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Journal of Geochemistry, Geophysics, Geosystems
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Supporting Information for
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Quantifying near-field and off-fault deformation patterns of the 1992 Mw 7.3 Landers
earthquake
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C. Milliner1, J. Dolan1, J. Hollingsworth2, S. Leprince3, A. Ayoub3, and C. Sammis1.
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University of Southern California, Los Angeles, CA, United States,
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ARUP consultants - London, United Kingdom,
California Institute of Technology, Pasadena, CA, United States
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Contents of this file
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Text S1
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Figures S1 to S17
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Table S1
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Introduction
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The supplementary text includes detailed results of our synthetic tests, which are a similar but
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more detailed analysis than the study of Michel and Avouac (2006). The supplementary figures
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are split into two parts, the first are results relating to our synthetic tests (Figures S1-S4), the
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second (Figures S5-S17) are results from our statistical analysis of the control of various
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parameters on our COSI-Corr displacement, off-fault deformation (OFD) and fault-zone width
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(FZW) data. For these synthetic tests we use two different images taken at different times in
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order to incorporate the effect of different images textures and quality.
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The COSI-Corr displacement (n = 1057), OFD (n = 280) and FZW (n = 1060) data are
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acquired from stacked profiles from the correlation maps. The tested parameters we considered
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include the inferred age of alluvial fans (proxy for degree of lithification), horizontal distance to
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nearest bedrock exposure (a proxy for sediment thickness), fault strike relative to an optimal
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orientation (a proxy for stress field), and fault length (a proxy for structural maturity). We infer
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the ages of alluvial fans from the development of desert varnish, surface texture and relative
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amount of incision between fan surfaces from false-color composite aerial photography and
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Google Earth imagery. The horizontal distance to bedrock is determined from the same geologic
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maps used in the main article. We also analyze how the COSI-Corr displacement, FZW and OFD
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scale with each other.
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The figures here present useful information on how the tested parameters show a control
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(or lack of) with our data that serves as a supplement to the results in the main text. The majority
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of the parameters presented here yield in most cases no discernable relation with our surface
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deformation data. However, several of these comparisons do appear to exhibit a systematic
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relationship. Specifically figure 10 shows a weak correlation between our data (COSI-Corr
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displacement, OFD and FZW) with the fault length. As might be expected longer faults can host
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larger displacements and wider fault-zones, while OFD should decrease as the fault matures and
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lengthens.
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We also provide a table (Table S1), which contains all the measurements made and used
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in our statistical analysis that were extracted from our correlation maps. Note there are numerous
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nan values in the OFD column, which represents no OFD was found, because we could only
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measure OFD where a COSI-Corr measurement could be sufficiently matched with a nearby
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field measurement at that location.
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Text S1
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Synthetic tests
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During the correlation process, the correlation window analyses a subset of pixels within
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the input aerial image and finds similar pixel pattern in the corresponding image that brackets the
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event. Therefore the correlation window essentially averages the tectonic deformation over the
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region defined by the window size. From this process of averaging, the sliding window is
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thought to smooth the resulting correlation maps, thus adding an ‘artificial’ FZW to the real
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width. Therefore, before we can measure the FZW reliably, we first need to understand the
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correlation process. Specifically we need to constrain the magnitude of the artificial ‘smoothing’
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and understand whether this process is linear, predictable, and therefore correctable. We also
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perform additional tests, the results of which constitute a powerful tool that uniquely constrains
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the measurement bias and precision when subjectively estimating the FZW and displacement
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from the stacked profiles.
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Test A – Correlation window
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The correlation process measures the average displacement over a given correlation
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window [Leprince et al., 2007a; 2007b]. On a first approximation, the correlation process can
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then be modeled as a simple convolution such as:
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dobs  dtr  hcorr
(S1)
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Where hcorr is the convolution kernel, which is in our case a Hanning window, dtr is the
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theoretical displacement to be measured, * represents the convolution operator, and dobs is the
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displacement observed through the correlation process. By the properties of the convolution, the
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support of dobs is therefore the sum of the supports of dtr and hcorr. In our case, the FZW can be
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modeled as the support of the derivative of the offset across the fault displacement, such that:
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d obs dtr

 hcorr
x
x
(S2)
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 d
FZWobs  supp  obs
 x

 dtr 
  supp 
  supp  hcorr 

 dx 
(S3)
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FZWobs  FZWth  supp  hcorr 
(S4)
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If no OFD where to be present, the theoretical offset would be an ideal step function, and
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its derivative an ideal Dirac delta function of null support [see equation (S2)]. A fault with no
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OFD would be measured with a FZW equal to the support of the correlation window, and
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generally, the observed FZW is biased by the support of the correlation window. Knowing the
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correlation window, we can therefore correct the observed measurement of the FZW to recover
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the true FZW. In practice, because the Hanning window quickly tapers down at the edges, its
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effective support can be expected to be about half its exact support. We therefore determine this
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correction term empirically.
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To determine the artificial FZW (hcorr) on a fault of known displacement and width, we
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imposed a synthetic earthquake in one of our post-event aerial image. In MATLAB we simply
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shift one half of a post-event, aerial image by a known amount, thereby imitating a rupture on a
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fault. We correlate the artificially dextrally sheared image with a different non-disturbed pre-
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event image (Figure S1a) using the same processing procedure in COSI-Corr that we use to
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produce our real dataset [Leprince et al., 2007a; 2007b]. We measured the FZW from the
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correlation images using stacked profiles in the same manner as we implemented in our true
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dataset. To shift image pixels by a non-integer amount, we applied a cubic interpolation to one
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side of the deformed image.
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We performed 39 synthetic tests with an array of faulting styles, widths and
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displacements expected in a real environment. Figure S2 shows as expected; the observed
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synthetic FZW (dobs) is systematically larger than the true synthetic FZW (dtr) by an amount
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approximately half the window size. Figure S2 shows our empirically derived calibration
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function with slope of 1.04, which unequivocally shows the linear and predictable nature of this
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problem. We found for multiple tests that supp(dcorr) is consistently 18 pixels, which is illustrated
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by the goodness-of-fit for our linear model. Therefore, to determine the true FZW (dtr), no matter
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the true width of deformation, one can use the calibration function to correct for hcorr by simply
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subtracting supp(dcorr) from the observed FZW (dh). Importantly, the synthetic tests reveal the
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observed step signal seen in the stacked profiles cannot be produced by any other process except
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by strain release occurring over a finite width.
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Knowing the synthetic displacement and FZW value allows robust estimation of any
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measurement bias, because we can directly compare the values to those subjectively estimated.
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When shearing an image synthetically, we applied uniform displacement to the entire fault,
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which also has a constant FZW along-strike. Repeatedly measuring the displacement and FZW
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along-strike of our synthetic fault across different parts of the correlation image therefore gives
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multiple independent measurements. This consequently yields an empirical distribution of the
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FZW and displacement measurement. When measuring both the FZW and displacement, as
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described below, the true values were not revealed to the user, in order to not influence the
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measurements.
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Test B - FZW measurement uncertainty
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We performed 71 independent measurements of the FZW of the synthetic fault using
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stacked profiles, shown in Figure S3. The synthetic fault has a known, pre-determined FZW of
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60 m. Subjectively picking the FZW of a fault multiple times expectedly produces an empirical
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distribution which is Gaussian, with a mode that exactly matches the true FZW. These tests
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demonstrate that when subjectively estimating the FZW there is minor measurement bias
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present, with ~2.00 m underestimation of the true FZW. From the Gaussian distribution seen in
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Figure S3 we derive an empirical measurement uncertainty of + 12 m (2σ). This empirical
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uncertainty value is consistent for any width of fault-zone because it is related to the correlator
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window size, which is constant during the correlating process.
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Test C – Displacement uncertainty
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We also charaterize the measurement distribution for the displacement measurements
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from the synthetic tests, the results of which are shown in Figure S4. We apply two tests, one for
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a fault with supra-pixel movement of 2 m displacement and another with sub-pixel movement of
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50 cm displacement. The tests indicate there is minor amount of measurement bias, with a small
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overestimation of the true displacment by 0.01 m. Both the sub- and supra-pixel displacement
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tests yield the same behavior with a 1 sigma measurement precision of + 0.07 m and + 0.05 m,
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respectively, which is in agreement with the results of Michel and Avouac (2006). The very tight
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precision and nearly zero measurement bias is reflective of the robustness of the correlation
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procedure, the quality of the aerial images, and the use of profile stacking to suppress noise.
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Furthermore, Figure S4a shows that subjectively estimating the displacement produces a small
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amount of artificial, along-strike slip variability + 0.05 m at the 1 σ level.
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Supplementary figures
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Figure S1 (a) left: Synthetic correlation map of a single dextral fault striking north-south, with a
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uniform, prescribed right-lateral displacement of 2m, with map co-ordinates in UTM. This
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correlation is produced by using two-different images taken at different times (1989 and 1994) of
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the same area, where the eastern half of the most recent image (1994) is displaced to the south.
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The hashed rectangle shows the dimensions of the stacked profile orientated perpendicular to our
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synthetic fault, with an along-strike width of 138 m and length of 1.75 km. (b) Right, shows the
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synthetic deformation signal seen in the stacked profile. The x-axis is distance along profile
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length. The y-axis is the pixel movement. The black line is the surface deformation from the
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synthetic correlation map in a). Red sub-horizontal dashed lines are the linear regression fits to
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the data. Displacement is defined as the difference between the 2 linear regressions where they
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intercept the fault trace at x = 0, which in this profile is measured as 2.09 m.
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Figure S2. Result from the synthetic tests measuring the FZW from the correlation maps in
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comparison to the known, pre-determined true value. The linear regression is our calibration
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function, which serves as an empirical tool to correct for the correlation window systematically
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and artificially widening the true FZW.
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Figure S3. Results from the synthetic tests repeatedly measuring the FZW along a fault of
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constant known width of 60m. Blue histogram bars show the binned data measured from the
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correlation maps. Red line shows our best model fit to the data with a Gaussian distribution.
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Green vertical line shows the known, synthetic, pre-determined FZW value (60m).
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Figure S4. Results from the synthetic tests repeatedly measuring the displacement along a fault
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of constant, known displacement using stacked profiles. Two tests are performed. Test 1: is a
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fault with uniform displacement of 0.5 m. Test 2: is a fault with uniform displacement of 2 m. (a)
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Blue points are displacement measured plotted along-strike of our synthetic fault. Green
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horizontal line shows the true, uniform displacement of the fault. The variability observed is a
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reflection of subjectively estimating the displacement, noise in the data and geometric artifacts.
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(b) Blue histogram bars show the binned displacement measured from the correlation maps. Red
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line shows our best model fit to the data with a Gaussian distribution. Green vertical line shows
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the known, synthetic, pre-determined displacement value.
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Figure S5. Fault-zone width plotted against off-fault deformation. We find a from a Spearman’s rank a
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value of 0.33, indicating that the FZW can only explain a small portion of the variabilty in the OFD data.
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We do find however, a p-value < 0.01, indicating that there is a linear relation between the data and that
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they are not independent.
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Figure S6. COSI-Corr displacement (which represents the total displacement across the fault) versus
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fault-zone width plotted.
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Figure S7. COSI-Corr displacement (which represents the total displacement across the fault) versus off-
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fault deformation.
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Figure S8. a) Locations of fault-zone width measurement plotted with the geologic maps which illustrates
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the range of near-surface materials used in the analysis [Dibblee, 1964a, 1964b; Dibblee, 1967a,
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1967b, 1967c]. b) shows enlargement of southern termination of
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Figure S9 a) Locations of off-fault deformation plotted with the geologic maps which illustrates the
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range of near-surface materials used in the analysis [Dibblee, 1964a, 1964b; Dibblee, 1967a, 1967b,
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1967c]. b) shows an enlargement of the Kickapoo stepover illustrating variation of OFD.
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Figure S10. a) Off-fault deformation plotted as a function of horizontal distance to the nearest outcrop of
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exposed bedrock which serves as a proxy for thickness of sediment. Larger distances from the nearest
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range front would expectedly have thicker amounts of sediment and therefore larger OFD and FZW. b)
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Shows fault-zone width plotted as a function of distance to bedrock, where location of bedrock exposures
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are determinded from the geologic map (Figure S3).
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Figure S11.a) Off-fault deformation plotted against the deviation of fault strike from a regional strike.
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The regional strike represents the regional stress field, and thus the deviation a proxy of the faults optimal
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orientation to the regional stress field. Faults with large deviations from zero (the presumed optimal
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faulting strike) will likely be misaligned with the regional stress field and likely yield larger OFD and
240
wider FZWs.
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Figure S12.a)Vertical offset plotted against off-fault deformation (%). Vertical deformation along a sub-
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vertical fault-plane can in places producing ponding of sediment against the fault scarp and therefore
244
produce local areas of thick sediment. Thicker sediment would expectedly produce larger amounts of
245
OFD.
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Figure S13. Fault-zone widths measured in alluvial fans of different inferred ages. Alluvial fan ages are
249
determinded relatively from multi-spectral aerial images and Google Earth and by analyzing the degree of
250
desert varnish development, surface texture and relative amount of incision of each fan. We designate
251
these with informal, local indexes as Q1 through Q4 from oldest to youngest, where degree of
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consolidation is expected to increase with age. a) Shows FZW for Q1, b) FZW for fans measured in Q2,
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c) FZWs measured in Q3 alluvial fans and d) FZWs measured in Q4 material.
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Figure S14. Off-fault deformation (%) measured in alluvial fans of different inferred ages. Q4 is the
258
youngest fan, assumed to be the least consolidated and most likely to produce the largest OFD. Q1 is the
259
oldest observable fan along the surface rupture and assumed to be the most consolidated and likely to
260
produce least strain accommodated off the primary fault strand. Alluvial fan ages are determinded
261
relatively from multi-spectral aerial images and Google Earth and analyzing the degree of desert varnish
262
development, surface texture and relative amount of incision of each fan. a) Shows OFD for Q1, b) OFD
263
for fans measured in Q2, c) OFD measured in Q3 alluvial fans and d) OFD measured in Q4 material.
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Figure S15 a) Mean OFD with 1 sigma error plotted for different zones of structural complexity with
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colored dots denoting different lithologies found within each bin of structural complexity. b) Mean FZW
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plotted with 1 sigma error for different zones of structural complexity with colored dots denoting different
269
lithologies found within each bin of structural complexity. We use three zones of structural complexity
270
instead of five, as used in the main text because this avoids parsing the data too finley and loosing sample
271
sizes.
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Figure S16. a) The Fault length of 69 individual faults plotted against mean displacement found along the
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given fault. Blue line shows best fit linear regression with R2 = 0.58 b) Fault length plotted against
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maximum displacement measured along the individual fault. Blue line shows best fitting linear model
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with R2 = 0.52. c) Mean OFD plotted as a function of length of fault. Blue line shows best fitting linear
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model with R2 = 0.10. d) Shows fault length plotted against the mean fault-zone width of each fault, red
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line shows best fitting linear model with R2 = 0.22.
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Figure S17 (a) Subset of the north-south correlation result along the southern section of the
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Johnson Valley fault, with location of profiles labelled. Color bar shows magnitude of pixel
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movement, blue is movement to the north and yellow towards the south. (b) Google earth image
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acquired of the same aerial extent as (a), illustrating the types of near-surface material and extent
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of the alluvial channel and location of profile transects.(c) Profile drawn across the Holocene
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alluvial channel showing the surface deformation signal taken from the correlation result in a).
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The signal exhibits a wide fault-zone of 68 m, as delineated by the red, vertical dashed lines and
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horizontal arrow. (d) Surface displacement signal from a profile drawn across the Landers
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surface rupture from a), within a Pleistocene, more consolidated alluvial fan, which shows a
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narrower 18 m fault-zone as delineated by the red, vertical dashed lines.
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Table S1
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Below is all 1060 measurements we made from our COSI-Corr correlation map. These
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contain all the measurements made and used in our statistical analysis that were extracted from
297
our correlation maps. Note there are numerous nan values in the OFD column, which represents
298
no OFD was found, because we could only measure OFD where a COSI-Corr measurement
299
could be sufficiently matched with a nearby field measurement at that location.
300
UTM
Easting
UTM
Northing
Displacement (m)
Displacemen
t error (1σ)
550338
550428
550524
550590
550650
550704
550758
550812
550866
550926
550998
551058
551094
551142
551166
551190
3795930
3795798
3795660
3795528
3795390
3795258
3795120
3794988
3794856
3794718
3794586
3794448
3794316
3794184
3794046
3793914
3.06
3.29
3.04
3.07
2.95
2.77
2.79
2.90
2.85
2.62
2.75
2.88
2.87
2.23
1.55
1.73
0.07
0.07
0.06
0.06
0.07
0.06
0.06
0.06
0.07
0.07
0.07
0.06
0.07
0.07
0.09
0.07
Fault
zone
width
(m)
174.00
234.00
132.00
48.00
66.00
42.00
24.00
222.00
198.00
30.00
66.00
156.00
90.00
93.50
30.00
30.00
Stack
Azimut
h
OFD
(m)
OFD
error (1
σ)
56.26
55.41
56.26
67.36
67.56
67.56
67.80
67.80
67.80
63.43
61.83
75.54
67.95
77.36
80.91
80.24
1.96
1.25
NaN
NaN
NaN
NaN
0.43
NaN
0.05
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.12
0.16
NaN
NaN
NaN
NaN
0.06
NaN
0.24
NaN
NaN
NaN
NaN
NaN
NaN
NaN
25
26
551220
551274
551316
551340
551358
551382
551406
551424
551448
551466
551490
551508
551532
551550
551556
551550
551568
551580
551592
551598
551586
551562
547848
547938
548034
548130
548226
548316
548412
548508
548598
548682
548772
548862
548946
549036
549126
549210
549294
549378
549468
3793776
3793644
3793506
3793374
3793242
3793104
3792972
3792834
3792702
3792564
3792432
3792294
3792156
3792018
3791880
3791736
3791586
3791442
3791310
3791178
3791040
3790902
3799998
3799866
3799734
3799596
3799464
3799332
3799200
3799062
3798930
3798798
3798660
3798528
3798396
3798258
3798126
3797994
3797862
3797724
3797592
1.36
1.85
3.35
3.34
3.58
3.27
3.26
3.31
2.97
3.12
3.19
3.39
3.08
2.96
2.89
2.87
3.04
3.07
3.10
2.79
2.75
2.54
0.13
0.14
0.17
0.21
0.50
0.67
0.84
0.85
0.76
0.65
0.69
0.87
0.96
1.00
1.13
1.24
1.37
1.25
1.31
0.09
0.07
0.07
0.07
0.07
0.07
0.07
0.07
0.07
0.06
0.06
0.07
0.06
0.06
0.07
0.07
0.07
0.06
0.07
0.06
0.06
0.07
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.07
0.07
0.06
0.06
0.06
0.06
0.06
0.06
42.00
48.00
408.00
474.00
468.00
516.00
654.00
678.00
342.00
372.00
552.00
372.00
102.00
72.00
66.00
120.00
126.00
144.00
66.00
138.00
102.00
60.00
78.00
102.00
186.00
138.00
102.00
102.00
168.00
126.00
78.00
30.00
48.00
48.00
48.00
30.00
36.00
48.00
48.00
48.00
42.00
69.52
68.19
80.24
80.91
80.46
80.24
81.29
80.91
81.29
81.02
81.29
81.02
81.07
81.35
97.54
84.30
84.30
84.08
84.64
93.73
94.35
100.69
55.02
54.64
54.68
54.76
55.02
54.64
54.68
54.76
57.29
57.01
56.69
56.26
57.09
57.29
56.85
56.41
59.46
55.41
56.41
NaN
NaN
NaN
0.42
0.71
NaN
0.76
NaN
NaN
NaN
0.69
NaN
NaN
NaN
0.01
NaN
NaN
NaN
0.30
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.26
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.88
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.12
0.12
NaN
0.53
NaN
NaN
NaN
0.31
NaN
NaN
NaN
0.61
NaN
NaN
NaN
0.59
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.06
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.08
NaN
NaN
NaN
NaN
26
27
549558
549648
549738
549822
549900
550008
550062
550134
550206
550278
552462
552456
552444
552450
552456
552456
552420
552426
552438
552438
552438
552438
552432
552420
552414
552408
552390
552360
552366
552354
552342
552336
552336
552348
551556
551538
551538
551682
551676
551712
551700
3797460
3797322
3797190
3797058
3796920
3796656
3796524
3796386
3796254
3796122
3782508
3782382
3782250
3782124
3781992
3781866
3781746
3781614
3781488
3781308
3781152
3781020
3780882
3780750
3780606
3780480
3780348
3782754
3782628
3782490
3782358
3782232
3782100
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48.00
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30.00
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84.00
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108.00
90.00
54.00
60.00
150.00
312.00
372.00
420.00
546.00
600.00
636.00
768.00
582.00
672.00
810.00
864.00
102.00
198.00
108.00
72.00
48.00
36.00
60.00
102.00
174.00
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54.00
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36.00
55.98
55.56
57.21
59.34
60.40
67.56
64.53
61.78
62.00
56.49
83.07
98.71
86.61
90.00
86.32
98.76
98.43
83.18
89.38
90.00
90.00
93.56
93.56
93.56
93.34
94.35
95.36
79.31
95.08
94.74
93.68
93.73
86.32
86.32
99.09
100.20
77.52
96.43
88.30
107.13
93.39
0.54
0.69
NaN
NaN
0.08
NaN
NaN
NaN
NaN
1.14
NaN
NaN
0.34
NaN
NaN
NaN
NaN
NaN
0.59
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.07
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NaN
0.88
NaN
0.02
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NaN
NaN
0.15
NaN
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0.12
NaN
NaN
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NaN
NaN
NaN
NaN
NaN
0.11
NaN
NaN
NaN
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NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.13
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NaN
NaN
0.21
NaN
0.13
NaN
NaN
NaN
27
28
551202
551196
551196
551196
551202
551202
551196
551190
551178
551166
551556
551502
551460
551424
551370
551298
551208
551094
550986
551520
551454
551688
551706
551598
551610
551616
551670
551688
551712
551748
551784
551820
551826
551790
551760
551742
551748
551748
551754
551772
551760
3789030
3788898
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3788406
3788280
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0.84
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0.37
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1.02
0.85
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0.33
0.30
0.30
0.41
2.21
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2.56
1.97
1.61
1.97
1.87
1.87
1.44
1.36
1.34
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1.86
1.91
1.94
2.00
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0.06
840.00
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552.00
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90.00
42.00
27.50
234.00
114.00
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36.00
30.00
108.00
30.00
66.00
30.00
96.00
42.00
30.00
24.00
48.00
87.50
84.00
93.51
90.00
90.00
86.83
90.00
90.00
93.73
95.08
95.42
95.42
116.57
108.16
107.44
106.72
120.24
123.98
139.31
142.39
141.05
124.75
114.11
81.51
86.27
85.65
86.27
85.65
72.71
84.30
75.80
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75.17
76.12
103.23
102.70
102.70
89.38
90.00
86.83
86.83
88.36
95.92
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.25
NaN
0.48
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NaN
NaN
NaN
0.25
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NaN
NaN
NaN
0.05
NaN
NaN
1.07
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NaN
NaN
NaN
0.84
NaN
0.24
NaN
0.67
NaN
0.24
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NaN
NaN
NaN
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NaN
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NaN
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NaN
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NaN
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NaN
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NaN
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NaN
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NaN
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0.36
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28
29
551748
551748
551742
551724
551706
551688
551694
551688
551670
551676
551646
551628
551610
551604
551622
551640
551616
551598
551580
551592
551634
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551736
551754
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551802
551856
551904
551952
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552048
552120
552192
552258
552300
552384
552438
552600
552660
3788178
3788040
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3783450
3783312
3783174
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3782658
3782544
1.45
1.30
2.16
2.22
2.58
2.54
2.73
2.28
1.14
1.04
2.49
2.30
2.39
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1.79
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2.43
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2.13
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2.01
2.09
1.90
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2.11
1.94
2.13
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24.00
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36.00
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354.00
36.00
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24.00
24.00
30.00
36.00
30.00
174.00
75.50
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42.00
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51.50
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95.70
96.04
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86.32
94.52
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97.38
85.42
81.62
91.98
97.93
97.93
97.88
75.70
75.17
77.79
81.24
80.79
81.07
80.91
80.57
76.71
69.22
69.82
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71.43
70.32
63.43
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63.43
72.30
58.26
54.10
53.42
73.80
0.05
NaN
NaN
0.32
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NaN
0.55
1.08
1.10
NaN
2.24
NaN
1.79
1.72
NaN
2.10
NaN
NaN
0.71
1.03
0.19
NaN
NaN
NaN
NaN
0.67
NaN
NaN
NaN
NaN
0.46
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.30
NaN
NaN
0.40
0.09
NaN
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NaN
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NaN
0.14
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NaN
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NaN
NaN
0.27
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NaN
NaN
NaN
NaN
0.18
NaN
NaN
NaN
NaN
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NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
29
30
552696
552804
552930
553068
553080
553086
553122
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553170
553206
553248
553290
553338
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0.80
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0.68
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0.95
0.84
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0.78
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0.56
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553440
3780534
0.86
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551208
551262
551322
551376
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550440
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550476
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3794214
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0.55
1.28
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0.06
258.00
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426.00
444.00
432.00
1158.0
0
42.00
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414.00
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144.00
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70.32
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NaN
NaN
NaN
NaN
NaN
NaN
0.11
0.07
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NaN
0.08
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NaN
0.08
NaN
NaN
NaN
NaN
NaN
NaN
69.72
NaN
NaN
69.52
64.81
64.72
64.81
96.65
56.69
66.84
100.25
84.24
83.74
84.02
102.26
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81.90
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95.53
93.68
92.88
92.32
93.56
95.31
NaN
NaN
NaN
NaN
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NaN
NaN
NaN
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0.40
NaN
NaN
NaN
1.91
NaN
NaN
NaN
1.81
1.15
NaN
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NaN
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NaN
NaN
NaN
NaN
NaN
NaN
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NaN
NaN
NaN
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NaN
NaN
NaN
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NaN
NaN
NaN
0.12
0.12
NaN
0.61
0.12
NaN
0.31
NaN
NaN
30
31
550326
550296
550260
550230
550188
550134
550086
550086
550080
550062
550038
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550830
3799068
3798936
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3798528
3798390
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3797484
3797346
3797214
2.21
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2.23
2.22
2.03
1.85
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1.84
1.69
1.77
1.50
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1.22
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0.07
0.06
66.00
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96.00
54.00
60.00
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126.00
192.00
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72.00
108.00
96.00
24.00
15.50
24.00
30.00
27.50
84.00
78.00
108.00
78.00
48.00
48.00
24.00
42.00
30.00
24.00
48.00
30.00
36.00
90.00
60.00
60.00
57.50
78.00
36.00
100.20
103.13
103.23
104.67
110.78
110.48
99.43
93.68
92.15
99.76
98.93
88.30
90.00
93.84
93.68
90.00
90.00
78.60
73.28
79.31
64.16
56.77
97.38
93.39
90.00
93.56
95.42
95.92
96.04
96.54
100.63
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91.19
82.01
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78.55
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NaN
NaN
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NaN
NaN
0.75
NaN
NaN
NaN
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NaN
NaN
NaN
NaN
0.71
NaN
NaN
NaN
NaN
NaN
0.35
NaN
NaN
NaN
NaN
NaN
NaN
0.26
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.01
NaN
NaN
NaN
NaN
0.12
NaN
NaN
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NaN
NaN
NaN
0.07
NaN
NaN
NaN
NaN
0.08
NaN
NaN
NaN
NaN
NaN
0.10
NaN
NaN
NaN
NaN
NaN
NaN
0.07
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.09
NaN
31
32
550818
550824
550830
550842
550866
550890
550890
552552
552534
552492
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0.33
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84.00
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66.00
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276.00
432.00
276.00
246.00
180.00
270.00
300.00
564.00
288.00
126.00
48.00
36.00
96.00
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2.40
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NaN
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32
33
543744
543882
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2.48
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0.32
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1.21
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0.57
NaN
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0.43
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1.04
NaN
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NaN
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NaN
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NaN
33
34
546642
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4.82
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550614
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102.00
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474.00
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57.50
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81.50
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324.00
1050.0
0
56.49
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56.41
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42.08
44.14
43.16
45.00
36.98
NaN
NaN
NaN
NaN
NaN
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NaN
NaN
2.49
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NaN
NaN
0.52
NaN
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1.65
NaN
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NaN
0.36
NaN
NaN
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NaN
NaN
0.83
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3.51
NaN
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NaN
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NaN
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NaN
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NaN
NaN
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NaN
0.51
NaN
NaN
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NaN
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NaN
NaN
NaN
NaN
0.92
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NaN
86.44
NaN
NaN
34
35
550620
3803394
3.77
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550620
3803262
3.64
0.06
550626
3803124
3.82
0.07
550626
550632
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3.92
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1098.0
0
984.00
1032.0
0
996.00
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NaN
87.45
NaN
NaN
90.00
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NaN
90.00
88.81
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86.83
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53.24
68.53
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63.43
63.43
87.62
86.27
71.07
66.26
61.87
NaN
NaN
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NaN
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NaN
0.41
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NaN
NaN
1.66
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NaN
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NaN
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NaN
NaN
NaN
0.11
NaN
0.34
0.99
0.48
NaN
NaN
0.25
0.33
NaN
NaN
NaN
NaN
NaN
NaN
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NaN
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NaN
NaN
NaN
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NaN
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NaN
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NaN
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NaN
NaN
0.16
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NaN
35
36
552660
542070
542118
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542232
542286
542334
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542400
542472
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542610
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0.82
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0.07
0.07
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0.06
336.00
102.00
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42.00
96.00
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72.00
60.00
72.00
78.00
90.00
156.00
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48.00
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66.00
54.00
42.00
69.50
126.00
60.00
84.00
96.00
90.00
84.00
33.50
45.50
54.00
60.00
114.00
57.29
67.27
64.76
65.04
65.04
65.04
79.04
80.30
59.50
59.55
59.13
59.84
67.36
81.62
81.35
81.46
63.43
56.53
55.29
70.27
63.03
58.51
71.58
76.18
93.68
93.73
93.68
75.80
70.82
54.68
63.84
64.72
64.72
93.73
92.55
90.62
85.99
81.62
81.51
99.26
108.88
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.52
NaN
NaN
NaN
NaN
NaN
NaN
NaN
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NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.05
0.03
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.08
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.07
0.07
36
37
543612
543018
543090
543150
543216
543288
543432
543486
543516
543540
543570
543624
543690
543756
543834
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544344
544398
544452
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3817086
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3814938
0.19
0.28
0.44
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0.34
0.45
0.54
0.81
0.80
1.06
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1.12
1.06
1.03
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1.20
1.22
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0.06
0.06
0.07
0.07
0.06
0.07
0.07
126.00
78.00
42.00
48.00
66.00
96.00
84.00
102.00
48.00
54.00
114.00
150.00
96.00
60.00
66.00
90.00
132.00
144.00
108.00
162.00
39.50
45.50
51.50
174.00
222.00
150.00
150.00
192.00
180.00
132.00
72.00
72.00
294.00
126.00
114.00
138.00
156.00
210.00
186.00
216.00
168.00
80.24
56.34
63.43
65.04
63.43
38.75
46.73
71.18
78.33
77.74
74.90
63.43
63.43
60.83
60.31
60.31
50.11
46.93
53.68
68.09
66.50
66.17
66.69
64.90
64.81
93.68
92.88
106.09
116.57
90.62
90.00
86.61
84.75
85.26
86.32
63.96
93.39
90.00
93.73
96.26
83.68
NaN
NaN
NaN
0.32
NaN
NaN
NaN
NaN
0.38
0.23
0.95
NaN
NaN
NaN
NaN
NaN
NaN
0.91
NaN
0.55
0.61
NaN
0.45
NaN
NaN
NaN
NaN
0.94
NaN
NaN
0.52
NaN
0.45
0.62
0.52
NaN
0.38
NaN
0.00
NaN
NaN
NaN
NaN
NaN
0.07
NaN
NaN
NaN
NaN
0.10
0.08
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NaN
NaN
NaN
NaN
NaN
NaN
0.08
NaN
0.09
0.07
NaN
0.07
NaN
NaN
NaN
NaN
0.09
NaN
NaN
0.07
NaN
0.08
0.12
0.08
NaN
0.07
NaN
0.08
NaN
NaN
37
38
544848
544914
544980
545034
545088
545136
545178
545214
544542
544572
544608
544638
544674
544818
544920
545040
545268
545370
545412
545502
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108.00
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NaN
132.00
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NaN
NaN
NaN
0.13
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NaN
NaN
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0.14
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NaN
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NaN
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NaN
NaN
NaN
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NaN
NaN
38
39
548262
548394
548520
548652
548784
548916
544560
544692
544824
544962
545094
545232
545322
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547734
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3814332
3814200
3814062
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3813522
3813390
3813252
3813120
0.42
0.44
0.54
0.43
0.22
0.53
2.80
0.52
0.55
0.70
0.78
0.64
0.75
0.60
0.56
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0.59
0.67
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0.69
1.11
1.16
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0.48
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0.81
0.74
0.92
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0.95
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0.06
228.00
90.00
48.00
21.50
27.50
96.00
366.00
66.00
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102.00
66.00
78.00
102.00
156.00
78.00
102.00
102.00
96.00
96.00
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228.00
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66.00
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42.00
66.00
60.00
30.00
60.00
96.00
54.00
48.00
54.00
54.00
78.00
54.00
102.00
108.00
78.00
66.00
-20.03
0.17
11.78
11.99
12.10
29.60
38.12
42.15
42.20
38.12
37.87
45.90
55.91
55.48
45.31
45.00
46.48
39.44
38.91
42.37
43.37
52.48
52.59
52.52
54.46
56.41
56.61
76.93
79.20
79.80
79.91
78.55
78.71
78.06
70.32
67.85
64.90
64.81
64.90
65.09
71.53
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.57
NaN
0.26
0.40
NaN
0.54
NaN
1.08
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.18
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.09
NaN
0.10
0.08
NaN
0.11
NaN
0.07
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.09
NaN
NaN
NaN
NaN
NaN
NaN
NaN
39
40
547836
547896
547980
548064
548148
548202
548250
548298
548358
548418
548538
548646
548766
548856
548946
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548928
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548886
3812982
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0.87
0.41
0.84
1.11
1.14
1.29
0.90
0.70
0.60
0.99
1.07
1.44
1.31
1.27
0.97
0.95
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1.05
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0.92
1.01
1.17
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0.90
0.86
1.06
1.19
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0.99
0.95
0.99
1.11
2.13
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0.07
0.06
0.07
0.13
0.16
0.08
156.00
60.00
66.00
114.00
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102.00
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102.00
120.00
114.00
78.00
222.00
60.00
60.00
132.00
132.00
186.00
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84.00
120.00
102.00
174.00
240.00
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258.00
306.00
216.00
162.00
180.00
102.00
102.00
102.00
114.00
138.00
204.00
102.00
102.00
246.00
51.50
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42.00
72.04
58.71
59.13
59.13
59.55
71.63
71.07
68.83
67.03
55.25
49.54
49.31
51.99
56.26
56.26
62.58
65.09
65.23
86.04
94.58
107.60
108.37
107.44
107.29
107.50
107.34
91.81
90.00
93.73
75.38
42.91
78.11
87.91
97.04
97.54
103.88
103.61
103.40
103.45
103.34
103.07
NaN
NaN
NaN
NaN
NaN
0.29
0.20
NaN
NaN
NaN
NaN
0.54
NaN
NaN
NaN
NaN
NaN
NaN
0.86
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
1.00
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.22
0.16
NaN
NaN
NaN
NaN
0.18
NaN
NaN
NaN
NaN
NaN
NaN
0.09
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.10
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
40
41
542988
543078
543114
543096
543144
543120
543090
543060
543036
543012
543006
543006
542976
542934
542898
542838
542772
531384
531462
531504
531564
531690
531816
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532062
532116
532242
532368
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532620
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532860
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533406
533526
533646
3819498
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0.44
1.19
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2.16
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1.71
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1.75
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0.52
0.75
0.79
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1.22
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2.31
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3.24
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0.07
0.07
0.07
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0.07
0.07
0.07
474.00
432.00
456.00
420.00
426.00
60.00
60.00
90.00
186.00
366.00
240.00
318.00
54.00
204.00
162.00
300.00
324.00
84.00
72.00
108.00
126.00
324.00
312.00
48.00
84.00
27.50
72.00
78.00
102.00
210.00
210.00
156.00
204.00
222.00
276.00
732.00
666.00
630.00
636.00
48.00
48.00
81.24
45.92
99.09
99.54
104.20
103.13
104.20
102.64
101.18
101.45
79.53
103.61
104.89
106.67
106.93
128.01
105.78
48.86
69.22
69.37
49.27
42.09
41.99
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72.76
72.40
50.27
43.25
41.68
39.63
39.71
40.07
40.55
46.82
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49.09
46.30
46.75
25.14
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NaN
NaN
1.94
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NaN
NaN
0.94
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NaN
0.85
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NaN
0.93
NaN
1.18
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1.18
NaN
NaN
NaN
NaN
NaN
NaN
0.54
1.13
NaN
NaN
NaN
1.89
NaN
NaN
NaN
NaN
0.20
NaN
2.58
2.76
NaN
NaN
0.13
0.10
NaN
NaN
0.08
0.32
0.41
NaN
0.50
0.21
NaN
0.12
NaN
0.08
0.10
0.14
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0.07
NaN
NaN
NaN
NaN
NaN
NaN
0.07
0.09
NaN
NaN
NaN
0.13
NaN
NaN
NaN
NaN
0.21
NaN
0.07
0.07
41
42
533766
533886
534006
534126
534246
534360
534462
534600
534720
534840
534972
535092
535212
535332
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535596
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536088
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536340
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538032
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538704
3828696
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2.74
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3.37
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3.73
3.42
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3.40
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3.54
3.45
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3.11
4.05
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3.85
3.67
3.84
4.35
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4.06
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0.07
0.07
0.07
0.07
0.09
0.09
0.07
0.08
0.07
0.08
0.08
24.00
192.00
66.00
96.00
294.00
234.00
102.00
72.00
66.00
72.00
204.00
90.00
132.00
156.00
36.00
60.00
162.00
168.00
138.00
210.00
102.00
84.00
66.00
186.00
144.00
138.00
42.00
102.00
90.00
108.00
36.00
48.00
192.00
204.00
168.00
114.00
204.00
270.00
141.50
222.00
78.00
45.00
43.91
36.10
36.38
49.06
48.96
28.30
26.31
39.86
39.22
26.31
26.06
26.06
26.31
42.12
43.07
42.74
24.91
24.44
24.30
23.98
23.74
19.92
19.43
20.13
21.52
30.21
30.21
30.41
30.43
30.58
30.96
36.63
48.48
26.57
25.10
10.09
8.48
52.16
38.02
33.45
NaN
NaN
NaN
NaN
1.22
1.21
NaN
NaN
NaN
NaN
NaN
0.61
0.37
NaN
1.64
NaN
NaN
NaN
NaN
NaN
NaN
0.61
0.58
1.03
0.11
0.22
NaN
3.40
NaN
1.28
3.06
NaN
NaN
NaN
1.80
0.80
NaN
NaN
NaN
2.41
NaN
NaN
NaN
NaN
NaN
0.10
0.10
NaN
NaN
NaN
NaN
NaN
1.00
0.63
NaN
0.22
NaN
NaN
NaN
NaN
NaN
NaN
0.26
0.21
0.21
0.21
0.31
NaN
0.07
NaN
2.00
0.08
NaN
NaN
NaN
0.22
0.27
NaN
NaN
NaN
0.61
NaN
42
43
538806
538932
539034
539130
539196
539256
539328
539394
539466
539562
539652
539718
539784
539850
539916
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540150
540198
540246
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542124
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3822138
3822018
3821898
3821844
3821772
3821670
3821562
3821466
3821412
3821364
3821256
3821136
3821040
4.37
4.06
3.72
4.47
4.56
4.53
4.64
4.48
4.62
4.62
5.13
5.15
5.13
5.14
5.25
5.32
5.31
5.54
5.45
5.41
5.41
5.38
5.14
5.28
5.12
4.91
5.58
5.04
3.95
3.82
3.59
3.44
3.62
3.42
3.39
3.69
3.38
3.56
2.70
3.89
4.08
0.08
0.09
0.11
0.08
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0.08
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0.10
0.07
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53.24
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41.81
56.38
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43
44
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542394
542478
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542676
3820938
3820824
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3820344
3820230
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542766
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66.00
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552.00
786.00
900.00
960.00
1020.0
0
732.00
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52.66
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59.04
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44
45
527628
527748
527856
527976
528090
528204
528324
528432
528558
528666
528780
528900
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530082
530094
530082
530100
530130
530196
530250
530298
530364
530454
530544
530610
3836646
3836556
3836472
3836388
3836304
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3836052
3835962
3835872
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3835470
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3834780
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3834204
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3833628
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3833280
3833166
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3832716
3832602
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3832368
1.00
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1.46
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1.29
1.28
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1.12
1.22
1.58
1.63
1.98
2.18
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51.50
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60.00
51.50
51.50
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54.00
54.00
66.00
78.00
87.50
108.00
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51.50
36.00
54.00
84.00
102.00
324.00
276.00
276.00
414.00
420.00
390.00
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276.00
222.00
384.00
660.00
450.00
282.00
348.00
198.00
96.00
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66.00
312.00
41.27
36.01
35.90
35.84
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35.88
36.01
35.90
38.26
38.43
38.16
39.01
62.49
55.48
54.95
53.97
53.35
48.96
48.96
47.54
46.63
47.54
69.77
70.32
85.99
88.81
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69.52
69.37
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45
46
525354
525456
525558
525660
525762
541488
541482
541464
541416
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541098
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NaN
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38.95
38.74
38.64
39.09
39.05
92.15
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106.30
107.24
30.24
30.45
50.06
48.60
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71.63
72.09
74.64
76.93
83.68
77.30
66.03
66.17
13.49
24.66
24.98
35.52
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NaN
NaN
NaN
NaN
NaN
NaN
NaN
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NaN
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NaN
NaN
0.16
46
47
542298
542328
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542442
542502
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0.11
30.00
24.00
84.00
84.00
42.00
33.50
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27.50
54.00
60.00
72.00
60.00
24.00
84.00
72.00
18.00
12.00
3.50
21.50
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54.00
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36.00
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15.50
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84.00
66.00
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65.51
65.37
65.51
65.37
64.20
37.79
65.47
67.03
73.28
73.18
86.27
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74.59
68.83
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47
48
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66.17
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96.71
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59.04
62.36
63.43
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61.65
46.75
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73.75
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49.12
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81.13
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NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.10
NaN
0.08
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
48
49
538590
538668
538734
538800
538860
537924
537918
539514
539586
539658
530868
530952
531024
531096
531180
531258
531306
536742
536616
536496
536364
536232
536100
541272
541296
541362
541512
541632
544794
544920
544992
545010
545028
545046
534720
534816
534882
534966
535074
529212
529308
3826554
3826428
3826308
3826182
3826062
3826398
3826248
3824688
3824562
3824442
3832236
3832146
3832050
3831960
3831852
3831744
3831600
3826674
3826632
3826596
3826608
3826614
3826626
3821550
3821442
3821328
3821148
3821004
3819552
3819372
3819252
3819120
3818976
3818850
3827514
3827388
3827268
3827142
3827022
3835404
3835302
0.44
0.25
0.29
0.34
0.55
-0.54
-0.44
0.13
0.89
0.55
0.55
0.71
0.56
0.78
0.93
1.10
1.13
-0.12
-0.25
-0.26
-0.42
-0.24
-0.13
0.41
0.50
0.42
0.26
0.26
0.28
0.32
0.30
0.25
0.30
0.24
0.15
0.32
0.33
0.15
0.15
0.36
0.35
0.07
0.07
0.07
0.08
0.07
0.10
0.07
0.07
0.09
0.10
0.12
0.08
0.07
0.07
0.07
0.06
0.08
0.06
0.07
0.07
0.07
0.07
0.06
0.07
0.07
0.07
0.07
0.07
0.07
0.06
0.06
0.06
0.06
0.06
0.20
0.07
0.07
0.08
0.07
0.09
0.08
114.00
51.50
72.00
51.50
66.00
96.00
30.00
21.50
66.00
48.00
594.00
486.00
324.00
264.00
432.00
276.00
168.00
9.50
24.00
42.00
72.00
48.00
54.00
9.50
39.50
27.50
12.00
6.00
36.00
102.00
72.00
42.00
78.00
66.00
NaN
72.00
54.00
NaN
39.50
33.50
27.50
53.75
60.61
60.96
63.43
60.57
86.27
100.69
59.76
58.84
61.96
46.90
49.15
53.24
51.26
51.67
56.73
70.32
160.42
160.72
178.98
-175.42
-176.27
-175.31
77.84
75.33
50.37
50.78
50.37
82.96
56.98
70.62
82.12
82.01
82.12
47.11
60.40
59.72
51.46
46.11
45.60
49.06
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.52
0.24
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.17
NaN
NaN
NaN
0.16
0.25
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.10
0.14
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.09
NaN
NaN
NaN
0.14
0.10
49
50
529392
529476
529560
529632
529710
541890
541980
542076
542160
542250
542334
532602
532632
532716
532812
532836
532854
532872
532908
531762
531792
531822
531852
531888
531924
532044
532164
534738
534870
535008
535122
535206
535320
535452
535584
535710
535788
535920
536058
536190
536322
3835200
3835092
3834978
3834870
3834762
3821022
3820914
3820806
3820698
3820572
3820452
3830586
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3830364
3830256
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3829926
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3830280
3830178
3830082
3830010
3830472
3830346
3830214
3830088
3829956
3829818
3829692
3829560
3829428
3829296
3829170
3829032
3828906
3828774
0.19
0.50
0.47
0.77
0.90
0.91
0.73
0.64
0.43
0.74
0.66
0.18
0.17
0.18
0.34
0.31
0.19
0.25
0.11
1.18
1.07
0.76
0.53
0.56
0.44
0.68
0.85
0.16
0.23
0.30
0.23
0.12
0.25
0.81
1.47
1.34
1.19
0.79
0.64
0.91
0.70
0.10
0.07
0.07
0.06
0.08
0.16
0.09
0.10
0.08
0.07
0.09
0.07
0.06
0.06
0.06
0.07
0.06
0.07
0.07
0.06
0.07
0.07
0.06
0.08
0.06
0.06
0.07
0.07
0.07
0.08
0.07
0.07
0.07
0.07
0.07
0.27
0.07
0.07
0.07
0.07
0.07
12.00
54.00
48.00
30.00
48.00
174.00
105.50
192.00
210.00
186.00
234.00
15.50
24.00
12.00
54.00
54.00
15.50
24.00
15.50
60.00
102.00
84.00
120.00
180.00
120.00
84.00
78.00
168.00
408.00
312.00
198.00
108.00
168.00
366.00
222.00
306.00
156.00
132.00
180.00
72.00
204.00
50.78
53.71
54.64
54.80
57.37
51.74
49.61
49.77
53.68
55.02
54.34
76.77
60.52
50.74
58.71
83.52
78.82
79.31
59.38
74.74
76.12
75.06
74.32
74.53
48.61
34.93
32.10
43.07
43.16
43.25
57.37
58.67
43.52
45.00
43.10
69.57
43.90
45.00
43.37
45.00
43.16
NaN
NaN
NaN
0.67
0.56
NaN
NaN
NaN
NaN
0.29
0.46
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.41
0.49
NaN
NaN
NaN
0.56
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.48
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.06
0.09
NaN
NaN
NaN
NaN
0.26
0.10
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.10
0.06
NaN
NaN
NaN
0.08
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.11
NaN
NaN
NaN
NaN
50
51
536460
536586
536706
536838
536904
536916
536946
537012
537084
537150
537222
537288
537354
537426
537498
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3828642
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3827706
3827574
3827442
3827304
3827172
3827040
3826902
3826770
3826638
3826500
0.88
1.13
1.32
1.15
1.16
1.15
0.80
1.01
1.44
1.29
1.39
1.38
1.15
1.44
1.36
0.94
0.53
0.08
0.07
0.07
0.07
0.06
0.08
0.07
0.07
0.06
0.06
0.07
0.07
0.07
0.08
0.07
0.07
0.09
132.00
102.00
126.00
168.00
408.00
378.00
408.00
312.00
54.00
66.00
36.00
30.00
66.00
78.00
60.00
72.00
144.00
45.60
46.75
46.84
52.23
77.47
85.09
66.93
62.09
62.54
63.43
62.54
63.43
63.43
63.43
59.30
59.55
59.93
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.13
1.42
NaN
0.81
0.43
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
NaN
0.26
0.08
NaN
0.09
0.13
301
302
303
51