Crop Yield Prediction

Introduction

This project aims to predict crop yield using Multivariate Adaptive Regression Splines (MARS) implemented with the earth package by Stephen Milborrow. In this project we will walk through data loading, some exploratory data analysis, preprocessing, model specification, tuning, and performance evaluation.

Loading Packages

We’ll load tidymodels, ggthemr, earth and vip packages using pacman’s p_load() function.

pacman::p_load(tidymodels, readr, earth, ggthemr, vip)
ggthemr(palette = "fresh", layout = "scientific", spacing = 3)

Data Import

Here, we load the dataset and clean up column names for easier reference. Then, we review the data structure and conduct an initial exploration of its properties. The data was gotten from kaggle data repository. The dataset contains agricultural data for 1,000,000 samples aimed at predicting crop yield (in tons per hectare) based on various factors. The features of the data are:

• Region: The geographical region where the crop is grown (North, East, South, West).
• Soil Type: The type of soil in which the crop is planted (Clay, Sandy, Loam, Silt, Peaty, Chalky).
• Crop: The type of crop grown (Wheat, Rice, Maize, Barley, Soybean, Cotton).
• Rainfall mm: The amount of rainfall received in millimeters during the crop growth period.
• Temperature Celsius: The average temperature during the crop growth period, measured in degrees Celsius.
• Fertilizer Used: Indicates whether fertilizer was applied (True = Yes, False = No).
• Irrigation Used: Indicates whether irrigation was used during the crop growth period (True = Yes, False = No).
• Weather Condition: The predominant weather condition during the growing season (Sunny, Rainy, Cloudy).
• Days to Harvest: The number of days taken for the crop to be harvested after planting.
• Yield tons per hectare: The total crop yield produced, measured in tons per hectare.

crop_yield <- read_csv("data/crop_yield.csv") |> 
  janitor::clean_names()

To get a detailed summary of the data, we use skimr()

skimr::skim_without_charts(crop_yield)

Table 1: Data Properties

(a)

Name	crop_yield
Number of rows	1000000
Number of columns	10
_______________________
Column type frequency:
character	4
logical	2
numeric	4
________________________
Group variables	None

Variable type: character

(b)

skim_variable	n_missing	complete_rate	min	max	empty	n_unique	whitespace
region	0	1	4	5	0	4	0
soil_type	0	1	4	6	0	6	0
crop	0	1	4	7	0	6	0
weather_condition	0	1	5	6	0	3	0

Variable type: logical

(c)

skim_variable	n_missing	complete_rate	mean	count
fertilizer_used	0	1	0.5	FAL: 500060, TRU: 499940
irrigation_used	0	1	0.5	FAL: 500509, TRU: 499491

Variable type: numeric

(d)

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100
rainfall_mm	0	1	549.98	259.85	100.00	324.89	550.12	774.74	1000.00
temperature_celsius	0	1	27.50	7.22	15.00	21.25	27.51	33.75	40.00
days_to_harvest	0	1	104.50	25.95	60.00	82.00	104.00	127.00	149.00
yield_tons_per_hectare	0	1	4.65	1.70	-1.15	3.42	4.65	5.88	9.96

The result from Table 1 shows the data is complete.

To ensure proper model performance, we mutate character columns into factors. This prepares the categorical variables for further analysis.

crop_yield <- crop_yield |> 
  mutate(
    across(where(is.character), factor)
  )

Exploratory Data Analysis

Let’s explore some of the relationship between the target variables and the predictors.

ggplot(
  data = crop_yield, 
  aes(region, y = after_stat(count), fill = crop)
) +
  geom_bar(position = "dodge") +
  coord_flip() +
  labs(
    x = "Count",
    y = "Regions",
    title = "Equal distibution of crops across regions"
  ) +
  theme(
    axis.ticks.x = element_blank()
  )

Warning: The `scale_name` argument of `discrete_scale()` is deprecated as of ggplot2
3.5.0.

Figure 1: Crop frequency across regions is equal. Figure show equal number of replication for the crops across regions

Figure 1 shows that crops are fairly equal in distribution across the regions. The same can also be said for the yield across across the different soil types Figure 2.

ggplot(
  crop_yield,
  aes(soil_type, yield_tons_per_hectare, fill = crop)
) +
  geom_col(position = "dodge") +
  labs(
    x = "Soil Type",
    y = "Yield (tons per hectare)"
  )

Figure 2: Yield from the soil types for the different crops are the same

crop_yield |> 
  ggplot(aes(yield_tons_per_hectare)) +
  geom_histogram() +
  labs(
    x = "Yield (tons per hectare)",
    y = "Count",
    title = "Target variable distribution"
  ) +
  theme(
    plot.title = element_text(hjust = .5)
  )

`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Figure 3: Yield distribution

Modeling

Data sharing

The data will be split into two part. The first which is the training data will be 70 % of all data and the second, the testing data will be 30 % of all the data.

set.seed(1012)
crop_yield_split <- crop_yield |> initial_split(prop = c(.7))

crop_train <- training(crop_yield_split)
crop_test <- testing(crop_yield_split)

Given the size of the training data, 700000 rows, 5 folds cross validation data will be used for evaluating the models.

crop_fold <- vfold_cv(crop_train, v = 5)

Model Specification

As stated in the start, we’ll be using the multivariate adaptive regression splines (MARS) model. Two parameters, the prod_degree, which captures the maximum degree of interactions, and the num_terms which determine the maximum number of features to retain in the final model will be tuned.

mars_spec <- mars(
  prod_degree = tune(),
  num_terms = tune()
) |> 
  set_mode("regression") |> 
  set_engine("earth")

Feature Engineering

MARS model generally require less preprocessing except creating dummy variables. Feature engineering methods and steps such as feature decorrelation and data transformation are not needed but might help the model.

mars_rec <- recipe(
  yield_tons_per_hectare ~ .,
  data = crop_train
  ) |> 
  step_mutate(across(where(is_logical), \(x) factor(x))) |> 
  step_pca(all_numeric_predictors()) |> 
  step_dummy(all_factor_predictors())

The preprocessed data can be seen in Table 2

mars_rec |> 
  prep() |> 
  juice() |>
  head(n = 1000) |> 
  knitr::kable()

Table 2: Preprocessed crop yield data. Logical features were firstly converted to factors, and principal component analysis applied on all numeric predictors to decorrelate the data before converting all factor variables to dummy data.

yield_tons_per_hectare	PC1	PC2	PC3	region_North	region_South	region_West	soil_type_Clay	soil_type_Loam	soil_type_Peaty	soil_type_Sandy	soil_type_Silt	crop_Cotton	crop_Maize	crop_Rice	crop_Soybean	crop_Wheat	fertilizer_used_TRUE.	irrigation_used_TRUE.	weather_condition_Rainy	weather_condition_Sunny
3.4007309	-443.5131	-3.2544271	6.5953117	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1
5.7512281	-413.4660	38.4651334	-4.7839110	0	1	0	1	0	0	0	0	0	0	0	1	0	1	1	0	1
1.0089759	-168.7606	87.5538465	-6.0975899	0	1	0	0	0	0	0	1	0	0	0	1	0	0	0	0	1
3.7173872	-394.7569	45.5903100	10.3686348	1	0	0	0	0	1	0	0	0	0	0	0	0	0	1	1	0
5.3969866	-720.9266	-46.7551966	15.2481557	0	1	0	0	0	0	1	0	0	1	0	0	0	1	0	0	1
5.4518593	-711.6603	-41.3647498	19.2116423	0	1	0	0	1	0	0	0	0	1	0	0	0	1	0	1	0
3.6847372	-495.8147	13.1038455	16.1939490	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1	1	0
3.0231389	-686.8627	25.5219354	-11.4658760	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	1	0
1.7232956	-323.3785	36.9915343	8.6552575	1	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0
4.6344744	-950.9416	-69.5868045	-2.8519015	0	0	1	0	0	0	1	0	0	0	0	1	0	0	0	1	0
1.7470245	-277.6119	94.8666909	3.3706059	0	1	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1
5.8388460	-744.2276	28.8373686	-16.1826853	1	0	0	1	0	0	0	0	0	1	0	0	0	1	0	1	0
6.9120319	-872.8384	-41.7072329	6.8584246	0	1	0	0	1	0	0	0	0	0	0	0	0	1	0	1	0
3.5802921	-240.0413	58.2084201	1.9630820	1	0	0	0	1	0	0	0	0	0	0	0	1	1	0	1	0
5.9702427	-810.7648	-28.6007998	-7.7296912	0	1	0	1	0	0	0	0	0	1	0	0	0	0	1	0	0
5.5212996	-962.8168	-61.4827331	-4.4806095	0	1	0	0	1	0	0	0	0	0	0	0	1	0	1	0	1
8.2644676	-1005.1906	-16.2531142	-17.9959450	0	0	0	0	0	0	0	0	0	0	1	0	0	1	1	1	0
2.6170623	-261.3142	37.6294917	8.8437005	1	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	1
1.2933271	-221.4408	86.5704468	-0.1552813	0	1	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0
4.5754139	-554.1366	0.8347687	16.8366677	0	1	0	0	0	0	1	0	0	1	0	0	0	0	1	0	1
4.1355801	-192.6099	49.8051290	19.8209766	0	1	0	0	0	0	0	0	0	1	0	0	0	1	1	0	0
3.5833654	-401.2845	52.4689066	-11.4656548	0	1	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0
3.4961461	-671.5287	-23.9025896	12.6958034	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	1
2.0240696	-385.8237	75.9651378	5.4313029	1	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	0
4.4702756	-556.4865	-3.4993558	7.6085121	0	1	0	1	0	0	0	0	0	0	0	0	1	1	0	0	0
2.6369102	-309.2241	94.1466605	-15.8569091	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	0	1
4.7785643	-734.4747	-20.6729247	-3.2105890	1	0	0	0	1	0	0	0	0	1	0	0	0	0	1	0	0
4.7404358	-643.3828	50.6757693	-3.2353822	1	0	0	0	0	0	1	0	0	0	1	0	0	0	1	0	1
4.2476672	-399.0755	71.8376503	0.6495655	0	0	1	0	0	0	1	0	1	0	0	0	0	1	0	0	0
3.1529306	-598.4676	24.8970443	-2.6472120	1	0	0	0	0	1	0	0	0	0	1	0	0	0	0	1	0
6.9765019	-814.5275	16.4940887	-1.5522390	0	0	0	0	0	0	0	1	0	0	0	0	1	1	1	0	1
4.4181121	-522.9164	32.8871108	-2.2873263	0	1	0	0	1	0	0	0	0	0	1	0	0	1	0	1	0
2.0831751	-126.8781	103.7691760	-9.9791434	0	0	0	0	0	0	0	1	0	0	0	0	1	0	1	1	0
4.6632981	-532.6092	17.1725916	14.2671621	0	1	0	0	1	0	0	0	0	0	0	0	1	0	1	1	0
4.9752266	-686.0732	25.6109428	-1.5719943	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	1	0
3.6300717	-415.7840	2.4882849	18.0693031	0	0	1	0	0	0	0	0	0	0	0	1	0	1	0	1	0
6.4523341	-997.9162	-74.9602323	-7.6363843	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0
6.0112715	-818.8715	-25.8789875	-13.3425221	0	0	0	0	0	0	1	0	1	0	0	0	0	1	0	0	0
4.3661961	-839.1552	-26.0351393	1.6664309	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1
5.1992998	-201.9132	50.4526120	10.0629973	0	0	0	0	0	1	0	0	0	0	1	0	0	1	1	0	0
4.0366910	-722.2231	-27.4922383	4.3886675	0	0	1	0	0	1	0	0	0	0	0	0	1	0	0	1	0
3.5889826	-238.2678	91.3990317	-3.8283655	0	0	1	0	0	1	0	0	0	0	0	1	0	1	1	0	1
3.3862257	-253.1853	84.8342756	5.9877058	1	0	0	0	0	1	0	0	1	0	0	0	0	1	0	1	0
3.3523189	-595.1667	52.6834751	-5.7502941	1	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0
4.7919624	-875.9382	7.1301541	-14.5667214	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0
6.9460113	-702.8506	-8.2979918	12.3828018	0	0	1	0	0	0	0	1	1	0	0	0	0	1	1	0	0
1.9405124	-189.2673	79.2593569	14.7421572	0	0	1	1	0	0	0	0	0	0	1	0	0	0	0	1	0
5.6777701	-969.0637	-82.4248910	14.1313447	0	0	1	0	0	0	1	0	0	1	0	0	0	0	0	1	0
6.4888201	-762.6764	-32.1070405	8.3061303	0	1	0	0	0	0	0	0	0	0	0	1	0	1	1	0	1
5.2197868	-638.2067	16.7834094	8.8424935	1	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0
2.9983532	-282.6216	39.0062232	17.0106199	1	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	0
3.2140991	-309.0261	45.6540870	14.5422432	0	1	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0
6.3233832	-846.5185	-62.0989419	-2.2030631	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0
7.4470691	-994.3449	-84.6029861	13.0948680	1	0	0	0	0	0	1	0	0	0	1	0	0	1	1	1	0
3.5663459	-754.8177	5.3919034	-1.3608244	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1
4.3447306	-340.9454	61.3961438	10.3268960	1	0	0	1	0	0	0	0	0	0	0	1	0	1	1	0	0
2.7466467	-491.4531	58.9693042	4.7008067	1	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1
0.4946346	-161.5081	57.4026657	2.4567212	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0
3.1621706	-358.6578	22.4308811	0.3589035	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0
3.2516285	-243.8357	29.2357258	9.7405682	0	0	1	0	0	0	0	0	0	1	0	0	0	1	0	0	0
1.1113103	-123.7512	114.5890046	10.1152081	0	0	1	0	0	0	0	1	0	0	0	0	1	0	0	0	0
4.5051287	-611.2904	-20.2209814	3.9573194	0	1	0	0	0	1	0	0	0	0	0	0	0	0	1	1	0
7.3947749	-810.5449	-34.1251994	5.4628878	0	0	0	0	0	1	0	0	0	0	0	0	0	1	1	0	1
5.6960466	-988.0859	-40.8155210	-15.0405340	0	0	1	0	0	0	1	0	1	0	0	0	0	0	0	0	1
5.3971366	-747.5126	-12.1129509	-1.7128336	0	1	0	0	0	0	1	0	0	0	0	1	0	1	0	0	0
3.0579990	-391.1635	34.2275497	2.5501523	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0
3.1550897	-149.5295	64.5764741	18.0422808	1	0	0	0	0	0	0	1	1	0	0	0	0	1	1	1	0
0.7741661	-204.6583	119.6636650	2.0568929	1	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	1
6.1482207	-511.1522	29.4710550	7.1711264	0	0	1	0	0	0	1	0	0	0	0	1	0	1	1	0	1
4.3991915	-675.1055	5.2790055	1.5938923	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1
5.4158483	-799.0493	-63.7442122	8.2757748	0	0	1	1	0	0	0	0	0	0	0	0	1	1	0	0	0
5.5254783	-703.0114	38.9456881	-3.9860368	0	1	0	0	0	0	0	1	0	0	1	0	0	0	1	1	0
5.2628468	-966.1125	-40.2704605	0.7541382	1	0	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0
7.3276775	-856.2400	-35.1210266	-9.1968654	1	0	0	0	0	0	0	1	0	1	0	0	0	1	1	0	1
3.2178113	-432.6284	-0.2544391	-2.3529524	0	0	1	0	1	0	0	0	0	0	0	1	0	1	0	1	0
7.8189852	-822.8985	-20.4399871	-3.8438921	1	0	0	1	0	0	0	0	0	0	0	1	0	1	1	0	0
3.3472399	-316.5635	55.3917554	-2.6428065	0	0	1	0	0	1	0	0	0	0	1	0	0	0	1	1	0
5.7537109	-839.7147	-31.9939865	-11.8374312	0	1	0	1	0	0	0	0	1	0	0	0	0	0	1	0	1
3.8318727	-525.0461	11.4747909	-4.2791470	0	0	1	1	0	0	0	0	0	0	0	1	0	0	1	0	1
6.6339019	-956.4380	-75.7190742	11.8216925	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0	1	0
3.9972611	-173.2195	96.8129699	12.2861965	1	0	0	0	1	0	0	0	0	0	1	0	0	1	1	0	1
6.7802046	-704.5575	-4.3295554	-12.2759326	0	0	0	0	0	0	0	1	0	0	0	0	0	1	1	1	0
5.3322213	-855.9965	-71.0544011	16.9136133	0	1	0	0	0	0	0	1	0	1	0	0	0	0	0	0	1
6.2124593	-625.7750	-11.2835448	8.4200247	0	0	1	0	0	0	0	1	1	0	0	0	0	1	1	0	1
4.1596184	-573.0405	22.1261086	-5.7032321	0	0	0	0	0	0	0	1	0	1	0	0	0	0	1	0	1
5.3260310	-651.6647	9.0284146	-8.4261225	1	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	1
4.9030226	-349.3675	93.2892297	6.1368595	0	0	1	0	0	0	0	0	0	0	0	0	1	1	1	1	0
3.3449965	-380.0887	11.6012576	-0.5154135	0	1	0	0	0	1	0	0	0	0	0	1	0	0	1	1	0
0.8748902	-129.4524	102.3394647	10.2368628	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1
8.3926429	-866.4641	-14.0487885	0.7418755	1	0	0	0	0	0	0	1	0	1	0	0	0	1	1	0	0
3.0062679	-141.2750	97.0176864	13.6324814	0	1	0	0	0	0	0	1	0	0	1	0	0	0	1	0	1
3.3423274	-435.3880	48.6672786	1.5529309	1	0	0	0	1	0	0	0	0	0	1	0	0	1	0	0	0
5.4658464	-631.3472	10.6210598	-6.3845896	0	0	1	0	0	1	0	0	0	0	0	1	0	0	1	0	0
3.1752940	-245.2288	96.3023701	10.3768534	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	1	0
4.6335297	-352.4818	67.1932729	12.2990132	0	0	1	0	0	0	1	0	0	0	0	0	0	1	0	0	0
4.0718863	-464.6855	18.1188507	-3.7076736	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	1	0
4.3408332	-577.1773	0.6634312	13.7674457	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0
5.4448235	-988.1821	-43.5195930	-13.0374796	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0
6.1853760	-784.7867	-48.9506160	8.8631950	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0
2.6881610	-303.1524	79.8933363	5.6382134	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	1	0
3.2529480	-333.2807	72.3298075	-12.8469427	0	0	1	0	0	1	0	0	0	0	1	0	0	1	0	0	0
4.3050642	-269.2587	26.0587662	8.9818179	0	0	1	0	0	0	1	0	1	0	0	0	0	1	1	0	0
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6.1105427	-964.2808	-32.1539307	3.6400508	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0
4.5110316	-339.0350	98.1122653	-8.6054509	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	0
2.8028519	-122.0556	58.3922494	6.8288522	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0
8.1109551	-954.3929	-20.8462653	-14.4020922	1	0	0	0	1	0	0	0	0	1	0	0	0	1	1	1	0
6.0894783	-837.6277	-28.3024032	4.5364869	0	0	1	0	0	0	0	1	0	0	0	0	1	0	1	0	1
5.2756628	-817.8507	-59.5945488	-2.2089459	0	0	0	0	1	0	0	0	1	0	0	0	0	0	1	0	1
3.1321989	-478.3769	26.2680689	6.3695401	0	0	0	0	1	0	0	0	0	0	1	0	0	0	1	1	0
4.9637088	-906.8462	-10.0085591	-18.6821839	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0
3.0907945	-221.1214	86.0177814	-8.1347538	0	0	0	0	1	0	0	0	0	0	0	1	0	1	1	1	0
6.3361851	-903.5577	-31.4526678	-14.9677230	0	1	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0
6.8824752	-733.1694	-42.3311902	1.0017099	0	0	1	0	0	0	0	0	1	0	0	0	0	1	1	0	0
3.4369844	-427.3560	28.5016992	-7.2984101	0	1	0	0	0	0	0	1	0	0	0	0	1	0	1	0	1
7.5876020	-925.3916	-32.8132443	-4.6252082	0	1	0	1	0	0	0	0	0	0	0	0	0	1	1	1	0
3.2151016	-388.7837	77.5510384	5.3901004	1	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	1
5.1077056	-441.3569	66.8383549	-0.9229598	0	0	1	1	0	0	0	0	0	0	0	1	0	0	1	0	0
6.9124137	-595.8584	-5.2713877	-0.6407174	0	1	0	0	0	1	0	0	0	0	0	0	1	1	1	0	0
5.2391170	-716.8464	6.7070514	-4.3237221	0	1	0	1	0	0	0	0	1	0	0	0	0	1	0	1	0
3.2937664	-300.6330	68.0263665	-3.8033144	0	0	1	0	0	0	0	0	1	0	0	0	0	1	0	0	0
6.3295446	-777.6458	-2.4133635	-6.5526246	0	0	1	0	1	0	0	0	0	0	1	0	0	1	1	0	0
7.0321483	-979.7115	-55.0868173	9.6135555	0	1	0	1	0	0	0	0	0	0	0	0	0	1	0	0	1
6.7660464	-980.5191	-86.3850195	-1.3049061	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0
4.2898324	-156.7333	48.9861108	18.1562561	0	1	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0
5.0884276	-861.0019	-34.0717831	-10.4532918	1	0	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0
2.6019736	-234.1177	72.0841064	9.5959909	1	0	0	0	1	0	0	0	0	1	0	0	0	0	1	0	0
3.6150298	-350.2816	12.9559401	23.2094936	0	0	1	0	0	1	0	0	0	0	0	0	0	0	1	0	1
2.3895981	-114.2045	61.3685387	0.1236504	0	0	1	0	1	0	0	0	0	0	1	0	0	1	0	1	0
3.3739165	-360.1593	47.2003368	1.3924499	1	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1
3.8229596	-550.2909	34.3789374	-3.9529129	0	1	0	0	1	0	0	0	0	1	0	0	0	1	0	0	1
4.6353874	-800.6465	3.3164498	-16.1429424	1	0	0	1	0	0	0	0	0	0	0	1	0	1	0	1	0
5.5550050	-706.9739	-32.7797163	17.1251468	0	0	1	0	0	0	0	1	0	0	0	0	1	1	0	0	0
4.3956659	-628.0293	28.1856371	-3.9268620	0	0	0	0	0	0	1	0	0	0	1	0	0	1	0	0	0
2.0399734	-476.5962	8.4338431	8.7070177	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0
5.6117565	-584.4886	51.4509838	-4.9500731	0	0	1	1	0	0	0	0	1	0	0	0	0	1	1	0	0
1.6296805	-131.3550	121.5022266	4.3970690	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0
5.0397658	-810.7915	-31.1166461	5.2107249	0	1	0	0	0	0	0	1	0	0	1	0	0	0	0	0	1
2.1941863	-136.6152	99.1692646	5.3878963	1	0	0	1	0	0	0	0	0	0	0	0	0	0	1	1	0
4.6977411	-234.7872	70.7198386	3.4657336	1	0	0	0	0	1	0	0	1	0	0	0	0	1	1	0	0
3.2895710	-368.0201	47.5492982	9.2052637	1	0	0	1	0	0	0	0	0	0	0	1	0	1	0	0	1
2.9493752	-317.2560	22.6841982	9.6999950	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	1
4.6312524	-696.8852	25.3549135	-9.5246966	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0
1.4183356	-227.7565	34.0060884	10.4211598	0	1	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0
3.5219190	-277.3219	107.3477768	-11.5627390	0	0	1	1	0	0	0	0	1	0	0	0	0	1	0	0	1
4.0898626	-632.5823	8.3838287	3.8166643	0	0	1	0	0	0	0	1	0	0	1	0	0	0	0	0	1
3.7158878	-305.6959	47.1391127	14.1556654	0	1	0	0	0	0	1	0	0	0	1	0	0	1	0	1	0
8.2581482	-897.1458	-23.1726347	-9.8089069	0	0	1	0	1	0	0	0	0	1	0	0	0	1	1	0	1
4.9337920	-493.7987	51.6084652	-9.2121650	1	0	0	0	0	1	0	0	1	0	0	0	0	1	1	0	0
3.9299444	-378.2260	39.7715489	14.4817019	0	1	0	0	0	1	0	0	1	0	0	0	0	1	0	0	0
2.9852806	-439.0428	-0.9318301	4.3686692	0	0	0	0	0	0	0	1	1	0	0	0	0	1	0	1	0
2.5430355	-231.9606	80.8735162	-4.6383739	1	0	0	0	0	1	0	0	0	1	0	0	0	1	0	0	1
3.6435313	-351.5781	50.1559369	4.0925019	0	0	1	0	0	0	1	0	0	0	0	0	1	0	1	0	1
2.9559296	-270.1444	59.5413807	-3.3924241	1	0	0	0	0	0	0	0	0	0	0	1	0	0	1	1	0
3.9032470	-668.6173	25.9411041	6.6135478	1	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	1
5.4176378	-678.1142	4.9390285	-12.8349937	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	1	0
5.5482786	-818.5936	-46.6186710	-3.8532900	0	1	0	0	0	0	0	0	0	0	1	0	0	0	1	1	0
1.6738436	-280.8219	36.4845539	-1.7186371	0	0	0	0	1	0	0	0	1	0	0	0	0	0	1	1	0
1.6182119	-242.1997	72.1099075	0.8947463	0	0	1	0	0	1	0	0	0	1	0	0	0	0	0	1	0
1.2614748	-115.3473	76.3038217	3.3053983	1	0	0	0	1	0	0	0	0	0	0	0	1	0	1	0	0
3.2087447	-158.4206	62.3863909	9.2413529	0	1	0	0	0	1	0	0	0	0	0	0	1	0	1	1	0
3.1405441	-391.5815	75.6932816	3.5456251	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0
0.9664496	-147.0548	52.9492401	9.8042598	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0
5.1464715	-458.1106	2.6533703	11.4869722	0	1	0	0	0	1	0	0	0	0	0	0	0	1	1	0	1
4.5377454	-627.7571	-3.6572808	6.8441362	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1	0	1
7.5136097	-934.8051	-57.6147641	7.7079940	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0	0	1
5.1176560	-763.5375	-24.9571138	-1.5004289	0	1	0	0	0	0	0	1	0	0	1	0	0	0	1	1	0
6.6916248	-535.1936	14.0198556	0.9068005	1	0	0	1	0	0	0	0	0	0	0	0	1	1	1	0	0
4.2969780	-174.7458	58.0769102	0.9250670	0	0	0	0	0	1	0	0	0	0	1	0	0	1	1	0	1
4.1840231	-179.7969	82.1480395	-3.7229383	0	1	0	0	0	0	0	1	0	1	0	0	0	1	1	0	1
6.8770636	-966.8941	-52.1260326	4.0083734	0	1	0	0	0	0	0	0	0	0	0	1	0	1	0	0	1
4.2691873	-826.3838	4.8329393	1.1863931	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1
5.7060346	-684.5987	22.4554320	-2.9908637	0	1	0	0	0	1	0	0	0	0	0	0	0	1	0	0	1
4.9793228	-751.8884	16.0218940	-2.1858181	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	1
2.5484145	-248.0181	49.9229946	13.1052700	0	1	0	0	0	0	0	0	0	1	0	0	0	0	1	0	1
4.1400309	-435.4839	50.8826906	-12.7568152	1	0	0	0	0	1	0	0	0	1	0	0	0	1	0	0	1
2.6458257	-138.6524	77.9622067	9.3617128	0	0	1	0	1	0	0	0	0	0	0	1	0	1	0	0	1
3.4977246	-278.0361	74.7820451	11.5620927	1	0	0	0	0	0	1	0	0	0	0	1	0	0	1	0	1
2.7701517	-169.7306	56.7674551	10.7898028	1	0	0	0	0	0	1	0	0	0	0	0	1	1	0	1	0
4.8889973	-576.0044	54.5931010	3.7715708	1	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0
3.2180131	-579.1083	19.0083360	-11.1479489	0	0	1	1	0	0	0	0	0	1	0	0	0	0	0	0	0
6.6539112	-711.4862	-30.5531745	1.2664185	0	0	1	0	0	0	1	0	0	0	0	0	0	1	1	1	0
3.4634941	-337.6049	59.5963779	14.0664802	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	1	0
3.9782171	-388.4453	90.5789087	3.1585494	0	1	0	0	0	0	1	0	0	0	1	0	0	1	1	0	1
2.8132439	-213.7064	52.7643062	5.3170294	0	1	0	0	1	0	0	0	0	0	0	0	1	1	0	1	0
6.1551766	-884.0958	-6.6800075	-15.1064748	0	1	0	0	0	0	1	0	0	0	0	0	0	1	0	1	0
6.7106234	-824.3774	-68.8486854	3.0834218	0	1	0	0	0	0	1	0	0	0	0	0	1	1	1	0	0
5.3663359	-738.1986	31.9053703	-0.8766878	0	1	0	0	0	0	1	0	0	0	0	0	1	1	0	1	0
1.3420953	-191.4532	49.7676826	13.7022158	1	0	0	0	0	0	0	1	0	0	1	0	0	0	0	1	0
4.6790143	-788.2147	-40.2223566	-1.3269296	0	1	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1
4.3086977	-409.3837	47.5866212	6.2882627	0	1	0	0	0	1	0	0	0	0	0	0	0	1	0	1	0
4.6230681	-579.3662	12.4812060	12.6384546	0	1	0	0	0	0	1	0	0	1	0	0	0	0	1	0	1
6.6224572	-715.5022	2.2880817	3.3099481	0	1	0	0	0	0	1	0	1	0	0	0	0	1	1	0	0
5.8996258	-787.9827	11.7471359	-10.0734647	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0
6.7479130	-855.3478	9.9864693	-1.5400992	0	0	0	1	0	0	0	0	0	1	0	0	0	0	1	0	0
6.1813935	-479.3274	32.4288931	11.9582503	0	0	0	0	1	0	0	0	0	0	0	0	0	1	1	0	1
6.4578054	-913.6984	-34.4265223	8.6401783	1	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	1
4.0306080	-531.9936	59.1939209	-18.0906303	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0
4.9425591	-578.1842	22.8806877	-3.0624718	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0
3.0416958	-552.1501	-6.2626991	5.8763476	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0
5.4699091	-524.2800	2.8808003	-1.4386690	0	0	0	0	0	0	1	0	0	1	0	0	0	1	0	0	0
6.2920332	-798.0368	10.0315073	-5.5834157	0	1	0	1	0	0	0	0	0	0	0	0	1	0	1	0	0
2.5034166	-557.1266	36.2534391	-14.6845974	0	1	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0
4.3857970	-307.2552	80.7805365	-12.0313268	0	0	0	0	1	0	0	0	0	0	1	0	0	1	1	1	0
4.7672297	-543.1666	0.3923298	1.1139308	0	0	1	0	1	0	0	0	0	0	0	0	1	0	1	0	0
4.5032743	-969.8746	-69.9640658	-5.0817069	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	1
5.2553721	-708.1022	33.5687542	3.9806104	0	1	0	1	0	0	0	0	0	0	0	0	1	0	1	0	0
2.9156537	-167.9979	60.1182409	15.7040427	0	0	1	1	0	0	0	0	0	0	0	0	1	1	0	0	0
5.9935652	-644.8321	-21.5347645	3.4829819	0	1	0	0	0	0	0	0	0	0	0	1	0	0	1	1	0
3.7923320	-304.8505	93.8544909	9.5397583	0	0	0	0	0	1	0	0	0	0	1	0	0	0	1	0	1
4.0891349	-950.7247	-46.9988476	-3.7154207	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0
4.9736708	-341.0145	48.3062582	12.0467419	0	0	0	0	1	0	0	0	0	1	0	0	0	1	1	0	1
4.9855087	-712.3770	-42.1656981	-4.2833251	0	0	0	0	0	0	0	1	0	0	0	1	0	0	1	1	0
6.0356640	-854.0724	-67.6166385	6.9924073	0	0	1	1	0	0	0	0	0	1	0	0	0	0	1	0	0
2.2109925	-412.7850	14.1478184	17.1722814	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	1	0
5.3570828	-615.5883	-22.6236519	10.6964507	0	0	1	0	0	0	0	0	0	0	0	1	0	0	1	0	1
4.1589142	-272.6428	81.3295607	9.0668779	0	0	0	0	0	0	0	1	1	0	0	0	0	1	1	0	1
5.8870088	-900.3288	-22.7424106	-15.3105868	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0
3.5418438	-507.8049	42.0990326	10.7245147	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0
2.1077768	-256.2516	38.8126922	10.6757523	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0
2.8609328	-386.6987	74.1362518	-2.8043026	0	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0	1
5.1940088	-943.5160	-4.6246588	-4.2207611	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	1
5.5243701	-901.8868	-33.2955989	10.0070548	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1
6.3635891	-888.4641	-53.3851656	7.4089536	1	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	1
5.0360617	-781.1320	18.5247554	-12.5800299	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	1	0
6.5874181	-757.8222	-13.7083507	-6.5118383	0	0	1	0	0	0	0	1	0	0	0	0	1	1	1	0	1
5.4557413	-915.7707	-76.2653724	12.7987285	0	1	0	0	0	0	1	0	0	0	0	0	1	0	1	0	0
2.7039015	-159.4381	92.5895205	6.1665467	0	1	0	0	0	1	0	0	0	1	0	0	0	0	1	0	1
4.6874292	-937.8941	-28.6499230	-9.8667541	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0
4.8243047	-615.5337	40.8075435	-12.5525383	0	0	1	0	1	0	0	0	0	0	0	0	0	1	0	0	1
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6.2889943	-845.2526	-65.1276704	2.1952102	0	0	1	0	0	0	1	0	0	0	1	0	0	1	0	0	1
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6.2349299	-766.7899	-40.6984298	-0.1575691	1	0	0	0	0	0	0	1	0	0	1	0	0	1	0	0	1
2.9931984	-277.4584	82.4034364	-2.1015688	1	0	0	0	0	0	1	0	1	0	0	0	0	0	1	0	0
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4.6398152	-613.5038	39.4987217	-10.4375358	1	0	0	0	0	0	0	1	1	0	0	0	0	1	0	0	0
4.8864087	-603.5883	32.6106923	-11.4307139	0	0	1	0	0	0	0	0	1	0	0	0	0	1	0	1	0
4.1319050	-474.9555	1.1555833	2.1710673	0	1	0	0	0	1	0	0	0	0	0	0	0	0	1	1	0
2.7321362	-592.8220	24.0678681	-11.0788059	1	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	1
7.5452177	-889.2733	-70.0211510	7.5276153	0	0	1	0	0	0	0	0	1	0	0	0	0	1	1	0	0
4.3509240	-212.6832	96.4626469	0.9653568	0	0	0	0	0	0	0	1	0	0	1	0	0	1	0	1	0
6.1352511	-449.7176	57.8131167	6.9110770	0	0	0	0	0	0	0	0	0	0	1	0	0	1	1	0	0
5.2851061	-562.0771	17.7273076	4.6238521	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1	1	0
5.9404784	-793.5967	3.1060326	-2.5022249	0	1	0	0	0	1	0	0	0	0	0	0	0	1	0	1	0
5.3105349	-857.5498	5.4803562	-16.7585985	1	0	0	0	0	0	0	1	1	0	0	0	0	1	0	0	0
4.9505311	-181.4537	90.5783059	13.4784691	0	1	0	0	0	0	1	0	1	0	0	0	0	1	1	0	0
3.0292050	-253.7671	96.5863616	-6.7848223	0	0	1	0	1	0	0	0	0	1	0	0	0	0	1	1	0
5.3686320	-1006.1995	-31.9529515	-18.1951006	0	0	1	0	0	0	1	0	0	0	0	1	0	0	0	0	1
2.4077060	-150.5143	47.5021869	11.1238990	0	0	0	0	0	1	0	0	0	0	1	0	0	0	1	1	0
2.8335168	-257.5293	46.0854301	-3.2450444	0	0	1	0	0	0	0	1	0	0	1	0	0	1	0	1	0
4.2357794	-732.4562	-22.6227031	-4.2113447	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1
8.0485617	-932.6538	-55.7381832	-10.0006233	0	0	0	0	0	0	1	0	0	0	0	0	0	1	1	0	1
2.4537281	-153.0463	128.5525884	0.2264128	1	0	0	1	0	0	0	0	0	0	0	1	0	0	1	1	0
4.6042194	-776.9467	-23.0390350	-6.9088428	0	1	0	0	0	0	0	1	0	0	0	1	0	0	0	0	1
4.1590302	-673.1457	18.7315184	-4.8650418	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1
5.2760840	-377.5502	87.5568253	5.1395729	0	0	0	0	0	1	0	0	0	1	0	0	0	1	1	0	0
3.6339503	-465.4743	42.1148049	3.0747239	0	1	0	0	0	1	0	0	0	1	0	0	0	0	1	0	0
2.0304268	-315.6172	43.3448623	13.4460130	0	0	1	0	0	0	0	1	0	1	0	0	0	0	0	1	0
6.4667103	-519.0856	33.4433833	12.5568177	0	1	0	0	0	0	0	1	1	0	0	0	0	1	1	1	0
3.4210293	-643.3462	-33.5123632	4.3794465	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1
4.6476202	-704.8050	29.4363822	-3.6175612	1	0	0	0	0	0	0	1	1	0	0	0	0	0	0	1	0
5.6842658	-643.1199	35.3280072	-7.7439569	1	0	0	0	1	0	0	0	0	0	0	0	1	1	1	1	0
4.3980772	-538.1136	60.7961136	-5.5217302	0	0	1	0	0	0	0	1	1	0	0	0	0	0	1	0	0
6.9504826	-874.8797	-7.4246713	-0.7176441	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0
3.3000427	-318.5904	58.1577721	7.3805847	1	0	0	0	0	0	1	0	0	0	1	0	0	0	1	0	1
4.5076231	-373.0716	54.8053756	8.2110827	0	0	1	0	0	1	0	0	1	0	0	0	0	0	1	1	0
2.7642792	-143.8652	61.9365496	5.8056621	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	1
5.0029561	-981.5546	-24.9962520	-18.5526264	1	0	0	0	0	1	0	0	0	0	1	0	0	0	0	1	0
4.1104364	-507.0101	9.0149924	-0.0720116	0	0	1	0	1	0	0	0	0	0	0	0	0	0	1	1	0
7.9289026	-999.1817	-67.1535988	11.2574254	1	0	0	0	1	0	0	0	0	1	0	0	0	1	1	0	0
4.1285018	-691.7457	20.5307929	-11.8537694	1	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	1
6.8936018	-913.3213	-51.5049966	-4.3943909	1	0	0	0	0	0	0	1	0	0	0	0	1	1	0	1	0
3.4896359	-212.6505	85.7913612	9.3599724	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	1
4.5379721	-347.4215	32.8400425	-2.9642065	0	1	0	0	0	0	1	0	0	1	0	0	0	1	1	1	0
2.2675810	-239.6916	63.7434504	-1.5467959	1	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0
6.4503617	-989.8496	-95.8653585	0.0276207	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0
2.4440281	-169.2017	68.5811631	17.6016981	0	0	1	0	1	0	0	0	0	0	1	0	0	1	0	0	1
3.8952272	-403.6341	62.9259396	6.0810901	0	1	0	1	0	0	0	0	0	0	1	0	0	1	0	1	0
6.4436277	-826.0862	-56.3401007	9.9857482	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0
6.2689992	-804.6980	2.0246669	5.8940048	0	0	0	0	0	0	0	1	0	0	0	1	0	0	1	0	0
4.8246947	-596.4298	33.4094320	2.0082016	0	0	1	0	0	1	0	0	1	0	0	0	0	0	1	0	1
4.8377699	-649.4561	38.3769081	-18.1755901	0	1	0	0	0	1	0	0	0	0	0	0	0	0	1	0	1
7.0401845	-852.5365	-72.9329246	-5.0080690	0	0	0	1	0	0	0	0	0	1	0	0	0	1	1	0	0
0.8249499	-236.7582	67.5543263	-5.3968831	0	0	1	1	0	0	0	0	0	0	1	0	0	0	0	0	1
4.0062386	-401.5606	17.9497244	6.8323071	1	0	0	0	0	0	0	1	0	1	0	0	0	1	0	0	1
2.6240449	-169.9185	121.2859349	3.1035965	0	1	0	0	0	1	0	0	1	0	0	0	0	1	0	0	0
2.8974774	-217.0007	44.1927497	1.3500341	1	0	0	0	0	1	0	0	1	0	0	0	0	1	0	0	0
4.1741083	-789.5545	17.3116348	-16.9826358	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1	0
4.4157001	-764.2947	23.1097687	-13.3924317	0	0	1	0	0	0	1	0	1	0	0	0	0	0	0	0	1
5.6683556	-884.9026	-53.4431189	-0.6794199	0	0	1	0	0	0	1	0	0	0	0	0	1	0	0	0	1
4.3569814	-600.1870	29.0705692	-1.1120095	1	0	0	0	0	1	0	0	1	0	0	0	0	0	1	0	1
7.3467078	-912.4202	-18.3102979	-14.5245627	0	0	0	0	0	0	1	0	0	0	1	0	0	1	1	0	0
1.2168438	-113.7766	45.7249705	4.1184793	1	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0
3.9222907	-274.2441	53.5945269	1.0253377	0	1	0	0	0	1	0	0	0	0	0	0	0	1	1	1	0
6.5575058	-885.3461	-60.2145116	1.9129393	0	0	1	0	0	0	0	1	0	1	0	0	0	0	1	0	0
3.4487885	-286.3936	106.2914606	-4.6223180	0	0	1	0	0	0	1	0	0	0	0	1	0	0	1	1	0
4.0812066	-255.5462	110.7352174	3.1316766	1	0	0	0	0	1	0	0	0	0	0	0	0	1	1	0	1
1.2509105	-157.5341	125.9197113	-14.1566041	1	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	1
7.8824668	-790.8658	-23.1670134	8.3259544	0	0	0	0	0	0	0	1	0	1	0	0	0	1	1	0	1
3.9939826	-490.1366	31.3122133	-5.2292395	0	0	1	0	0	1	0	0	0	0	0	0	0	1	0	1	0
5.6145572	-606.5495	19.5291230	-7.4217443	0	0	1	0	0	0	1	0	0	0	0	0	1	1	1	1	0
6.2181158	-916.1291	-26.8585875	-7.9819616	0	1	0	0	0	0	0	0	1	0	0	0	0	1	0	1	0
5.5292264	-612.6347	40.4075331	-11.7196464	0	1	0	0	0	0	0	0	0	1	0	0	0	1	1	0	0
1.4493018	-208.8937	45.0870756	19.5544219	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1
4.1065806	-137.1680	105.8199036	13.0552032	0	1	0	1	0	0	0	0	0	1	0	0	0	1	1	0	1
4.5549576	-759.8418	-44.4124908	16.6294463	1	0	0	0	1	0	0	0	0	0	0	0	1	0	1	0	0
2.7559239	-246.6801	70.0823076	-0.4695314	0	1	0	0	1	0	0	0	0	0	0	0	0	0	1	0	1
6.5377803	-909.2534	-68.2504175	11.5464573	1	0	0	0	0	1	0	0	0	0	0	0	0	0	1	1	0
5.3773675	-580.1876	28.6935656	-8.4251729	0	0	0	0	0	0	1	0	0	0	0	1	0	1	1	0	1
5.6250094	-555.0963	54.1334885	0.3860005	0	0	0	1	0	0	0	0	0	0	0	0	0	1	1	0	0
3.3446724	-172.8747	112.9326928	10.0118273	0	1	0	0	0	0	1	0	0	0	1	0	0	1	1	0	0
4.0508659	-589.3924	33.0138039	9.7187929	0	0	0	0	0	0	0	1	0	0	0	1	0	0	1	1	0
5.1408429	-646.6419	11.6371934	-4.6503176	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0
4.2164507	-477.6320	23.1352912	10.6656122	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	1
3.2781092	-125.9537	45.7197443	13.5604239	0	1	0	1	0	0	0	0	0	0	0	1	0	1	1	0	1
1.2873343	-158.2535	114.3132446	-4.6994698	1	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	0
4.8313742	-913.9659	-3.5723998	-6.9548221	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1
5.3750125	-818.9629	-51.3232993	13.7938188	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	1	0
5.7890893	-582.0634	-3.6308484	6.7053700	0	0	0	0	0	0	1	0	0	0	1	0	0	1	1	1	0
5.1405750	-559.6216	-13.4993144	6.6280474	0	0	0	0	0	0	0	1	1	0	0	0	0	1	0	1	0
3.2171329	-283.2962	34.1837601	14.1730908	0	1	0	0	0	0	0	1	0	0	0	0	1	1	0	1	0
5.6795379	-966.5624	-10.7052517	-15.9456865	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	1	0
3.0827269	-567.1337	17.9136977	-10.6836962	0	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	1
2.9779580	-495.4812	41.8083287	-0.2740938	1	0	0	0	0	1	0	0	0	0	0	0	1	0	0	1	0
5.0521505	-333.9196	48.0387451	15.3002870	0	0	0	0	1	0	0	0	0	0	0	1	0	1	1	0	1
3.6474913	-466.3239	75.7132787	-13.7996454	0	0	1	0	0	0	1	0	0	1	0	0	0	0	1	0	0
4.0968096	-711.2771	-25.5320592	5.4342962	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0
3.4201353	-459.4907	76.1653280	-11.8716858	0	0	0	0	0	0	0	1	0	0	1	0	0	1	0	0	0
4.9726807	-663.5749	37.7151494	4.6860295	1	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0
6.4445661	-692.9242	-41.4000227	4.4727347	0	0	0	0	0	1	0	0	0	0	1	0	0	1	1	0	0
4.7017633	-498.7646	2.7589594	8.3510351	1	0	0	0	0	0	0	1	1	0	0	0	0	0	1	1	0
4.4298187	-356.9641	7.9488483	3.9953460	0	1	0	0	0	0	0	0	0	0	0	0	1	1	1	1	0
6.1111277	-931.1208	-16.7627947	-12.5886689	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1	0	0
7.5245835	-953.5187	-44.7162886	-10.5631880	1	0	0	0	0	1	0	0	0	0	0	1	0	1	1	0	0
6.7109746	-679.7840	17.6150326	4.9269685	0	0	0	0	0	0	0	1	0	1	0	0	0	1	1	0	0
6.8023498	-940.5379	-83.2141799	18.3266668	0	0	0	1	0	0	0	0	1	0	0	0	0	0	1	0	0
6.7397076	-899.8274	2.7760381	2.9277760	0	0	0	0	1	0	0	0	1	0	0	0	0	0	1	0	1
4.2715011	-933.4077	-60.3085868	-6.5108547	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1
9.1233316	-976.7704	-29.4661468	1.2689346	0	1	0	0	0	1	0	0	1	0	0	0	0	1	1	0	0
7.5608041	-826.7351	9.2091076	-7.4279390	0	0	0	0	0	0	1	0	0	1	0	0	0	1	1	1	0
3.2938708	-224.5023	100.7635949	10.9740940	0	0	1	0	0	0	0	0	0	0	0	1	0	0	1	0	0
7.3740122	-905.7231	-78.2336560	-4.6084980	0	1	0	0	1	0	0	0	0	1	0	0	0	1	0	0	1
3.4505749	-430.8254	48.2659660	11.1598767	1	0	0	0	0	1	0	0	1	0	0	0	0	1	0	1	0
6.9083148	-737.9224	16.1658796	-2.2683265	0	0	1	0	0	1	0	0	0	0	0	1	0	1	1	0	0
6.8962304	-988.8203	-21.5405367	-6.1308235	0	1	0	0	0	1	0	0	0	0	0	0	1	1	0	0	1
5.9062557	-830.5662	9.8225867	-1.4585841	1	0	0	0	0	0	1	0	0	0	0	1	0	0	1	0	1
3.6773274	-550.5756	19.6856756	5.2287554	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	1
5.2338139	-769.9489	-38.4878174	13.0752283	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1
6.2395233	-632.2107	45.5431755	3.3521584	1	0	0	0	0	0	0	0	0	1	0	0	0	1	1	1	0
2.6224127	-349.4305	57.1507314	-8.8094698	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0
3.1628088	-303.5304	49.1789654	17.3794635	0	1	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0
1.5528526	-265.8677	66.6171443	-2.4443955	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	1
4.5440307	-568.6397	16.6933153	4.6853441	1	0	0	0	1	0	0	0	0	1	0	0	0	0	1	1	0
7.6639049	-968.9015	-59.4470610	5.1371567	0	0	0	1	0	0	0	0	1	0	0	0	0	1	1	0	1
6.4792319	-445.3797	74.5872530	4.7224081	0	0	0	0	0	0	0	1	0	0	1	0	0	1	1	0	1
4.2104224	-742.2513	-26.1433145	-3.6851423	1	0	0	0	1	0	0	0	1	0	0	0	0	0	0	1	0
6.8111336	-730.9841	11.1523757	3.1545696	0	0	1	0	0	1	0	0	0	1	0	0	0	1	1	1	0
5.0533069	-724.0433	34.3920364	-19.9071585	0	0	0	0	1	0	0	0	0	1	0	0	0	1	0	0	1
2.8876022	-245.0424	74.0835926	2.6528447	0	0	0	0	0	0	1	0	0	0	0	1	0	1	0	1	0
6.2910916	-848.8813	-71.8306508	2.5605837	1	0	0	0	0	0	0	1	0	0	0	0	1	0	1	1	0
4.0650094	-230.0516	94.8688200	6.6989881	0	0	1	0	0	1	0	0	0	0	0	1	0	1	0	0	1
6.9618735	-692.1372	-2.4189011	2.4927073	0	0	1	0	1	0	0	0	0	0	0	1	0	1	1	1	0
5.3074002	-355.9091	48.9204089	6.4734520	0	1	0	0	0	0	0	0	0	0	1	0	0	1	1	0	1
5.7760664	-967.8327	-80.7469811	6.2433993	0	0	1	0	1	0	0	0	0	0	1	0	0	0	0	0	1
6.1061140	-825.9988	-63.3805522	0.7798953	0	0	1	0	0	0	0	1	0	1	0	0	0	1	0	1	0
2.4843589	-226.5453	48.3717468	8.9958697	0	0	0	0	1	0	0	0	0	0	0	1	0	0	1	0	0
3.3231166	-274.3225	68.5144675	13.3785788	0	0	1	0	0	0	0	0	1	0	0	0	0	1	0	0	1
6.5096097	-665.7675	-18.6966368	8.4113261	0	1	0	0	1	0	0	0	0	0	0	0	0	1	1	1	0
1.4087969	-267.0545	26.1693308	7.8070777	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0
5.0943652	-690.4378	42.6116524	-5.9638640	0	0	1	1	0	0	0	0	0	0	0	1	0	1	0	0	0
6.7518302	-817.5837	6.4521468	-2.7986855	1	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0
2.1522955	-407.9782	68.3284314	5.5744300	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	0
5.6388857	-908.5745	-22.0949228	-0.7063514	0	1	0	0	0	1	0	0	0	1	0	0	0	0	0	0	1
4.1718742	-877.7311	-29.7594180	-11.6820603	0	0	1	1	0	0	0	0	0	0	1	0	0	0	0	1	0
6.9164467	-1001.6360	-31.8475494	-16.1924318	0	0	1	0	1	0	0	0	0	1	0	0	0	1	0	0	0
4.3029938	-603.2179	50.5719704	-4.7474256	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	1	0
7.6244563	-834.5227	-66.6436997	11.6467225	0	0	1	0	0	0	0	1	0	0	1	0	0	1	1	0	1
5.3720144	-955.1839	-43.2158422	-6.9907129	0	0	1	1	0	0	0	0	0	0	0	1	0	0	0	0	0
6.5279047	-958.9594	-23.6069514	-4.1625802	0	0	1	0	1	0	0	0	0	0	0	1	0	0	1	0	1
6.0131362	-858.1934	-30.5187336	-10.4263370	0	0	1	0	0	0	1	0	0	0	0	1	0	0	1	0	0
4.1972393	-410.1493	74.5635869	7.4375326	1	0	0	0	0	0	0	1	0	0	0	0	0	0	1	1	0
2.8428552	-463.8303	13.7159916	14.4585853	0	1	0	0	0	0	0	1	0	1	0	0	0	0	0	1	0
2.3773890	-126.7455	55.7252474	2.5104107	1	0	0	0	0	0	0	1	0	0	0	0	1	1	0	1	0
2.8869462	-308.3099	21.5986593	2.4894599	0	1	0	1	0	0	0	0	0	1	0	0	0	0	1	0	1
3.7013614	-216.7209	64.5889512	-5.2103862	0	1	0	0	0	1	0	0	1	0	0	0	0	1	1	0	1
4.8737153	-311.8323	98.2873031	-3.7171398	0	0	1	0	0	0	0	1	0	1	0	0	0	1	1	1	0
3.9167966	-641.0499	-5.8671072	-8.7045839	0	1	0	0	0	0	1	0	0	0	0	0	1	0	0	0	1
4.4375689	-731.9051	-38.8559255	-3.1868210	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1
2.2156338	-313.1730	37.5340732	13.4393649	1	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0
5.7851678	-573.6877	-25.7643102	13.1778603	1	0	0	0	0	0	0	1	0	0	0	0	1	1	1	1	0
2.2643255	-209.1808	37.8609381	4.6976380	0	0	1	0	0	1	0	0	0	0	1	0	0	0	1	1	0
3.5338729	-679.2596	-43.0645736	15.9554372	1	0	0	0	0	1	0	0	0	1	0	0	0	0	0	1	0
5.4116059	-559.2979	23.9831756	2.7391953	0	0	1	0	0	1	0	0	0	0	0	0	1	1	1	0	1
3.7826466	-523.5704	-7.0785821	19.9739482	0	1	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0
3.3145035	-475.3744	4.9534718	10.9377326	0	0	1	0	0	0	1	0	0	0	1	0	0	0	0	1	0
5.3107613	-496.9802	37.1655160	8.4788893	0	1	0	0	0	0	1	0	0	0	0	0	1	1	1	0	0
4.1999480	-318.7578	22.8643210	16.7825969	0	0	0	0	0	0	0	0	0	0	1	0	0	1	1	0	1
5.3756906	-788.1624	-61.3100368	1.6042598	1	0	0	1	0	0	0	0	0	0	0	1	0	1	0	0	0
7.1558467	-746.0993	-39.4972893	9.7590988	0	1	0	0	0	1	0	0	1	0	0	0	0	1	1	0	0
7.9062724	-885.8928	-65.2183650	-1.9082965	0	0	0	0	1	0	0	0	0	0	0	0	0	1	1	0	0
4.8230751	-358.3803	40.1727046	16.1184201	1	0	0	1	0	0	0	0	0	0	0	1	0	1	1	0	0
5.6248377	-700.5317	1.7878640	-5.7309534	0	1	0	0	0	0	0	0	1	0	0	0	0	1	0	0	1
1.8418645	-266.8658	104.8329140	3.3061571	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0
2.2685063	-514.3849	-19.7481700	1.4368590	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1
3.1927322	-387.6457	50.5007228	8.6306037	0	0	1	0	0	0	0	1	0	0	0	0	0	0	1	0	1
5.1761626	-958.8797	-2.9297877	-14.2346422	0	1	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1
5.6680145	-806.0283	-32.6930233	-1.1405583	0	1	0	0	0	0	0	1	0	0	0	1	0	0	0	1	0
3.3069584	-517.6828	-7.2239381	14.6878349	0	1	0	0	0	0	1	0	0	0	0	1	0	0	0	0	1
4.4897535	-248.2653	91.5904546	9.9145537	0	0	1	0	0	0	0	1	0	0	0	0	0	1	1	1	0
5.3092010	-712.2988	-14.2757903	10.7342541	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0
6.7913748	-905.1432	-79.2513528	15.1638174	0	0	1	0	0	0	1	0	0	0	1	0	0	1	0	0	0
6.1031949	-890.2575	-75.4186282	2.1275456	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0	1	0
3.6415110	-646.5470	41.2242338	-1.5197329	0	0	1	0	0	0	1	0	0	0	1	0	0	0	0	0	1
0.8099949	-179.6676	62.5243898	16.3593697	1	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0
4.2180567	-465.0987	51.7516193	4.4303158	0	1	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0
2.8916601	-246.4848	29.3079113	22.2258533	0	0	0	0	0	0	0	1	0	0	0	0	1	0	1	0	0
4.6527375	-457.2466	-7.0307690	13.9737635	0	0	1	0	0	0	0	1	1	0	0	0	0	0	1	1	0
6.7137534	-544.1364	-18.6131232	20.0276073	0	0	1	0	0	0	0	1	0	0	0	0	0	1	1	1	0
2.1374051	-277.4174	23.8897797	19.8618500	0	1	0	0	0	0	1	0	1	0	0	0	0	0	0	0	1
1.2730756	-403.7689	40.8605712	-0.6453636	0	0	1	0	1	0	0	0	1	0	0	0	0	0	0	0	1
6.1944621	-857.5680	-18.5235125	2.2323270	0	0	1	0	0	0	0	1	0	0	0	0	0	1	0	1	0
5.2928413	-688.2897	-27.6849054	12.3251468	0	0	1	0	0	1	0	0	0	0	1	0	0	1	0	0	1
5.6800804	-806.0066	-11.4315459	-3.2820471	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	1	0
1.1549197	-176.6004	42.5388356	7.2088647	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1
6.1890379	-890.5937	-39.6325190	10.6294438	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	1
6.0184125	-696.6053	-29.0410582	17.2160084	1	0	0	0	0	0	1	0	0	0	0	1	0	1	1	0	1
5.7177622	-536.1300	34.8745035	-12.5468508	0	1	0	0	0	1	0	0	0	0	0	0	0	1	1	1	0
2.0740643	-472.7035	20.3580080	-6.7054524	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	0
3.5155632	-755.8855	-37.1713174	13.5960957	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0
2.3502697	-256.5102	44.7446323	14.6106777	0	1	0	0	0	0	1	0	0	0	1	0	0	1	0	0	1
3.8272796	-488.5270	52.8172285	7.6925891	0	0	1	1	0	0	0	0	0	0	0	1	0	0	1	1	0
5.3454508	-675.9454	13.9053618	-6.0683446	0	1	0	0	0	0	0	1	0	0	0	0	1	1	0	0	1
8.0239992	-886.5854	-70.5591052	7.8521828	0	1	0	0	0	1	0	0	0	0	0	0	1	1	1	0	0
3.2348227	-432.7085	83.9375832	0.1587284	1	0	0	1	0	0	0	0	0	0	1	0	0	1	0	0	1
5.1438171	-570.6772	43.5326400	6.1525353	0	0	1	0	1	0	0	0	0	0	1	0	0	1	0	0	0
4.7100035	-913.4156	-77.2208582	1.2727872	0	1	0	0	0	1	0	0	0	1	0	0	0	0	0	0	1
5.5993647	-771.3969	16.3213090	-5.7062986	1	0	0	0	0	1	0	0	0	1	0	0	0	1	0	1	0
4.3222459	-951.3953	-60.8620306	-5.2977409	1	0	0	0	0	0	1	0	0	0	0	1	0	0	0	1	0
4.9486752	-738.1396	-27.4247248	-8.0919110	0	1	0	0	1	0	0	0	0	1	0	0	0	0	1	1	0
3.4441080	-143.5587	125.6143787	-11.4000086	0	0	0	0	1	0	0	0	0	0	0	0	1	1	1	1	0
6.5046543	-1000.1386	-60.1861320	0.6358662	1	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1
4.7280527	-154.4845	85.3568150	-2.7230128	0	1	0	1	0	0	0	0	0	0	0	1	0	1	1	0	1
3.2227497	-611.2397	19.7716959	-2.5926701	0	0	1	0	1	0	0	0	0	0	1	0	0	0	0	0	0
3.7447803	-406.5591	41.8076603	-3.9327550	0	0	0	0	1	0	0	0	0	1	0	0	0	1	0	0	0
4.3080530	-692.0342	9.8214273	-13.4689159	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0	1
5.9857009	-611.4411	12.5858896	-7.2456742	0	0	0	0	0	1	0	0	1	0	0	0	0	1	1	0	1
4.5963257	-465.1314	78.2530004	2.6913156	1	0	0	0	0	0	0	1	0	1	0	0	0	0	1	0	0
6.4867319	-972.8334	-47.4305048	1.2955143	0	0	0	0	0	0	1	0	0	0	1	0	0	1	1	1	0
6.8055681	-693.6506	10.8049440	-7.4175650	0	0	0	0	0	0	0	1	0	1	0	0	0	1	1	0	0
6.8273651	-874.9046	7.9864654	-6.1589075	0	0	1	0	0	1	0	0	0	0	1	0	0	0	1	1	0
4.8518789	-279.2081	60.9800965	15.7050225	0	0	0	0	0	0	0	1	1	0	0	0	0	1	1	0	1
6.2723411	-915.7085	-18.7578943	-14.1499877	1	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0	0
6.1586916	-779.7780	-15.3680947	7.5039274	0	1	0	0	0	0	1	0	0	0	1	0	0	1	1	1	0
3.9560486	-767.7594	-37.1419124	-2.2132829	0	1	0	1	0	0	0	0	0	0	0	1	0	0	0	1	0
5.0436284	-582.3439	16.9641067	-8.5242143	0	1	0	0	0	0	0	0	1	0	0	0	0	1	0	0	1
4.0714547	-665.9600	-32.9254207	9.7118344	0	1	0	0	0	1	0	0	0	0	0	1	0	0	1	0	1
4.1835612	-386.0604	14.3366567	12.4257391	1	0	0	0	0	1	0	0	0	0	0	0	1	1	0	1	0
3.1702310	-205.4174	39.0496094	17.6402379	1	0	0	1	0	0	0	0	0	1	0	0	0	1	0	1	0
1.2373333	-139.8812	127.7444440	6.1986973	1	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	1
3.6491467	-195.3869	62.6776352	-0.8934208	1	0	0	1	0	0	0	0	0	1	0	0	0	0	1	0	0
3.7922904	-321.8485	51.0323190	10.4352393	0	0	1	0	0	0	0	1	0	1	0	0	0	1	1	1	0
1.8912787	-221.4868	33.7210317	14.2307729	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0
6.2014124	-896.0731	-23.1160660	-15.4040121	0	1	0	0	0	1	0	0	0	0	0	0	0	0	1	0	1
3.4088361	-290.1843	95.2819769	-15.0514729	1	0	0	0	0	0	0	1	0	0	1	0	0	1	0	1	0
2.6758811	-331.2017	40.7822122	13.0697159	0	0	1	1	0	0	0	0	0	1	0	0	0	0	1	0	0
4.1023423	-284.7359	57.1586186	16.4837007	0	1	0	0	1	0	0	0	0	0	1	0	0	1	1	1	0
3.9683522	-707.7085	29.2833014	2.9304304	1	0	0	0	1	0	0	0	1	0	0	0	0	0	0	1	0
5.0910800	-723.3762	22.6790288	-7.0104421	1	0	0	0	0	0	1	0	1	0	0	0	0	1	0	1	0
4.1232204	-811.5934	-40.0808414	2.4286813	0	0	1	0	0	1	0	0	0	0	0	0	0	0	0	1	0
4.6379153	-293.9234	37.3675854	17.8091517	0	1	0	0	0	0	0	1	0	0	0	1	0	1	1	1	0
4.5474735	-635.3947	50.8088252	-8.7973742	0	1	0	0	0	1	0	0	0	0	1	0	0	0	1	0	1
6.6169685	-745.6205	-23.1554490	-6.6473330	0	1	0	0	0	1	0	0	0	0	1	0	0	1	1	1	0
7.4384623	-951.5319	-17.3698156	-19.8262763	0	0	1	0	0	1	0	0	1	0	0	0	0	1	0	1	0
1.3633758	-163.3070	75.4682117	11.3349361	1	0	0	0	0	1	0	0	0	0	0	0	0	0	1	1	0
6.3408259	-870.4402	4.4578674	-6.6842860	0	0	1	0	0	0	0	0	1	0	0	0	0	1	0	0	0
4.0087129	-273.0190	66.3347987	-3.2977206	0	1	0	0	0	1	0	0	0	0	0	1	0	1	1	0	1
5.2875374	-663.1808	16.6725331	7.5711920	1	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	1
4.4637795	-607.7693	-16.9344254	-2.9057706	0	0	1	1	0	0	0	0	0	1	0	0	0	1	0	0	1
5.0636948	-640.0777	38.9566172	-12.5671967	0	1	0	0	0	0	1	0	0	0	0	1	0	1	0	0	0
3.1324418	-333.5377	70.7803889	10.0207667	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0
6.2379550	-567.3358	-10.7877100	5.6971565	0	0	0	0	0	1	0	0	0	0	1	0	0	1	1	0	1
3.1890879	-159.0601	43.8313434	25.0570797	0	1	0	0	0	0	1	0	0	0	0	0	1	1	0	1	0
0.9760818	-138.2599	116.0001553	3.0903449	1	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	1
6.3217087	-867.4317	-27.2623333	-7.5162832	0	0	1	0	1	0	0	0	0	0	0	0	0	1	0	0	0
7.2084237	-868.5406	-61.7187076	-3.3752790	0	0	1	0	0	0	0	0	0	0	0	0	1	1	1	0	0
4.6953105	-211.4330	85.7822866	13.4060193	0	0	1	0	0	0	0	1	0	1	0	0	0	0	1	1	0
2.3259871	-227.6954	47.2073289	-0.8233763	0	1	0	0	0	1	0	0	0	1	0	0	0	1	0	0	1
5.0694035	-703.1967	-47.2632397	-1.0131885	0	1	0	0	0	0	1	0	0	0	1	0	0	1	0	0	1
7.0147527	-965.6025	-89.2159242	-6.5553951	0	0	1	0	0	1	0	0	1	0	0	0	0	0	1	0	0
6.5653698	-897.1773	-76.7629038	16.0648818	1	0	0	0	1	0	0	0	0	1	0	0	0	1	0	1	0
4.5706750	-286.4582	26.4261695	14.0713309	0	0	0	0	0	0	0	0	0	1	0	0	0	1	1	0	0
4.8010091	-573.1778	36.6853303	-10.1733966	1	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0	1
5.2528277	-329.2617	57.1375641	0.6299589	0	1	0	1	0	0	0	0	0	1	0	0	0	1	1	0	0
7.9543285	-619.1471	23.8278286	-11.9293435	0	0	1	1	0	0	0	0	0	0	0	0	1	1	1	0	0
3.0419017	-549.3655	5.8634596	-2.6529094	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	1
2.2264150	-191.7550	86.0243206	14.3973915	0	0	1	1	0	0	0	0	0	1	0	0	0	0	1	0	1
4.0203189	-659.8201	39.1488128	3.7189791	1	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	1
5.5368307	-944.2565	-81.0446248	6.6100236	0	0	1	0	1	0	0	0	0	0	0	0	1	0	0	0	0
5.7936321	-804.8752	-25.1124695	4.6969681	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0
3.5610733	-470.6456	58.0325020	-11.0065449	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	1
3.5969594	-495.8836	44.2976840	-13.0100356	0	0	1	0	1	0	0	0	0	0	1	0	0	0	1	0	0
1.5969641	-233.2999	105.5498305	0.8519035	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0
3.3309180	-136.5906	94.4469588	7.5318954	1	0	0	0	0	0	0	1	0	0	0	0	1	1	1	0	1
7.1743369	-921.6128	-29.1167575	-9.6902350	0	0	0	0	0	0	1	0	0	0	0	0	1	1	0	1	0
2.2906542	-318.8234	20.5141102	20.4869491	0	1	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0
1.5141401	-281.2856	39.4470408	8.0471292	0	1	0	0	1	0	0	0	0	0	0	0	0	0	0	0	1
5.8120386	-705.0390	-6.6470809	7.0217964	0	0	0	0	1	0	0	0	0	0	0	1	0	1	0	1	0
6.5742943	-736.2341	-26.2214706	6.3662836	0	0	1	0	0	1	0	0	0	0	1	0	0	1	0	1	0
4.2652848	-757.5362	-19.4055915	-9.3238600	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0
3.7237111	-444.4760	49.9988552	-10.0743399	0	0	0	1	0	0	0	0	0	0	0	0	1	1	0	0	0
4.2061826	-458.1249	-2.4617091	21.8201543	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1
4.5846572	-549.7353	-0.0627048	14.0764129	1	0	0	0	0	0	0	0	0	1	0	0	0	0	1	1	0
4.5988105	-456.2115	9.3754812	-2.5512098	0	0	0	0	0	0	0	1	0	0	1	0	0	1	0	0	0
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8.4388482	-989.7742	-29.9807878	-6.2404615	0	1	0	0	1	0	0	0	0	0	0	0	1	1	1	0	1
5.3364834	-704.8550	-41.7077141	-2.8619595	0	0	1	0	0	0	0	1	1	0	0	0	0	0	1	0	1
5.8049226	-648.7738	-32.4254045	3.8244481	1	0	0	0	0	1	0	0	0	0	1	0	0	1	0	0	1
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6.6816668	-605.4276	-19.9655618	5.6811922	1	0	0	0	0	0	0	1	0	0	0	0	0	1	1	0	1
5.7478624	-463.4264	23.6880422	7.3526922	1	0	0	1	0	0	0	0	0	0	1	0	0	1	1	0	0
1.7416592	-270.4996	93.6944855	7.2371177	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	1
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3.4285469	-166.1943	80.8960485	-0.2545303	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	1	0
4.7152563	-191.2776	103.9726584	5.8237454	0	1	0	0	1	0	0	0	0	1	0	0	0	1	1	0	1
6.9473518	-751.5574	-44.6527570	-6.0934541	0	1	0	0	0	1	0	0	0	1	0	0	0	1	1	1	0
6.5548521	-509.6564	22.2085101	-4.2123612	0	0	0	0	0	1	0	0	0	0	0	0	1	1	1	1	0
2.4153736	-428.1899	38.1870776	-4.7656947	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	1	0
3.1174301	-152.4243	108.2805961	-8.4194642	0	0	1	0	0	0	0	1	0	0	0	0	0	1	1	0	1
3.1980576	-248.6829	58.9312322	-2.9051961	0	0	0	0	1	0	0	0	0	0	0	0	1	1	0	0	0
0.8833023	-147.9545	71.2196470	-1.1655287	0	1	0	0	0	0	0	1	0	0	1	0	0	0	0	0	1
2.9311016	-197.5498	36.6503259	19.9743720	1	0	0	0	0	0	0	1	0	0	0	0	1	1	0	0	1
3.5951455	-492.0189	58.7278709	-16.1838271	0	1	0	0	0	1	0	0	0	0	0	1	0	0	1	0	1
2.8753512	-451.9723	17.8528637	10.2958688	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	0
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0.3557158	-135.0680	110.6450520	9.7607289	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0
3.6005726	-464.9368	16.3861397	-6.9223808	0	1	0	0	0	0	1	0	0	0	0	0	1	1	0	0	0
4.0911098	-324.5647	96.4326481	-2.8594903	0	0	0	1	0	0	0	0	1	0	0	0	0	1	0	1	0
2.5881624	-327.5252	56.1665063	4.6197423	0	1	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1
4.7880953	-595.4916	43.7019388	-8.9877190	0	0	0	0	0	1	0	0	0	1	0	0	0	0	1	1	0
2.8772645	-207.6697	94.7110233	-1.3979240	0	0	1	0	0	0	0	1	0	0	1	0	0	1	0	0	0
7.6979781	-862.3932	13.4037458	-9.6245301	0	0	1	1	0	0	0	0	1	0	0	0	0	1	1	0	0
2.5383205	-331.2815	17.1750160	18.9316161	0	1	0	0	0	0	1	0	0	1	0	0	0	0	0	1	0
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7.1766384	-968.5210	-42.9051810	4.8930149	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	1	0
7.0406882	-684.9278	-44.2437422	4.5401567	0	0	1	0	1	0	0	0	0	0	1	0	0	1	1	0	1
2.7609374	-249.6389	62.3733335	9.5814554	0	1	0	0	0	0	0	0	0	0	0	1	0	0	1	0	0
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3.6223242	-469.9128	36.1519003	-7.4329925	0	0	1	0	0	0	0	0	0	0	0	1	0	0	1	1	0
1.0964048	-194.2845	99.9534691	-11.4320786	0	0	1	1	0	0	0	0	0	0	1	0	0	0	0	1	0
2.9415311	-307.6393	79.7726907	8.5385110	0	0	1	0	0	1	0	0	0	0	0	0	1	0	1	0	0
7.2587950	-990.8307	-61.7235494	6.0518055	0	1	0	0	0	0	0	0	0	0	0	0	1	0	1	0	1
5.6136095	-621.6611	23.3329386	-7.3504790	0	1	0	0	0	0	1	0	0	0	0	1	0	1	0	1	0
2.5299496	-222.0653	47.3284971	5.4637686	0	0	1	0	0	0	0	1	0	0	0	0	1	0	1	1	0
1.2371294	-134.9295	50.4805309	23.6003145	0	0	1	0	0	0	1	0	0	0	0	0	0	0	0	1	0
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5.3838914	-751.5363	-8.2558201	5.1084274	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	1	0
6.5301969	-727.1082	-17.4188668	11.9625924	1	0	0	1	0	0	0	0	0	0	1	0	0	0	1	0	0
6.3453862	-533.5784	29.3464582	-1.1848526	0	0	1	0	0	0	1	0	0	1	0	0	0	1	1	1	0
7.0799897	-589.6844	9.5541094	11.4278661	0	1	0	0	1	0	0	0	0	0	0	0	0	1	1	0	1
1.7410031	-123.2335	73.0172733	18.5992082	0	0	0	0	0	1	0	0	0	0	0	0	0	0	1	1	0
6.0038555	-970.1026	-58.5242537	-4.5409962	0	0	1	0	1	0	0	0	0	0	0	1	0	0	1	0	0
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6.7358269	-717.8082	25.5877809	-2.1961399	0	0	1	0	0	0	1	0	0	0	0	1	0	1	1	0	0
4.1455027	-741.2126	-9.8687271	9.3666028	1	0	0	0	0	1	0	0	0	0	1	0	0	0	0	1	0
0.9619155	-247.2072	89.4713929	-11.3123039	1	0	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0
4.7642057	-985.7405	-25.9687418	-20.0391163	1	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	1
3.8695022	-532.3697	35.2369676	6.4441875	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0
2.9563569	-391.5949	49.1672067	10.2370132	0	1	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1
6.9904443	-739.2759	17.5675456	0.5802402	0	1	0	0	0	0	0	0	0	0	0	0	1	1	1	1	0
5.2606702	-576.4983	52.7037745	-15.1287811	1	0	0	0	1	0	0	0	0	1	0	0	0	1	1	0	0
4.6479974	-686.2411	-8.8083916	12.0917585	1	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0
5.2331346	-960.3070	-84.8591853	15.6035654	1	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0
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5.8664600	-680.4057	-44.8460711	3.1248458	1	0	0	0	1	0	0	0	0	1	0	0	0	0	1	1	0
3.4213213	-444.2505	33.3315624	-0.8390030	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	1
5.7344270	-905.8010	-14.3087430	-10.2369371	0	1	0	0	0	1	0	0	1	0	0	0	0	1	1	1	0
7.2033502	-833.6400	-3.9962932	4.0803572	0	0	0	0	0	0	1	0	1	0	0	0	0	1	0	0	1
2.1317769	-352.1942	80.7382882	2.5543035	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0
2.2234298	-243.3012	58.1245499	-0.9482041	0	1	0	0	0	1	0	0	0	0	0	1	0	0	1	0	1
2.9615111	-229.7528	93.2601837	3.6614896	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0
5.4824758	-646.4314	-13.6665360	-7.2847495	0	1	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1
4.5600568	-938.2152	-44.0725027	-9.2490891	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0
5.2263981	-456.2501	56.5116128	5.6451362	0	1	0	1	0	0	0	0	0	0	0	0	1	1	1	0	0
7.3560267	-896.9518	-35.8371793	-11.2568931	1	0	0	1	0	0	0	0	0	0	0	1	0	1	1	0	1
4.6615484	-629.6402	26.6429060	-15.2321563	0	0	1	0	0	0	0	1	0	0	0	0	0	1	0	0	1
7.3146858	-757.4147	-17.9440700	2.7435124	0	0	1	0	1	0	0	0	0	0	0	0	0	1	1	0	1
7.0857939	-957.9367	-55.3124470	-8.4158384	0	0	1	0	0	0	0	0	1	0	0	0	0	1	1	0	0
5.7933062	-465.5236	53.4792947	-12.0013539	1	0	0	0	1	0	0	0	1	0	0	0	0	1	1	1	0
8.3292751	-916.7946	-0.4048277	-19.5349766	0	1	0	0	0	1	0	0	0	0	0	0	1	1	1	0	0
1.6111493	-128.9128	46.8367392	16.2695668	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0	1	0
4.4452150	-886.6260	-39.4758985	-11.8393891	0	1	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0
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7.4430980	-922.9750	-61.9924644	7.3903162	1	0	0	0	0	1	0	0	0	0	1	0	0	1	1	0	1
2.9423640	-304.1000	74.1928265	8.8061881	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	0
7.4731006	-818.7589	-36.3701861	0.9047611	1	0	0	0	0	1	0	0	0	0	0	0	1	1	1	1	0
6.9145633	-873.1602	-48.7511906	2.9905628	0	0	0	0	1	0	0	0	0	1	0	0	0	1	0	1	0
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4.9631104	-431.0958	38.2304783	-7.3317562	0	0	1	0	0	0	1	0	0	0	0	1	0	1	1	0	0
5.0195884	-637.7364	36.6033970	-15.7857291	0	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0	0
2.0572535	-126.6471	56.1105361	4.3121809	1	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0	1
1.4155678	-323.6836	28.0379861	0.5019642	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	0
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5.5519297	-920.9490	-54.6666336	11.3073798	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	1	0
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6.3028546	-725.9784	34.4980432	-2.7752020	1	0	0	0	0	0	1	0	1	0	0	0	0	1	1	0	0
3.2887344	-259.5360	103.7078339	-2.8405588	0	0	0	1	0	0	0	0	0	0	0	1	0	1	0	1	0
2.7027625	-131.5311	72.6838775	8.3144635	1	0	0	0	0	0	1	0	1	0	0	0	0	0	1	1	0
6.6450799	-607.8573	-23.2009464	16.9821817	0	0	0	0	0	1	0	0	0	1	0	0	0	1	1	0	0
3.1572504	-680.0908	8.9239272	-1.9455752	0	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1	0
4.1502383	-660.9626	12.0057668	3.2436048	0	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	1
5.2788227	-876.4613	-34.5852825	-5.9741659	0	1	0	0	0	1	0	0	1	0	0	0	0	0	1	1	0
3.8602587	-604.0464	56.7668374	0.9123535	1	0	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0
5.6632613	-594.1455	5.1634830	-6.5080933	1	0	0	0	0	0	1	0	0	0	0	0	0	1	1	0	0
1.6093167	-265.8649	75.7230013	1.6495559	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0
4.9598848	-972.9864	-32.3686364	-15.8227175	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	1	0
3.6924689	-561.7527	-16.5676222	8.4374788	0	1	0	0	0	0	0	1	0	0	1	0	0	0	0	0	1
4.1496045	-586.9725	-16.5521256	2.9364318	0	1	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0
3.1770919	-262.1569	69.2426116	7.4697497	0	0	0	0	1	0	0	0	0	0	0	0	1	1	0	0	1
6.0513795	-609.6835	45.9873488	-6.9599899	0	1	0	0	0	0	0	1	0	0	0	0	1	1	1	0	1
4.2513388	-318.7826	29.7682340	10.1634312	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0	0	1
2.3059660	-128.9802	118.7062102	-11.0798852	1	0	0	0	0	0	0	0	0	0	1	0	0	0	1	1	0
7.6397076	-968.5723	-49.4700896	-1.8866875	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	0
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5.4672137	-443.5776	18.0978724	10.0004754	0	1	0	1	0	0	0	0	0	1	0	0	0	1	1	0	0
3.5423480	-614.3733	22.6243329	-1.3604029	0	1	0	1	0	0	0	0	0	0	0	0	1	0	0	1	0
4.4193610	-887.4791	-75.1606373	-3.8117246	0	0	1	0	0	0	0	1	0	0	1	0	0	0	0	0	0
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5.7148292	-325.6459	78.3777487	10.7010205	0	0	1	0	0	1	0	0	0	1	0	0	0	1	1	0	1
7.3732777	-900.2836	0.6122613	-2.2290941	0	1	0	0	0	1	0	0	0	0	0	1	0	1	1	0	1
3.9460867	-623.1279	44.4171497	5.9117924	1	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0	1
5.2485869	-680.2863	36.4335920	-18.7901980	0	0	1	0	0	1	0	0	0	0	0	0	0	1	0	0	0
3.6755371	-442.6857	50.8338956	2.6783598	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	1	0
5.3041114	-358.7596	93.3888780	-1.1858880	1	0	0	1	0	0	0	0	0	0	0	0	0	1	1	0	0
1.7643515	-200.1902	56.9335703	0.0230523	1	0	0	0	0	0	0	1	0	1	0	0	0	0	1	0	0
4.2349730	-192.8859	73.9503000	1.7476334	0	1	0	0	0	1	0	0	0	0	0	1	0	1	1	0	1
3.5850273	-345.3207	11.8500050	24.0348552	0	1	0	0	0	1	0	0	0	0	0	0	0	0	1	1	0
6.6744098	-983.2324	-74.1859392	9.9064620	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	1	0
1.0487341	-117.1774	95.6809486	-6.5825746	0	0	1	1	0	0	0	0	0	0	0	1	0	0	0	0	0
2.9722115	-473.0769	4.7863145	8.3365702	1	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0
5.5728336	-785.9440	-45.4187275	1.7965446	0	0	0	0	0	1	0	0	1	0	0	0	0	0	1	1	0
4.0331374	-405.2919	38.7583690	-4.6726849	0	0	0	1	0	0	0	0	0	0	1	0	0	1	0	1	0
5.5221494	-694.8952	11.5782324	-7.7169916	0	0	1	0	0	0	0	1	0	0	1	0	0	1	1	0	1
8.2219863	-998.4987	-59.0167176	0.0249471	0	0	1	0	0	1	0	0	0	1	0	0	0	1	1	1	0
8.3509921	-972.9375	-82.4387319	7.0018932	1	0	0	0	0	0	1	0	0	0	1	0	0	1	1	1	0
9.0718419	-789.9412	-49.9597007	7.9514372	1	0	0	0	0	0	1	0	0	1	0	0	0	1	1	0	0
5.9969887	-829.8536	-57.0645696	-5.7276616	0	1	0	0	0	0	0	1	0	0	0	0	1	1	0	0	0
2.1967471	-347.5320	83.4925366	-7.7910245	0	1	0	0	0	0	1	0	1	0	0	0	0	0	0	0	1
1.8786978	-170.4598	76.6089363	2.3095989	1	0	0	0	0	0	0	1	0	0	0	0	1	0	1	0	0
6.7955412	-898.9757	-53.3123377	10.8996128	0	0	1	0	0	0	0	1	0	0	0	1	0	1	0	0	1
2.6397827	-366.5869	23.8219972	18.3422078	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	1	0
2.4761716	-117.6009	91.6624156	4.3775699	0	0	1	0	1	0	0	0	1	0	0	0	0	1	0	1	0
2.7620282	-321.3193	90.0314448	-6.3673192	0	0	1	0	0	0	0	1	0	0	0	0	0	1	0	0	1
3.9981669	-635.3012	40.4601087	-13.9881532	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1
1.6784543	-307.6299	53.8679606	-6.9432182	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0
5.3168528	-366.5872	37.9354387	-3.5182592	0	1	0	0	0	0	0	1	0	0	0	0	1	1	1	0	0
4.9614370	-779.1779	-32.7528509	7.9135226	0	0	1	0	0	1	0	0	0	0	0	0	1	0	0	0	1
3.3162019	-414.3750	9.8223532	-2.6782824	0	0	1	0	0	0	0	0	0	0	1	0	0	0	1	0	0
3.8935219	-348.5650	46.6594298	-5.2218657	0	0	0	0	0	0	0	1	0	0	1	0	0	1	0	0	0
2.5957384	-459.1439	44.6371925	5.4127360	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	1	0
3.0193812	-466.5849	-4.0389658	10.6347311	0	1	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1
5.9325970	-796.7744	-52.1543162	2.5652785	1	0	0	1	0	0	0	0	0	1	0	0	0	0	1	1	0
0.5605372	-129.6207	109.8888600	-3.1977250	0	0	1	0	0	0	1	0	0	1	0	0	0	0	0	0	0
2.1476524	-126.1132	105.3065194	6.9945142	0	1	0	0	0	0	1	0	0	0	0	1	0	1	0	0	1
8.2222341	-991.4187	-74.5080310	-10.4835247	1	0	0	0	0	0	0	1	1	0	0	0	0	1	1	0	1
3.6098390	-342.6319	50.1664080	-2.8119201	0	0	0	0	1	0	0	0	0	0	0	0	1	0	1	0	1
6.3704834	-803.0819	14.6643348	0.7765512	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0	1	0
2.6932211	-280.0661	70.7817186	8.7493945	0	0	1	0	1	0	0	0	0	0	0	1	0	0	1	0	0
3.7878156	-331.3828	90.8072955	-14.9084605	0	0	0	0	0	0	1	0	0	1	0	0	0	1	0	1	0
2.2788770	-294.3568	72.3661522	12.4735929	0	1	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0
2.9695598	-511.0737	40.4136044	-5.0243332	0	1	0	0	0	1	0	0	0	1	0	0	0	1	0	0	0
4.5325140	-406.0510	49.8344878	-10.5289101	1	0	0	0	1	0	0	0	1	0	0	0	0	1	0	0	1
6.7270428	-806.7846	-46.8956671	-4.3111070	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0
3.2438143	-368.7278	54.3718915	7.7575263	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	1	0
4.9952146	-995.1834	-68.5820506	-8.8886937	0	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1
2.1420347	-363.5274	14.3247404	4.9225130	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0
3.4192708	-325.5380	27.2364301	18.1836883	1	0	0	0	0	0	0	1	0	0	0	0	0	0	1	1	0
6.2243440	-899.4477	-7.4379304	3.2081506	0	1	0	0	1	0	0	0	0	0	0	0	1	0	1	1	0
3.7491856	-633.4045	22.1853729	6.2591259	0	0	1	0	1	0	0	0	0	0	0	0	1	0	0	0	1
1.8053534	-222.1468	101.6653264	-1.5719274	0	0	1	0	0	1	0	0	0	0	1	0	0	0	0	0	0
6.3742752	-835.1834	-59.7906432	15.3477693	0	1	0	0	0	0	0	1	0	1	0	0	0	1	0	0	1
3.5435666	-186.7519	72.5871825	5.4440231	1	0	0	0	0	0	0	0	0	0	1	0	0	1	1	0	1
8.0893076	-859.5472	-17.5826739	3.3208501	1	0	0	0	0	0	0	1	0	0	0	0	0	1	1	0	0
2.3536709	-319.2820	16.3794291	20.8344347	1	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1	0
6.7407502	-980.2413	-74.6531371	5.3032876	0	0	0	0	0	0	1	0	0	0	0	1	0	0	1	0	0
5.9964238	-942.1617	-66.4466330	0.5934104	0	0	1	0	1	0	0	0	1	0	0	0	0	1	0	0	1
5.7630203	-804.5622	-28.8679360	6.2931697	1	0	0	0	0	0	0	1	0	0	0	0	1	1	0	0	0
6.0202990	-799.4797	21.3267532	-19.9135718	0	1	0	1	0	0	0	0	0	0	0	0	0	1	0	1	0
1.3743217	-147.8707	130.2987440	-0.3218381	0	0	1	0	0	1	0	0	1	0	0	0	0	0	0	1	0
2.4007914	-152.6345	42.7503425	14.7914485	0	0	0	1	0	0	0	0	0	1	0	0	0	0	1	1	0
4.3879314	-445.2666	5.2285786	9.0183152	0	1	0	0	0	0	1	0	0	0	0	0	1	1	0	0	1
3.6860215	-322.1288	58.0103134	-0.6610311	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0
4.0979686	-383.9283	62.5465761	-11.0891818	0	0	0	0	0	0	1	0	0	1	0	0	0	1	0	1	0
3.2971727	-565.4330	-6.8162650	8.4680298	0	1	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0
5.1802420	-590.8554	51.1768779	-11.4100503	0	0	1	0	1	0	0	0	0	0	0	0	1	0	1	1	0
3.5393674	-368.9301	52.6463586	4.5396544	0	0	0	0	1	0	0	0	1	0	0	0	0	1	0	0	0
5.6073821	-647.4521	11.2113772	9.0143981	1	0	0	0	0	0	0	1	0	0	0	0	1	1	0	0	0
3.5405449	-198.5368	70.5714279	4.7796327	0	0	0	0	0	0	1	0	0	0	0	1	0	1	1	0	0
6.1089959	-746.0714	29.3496158	2.8586917	0	0	0	0	0	0	0	1	0	0	1	0	0	0	1	1	0
5.2892183	-378.6559	36.8374914	10.5861424	1	0	0	0	0	0	0	0	0	0	0	1	0	1	1	0	0
5.4184177	-642.8365	0.2579623	2.3966815	0	0	1	0	0	0	1	0	0	0	0	1	0	0	1	0	0
6.4519395	-812.0407	-17.8040414	0.5646650	0	0	0	0	0	0	0	0	0	0	1	0	0	1	0	1	0
4.1637478	-394.9650	85.4879528	-1.4803607	0	0	1	0	0	0	1	0	0	0	1	0	0	0	1	0	0
2.5912830	-235.2796	70.7376786	-6.1382883	0	1	0	0	0	0	1	0	0	0	0	1	0	1	0	0	1
4.7083071	-237.9939	72.3254589	13.7862600	0	0	1	1	0	0	0	0	0	0	1	0	0	1	1	0	0
3.1318616	-244.0416	76.2726819	12.5465801	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1	0	0
5.6917192	-611.9938	23.5983303	1.5378191	1	0	0	0	0	0	1	0	0	1	0	0	0	1	1	0	0
3.5596356	-346.4557	72.3955258	-2.2832487	0	0	0	0	0	0	0	1	0	0	0	0	1	0	1	0	0
3.1167645	-173.2467	92.4015212	-9.1985881	0	0	1	0	0	1	0	0	0	0	1	0	0	0	1	0	1
4.7951828	-704.8994	15.9929271	-8.6385628	0	0	0	0	1	0	0	0	0	0	0	0	1	0	1	1	0
2.8684667	-276.8206	29.6293054	2.0460564	0	0	0	1	0	0	0	0	0	0	0	0	0	0	1	0	1
6.4619099	-758.3410	-12.8829834	-7.1216987	0	0	1	0	0	0	0	1	1	0	0	0	0	1	1	1	0
3.7295130	-847.5215	-25.7937012	-10.7995535	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1	0
6.1226501	-769.9430	-37.8488484	6.1118701	0	0	0	0	0	0	1	0	0	1	0	0	0	0	1	0	0
6.7451620	-659.0330	10.8134577	6.0046189	0	1	0	0	0	0	0	1	1	0	0	0	0	1	1	0	0
5.8709844	-633.3569	22.7841700	9.1412721	1	0	0	1	0	0	0	0	1	0	0	0	0	1	0	1	0
2.6857259	-435.7240	32.6515732	-5.7462175	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1
4.7020901	-846.8846	-35.6600375	-9.0243672	0	0	1	0	1	0	0	0	0	0	0	1	0	0	0	1	0
3.2563847	-350.6548	73.2746169	0.2301095	0	1	0	0	0	0	1	0	0	0	0	0	1	0	1	0	1
6.2602501	-710.9184	-28.6902474	-0.1669734	1	0	0	1	0	0	0	0	0	0	0	0	0	1	1	1	0
5.3216892	-773.6597	19.9480884	-1.3770481	0	1	0	0	0	0	1	0	1	0	0	0	0	1	0	0	1
4.1337345	-552.3141	24.3964665	-10.7495594	0	1	0	0	0	0	1	0	1	0	0	0	0	0	1	1	0
2.1276519	-389.3827	40.0119558	-0.8566912	0	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	1
2.3878063	-134.4806	127.7279628	-3.1174046	0	0	1	0	0	1	0	0	0	0	0	0	1	1	0	1	0
3.5805595	-474.4743	67.9269487	4.9474913	0	1	0	0	1	0	0	0	0	0	0	1	0	0	0	1	0
5.1516258	-991.0639	-66.4838056	3.1743638	0	0	1	0	0	0	0	1	0	0	0	1	0	0	0	1	0
1.9540272	-293.9069	64.2251170	-2.3794749	1	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1	0
5.4387369	-452.0464	-6.9746857	10.2041564	0	0	0	0	0	1	0	0	0	0	0	0	1	1	1	0	1
2.7267795	-224.2159	73.8320524	0.3450764	0	0	0	0	0	0	0	1	0	0	1	0	0	1	0	1	0
1.4024294	-270.7565	82.8159960	-0.2639727	1	0	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0
2.9061439	-346.3795	20.6474496	12.3399123	0	1	0	1	0	0	0	0	0	1	0	0	0	0	1	0	1
5.6614825	-946.7971	-50.1395238	-1.9323210	0	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0
4.7094960	-451.3733	37.7054795	5.8741678	0	0	1	0	0	0	0	0	0	0	0	0	1	1	0	0	0
5.7860001	-702.6745	26.2834375	-15.6077897	0	0	1	0	0	0	0	1	1	0	0	0	0	1	1	0	1
4.7400258	-448.4349	11.0820260	9.7958953	0	0	1	0	0	0	1	0	0	0	1	0	0	1	0	1	0
5.4032576	-393.1903	24.9758531	-0.6811211	1	0	0	0	0	0	0	1	0	0	1	0	0	1	1	0	1
5.5559356	-760.2688	-11.0112268	-6.5718113	0	0	1	0	0	0	0	0	0	0	1	0	0	0	1	0	0
3.8286405	-133.0760	71.4029729	3.2711065	0	1	0	1	0	0	0	0	0	0	0	0	1	1	1	0	0
4.1173598	-400.7680	30.4253060	16.6658208	0	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	0
5.0259616	-755.3758	3.0240066	-12.4704026	0	0	1	1	0	0	0	0	0	0	1	0	0	0	1	0	1
6.3602198	-829.9739	-49.9873944	-1.3541318	1	0	0	0	0	0	1	0	0	0	1	0	0	1	1	0	1
4.7945551	-178.3547	71.9010065	5.6440609	0	0	0	0	1	0	0	0	0	0	0	0	1	1	1	1	0
6.6070907	-962.4281	-32.8877122	3.6592500	1	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0
6.8104632	-898.8336	-13.4430198	-11.4335529	1	0	0	0	1	0	0	0	0	0	1	0	0	0	1	1	0
3.2364528	-552.4238	31.8928300	-4.3407092	0	0	0	0	0	0	1	0	0	0	0	1	0	0	1	0	0
8.4139848	-965.1969	-58.4514623	2.0735835	1	0	0	0	0	1	0	0	0	0	0	1	0	1	1	1	0
6.0287969	-505.4069	63.8844255	4.2526513	0	1	0	0	0	1	0	0	0	1	0	0	0	1	1	0	0
2.7693482	-178.7507	36.0641039	12.5744434	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	0	1
6.1251012	-938.6275	-21.4571792	-9.4900270	0	1	0	0	0	0	1	0	1	0	0	0	0	0	1	0	0
3.7591077	-280.0807	93.1422266	-8.1536608	0	1	0	0	0	0	1	0	0	1	0	0	0	1	0	1	0
5.6279153	-584.5386	45.2363597	-10.0231419	1	0	0	0	0	0	0	1	0	0	1	0	0	1	1	1	0
3.1153989	-485.7655	-1.6665646	6.8913916	0	0	1	0	0	0	1	0	0	0	0	0	1	0	0	0	0
4.5842354	-597.9286	-28.5068127	18.6548236	0	0	1	0	0	1	0	0	0	0	0	1	0	0	0	1	0
3.2250581	-266.2258	54.0294063	6.9851155	1	0	0	0	0	0	1	0	0	0	1	0	0	1	0	1	0
2.5211542	-372.2102	19.9783117	9.0130567	0	1	0	1	0	0	0	0	0	0	0	0	1	1	0	1	0
3.1900046	-511.8592	27.5922984	8.6356177	0	0	1	0	0	1	0	0	0	1	0	0	0	0	0	0	1
6.6956703	-961.8224	-63.9776697	12.8047430	0	1	0	0	0	1	0	0	0	0	0	1	0	0	1	1	0
1.3947011	-142.2801	89.2537252	-3.2879516	0	0	1	0	0	1	0	0	1	0	0	0	0	0	0	0	0
3.0797904	-236.7595	100.7101784	0.0958775	0	0	1	0	1	0	0	0	0	1	0	0	0	1	0	0	1
5.2453535	-411.4603	34.0633229	2.4191925	0	0	1	0	0	0	1	0	1	0	0	0	0	1	1	1	0
1.2806235	-226.1374	32.0869616	24.9910510	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0
5.1398492	-645.4918	34.7660318	-8.6395192	1	0	0	0	0	1	0	0	0	0	0	0	1	0	1	0	0
7.3530824	-938.5942	-39.9793119	-4.1107338	1	0	0	0	0	0	1	0	0	0	1	0	0	1	1	0	1
6.1536843	-917.2288	-25.5846110	4.1205690	1	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	1
6.4781777	-848.0641	-27.7212534	5.4099276	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0
3.3717393	-233.9077	59.8881421	15.4568324	1	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0
4.4610721	-525.1187	27.8142055	-10.1949427	0	1	0	0	0	0	1	0	0	0	1	0	0	1	0	1	0
4.9068722	-760.4565	11.2214087	1.2207942	0	1	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0
3.3788689	-316.5194	56.5439395	13.0136453	0	0	1	0	0	0	0	1	0	0	0	0	0	1	0	0	0
5.5085377	-697.6658	25.2476174	0.6328971	0	0	0	0	0	0	0	1	0	0	0	1	0	0	1	1	0
6.1098516	-649.8434	41.8679875	4.1814563	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	0	0
1.5546197	-302.6147	46.5596382	13.9720398	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1
5.6758099	-420.1195	75.3866674	-5.9827789	0	0	0	1	0	0	0	0	0	0	0	1	0	1	1	0	0
5.5225287	-832.7628	5.0542434	2.1878864	0	0	1	0	0	1	0	0	0	0	1	0	0	0	1	0	1
4.2762288	-488.6672	38.9340152	-4.4734592	0	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0
5.2903145	-368.7503	81.2167071	2.6479334	0	0	0	0	0	0	0	1	0	0	1	0	0	1	1	1	0
1.8926090	-269.0603	98.9510332	-8.5513112	1	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	0
7.9165120	-962.8080	-76.2711219	-1.0277298	0	1	0	1	0	0	0	0	0	0	0	0	1	1	1	0	1
6.5012840	-918.2298	-28.8324557	4.1761867	1	0	0	0	0	0	0	1	0	0	1	0	0	0	1	0	1
5.7903613	-768.8439	-26.0445423	-2.6759973	0	0	0	1	0	0	0	0	0	1	0	0	0	1	0	0	1
4.8626847	-553.2674	33.9996237	1.5489389	0	0	0	0	0	0	0	1	0	0	1	0	0	1	0	1	0
4.9112377	-661.3321	-34.8474848	6.8174528	0	0	1	0	1	0	0	0	0	0	0	1	0	0	1	1	0
7.6633758	-606.4368	-23.6294767	-1.3220118	0	1	0	0	1	0	0	0	0	0	1	0	0	1	1	0	0
5.1350763	-343.3536	87.9942616	5.8694701	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0
4.9273412	-782.3499	-61.6459433	-4.5523323	0	0	1	0	0	1	0	0	0	0	0	0	0	0	1	1	0
3.8412298	-817.4859	8.4292994	-18.4205124	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0
3.7086761	-773.9376	-11.3973569	-7.9007727	0	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1
5.1435020	-573.5536	34.0642310	2.5252796	0	0	1	0	0	0	0	0	0	0	0	0	1	0	1	0	0
5.8489542	-521.6711	-14.9460680	15.4013683	0	1	0	0	0	0	1	0	0	0	0	0	1	1	1	1	0
6.5868550	-805.7659	-39.8937509	3.8468786	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	1	0
4.3628865	-224.9121	88.4540694	11.7262361	0	1	0	0	0	1	0	0	0	0	0	0	0	1	0	0	0
4.0452426	-189.3878	105.8495908	8.4676670	1	0	0	0	1	0	0	0	0	0	1	0	0	1	1	0	0
5.1162990	-772.5271	-41.9751480	-6.9579660	0	1	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0
6.5220293	-826.0873	8.1807192	2.1656532	0	1	0	1	0	0	0	0	0	1	0	0	0	1	1	0	0
5.5674342	-572.1999	30.3507145	-11.5937395	0	0	1	0	0	0	1	0	1	0	0	0	0	1	1	0	1
3.9994799	-424.6169	67.7384546	-9.5499350	0	1	0	1	0	0	0	0	0	0	1	0	0	1	0	1	0
3.4507876	-199.4673	83.1565330	1.3761306	1	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	1
5.1644096	-550.5504	62.8301027	-1.0473185	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1
2.5104892	-324.6469	68.0106536	-0.3203623	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	0
3.6033427	-370.3285	72.3047553	-9.3496689	0	1	0	0	0	0	1	0	0	0	0	1	0	1	0	1	0
3.6320573	-351.1549	39.7637649	13.5440953	0	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	1
3.9030197	-741.9187	-52.7113949	17.6430945	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	0
5.6377702	-759.0356	-40.6281660	14.3037526	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1	0	1
1.4713569	-236.0450	73.3178500	1.9983017	0	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0
5.8558071	-818.8505	14.4749253	2.0391142	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	1	0
7.0892847	-796.1936	22.6534459	-0.8901069	0	1	0	0	0	0	0	1	0	0	0	1	0	1	0	1	0
3.5717653	-420.1485	72.0845640	-11.9842598	0	1	0	0	0	0	1	0	1	0	0	0	0	0	1	0	1
4.8112795	-585.9868	20.9361435	-1.4389155	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0
4.8244638	-871.2624	-47.0202806	-0.1205405	0	1	0	0	0	0	0	0	1	0	0	0	0	0	0	0	1
3.9067661	-576.3148	7.7166108	12.2230089	1	0	0	1	0	0	0	0	1	0	0	0	0	0	0	1	0
3.1890818	-338.3413	79.2152187	4.5065417	0	0	0	0	0	1	0	0	0	0	0	0	1	0	1	1	0
3.4693338	-551.4472	21.9722936	-3.0938907	0	1	0	0	0	0	1	0	0	0	0	0	1	0	0	1	0
6.5477029	-837.6881	-3.4906987	4.6555818	1	0	0	0	0	0	0	0	0	0	0	0	0	1	0	0	1
7.0982946	-956.2131	-82.8831689	6.9430551	0	1	0	1	0	0	0	0	0	0	0	1	0	1	1	0	1
4.5955914	-313.9811	84.9854543	3.6232352	0	0	1	0	0	0	0	0	0	0	1	0	0	1	1	1	0
4.1048883	-172.7788	45.0290085	21.4141825	0	0	0	0	0	0	0	1	0	1	0	0	0	1	0	0	1
4.4773459	-498.8541	44.9093011	2.3548682	0	1	0	0	0	0	0	0	0	0	0	0	1	0	1	0	1
6.0221234	-771.1293	-37.1641137	-4.7383848	0	0	1	0	0	1	0	0	0	0	0	0	1	1	0	1	0
5.1064796	-261.6977	64.1452754	12.4844691	0	0	0	0	0	0	1	0	0	0	0	0	0	1	1	1	0
1.5581819	-180.8481	124.8672625	3.8756988	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1
7.4350426	-813.4660	-27.5121497	-0.3223569	0	1	0	0	0	0	1	0	0	1	0	0	0	1	1	0	0
5.7311956	-501.2304	28.8038369	-3.7955796	1	0	0	0	0	0	0	1	0	0	0	0	1	1	1	1	0
6.5088626	-483.2401	60.6086426	-8.8034870	0	1	0	0	1	0	0	0	1	0	0	0	0	1	1	0	0
4.0728802	-552.2808	56.0808735	-2.3832119	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0
1.6381576	-142.2456	120.5295747	3.0857237	0	0	1	0	1	0	0	0	0	0	0	0	1	1	0	0	0
6.2315163	-824.2011	13.5099614	1.4949069	0	0	1	1	0	0	0	0	0	1	0	0	0	1	0	0	0
2.5145947	-296.3491	95.3152329	-5.0594703	0	1	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0
4.7702831	-484.6200	2.4587454	11.0010240	0	0	1	0	0	1	0	0	1	0	0	0	0	0	1	1	0
5.8097099	-736.9180	13.2485095	-2.1607827	0	1	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0
0.4128649	-167.8157	73.5292741	-4.6857662	0	1	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1
5.6339134	-717.3513	4.4306316	-9.9919152	0	0	1	0	1	0	0	0	0	1	0	0	0	1	0	0	0
3.8116203	-265.8546	100.8150469	3.0803615	0	1	0	0	0	0	0	1	0	0	0	0	1	1	1	0	1
5.5566373	-554.6663	43.0191758	-13.8356197	0	0	0	0	0	0	0	0	0	1	0	0	0	1	1	0	1
4.3604842	-224.8033	44.6209591	14.5407885	0	1	0	0	0	1	0	0	0	0	1	0	0	1	1	0	0
5.7537008	-833.7362	-49.0867082	0.9249284	0	1	0	0	0	0	0	1	0	0	0	1	0	1	0	0	1
7.2557624	-795.9713	-30.7603690	-9.6116820	0	0	1	0	1	0	0	0	0	0	1	0	0	1	1	0	0
5.0860318	-454.5704	9.8965110	8.7866987	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	1

model Workflow

We continue with a workflow to tie the model and feature engineering process together using the workflows package.

mars_wf <- workflow() |> 
  add_model(mars_spec) |> 
  add_recipe(mars_rec)

Parameter Grid

The tuning parameters are updated, the maximum interaction, prod_degree used should not be more than 3rd degree, as there’s rarely any benefit when it’s above such degree. num_terms is set to include also possible interaction terms, as data includes 10 features. The grid table can be seen in Table 3

yield_grid <- extract_parameter_set_dials(mars_spec) |> 
  update(
    prod_degree = prod_degree(range = c(1, 3)),
    num_terms = num_terms(range = c(2, 20))
  ) |> 
  grid_regular(levels = 20)

yield_grid |> 
  knitr::kable()

Table 3: Grid table

num_terms	prod_degree
2	1
3	1
4	1
5	1
6	1
7	1
8	1
9	1
10	1
11	1
12	1
13	1
14	1
15	1
16	1
17	1
18	1
19	1
20	1
2	2
3	2
4	2
5	2
6	2
7	2
8	2
9	2
10	2
11	2
12	2
13	2
14	2
15	2
16	2
17	2
18	2
19	2
20	2
2	3
3	3
4	3
5	3
6	3
7	3
8	3
9	3
10	3
11	3
12	3
13	3
14	3
15	3
16	3
17	3
18	3
19	3
20	3

Model Tuning

crop_tune <- tune_grid(
  mars_wf,
  mars_rec,
  resamples = crop_fold,
  grid = yield_grid,
  control = control_grid(save_pred = FALSE, save_workflow = TRUE)
)

Tune Evaluation

After tuning the result can be seen in Table 4 and Figure 4

collect_metrics(crop_tune) |> 
  knitr::kable()

Table 4: Result from tuning

num_terms	prod_degree	.metric	.estimator	mean	n	std_err	.config
2	1	rmse	standard	1.1081261	5	0.0125847	Preprocessor1_Model01
2	1	rsq	standard	0.5731602	5	0.0095423	Preprocessor1_Model01
3	1	rmse	standard	0.8147771	5	0.0166209	Preprocessor1_Model02
3	1	rsq	standard	0.7689832	5	0.0095183	Preprocessor1_Model02
4	1	rmse	standard	0.5506631	5	0.0244822	Preprocessor1_Model03
4	1	rsq	standard	0.8938372	5	0.0098961	Preprocessor1_Model03
5	1	rmse	standard	0.5131969	5	0.0021955	Preprocessor1_Model04
5	1	rsq	standard	0.9084858	5	0.0007566	Preprocessor1_Model04
6	1	rmse	standard	0.5054024	5	0.0002356	Preprocessor1_Model05
6	1	rsq	standard	0.9112499	5	0.0001432	Preprocessor1_Model05
7	1	rmse	standard	0.5015983	5	0.0002469	Preprocessor1_Model06
7	1	rsq	standard	0.9125810	5	0.0001505	Preprocessor1_Model06
8	1	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model07
8	1	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model07
9	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model08
9	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model08
10	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model09
10	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model09
11	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model10
11	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model10
12	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model11
12	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model11
13	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model12
13	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model12
14	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model13
14	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model13
15	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model14
15	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model14
16	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model15
16	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model15
17	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model16
17	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model16
18	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model17
18	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model17
19	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model18
19	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model18
20	1	rmse	standard	0.5005388	5	0.0002499	Preprocessor1_Model19
20	1	rsq	standard	0.9129500	5	0.0001428	Preprocessor1_Model19
2	2	rmse	standard	1.1081261	5	0.0125847	Preprocessor1_Model20
2	2	rsq	standard	0.5731602	5	0.0095423	Preprocessor1_Model20
3	2	rmse	standard	0.8147771	5	0.0166209	Preprocessor1_Model21
3	2	rsq	standard	0.7689832	5	0.0095183	Preprocessor1_Model21
4	2	rmse	standard	0.5506631	5	0.0244822	Preprocessor1_Model22
4	2	rsq	standard	0.8938372	5	0.0098961	Preprocessor1_Model22
5	2	rmse	standard	0.5131969	5	0.0021955	Preprocessor1_Model23
5	2	rsq	standard	0.9084858	5	0.0007566	Preprocessor1_Model23
6	2	rmse	standard	0.5054024	5	0.0002356	Preprocessor1_Model24
6	2	rsq	standard	0.9112499	5	0.0001432	Preprocessor1_Model24
7	2	rmse	standard	0.5015983	5	0.0002469	Preprocessor1_Model25
7	2	rsq	standard	0.9125810	5	0.0001505	Preprocessor1_Model25
8	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model26
8	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model26
9	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model27
9	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model27
10	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model28
10	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model28
11	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model29
11	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model29
12	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model30
12	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model30
13	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model31
13	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model31
14	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model32
14	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model32
15	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model33
15	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model33
16	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model34
16	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model34
17	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model35
17	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model35
18	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model36
18	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model36
19	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model37
19	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model37
20	2	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model38
20	2	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model38
2	3	rmse	standard	1.1081261	5	0.0125847	Preprocessor1_Model39
2	3	rsq	standard	0.5731602	5	0.0095423	Preprocessor1_Model39
3	3	rmse	standard	0.8147771	5	0.0166209	Preprocessor1_Model40
3	3	rsq	standard	0.7689832	5	0.0095183	Preprocessor1_Model40
4	3	rmse	standard	0.5506631	5	0.0244822	Preprocessor1_Model41
4	3	rsq	standard	0.8938372	5	0.0098961	Preprocessor1_Model41
5	3	rmse	standard	0.5131969	5	0.0021955	Preprocessor1_Model42
5	3	rsq	standard	0.9084858	5	0.0007566	Preprocessor1_Model42
6	3	rmse	standard	0.5054024	5	0.0002356	Preprocessor1_Model43
6	3	rsq	standard	0.9112499	5	0.0001432	Preprocessor1_Model43
7	3	rmse	standard	0.5015983	5	0.0002469	Preprocessor1_Model44
7	3	rsq	standard	0.9125810	5	0.0001505	Preprocessor1_Model44
8	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model45
8	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model45
9	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model46
9	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model46
10	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model47
10	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model47
11	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model48
11	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model48
12	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model49
12	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model49
13	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model50
13	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model50
14	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model51
14	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model51
15	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model52
15	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model52
16	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model53
16	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model53
17	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model54
17	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model54
18	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model55
18	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model55
19	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model56
19	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model56
20	3	rmse	standard	0.5005376	5	0.0002504	Preprocessor1_Model57
20	3	rsq	standard	0.9129504	5	0.0001428	Preprocessor1_Model57

collect_metrics(crop_tune) |> 
  ggplot(aes(num_terms, mean, col = factor(prod_degree))) +
  geom_point() +
  geom_errorbar(
    aes(ymin = mean - std_err, ymax = mean + std_err),
    position = "dodge"
  ) +
  labs(
    title = "Tune Result from MARS (Earth) Model",
    x = "Number of Terms Used in Model",
    col = "Degree of Interaction"
  ) +
  facet_wrap(~.metric, scales = "free_y")

Figure 4

Making Use of Best tune Parameter

The original workflow which was initially set will be extracted. This is a very crucial step when comparing performance across different ML method.

mars_wf_extract <- extract_workflow(crop_tune)
mars_wf_extract

══ Workflow ════════════════════════════════════════════════════════════════════
Preprocessor: Recipe
Model: mars()

── Preprocessor ────────────────────────────────────────────────────────────────
3 Recipe Steps

• step_mutate()
• step_pca()
• step_dummy()

── Model ───────────────────────────────────────────────────────────────────────
MARS Model Specification (regression)

Main Arguments:
  num_terms = tune()
  prod_degree = tune()

Computational engine: earth 

To get the absolute model performance, rmse will be used instead of rsq when selecting the best tune parameter.

best_params <- select_best(crop_tune, metric = "rmse")

Next, we combine both workflow and parameters together to get a finalized workflow.

crop_mars_wf <- finalize_workflow(
  mars_wf_extract, 
  best_params
)

crop_mars_wf

══ Workflow ════════════════════════════════════════════════════════════════════
Preprocessor: Recipe
Model: mars()

── Preprocessor ────────────────────────────────────────────────────────────────
3 Recipe Steps

• step_mutate()
• step_pca()
• step_dummy()

── Model ───────────────────────────────────────────────────────────────────────
MARS Model Specification (regression)

Main Arguments:
  num_terms = 8
  prod_degree = 1

Computational engine: earth 

Final Model FIt

After getting our finalized we make the final model fit on the split object of our data.

crop_final_fit <- last_fit(
  crop_mars_wf,
  crop_yield_split
)

Model Evaluation

We collect the metrics from our final model showing the predicted and observed data on the test of the split in Table 5. A goodness of fit test can be seen in Figure 5

crop_final_fit |> 
  collect_metrics()

# A tibble: 2 × 4
  .metric .estimator .estimate .config             
  <chr>   <chr>          <dbl> <chr>               
1 rmse    standard       0.500 Preprocessor1_Model1
2 rsq     standard       0.913 Preprocessor1_Model1

test_pred <- crop_final_fit |> 
  collect_predictions()

head(test_pred, n = 1000) |> 
  knitr::kable()

Table 5: Predictions from model vs observed data

.pred	id	.row	yield_tons_per_hectare	.config
1.3402491	train/test split	3	1.1274433	Preprocessor1_Model1
5.9398453	train/test split	6	5.8984163	Preprocessor1_Model1
5.5221602	train/test split	8	5.8295423	Preprocessor1_Model1
2.9433855	train/test split	9	2.9437165	Preprocessor1_Model1
3.5284231	train/test split	10	3.7072931	Preprocessor1_Model1
6.0464413	train/test split	13	6.5251862	Preprocessor1_Model1
4.4493048	train/test split	17	4.3668806	Preprocessor1_Model1
5.2481223	train/test split	18	4.8589244	Preprocessor1_Model1
2.6380672	train/test split	26	2.3322549	Preprocessor1_Model1
5.1309009	train/test split	27	4.8765873	Preprocessor1_Model1
5.3131356	train/test split	31	5.1135877	Preprocessor1_Model1
4.9197328	train/test split	34	4.8981808	Preprocessor1_Model1
2.8384163	train/test split	36	3.6074964	Preprocessor1_Model1
4.8977568	train/test split	37	4.6964255	Preprocessor1_Model1
6.2654790	train/test split	40	6.3147863	Preprocessor1_Model1
2.8305119	train/test split	41	2.3683217	Preprocessor1_Model1
2.6008310	train/test split	44	2.9680630	Preprocessor1_Model1
6.2206373	train/test split	50	6.6549495	Preprocessor1_Model1
5.2424521	train/test split	53	5.4931742	Preprocessor1_Model1
6.3134873	train/test split	60	6.4119307	Preprocessor1_Model1
6.4194002	train/test split	61	5.8181997	Preprocessor1_Model1
5.1829557	train/test split	62	5.0202922	Preprocessor1_Model1
1.0425583	train/test split	70	0.8055127	Preprocessor1_Model1
6.3946198	train/test split	77	6.4800590	Preprocessor1_Model1
6.5472177	train/test split	78	6.5631304	Preprocessor1_Model1
3.8775188	train/test split	79	4.2637995	Preprocessor1_Model1
1.6082854	train/test split	80	0.6166115	Preprocessor1_Model1
4.0536182	train/test split	85	3.1344321	Preprocessor1_Model1
4.0335644	train/test split	86	5.0959326	Preprocessor1_Model1
2.7124701	train/test split	90	3.1455141	Preprocessor1_Model1
1.3059498	train/test split	92	1.2245024	Preprocessor1_Model1
4.7878771	train/test split	93	5.5784995	Preprocessor1_Model1
3.7401010	train/test split	100	3.6265013	Preprocessor1_Model1
5.5019699	train/test split	102	4.8367270	Preprocessor1_Model1
5.5172825	train/test split	107	5.1682150	Preprocessor1_Model1
2.6759737	train/test split	112	3.0500421	Preprocessor1_Model1
7.9102788	train/test split	115	7.6623721	Preprocessor1_Model1
6.0018563	train/test split	122	6.7327003	Preprocessor1_Model1
4.7593909	train/test split	123	3.9539290	Preprocessor1_Model1
6.5135058	train/test split	128	7.4148925	Preprocessor1_Model1
4.0732332	train/test split	133	3.3718108	Preprocessor1_Model1
5.9533235	train/test split	134	5.3263671	Preprocessor1_Model1
5.4547671	train/test split	141	5.9333616	Preprocessor1_Model1
5.0391360	train/test split	142	5.7451909	Preprocessor1_Model1
5.6403392	train/test split	143	5.8798318	Preprocessor1_Model1
1.0293026	train/test split	145	0.9621414	Preprocessor1_Model1
4.3215914	train/test split	147	3.8281463	Preprocessor1_Model1
4.9149370	train/test split	148	5.4503221	Preprocessor1_Model1
4.8466212	train/test split	149	4.8023728	Preprocessor1_Model1
3.6504194	train/test split	155	3.4862208	Preprocessor1_Model1
4.6595649	train/test split	157	4.5032000	Preprocessor1_Model1
4.3021745	train/test split	159	4.0032180	Preprocessor1_Model1
6.6094801	train/test split	160	7.2341936	Preprocessor1_Model1
3.6622055	train/test split	164	3.5919133	Preprocessor1_Model1
6.1565469	train/test split	165	5.6127836	Preprocessor1_Model1
2.4943377	train/test split	180	2.2483458	Preprocessor1_Model1
3.0030471	train/test split	188	3.0542928	Preprocessor1_Model1
7.8780592	train/test split	191	8.1147600	Preprocessor1_Model1
4.5695917	train/test split	196	3.4621095	Preprocessor1_Model1
2.6693367	train/test split	197	2.5492481	Preprocessor1_Model1
4.3271426	train/test split	198	4.5067078	Preprocessor1_Model1
5.1380509	train/test split	200	4.6743089	Preprocessor1_Model1
5.5297051	train/test split	202	4.8231473	Preprocessor1_Model1
6.5762263	train/test split	204	5.7822921	Preprocessor1_Model1
5.7697253	train/test split	207	5.1601046	Preprocessor1_Model1
2.7056179	train/test split	208	2.5595962	Preprocessor1_Model1
4.3631661	train/test split	210	3.9324384	Preprocessor1_Model1
7.8769264	train/test split	212	7.9809983	Preprocessor1_Model1
4.0707733	train/test split	215	3.7542764	Preprocessor1_Model1
3.7466605	train/test split	216	4.6427379	Preprocessor1_Model1
5.2702066	train/test split	217	4.7346597	Preprocessor1_Model1
1.2995343	train/test split	220	1.3232243	Preprocessor1_Model1
3.3083821	train/test split	222	2.8475063	Preprocessor1_Model1
4.5629477	train/test split	226	4.2505988	Preprocessor1_Model1
7.1540006	train/test split	227	7.1388154	Preprocessor1_Model1
6.1800928	train/test split	228	6.7160288	Preprocessor1_Model1
2.3148275	train/test split	233	1.7568555	Preprocessor1_Model1
1.3475430	train/test split	240	1.9787821	Preprocessor1_Model1
3.0186386	train/test split	241	2.9054304	Preprocessor1_Model1
3.6960169	train/test split	242	4.0782917	Preprocessor1_Model1
3.6615831	train/test split	243	4.3320452	Preprocessor1_Model1
6.5362816	train/test split	244	6.5064709	Preprocessor1_Model1
5.3106879	train/test split	251	6.3427708	Preprocessor1_Model1
5.2297283	train/test split	252	4.9904727	Preprocessor1_Model1
5.4200544	train/test split	260	6.0740674	Preprocessor1_Model1
5.2181713	train/test split	264	5.7269896	Preprocessor1_Model1
8.0041245	train/test split	269	8.2097962	Preprocessor1_Model1
2.4102305	train/test split	272	2.7276966	Preprocessor1_Model1
3.4060229	train/test split	279	3.9758837	Preprocessor1_Model1
4.4206152	train/test split	281	4.4820545	Preprocessor1_Model1
2.9887767	train/test split	283	3.1960797	Preprocessor1_Model1
3.6876722	train/test split	287	3.3020495	Preprocessor1_Model1
8.1125925	train/test split	288	7.4329464	Preprocessor1_Model1
2.3714568	train/test split	294	2.0716482	Preprocessor1_Model1
5.1288160	train/test split	297	5.1225016	Preprocessor1_Model1
7.6091151	train/test split	301	7.4094933	Preprocessor1_Model1
2.9619525	train/test split	302	2.8322017	Preprocessor1_Model1
1.2821707	train/test split	304	1.3521265	Preprocessor1_Model1
1.6441430	train/test split	307	0.9272761	Preprocessor1_Model1
4.9985205	train/test split	309	4.8434830	Preprocessor1_Model1
2.9421963	train/test split	312	3.4080261	Preprocessor1_Model1
6.5742483	train/test split	321	6.6016305	Preprocessor1_Model1
2.6923284	train/test split	328	2.9788611	Preprocessor1_Model1
4.3916751	train/test split	332	5.2531037	Preprocessor1_Model1
1.5241675	train/test split	334	1.6126739	Preprocessor1_Model1
6.9735116	train/test split	336	6.2645059	Preprocessor1_Model1
1.1635528	train/test split	339	1.1681240	Preprocessor1_Model1
1.4743539	train/test split	341	1.6572527	Preprocessor1_Model1
5.0319129	train/test split	342	5.1601442	Preprocessor1_Model1
4.7810921	train/test split	347	3.7247250	Preprocessor1_Model1
4.4646479	train/test split	350	4.2393580	Preprocessor1_Model1
4.9476521	train/test split	351	4.6139119	Preprocessor1_Model1
4.2280014	train/test split	355	3.9390599	Preprocessor1_Model1
5.4408357	train/test split	357	6.2070703	Preprocessor1_Model1
4.0656814	train/test split	360	4.5942937	Preprocessor1_Model1
4.1966504	train/test split	361	4.2748848	Preprocessor1_Model1
5.5626857	train/test split	363	5.6168513	Preprocessor1_Model1
4.1917404	train/test split	368	4.0432257	Preprocessor1_Model1
2.5047105	train/test split	369	1.5442522	Preprocessor1_Model1
3.3252664	train/test split	370	3.8490280	Preprocessor1_Model1
4.7105861	train/test split	373	5.2783259	Preprocessor1_Model1
4.8983506	train/test split	379	5.1504590	Preprocessor1_Model1
7.0038959	train/test split	382	7.1170363	Preprocessor1_Model1
3.6856763	train/test split	384	3.3249334	Preprocessor1_Model1
3.4797937	train/test split	391	3.8142162	Preprocessor1_Model1
6.5888809	train/test split	393	6.2412911	Preprocessor1_Model1
6.4713280	train/test split	394	6.5546353	Preprocessor1_Model1
3.7347323	train/test split	398	3.5537411	Preprocessor1_Model1
6.3854144	train/test split	399	7.0369377	Preprocessor1_Model1
6.1441474	train/test split	408	6.7705652	Preprocessor1_Model1
5.8067029	train/test split	414	4.7564128	Preprocessor1_Model1
2.4168558	train/test split	418	2.3632790	Preprocessor1_Model1
3.1474530	train/test split	420	3.2314496	Preprocessor1_Model1
5.5710718	train/test split	421	5.5654029	Preprocessor1_Model1
3.6945855	train/test split	422	3.4936565	Preprocessor1_Model1
6.2186870	train/test split	429	6.1269051	Preprocessor1_Model1
5.0301423	train/test split	430	5.0639347	Preprocessor1_Model1
2.4080279	train/test split	432	2.2543915	Preprocessor1_Model1
6.7599045	train/test split	434	6.7337711	Preprocessor1_Model1
5.0719740	train/test split	435	4.9505891	Preprocessor1_Model1
1.3661688	train/test split	438	0.9611130	Preprocessor1_Model1
6.7779148	train/test split	446	8.2000992	Preprocessor1_Model1
6.6813767	train/test split	450	7.0679133	Preprocessor1_Model1
4.7694037	train/test split	454	5.7096012	Preprocessor1_Model1
5.3810704	train/test split	456	5.0767879	Preprocessor1_Model1
6.3619234	train/test split	464	5.9169219	Preprocessor1_Model1
6.4482486	train/test split	467	7.3867335	Preprocessor1_Model1
5.9989608	train/test split	469	4.7715963	Preprocessor1_Model1
2.9481238	train/test split	473	2.9480814	Preprocessor1_Model1
1.3759196	train/test split	477	1.8039785	Preprocessor1_Model1
5.2424912	train/test split	480	5.3207109	Preprocessor1_Model1
4.0606563	train/test split	481	3.5097518	Preprocessor1_Model1
2.7778702	train/test split	482	2.3677704	Preprocessor1_Model1
5.4115764	train/test split	488	5.2627378	Preprocessor1_Model1
4.2377779	train/test split	489	4.2161295	Preprocessor1_Model1
2.7727638	train/test split	491	1.9478134	Preprocessor1_Model1
7.6311416	train/test split	492	7.8330519	Preprocessor1_Model1
6.9257922	train/test split	494	6.8498653	Preprocessor1_Model1
5.5622778	train/test split	501	4.8926683	Preprocessor1_Model1
4.3280101	train/test split	502	4.1459583	Preprocessor1_Model1
5.8300608	train/test split	504	5.7056469	Preprocessor1_Model1
2.7407559	train/test split	521	2.8700818	Preprocessor1_Model1
6.5840867	train/test split	522	6.5834582	Preprocessor1_Model1
3.2274737	train/test split	523	2.8031361	Preprocessor1_Model1
3.0595693	train/test split	527	3.5259476	Preprocessor1_Model1
7.2056132	train/test split	537	6.6945222	Preprocessor1_Model1
4.8723366	train/test split	543	5.1759182	Preprocessor1_Model1
5.6042716	train/test split	544	5.2286334	Preprocessor1_Model1
7.4113592	train/test split	551	6.7382400	Preprocessor1_Model1
7.3427499	train/test split	552	8.1409281	Preprocessor1_Model1
4.6371023	train/test split	559	4.5975932	Preprocessor1_Model1
1.1167718	train/test split	560	1.1297513	Preprocessor1_Model1
4.9709642	train/test split	561	4.5709657	Preprocessor1_Model1
4.2790580	train/test split	563	2.7858012	Preprocessor1_Model1
4.3799662	train/test split	566	4.9241781	Preprocessor1_Model1
5.9401454	train/test split	568	5.8664662	Preprocessor1_Model1
2.5649586	train/test split	569	2.7735562	Preprocessor1_Model1
5.5073714	train/test split	570	5.7493197	Preprocessor1_Model1
4.8509058	train/test split	572	5.5009584	Preprocessor1_Model1
5.1139749	train/test split	574	5.2996095	Preprocessor1_Model1
2.4293453	train/test split	575	2.0649413	Preprocessor1_Model1
6.8816002	train/test split	579	6.5368217	Preprocessor1_Model1
2.8620235	train/test split	580	3.6659901	Preprocessor1_Model1
4.4128630	train/test split	583	4.8054830	Preprocessor1_Model1
1.3371503	train/test split	585	1.2119495	Preprocessor1_Model1
6.1752889	train/test split	587	5.9497474	Preprocessor1_Model1
3.8623333	train/test split	588	4.3200701	Preprocessor1_Model1
6.2969531	train/test split	596	6.8940667	Preprocessor1_Model1
4.6996112	train/test split	598	5.0533907	Preprocessor1_Model1
6.4111707	train/test split	601	6.2389380	Preprocessor1_Model1
6.4070433	train/test split	603	6.5791668	Preprocessor1_Model1
2.4510115	train/test split	605	2.5490218	Preprocessor1_Model1
3.3190561	train/test split	610	2.4465316	Preprocessor1_Model1
4.9344872	train/test split	618	4.8950205	Preprocessor1_Model1
6.6419928	train/test split	619	6.2979205	Preprocessor1_Model1
2.9087421	train/test split	621	2.6889805	Preprocessor1_Model1
2.8819758	train/test split	622	3.6440374	Preprocessor1_Model1
6.7098570	train/test split	623	5.4725669	Preprocessor1_Model1
2.7598275	train/test split	624	3.2060131	Preprocessor1_Model1
6.4501506	train/test split	625	6.5131616	Preprocessor1_Model1
3.5564170	train/test split	626	2.9072698	Preprocessor1_Model1
6.5224083	train/test split	628	5.8672376	Preprocessor1_Model1
7.1790443	train/test split	629	6.8605012	Preprocessor1_Model1
7.9245300	train/test split	630	7.5269298	Preprocessor1_Model1
5.7806381	train/test split	633	5.7051072	Preprocessor1_Model1
4.6072099	train/test split	634	5.0120632	Preprocessor1_Model1
3.8544259	train/test split	635	4.0971454	Preprocessor1_Model1
4.1475236	train/test split	638	3.8220381	Preprocessor1_Model1
3.3618609	train/test split	639	2.3407757	Preprocessor1_Model1
5.4913895	train/test split	646	5.0761760	Preprocessor1_Model1
4.7366199	train/test split	651	5.5467685	Preprocessor1_Model1
1.8064493	train/test split	657	1.8395541	Preprocessor1_Model1
4.9890961	train/test split	661	4.5820340	Preprocessor1_Model1
4.6762783	train/test split	670	4.3270502	Preprocessor1_Model1
5.6195748	train/test split	671	6.0240709	Preprocessor1_Model1
2.3957836	train/test split	674	2.4058534	Preprocessor1_Model1
6.1878869	train/test split	682	5.7225500	Preprocessor1_Model1
4.3948864	train/test split	688	4.1043602	Preprocessor1_Model1
2.6709422	train/test split	690	2.2533319	Preprocessor1_Model1
4.5044774	train/test split	698	5.3272669	Preprocessor1_Model1
6.5951273	train/test split	700	6.0400879	Preprocessor1_Model1
6.5035476	train/test split	702	6.9809290	Preprocessor1_Model1
1.2652120	train/test split	711	1.6165474	Preprocessor1_Model1
2.6792206	train/test split	712	3.0311156	Preprocessor1_Model1
3.1740378	train/test split	713	2.7352374	Preprocessor1_Model1
6.0904903	train/test split	714	6.5676968	Preprocessor1_Model1
4.5966753	train/test split	725	3.9668657	Preprocessor1_Model1
4.9750965	train/test split	727	4.2452741	Preprocessor1_Model1
3.9409506	train/test split	728	3.5383189	Preprocessor1_Model1
5.3544811	train/test split	729	5.4787174	Preprocessor1_Model1
6.0882798	train/test split	734	6.7431691	Preprocessor1_Model1
7.5137169	train/test split	736	7.5336646	Preprocessor1_Model1
5.2007207	train/test split	740	5.2233386	Preprocessor1_Model1
2.7916051	train/test split	742	1.7462741	Preprocessor1_Model1
7.7356392	train/test split	744	8.3862962	Preprocessor1_Model1
5.3753745	train/test split	748	5.5289727	Preprocessor1_Model1
4.7979513	train/test split	750	5.0013762	Preprocessor1_Model1
5.7159317	train/test split	755	5.7564766	Preprocessor1_Model1
2.8082439	train/test split	762	2.3954561	Preprocessor1_Model1
4.8267068	train/test split	763	3.9463858	Preprocessor1_Model1
3.4629509	train/test split	765	3.2942095	Preprocessor1_Model1
3.7241323	train/test split	766	3.5469961	Preprocessor1_Model1
6.6221296	train/test split	767	6.1377587	Preprocessor1_Model1
2.3158103	train/test split	770	1.6465621	Preprocessor1_Model1
5.0002468	train/test split	773	4.5090377	Preprocessor1_Model1
4.7841390	train/test split	774	5.2599878	Preprocessor1_Model1
4.1434929	train/test split	777	3.8120994	Preprocessor1_Model1
6.0047621	train/test split	778	5.7679181	Preprocessor1_Model1
3.0748156	train/test split	785	3.7764382	Preprocessor1_Model1
4.5183685	train/test split	787	4.5924021	Preprocessor1_Model1
3.0888236	train/test split	788	3.1356607	Preprocessor1_Model1
4.6689192	train/test split	789	4.0078991	Preprocessor1_Model1
4.2294366	train/test split	790	3.9235714	Preprocessor1_Model1
2.7955441	train/test split	800	2.9113098	Preprocessor1_Model1
4.1812292	train/test split	811	4.1279959	Preprocessor1_Model1
5.4830696	train/test split	815	5.4430589	Preprocessor1_Model1
7.1851624	train/test split	817	6.4976319	Preprocessor1_Model1
1.5170701	train/test split	819	1.4612952	Preprocessor1_Model1
2.3858318	train/test split	822	2.6184187	Preprocessor1_Model1
4.5725284	train/test split	823	4.4502410	Preprocessor1_Model1
4.6139047	train/test split	825	5.0028171	Preprocessor1_Model1
4.8202173	train/test split	826	4.4765749	Preprocessor1_Model1
2.7187719	train/test split	827	2.3665216	Preprocessor1_Model1
2.5201850	train/test split	837	3.0659051	Preprocessor1_Model1
4.2469051	train/test split	845	4.5936490	Preprocessor1_Model1
5.5931893	train/test split	846	4.8871753	Preprocessor1_Model1
5.6558486	train/test split	847	5.3403292	Preprocessor1_Model1
4.1250807	train/test split	853	3.8067297	Preprocessor1_Model1
5.5047377	train/test split	861	5.6065687	Preprocessor1_Model1
4.3101854	train/test split	864	4.2338495	Preprocessor1_Model1
4.2533163	train/test split	865	3.6899145	Preprocessor1_Model1
6.5298274	train/test split	866	5.7908440	Preprocessor1_Model1
4.4976878	train/test split	867	5.4414915	Preprocessor1_Model1
4.3277330	train/test split	869	4.4084285	Preprocessor1_Model1
5.7364426	train/test split	876	6.3256689	Preprocessor1_Model1
3.5679932	train/test split	877	3.1399825	Preprocessor1_Model1
3.5384292	train/test split	881	4.0836455	Preprocessor1_Model1
5.0629000	train/test split	883	4.7984831	Preprocessor1_Model1
4.4704597	train/test split	884	4.7818132	Preprocessor1_Model1
1.7167088	train/test split	886	0.9772871	Preprocessor1_Model1
5.7506277	train/test split	887	5.7727492	Preprocessor1_Model1
4.5933583	train/test split	888	4.2776301	Preprocessor1_Model1
2.9957340	train/test split	889	3.3892994	Preprocessor1_Model1
5.0032073	train/test split	890	4.2808841	Preprocessor1_Model1
5.2081934	train/test split	891	5.2263150	Preprocessor1_Model1
4.8024236	train/test split	898	5.3695306	Preprocessor1_Model1
3.9713776	train/test split	899	3.3617204	Preprocessor1_Model1
5.6982414	train/test split	902	6.1775464	Preprocessor1_Model1
3.7125963	train/test split	906	3.3463267	Preprocessor1_Model1
4.8810150	train/test split	908	5.5517442	Preprocessor1_Model1
1.2695782	train/test split	919	1.3936892	Preprocessor1_Model1
2.6181137	train/test split	921	2.5513613	Preprocessor1_Model1
4.4178492	train/test split	924	3.6692884	Preprocessor1_Model1
3.9501374	train/test split	925	3.2618521	Preprocessor1_Model1
7.0451417	train/test split	927	7.6078213	Preprocessor1_Model1
4.8680195	train/test split	929	4.3529869	Preprocessor1_Model1
2.5979435	train/test split	931	2.7149104	Preprocessor1_Model1
3.2705150	train/test split	933	3.7996882	Preprocessor1_Model1
1.2186695	train/test split	935	0.9795276	Preprocessor1_Model1
7.2775940	train/test split	937	6.7459460	Preprocessor1_Model1
2.3199218	train/test split	941	2.0598001	Preprocessor1_Model1
2.7290650	train/test split	943	2.1148080	Preprocessor1_Model1
6.6596016	train/test split	945	6.3480510	Preprocessor1_Model1
3.4249809	train/test split	947	2.9242694	Preprocessor1_Model1
6.2442313	train/test split	955	4.7391200	Preprocessor1_Model1
6.4834678	train/test split	956	6.2197066	Preprocessor1_Model1
4.5779156	train/test split	957	4.9330815	Preprocessor1_Model1
5.0238564	train/test split	966	4.4433924	Preprocessor1_Model1
8.0587986	train/test split	967	7.0992344	Preprocessor1_Model1
4.6534793	train/test split	968	3.6213426	Preprocessor1_Model1
4.0459045	train/test split	969	4.2089005	Preprocessor1_Model1
2.8514973	train/test split	970	2.4368372	Preprocessor1_Model1
2.6890094	train/test split	973	2.4019745	Preprocessor1_Model1
4.5080739	train/test split	975	4.7845012	Preprocessor1_Model1
6.5450507	train/test split	984	6.7632246	Preprocessor1_Model1
7.0335667	train/test split	986	6.2795928	Preprocessor1_Model1
6.3866636	train/test split	989	6.6537450	Preprocessor1_Model1
4.7018316	train/test split	991	4.8943184	Preprocessor1_Model1
3.3761705	train/test split	992	3.7670797	Preprocessor1_Model1
6.9206382	train/test split	994	7.2939924	Preprocessor1_Model1
2.4549576	train/test split	997	2.1736186	Preprocessor1_Model1
3.5543198	train/test split	999	3.4993218	Preprocessor1_Model1
4.4292498	train/test split	1000	4.2690711	Preprocessor1_Model1
5.5311610	train/test split	1002	5.6719529	Preprocessor1_Model1
4.7460796	train/test split	1004	4.1916027	Preprocessor1_Model1
5.1383010	train/test split	1007	6.1242725	Preprocessor1_Model1
4.7935311	train/test split	1008	5.0953440	Preprocessor1_Model1
3.0775379	train/test split	1009	3.0651815	Preprocessor1_Model1
3.7105129	train/test split	1010	3.3445250	Preprocessor1_Model1
5.7962705	train/test split	1015	5.6470525	Preprocessor1_Model1
5.0621926	train/test split	1020	4.0925511	Preprocessor1_Model1
5.3737436	train/test split	1025	4.9531711	Preprocessor1_Model1
5.4861865	train/test split	1028	5.0195550	Preprocessor1_Model1
6.1760617	train/test split	1029	6.6423880	Preprocessor1_Model1
6.1426523	train/test split	1030	7.0956302	Preprocessor1_Model1
3.9558042	train/test split	1031	4.8141253	Preprocessor1_Model1
4.8117741	train/test split	1033	4.5538862	Preprocessor1_Model1
4.5613702	train/test split	1036	5.1149749	Preprocessor1_Model1
4.1190987	train/test split	1040	3.5881248	Preprocessor1_Model1
1.8795459	train/test split	1042	1.2838171	Preprocessor1_Model1
5.7485888	train/test split	1043	5.7415194	Preprocessor1_Model1
1.1940806	train/test split	1048	0.8460361	Preprocessor1_Model1
5.8157660	train/test split	1049	6.0499043	Preprocessor1_Model1
4.5645257	train/test split	1053	4.9332310	Preprocessor1_Model1
5.4404293	train/test split	1057	6.0228008	Preprocessor1_Model1
3.6103247	train/test split	1071	3.2399776	Preprocessor1_Model1
6.0928961	train/test split	1073	6.3349206	Preprocessor1_Model1
6.7083856	train/test split	1075	8.3435655	Preprocessor1_Model1
2.5137321	train/test split	1076	1.3198992	Preprocessor1_Model1
4.4116024	train/test split	1079	4.1133011	Preprocessor1_Model1
5.9729364	train/test split	1080	5.9318623	Preprocessor1_Model1
4.2956789	train/test split	1086	4.7617254	Preprocessor1_Model1
4.5144606	train/test split	1089	3.9091135	Preprocessor1_Model1
6.2210613	train/test split	1095	5.5276296	Preprocessor1_Model1
5.4726111	train/test split	1097	5.4705623	Preprocessor1_Model1
4.9807411	train/test split	1107	4.0786455	Preprocessor1_Model1
4.5940750	train/test split	1113	4.4133014	Preprocessor1_Model1
1.7029833	train/test split	1119	1.3517011	Preprocessor1_Model1
2.7770347	train/test split	1126	3.1235018	Preprocessor1_Model1
7.3487825	train/test split	1127	7.7880874	Preprocessor1_Model1
4.1209185	train/test split	1131	5.0111238	Preprocessor1_Model1
3.5057831	train/test split	1133	3.2855193	Preprocessor1_Model1
3.6278526	train/test split	1138	4.2347399	Preprocessor1_Model1
6.0816549	train/test split	1140	6.8597710	Preprocessor1_Model1
7.6527998	train/test split	1144	8.3900262	Preprocessor1_Model1
1.1581657	train/test split	1148	1.5277010	Preprocessor1_Model1
2.1494688	train/test split	1151	0.8788206	Preprocessor1_Model1
5.4917774	train/test split	1155	5.4072648	Preprocessor1_Model1
4.1222815	train/test split	1156	3.5492884	Preprocessor1_Model1
3.0098141	train/test split	1159	4.0445614	Preprocessor1_Model1
6.0645841	train/test split	1161	5.9846549	Preprocessor1_Model1
4.1601881	train/test split	1165	3.9756401	Preprocessor1_Model1
7.6240494	train/test split	1166	7.0187167	Preprocessor1_Model1
5.8920112	train/test split	1168	6.1870133	Preprocessor1_Model1
4.4729944	train/test split	1176	5.2288616	Preprocessor1_Model1
6.9740172	train/test split	1190	6.1087332	Preprocessor1_Model1
1.8974795	train/test split	1191	2.8058186	Preprocessor1_Model1
2.4063910	train/test split	1192	1.9235869	Preprocessor1_Model1
5.4734188	train/test split	1193	5.6305272	Preprocessor1_Model1
5.7067479	train/test split	1195	5.6350943	Preprocessor1_Model1
4.3985542	train/test split	1198	4.7904612	Preprocessor1_Model1
6.6888111	train/test split	1207	6.5747006	Preprocessor1_Model1
3.0937847	train/test split	1211	3.2129271	Preprocessor1_Model1
6.3766008	train/test split	1215	7.0920465	Preprocessor1_Model1
3.8985188	train/test split	1216	3.3136976	Preprocessor1_Model1
5.6630955	train/test split	1217	5.2124544	Preprocessor1_Model1
5.4850483	train/test split	1221	5.7612030	Preprocessor1_Model1
6.9841915	train/test split	1223	7.0175166	Preprocessor1_Model1
4.8449372	train/test split	1224	4.8261333	Preprocessor1_Model1
3.9109045	train/test split	1227	3.9219403	Preprocessor1_Model1
3.5721860	train/test split	1233	3.7874033	Preprocessor1_Model1
4.2241099	train/test split	1234	4.3068655	Preprocessor1_Model1
4.5096508	train/test split	1238	3.6899924	Preprocessor1_Model1
5.5396166	train/test split	1239	4.7950384	Preprocessor1_Model1
5.5912394	train/test split	1240	6.0423176	Preprocessor1_Model1
3.1666899	train/test split	1242	2.9722814	Preprocessor1_Model1
5.4862296	train/test split	1248	5.5743709	Preprocessor1_Model1
4.0472183	train/test split	1250	3.8950607	Preprocessor1_Model1
4.8127261	train/test split	1252	4.3806050	Preprocessor1_Model1
4.0840289	train/test split	1257	4.3116597	Preprocessor1_Model1
5.9842757	train/test split	1258	6.5173522	Preprocessor1_Model1
6.9715319	train/test split	1259	6.5687002	Preprocessor1_Model1
5.1430126	train/test split	1261	4.3638511	Preprocessor1_Model1
5.8681693	train/test split	1262	5.8855858	Preprocessor1_Model1
3.5845277	train/test split	1263	3.5273644	Preprocessor1_Model1
3.5290011	train/test split	1264	3.9370319	Preprocessor1_Model1
6.5520365	train/test split	1266	6.9022258	Preprocessor1_Model1
6.1161428	train/test split	1270	5.9176668	Preprocessor1_Model1
2.3411857	train/test split	1271	3.0732647	Preprocessor1_Model1
4.3268359	train/test split	1272	4.3467312	Preprocessor1_Model1
7.5272222	train/test split	1274	7.3420225	Preprocessor1_Model1
4.0404903	train/test split	1276	4.4724170	Preprocessor1_Model1
4.1561847	train/test split	1280	4.0274414	Preprocessor1_Model1
3.2289783	train/test split	1281	3.5222301	Preprocessor1_Model1
1.8283264	train/test split	1282	1.4390950	Preprocessor1_Model1
4.5815250	train/test split	1293	5.2877730	Preprocessor1_Model1
5.4708639	train/test split	1295	5.3103202	Preprocessor1_Model1
4.7042037	train/test split	1300	5.6020606	Preprocessor1_Model1
6.8945885	train/test split	1302	6.8504749	Preprocessor1_Model1
3.2051472	train/test split	1304	3.5899634	Preprocessor1_Model1
1.6407883	train/test split	1308	2.8920887	Preprocessor1_Model1
7.3251018	train/test split	1309	7.5668601	Preprocessor1_Model1
7.1374707	train/test split	1310	7.2762496	Preprocessor1_Model1
6.0918167	train/test split	1312	6.5104388	Preprocessor1_Model1
4.5237670	train/test split	1318	5.8195480	Preprocessor1_Model1
4.1831630	train/test split	1319	4.0880753	Preprocessor1_Model1
3.8321332	train/test split	1322	4.8720853	Preprocessor1_Model1
2.2203971	train/test split	1325	1.4444573	Preprocessor1_Model1
7.8682592	train/test split	1328	7.9318720	Preprocessor1_Model1
1.4811358	train/test split	1331	1.0263812	Preprocessor1_Model1
5.1126461	train/test split	1333	5.0046162	Preprocessor1_Model1
3.3296405	train/test split	1334	3.0495375	Preprocessor1_Model1
4.3542714	train/test split	1337	5.0466663	Preprocessor1_Model1
2.5137912	train/test split	1339	3.2018218	Preprocessor1_Model1
4.4361172	train/test split	1342	4.7927471	Preprocessor1_Model1
3.1572426	train/test split	1343	3.2955867	Preprocessor1_Model1
3.8284983	train/test split	1344	4.0618828	Preprocessor1_Model1
2.1902843	train/test split	1346	2.5864392	Preprocessor1_Model1
3.0126684	train/test split	1347	3.4075795	Preprocessor1_Model1
7.6068780	train/test split	1348	7.2981753	Preprocessor1_Model1
5.2262378	train/test split	1351	5.4838466	Preprocessor1_Model1
3.5020894	train/test split	1352	3.3116674	Preprocessor1_Model1
6.1571600	train/test split	1355	6.8855888	Preprocessor1_Model1
3.8595229	train/test split	1358	3.6000836	Preprocessor1_Model1
3.2770117	train/test split	1361	3.0011973	Preprocessor1_Model1
5.9378863	train/test split	1363	5.5388780	Preprocessor1_Model1
2.6864603	train/test split	1367	2.7653171	Preprocessor1_Model1
4.9210333	train/test split	1368	5.0496333	Preprocessor1_Model1
5.0924695	train/test split	1374	5.1151574	Preprocessor1_Model1
5.5436138	train/test split	1375	5.9578745	Preprocessor1_Model1
6.3799105	train/test split	1376	5.6096945	Preprocessor1_Model1
6.7378580	train/test split	1381	6.4147385	Preprocessor1_Model1
3.4422579	train/test split	1386	2.9529319	Preprocessor1_Model1
3.0727206	train/test split	1387	3.6490325	Preprocessor1_Model1
4.1451798	train/test split	1388	3.6715995	Preprocessor1_Model1
2.6123651	train/test split	1396	2.9957719	Preprocessor1_Model1
4.0056683	train/test split	1402	4.4130135	Preprocessor1_Model1
5.8369210	train/test split	1403	6.3945393	Preprocessor1_Model1
6.8370429	train/test split	1404	7.7126278	Preprocessor1_Model1
4.9773437	train/test split	1405	4.2289698	Preprocessor1_Model1
1.8634746	train/test split	1409	2.3576552	Preprocessor1_Model1
2.7029283	train/test split	1413	2.9772135	Preprocessor1_Model1
1.2260438	train/test split	1415	0.9455504	Preprocessor1_Model1
6.5422693	train/test split	1419	6.7273217	Preprocessor1_Model1
6.3581396	train/test split	1422	6.0425269	Preprocessor1_Model1
4.0496852	train/test split	1424	4.2485258	Preprocessor1_Model1
5.5506478	train/test split	1427	5.3118323	Preprocessor1_Model1
3.6689928	train/test split	1428	2.8399040	Preprocessor1_Model1
4.9496329	train/test split	1433	5.5995083	Preprocessor1_Model1
3.3292983	train/test split	1435	3.9951160	Preprocessor1_Model1
6.0189655	train/test split	1438	6.3094798	Preprocessor1_Model1
6.5197853	train/test split	1440	5.8586563	Preprocessor1_Model1
5.4866175	train/test split	1444	5.8243748	Preprocessor1_Model1
6.1554232	train/test split	1448	6.5106816	Preprocessor1_Model1
5.9805115	train/test split	1451	5.4357386	Preprocessor1_Model1
2.7568331	train/test split	1453	2.9017019	Preprocessor1_Model1
7.6717765	train/test split	1455	8.0064630	Preprocessor1_Model1
6.3743278	train/test split	1458	6.4111720	Preprocessor1_Model1
2.6290614	train/test split	1460	1.9058707	Preprocessor1_Model1
5.8128089	train/test split	1470	6.1146801	Preprocessor1_Model1
3.6895680	train/test split	1472	4.3988590	Preprocessor1_Model1
7.0959546	train/test split	1474	8.0082428	Preprocessor1_Model1
4.0324486	train/test split	1475	4.4885673	Preprocessor1_Model1
2.2516420	train/test split	1480	1.9323845	Preprocessor1_Model1
4.5813205	train/test split	1482	4.2342810	Preprocessor1_Model1
4.5648282	train/test split	1483	3.7855844	Preprocessor1_Model1
7.3149610	train/test split	1486	7.7386215	Preprocessor1_Model1
4.9597262	train/test split	1490	5.4137675	Preprocessor1_Model1
2.9454381	train/test split	1492	3.2070221	Preprocessor1_Model1
3.9116408	train/test split	1497	3.9696297	Preprocessor1_Model1
6.0511768	train/test split	1498	6.4002352	Preprocessor1_Model1
0.8781412	train/test split	1501	0.9296281	Preprocessor1_Model1
3.2439701	train/test split	1503	2.9939645	Preprocessor1_Model1
6.1298259	train/test split	1505	6.3777329	Preprocessor1_Model1
3.8849915	train/test split	1507	3.3098189	Preprocessor1_Model1
4.6120939	train/test split	1511	4.6116652	Preprocessor1_Model1
6.4696203	train/test split	1513	6.2836536	Preprocessor1_Model1
3.5666650	train/test split	1514	3.2975365	Preprocessor1_Model1
5.4022562	train/test split	1517	4.9748216	Preprocessor1_Model1
4.5893187	train/test split	1524	4.5882721	Preprocessor1_Model1
5.4592412	train/test split	1527	6.3207851	Preprocessor1_Model1
4.2675211	train/test split	1529	4.1761135	Preprocessor1_Model1
8.0519051	train/test split	1532	7.7786533	Preprocessor1_Model1
6.3262950	train/test split	1538	5.9269580	Preprocessor1_Model1
6.6694400	train/test split	1547	5.8758599	Preprocessor1_Model1
4.9519670	train/test split	1548	4.4413933	Preprocessor1_Model1
2.2164159	train/test split	1549	2.2015375	Preprocessor1_Model1
6.9164657	train/test split	1550	7.1777302	Preprocessor1_Model1
2.1483205	train/test split	1553	1.6950091	Preprocessor1_Model1
7.0940228	train/test split	1561	7.4329231	Preprocessor1_Model1
3.6242537	train/test split	1564	3.9992213	Preprocessor1_Model1
2.4205481	train/test split	1566	2.2960546	Preprocessor1_Model1
3.3378210	train/test split	1570	3.5311024	Preprocessor1_Model1
6.8065302	train/test split	1572	7.2467737	Preprocessor1_Model1
2.6668532	train/test split	1579	3.3432183	Preprocessor1_Model1
6.9249191	train/test split	1588	6.5758472	Preprocessor1_Model1
4.5140463	train/test split	1589	4.2390172	Preprocessor1_Model1
2.6135264	train/test split	1598	1.4540275	Preprocessor1_Model1
4.2908599	train/test split	1606	5.4197017	Preprocessor1_Model1
4.4294339	train/test split	1607	4.7722143	Preprocessor1_Model1
1.7959757	train/test split	1622	2.3741029	Preprocessor1_Model1
4.8967323	train/test split	1627	4.4614582	Preprocessor1_Model1
6.6712793	train/test split	1633	6.5199435	Preprocessor1_Model1
6.8093930	train/test split	1638	6.5748824	Preprocessor1_Model1
5.3699622	train/test split	1641	4.7496760	Preprocessor1_Model1
3.5961163	train/test split	1642	2.9390501	Preprocessor1_Model1
5.1657638	train/test split	1644	5.9258866	Preprocessor1_Model1
5.9994002	train/test split	1654	6.2994831	Preprocessor1_Model1
2.3328989	train/test split	1659	2.5823093	Preprocessor1_Model1
4.3140816	train/test split	1669	4.2180190	Preprocessor1_Model1
5.3169888	train/test split	1674	5.6430836	Preprocessor1_Model1
3.8823721	train/test split	1675	3.9267266	Preprocessor1_Model1
1.3368731	train/test split	1678	1.8138060	Preprocessor1_Model1
4.1210332	train/test split	1681	4.4724448	Preprocessor1_Model1
3.8122862	train/test split	1683	3.9522603	Preprocessor1_Model1
4.1590273	train/test split	1690	4.3993544	Preprocessor1_Model1
5.2638828	train/test split	1695	6.0488033	Preprocessor1_Model1
8.0209598	train/test split	1696	7.3193047	Preprocessor1_Model1
2.0252078	train/test split	1698	1.8525113	Preprocessor1_Model1
6.2574354	train/test split	1703	6.4667771	Preprocessor1_Model1
6.7726924	train/test split	1706	7.1047813	Preprocessor1_Model1
2.4782085	train/test split	1713	1.8846272	Preprocessor1_Model1
2.0480359	train/test split	1716	1.4433604	Preprocessor1_Model1
4.5255550	train/test split	1720	4.0908767	Preprocessor1_Model1
2.5969829	train/test split	1721	2.2522601	Preprocessor1_Model1
4.7897206	train/test split	1726	5.5759893	Preprocessor1_Model1
3.0477209	train/test split	1727	3.8822615	Preprocessor1_Model1
4.0054193	train/test split	1732	3.5810260	Preprocessor1_Model1
2.3116175	train/test split	1733	2.2503471	Preprocessor1_Model1
4.3296121	train/test split	1737	4.4909965	Preprocessor1_Model1
5.8019032	train/test split	1741	5.8458476	Preprocessor1_Model1
5.2814628	train/test split	1743	5.5530436	Preprocessor1_Model1
3.0656733	train/test split	1744	2.9050427	Preprocessor1_Model1
6.8956119	train/test split	1745	6.4068937	Preprocessor1_Model1
6.2809455	train/test split	1752	6.7055130	Preprocessor1_Model1
4.3023904	train/test split	1756	3.6416337	Preprocessor1_Model1
5.5786014	train/test split	1757	5.4610054	Preprocessor1_Model1
5.9496324	train/test split	1760	5.5388786	Preprocessor1_Model1
2.4325727	train/test split	1764	2.2871704	Preprocessor1_Model1
3.2345598	train/test split	1766	3.3513429	Preprocessor1_Model1
4.7352938	train/test split	1768	4.8772228	Preprocessor1_Model1
3.1414639	train/test split	1773	3.3076738	Preprocessor1_Model1
7.3043269	train/test split	1784	6.1759717	Preprocessor1_Model1
6.0074658	train/test split	1789	5.3278579	Preprocessor1_Model1
2.5447550	train/test split	1799	2.1832737	Preprocessor1_Model1
4.4265992	train/test split	1804	4.0205532	Preprocessor1_Model1
4.8784904	train/test split	1809	4.3225948	Preprocessor1_Model1
7.2216273	train/test split	1811	7.5050141	Preprocessor1_Model1
3.6609080	train/test split	1812	3.8834565	Preprocessor1_Model1
4.1024349	train/test split	1816	3.7068998	Preprocessor1_Model1
3.8643961	train/test split	1827	4.2191721	Preprocessor1_Model1
4.2889603	train/test split	1828	4.7403852	Preprocessor1_Model1
5.3839307	train/test split	1831	5.4611426	Preprocessor1_Model1
3.8166597	train/test split	1842	3.7455416	Preprocessor1_Model1
5.6717979	train/test split	1846	5.4738770	Preprocessor1_Model1
3.6046426	train/test split	1848	3.0469588	Preprocessor1_Model1
4.1796260	train/test split	1857	3.6610268	Preprocessor1_Model1
4.1646752	train/test split	1858	4.3575710	Preprocessor1_Model1
4.6529721	train/test split	1860	4.8850697	Preprocessor1_Model1
7.8023439	train/test split	1861	8.3929078	Preprocessor1_Model1
4.0871531	train/test split	1862	4.1684639	Preprocessor1_Model1
6.3509075	train/test split	1864	6.8759351	Preprocessor1_Model1
4.9485693	train/test split	1869	4.3062260	Preprocessor1_Model1
6.8223960	train/test split	1871	6.9366760	Preprocessor1_Model1
5.4460690	train/test split	1872	5.1326031	Preprocessor1_Model1
6.9443418	train/test split	1875	7.7637012	Preprocessor1_Model1
6.0217755	train/test split	1876	6.1833757	Preprocessor1_Model1
4.4289777	train/test split	1880	3.6395083	Preprocessor1_Model1
7.4198014	train/test split	1882	7.0406727	Preprocessor1_Model1
6.9395924	train/test split	1885	7.1216582	Preprocessor1_Model1
3.8681763	train/test split	1889	4.5045995	Preprocessor1_Model1
4.4361738	train/test split	1892	4.3670261	Preprocessor1_Model1
5.2324035	train/test split	1893	4.8159364	Preprocessor1_Model1
5.8128352	train/test split	1900	5.0026660	Preprocessor1_Model1
5.0861786	train/test split	1901	6.0983433	Preprocessor1_Model1
3.5595939	train/test split	1902	3.2826512	Preprocessor1_Model1
3.3194689	train/test split	1908	3.5595496	Preprocessor1_Model1
4.0858215	train/test split	1910	3.6046850	Preprocessor1_Model1
8.1746116	train/test split	1911	8.3097097	Preprocessor1_Model1
2.9536787	train/test split	1913	2.7977082	Preprocessor1_Model1
4.9353428	train/test split	1918	3.8705440	Preprocessor1_Model1
5.6666529	train/test split	1922	5.7653396	Preprocessor1_Model1
3.6526650	train/test split	1923	4.0364922	Preprocessor1_Model1
2.7520893	train/test split	1929	2.3790286	Preprocessor1_Model1
2.0952060	train/test split	1931	2.6765036	Preprocessor1_Model1
4.9823322	train/test split	1938	5.1676877	Preprocessor1_Model1
3.2334720	train/test split	1942	3.7003209	Preprocessor1_Model1
4.5798074	train/test split	1947	4.1702903	Preprocessor1_Model1
3.9951602	train/test split	1948	4.0656372	Preprocessor1_Model1
2.7475188	train/test split	1950	2.5778809	Preprocessor1_Model1
3.3090963	train/test split	1951	2.9438519	Preprocessor1_Model1
7.0117806	train/test split	1958	6.7005573	Preprocessor1_Model1
6.8417839	train/test split	1959	7.8843285	Preprocessor1_Model1
5.6061919	train/test split	1972	4.8182114	Preprocessor1_Model1
3.6637228	train/test split	1977	4.1273255	Preprocessor1_Model1
5.3803338	train/test split	1980	5.4376363	Preprocessor1_Model1
5.2480358	train/test split	1983	4.9280200	Preprocessor1_Model1
3.4122023	train/test split	1987	3.9382601	Preprocessor1_Model1
4.3441093	train/test split	1988	5.2461895	Preprocessor1_Model1
1.7535596	train/test split	1989	1.3818721	Preprocessor1_Model1
5.6537927	train/test split	1990	5.3197982	Preprocessor1_Model1
3.4962502	train/test split	1993	3.7109824	Preprocessor1_Model1
2.6133428	train/test split	1999	2.7405951	Preprocessor1_Model1
3.5828298	train/test split	2003	3.5077018	Preprocessor1_Model1
5.3070152	train/test split	2006	4.9199507	Preprocessor1_Model1
2.9358570	train/test split	2011	4.0130787	Preprocessor1_Model1
7.4557054	train/test split	2012	7.8839075	Preprocessor1_Model1
2.4814339	train/test split	2013	2.7268428	Preprocessor1_Model1
3.0459458	train/test split	2016	2.2776628	Preprocessor1_Model1
1.5396812	train/test split	2020	1.0628858	Preprocessor1_Model1
3.9020246	train/test split	2021	4.2001627	Preprocessor1_Model1
6.5263939	train/test split	2024	5.9085100	Preprocessor1_Model1
6.3353576	train/test split	2029	7.0904559	Preprocessor1_Model1
2.0182109	train/test split	2030	2.6556782	Preprocessor1_Model1
2.7668630	train/test split	2034	3.1538203	Preprocessor1_Model1
2.7222417	train/test split	2038	2.3441173	Preprocessor1_Model1
4.9241195	train/test split	2043	4.5093715	Preprocessor1_Model1
6.1976622	train/test split	2052	5.6284849	Preprocessor1_Model1
6.0566191	train/test split	2056	6.2293798	Preprocessor1_Model1
6.4615589	train/test split	2058	7.2387758	Preprocessor1_Model1
6.4841810	train/test split	2059	6.7082595	Preprocessor1_Model1
2.6996399	train/test split	2060	2.9771475	Preprocessor1_Model1
5.4496981	train/test split	2065	5.3082974	Preprocessor1_Model1
4.7498664	train/test split	2067	4.7357904	Preprocessor1_Model1
6.2002696	train/test split	2071	6.2946918	Preprocessor1_Model1
3.2048652	train/test split	2074	3.6829797	Preprocessor1_Model1
6.2325366	train/test split	2078	6.0148271	Preprocessor1_Model1
4.7819455	train/test split	2081	5.2678974	Preprocessor1_Model1
2.4797807	train/test split	2082	2.4869641	Preprocessor1_Model1
2.4064210	train/test split	2086	2.5083575	Preprocessor1_Model1
5.8181698	train/test split	2090	5.9680574	Preprocessor1_Model1
2.2473842	train/test split	2096	1.7532148	Preprocessor1_Model1
6.1290104	train/test split	2104	5.6473506	Preprocessor1_Model1
2.5298897	train/test split	2109	1.5056802	Preprocessor1_Model1
3.7397187	train/test split	2111	3.2485037	Preprocessor1_Model1
5.1744831	train/test split	2113	6.0386235	Preprocessor1_Model1
3.4043751	train/test split	2115	3.5466733	Preprocessor1_Model1
7.8422581	train/test split	2116	8.2626472	Preprocessor1_Model1
5.2860504	train/test split	2117	5.8083499	Preprocessor1_Model1
5.1906612	train/test split	2118	5.1135987	Preprocessor1_Model1
6.1116383	train/test split	2131	6.3016650	Preprocessor1_Model1
5.0252632	train/test split	2132	5.1357557	Preprocessor1_Model1
4.1135766	train/test split	2135	4.6352538	Preprocessor1_Model1
4.9558508	train/test split	2137	4.6851068	Preprocessor1_Model1
4.0842820	train/test split	2140	3.4134135	Preprocessor1_Model1
5.1457236	train/test split	2142	4.9906056	Preprocessor1_Model1
4.1705193	train/test split	2143	4.9382043	Preprocessor1_Model1
3.1783324	train/test split	2144	3.8997028	Preprocessor1_Model1
3.3353083	train/test split	2147	2.8859582	Preprocessor1_Model1
6.6429035	train/test split	2154	6.5842972	Preprocessor1_Model1
6.6477605	train/test split	2162	6.4708603	Preprocessor1_Model1
1.7573509	train/test split	2165	1.8362612	Preprocessor1_Model1
5.6145338	train/test split	2167	5.4690729	Preprocessor1_Model1
4.7378302	train/test split	2170	4.6014699	Preprocessor1_Model1
4.9463672	train/test split	2182	4.4977592	Preprocessor1_Model1
5.3215088	train/test split	2183	4.2727872	Preprocessor1_Model1
3.5134953	train/test split	2185	3.8423091	Preprocessor1_Model1
6.7749400	train/test split	2188	6.6957072	Preprocessor1_Model1
4.4068234	train/test split	2194	5.1073079	Preprocessor1_Model1
5.9227253	train/test split	2198	5.9558794	Preprocessor1_Model1
6.4614561	train/test split	2206	6.7285063	Preprocessor1_Model1
5.6609427	train/test split	2207	5.3085166	Preprocessor1_Model1
3.9357698	train/test split	2209	3.4487406	Preprocessor1_Model1
3.6267399	train/test split	2210	3.5685144	Preprocessor1_Model1
2.6931180	train/test split	2212	3.1118853	Preprocessor1_Model1
6.4787335	train/test split	2214	6.6557963	Preprocessor1_Model1
6.3312306	train/test split	2215	7.0734404	Preprocessor1_Model1
4.9200445	train/test split	2217	5.5312144	Preprocessor1_Model1
6.5916568	train/test split	2218	5.9769508	Preprocessor1_Model1
3.6656796	train/test split	2220	4.1917855	Preprocessor1_Model1
6.8369701	train/test split	2223	7.4981137	Preprocessor1_Model1
3.5978712	train/test split	2224	3.3070873	Preprocessor1_Model1
4.9589236	train/test split	2228	4.8299205	Preprocessor1_Model1
4.6296262	train/test split	2232	4.9493450	Preprocessor1_Model1
1.8726198	train/test split	2236	2.3879961	Preprocessor1_Model1
2.3029316	train/test split	2241	1.8899735	Preprocessor1_Model1
6.7253205	train/test split	2242	6.4690948	Preprocessor1_Model1
4.5236370	train/test split	2246	4.1044813	Preprocessor1_Model1
3.0321379	train/test split	2253	2.8502622	Preprocessor1_Model1
6.1092093	train/test split	2262	6.2374078	Preprocessor1_Model1
3.7276774	train/test split	2270	3.2740113	Preprocessor1_Model1
4.2920873	train/test split	2278	4.6802263	Preprocessor1_Model1
7.4085000	train/test split	2279	7.5380730	Preprocessor1_Model1
7.5065098	train/test split	2280	7.7598312	Preprocessor1_Model1
3.6988369	train/test split	2287	3.7788914	Preprocessor1_Model1
3.2812787	train/test split	2290	3.8551377	Preprocessor1_Model1
5.0180914	train/test split	2293	5.2314084	Preprocessor1_Model1
5.5729481	train/test split	2295	5.5189709	Preprocessor1_Model1
4.5033729	train/test split	2296	4.5923321	Preprocessor1_Model1
2.6792019	train/test split	2298	3.3077839	Preprocessor1_Model1
3.3446158	train/test split	2303	3.0217493	Preprocessor1_Model1
6.7910342	train/test split	2306	7.4436359	Preprocessor1_Model1
8.2231612	train/test split	2309	7.8846307	Preprocessor1_Model1
6.8147867	train/test split	2310	7.2087123	Preprocessor1_Model1
6.0668911	train/test split	2311	6.3930091	Preprocessor1_Model1
5.4165338	train/test split	2313	6.0728524	Preprocessor1_Model1
5.4444934	train/test split	2320	6.6682755	Preprocessor1_Model1
2.3537587	train/test split	2321	1.9215502	Preprocessor1_Model1
5.4871180	train/test split	2326	5.1858219	Preprocessor1_Model1
2.4741999	train/test split	2328	2.1284549	Preprocessor1_Model1
6.2716843	train/test split	2329	6.3195971	Preprocessor1_Model1
7.8165627	train/test split	2331	7.8077230	Preprocessor1_Model1
2.7903466	train/test split	2332	2.8187198	Preprocessor1_Model1
3.7942509	train/test split	2338	3.6953698	Preprocessor1_Model1
3.3404161	train/test split	2341	3.5394638	Preprocessor1_Model1
1.6620794	train/test split	2343	2.4689217	Preprocessor1_Model1
3.7134649	train/test split	2344	3.9414051	Preprocessor1_Model1
4.0880768	train/test split	2353	4.6680679	Preprocessor1_Model1
5.8029815	train/test split	2356	6.7453526	Preprocessor1_Model1
4.8716888	train/test split	2359	4.6994694	Preprocessor1_Model1
3.4136927	train/test split	2360	1.8662936	Preprocessor1_Model1
7.5123867	train/test split	2364	7.4970924	Preprocessor1_Model1
1.5753425	train/test split	2368	1.6707585	Preprocessor1_Model1
2.6470259	train/test split	2369	1.6677123	Preprocessor1_Model1
3.4175496	train/test split	2371	3.8779781	Preprocessor1_Model1
5.4866233	train/test split	2373	5.8390020	Preprocessor1_Model1
5.8581648	train/test split	2379	5.9340728	Preprocessor1_Model1
6.9405747	train/test split	2380	6.4968229	Preprocessor1_Model1
4.1442607	train/test split	2389	3.4406778	Preprocessor1_Model1
5.7428066	train/test split	2400	5.5838883	Preprocessor1_Model1
6.5197607	train/test split	2402	6.1054171	Preprocessor1_Model1
2.5711255	train/test split	2403	2.8164708	Preprocessor1_Model1
4.2350352	train/test split	2407	4.4089266	Preprocessor1_Model1
5.8134731	train/test split	2408	5.2628132	Preprocessor1_Model1
6.5599508	train/test split	2411	6.5803158	Preprocessor1_Model1
5.3719919	train/test split	2416	5.1758059	Preprocessor1_Model1
2.4941638	train/test split	2417	2.1013917	Preprocessor1_Model1
5.5156888	train/test split	2419	5.6555978	Preprocessor1_Model1
3.5555754	train/test split	2426	3.5931913	Preprocessor1_Model1
5.9403517	train/test split	2430	6.6355896	Preprocessor1_Model1
5.7176202	train/test split	2439	5.6155855	Preprocessor1_Model1
2.3302215	train/test split	2442	2.2757864	Preprocessor1_Model1
4.3091983	train/test split	2450	3.2426902	Preprocessor1_Model1
2.7619824	train/test split	2454	2.9062983	Preprocessor1_Model1
6.7437046	train/test split	2455	6.5107992	Preprocessor1_Model1
2.6337104	train/test split	2458	1.4977065	Preprocessor1_Model1
4.0477793	train/test split	2459	4.1781790	Preprocessor1_Model1
4.7610821	train/test split	2461	4.9479167	Preprocessor1_Model1
4.5358908	train/test split	2466	4.7695288	Preprocessor1_Model1
6.5529459	train/test split	2469	6.6680175	Preprocessor1_Model1
4.5977597	train/test split	2474	4.0331421	Preprocessor1_Model1
5.9322084	train/test split	2475	5.7062018	Preprocessor1_Model1
2.5996692	train/test split	2477	2.8213100	Preprocessor1_Model1
8.1785673	train/test split	2480	8.7443284	Preprocessor1_Model1
6.7363807	train/test split	2483	7.8061311	Preprocessor1_Model1
1.7491613	train/test split	2487	1.3017421	Preprocessor1_Model1
4.6369060	train/test split	2488	4.0034420	Preprocessor1_Model1
4.3134279	train/test split	2495	3.7738226	Preprocessor1_Model1
5.8066150	train/test split	2497	5.8416512	Preprocessor1_Model1
5.2440403	train/test split	2502	4.5825585	Preprocessor1_Model1
1.2240428	train/test split	2507	1.1231159	Preprocessor1_Model1
5.8992081	train/test split	2509	6.2838433	Preprocessor1_Model1
4.8136044	train/test split	2510	4.7573647	Preprocessor1_Model1
4.3906581	train/test split	2511	4.3382336	Preprocessor1_Model1
4.1406745	train/test split	2513	3.8210722	Preprocessor1_Model1
2.6423705	train/test split	2516	2.3968140	Preprocessor1_Model1
6.0434768	train/test split	2518	5.2276691	Preprocessor1_Model1
4.2198981	train/test split	2526	4.4741420	Preprocessor1_Model1
5.9397247	train/test split	2529	6.0264293	Preprocessor1_Model1
2.5749076	train/test split	2537	1.9558111	Preprocessor1_Model1
2.4362945	train/test split	2539	1.7140969	Preprocessor1_Model1
2.8698926	train/test split	2540	3.6258626	Preprocessor1_Model1
2.9356931	train/test split	2541	2.0322945	Preprocessor1_Model1
3.6994065	train/test split	2543	4.1318725	Preprocessor1_Model1
3.5544553	train/test split	2544	3.8312213	Preprocessor1_Model1
4.7175078	train/test split	2546	4.7320243	Preprocessor1_Model1
6.0637813	train/test split	2554	5.6842796	Preprocessor1_Model1
6.2138186	train/test split	2557	6.3032525	Preprocessor1_Model1
6.6031600	train/test split	2559	5.8754997	Preprocessor1_Model1
6.1570014	train/test split	2560	6.8157922	Preprocessor1_Model1
3.6402807	train/test split	2561	3.3022305	Preprocessor1_Model1
3.5313223	train/test split	2565	3.7840733	Preprocessor1_Model1
6.1412441	train/test split	2568	6.0421127	Preprocessor1_Model1
4.7415890	train/test split	2573	5.8167107	Preprocessor1_Model1
5.5328277	train/test split	2574	5.9788186	Preprocessor1_Model1
4.0161405	train/test split	2578	4.2426976	Preprocessor1_Model1
5.4860270	train/test split	2581	5.9067205	Preprocessor1_Model1
2.7362305	train/test split	2589	2.5341152	Preprocessor1_Model1
3.8646302	train/test split	2595	3.3088631	Preprocessor1_Model1
4.0965790	train/test split	2598	3.1638063	Preprocessor1_Model1
2.6496571	train/test split	2602	3.3321603	Preprocessor1_Model1
2.9926090	train/test split	2603	3.3597786	Preprocessor1_Model1
5.6839546	train/test split	2619	6.5909071	Preprocessor1_Model1
5.1894461	train/test split	2623	4.9936893	Preprocessor1_Model1
4.3051747	train/test split	2624	3.3427619	Preprocessor1_Model1
3.6649376	train/test split	2629	3.0590888	Preprocessor1_Model1
6.0851569	train/test split	2630	6.2256936	Preprocessor1_Model1
5.6924368	train/test split	2633	5.1398699	Preprocessor1_Model1
2.7139973	train/test split	2635	2.4303665	Preprocessor1_Model1
3.6604625	train/test split	2641	3.8488216	Preprocessor1_Model1
5.1832509	train/test split	2643	5.9282893	Preprocessor1_Model1
3.7920495	train/test split	2649	3.8302336	Preprocessor1_Model1
3.2986407	train/test split	2650	4.8099906	Preprocessor1_Model1
6.2497523	train/test split	2651	6.0742996	Preprocessor1_Model1
3.3080887	train/test split	2652	2.8126419	Preprocessor1_Model1
5.3113912	train/test split	2653	5.7908726	Preprocessor1_Model1
6.8983359	train/test split	2655	7.4134986	Preprocessor1_Model1
6.5925409	train/test split	2661	7.1334891	Preprocessor1_Model1
3.6275638	train/test split	2672	3.5893602	Preprocessor1_Model1
4.9615605	train/test split	2673	4.3984028	Preprocessor1_Model1
5.3206735	train/test split	2677	4.4268701	Preprocessor1_Model1
5.4363838	train/test split	2678	5.3371064	Preprocessor1_Model1
4.2678802	train/test split	2682	4.5327809	Preprocessor1_Model1
7.5478678	train/test split	2685	8.0067571	Preprocessor1_Model1
5.9742686	train/test split	2690	6.1267591	Preprocessor1_Model1
2.6873000	train/test split	2697	2.8823169	Preprocessor1_Model1
3.4154243	train/test split	2698	2.7939654	Preprocessor1_Model1
7.1564044	train/test split	2701	6.2874838	Preprocessor1_Model1
7.7476498	train/test split	2702	7.2248049	Preprocessor1_Model1
5.3337257	train/test split	2703	5.4397558	Preprocessor1_Model1
5.9091767	train/test split	2705	5.2144664	Preprocessor1_Model1
6.8179414	train/test split	2710	7.5394777	Preprocessor1_Model1
3.6886239	train/test split	2711	3.4021905	Preprocessor1_Model1
4.0723461	train/test split	2713	4.8098465	Preprocessor1_Model1
5.2055559	train/test split	2721	5.3074678	Preprocessor1_Model1
6.6347958	train/test split	2722	7.2814445	Preprocessor1_Model1
6.8513073	train/test split	2725	7.2640943	Preprocessor1_Model1
5.1431516	train/test split	2726	5.0827006	Preprocessor1_Model1
6.8908797	train/test split	2728	7.0644372	Preprocessor1_Model1
5.2845076	train/test split	2729	4.3091607	Preprocessor1_Model1
6.0140970	train/test split	2732	5.1867192	Preprocessor1_Model1
4.7406464	train/test split	2746	4.9930954	Preprocessor1_Model1
5.7597680	train/test split	2754	5.5537708	Preprocessor1_Model1
4.5148992	train/test split	2766	4.7358772	Preprocessor1_Model1
4.6335606	train/test split	2770	4.4299172	Preprocessor1_Model1
2.9518865	train/test split	2773	2.7876561	Preprocessor1_Model1
4.5204948	train/test split	2776	4.4657698	Preprocessor1_Model1
5.9854010	train/test split	2780	5.9035112	Preprocessor1_Model1
5.0922728	train/test split	2781	5.0275582	Preprocessor1_Model1
4.1334506	train/test split	2782	3.8300601	Preprocessor1_Model1
5.6029185	train/test split	2783	5.4925585	Preprocessor1_Model1
4.4891909	train/test split	2790	4.8331064	Preprocessor1_Model1
2.3753750	train/test split	2798	2.0320507	Preprocessor1_Model1
4.7947770	train/test split	2807	4.6779183	Preprocessor1_Model1
4.4712512	train/test split	2812	4.8358087	Preprocessor1_Model1
7.6260933	train/test split	2817	7.8189233	Preprocessor1_Model1
6.6692060	train/test split	2820	7.5702823	Preprocessor1_Model1
4.5527232	train/test split	2821	2.9924419	Preprocessor1_Model1
2.4907727	train/test split	2822	3.1734835	Preprocessor1_Model1
5.7833588	train/test split	2846	5.3905243	Preprocessor1_Model1
6.4047488	train/test split	2847	6.2017346	Preprocessor1_Model1
4.2409757	train/test split	2851	4.4227497	Preprocessor1_Model1
6.1332028	train/test split	2858	6.6341004	Preprocessor1_Model1
6.5593433	train/test split	2860	6.7272612	Preprocessor1_Model1
3.8969680	train/test split	2863	3.5343020	Preprocessor1_Model1
1.4529970	train/test split	2869	1.3214125	Preprocessor1_Model1
2.6363477	train/test split	2871	2.6458469	Preprocessor1_Model1
4.8841986	train/test split	2875	4.9876375	Preprocessor1_Model1
6.2558773	train/test split	2882	6.4878189	Preprocessor1_Model1
5.5202461	train/test split	2883	5.8648739	Preprocessor1_Model1
5.7072013	train/test split	2885	4.9929801	Preprocessor1_Model1
4.5625255	train/test split	2887	5.5518430	Preprocessor1_Model1
3.6918810	train/test split	2888	4.0199286	Preprocessor1_Model1
0.9750394	train/test split	2889	0.7534951	Preprocessor1_Model1
5.7037352	train/test split	2894	6.1626394	Preprocessor1_Model1
3.8190240	train/test split	2896	3.1856939	Preprocessor1_Model1
5.0309693	train/test split	2900	3.9141038	Preprocessor1_Model1
4.6378437	train/test split	2902	5.1186247	Preprocessor1_Model1
3.5370286	train/test split	2916	2.8239757	Preprocessor1_Model1
5.1130973	train/test split	2925	5.1017390	Preprocessor1_Model1
1.3567157	train/test split	2931	1.8101876	Preprocessor1_Model1
8.1144694	train/test split	2932	7.8138152	Preprocessor1_Model1
6.6905232	train/test split	2933	7.6459253	Preprocessor1_Model1
5.9114682	train/test split	2934	5.9034884	Preprocessor1_Model1
2.6194980	train/test split	2935	2.9499495	Preprocessor1_Model1
3.2308821	train/test split	2936	2.7703988	Preprocessor1_Model1
6.5521171	train/test split	2938	6.0905691	Preprocessor1_Model1
3.4907447	train/test split	2939	3.0915931	Preprocessor1_Model1
4.5578449	train/test split	2944	5.2538635	Preprocessor1_Model1
8.1509360	train/test split	2945	7.4579491	Preprocessor1_Model1
6.9811998	train/test split	2948	6.4262820	Preprocessor1_Model1
4.2286402	train/test split	2951	3.6407330	Preprocessor1_Model1
1.4097761	train/test split	2954	2.6541079	Preprocessor1_Model1
2.8880017	train/test split	2956	3.7691402	Preprocessor1_Model1
4.7696491	train/test split	2957	4.8004877	Preprocessor1_Model1
2.6375849	train/test split	2959	2.8544663	Preprocessor1_Model1
1.3259734	train/test split	2968	0.9677686	Preprocessor1_Model1
4.2978580	train/test split	2969	4.3442595	Preprocessor1_Model1
3.9522835	train/test split	2987	3.4894791	Preprocessor1_Model1
2.8768431	train/test split	2994	2.4993383	Preprocessor1_Model1
8.0297208	train/test split	2998	7.3718562	Preprocessor1_Model1
7.0713845	train/test split	2999	6.7521436	Preprocessor1_Model1
1.1597205	train/test split	3002	1.0145356	Preprocessor1_Model1
5.2981246	train/test split	3004	5.8900692	Preprocessor1_Model1
1.0558377	train/test split	3007	1.4272555	Preprocessor1_Model1
6.1367989	train/test split	3010	5.2144551	Preprocessor1_Model1
2.2160441	train/test split	3012	2.5125223	Preprocessor1_Model1
2.5815755	train/test split	3014	2.6770016	Preprocessor1_Model1
4.1735260	train/test split	3017	4.2961908	Preprocessor1_Model1
3.1175270	train/test split	3018	2.6455813	Preprocessor1_Model1
4.5443395	train/test split	3020	4.3499982	Preprocessor1_Model1
5.1603687	train/test split	3021	5.6855086	Preprocessor1_Model1
3.7178343	train/test split	3024	3.3348005	Preprocessor1_Model1
6.6075877	train/test split	3026	6.8846480	Preprocessor1_Model1
3.9796195	train/test split	3032	4.2644013	Preprocessor1_Model1
6.2517673	train/test split	3035	5.3535336	Preprocessor1_Model1
4.0849944	train/test split	3046	3.7323642	Preprocessor1_Model1
5.7669156	train/test split	3049	5.9001828	Preprocessor1_Model1
1.5690847	train/test split	3050	1.5500590	Preprocessor1_Model1
7.0473209	train/test split	3056	6.8811726	Preprocessor1_Model1
6.3669846	train/test split	3060	6.6597116	Preprocessor1_Model1
4.9814939	train/test split	3062	4.5210590	Preprocessor1_Model1
5.3351678	train/test split	3064	5.3494781	Preprocessor1_Model1
3.6967482	train/test split	3065	3.5521256	Preprocessor1_Model1
2.5942509	train/test split	3067	2.2162457	Preprocessor1_Model1
1.8687107	train/test split	3069	1.9334647	Preprocessor1_Model1
6.4176956	train/test split	3071	5.9629126	Preprocessor1_Model1
3.0269707	train/test split	3072	3.3463866	Preprocessor1_Model1
6.7026059	train/test split	3080	7.2598997	Preprocessor1_Model1
2.2971590	train/test split	3082	2.1975225	Preprocessor1_Model1
5.2292707	train/test split	3084	5.1365790	Preprocessor1_Model1
4.5092627	train/test split	3089	4.5224883	Preprocessor1_Model1
4.9603423	train/test split	3090	5.1794323	Preprocessor1_Model1
2.5002111	train/test split	3092	2.6528353	Preprocessor1_Model1
1.8186946	train/test split	3104	1.5458185	Preprocessor1_Model1
1.9936329	train/test split	3110	1.9782855	Preprocessor1_Model1
4.8180400	train/test split	3111	4.2613282	Preprocessor1_Model1
4.0032382	train/test split	3117	3.7589215	Preprocessor1_Model1
6.0976606	train/test split	3119	5.3223830	Preprocessor1_Model1
3.5486901	train/test split	3122	3.7107538	Preprocessor1_Model1
5.0654804	train/test split	3123	5.4125933	Preprocessor1_Model1
6.9166883	train/test split	3125	7.2067818	Preprocessor1_Model1
6.5111359	train/test split	3129	6.7817204	Preprocessor1_Model1
7.5209451	train/test split	3134	7.4136745	Preprocessor1_Model1
5.5327232	train/test split	3137	6.1078612	Preprocessor1_Model1
6.0562396	train/test split	3138	6.7612920	Preprocessor1_Model1
4.9282310	train/test split	3139	5.5063292	Preprocessor1_Model1
3.3546100	train/test split	3141	2.5364093	Preprocessor1_Model1
6.4043795	train/test split	3142	6.9220032	Preprocessor1_Model1
4.7271075	train/test split	3145	4.0763663	Preprocessor1_Model1
6.6330892	train/test split	3153	6.3332738	Preprocessor1_Model1
4.9386621	train/test split	3154	5.0296380	Preprocessor1_Model1
7.0652564	train/test split	3157	7.6514180	Preprocessor1_Model1
5.2126807	train/test split	3161	4.9468827	Preprocessor1_Model1
4.9846112	train/test split	3163	5.6330179	Preprocessor1_Model1
5.1978782	train/test split	3167	5.8558827	Preprocessor1_Model1
4.1425701	train/test split	3168	4.7264042	Preprocessor1_Model1
6.8470182	train/test split	3170	6.2463646	Preprocessor1_Model1
3.9910715	train/test split	3172	2.6021992	Preprocessor1_Model1
3.9563766	train/test split	3178	3.7067615	Preprocessor1_Model1
5.5663988	train/test split	3179	5.2231676	Preprocessor1_Model1
3.6231488	train/test split	3180	2.6369306	Preprocessor1_Model1
5.0009057	train/test split	3181	5.0277522	Preprocessor1_Model1
3.6111660	train/test split	3182	3.0180492	Preprocessor1_Model1
3.8604348	train/test split	3185	3.8380361	Preprocessor1_Model1
4.2398516	train/test split	3189	3.9291827	Preprocessor1_Model1
3.7846612	train/test split	3190	3.2815979	Preprocessor1_Model1
5.2229651	train/test split	3194	4.1832883	Preprocessor1_Model1
6.5983529	train/test split	3198	5.6281927	Preprocessor1_Model1
6.1413319	train/test split	3199	5.5949220	Preprocessor1_Model1
3.9023353	train/test split	3201	4.2516976	Preprocessor1_Model1
5.5357684	train/test split	3203	5.4769940	Preprocessor1_Model1
4.5948757	train/test split	3204	4.8653485	Preprocessor1_Model1
5.2810284	train/test split	3212	5.7356121	Preprocessor1_Model1
5.8189390	train/test split	3215	6.3629157	Preprocessor1_Model1
5.1016563	train/test split	3219	3.8721550	Preprocessor1_Model1
2.9852105	train/test split	3223	3.0321327	Preprocessor1_Model1
5.1150102	train/test split	3224	5.3088025	Preprocessor1_Model1
3.7784483	train/test split	3227	3.6232884	Preprocessor1_Model1
3.5072157	train/test split	3232	3.7942979	Preprocessor1_Model1
4.4223230	train/test split	3236	4.3776219	Preprocessor1_Model1
3.3268819	train/test split	3237	2.8547074	Preprocessor1_Model1
5.9776417	train/test split	3238	6.0187547	Preprocessor1_Model1
2.7144450	train/test split	3240	2.9429132	Preprocessor1_Model1
6.9079943	train/test split	3242	6.4836742	Preprocessor1_Model1
5.7268370	train/test split	3243	6.0090906	Preprocessor1_Model1
6.2454984	train/test split	3247	6.8951867	Preprocessor1_Model1
6.3716839	train/test split	3250	6.3723061	Preprocessor1_Model1
4.1397031	train/test split	3251	3.8599920	Preprocessor1_Model1
4.3940623	train/test split	3252	3.9718315	Preprocessor1_Model1
4.3005972	train/test split	3256	4.2331727	Preprocessor1_Model1
2.7233808	train/test split	3260	3.1431053	Preprocessor1_Model1
2.2460118	train/test split	3266	2.0557232	Preprocessor1_Model1
1.4163317	train/test split	3267	1.0717115	Preprocessor1_Model1
6.1311257	train/test split	3272	6.1662378	Preprocessor1_Model1
6.7615194	train/test split	3273	7.4612847	Preprocessor1_Model1
5.1008892	train/test split	3274	5.5964587	Preprocessor1_Model1
2.5673745	train/test split	3281	2.5026974	Preprocessor1_Model1
4.0553743	train/test split	3282	4.6275046	Preprocessor1_Model1
2.6400253	train/test split	3284	2.5758080	Preprocessor1_Model1

set.seed(3234)
#| label: fig-final-eval
#| fig-cap: Model evaluation measured vs predicted


test_pred |> 
  janitor::clean_names() |> 
  slice_sample(n = 100000) |> 
  ggplot(aes(yield_tons_per_hectare, pred)) +
  geom_jitter(alpha = .4) +
  geom_abline(col = "red") +
  labs(
    x = "Measured",
    y = "Predicted",
    title = "Predicted vs Measured Crop Yield (tons per ha)"
  )

crop_final_fit |> 
  extract_fit_engine() |> 
  plot(3)

crop_final_fit |> 
  extract_fit_engine(4) |> 
  plot(1)

crop_final_fit |> 
  extract_fit_engine() |> 
  plot(4)

(a)

(b)

(c)

Figure 5: Goodness-of-fit test for MARS -earth model

Variable importance

vip(
  crop_final_fit |> 
    extract_fit_engine()
)

Figure 6: Variable importance plot of the mars model