42e-14 1.93e-12
2 9.51 3568.63 59.74 6.22e-13 2.26e-14 -5.87e-13 -2.84e-13 3.41e-13 0.00e+00 4.54e-13 9.59e-14 -2.27e-13 1.05e-12
50 1 8.36 2758.15 52.52 9.64e-13 7.11e-13 -6.57e-14 -3.91e-14 7.11e-13 9.38e-13 -4.26e-14 -1.57e-13 1.42e-14 9.29e-13
2 9.51 3568.63 59.74 4.88e-13 -1.28e-13 -1.21e-12 -3.98e-13 1.14e-13 -5.68e-13 -5.68e-13 -4.90e-13 -2.27e-13 1.49e-12
1015 1 8.36 2758.15 52.52 8.67e-13 1.56e-13 -6.65e-13 2.98e-13 1.53e-13 -9.24e-14 2.84e-14 -7.39e-13 4.51e-14 1.33e-12
2 9.51 3568.63 59.74 1.19e-12 -9.78e-14 -6.96e-13 3.41e-13 -5.68e-14 1.14e-13 -2.27e-13 -9.09e-13 1.13e-13 1.67e-12
1021 1 8.36 2758.15 52.52 7.75e-13 1.86e-13 -5.38e-13 1.56e-13 1.60e-13 1.07e-13 1.94e-13 -6.25e-13 5.47e-14 1.14e-12
2 9.51 3568.63 59.74 9.04e-13 4.58e-13 -3.01e-12 -1.48e-12 5.68e-13 -7.39e-13 4.50e-13 -1.82e-12 9.06e-14 3.71e-12
1031 1 8.36 2758.15 52.52 -8.72e-13 -1.24e-12 -1.87e-12 -1.68e-12 -8.81e-13 -1.42e-12 8.53e-14 -2.84e-13 4.26e-14 8.75e-13
2 9.51 3568.63 59.74 2.32e-12 -6.90e-13 -1.63e-12 -2.27e-13 -6.82e-13 9.09e-13 4.55e-13 -1.82e-12 -2.27e-13 3.57e-12
1037 1 8.36 2758.15 52.52 -7.47e-15 -1.15e-13 -1.00e-12 -9.95e-14 -1.14e-13 -9.09e-13 -7.11e-15 -2.84e-13 2.84e-14 9.43e-13
2 9.51 3568.63 59.74 2.08e-12 -2.71e-13 -1.70e-12 4.55e-13 -3.41e-13 0.00e+00 -3.98e-13 -1.82e-12 -1.14e-13 3.30e-12