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APSU dictionaries

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%% Cell type:code id: tags:
``` python
# You must include this next line for the ImageTool to show up!
%gui qt
from pyimagetool import imagetool # workhorse function
# only need these packages for data you create with meaningful axes
from pyimagetool import RegularDataArray
import numpy as np
```
%% Cell type:markdown id: tags:
# Generate Data
%% Cell type:code id: tags:
``` python
x = np.linspace(-1, 1, 51)
y = np.linspace(-1, 1, 51)
xy = np.meshgrid(x, y, indexing='ij')
z = np.sin(np.pi*np.exp(-1*(xy[0]**2 + xy[1]**2)))*np.cos(np.pi/2*xy[1])
data = RegularDataArray(z, delta=[x[1] - x[0], y[1] - y[0]], coord_min=[x[0], y[0]])
```
%% Output
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[6], line 1
----> 1 x = np.linspace(-1, 1, 51)
2 y = np.linspace(-1, 1, 51)
3 xy = np.meshgrid(x, y, indexing='ij')
NameError: name 'np' is not defined
%% Cell type:markdown id: tags:
# Create an ImageTool object
%% Cell type:code id: tags:
``` python
tool = imagetool(data)
```
%% Output
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[7], line 1
----> 1 tool = imagetool(data)
NameError: name 'imagetool' is not defined
%% Cell type:code id: tags:
``` python
tool.get('xy').plot(cmap='afmhot')
```
%% Output
%% Cell type:markdown id: tags:
# Controls
- Hold shift to drag the cursors to mouse location.
- While hovering over the cursor index or cursor coordinate spinbox, use the middle mouse wheel to move by increments of 1
- Hold control and scroll middle mouse wheel to move by increments of 10
- Left-click and drag to move image/plot
- Right-click and drag to resize (horizontal drag resizes horizontally, vertical drag resizes vertically)
- Ctrl+A will undo manipulations to view all data
- Right-click to open a menu.
- If you right-click on an image, you can set aspect ratio and make quick edits to the colormap
- You can export images and line cuts to png files
- If you return the ImageTool object to a variabel in the Python kernel, you can access a slice of the data at any time using the tool.get() function. See above for example.
## Editing Colormaps
- Right-click image, hover over "Color Map" and select "Edit Color Map"
- Color map normalizations on top, choices are "Power Law" or "Piecewise." Power law useful for quickly rescaling to make weak features stronger or vice versa with the gamma control, but piecewise gives you much more control.
- You can always see how the colormap is changing in the top right image of the colorbar.
- Bottom right is a histogram of the data. The x-axis is the value in the data and the y-axis is normalized weight at that value. For example, an image of a gaussian (z = exp(-x^2-y^2)) would have a large amount of weight at x-axis=0 falling off rapidly to almost zero at x-axis=1 (because there is only one point where z = 1 which is at x=0, y=0 in the image).
- You can scan the vertical bar in the histogram which controls the isocurve level. Because the algorithm that computes the isocurve is pure python, it is slow. If the tool noticeably slows down, consider disabling the isocurve calculations by unticking the box in the top left.
- In addition to the histogram, a line is drawn representing how values in your data is mapped to the colorbar. Imagine the colorbar is the y-axis and values in the image are on the x-axis. By default, color scales are linear. As you change gamma in power-law mode, you will see this curve become nonlinear, as the colorbar will noticeably deform.
- If the color map editor is in piecewise mode, you can drag points representing the max and min of the color scale. Furthermore, by right-clicking in the histogram area, you can add more points. This is useful for forcing your colorbar to highlight a region between two isosurfaces.
%% Cell type:code id: tags:
``` python
```
%% Cell type:markdown id:9b92de86 tags:
 
# Example of ARPES/XPS Experiment
 
%% Cell type:markdown id:53e8117f-0685-472b-b49f-7da2ca7f9097 tags:
 
## - Setting up the experiment
 
%% Cell type:markdown id:fac65c76 tags:
 
<span style='color:Blue'> Top cell is where we import and initialize </span>
 
%% Cell type:code id:158a3d4c-5796-4f0a-9ecc-a9c6beb1fc28 tags:
 
``` python
from iexcode import *
from iexplot import *
import orangebook as ob
 
tey,ca15 = ARPES_init()
```
 
%% Cell type:code id:657d7516-40c4-4fb4-b504-7d86929f98d3 tags:
``` python
```
%% Cell type:markdown id:d8d6c4f2-d78f-4ced-b5dd-d279ed113e64 tags:
 
<span style='color:Blue'> Sample positions and definitions; cut and paste them here to find more easily later </span>
 
%% Cell type:code id:0ba46d30 tags:
 
``` python
S123_top=["Mn-Bi2Se3",-0.7, -0.0, 12.4, 0.0, 0.0, 0.0]
S123_middle=["Bi2Se3",-0.6, -0.18, 15.1, 0.0, 0.0, 0.0]
S123_bottom=["Au",-0.0, 0, 16.9, 0.0, 0.0, 0.0]
 
RoughPositions=[
[-0.85, -0.0, 15.1, 10.0, 0.0, 0.0],
[-0.8, -0.0, 15.1, 7.5, 0.0, 0.0],
[-0.75, -0.0, 15.1, 5.0, 0.0, 0.0],
[-0.7, -0.0, 15.1, 2.5, 0.0, 0.0],
[-0.65, -0.0, 15.1, 0.0, 0.0, 0.0],
[-0.6, -0.0, 15.1, -2.5, 0.0, 0.0],
[-0.55, -0.0, 15.1, -5.0, 0.0, 0.0],
[-0.45, -0.0, 15.1, -7.5, 0.0, 0.0],
[-0.4, -0.0, 15.1, -10.0, 0.0, 0.0]
]
 
def XPS_overview():
energy(1200)
EAlist = ['KE',300,1205,0.25,1,1]
scanEA(EAlist)
```
 
%% Cell type:markdown id:dd08f0ca-aa1d-4075-95e4-37d44b199f62 tags:
 
## Scan Types
**mda:** point detectors <br>
**EA spectra:** Angle-resolved electron analyzer spectra<br>
**EA EDC:** Angle-integrated electron analyzer spectra<br>
 
%% Cell type:markdown id:4dba5cd8 tags:
 
<span style='color:Blue'> Setting the energy for finding the samples (hv = 500 is often a good place to start; RCP has the most flux) </span>
 
%% Cell type:code id:3da63cfc tags:
 
``` python
polarization('RCP')
energy(500)
```
 
%% Cell type:markdown id:cf20a7f1 tags:
 
## - Finding the sample(s)
 
%% Cell type:markdown id:56260a94-0628-4bae-a3de-748c1705882c tags:
 
<span style='color:Blue'> Cam2 is a good starting point to find samples; Note the y-position is dependent on the sample x-position. </span>
 
%% Cell type:markdown id:51d3265e-f6bb-4525-a6ed-dbb12607f422 tags:
 
<span style='color:Blue'> Setting x to good starting value<br>
- x = 0 if focus for the top hat<br>
- x = (-) taller samples, move back<br>
- x = 2.5 flat plates<br>
</span>
 
%% Cell type:code id:5f48037e-f5cd-4da0-95c2-10db18c7b710 tags:
 
``` python
mvx(0)
```
 
%% Cell type:markdown id:38a43548-6dcf-4b31-aa95-de99a2210690 tags:
 
<span style='color:Blue'> Scanning z (vertical) </span>
 
%% Cell type:code id:af149fc5 tags:
 
``` python
scanz(10.6,18.6,.1)
```
 
%% Cell type:markdown id:5f50f71e-c39c-4bb0-93e7-3f350a904f8d tags:
 
<span style='color:Blue'> plotting mda scans <br>
 
%% Cell type:code id:ba9b23d0 tags:
 
``` python
plot_mda(1143,17)
```
 
%% Output
 
 
%% Cell type:markdown id:bf400526 tags:
 
<span style='color:Blue'> Picking top sample (smallest z value)
</span>
 
%% Cell type:code id:28bb5382 tags:
 
``` python
mvz(12.4)
```
 
%% Output
 
z = 12.401
 
%% Cell type:markdown id:81821015 tags:
 
<span style='color:Blue'> Scanning y (horizontal) to find the center; Note: y is a left-handed motor </span>
 
%% Cell type:code id:06839420 tags:
 
``` python
scany(-3,3,.1)
```
 
%% Cell type:code id:582f449f tags:
 
``` python
plot_mda(1144,17,1144,16,Norm2One=True)
```
 
%% Output
 
/home/beams/29IDUSER/Documents/User_Folders/Staff/lastfigure.png
 
 
%% Cell type:markdown id:6407ac06-0af5-431a-9495-db6660a8f56e tags:
 
<span style='color:Blue'> Move to center of the sample </span>
 
%% Cell type:code id:bbf3b8dc tags:
 
``` python
mvy(0)
```
 
%% Output
 
y = -0.002
 
%% Cell type:markdown id:d04aed69-b45c-44cd-9ef3-5a447934bda1 tags:
 
## -Finding the focus (x)
 
%% Cell type:markdown id:e8d391af-85d1-487d-9864-1a3ea552e8ba tags:
 
<span style='color:Blue'> Adjust x by hand (narrowest tranmission line, depth of focus ~0.05mm) <br><br>WARNING: To not decrease the slit size or change the kinetic energy if you can not resolve the individual pixels in the EA live image
</span>
 
%% Cell type:code id:5ef11f4d tags:
 
``` python
#Pick a KE without core levels but with counts but greater than KEmin (PE=200; KEmin=230)
EA.put(300,200,'Transmission')
```
 
%% Cell type:markdown id:91cf3af2-0fc5-4918-839d-db336ff6162a tags:
 
<span style='color:Blue'> delta (relative) scan of x to find focus </span>
 
%% Cell type:markdown id:313d8fcc tags:
 
dscanx(-.25,.25,.05)
 
%% Cell type:code id:8add9ba2-1162-49a1-b992-06450be4d2d4 tags:
 
``` python
```
 
%% Cell type:code id:59db046c tags:
 
``` python
mprint() #Top sample position; copy this to top cell for later user
```
 
%% Output
 
[-0.7, -0.0, 12.4, 0.0, 0.0, 0.0]
 
%% Cell type:markdown id:eb9d845d tags:
 
<span style='color:Blue'> Overview XPS scan to check sample quality </span>
 
%% Cell type:code id:59f8aacc tags:
 
``` python
energy(1200)
XPS_overview=["KE",300,1205,1,200,1,1]
scanEA(XPS_overview)
```
 
%% Cell type:markdown id:3d607acd tags:
 
<span style='color:Blue'> Plotting EA spectra </span>
 
%% Cell type:code id:e4a34a78 tags:
 
``` python
data=IEXdata(1)
```
 
%% Output
 
path = /net/s29data/export/data_29idc/2021_2/NXschool/mda/
Loaded mdaAD scanNums: [[1]]
 
%% Cell type:code id:a5f2699f tags:
 
``` python
data.plotEDC(1)
```
 
%% Output
 
 
%% Cell type:markdown id:fef731f8 tags:
 
<span style='color:Blue'> Mn XAS </span>
 
%% Cell type:code id:07e375c2 tags:
 
``` python
Mn_XAS=[[630,635,0.5],[635,637,0.25],[637,645,0.1],[645,649,0.25],[649,655,0.1],[655,670,0.5]]
scanXAS_BL(Mn_XAS])
```
 
%% Cell type:code id:c847c7b2 tags:
 
``` python
data.update(34)
data.plotmda(34,16,xrange=(631,670))
```
 
%% Output
 
 
%% Cell type:markdown id:268c175a tags:
 
<span style='color:Blue'> Moving to a different sample positions to look for bands</span>
 
%% Cell type:code id:5b930558 tags:
 
``` python
mvsample(S_top)
```
 
%% Output
 
x=-0.7 y=-0.0 z=12.4 theta=0.0 chi=0.0 phi=0.0
 
%% Cell type:markdown id:7b6e0d7d-1ab3-4e7f-aca9-351a1e33adfb tags:
 
<span style='color:Blue'> Taking a spectra to look for bands</span>
 
%% Cell type:code id:7bbd61f6 tags:
 
``` python
energy(500)
scanEA(["KE",495,200,17*60*4,1])
```
 
%% Cell type:code id:f3049912 tags:
 
``` python
data.update(13)
data.plotEA(13)
```
 
%% Output
 
 
%% Cell type:markdown id:9111c293-2f4d-4c68-a60a-243a5ce4133a tags:
 
## Setting up for a Fermi Map
 
%% Cell type:markdown id:e7db10a7 tags:
 
<span style='color:Blue'>
Cu<span style='color:Blue'>
 
The focus of an analyzer is not at the center of rotation, therfore we need to addjust the
position as we rotate the sample.
 
Put the analyzer in tranmission mode
1) mvth(val) val starts with largest (most positive) th you will use and ends with the smallest (most negative) value (@ 500 eV +/= 10 will get you more than one zone for most materials)
2) Iterate scanning x and y (lateral and focus) (so that you are in focus at the lateral position you want)
3) mprint() and copy the output into a list of RoughPositions (see cell below)
 
Repeat 1-3 for you whole theta range. We will linearly interpolate between the rough positions when taking a Fermi map. Small rough sample far from the center of rotation require smaller theta step, larg uniform flat sample can use 5 degree steps
</span>
 
%% Cell type:code id:6a9bd7fe tags:
 
``` python
EA.put(495-10,200,"Transmission")
```
 
%% Cell type:code id:805b8300 tags:
 
``` python
mprint()
```
 
%% Output
 
[-0.4, -0.0, 14.85, -10.0, 0.0, 0.0]
 
%% Cell type:markdown id:3c56ed7a tags:
 
<span style='color:Blue'>Taking a Fermi map </span>
 
%% Cell type:code id:82627a3d tags:
 
``` python
z=12.5
logprint('FermiMap Bi2Se3, z='+str(z))
RoughPositions=[[-0.85, -0.0, z, 10.0, 0.0, 0.0],
[-0.8, -0.0, z, 7.5, 0.0, 0.0],
[-0.75, -0.0, z, 5.0, 0.0, 0.0],
[-0.7, -0.0, z, 2.5, 0.0, 0.0],
[-0.65, -0.0, z, 0.0, 0.0, 0.0],
[-0.6, -0.0, z, -2.5, 0.0, 0.0],
[-0.55, -0.0, z, -5.0, 0.0, 0.0],
[-0.45, -0.0, z, -7.5, 0.0, 0.0],
[-0.4, -0.0, z, -10.0, 0.0, 0.0]]
 
EAlist=['BE',5,200,20*4,1,'BS']
scanFM(RoughPositions,[9,-9,.25],EAlist)
 
```
 
%% Output
 
FermiMap Bi2Se3, z=12.5
_scanEAPrefix prefix: MDAscan0015
All extra positionners cleared
Baby-Sweep scan KE: 495.0015156
Scan1: 29idcScienta:userCalcOut10.PROC= 0.0 / 0.0 / 0.0
Scan2: 29idc:m4.VAL= 0.0 / 0.0 / 0.0
ARPES_15 started at Tue 20 Jul 2021 20:48:54
ARPES_15 finished at Wed 21 Jul 2021 02:14:15
_scanEAPrefix prefix: EA
All extra positionners cleared
 
%% Cell type:code id:773d6683 tags:
 
``` python
path = '/net/s29data/export/data_29idc/2022_3/McChesney/mda/'
data.update(15)
```
 
%% Output
 
Loaded mdaAD scanNums: [[15]]
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[2], line 2
1 path = '/net/s29data/export/data_29idc/2022_3/McChesney/mda/'
----> 2 data.update(15)
NameError: name 'data' is not defined
 
%% Cell type:markdown id:04ca1e32 tags:
 
<span style='color:Blue'>Checking the individual scans </span>
 
%% Cell type:code id:d539ac82 tags:
 
``` python
data.plotEA(15,6) #scan 15, spectra(image) 6
```
 
%% Output
 
 
%% Cell type:markdown id:8ccef79f tags:
 
<span style='color:Blue'>Plotting a Fermi Map with Image Tool </span>
 
%% Cell type:code id:1c933ca0-fe67-45b6-b5bf-a43f80f6a099 tags:
 
``` python
from iexplot import *
```
 
%% Cell type:code id:6d3ac181-6188-4dcd-9374-c3e44ebc558a tags:
 
``` python
data.plot_stack_mdaEA(15,xCen=498.6,cmap='twilight')
```
 
%% Output
 
 
%% Cell type:code id:a150b3b8 tags:
 
``` python
#creating a regular array for Image Tool
ra=data.stackmdaEA(15)
```
 
%% Output
 
Degrees Kinetic Energy (eV)
 
%% Cell type:markdown id:af7ef19b tags:
 
![image.png](attachment:0726f6cf-7682-49cc-bd86-57e59e50dd94.png)
 
%% Cell type:markdown id:8c09064a tags:
 
![image.png](attachment:3efa28b7-dbe1-4ce8-8b2b-30dc03e9f2cb.png)
 
%% Cell type:markdown id:9a848f12 tags:
 
<span style='color:Blue'>Putting Beamline in safe state </span>
 
%% Cell type:code id:9dbde7c4 tags:
 
``` python
ARPES_safe_state()
```
 
%% Cell type:code id:de0dc6c2 tags:
 
``` python
```
......
......@@ -1850,10 +1850,6 @@
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......@@ -3205,7 +3201,7 @@
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"pygments_lexer": "ipython3",
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"version": "3.11.9"
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......@@ -429,7 +429,7 @@
],
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......@@ -443,7 +443,7 @@
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"nbformat": 4,
......
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......@@ -69,3 +69,12 @@
======= 20230328:
{'TX': 2.0, 'TY': -21.5, 'TZ': 2.0, 'RX': -0.0, 'RY': 8.485, 'RZ': 2.0}
======= 20230404:
{'TX': 2.0, 'TY': -21.5, 'TZ': 2.0, 'RX': 0.0, 'RY': 8.483, 'RZ': 2.0}
======= 20230411:
{'TX': 2.0, 'TY': -21.5, 'TZ': 2.0, 'RX': 0.0, 'RY': 8.485, 'RZ': 2.0}
======= 20240809:
{'TX': 1.0, 'TY': -21.5, 'TZ': 1.0, 'RX': 0.0, 'RY': 8.544, 'RZ': 1.0}
File moved
......@@ -239,3 +239,15 @@
======= 20230322:
{'HEG': {'S2V': -0.154245, 'S2H': 0.168986, 'S1V': -0.0169762, 'S1H': 0.100001}, 'MEG': {'S2V': 0.004826, 'S2H': 0.127945, 'S1V': -0.13033, 'S1H': 0.058428}}
======= 20230404:
{'HEG': {'S2V': -0.154245, 'S2H': 0.168986, 'S1V': -0.0169762, 'S1H': 0.100001}, 'MEG': {'S2V': -0.154245, 'S2H': 0.168986, 'S1V': 0.14502724522108865, 'S1H': -0.13118039842721255}}
======= 20230411:
{'HEG': {'S2V': -0.154245, 'S2H': 0.168986, 'S1V': -0.0169762, 'S1H': 0.100001}, 'MEG': {'S2V': -0.06017898594634274, 'S2H': -0.012385692087779777, 'S1V': 0.19043068287637727, 'S1H': -0.14642468336237846}}
======= 20240807:
{'HEG': {'S2V': -0.0, 'S2H': 0.0, 'S1V': -0.0, 'S1H': 0.0}, 'MEG': {'S2V': -0.0, 'S2H': -0.0, 'S1V': 0.0, 'S1H': -0.0}}
======= 20240809:
{'HEG': {'S2V': -0.0, 'S2H': 0.0, 'S1V': -0.0, 'S1H': 0.0}, 'MEG': {'S2V': 0.0, 'S2H': 0.0, 'S1V': 0.0, 'S1H': 0.0}}
Responsivity Energy
0.109341 10.0752
0.1075 10.168
0.105579 10.2777
0.103737 10.3979
0.101656 10.5007
0.099895 10.614
0.0978137 10.719
0.0959725 10.8153
0.0943715 10.9124
0.0926103 11.0203
0.0910093 11.1193
0.0896484 11.1792
0.0880474 11.2695
0.0864464 11.3809
0.0847653 11.514
0.0830042 11.6591
0.0812431 11.8378
0.0798822 11.9762
0.0790816 12.2033
0.0788414 12.457
0.0790015 12.7502
0.079882 12.992
0.081403 13.2029
0.083084 13.4172
0.0842847 13.5257
0.0866862 13.733
0.0882072 13.844
0.0898882 14.006
0.0918894 14.1572
0.0939708 14.3613
0.0965323 14.5553
0.0983735 14.6862
0.100215 14.8049
0.101976 14.9113
0.103817 15.0453
0.106058 15.2077
0.107899 15.3169
0.109981 15.4546
0.112062 15.5796
0.113983 15.7196
0.115824 15.8325
0.117585 15.9748
0.119747 16.1328
0.121588 16.2342
0.123349 16.3654
0.12535 16.5421
0.127832 16.7207
0.130233 16.9466
0.132419 17.1223
0.135033 17.342
0.137321 17.5348
0.139608 17.7901
0.141896 18.0644
0.144837 18.3742
0.14756 18.6576
0.149957 18.881
0.152462 19.1722
0.154532 19.4348
0.157364 19.7345
0.159325 20.0048
0.161395 20.2615
0.163356 20.5216
0.165752 20.7673
0.167822 21.016
0.170545 21.3039
0.172942 21.5957
0.175774 21.9287
0.178389 22.248
0.180131 22.4379
0.182419 22.7259
0.184707 22.9981
0.186667 23.2932
0.188193 23.6323
0.189718 24.0376
0.191352 24.4498
0.193203 24.975
0.194837 25.4466
0.196036 25.8609
0.197016 26.3044
0.198105 26.9839
0.199086 27.5401
0.19963 27.9886
0.200284 28.5655
0.201062 29.1788
0.202043 29.8563
0.202874 30.4717
0.203931 31.2588
0.204762 31.8625
0.205385 32.3423
0.205728 32.6468
0.2059 33.0831
0.205685 33.4729
0.205685 33.9202
0.205814 34.4273
0.205942 34.8329
0.206423 35.5101
0.206929 36.335
0.207582 37.2736
0.208236 38.2689
0.20878 39.2241
0.209543 40.3401
0.210196 41.4878
0.211068 43.0324
0.211721 44.1815
0.212375 45.5159
0.213029 46.8506
0.213847 48.4147
0.21499 51.095
0.217278 56.3781
0.220137 63.5332
0.222901 71.5962
0.225284 79.93
0.227667 88.1947
0.23024 98.0003
0.232909 110.697
0.235768 124.745
0.238437 137.322
0.240915 151.521
0.24406 168.367
0.24692 187.965
0.25016 211.325
0.252924 234.82
0.256451 265.864
0.259215 294.732
0.26217 329.039
0.263599 344.016
0.26522 365.622
0.266649 386.769
0.267602 405.322
0.268365 421.79
0.269127 442.023
0.270176 464.314
0.271034 482.048
0.271863 502.915
0.272661 524.768
0.273353 544.89
0.273888 560.168
0.274296 577.813
0.274432 596.754
0.274432 613.265
0.274387 630.233
0.274387 655.755
0.274577 677.334
0.274896 698.718
0.275163 720.777
0.275588 742.318
0.275801 762.005
0.275908 786.062
0.275961 813.536
0.275961 836.479
0.275961 860.069
0.275961 881.435
0.275854 906.293
0.275804 934.582
0.275686 968.151
0.27545 999.14
0.275214 1031.12
0.275095 1056.11
0.274918 1083.07
0.274682 1109.32
0.274446 1141.94
0.27421 1174.05
0.273856 1210.1
0.273561 1248.84
0.273207 1287.19
0.272819 1322.48
0.272499 1357.16
0.272086 1386.55
0.271732 1413.01
0.271437 1436.35
0.271161 1464.13
0.270905 1482.33
0.270669 1501.13
0.270374 1520.17
0.269961 1543.33
0.26943 1568.82
0.268401 1596.21
0.26707 1629.27
0.265713 1664.55
0.264474 1696.32
0.26347 1724.34
0.26228 1755.08
0.261215 1786.94
0.259937 1822.37
0.259032 1849.4
0.258155 1871.57
0.257397 1894.63
0.256576 1915.74
0.255377 1947.28
0.275058 1957.05
0.275058 2160.44
0.275058 2389.74
0.275058 2507.09
0.275058 2604.07
0.275058 2715.63
0.275058 2962.14
0.275058 3276.53
0.275058 3649.72
0.275058 3981.03
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