import sys
%matplotlib inline
import matplotlib.pyplot as plt
import itertools
import ipyparallel as ipp
import pandas as pd
import numpy as np
import os
import seaborn as sns
from IPython.display import display
import csv
from sklearn import metrics
from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier
from sklearn.model_selection import train_test_split, cross_val_score, RandomizedSearchCV, GridSearchCV
from sklearn.preprocessing import PowerTransformer, QuantileTransformer, StandardScaler
from sklearn.decomposition import PCA
from sklearn.datasets import make_regression
import MESS
from MESS.util import set_params
pd.set_option('display.max_columns', 500)
pd.set_option('display.max_rows', 100)
pd.set_option('display.width', 1000)
## set directory for analysis
analysis_dir = "/mnt/lfs2/ruff6699/Mess2.0/git/Figure4_Data/"
##make if doesn't exist
if not os.path.exists(analysis_dir):
os.mkdir(analysis_dir)
/mnt/ceph/ruff6699/scratch/Mess2.0/minicoiconda2/envs/py2.7/lib/python2.7/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`. from ._conv import register_converters as _register_converters
## quick test to make sure Mess will run
r = MESS.Region("r1")
r.paramsdict["generations"] = 0.25
r.set_param("project_dir", analysis_dir)
r.set_param("m", 0.01)
r.set_param("community_assembly_model", "*")
r.run(sims=10)
Generating 10 simulation(s). [#### ] 20% Performing Simulations | 0:00:22 |
/mnt/ceph/ruff6699/scratch/Mess2.0/minicoiconda2/envs/py2.7/lib/python2.7/site-packages/scipy/stats/stats.py:380: RuntimeWarning: invalid value encountered in double_scalars return size / np.sum(1.0 / a, axis=axis, dtype=dtype)
[####################] 100% Finished 9 simulations | 0:00:46 |
## run the below line in terminal, not in jupyter notebooks
## this will start and ipcluster
## ipcluster start -n 40 --cluster-id="MESS-Rich" --daemonize
## check to make sure the client is working
## should print the number of cores ready to go
ipyclient = ipp.Client(cluster_id="MESS-Rich")
print(len(ipyclient))
40
## This chunk runs a bunch of simulations with different param combos
## set dir (again) bc just in case..
analysis_dir = "/mnt/lfs2/ruff6699/Mess2.0/git/Figure4_Data/"
## different param combinations to try
specrates = np.array([0.001])
#modnames = np.array(["neutral", "filtering", "competition"])
localcomsize = np.array([500, 1000, 2000, 5000])
## go through all param combinations
params = [specrates, localcomsize]
params = list(itertools.product(*params))
for i, p in enumerate(params):
specrates, localcomsize = p
print(specrates, localcomsize)
ldir = analysis_dir + "Speciation-{}/".format(specrates)
if not os.path.exists(ldir):
os.mkdir(ldir)
ldir = ldir + "LocalComSize-{}".format(localcomsize)
if not os.path.exists(ldir):
os.mkdir(ldir)
r = MESS.Region("sim-{}".format(i))
r._log_files = True
r.set_param("generations", 0.5)
r.set_param("community_assembly_model", "*")
r.set_param("S_m", 500)
r.set_param("J", localcomsize)
r.set_param("speciation_rate", specrates)
r.set_param("project_dir", ldir)
r.run(sims=3000, ipyclient=ipyclient, quiet=False)
#r.run(sims=100, quiet=False)
(0.001, 500) Generating 3000 simulation(s). [################### ] 99% Performing Simulations | 0:35:32 |
ldir = analysis_dir + "Speciation-0.001/LocalComSize-500/SIMOUT.txt"
##Begin with No Speciation
df = pd.read_csv(ldir, sep="\t", header=0)
df
S_m | J_m | speciation_rate | death_proportion | trait_rate_meta | ecological_strength | generations | community_assembly_model | speciation_model | mutation_rate | alpha | sequence_length | J | m | speciation_prob | generation | _lambda | migrate_calculated | extrate_calculated | trait_rate_local | filtering_optimum | S | abund_h1 | abund_h2 | abund_h3 | abund_h4 | pi_h1 | pi_h2 | pi_h3 | pi_h4 | mean_pi | std_pi | skewness_pi | kurtosis_pi | median_pi | iqr_pi | mean_dxys | std_dxys | skewness_dxys | kurtosis_dxys | median_dxys | iqr_dxys | trees | trait_h1 | trait_h2 | trait_h3 | trait_h4 | mean_local_traits | std_local_traits | skewness_local_traits | kurtosis_local_traits | median_local_traits | iqr_local_traits | mean_regional_traits | std_regional_traits | skewness_regional_traits | kurtosis_regional_traits | median_regional_traits | iqr_regional_traits | reg_loc_mean_trait_dif | reg_loc_std_trait_dif | reg_loc_skewness_trait_dif | reg_loc_kurtosis_trait_dif | reg_loc_median_trait_dif | reg_loc_iqr_trait_dif | abundance_dxy_cor | abundance_pi_cor | abundance_trait_cor | dxy_pi_cor | dxy_trait_cor | pi_trait_cor | SGD_0 | SGD_1 | SGD_2 | SGD_3 | SGD_4 | SGD_5 | SGD_6 | SGD_7 | SGD_8 | SGD_9 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 13.0 | 0.650 | 0.01169 | 0.00769 | 0.58824 | 0.29846 | 12.0 | 5.82394 | 4.49349 | 3.94202 | 3.65633 | 3.88368 | 3.79607 | 3.73111 | 3.68271 | 0.00019 | 0.00028 | 0.90034 | -1.03271 | 0.00000 | 0.00042 | 0.00088 | 0.00097 | 0.91700 | -0.72289 | 0.00035 | 0.00118 | 0.0 | 6.79640 | 5.28759 | 4.59281 | 4.21692 | 0.10533 | 0.95916 | -0.75511 | 0.41293 | 0.19535 | 1.02062 | 0.94916 | 2.58467 | -0.16480 | -0.20490 | 1.03746 | 3.39993 | 0.84383 | 1.62551 | 0.59031 | -0.61783 | 0.84211 | 2.37932 | 0.33810 | 0.12556 | -0.49825 | 0.38073 | -0.56743 | -0.43793 | 8.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 2.0 | 1.0 |
1 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 141.0 | 0.536 | 0.00990 | 0.00780 | 0.58824 | 3.64268 | 21.0 | 5.47850 | 3.00055 | 2.42898 | 2.21612 | 5.73763 | 4.99537 | 4.58524 | 4.34447 | 0.00030 | 0.00054 | 1.80721 | 1.99378 | 0.00000 | 0.00035 | 0.00100 | 0.00109 | 0.80883 | -0.78698 | 0.00053 | 0.00193 | 0.0 | 7.90855 | 5.30509 | 4.60828 | 4.31162 | 0.64331 | 2.68314 | 0.28157 | -1.07907 | 0.60742 | 4.35274 | 0.98575 | 2.69103 | -0.10393 | -0.67260 | 1.16725 | 4.19339 | 0.34244 | 0.00789 | -0.38550 | 0.40646 | 0.55983 | -0.15935 | 0.44112 | 0.48405 | 0.35494 | 0.53387 | -0.06047 | 0.06355 | 14.0 | 3.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 2.0 |
2 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 123.0 | 0.518 | 0.00985 | 0.00771 | 0.58824 | 2.18450 | 19.0 | 6.36010 | 3.59774 | 2.89481 | 2.61665 | 6.45581 | 5.97027 | 5.58080 | 5.28624 | 0.00019 | 0.00028 | 1.25414 | 0.39358 | 0.00000 | 0.00035 | 0.00251 | 0.00275 | 1.01883 | -0.06691 | 0.00140 | 0.00421 | 0.0 | 7.18814 | 4.94005 | 4.30632 | 4.04016 | -0.76314 | 3.14713 | -0.02360 | -1.24162 | -0.48337 | 5.12524 | 0.51183 | 3.21759 | 0.31548 | 0.06781 | 0.47159 | 4.22202 | 1.27497 | 0.07046 | 0.33908 | 1.30942 | 0.95496 | -0.90321 | 0.14108 | 0.65929 | -0.07234 | 0.25428 | -0.11469 | 0.26099 | 12.0 | 0.0 | 0.0 | 4.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 1.0 |
3 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 14.0 | 0.564 | 0.01257 | 0.00771 | 0.58824 | -2.38398 | 14.0 | 5.12517 | 3.69904 | 3.19964 | 2.94421 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00003 | 0.00009 | 3.32820 | 9.07692 | 0.00000 | 0.00000 | 0.00103 | 0.00138 | 1.26489 | 0.12679 | 0.00035 | 0.00140 | 0.0 | 5.34654 | 4.16811 | 3.84675 | 3.70285 | 1.43440 | 2.63978 | 0.43809 | -0.14837 | 1.45077 | 3.69584 | 1.57586 | 2.89657 | 0.37117 | 0.23631 | 1.46974 | 3.91605 | 0.14146 | 0.25679 | -0.06691 | 0.38468 | 0.01897 | 0.22022 | 0.04541 | 0.10412 | 0.50778 | -0.07045 | -0.40506 | 0.44721 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
4 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 8.0 | 0.542 | 0.00800 | 0.00200 | 0.58824 | -0.27385 | 12.0 | 4.31832 | 3.31169 | 2.98457 | 2.80288 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00003 | 0.00010 | 3.01511 | 7.09091 | 0.00000 | 0.00000 | 0.00221 | 0.00254 | 1.33982 | 0.40685 | 0.00167 | 0.00193 | 0.0 | 7.30229 | 4.81253 | 4.05722 | 3.74594 | 0.41868 | 4.14341 | -0.26922 | -1.80346 | 2.79501 | 8.16161 | -0.20107 | 4.15094 | 0.10489 | -1.10729 | -0.62690 | 7.20345 | -0.61975 | 0.00753 | 0.37411 | 0.69617 | -3.42191 | -0.95816 | 0.24291 | 0.39652 | -0.20459 | 0.30732 | 0.16872 | 0.30570 | 11.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
5 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 117.0 | 0.516 | 0.01002 | 0.00790 | 0.58824 | -0.69301 | 16.0 | 5.91773 | 3.26738 | 2.58909 | 2.34168 | 6.47972 | 6.05437 | 5.72944 | 5.48682 | 0.00026 | 0.00033 | 0.88837 | -0.60650 | 0.00000 | 0.00042 | 0.00162 | 0.00189 | 0.88852 | -0.88065 | 0.00053 | 0.00325 | 0.0 | 9.48187 | 6.80285 | 5.96826 | 5.57879 | 1.26270 | 3.39598 | 0.97150 | 1.71994 | 0.56226 | 3.19817 | 1.79096 | 4.35098 | 0.41001 | -0.55924 | 1.16200 | 6.61284 | 0.52827 | 0.95500 | -0.56149 | -2.27919 | 0.59974 | 3.41466 | -0.00371 | 0.08803 | -0.19735 | 0.34248 | -0.12584 | -0.21324 | 9.0 | 0.0 | 0.0 | 3.0 | 0.0 | 0.0 | 2.0 | 0.0 | 1.0 | 1.0 |
6 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 62.0 | 0.500 | 0.01045 | 0.00735 | 0.58824 | 4.94500 | 22.0 | 6.60265 | 3.51647 | 2.77824 | 2.50217 | 3.66750 | 3.43860 | 3.27715 | 3.15758 | 0.00015 | 0.00035 | 2.22244 | 3.63556 | 0.00000 | 0.00000 | 0.00081 | 0.00087 | 0.62862 | -1.23235 | 0.00044 | 0.00167 | 0.0 | 11.25994 | 7.35999 | 6.22512 | 5.70934 | -1.82252 | 4.51627 | -0.35706 | -1.08823 | -0.84598 | 7.55794 | -2.26797 | 4.15044 | -0.30237 | -0.81817 | -1.88605 | 6.24361 | -0.44545 | -0.36583 | 0.05469 | 0.27006 | -1.04007 | -1.31433 | 0.15140 | 0.64401 | 0.09014 | 0.31719 | 0.10709 | -0.16792 | 18.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 1.0 |
7 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 12.0 | 0.532 | 0.01100 | 0.00800 | 0.58824 | -0.70794 | 5.0 | 3.14144 | 2.72011 | 2.56057 | 2.47641 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00007 | 0.00014 | 1.50000 | 0.25000 | 0.00000 | 0.00000 | 0.00147 | 0.00203 | 1.33102 | 0.02571 | 0.00088 | 0.00105 | 0.0 | 3.47536 | 3.04504 | 2.83879 | 2.72340 | -1.30242 | 0.51755 | 0.27707 | -0.67325 | -1.29528 | 0.32799 | -0.74410 | 3.12484 | -0.42574 | -0.32376 | -0.28797 | 4.45812 | 0.55832 | 2.60729 | -0.70280 | 0.34949 | 1.00731 | 4.13013 | 0.20520 | 0.70711 | 0.50000 | 0.36274 | 0.87208 | -0.70711 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
8 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 11.0 | 0.636 | 0.00982 | 0.00691 | 0.58824 | 1.78938 | 7.0 | 3.26937 | 2.89970 | 2.77896 | 2.70845 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00014 | 0.00034 | 2.04124 | 2.16667 | 0.00000 | 0.00000 | 0.00226 | 0.00170 | -0.11973 | -1.74662 | 0.00246 | 0.00342 | 0.0 | 4.07935 | 3.71480 | 3.61969 | 3.54678 | -1.16748 | 3.55601 | 0.91533 | -0.46747 | -2.46726 | 2.97397 | 0.16278 | 2.57933 | 0.02871 | -0.21066 | 0.26101 | 3.46200 | 1.33026 | -0.97668 | -0.88662 | 0.25681 | 2.72827 | 0.48803 | 0.61538 | -0.42366 | -0.44475 | 0.00000 | 0.18531 | 0.40825 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
9 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 8.0 | 0.564 | 0.01350 | 0.00750 | 0.58824 | -0.17878 | 11.0 | 4.47208 | 3.40105 | 3.05850 | 2.89603 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00183 | 0.00184 | 0.22886 | -1.73872 | 0.00105 | 0.00351 | 0.0 | 10.29247 | 7.02356 | 5.50925 | 4.67023 | -0.90271 | 5.46922 | -0.10795 | -0.80307 | 1.09221 | 7.86710 | -0.79054 | 3.24432 | -0.17120 | 0.30430 | -0.65317 | 4.17124 | 0.11217 | -2.22490 | -0.06324 | 1.10738 | -1.74538 | -3.69586 | 0.46041 | 0.00000 | -0.67426 | 0.00000 | 0.63424 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 11.0 | 0.0 | 0.0 | 0.0 | 0.0 |
10 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 10.0 | 0.564 | 0.00920 | 0.00760 | 0.58824 | 4.90301 | 5.0 | 3.04046 | 2.74523 | 2.62949 | 2.56807 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00561 | 0.00322 | -0.40916 | -1.83136 | 0.00825 | 0.00649 | 0.0 | 2.96726 | 2.71886 | 2.61866 | 2.56472 | 5.57649 | 0.40611 | -0.30739 | -1.27957 | 5.57004 | 0.63124 | 2.99840 | 3.19745 | 0.26824 | -0.20782 | 2.63591 | 4.62819 | -2.57809 | 2.79134 | 0.57563 | 1.07175 | -2.93413 | 3.99695 | -0.33541 | 0.00000 | 0.10000 | 0.00000 | -0.78262 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5.0 | 0.0 | 0.0 | 0.0 | 0.0 |
11 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 10.0 | 0.600 | 0.00960 | 0.00320 | 0.58824 | -1.48114 | 16.0 | 6.96135 | 4.77921 | 3.87714 | 3.44386 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00006 | 0.00023 | 3.61478 | 11.06667 | 0.00000 | 0.00000 | 0.00115 | 0.00119 | 1.79764 | 3.50019 | 0.00105 | 0.00096 | 0.0 | 9.04265 | 7.18018 | 6.37144 | 5.92376 | -1.32852 | 3.86828 | -0.89889 | -0.00668 | -0.73256 | 3.79254 | -0.83863 | 3.28862 | -0.52234 | 0.05825 | -0.31500 | 4.76150 | 0.48989 | -0.57966 | 0.37656 | 0.06493 | 0.41755 | 0.96896 | 0.03071 | 0.08464 | -0.18371 | -0.08496 | 0.10856 | 0.30806 | 15.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
12 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 31.0 | 0.500 | 0.00890 | 0.00890 | 0.58824 | 1.41098 | 7.0 | 2.94537 | 2.61331 | 2.46471 | 2.36935 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00005 | 0.00012 | 2.04124 | 2.16667 | 0.00000 | 0.00000 | 0.00163 | 0.00128 | 0.30917 | -1.37893 | 0.00175 | 0.00202 | 0.0 | 3.11129 | 2.77270 | 2.67827 | 2.62701 | 1.14947 | 0.59371 | -0.43392 | -0.52679 | 1.12898 | 0.64614 | -0.63099 | 2.88313 | -0.99058 | 1.10641 | -0.22223 | 3.46673 | -1.78046 | 2.28942 | -0.55666 | 1.63320 | -1.35121 | 2.82058 | 0.54727 | 0.63549 | -0.55594 | 0.62361 | 0.56373 | -0.61237 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
13 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 108.0 | 0.532 | 0.00989 | 0.00811 | 0.58824 | 0.00777 | 15.0 | 6.26539 | 3.79041 | 3.03554 | 2.72589 | 2.66438 | 2.39024 | 2.20183 | 2.08178 | 0.00011 | 0.00025 | 2.44150 | 5.01603 | 0.00000 | 0.00000 | 0.00195 | 0.00310 | 2.94297 | 7.75268 | 0.00088 | 0.00140 | 0.0 | 10.79898 | 7.30394 | 5.96223 | 5.34432 | 2.79476 | 1.93563 | 0.36206 | -0.49460 | 2.26145 | 2.46766 | 3.73641 | 2.94776 | 0.51131 | -0.19976 | 3.20640 | 4.07305 | 0.94165 | 1.01213 | 0.14925 | 0.29484 | 0.94495 | 1.60539 | 0.27061 | 0.01280 | 0.00000 | -0.03462 | -0.37064 | 0.00512 | 12.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
14 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 128.0 | 0.510 | 0.01091 | 0.00806 | 0.58824 | -1.31001 | 18.0 | 5.49412 | 2.97117 | 2.42021 | 2.21394 | 4.83318 | 4.68872 | 4.56750 | 4.46775 | 0.00027 | 0.00046 | 1.25715 | -0.10820 | 0.00000 | 0.00047 | 0.00184 | 0.00211 | 1.46955 | 1.28328 | 0.00123 | 0.00215 | 0.0 | 7.54391 | 4.97650 | 4.29864 | 4.01428 | 0.50399 | 3.70396 | -0.43616 | -0.67141 | 0.86381 | 5.61537 | -0.08738 | 3.11276 | -0.29898 | -0.08770 | 0.11632 | 3.94924 | -0.59137 | -0.59120 | 0.13718 | 0.58371 | -0.74749 | -1.66612 | 0.04688 | 0.69174 | 0.64286 | 0.32987 | 0.23780 | 0.28341 | 13.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 2.0 |
15 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 13.0 | 0.512 | 0.00923 | 0.00769 | 0.58824 | 3.90711 | 3.0 | 2.04689 | 2.01551 | 2.01128 | 2.00968 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00012 | 0.00017 | 0.70711 | -1.50000 | 0.00000 | 0.00018 | 0.00152 | 0.00147 | 0.44511 | -1.50000 | 0.00105 | 0.00175 | 0.0 | 2.14535 | 2.03610 | 2.02226 | 2.01759 | 3.67504 | 0.51850 | 0.13867 | -1.50000 | 3.62683 | 0.63366 | 0.25682 | 3.33978 | 0.15464 | -0.04608 | 0.07336 | 4.33763 | -3.41822 | 2.82128 | 0.01597 | 1.45392 | -3.55347 | 3.70397 | 0.50000 | 0.00000 | -1.00000 | 0.86603 | -0.50000 | 0.00000 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
16 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 16.0 | 0.508 | 0.00800 | 0.00625 | 0.58824 | -0.31317 | 11.0 | 4.17159 | 3.06177 | 2.68770 | 2.49467 | 2.64369 | 2.38722 | 2.21952 | 2.11190 | 0.00020 | 0.00038 | 1.85885 | 2.20123 | 0.00000 | 0.00018 | 0.00156 | 0.00112 | 0.10984 | -1.28504 | 0.00158 | 0.00175 | 0.0 | 4.52220 | 3.67955 | 3.46656 | 3.38127 | 0.49856 | 2.31520 | 0.35488 | -1.53487 | -1.05097 | 3.92656 | 1.78524 | 3.39134 | -0.40892 | 0.51849 | 1.99240 | 4.44087 | 1.28668 | 1.07614 | -0.76379 | 2.05336 | 3.04337 | 0.51431 | 0.62700 | -0.16552 | -0.01827 | -0.04925 | -0.30524 | 0.54343 | 8.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
17 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 17.0 | 0.602 | 0.01153 | 0.00471 | 0.58824 | 1.92892 | 19.0 | 8.06251 | 4.79791 | 3.72646 | 3.28617 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00004 | 0.00018 | 4.00694 | 14.05556 | 0.00000 | 0.00000 | 0.00095 | 0.00134 | 1.53776 | 1.45180 | 0.00035 | 0.00132 | 0.0 | 9.96463 | 7.45864 | 6.48043 | 5.92591 | 1.77824 | 3.15410 | -0.29272 | -0.02262 | 1.91440 | 3.91447 | 1.15954 | 3.60699 | 0.13463 | -0.38763 | 0.83619 | 5.00436 | -0.61871 | 0.45290 | 0.42735 | -0.36501 | -1.07822 | 1.08990 | 0.43166 | 0.00000 | -0.48264 | 0.31877 | 0.09840 | 0.38730 | 18.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
18 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 8.0 | 0.644 | 0.01000 | 0.00700 | 0.58824 | 5.29703 | 7.0 | 3.22816 | 3.04562 | 2.99984 | 2.97207 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00005 | 0.00012 | 2.04124 | 2.16667 | 0.00000 | 0.00000 | 0.00228 | 0.00200 | 0.37993 | -1.32844 | 0.00193 | 0.00342 | 0.0 | 3.15472 | 3.00452 | 2.96827 | 2.94663 | 4.48057 | 2.85037 | -1.83122 | 1.70451 | 5.46933 | 1.44489 | 2.83562 | 3.47549 | -0.15240 | 0.10978 | 3.06449 | 4.37001 | -1.64495 | 0.62512 | 1.67881 | -1.59473 | -2.40484 | 2.92512 | 0.67316 | 0.42366 | 0.48181 | 0.61791 | 0.45047 | 0.61237 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
19 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 112.0 | 0.518 | 0.00954 | 0.00693 | 0.58824 | 4.33691 | 18.0 | 4.71396 | 3.01510 | 2.55529 | 2.35042 | 2.85394 | 2.72045 | 2.60701 | 2.51556 | 0.00015 | 0.00036 | 2.24043 | 3.73240 | 0.00000 | 0.00000 | 0.00160 | 0.00173 | 1.09575 | 0.31899 | 0.00132 | 0.00202 | 0.0 | 5.19388 | 3.97203 | 3.65804 | 3.51867 | -2.63129 | 4.74799 | 0.37704 | -0.60661 | -3.55011 | 4.89416 | -1.46997 | 4.79954 | 0.17637 | -0.75912 | -2.05186 | 6.98774 | 1.16132 | 0.05155 | -0.20067 | -0.15251 | 1.49825 | 2.09358 | 0.24084 | 0.50588 | 0.09077 | 0.22825 | 0.05259 | 0.01747 | 15.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 |
20 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 17.0 | 0.584 | 0.00988 | 0.00635 | 0.58824 | -1.85203 | 11.0 | 2.84747 | 2.33318 | 2.24175 | 2.20631 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00007 | 0.00024 | 2.84605 | 6.10000 | 0.00000 | 0.00000 | 0.00077 | 0.00098 | 0.75112 | -1.14947 | 0.00018 | 0.00167 | 0.0 | 3.22455 | 2.42594 | 2.30119 | 2.25838 | 1.79312 | 4.50360 | 0.39226 | -0.68218 | 2.71089 | 6.56938 | 2.37208 | 3.09800 | -0.10482 | 0.03859 | 2.46889 | 4.16787 | 0.57896 | -1.40560 | -0.49708 | 0.72076 | -0.24200 | -2.40152 | -0.23970 | -0.35824 | 0.16283 | 0.52572 | -0.19117 | -0.30000 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
21 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 20.0 | 0.564 | 0.01080 | 0.00540 | 0.58824 | 0.41581 | 22.0 | 5.22004 | 3.29329 | 2.90136 | 2.74703 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00002 | 0.00007 | 4.36436 | 17.04762 | 0.00000 | 0.00000 | 0.00338 | 0.00563 | 1.45250 | 0.30918 | 0.00044 | 0.00202 | 0.0 | 6.15389 | 3.58611 | 3.12107 | 2.95981 | -0.16381 | 3.17754 | -0.06894 | -0.76936 | -0.18879 | 4.27953 | -0.51563 | 4.00172 | -0.32134 | -0.67710 | -0.35122 | 6.14868 | -0.35183 | 0.82418 | -0.25240 | 0.09227 | -0.16243 | 1.86915 | -0.04627 | 0.37059 | -0.37197 | 0.34335 | -0.32039 | 0.32676 | 21.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
22 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 11.0 | 0.524 | 0.00727 | 0.00400 | 0.58824 | 3.84019 | 11.0 | 3.01458 | 2.45904 | 2.34451 | 2.29869 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00003 | 0.00010 | 2.84605 | 6.10000 | 0.00000 | 0.00000 | 0.00077 | 0.00075 | 0.62225 | -1.17538 | 0.00053 | 0.00123 | 0.0 | 3.23654 | 2.53311 | 2.39474 | 2.34238 | -0.87060 | 2.95834 | 0.36817 | -1.25961 | -1.84769 | 4.75806 | -1.57396 | 3.78549 | 0.02115 | -0.44713 | -1.45693 | 5.57459 | -0.70336 | 0.82715 | -0.34702 | 0.81248 | 0.39075 | 0.81653 | 0.42254 | 0.20374 | -0.07409 | -0.20278 | -0.05530 | -0.40000 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
23 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 17.0 | 0.512 | 0.00965 | 0.00682 | 0.58824 | 0.44162 | 10.0 | 3.56528 | 2.90178 | 2.65278 | 2.50578 | 1.75477 | 1.60000 | 1.51186 | 1.46153 | 0.00014 | 0.00032 | 2.24453 | 3.52381 | 0.00000 | 0.00000 | 0.00070 | 0.00061 | 0.36609 | -1.16044 | 0.00061 | 0.00096 | 0.0 | 3.75794 | 3.22086 | 3.09795 | 3.03951 | 0.02852 | 0.80836 | -0.17649 | -1.29007 | 0.19566 | 1.32747 | -0.26135 | 3.29192 | 0.08655 | -0.32297 | -0.60345 | 4.44730 | -0.28987 | 2.48356 | 0.26304 | 0.96710 | -0.79911 | 3.11983 | 0.11113 | 0.48193 | -0.38144 | 0.39528 | -0.01231 | -0.12975 | 8.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
24 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 16.0 | 0.672 | 0.01075 | 0.00950 | 0.58824 | 0.62669 | 8.0 | 4.42948 | 3.71096 | 3.44177 | 3.29934 | 1.92210 | 1.85460 | 1.79954 | 1.75636 | 0.00012 | 0.00022 | 1.46264 | 0.49071 | 0.00000 | 0.00009 | 0.00178 | 0.00054 | -2.18142 | 2.93690 | 0.00193 | 0.00004 | 0.0 | 4.46984 | 3.85316 | 3.58337 | 3.41859 | 0.43441 | 0.11404 | -0.07137 | -1.03905 | 0.43475 | 0.13709 | -0.74174 | 2.53220 | 0.21074 | -0.27470 | -1.01150 | 3.47319 | -1.17614 | 2.41816 | 0.28210 | 0.76435 | -1.44626 | 3.33609 | 0.19094 | 0.01559 | 0.42857 | -0.12500 | -0.51827 | 0.26498 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
25 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 11.0 | 0.688 | 0.01091 | 0.00473 | 0.58824 | 2.77750 | 14.0 | 4.37567 | 3.13613 | 2.81120 | 2.66604 | 1.89681 | 1.81150 | 1.74596 | 1.69762 | 0.00017 | 0.00045 | 2.47015 | 4.66598 | 0.00000 | 0.00000 | 0.00128 | 0.00147 | 0.80645 | -0.82662 | 0.00053 | 0.00202 | 0.0 | 5.96998 | 3.67614 | 3.17276 | 2.98661 | -0.62865 | 3.45716 | -0.66549 | -0.61767 | 0.02063 | 3.90981 | 0.95079 | 4.31927 | 0.28356 | -0.42632 | 0.75375 | 6.30329 | 1.57943 | 0.86211 | 0.94906 | 0.19135 | 0.73312 | 2.39347 | -0.13576 | 0.61351 | 0.05089 | 0.39464 | 0.42033 | 0.21998 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
26 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 35.0 | 0.504 | 0.01063 | 0.01017 | 0.58824 | -2.49161 | 3.0 | 2.12940 | 2.05110 | 2.03490 | 2.02757 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00027 | 0.00039 | 0.70711 | -1.50000 | 0.00000 | 0.00041 | 0.00246 | 0.00025 | 0.70711 | -1.50000 | 0.00228 | 0.00026 | 0.0 | 2.13616 | 2.05986 | 2.04581 | 2.04088 | -2.43734 | 0.06547 | 0.65224 | -1.50000 | -2.47267 | 0.07412 | -4.21398 | 3.58768 | 0.79790 | 0.89044 | -4.86701 | 4.56612 | -1.77664 | 3.52220 | 0.14566 | 2.39044 | -2.39434 | 4.49199 | -0.86603 | -0.86603 | 1.00000 | 1.00000 | 0.00000 | -0.86603 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
27 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 17.0 | 0.534 | 0.01082 | 0.00800 | 0.58824 | 0.48975 | 16.0 | 5.50257 | 3.68232 | 3.04399 | 2.75072 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00002 | 0.00008 | 3.61478 | 11.06667 | 0.00000 | 0.00000 | 0.00308 | 0.00394 | 0.86262 | -1.04015 | 0.00105 | 0.00632 | 0.0 | 6.81651 | 5.07200 | 4.63403 | 4.43464 | -0.77188 | 1.47140 | -1.12676 | 1.12908 | -0.44787 | 0.91061 | -0.41250 | 2.94444 | 0.10627 | -0.19338 | -0.46327 | 4.04484 | 0.35938 | 1.47305 | 1.23303 | -1.32246 | -0.01540 | 3.13422 | -0.07359 | 0.02845 | -0.17926 | 0.44030 | 0.25740 | -0.42008 | 15.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
28 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 7.0 | 0.684 | 0.01429 | 0.00800 | 0.58824 | -7.01727 | 9.0 | 3.41112 | 2.93198 | 2.76403 | 2.65510 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00004 | 0.00011 | 2.47487 | 4.12500 | 0.00000 | 0.00000 | 0.00062 | 0.00066 | 0.94582 | -0.53655 | 0.00035 | 0.00053 | 0.0 | 3.47814 | 3.06459 | 2.97744 | 2.93354 | -2.72278 | 3.80692 | 0.47828 | -1.22188 | -4.39824 | 6.27410 | -1.33594 | 3.20785 | 0.05202 | 0.04768 | -1.02298 | 4.19414 | 1.38684 | -0.59906 | -0.42626 | 1.26956 | 3.37526 | -2.07996 | -0.24153 | -0.48127 | -0.30126 | -0.20801 | 0.28694 | 0.00000 | 8.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
29 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 10.0 | 0.722 | 0.00880 | 0.00800 | 0.58824 | -6.69937 | 5.0 | 1.99700 | 1.74307 | 1.64086 | 1.58177 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00126 | 0.00148 | 0.64779 | -1.27201 | 0.00035 | 0.00228 | 0.0 | 2.49154 | 2.32086 | 2.29239 | 2.28248 | 0.05068 | 3.42918 | -0.95150 | -0.24265 | 1.03056 | 0.68879 | 1.98742 | 3.40633 | -0.25258 | -0.43290 | 2.52979 | 4.88863 | 1.93675 | -0.02285 | 0.69891 | -0.19025 | 1.49924 | 4.19984 | 0.66689 | 0.00000 | 0.90000 | 0.00000 | -0.41039 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5.0 | 0.0 | 0.0 | 0.0 | 0.0 |
30 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 13.0 | 0.502 | 0.01077 | 0.00708 | 0.58824 | 2.82388 | 15.0 | 2.99232 | 2.39560 | 2.28385 | 2.23645 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00002 | 0.00009 | 3.47440 | 10.07143 | 0.00000 | 0.00000 | 0.00057 | 0.00061 | 1.31702 | 0.47490 | 0.00035 | 0.00044 | 0.0 | 3.62027 | 2.53284 | 2.37817 | 2.32447 | -0.96863 | 3.67242 | 0.16031 | 0.92080 | -0.56831 | 3.38800 | -0.45799 | 3.32493 | -0.06602 | -0.29421 | -0.42541 | 4.55334 | 0.51065 | -0.34748 | -0.22633 | -1.21500 | 0.14290 | 1.16534 | -0.11027 | -0.23508 | -0.10470 | 0.31410 | -0.12331 | -0.06186 | 14.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
31 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 16.0 | 0.766 | 0.01050 | 0.00800 | 0.58824 | -1.78823 | 9.0 | 4.89637 | 4.24750 | 3.96209 | 3.77614 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00004 | 0.00011 | 2.47487 | 4.12500 | 0.00000 | 0.00000 | 0.00250 | 0.00167 | -0.21385 | -1.27566 | 0.00228 | 0.00263 | 0.0 | 5.52075 | 4.82427 | 4.52905 | 4.35798 | -0.77027 | 5.21572 | -0.78815 | -1.20929 | 2.47464 | 8.43996 | -0.47779 | 3.40538 | 0.08396 | 0.27510 | -0.22894 | 4.71641 | 0.29249 | -1.81035 | 0.87211 | 1.48439 | -2.70358 | -3.72355 | 0.07173 | -0.48127 | -0.10879 | 0.55234 | 0.71431 | -0.54772 | 8.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
32 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 14.0 | 0.556 | 0.00829 | 0.00486 | 0.58824 | -0.58973 | 13.0 | 3.88711 | 2.81671 | 2.60025 | 2.52011 | 2.63792 | 2.34943 | 2.15735 | 2.03824 | 0.00013 | 0.00027 | 2.24947 | 4.02711 | 0.00000 | 0.00000 | 0.00089 | 0.00119 | 1.38576 | 1.08009 | 0.00018 | 0.00140 | 0.0 | 4.25612 | 2.95552 | 2.68223 | 2.58463 | 4.83459 | 4.94864 | -0.18881 | -1.15398 | 6.59093 | 8.05478 | 3.09346 | 4.88527 | 0.26075 | -0.66882 | 2.66400 | 7.62121 | -1.74113 | -0.06337 | 0.44957 | 0.48516 | -3.92693 | -0.43357 | 0.18862 | 0.39438 | 0.14682 | 0.54184 | 0.22107 | -0.22350 | 10.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
33 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 11.0 | 0.552 | 0.01055 | 0.00618 | 0.58824 | 2.39712 | 10.0 | 4.99704 | 3.63532 | 3.08752 | 2.81139 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00004 | 0.00011 | 2.66667 | 5.11111 | 0.00000 | 0.00000 | 0.00153 | 0.00149 | 0.87541 | -0.62089 | 0.00123 | 0.00140 | 0.0 | 7.31566 | 5.45661 | 4.81469 | 4.52393 | 0.83236 | 4.15184 | -0.28111 | -1.08049 | 1.06580 | 6.70447 | 1.24406 | 2.69265 | -0.26522 | 1.05486 | 1.02199 | 3.32144 | 0.41169 | -1.45919 | 0.01589 | 2.13535 | -0.04381 | -3.38303 | 0.32202 | 0.23281 | -0.32219 | -0.23644 | 0.01235 | 0.29013 | 9.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
34 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 15.0 | 0.642 | 0.01227 | 0.00960 | 0.58824 | 1.25803 | 7.0 | 3.09977 | 2.52581 | 2.35928 | 2.27912 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00341 | 0.00248 | -0.37657 | -1.59186 | 0.00439 | 0.00474 | 0.0 | 3.29503 | 2.72045 | 2.54979 | 2.47878 | -0.05119 | 6.04278 | 0.27836 | -1.82754 | -4.47422 | 11.13485 | 0.58122 | 3.63130 | -0.03857 | -0.47803 | 0.52825 | 5.29308 | 0.63241 | -2.41148 | -0.31693 | 1.34951 | 5.00247 | -5.84177 | 0.43038 | 0.00000 | -0.10714 | 0.00000 | 0.26197 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 |
35 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 155.0 | 0.508 | 0.00991 | 0.00805 | 0.58824 | -0.42833 | 19.0 | 5.85455 | 3.39665 | 2.73629 | 2.47435 | 6.14450 | 5.30493 | 4.65737 | 4.22642 | 0.00019 | 0.00030 | 1.90411 | 3.41793 | 0.00000 | 0.00035 | 0.00246 | 0.00305 | 2.28287 | 5.74268 | 0.00263 | 0.00298 | 0.0 | 10.14916 | 6.77565 | 5.61304 | 5.10254 | 2.67410 | 3.42036 | 0.19266 | -0.91998 | 2.63150 | 5.17201 | 2.06071 | 3.21164 | 0.07690 | -0.46515 | 2.07867 | 4.53899 | -0.61339 | -0.20872 | -0.11576 | 0.45483 | -0.55282 | -0.63302 | 0.34492 | 0.60264 | 0.08915 | 0.10770 | 0.13641 | -0.23588 | 12.0 | 0.0 | 0.0 | 5.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
36 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 8.0 | 0.592 | 0.01050 | 0.00250 | 0.58824 | 1.78362 | 13.0 | 4.98594 | 3.73277 | 3.34484 | 3.14838 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00119 | 0.00195 | 1.82931 | 1.96585 | 0.00035 | 0.00123 | 0.0 | 5.94227 | 4.56195 | 4.11552 | 3.88780 | 2.67663 | 3.76219 | 0.27819 | -0.02512 | 1.97000 | 3.54855 | 2.33018 | 2.79058 | 0.10451 | -0.35917 | 2.12800 | 3.86307 | -0.34645 | -0.97161 | -0.17368 | -0.33405 | 0.15800 | 0.31452 | 0.36281 | 0.00000 | 0.20194 | 0.00000 | 0.30967 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 |
37 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 7.0 | 0.680 | 0.00857 | 0.00171 | 0.58824 | 1.93836 | 11.0 | 4.07566 | 3.08016 | 2.75834 | 2.60050 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00096 | 0.00102 | 0.76312 | -0.53546 | 0.00088 | 0.00167 | 0.0 | 5.70701 | 4.31623 | 3.71452 | 3.40018 | -0.07165 | 3.62591 | 0.23135 | -0.96570 | -0.29284 | 5.35858 | 0.09019 | 3.43080 | 0.24998 | -0.54103 | -0.12534 | 4.84246 | 0.16184 | -0.19511 | 0.01863 | 0.42467 | 0.16751 | -0.51612 | -0.00941 | 0.00000 | 0.15597 | 0.00000 | 0.21452 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 11.0 | 0.0 | 0.0 | 0.0 | 0.0 |
38 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 11.0 | 0.708 | 0.01055 | 0.00436 | 0.58824 | -0.95500 | 18.0 | 6.88761 | 4.90787 | 4.26684 | 3.97746 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00002 | 0.00008 | 3.88057 | 13.05882 | 0.00000 | 0.00000 | 0.00145 | 0.00220 | 2.79437 | 7.70920 | 0.00079 | 0.00184 | 0.0 | 8.85612 | 6.06473 | 4.94178 | 4.41955 | 3.13993 | 3.54164 | -0.61831 | -0.23666 | 3.90105 | 4.52159 | 3.27974 | 3.73182 | -0.72614 | -0.15636 | 4.19628 | 4.14691 | 0.13981 | 0.19018 | -0.10783 | 0.08030 | 0.29523 | -0.37468 | -0.18595 | 0.16542 | 0.29423 | 0.40237 | 0.08256 | -0.11687 | 17.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
39 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 14.0 | 0.594 | 0.00771 | 0.00743 | 0.58824 | -1.74019 | 5.0 | 2.31446 | 2.09675 | 2.03835 | 2.00472 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00007 | 0.00014 | 1.50000 | 0.25000 | 0.00000 | 0.00000 | 0.00193 | 0.00136 | 0.09970 | -1.66048 | 0.00158 | 0.00263 | 0.0 | 2.38708 | 2.17998 | 2.14184 | 2.12819 | -1.78262 | 0.20368 | 0.62860 | -1.10755 | -1.90058 | 0.24214 | -2.22731 | 2.91861 | 0.19934 | -0.15092 | -2.37669 | 4.06299 | -0.44469 | 2.71494 | -0.42926 | 0.95663 | -0.47610 | 3.82086 | -0.20520 | 0.70711 | -0.10000 | -0.72548 | -0.20520 | -0.70711 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
40 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 22.0 | 0.624 | 0.00945 | 0.00873 | 0.58824 | 6.32857 | 5.0 | 3.08091 | 2.89372 | 2.81819 | 2.76894 | 2.77280 | 2.59875 | 2.47234 | 2.38151 | 0.00039 | 0.00037 | 0.35803 | -1.31520 | 0.00035 | 0.00062 | 0.00344 | 0.00173 | -1.46150 | 0.19888 | 0.00421 | 0.00035 | 0.0 | 2.99187 | 2.85131 | 2.79415 | 2.75509 | 0.05262 | 5.01438 | 1.49344 | 0.24142 | -2.25241 | 0.25560 | 3.43056 | 3.41126 | 0.25469 | -0.54745 | 3.34031 | 5.05623 | 3.37794 | -1.60312 | -1.23875 | -0.78887 | 5.59271 | 4.80063 | -0.30000 | -0.15390 | 0.30000 | 0.97468 | 0.00000 | -0.97468 | 2.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 |
41 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 11.0 | 0.722 | 0.01345 | 0.01273 | 0.58824 | 5.54536 | 4.0 | 2.88875 | 2.72496 | 2.60115 | 2.50216 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00009 | 0.00015 | 1.15470 | -0.66667 | 0.00000 | 0.00009 | 0.00303 | 0.00187 | -0.20109 | -1.72864 | 0.00333 | 0.00320 | 0.0 | 3.25445 | 3.15443 | 3.10448 | 3.06766 | 1.23155 | 5.39901 | -0.01229 | -1.96819 | 1.36026 | 10.28886 | 0.70353 | 3.12690 | 0.15536 | 0.05993 | 0.37808 | 4.03485 | -0.52802 | -2.27211 | 0.16765 | 2.02812 | -0.98218 | -6.25402 | 0.60000 | 0.25820 | 0.40000 | 0.77460 | 0.89443 | 0.00000 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
42 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 9.0 | 0.668 | 0.00578 | 0.00222 | 0.58824 | -2.77571 | 8.0 | 2.16749 | 1.88883 | 1.79540 | 1.73694 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00145 | 0.00204 | 1.03500 | -0.78674 | 0.00026 | 0.00215 | 0.0 | 4.34374 | 2.56097 | 2.36269 | 2.29856 | 2.53492 | 2.59983 | -1.36279 | 0.28053 | 3.80766 | 1.78704 | -0.25875 | 2.82851 | -0.19201 | -0.67589 | 0.09948 | 4.34943 | -2.79367 | 0.22869 | 1.17078 | -0.95642 | -3.70818 | 2.56239 | 0.09876 | 0.00000 | -0.77337 | 0.00000 | 0.60020 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 8.0 | 0.0 | 0.0 | 0.0 | 0.0 |
43 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 113.0 | 0.512 | 0.00995 | 0.00733 | 0.58824 | -2.00509 | 20.0 | 6.74713 | 3.68113 | 2.88381 | 2.58504 | 4.15332 | 3.58803 | 3.23876 | 3.02163 | 0.00027 | 0.00057 | 2.39311 | 5.02443 | 0.00000 | 0.00009 | 0.00177 | 0.00260 | 2.11154 | 3.74859 | 0.00079 | 0.00250 | 0.0 | 8.94449 | 6.42990 | 5.67481 | 5.32570 | -0.09805 | 3.14397 | -0.49363 | 0.64348 | -0.04583 | 3.89071 | -1.99564 | 2.65555 | 0.37008 | 0.16371 | -2.18004 | 3.28539 | -1.89759 | -0.48842 | 0.86371 | -0.47977 | -2.13421 | -0.60532 | 0.21827 | 0.42319 | 0.33183 | 0.28986 | 0.17629 | 0.02174 | 15.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
44 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 12.0 | 0.500 | 0.01233 | 0.00900 | 0.58824 | 0.57489 | 6.0 | 3.24710 | 2.73463 | 2.51312 | 2.38014 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00088 | 0.00102 | 0.81714 | -0.61419 | 0.00061 | 0.00123 | 0.0 | 4.34788 | 3.64370 | 3.37864 | 3.22883 | -0.17094 | 5.77074 | 0.01101 | -1.73267 | -0.60706 | 10.34393 | -1.15237 | 3.33799 | -0.12267 | -0.08764 | -1.14116 | 4.51148 | -0.98143 | -2.43275 | -0.13369 | 1.64502 | -0.53410 | -5.83244 | 0.15430 | 0.00000 | -0.77143 | 0.00000 | 0.30861 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 |
45 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 4.0 | 0.522 | 0.01400 | 0.00300 | 0.58824 | 4.33451 | 13.0 | 4.12796 | 2.97077 | 2.72528 | 2.63426 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00116 | 0.00130 | 1.03168 | -0.11086 | 0.00070 | 0.00228 | 0.0 | 4.61871 | 3.15639 | 2.82427 | 2.70082 | 0.25226 | 3.38661 | -0.06225 | -0.34986 | -0.18579 | 4.13469 | -0.16881 | 3.74530 | 0.40530 | 0.30509 | -0.41375 | 4.52546 | -0.42107 | 0.35870 | 0.46755 | 0.65495 | -0.22797 | 0.39078 | 0.15494 | 0.00000 | -0.05540 | 0.00000 | 0.32127 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 |
46 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 21.0 | 0.548 | 0.00838 | 0.00514 | 0.58824 | 4.53188 | 12.0 | 3.12600 | 2.47388 | 2.35503 | 2.31202 | 3.00000 | 3.00000 | 3.00000 | 3.00000 | 0.00009 | 0.00015 | 1.15470 | -0.66667 | 0.00000 | 0.00009 | 0.00072 | 0.00085 | 1.28302 | 0.65645 | 0.00044 | 0.00105 | 0.0 | 4.21878 | 2.81642 | 2.53027 | 2.42820 | 1.16723 | 4.26334 | -0.18867 | -1.24497 | 1.38323 | 6.11364 | -0.81287 | 3.32753 | 0.21199 | -0.52232 | -1.18314 | 4.45090 | -1.98009 | -0.93582 | 0.40066 | 0.72265 | -2.56637 | -1.66274 | 0.12094 | 0.19756 | -0.23011 | 0.19899 | -0.07488 | -0.02787 | 9.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 |
47 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 16.0 | 0.650 | 0.00950 | 0.00750 | 0.58824 | 8.47165 | 9.0 | 4.22717 | 3.33482 | 3.06665 | 2.94460 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00004 | 0.00011 | 2.47487 | 4.12500 | 0.00000 | 0.00000 | 0.00279 | 0.00285 | 0.20035 | -1.93174 | 0.00088 | 0.00596 | 0.0 | 12.15795 | 8.05429 | 5.47132 | 4.39546 | -4.55463 | 8.23351 | 0.25214 | -1.89416 | -11.51461 | 15.60629 | -1.47001 | 4.99206 | -0.39627 | -0.71713 | -0.44281 | 7.56053 | 3.08461 | -3.24145 | -0.64841 | 1.17702 | 11.07180 | -8.04575 | 0.65443 | 0.00000 | -0.66109 | -0.14569 | 0.33693 | 0.00000 | 8.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
48 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 14.0 | 0.588 | 0.01057 | 0.00571 | 0.58824 | 6.36465 | 10.0 | 3.78832 | 3.09989 | 2.90581 | 2.80848 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00100 | 0.00101 | 0.85120 | -0.66075 | 0.00070 | 0.00101 | 0.0 | 4.43526 | 3.44633 | 3.18527 | 3.04667 | 3.27035 | 2.52384 | -0.51627 | -0.51688 | 3.53051 | 2.66443 | -0.01743 | 3.17925 | -0.20268 | -0.36094 | 0.27929 | 4.23885 | -3.28778 | 0.65541 | 0.31359 | 0.15595 | -3.25122 | 1.57442 | 0.38771 | 0.00000 | -0.30395 | 0.00000 | 0.01841 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 |
49 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 12.0 | 0.568 | 0.01167 | 0.00567 | 0.58824 | -0.72892 | 20.0 | 5.30202 | 3.45552 | 3.03018 | 2.85178 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00002 | 0.00008 | 4.12948 | 15.05263 | 0.00000 | 0.00000 | 0.00133 | 0.00188 | 1.59481 | 1.48726 | 0.00035 | 0.00184 | 0.0 | 5.54678 | 3.80406 | 3.33786 | 3.14619 | 0.19386 | 2.20777 | 0.75952 | -0.35188 | -0.49430 | 2.37609 | -0.28887 | 2.54571 | -0.16954 | -0.37978 | -0.38571 | 3.69878 | -0.48273 | 0.33794 | -0.92905 | -0.02790 | 0.10860 | 1.32269 | 0.21757 | -0.14063 | -0.22552 | -0.06173 | 0.44720 | 0.13925 | 19.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
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3890 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 35.0 | 0.546 | 0.01040 | 0.00971 | 0.58824 | -0.04631 | 2.0 | 1.99295 | 1.98599 | 1.97916 | 1.97252 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00035 | 0.00035 | 0.00000 | -2.00000 | 0.00035 | 0.00035 | 0.00070 | 0.00070 | 0.00000 | -2.00000 | 0.00070 | 0.00070 | 0.0 | 2.00709 | 2.00709 | 2.00709 | 2.00709 | 0.13431 | 0.01747 | 0.00000 | -2.00000 | 0.13431 | 0.01747 | -0.83830 | 3.25411 | -0.22137 | -0.38203 | -0.37380 | 4.67880 | -0.97261 | 3.23664 | -0.22137 | 1.61797 | -0.50811 | 4.66133 | -1.00000 | -1.00000 | 0.00000 | 1.00000 | 0.00000 | 0.00000 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3891 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 12.0 | 0.678 | 0.01133 | 0.00600 | 0.58824 | -1.96134 | 9.0 | 2.34748 | 1.96797 | 1.85705 | 1.79224 | 2.82843 | 2.66667 | 2.52982 | 2.42283 | 0.00016 | 0.00024 | 1.23801 | 0.17036 | 0.00000 | 0.00035 | 0.00113 | 0.00095 | 0.66561 | -0.77874 | 0.00070 | 0.00105 | 0.0 | 2.89965 | 2.36276 | 2.28617 | 2.26012 | 3.69813 | 4.28216 | -0.18202 | -1.43175 | 4.58239 | 7.05837 | 1.80314 | 4.19068 | -0.23854 | -0.14189 | 1.94261 | 5.08820 | -1.89498 | -0.09147 | -0.05652 | 1.28986 | -2.63977 | -1.97017 | 0.23935 | 0.26962 | 0.05959 | 0.34007 | -0.11716 | 0.53785 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3892 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 7.0 | 0.502 | 0.00686 | 0.00686 | 0.58824 | 1.19394 | 3.0 | 2.79411 | 2.64244 | 2.53467 | 2.45755 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00111 | 0.00071 | 0.67456 | -1.50000 | 0.00070 | 0.00079 | 0.0 | 3.50116 | 3.40962 | 3.30315 | 3.19061 | -0.65993 | 5.97250 | -0.66864 | -1.50000 | 2.73126 | 6.69933 | -0.84049 | 4.35156 | 0.08062 | -0.76016 | -1.05536 | 6.40806 | -0.18056 | -1.62094 | 0.74927 | 0.73984 | -3.78662 | -0.29127 | 0.50000 | 0.00000 | -1.00000 | 0.00000 | 0.50000 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3893 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 8.0 | 0.598 | 0.01050 | 0.00650 | 0.58824 | -0.14972 | 12.0 | 4.36796 | 3.52724 | 3.26530 | 3.11847 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00008 | 0.00026 | 3.01511 | 7.09091 | 0.00000 | 0.00000 | 0.00083 | 0.00082 | 0.82862 | -0.22496 | 0.00088 | 0.00105 | 0.0 | 4.95453 | 3.94156 | 3.65491 | 3.52141 | 0.60142 | 3.63817 | 0.67837 | -0.51362 | -0.43729 | 2.91604 | 2.00700 | 2.86744 | 0.34146 | 0.08591 | 1.88838 | 3.82695 | 1.40558 | -0.77074 | -0.33691 | 0.59954 | 2.32567 | 0.91091 | -0.07750 | 0.31119 | -0.07830 | -0.04528 | -0.00725 | 0.30570 | 11.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3894 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 84.0 | 0.502 | 0.01010 | 0.00833 | 0.58824 | -1.38744 | 13.0 | 4.53775 | 2.87165 | 2.39710 | 2.20146 | 1.92210 | 1.85460 | 1.79954 | 1.75636 | 0.00007 | 0.00018 | 2.25074 | 3.52924 | 0.00000 | 0.00000 | 0.00170 | 0.00254 | 2.44181 | 5.16924 | 0.00088 | 0.00158 | 0.0 | 7.51793 | 5.96433 | 5.32599 | 4.96297 | -0.95884 | 3.01748 | 0.20521 | -1.08126 | -1.18922 | 5.29116 | -1.31554 | 2.74888 | 0.08225 | -0.45109 | -1.45400 | 4.01545 | -0.35670 | -0.26859 | -0.12296 | 0.63017 | -0.26479 | -1.27571 | 0.49448 | 0.28031 | 0.22865 | 0.12264 | 0.40496 | 0.29701 | 11.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3895 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 10.0 | 0.748 | 0.00800 | 0.00360 | 0.58824 | 7.09121 | 14.0 | 4.03782 | 3.37776 | 3.23355 | 3.16420 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00003 | 0.00009 | 3.32820 | 9.07692 | 0.00000 | 0.00000 | 0.00108 | 0.00081 | 0.00027 | -1.16753 | 0.00123 | 0.00132 | 0.0 | 3.87232 | 3.32621 | 3.20765 | 3.15387 | 1.71468 | 3.20718 | 1.29100 | 1.36655 | 1.19478 | 1.79122 | 1.28832 | 2.94894 | 0.62415 | 0.81085 | 1.03079 | 3.52578 | -0.42635 | -0.25824 | -0.66685 | -0.55570 | -0.16399 | 1.73456 | -0.21548 | 0.11021 | 0.49052 | -0.17354 | -0.52108 | -0.17201 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3896 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 102.0 | 0.510 | 0.00953 | 0.00733 | 0.58824 | 8.22741 | 19.0 | 5.48391 | 3.29216 | 2.75663 | 2.53471 | 5.61739 | 5.27248 | 4.98530 | 4.75823 | 0.00031 | 0.00050 | 1.36021 | 0.56834 | 0.00000 | 0.00062 | 0.00131 | 0.00121 | 0.46766 | -1.19720 | 0.00105 | 0.00246 | 0.0 | 6.82675 | 4.27060 | 3.65144 | 3.41783 | 0.03237 | 2.15412 | -0.28014 | -1.17742 | 0.68589 | 3.75932 | -0.12520 | 3.16018 | 0.20805 | 0.10889 | -0.30581 | 4.33227 | -0.15757 | 1.00607 | 0.48819 | 1.28631 | -0.99170 | 0.57295 | 0.52462 | 0.34155 | 0.00443 | 0.31034 | 0.10448 | -0.24363 | 13.0 | 0.0 | 0.0 | 2.0 | 0.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 |
3897 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 12.0 | 0.592 | 0.01433 | 0.01433 | 0.58824 | 1.61145 | 5.0 | 3.22707 | 2.73917 | 2.58047 | 2.51219 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00077 | 0.00056 | -0.03516 | -1.58105 | 0.00070 | 0.00105 | 0.0 | 3.83767 | 3.07617 | 2.77667 | 2.64554 | 1.78549 | 0.31469 | -0.10776 | -1.13944 | 1.81652 | 0.38518 | -0.40617 | 5.19902 | 0.28648 | -0.36438 | -0.24065 | 7.50796 | -2.19166 | 4.88433 | 0.39424 | 0.77506 | -2.05716 | 7.12278 | -0.46169 | 0.00000 | -0.30000 | 0.00000 | -0.66689 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3898 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 106.0 | 0.502 | 0.01060 | 0.00785 | 0.58824 | -4.80533 | 22.0 | 6.35757 | 3.10752 | 2.44399 | 2.21863 | 5.35726 | 4.80615 | 4.38925 | 4.09286 | 0.00016 | 0.00031 | 1.97890 | 3.19459 | 0.00000 | 0.00026 | 0.00080 | 0.00089 | 0.67698 | -1.18346 | 0.00035 | 0.00158 | 0.0 | 12.50735 | 8.26000 | 7.09040 | 6.56389 | -2.09993 | 2.77559 | 0.31064 | -0.89750 | -2.28163 | 3.71625 | -1.17049 | 3.16546 | -0.17853 | -0.05807 | -1.34130 | 4.30272 | 0.92945 | 0.38987 | -0.48917 | 0.83943 | 0.94033 | 0.58647 | 0.70900 | 0.49655 | 0.21688 | 0.34003 | -0.00580 | 0.26595 | 16.0 | 0.0 | 0.0 | 3.0 | 0.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 |
3899 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 18.0 | 0.688 | 0.00978 | 0.00689 | 0.58824 | 3.66341 | 13.0 | 4.07741 | 2.87773 | 2.57900 | 2.44604 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00003 | 0.00009 | 3.17543 | 8.08333 | 0.00000 | 0.00000 | 0.00190 | 0.00151 | 0.08302 | -1.55419 | 0.00211 | 0.00316 | 0.0 | 4.77054 | 3.22469 | 2.89611 | 2.77592 | 1.33223 | 3.24292 | -0.56423 | -0.95020 | 2.18328 | 4.39877 | 0.24916 | 2.93628 | 0.56184 | 0.52871 | 0.03954 | 3.95627 | -1.08307 | -0.30665 | 1.12607 | 1.47891 | -2.14374 | -0.44251 | 0.04045 | 0.03890 | -0.24101 | -0.34959 | 0.22407 | 0.38576 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3900 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 114.0 | 0.512 | 0.01028 | 0.00775 | 0.58824 | 5.24365 | 17.0 | 5.17003 | 3.30977 | 2.79423 | 2.56633 | 3.00000 | 3.00000 | 3.00000 | 3.00000 | 0.00006 | 0.00013 | 1.69734 | 0.88095 | 0.00000 | 0.00000 | 0.00252 | 0.00415 | 2.74827 | 7.17138 | 0.00158 | 0.00175 | 0.0 | 7.67331 | 4.70102 | 3.92419 | 3.62420 | -1.67586 | 3.65251 | -0.10977 | -0.86474 | -1.52616 | 5.43102 | -0.79929 | 4.01976 | 0.02380 | -0.94035 | -0.81580 | 6.75675 | 0.87658 | 0.36725 | 0.13357 | -0.07561 | 0.71037 | 1.32572 | 0.14822 | 0.38149 | -0.18677 | 0.19110 | -0.04957 | -0.06299 | 14.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 |
3901 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 13.0 | 0.612 | 0.01015 | 0.00677 | 0.58824 | 2.84308 | 14.0 | 4.44711 | 3.42105 | 3.11550 | 2.97538 | 2.00000 | 2.00000 | 2.00000 | 2.00000 | 0.00005 | 0.00012 | 2.04124 | 2.16667 | 0.00000 | 0.00000 | 0.00088 | 0.00102 | 1.94846 | 3.78634 | 0.00079 | 0.00123 | 0.0 | 5.01934 | 3.60951 | 3.23582 | 3.07271 | 0.57595 | 2.31764 | -0.48875 | -0.59501 | 0.85832 | 3.00944 | 0.29412 | 2.83524 | -0.06535 | 0.01268 | 0.35592 | 3.99596 | -0.28183 | 0.51760 | 0.42340 | 0.60769 | -0.50240 | 0.98652 | 0.47187 | 0.25924 | -0.16428 | 0.20668 | 0.45525 | -0.20255 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 |
3902 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 5.0 | 0.604 | 0.01120 | 0.00400 | 0.58824 | 1.92499 | 12.0 | 3.23429 | 2.50439 | 2.31017 | 2.21530 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00181 | 0.00181 | 0.56061 | -0.81779 | 0.00167 | 0.00333 | 0.0 | 5.28466 | 3.46261 | 2.94744 | 2.74855 | 0.88270 | 4.22664 | 0.01003 | -1.64945 | 0.55457 | 8.37687 | 2.12153 | 4.02393 | 0.43722 | -0.58338 | 1.50003 | 5.95619 | 1.23883 | -0.20271 | 0.42719 | 1.06607 | 0.94546 | -2.42067 | 0.11653 | 0.00000 | 0.10097 | 0.00000 | 0.09288 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3903 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 61.0 | 0.660 | 0.00970 | 0.01023 | 0.58824 | 0.52475 | 3.0 | 1.92696 | 1.82714 | 1.76144 | 1.71321 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00027 | 0.00039 | 0.70711 | -1.50000 | 0.00000 | 0.00041 | 0.00064 | 0.00050 | -0.17280 | -1.50000 | 0.00070 | 0.00061 | 0.0 | 2.13778 | 2.11619 | 2.11372 | 2.11289 | 0.56311 | 0.06590 | -0.24014 | -1.50000 | 0.57385 | 0.08017 | -2.14069 | 3.56791 | -0.47185 | -0.05073 | -1.67974 | 5.13655 | -2.70381 | 3.50202 | -0.23171 | 1.44927 | -2.25359 | 5.05638 | -0.50000 | 0.00000 | 1.00000 | 0.86603 | -0.50000 | 0.00000 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3904 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 14.0 | 0.640 | 0.00914 | 0.00400 | 0.58824 | 1.70972 | 16.0 | 6.92076 | 4.84853 | 4.09715 | 3.72255 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00002 | 0.00008 | 3.61478 | 11.06667 | 0.00000 | 0.00000 | 0.00154 | 0.00150 | 0.39906 | -1.39734 | 0.00114 | 0.00276 | 0.0 | 7.95321 | 5.81689 | 5.04699 | 4.66758 | -1.21537 | 2.48118 | 0.05781 | -1.50555 | -1.14758 | 4.15014 | -1.79734 | 3.28830 | -0.48191 | 1.07928 | -1.80506 | 4.18125 | -0.58197 | 0.80713 | -0.53972 | 2.58483 | -0.65748 | 0.03111 | 0.72713 | 0.25261 | 0.05748 | 0.20191 | 0.31354 | -0.08402 | 15.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3905 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 29.0 | 0.568 | 0.00745 | 0.00690 | 0.58824 | 4.29791 | 4.0 | 2.41526 | 2.21789 | 2.16109 | 2.13510 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00024 | 0.00042 | 1.15470 | -0.66667 | 0.00000 | 0.00024 | 0.00184 | 0.00203 | 0.99470 | -0.80437 | 0.00096 | 0.00193 | 0.0 | 2.41431 | 2.23350 | 2.18429 | 2.16471 | 4.51894 | 0.53050 | -0.23270 | -1.41362 | 4.57480 | 0.74817 | 5.44882 | 4.42441 | 0.07105 | -0.78695 | 5.19657 | 6.85848 | 0.92988 | 3.89391 | 0.30375 | 0.62667 | 0.62176 | 6.11031 | -0.40000 | 0.25820 | 0.80000 | 0.77460 | -1.00000 | 0.57735 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3906 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 22.0 | 0.518 | 0.00964 | 0.00509 | 0.58824 | -1.13387 | 18.0 | 4.89524 | 3.34905 | 2.85253 | 2.60875 | 2.77280 | 2.59875 | 2.47234 | 2.38151 | 0.00011 | 0.00026 | 2.37238 | 4.35455 | 0.00000 | 0.00000 | 0.00157 | 0.00184 | 1.36070 | 1.65548 | 0.00105 | 0.00259 | 0.0 | 5.35584 | 4.18321 | 3.94290 | 3.84087 | 2.07489 | 4.16696 | -0.82195 | -0.28427 | 2.81709 | 5.37793 | 1.24771 | 4.79928 | -0.54734 | -0.61515 | 2.01622 | 6.65575 | -0.82718 | 0.63232 | 0.27460 | -0.33088 | -0.80087 | 1.27782 | 0.20770 | 0.38102 | 0.03776 | 0.25393 | 0.02342 | -0.44953 | 15.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 |
3907 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 13.0 | 0.682 | 0.00954 | 0.00585 | 0.58824 | 4.74434 | 12.0 | 4.57396 | 3.73670 | 3.54991 | 3.47639 | 2.00000 | 2.00000 | 2.00000 | 2.00000 | 0.00006 | 0.00013 | 1.78885 | 1.20000 | 0.00000 | 0.00000 | 0.00079 | 0.00096 | 1.01447 | -0.19530 | 0.00018 | 0.00132 | 0.0 | 4.38802 | 3.66631 | 3.50193 | 3.43895 | 3.26424 | 2.06875 | -0.89184 | -0.20136 | 3.60329 | 2.51234 | 2.11023 | 2.68011 | -0.19739 | -0.12865 | 2.16831 | 3.78143 | -1.15402 | 0.61136 | 0.69445 | 0.07271 | -1.43498 | 1.26910 | 0.08759 | -0.19781 | 0.15305 | -0.06642 | 0.58800 | -0.38865 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 |
3908 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 6.0 | 0.636 | 0.00800 | 0.00200 | 0.58824 | 1.10175 | 12.0 | 4.16884 | 3.30927 | 3.09335 | 2.98781 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00005 | 0.00017 | 3.01511 | 7.09091 | 0.00000 | 0.00000 | 0.00165 | 0.00212 | 1.03581 | -0.77327 | 0.00053 | 0.00211 | 0.0 | 4.27399 | 3.46843 | 3.25624 | 3.14589 | -2.07710 | 3.55125 | 0.25956 | -0.78117 | -2.90116 | 3.60143 | -0.22726 | 3.03977 | -0.48861 | 0.35093 | -0.07063 | 3.93333 | 1.84984 | -0.51148 | -0.74818 | 1.13210 | 2.83052 | 0.33190 | 0.22324 | -0.21912 | 0.23509 | -0.08891 | -0.16017 | -0.30570 | 11.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3909 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 83.0 | 0.500 | 0.01104 | 0.00843 | 0.58824 | 0.70319 | 17.0 | 4.19036 | 2.54728 | 2.12744 | 1.96592 | 2.82843 | 2.66667 | 2.52982 | 2.42283 | 0.00008 | 0.00019 | 2.24944 | 3.92509 | 0.00000 | 0.00000 | 0.00175 | 0.00216 | 1.07979 | -0.37579 | 0.00070 | 0.00193 | 0.0 | 6.19453 | 5.00159 | 4.66783 | 4.49063 | 0.22576 | 2.71678 | 0.88666 | 0.46128 | 0.41311 | 3.00892 | 0.03489 | 2.92184 | -0.45784 | 1.82999 | 0.28732 | 3.12200 | -0.19087 | 0.20506 | -1.34450 | 1.36871 | -0.12578 | 0.11307 | 0.70049 | 0.48209 | -0.12961 | 0.39995 | -0.26751 | 0.03506 | 14.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3910 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 2.0 | 0.552 | 0.01000 | 0.00200 | 0.58824 | -3.68764 | 5.0 | 1.77954 | 1.41801 | 1.32392 | 1.28557 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00126 | 0.00185 | 1.38261 | 0.08859 | 0.00053 | 0.00088 | 0.0 | 3.60124 | 3.16800 | 3.07371 | 3.03732 | -0.62851 | 3.20062 | 0.59857 | -0.77172 | -0.44279 | 3.01469 | -1.59032 | 3.85277 | -0.01639 | -0.60947 | -1.60086 | 5.95597 | -0.96181 | 0.65215 | -0.61496 | 0.16224 | -1.15807 | 2.94128 | 0.56429 | 0.00000 | -0.30000 | 0.00000 | -0.05130 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 5.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3911 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 91.0 | 0.506 | 0.01020 | 0.00774 | 0.58824 | 0.55731 | 22.0 | 7.48498 | 3.66354 | 2.79909 | 2.50552 | 2.82843 | 2.66667 | 2.52982 | 2.42283 | 0.00006 | 0.00017 | 2.70859 | 6.37337 | 0.00000 | 0.00000 | 0.00183 | 0.00261 | 1.40591 | 0.50859 | 0.00026 | 0.00215 | 0.0 | 11.92561 | 8.75180 | 7.77395 | 7.24245 | 1.03313 | 3.75099 | 0.54246 | -0.89686 | 0.31371 | 5.63269 | 0.29563 | 3.51229 | -0.04666 | -0.59019 | 0.47967 | 5.52188 | -0.73750 | -0.23870 | -0.58912 | 0.30667 | 0.16596 | -0.11081 | 0.07063 | 0.13004 | -0.03068 | 0.50770 | -0.12240 | 0.07100 | 19.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3912 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 151.0 | 0.518 | 0.00951 | 0.00787 | 0.58824 | 2.98436 | 22.0 | 4.79061 | 2.77543 | 2.37140 | 2.20491 | 4.77184 | 4.61337 | 4.50256 | 4.42243 | 0.00016 | 0.00031 | 1.58108 | 0.74727 | 0.00000 | 0.00000 | 0.00094 | 0.00151 | 2.81772 | 7.98322 | 0.00035 | 0.00114 | 0.0 | 6.05676 | 3.81469 | 3.31266 | 3.12908 | 1.10023 | 2.97822 | 0.01382 | -1.27553 | 1.07379 | 5.21273 | 1.09040 | 3.74454 | -0.13808 | -0.93434 | 1.08674 | 5.71014 | -0.00983 | 0.76632 | -0.15190 | 0.34119 | 0.01295 | 0.49742 | 0.17786 | 0.43207 | 0.11671 | 0.38642 | -0.10292 | -0.33851 | 17.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 2.0 | 1.0 |
3913 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 13.0 | 0.630 | 0.01323 | 0.00800 | 0.58824 | 0.75057 | 16.0 | 6.91896 | 4.86454 | 4.07401 | 3.66809 | 2.90747 | 2.83474 | 2.77951 | 2.73824 | 0.00010 | 0.00022 | 1.81877 | 1.53532 | 0.00000 | 0.00000 | 0.00375 | 0.00347 | 0.33791 | -1.56539 | 0.00263 | 0.00697 | 0.0 | 9.12965 | 7.32688 | 6.55855 | 6.07727 | 4.02290 | 6.08731 | -0.27459 | -1.87659 | 8.98721 | 11.59608 | 3.19514 | 4.34103 | -0.14888 | -0.96946 | 3.54651 | 7.23862 | -0.82777 | -1.74628 | 0.12571 | 0.90713 | -5.44070 | -4.35746 | -0.19062 | 0.28277 | 0.22798 | 0.27821 | -0.16864 | -0.03241 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 2.0 |
3914 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 9.0 | 0.762 | 0.00978 | 0.00622 | 0.58824 | -9.35799 | 7.0 | 2.30220 | 1.81856 | 1.66481 | 1.59124 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00075 | 0.00112 | 1.61008 | 1.05570 | 0.00018 | 0.00070 | 0.0 | 3.03742 | 2.64576 | 2.57088 | 2.54377 | -6.76205 | 2.98453 | 0.45958 | -1.52473 | -8.56583 | 5.13575 | -3.67435 | 3.66950 | 0.37819 | -0.48005 | -3.92847 | 5.32448 | 3.08769 | 0.68496 | -0.08139 | 1.04468 | 4.63735 | 0.18873 | 0.43404 | 0.00000 | 0.22237 | 0.00000 | -0.38188 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3915 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 76.0 | 0.516 | 0.00979 | 0.00747 | 0.58824 | 1.71925 | 21.0 | 6.99580 | 3.45877 | 2.69343 | 2.42631 | 5.43755 | 5.04503 | 4.77626 | 4.58543 | 0.00021 | 0.00038 | 1.57251 | 1.06981 | 0.00000 | 0.00035 | 0.00197 | 0.00186 | 1.13700 | 0.58282 | 0.00193 | 0.00175 | 0.0 | 17.21917 | 11.60950 | 9.67245 | 8.46040 | 0.09687 | 3.72135 | 0.38822 | -0.00054 | -0.61634 | 3.09162 | -0.48449 | 3.46041 | 0.33418 | -0.30837 | -0.92912 | 4.77963 | -0.58136 | -0.26094 | -0.05403 | -0.30783 | -0.31278 | 1.68800 | 0.18185 | 0.03914 | -0.40442 | -0.11697 | 0.18194 | -0.27039 | 15.0 | 0.0 | 2.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 |
3916 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 112.0 | 0.528 | 0.01046 | 0.00782 | 0.58824 | 1.81677 | 23.0 | 7.57315 | 3.85993 | 2.96436 | 2.64383 | 6.84809 | 5.95042 | 5.32537 | 4.90171 | 0.00024 | 0.00040 | 1.86749 | 2.95482 | 0.00000 | 0.00035 | 0.00142 | 0.00174 | 1.86877 | 3.03549 | 0.00123 | 0.00167 | 0.0 | 10.93942 | 7.68449 | 6.67322 | 6.18765 | 2.36441 | 2.22007 | -0.84610 | 1.31184 | 2.10160 | 3.17942 | 2.64329 | 2.59866 | 0.16769 | -0.19037 | 2.71941 | 3.78210 | 0.27889 | 0.37859 | 1.01379 | -1.50221 | 0.61782 | 0.60268 | -0.19295 | -0.17861 | -0.36084 | 0.09873 | 0.11125 | -0.24166 | 15.0 | 0.0 | 4.0 | 0.0 | 0.0 | 3.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3917 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 9.0 | 0.576 | 0.00800 | 0.00267 | 0.58824 | 1.83312 | 14.0 | 4.63911 | 3.35851 | 3.02027 | 2.87246 | 1.92210 | 1.85460 | 1.79954 | 1.75636 | 0.00007 | 0.00018 | 2.37955 | 4.15020 | 0.00000 | 0.00000 | 0.00125 | 0.00135 | 0.83259 | -0.71452 | 0.00061 | 0.00206 | 0.0 | 5.33841 | 3.76101 | 3.30327 | 3.10519 | -0.88776 | 4.46531 | 0.14952 | -1.31218 | -1.19145 | 8.28916 | 0.02006 | 4.20074 | -0.57565 | -0.20417 | 0.81522 | 5.87984 | 0.90782 | -0.26456 | -0.72518 | 1.10801 | 2.00668 | -2.40932 | 0.35786 | 0.06171 | -0.01991 | 0.22896 | 0.24142 | 0.38586 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3918 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 69.0 | 0.516 | 0.00916 | 0.00678 | 0.58824 | -4.74014 | 17.0 | 5.05380 | 3.22572 | 2.73087 | 2.50748 | 1.92210 | 1.85460 | 1.79954 | 1.75636 | 0.00006 | 0.00016 | 2.73145 | 6.02398 | 0.00000 | 0.00000 | 0.00212 | 0.00302 | 1.44759 | 0.91861 | 0.00053 | 0.00333 | 0.0 | 8.54962 | 5.47253 | 4.56352 | 4.18796 | 1.30662 | 4.36943 | -0.19252 | -0.97376 | 2.41662 | 6.74726 | 1.61183 | 4.02002 | 0.11366 | -0.69857 | 1.45961 | 6.01844 | 0.30521 | -0.34941 | 0.30618 | 0.27520 | -0.95701 | -0.72882 | -0.08406 | 0.49497 | 0.17204 | 0.29038 | 0.26938 | 0.17066 | 15.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3919 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 16.0 | 0.764 | 0.01100 | 0.01025 | 0.58824 | -7.14003 | 3.0 | 2.79973 | 2.61545 | 2.46534 | 2.35268 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00023 | 0.00033 | 0.70711 | -1.50000 | 0.00000 | 0.00035 | 0.00275 | 0.00183 | -0.68756 | -1.50000 | 0.00386 | 0.00202 | 0.0 | 3.16055 | 3.07170 | 3.00644 | 2.96054 | 2.09744 | 6.34960 | -0.70699 | -1.50000 | 6.54086 | 6.75783 | -1.14915 | 4.10394 | 0.62419 | -0.28203 | -2.11572 | 5.70244 | -3.24659 | -2.24566 | 1.33118 | 1.21797 | -8.65658 | -1.05539 | -0.50000 | -0.86603 | 0.50000 | 0.86603 | -0.50000 | -0.86603 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3920 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 47.0 | 0.514 | 0.00936 | 0.00613 | 0.58824 | -8.65552 | 20.0 | 5.28190 | 3.17872 | 2.71023 | 2.51446 | 5.68347 | 5.35828 | 5.05359 | 4.79107 | 0.00025 | 0.00042 | 1.43122 | 0.94932 | 0.00000 | 0.00062 | 0.00109 | 0.00125 | 1.54049 | 1.94898 | 0.00070 | 0.00114 | 0.0 | 6.68123 | 4.04289 | 3.45488 | 3.23643 | -3.52182 | 3.04835 | 0.48959 | -0.02563 | -3.84898 | 3.96495 | -4.32252 | 3.50528 | 0.34005 | -0.58195 | -4.81274 | 5.30115 | -0.80070 | 0.45693 | -0.14954 | -0.55632 | -0.96376 | 1.33621 | -0.00878 | 0.47818 | 0.16769 | 0.47158 | -0.10817 | -0.04738 | 14.0 | 0.0 | 0.0 | 0.0 | 3.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 |
3921 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 18.0 | 0.596 | 0.01044 | 0.01000 | 0.58824 | 3.22817 | 8.0 | 3.46777 | 2.70118 | 2.52371 | 2.45651 | 1.78233 | 1.63739 | 1.55027 | 1.49844 | 0.00017 | 0.00033 | 1.82409 | 1.76654 | 0.00000 | 0.00009 | 0.00386 | 0.00219 | -0.50122 | -1.20586 | 0.00491 | 0.00303 | 0.0 | 4.27954 | 3.00308 | 2.68585 | 2.56892 | 3.00756 | 0.25469 | 0.81517 | -0.72598 | 2.93063 | 0.22823 | 1.02268 | 3.38571 | -0.27042 | -0.74825 | 1.35542 | 5.43727 | -1.98488 | 3.13101 | -1.08560 | -0.02227 | -1.57520 | 5.20904 | 0.28226 | 0.02352 | -0.14372 | 0.07986 | -0.24398 | 0.17146 | 6.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3922 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 7.0 | 0.544 | 0.00800 | 0.00457 | 0.58824 | -0.24922 | 7.0 | 2.32375 | 2.10920 | 2.06849 | 2.04869 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00073 | 0.00088 | 0.87426 | -0.61540 | 0.00018 | 0.00123 | 0.0 | 2.53277 | 2.17750 | 2.12625 | 2.10868 | 2.45239 | 3.86071 | -0.48886 | -0.61200 | 1.41936 | 4.61206 | -0.45382 | 2.96751 | 0.18905 | -0.05673 | -0.55159 | 3.72174 | -2.90621 | -0.89319 | 0.67791 | 0.55527 | -1.97095 | -0.89032 | 0.41517 | 0.00000 | 0.03637 | 0.00000 | 0.22237 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3923 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 12.0 | 0.674 | 0.00900 | 0.00467 | 0.58824 | -8.33744 | 13.0 | 5.06085 | 4.02097 | 3.74748 | 3.62686 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00003 | 0.00009 | 3.17543 | 8.08333 | 0.00000 | 0.00000 | 0.00112 | 0.00116 | 0.69255 | -1.01613 | 0.00053 | 0.00158 | 0.0 | 5.38010 | 4.23392 | 3.94338 | 3.82421 | -2.92268 | 3.74750 | -0.37068 | -1.33455 | -1.44853 | 6.19414 | -2.80576 | 3.76570 | 0.62268 | 0.22601 | -3.06477 | 4.70191 | 0.11692 | 0.01820 | 0.99335 | 1.56057 | -1.61624 | -1.49223 | 0.27894 | -0.23306 | -0.03320 | -0.19449 | 0.10804 | 0.23146 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3924 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 7.0 | 0.612 | 0.00686 | 0.00229 | 0.58824 | 1.44596 | 11.0 | 4.09892 | 3.51165 | 3.30278 | 3.18477 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00091 | 0.00104 | 1.24686 | 0.78900 | 0.00070 | 0.00149 | 0.0 | 5.20378 | 4.31518 | 3.88937 | 3.62040 | -2.73327 | 3.61480 | 1.35166 | 0.26749 | -4.45294 | 2.90530 | -3.05512 | 3.48092 | 0.10349 | 0.10423 | -3.26005 | 4.24531 | -0.32185 | -0.13387 | -1.24817 | -0.16326 | 1.19289 | 1.34002 | 0.29496 | 0.00000 | -0.05596 | 0.00000 | 0.00935 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 11.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3925 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 19.0 | 0.732 | 0.00800 | 0.00779 | 0.58824 | -2.01935 | 2.0 | 1.78829 | 1.64569 | 1.55894 | 1.50686 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00614 | 0.00421 | 0.00000 | -2.00000 | 0.00614 | 0.00421 | 0.0 | 2.25776 | 2.25776 | 2.25776 | 2.25776 | -1.76224 | 0.16714 | 0.00000 | -2.00000 | -1.76224 | 0.16714 | -1.59073 | 3.14216 | 0.12059 | -0.14331 | -1.81130 | 3.91144 | 0.17151 | 2.97503 | 0.12059 | 1.85669 | -0.04905 | 3.74430 | -1.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3926 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 11.0 | 0.534 | 0.00873 | 0.00618 | 0.58824 | -3.10901 | 9.0 | 4.87229 | 3.47116 | 2.94744 | 2.70365 | 2.00000 | 2.00000 | 2.00000 | 2.00000 | 0.00008 | 0.00015 | 1.33631 | -0.21429 | 0.00000 | 0.00000 | 0.00193 | 0.00267 | 1.02042 | -0.48100 | 0.00018 | 0.00439 | 0.0 | 8.35311 | 6.39242 | 5.24739 | 4.56957 | -4.46125 | 5.28242 | 0.63141 | -1.37785 | -7.01177 | 9.27030 | -4.04162 | 2.88944 | 0.25980 | 0.24220 | -4.29680 | 3.46677 | 0.41963 | -2.39297 | -0.37161 | 1.62005 | 2.71497 | -5.80354 | 0.80946 | 0.10351 | -0.71667 | 0.32434 | 0.17408 | -0.10351 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 |
3927 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 115.0 | 0.522 | 0.00890 | 0.00664 | 0.58824 | 3.41541 | 22.0 | 5.81829 | 3.36374 | 2.81929 | 2.59538 | 3.83761 | 3.71688 | 3.62783 | 3.56095 | 0.00011 | 0.00025 | 1.92657 | 2.01026 | 0.00000 | 0.00000 | 0.00171 | 0.00251 | 1.18731 | -0.36416 | 0.00026 | 0.00202 | 0.0 | 6.28344 | 4.00292 | 3.50492 | 3.31759 | 0.99020 | 4.33475 | 0.70903 | -0.59103 | 0.11247 | 5.63338 | 0.73330 | 3.43750 | 0.29697 | -0.11299 | 0.96144 | 4.56620 | -0.25690 | -0.89724 | -0.41206 | 0.47804 | 0.84896 | -1.06718 | -0.16571 | -0.23061 | 0.34056 | 0.28600 | -0.24234 | -0.32053 | 18.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 |
3928 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 77.0 | 0.518 | 0.00899 | 0.00644 | 0.58824 | 1.17662 | 22.0 | 6.79148 | 3.70283 | 2.90010 | 2.59890 | 4.56640 | 4.17581 | 3.86757 | 3.64242 | 0.00012 | 0.00025 | 2.10369 | 3.56031 | 0.00000 | 0.00000 | 0.00121 | 0.00140 | 1.36341 | 1.32563 | 0.00061 | 0.00211 | 0.0 | 10.67274 | 7.10819 | 6.07250 | 5.61481 | 1.94272 | 2.67780 | -0.54139 | -0.45668 | 2.57690 | 3.64114 | 1.07309 | 2.91279 | 0.40513 | 0.07911 | 0.87202 | 4.05343 | -0.86963 | 0.23499 | 0.94652 | 0.53578 | -1.70488 | 0.41230 | 0.44587 | 0.27080 | -0.16199 | 0.08772 | 0.25200 | -0.17491 | 17.0 | 0.0 | 0.0 | 3.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 |
3929 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 9.0 | 0.514 | 0.01067 | 0.00711 | 0.58824 | 4.81433 | 11.0 | 3.96513 | 2.92243 | 2.63071 | 2.49476 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00485 | 0.00462 | 0.35832 | -1.70371 | 0.00263 | 0.01000 | 0.0 | 4.09674 | 3.15597 | 2.90006 | 2.79317 | 5.07326 | 1.01257 | 0.27682 | -0.92302 | 5.15451 | 1.36206 | 0.49061 | 3.98944 | 0.21521 | -0.40431 | -0.10705 | 6.04212 | -4.58265 | 2.97687 | -0.06161 | 0.51871 | -5.26156 | 4.68006 | -0.19630 | 0.00000 | -0.19635 | 0.00000 | -0.09770 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 11.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3930 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 13.0 | 0.642 | 0.00892 | 0.00400 | 0.58824 | 7.26724 | 15.0 | 5.00620 | 3.65604 | 3.26859 | 3.10801 | 3.00000 | 3.00000 | 3.00000 | 3.00000 | 0.00007 | 0.00014 | 1.50000 | 0.25000 | 0.00000 | 0.00000 | 0.00109 | 0.00092 | 1.00185 | 0.34255 | 0.00105 | 0.00088 | 0.0 | 5.71523 | 3.97908 | 3.45759 | 3.23378 | 4.39552 | 2.83612 | -0.99219 | 0.31713 | 5.74578 | 3.31552 | 3.26314 | 3.77733 | 0.05838 | 0.14626 | 3.42557 | 5.00967 | -1.13237 | 0.94121 | 1.05057 | -0.17087 | -2.32021 | 1.69415 | 0.10560 | -0.19939 | -0.26583 | 0.44522 | -0.19534 | 0.27003 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 |
3931 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | competition | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 8.0 | 0.536 | 0.00550 | 0.00250 | 0.58824 | 4.66024 | 8.0 | 3.14972 | 2.70116 | 2.56462 | 2.49570 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00283 | 0.00228 | 0.18008 | -1.57417 | 0.00202 | 0.00430 | 0.0 | 4.37908 | 3.63458 | 3.26999 | 3.03338 | 0.46463 | 3.43427 | -0.35499 | -1.07884 | 1.78512 | 4.43603 | 0.24522 | 3.02810 | 0.24820 | 0.22507 | 0.11795 | 4.13805 | -0.21941 | -0.40616 | 0.60318 | 1.30391 | -1.66717 | -0.29798 | -0.13584 | 0.00000 | -0.05988 | 0.00000 | 0.56468 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 8.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3932 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 9.0 | 0.574 | 0.01200 | 0.00978 | 0.58824 | 4.25839 | 7.0 | 2.30612 | 2.07821 | 2.03132 | 2.00482 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | 0.00000 | -3.00000 | 0.00000 | 0.00000 | 0.00356 | 0.00308 | -0.12225 | -1.80091 | 0.00456 | 0.00614 | 0.0 | 2.63205 | 2.19379 | 2.13590 | 2.11645 | 4.30208 | 0.35608 | -0.18877 | -1.42405 | 4.36527 | 0.58791 | 4.02092 | 3.95746 | 0.31577 | -0.10849 | 4.13015 | 5.11288 | -0.28116 | 3.60138 | 0.50454 | 1.31556 | -0.23512 | 4.52497 | 0.26607 | 0.00000 | -0.23424 | 0.00000 | -0.30914 | 0.00000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 |
3933 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 18.0 | 0.558 | 0.01133 | 0.00644 | 0.58824 | -5.20893 | 15.0 | 3.76250 | 2.86205 | 2.65210 | 2.56404 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00009 | 0.00033 | 3.47440 | 10.07143 | 0.00000 | 0.00000 | 0.00077 | 0.00117 | 1.53879 | 1.16647 | 0.00000 | 0.00105 | 0.0 | 3.73092 | 2.88193 | 2.68446 | 2.60439 | -0.93270 | 2.43826 | 0.49753 | -0.51828 | -1.48632 | 3.70862 | -1.22677 | 2.77830 | -0.49317 | 0.98469 | -1.19523 | 3.22859 | -0.29407 | 0.34004 | -0.99069 | 1.50297 | 0.29109 | -0.48003 | 0.13178 | 0.31644 | 0.30328 | 0.20129 | -0.24792 | -0.24744 | 14.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3934 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 198.0 | 0.516 | 0.00937 | 0.00788 | 0.58824 | 0.95718 | 16.0 | 4.77633 | 3.05848 | 2.65256 | 2.47619 | 4.72313 | 4.50465 | 4.34066 | 4.21913 | 0.00018 | 0.00028 | 1.20972 | -0.15916 | 0.00000 | 0.00035 | 0.00137 | 0.00100 | 0.41902 | -0.48535 | 0.00167 | 0.00149 | 0.0 | 6.93826 | 4.08234 | 3.43338 | 3.19301 | 2.68013 | 1.63311 | -0.06289 | -0.73544 | 2.76209 | 1.95983 | 2.09774 | 2.63248 | 0.12579 | 0.29739 | 2.28837 | 2.81555 | -0.58238 | 0.99937 | 0.18868 | 1.03282 | -0.47371 | 0.85572 | 0.32890 | 0.21332 | -0.23859 | 0.24164 | 0.41476 | -0.23269 | 11.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 |
3935 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 3.0 | 0.566 | 0.00933 | 0.00133 | 0.58824 | -2.34347 | 7.0 | 2.08489 | 1.76383 | 1.65320 | 1.59146 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00005 | 0.00012 | 2.04124 | 2.16667 | 0.00000 | 0.00000 | 0.00118 | 0.00173 | 1.76024 | 1.53899 | 0.00053 | 0.00105 | 0.0 | 2.59302 | 2.35495 | 2.32116 | 2.30963 | -0.32454 | 2.87328 | 0.63583 | -1.11167 | -0.99824 | 3.97966 | -0.62445 | 3.13534 | 0.48248 | 0.31108 | -0.84640 | 3.73203 | -0.29991 | 0.26206 | -0.15334 | 1.42275 | 0.15184 | -0.24763 | -0.08257 | 0.62361 | 0.34551 | 0.00000 | 0.19821 | 0.00000 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3936 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 10.0 | 0.626 | 0.00880 | 0.00600 | 0.58824 | -1.43052 | 5.0 | 2.20497 | 1.98834 | 1.91538 | 1.86778 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00007 | 0.00014 | 1.50000 | 0.25000 | 0.00000 | 0.00000 | 0.00151 | 0.00133 | -0.03939 | -1.75069 | 0.00158 | 0.00298 | 0.0 | 2.53032 | 2.22341 | 2.17213 | 2.15437 | -1.37403 | 0.61083 | 0.11459 | -1.70143 | -1.47516 | 1.20739 | -0.54865 | 3.28008 | 0.02337 | -0.52583 | -0.60497 | 4.65775 | 0.82539 | 2.66924 | -0.09122 | 1.17560 | 0.87019 | 3.45036 | 0.31623 | 0.70711 | 0.00000 | 0.00000 | 0.31623 | 0.70711 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3937 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 110.0 | 0.524 | 0.00982 | 0.00800 | 0.58824 | 3.21547 | 23.0 | 6.64570 | 3.38735 | 2.65013 | 2.38981 | 2.88169 | 2.76555 | 2.66021 | 2.57074 | 0.00006 | 0.00016 | 2.61750 | 5.66855 | 0.00000 | 0.00000 | 0.00198 | 0.00367 | 2.05898 | 2.73311 | 0.00018 | 0.00175 | 0.0 | 12.08613 | 8.08468 | 6.83329 | 6.19791 | -1.29958 | 2.12129 | -0.37986 | -0.55513 | -0.91838 | 2.33056 | -0.61702 | 2.97200 | 0.39137 | -0.07449 | -0.78715 | 3.79648 | 0.68256 | 0.85071 | 0.77123 | 0.48064 | 0.13124 | 1.46592 | 0.45194 | 0.14570 | -0.03400 | 0.33753 | -0.39092 | -0.16212 | 20.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3938 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | neutral | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 114.0 | 0.510 | 0.01091 | 0.00898 | 0.58824 | 8.44104 | 19.0 | 4.70032 | 2.96926 | 2.49475 | 2.28796 | 1.00000 | 1.00000 | 1.00000 | 1.00000 | 0.00002 | 0.00008 | 4.00694 | 14.05556 | 0.00000 | 0.00000 | 0.00095 | 0.00159 | 2.03996 | 2.75986 | 0.00035 | 0.00061 | 0.0 | 7.12697 | 5.00320 | 4.48433 | 4.25283 | 3.74786 | 6.22290 | -0.47942 | -0.92487 | 5.19128 | 9.56486 | 4.58988 | 6.21536 | -0.28587 | -1.07311 | 4.98637 | 11.21698 | 0.84202 | -0.00754 | 0.19355 | -0.14825 | -0.20491 | 1.65212 | 0.40310 | 0.34873 | -0.03910 | -0.10992 | -0.01076 | -0.21517 | 18.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3939 | 500 | 750000 | 2.0 | 0.7 | 2.0 | 5.0 | 0.5 | filtering | point_mutation | 0.0 | 2000 | 570.0 | 500.0 | 0.01 | 0.001 | 14.0 | 0.632 | 0.00800 | 0.00571 | 0.58824 | 2.58037 | 11.0 | 4.37982 | 3.58807 | 3.35487 | 3.23767 | 1.78233 | 1.63739 | 1.55027 | 1.49844 | 0.00012 | 0.00029 | 2.35448 | 4.08112 | 0.00000 | 0.00000 | 0.00107 | 0.00190 | 2.27942 | 3.96594 | 0.00018 | 0.00088 | 0.0 | 4.40588 | 3.56227 | 3.35700 | 3.26319 | 2.01674 | 1.75129 | -0.60035 | -0.15716 | 2.23206 | 1.36596 | 0.97676 | 2.64371 | 0.06791 | 0.31055 | 0.90403 | 3.28879 | -1.03998 | 0.89243 | 0.66826 | 0.46771 | -1.32803 | 1.92282 | -0.15889 | 0.13608 | -0.41286 | 0.34340 | 0.19448 | 0.16181 | 9.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
3940 rows × 81 columns
## This whole chunk is like data exploration
analysis_dir = "/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0"
##load data for one plot
ldir = analysis_dir + "/LocalComSize-500/SIMOUT.txt"
##Begin with No Speciation
df = pd.read_csv(ldir, sep="\t", header=0)
print(loccom.columns)
#print(loccom.loc[:, "S":"abund_h4"])
#print(loccom.loc[:, "pi_h1":"iqr_dxys"])
#print(loccom.loc[:, "SGD_0":"SGD_9"])
#print(loccom.loc[:, "mean_local_traits":"reg_loc_iqr_trait_dif"])
genetic_flag = True
abund_flag = False
trait_flag = True
genX = pd.concat([df.loc[:, "pi_h1":"iqr_dxys"], df.loc[:, "SGD_0":"SGD_9"]], axis=1)
abundX = df.loc[:, "S":"abund_h4"]
traitX = df.loc[:, "mean_local_traits":"reg_loc_iqr_trait_dif"]
## y will always be this
y = df['community_assembly_model']
X = df['community_assembly_model']
if (genetic_flag == True):
X = pd.concat([X, genX], axis=1)
elif (abund_flag == True):
X = pd.concat([X, abundX], axis=1)
elif (trait_flag == True):
X = pd.concat([X, traitX], axis=1)
X = X.drop(['community_assembly_model'], axis=1)
X
pi_h1 | pi_h2 | pi_h3 | pi_h4 | mean_pi | std_pi | skewness_pi | kurtosis_pi | median_pi | iqr_pi | mean_dxys | std_dxys | skewness_dxys | kurtosis_dxys | median_dxys | iqr_dxys | SGD_0 | SGD_1 | SGD_2 | SGD_3 | SGD_4 | SGD_5 | SGD_6 | SGD_7 | SGD_8 | SGD_9 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 2.796571 | 2.651376 | 2.550938 | 2.480410 | 0.000124 | 0.000279 | 2.056966 | 2.690958 | 0.000000 | 0.000000 | 0.001020 | 0.001101 | 1.051648 | -0.061627 | 0.000702 | 0.001272 | 13.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 |
1 | 4.752226 | 3.521397 | 2.985570 | 2.728739 | 0.000392 | 0.000738 | 2.561786 | 5.837293 | 0.000000 | 0.000351 | 0.001579 | 0.001690 | 1.041567 | 0.067516 | 0.000702 | 0.002281 | 9.0 | 4.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2 | 3.987807 | 3.455558 | 3.183188 | 3.027976 | 0.000273 | 0.000579 | 2.214917 | 3.648801 | 0.000000 | 0.000175 | 0.000840 | 0.001290 | 1.815727 | 2.713588 | 0.000175 | 0.001316 | 14.0 | 2.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 |
3 | 4.826410 | 4.651163 | 4.483358 | 4.330632 | 0.000260 | 0.000440 | 1.338725 | 0.344766 | 0.000000 | 0.000526 | 0.001199 | 0.001212 | 0.691247 | -0.626316 | 0.000614 | 0.001930 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 2.0 | 0.0 | 0.0 | 1.0 |
4 | 6.632732 | 6.297464 | 6.013299 | 5.784444 | 0.000397 | 0.000493 | 0.762170 | -0.856422 | 0.000000 | 0.000673 | 0.001272 | 0.001790 | 1.967814 | 3.325758 | 0.000526 | 0.001754 | 9.0 | 0.0 | 0.0 | 0.0 | 3.0 | 1.0 | 1.0 | 0.0 | 0.0 | 2.0 |
5 | 3.856988 | 3.705411 | 3.557289 | 3.423307 | 0.000105 | 0.000191 | 1.534813 | 1.004494 | 0.000000 | 0.000088 | 0.000800 | 0.000979 | 1.643700 | 2.212247 | 0.000439 | 0.001009 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 | 0.0 | 0.0 | 0.0 | 1.0 |
6 | 6.299853 | 5.878261 | 5.624941 | 5.463390 | 0.000358 | 0.000492 | 0.944481 | -0.781020 | 0.000000 | 0.000702 | 0.001311 | 0.001721 | 1.609853 | 1.823030 | 0.000702 | 0.001754 | 10.0 | 0.0 | 2.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 3.0 |
7 | 5.225238 | 4.760151 | 4.471861 | 4.275327 | 0.000395 | 0.000551 | 1.101164 | -0.198541 | 0.000000 | 0.000789 | 0.001241 | 0.001455 | 1.695557 | 2.320012 | 0.000702 | 0.001360 | 8.0 | 0.0 | 2.0 | 0.0 | 0.0 | 2.0 | 0.0 | 1.0 | 0.0 | 1.0 |
8 | 3.940566 | 3.878187 | 3.814614 | 3.751783 | 0.000180 | 0.000319 | 1.305842 | -0.037385 | 0.000000 | 0.000156 | 0.000822 | 0.001114 | 1.746248 | 2.622374 | 0.000439 | 0.001447 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 1.0 | 0.0 | 1.0 |
9 | 2.295491 | 1.918537 | 1.742995 | 1.656109 | 0.000171 | 0.000495 | 3.317197 | 9.961197 | 0.000000 | 0.000000 | 0.001296 | 0.001673 | 1.239862 | 0.425176 | 0.000263 | 0.001886 | 15.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
10 | 3.867052 | 3.068146 | 2.645006 | 2.428749 | 0.000156 | 0.000387 | 3.240577 | 10.303404 | 0.000000 | 0.000000 | 0.000853 | 0.001632 | 3.365938 | 11.304989 | 0.000263 | 0.001053 | 17.0 | 0.0 | 3.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
11 | 5.849165 | 5.101133 | 4.644532 | 4.359074 | 0.000509 | 0.000744 | 1.427389 | 0.899539 | 0.000000 | 0.000702 | 0.001645 | 0.001819 | 1.309880 | 1.541931 | 0.001491 | 0.002368 | 9.0 | 1.0 | 2.0 | 1.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 1.0 |
12 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | -3.000000 | 0.000000 | 0.000000 | 0.001012 | 0.001280 | 1.489749 | 1.783038 | 0.000702 | 0.001754 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 |
13 | 5.684079 | 4.672811 | 4.030435 | 3.649263 | 0.000380 | 0.000592 | 1.983794 | 3.601540 | 0.000000 | 0.000624 | 0.001831 | 0.002093 | 1.336335 | 1.346922 | 0.001053 | 0.002588 | 9.0 | 2.0 | 2.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
14 | 5.712916 | 5.495023 | 5.334716 | 5.216496 | 0.000209 | 0.000302 | 0.948586 | -0.820664 | 0.000000 | 0.000351 | 0.000826 | 0.000818 | 0.834363 | -0.236437 | 0.000526 | 0.001404 | 11.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 1.0 | 2.0 | 1.0 |
15 | 4.521996 | 3.499820 | 2.962298 | 2.690405 | 0.000303 | 0.000697 | 3.151175 | 9.915155 | 0.000000 | 0.000263 | 0.001762 | 0.002676 | 1.977095 | 3.218884 | 0.000439 | 0.002281 | 16.0 | 3.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
16 | 3.723916 | 3.504854 | 3.345031 | 3.232312 | 0.000159 | 0.000275 | 1.453840 | 0.585826 | 0.000000 | 0.000263 | 0.001504 | 0.001484 | 0.448974 | -1.177556 | 0.001491 | 0.002632 | 10.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 |
17 | 3.634256 | 3.349235 | 3.147276 | 3.008010 | 0.000125 | 0.000271 | 2.121091 | 3.286341 | 0.000000 | 0.000000 | 0.002271 | 0.003464 | 2.740261 | 7.539843 | 0.001053 | 0.002719 | 15.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 |
18 | 5.334887 | 4.842549 | 4.494317 | 4.246177 | 0.000213 | 0.000390 | 1.775856 | 2.088993 | 0.000000 | 0.000351 | 0.001170 | 0.001730 | 2.313942 | 5.933029 | 0.000526 | 0.002105 | 15.0 | 0.0 | 2.0 | 0.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 1.0 |
19 | 1.889882 | 1.800000 | 1.732051 | 1.682721 | 0.000132 | 0.000370 | 2.737955 | 6.137274 | 0.000000 | 0.000000 | 0.002138 | 0.002359 | 1.010133 | -0.232543 | 0.001404 | 0.002763 | 14.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
20 | 7.070900 | 6.230415 | 5.619254 | 5.223935 | 0.000239 | 0.000314 | 1.305494 | 0.756589 | 0.000000 | 0.000351 | 0.001806 | 0.002408 | 2.714370 | 7.221920 | 0.001053 | 0.001754 | 9.0 | 0.0 | 0.0 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 |
21 | 5.129938 | 4.301172 | 3.713521 | 3.357380 | 0.000342 | 0.000611 | 2.276641 | 5.107034 | 0.000000 | 0.000624 | 0.001170 | 0.001859 | 1.997987 | 2.997265 | 0.000351 | 0.001579 | 12.0 | 0.0 | 2.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
22 | 3.199806 | 2.714286 | 2.451814 | 2.303880 | 0.000456 | 0.000887 | 2.134374 | 3.472331 | 0.000000 | 0.000624 | 0.001606 | 0.002076 | 1.569975 | 0.959916 | 0.000702 | 0.001228 | 9.0 | 0.0 | 2.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
23 | 5.664932 | 5.393100 | 5.176710 | 5.005962 | 0.000283 | 0.000378 | 0.863120 | -0.791641 | 0.000000 | 0.000624 | 0.000830 | 0.000751 | 0.433482 | -1.100726 | 0.000877 | 0.001140 | 9.0 | 0.0 | 0.0 | 1.0 | 0.0 | 3.0 | 0.0 | 0.0 | 0.0 | 2.0 |
24 | 4.759799 | 4.005215 | 3.601587 | 3.374592 | 0.000381 | 0.000571 | 1.572235 | 1.268839 | 0.000000 | 0.000351 | 0.000918 | 0.000908 | 0.416940 | -1.339959 | 0.000351 | 0.001754 | 7.0 | 3.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 |
25 | 4.052433 | 3.408795 | 3.014495 | 2.780114 | 0.000322 | 0.000689 | 2.556267 | 6.117919 | 0.000000 | 0.000175 | 0.001671 | 0.002197 | 2.557987 | 6.379227 | 0.001053 | 0.001140 | 14.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
26 | 4.781557 | 4.081892 | 3.692062 | 3.458956 | 0.000314 | 0.000639 | 2.242016 | 4.116005 | 0.000000 | 0.000351 | 0.001086 | 0.001332 | 1.872807 | 3.729034 | 0.000702 | 0.001754 | 15.0 | 2.0 | 0.0 | 2.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 |
27 | 4.153556 | 3.476880 | 3.051777 | 2.805012 | 0.000171 | 0.000350 | 2.490059 | 5.777965 | 0.000000 | 0.000263 | 0.001150 | 0.001573 | 1.139890 | -0.228346 | 0.000351 | 0.002061 | 13.0 | 0.0 | 3.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
28 | 3.777309 | 3.604255 | 3.473572 | 3.374918 | 0.000375 | 0.000696 | 1.552140 | 0.831619 | 0.000000 | 0.000205 | 0.001305 | 0.001305 | 0.580799 | -1.078772 | 0.000965 | 0.002281 | 12.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 |
29 | 5.728387 | 5.494903 | 5.306781 | 5.160913 | 0.000131 | 0.000233 | 1.446911 | 0.496977 | 0.000000 | 0.000175 | 0.001350 | 0.002055 | 1.958977 | 3.347370 | 0.000351 | 0.001930 | 17.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 | 0.0 | 0.0 | 2.0 | 1.0 |
30 | 4.492839 | 4.150617 | 3.913973 | 3.742931 | 0.000192 | 0.000430 | 2.196516 | 3.655036 | 0.000000 | 0.000000 | 0.000835 | 0.000959 | 1.134858 | 0.172618 | 0.000526 | 0.001404 | 20.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 1.0 |
31 | 8.073023 | 7.553118 | 7.263509 | 7.089906 | 0.000388 | 0.000498 | 0.774291 | -1.155787 | 0.000000 | 0.000936 | 0.001053 | 0.001274 | 1.275046 | 0.776739 | 0.000526 | 0.001623 | 11.0 | 0.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 4.0 |
32 | 6.030450 | 4.968346 | 4.454545 | 4.177754 | 0.000412 | 0.000666 | 1.755989 | 1.855695 | 0.000000 | 0.000351 | 0.000877 | 0.000986 | 1.335129 | 0.716673 | 0.000702 | 0.000877 | 10.0 | 4.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 1.0 |
33 | 2.637924 | 2.349428 | 2.157350 | 2.038238 | 0.000186 | 0.000313 | 1.661196 | 1.550273 | 0.000000 | 0.000351 | 0.001248 | 0.001352 | 0.649604 | -0.917026 | 0.000877 | 0.002105 | 6.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
34 | 3.788928 | 3.645570 | 3.548262 | 3.479764 | 0.000201 | 0.000338 | 1.263251 | -0.162099 | 0.000000 | 0.000263 | 0.001028 | 0.001355 | 1.130299 | -0.287710 | 0.000351 | 0.001667 | 10.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 |
35 | 5.117650 | 4.328939 | 3.781393 | 3.444151 | 0.000184 | 0.000327 | 2.171145 | 4.425844 | 0.000000 | 0.000351 | 0.000936 | 0.001272 | 1.584611 | 1.216364 | 0.000351 | 0.000921 | 12.0 | 0.0 | 4.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
36 | 2.586409 | 2.272727 | 2.076137 | 1.960051 | 0.000125 | 0.000285 | 2.473453 | 5.130341 | 0.000000 | 0.000000 | 0.000952 | 0.001113 | 1.970858 | 3.677111 | 0.000702 | 0.001009 | 11.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
37 | 4.352915 | 3.961918 | 3.729720 | 3.580447 | 0.000258 | 0.000450 | 1.564773 | 0.992188 | 0.000000 | 0.000351 | 0.001919 | 0.002046 | 1.068936 | 0.105535 | 0.001053 | 0.002500 | 11.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 1.0 |
38 | 1.973557 | 1.948367 | 1.924944 | 1.903621 | 0.000112 | 0.000289 | 2.285526 | 3.452740 | 0.000000 | 0.000000 | 0.001637 | 0.001931 | 1.199145 | 0.341849 | 0.001053 | 0.002193 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 |
39 | 4.778016 | 4.615018 | 4.494057 | 4.401397 | 0.000229 | 0.000343 | 1.004195 | -0.724593 | 0.000000 | 0.000487 | 0.001509 | 0.002327 | 2.584176 | 6.224485 | 0.000702 | 0.001754 | 10.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 1.0 | 1.0 |
40 | 2.861709 | 2.275591 | 2.017320 | 1.892856 | 0.000234 | 0.000595 | 3.074398 | 8.516798 | 0.000000 | 0.000000 | 0.001651 | 0.001617 | 0.506077 | -1.396879 | 0.001053 | 0.002982 | 13.0 | 2.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
41 | 2.322147 | 1.949688 | 1.771759 | 1.682271 | 0.000167 | 0.000479 | 3.281837 | 9.756714 | 0.000000 | 0.000000 | 0.000760 | 0.001231 | 1.270475 | -0.111838 | 0.000000 | 0.001140 | 15.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
42 | 3.893668 | 3.177158 | 2.787082 | 2.573965 | 0.000210 | 0.000497 | 2.931089 | 8.205819 | 0.000000 | 0.000000 | 0.000693 | 0.000968 | 1.569680 | 1.200620 | 0.000175 | 0.000877 | 16.0 | 2.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
43 | 2.841399 | 2.731167 | 2.657611 | 2.608622 | 0.000210 | 0.000462 | 1.930331 | 1.995478 | 0.000000 | 0.000000 | 0.001064 | 0.001842 | 2.878231 | 7.717696 | 0.000439 | 0.001404 | 13.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 |
44 | 1.655151 | 1.477160 | 1.392841 | 1.350354 | 0.000171 | 0.000572 | 3.540596 | 11.151451 | 0.000000 | 0.000000 | 0.000819 | 0.001204 | 1.498277 | 0.832069 | 0.000263 | 0.001053 | 16.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
45 | 3.358660 | 2.924775 | 2.657403 | 2.493210 | 0.000222 | 0.000488 | 2.414227 | 4.996109 | 0.000000 | 0.000000 | 0.001135 | 0.001085 | 0.570007 | -0.523440 | 0.001228 | 0.001930 | 13.0 | 1.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
46 | 4.646023 | 4.408534 | 4.242613 | 4.119030 | 0.000250 | 0.000422 | 1.343973 | 0.213546 | 0.000000 | 0.000351 | 0.001517 | 0.001224 | 0.130047 | -1.152847 | 0.001754 | 0.002281 | 12.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 2.0 | 0.0 | 1.0 |
47 | 2.796571 | 2.651376 | 2.550938 | 2.480410 | 0.000133 | 0.000286 | 1.950432 | 2.246077 | 0.000000 | 0.000000 | 0.001368 | 0.001161 | 0.845880 | -0.090042 | 0.001053 | 0.001491 | 12.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 |
48 | 4.081011 | 3.616643 | 3.384522 | 3.255113 | 0.000247 | 0.000541 | 2.190159 | 3.335051 | 0.000000 | 0.000000 | 0.001679 | 0.001550 | 0.540281 | -0.871474 | 0.001404 | 0.003158 | 16.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 |
49 | 1.889882 | 1.800000 | 1.732051 | 1.682721 | 0.000053 | 0.000167 | 3.172502 | 8.829127 | 0.000000 | 0.000000 | 0.000702 | 0.001048 | 1.658184 | 1.837935 | 0.000175 | 0.000789 | 18.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
2940 | 2.745875 | 2.522388 | 2.352447 | 2.233615 | 0.000095 | 0.000220 | 2.366602 | 4.621340 | 0.000000 | 0.000000 | 0.002752 | 0.003146 | 1.173527 | 0.282177 | 0.001404 | 0.003947 | 13.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2941 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000064 | 0.000202 | 2.846050 | 6.100000 | 0.000000 | 0.000000 | 0.000893 | 0.001013 | 0.995222 | -0.149468 | 0.000702 | 0.001316 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2942 | 2.881688 | 2.765550 | 2.660207 | 2.570737 | 0.000083 | 0.000181 | 1.988685 | 2.594024 | 0.000000 | 0.000000 | 0.001864 | 0.003428 | 2.624799 | 6.054409 | 0.000351 | 0.001754 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2943 | 4.000000 | 4.000000 | 4.000000 | 4.000000 | 0.000074 | 0.000143 | 1.420094 | 0.016667 | 0.000000 | 0.000000 | 0.000886 | 0.001063 | 1.001866 | -0.276627 | 0.000526 | 0.001404 | 15.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 4.0 |
2944 | 5.231677 | 4.624564 | 4.184699 | 3.880213 | 0.000366 | 0.000549 | 1.522961 | 1.537130 | 0.000000 | 0.000624 | 0.001602 | 0.001807 | 1.835554 | 2.797311 | 0.000877 | 0.001667 | 9.0 | 1.0 | 0.0 | 2.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2945 | 1.823097 | 1.386429 | 1.288441 | 1.253077 | 0.001847 | 0.004034 | 2.230798 | 3.048313 | 0.000312 | 0.000770 | 0.003487 | 0.004274 | 1.611655 | 1.466839 | 0.002193 | 0.003465 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2946 | 2.745875 | 2.522388 | 2.352447 | 2.233615 | 0.000117 | 0.000238 | 2.017131 | 2.965021 | 0.000000 | 0.000000 | 0.001296 | 0.001843 | 2.173405 | 4.249532 | 0.000526 | 0.001754 | 10.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2947 | 3.000000 | 3.000000 | 3.000000 | 3.000000 | 0.000058 | 0.000131 | 1.788854 | 1.200000 | 0.000000 | 0.000000 | 0.001501 | 0.001690 | 1.534349 | 2.228443 | 0.000965 | 0.002105 | 15.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 |
2948 | 3.811647 | 3.083916 | 2.699066 | 2.491722 | 0.000491 | 0.000736 | 1.786259 | 2.207011 | 0.000175 | 0.000702 | 0.001947 | 0.002004 | 1.575424 | 1.900205 | 0.001754 | 0.002061 | 5.0 | 2.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2949 | 3.000000 | 3.000000 | 3.000000 | 3.000000 | 0.000070 | 0.000140 | 1.500000 | 0.250000 | 0.000000 | 0.000000 | 0.002000 | 0.002305 | 1.634117 | 2.255174 | 0.000877 | 0.002544 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 |
2950 | 2.838721 | 2.723404 | 2.643816 | 2.588646 | 0.000134 | 0.000272 | 1.735094 | 1.308309 | 0.000000 | 0.000000 | 0.000652 | 0.000932 | 1.521599 | 1.304472 | 0.000175 | 0.001053 | 11.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 |
2951 | 4.762203 | 4.500000 | 4.242641 | 4.016598 | 0.000096 | 0.000189 | 1.854510 | 2.494694 | 0.000000 | 0.000000 | 0.001451 | 0.001722 | 1.342498 | 1.051656 | 0.001053 | 0.001974 | 17.0 | 0.0 | 0.0 | 0.0 | 0.0 | 4.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2952 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000032 | 0.000101 | 2.846050 | 6.100000 | 0.000000 | 0.000000 | 0.001164 | 0.001257 | 0.529722 | -1.212242 | 0.000702 | 0.002193 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2953 | 3.740489 | 3.521537 | 3.351145 | 3.223708 | 0.000165 | 0.000271 | 1.352880 | 0.386431 | 0.000000 | 0.000351 | 0.001781 | 0.002864 | 2.262594 | 4.329986 | 0.000526 | 0.002105 | 9.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 |
2954 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | -3.000000 | 0.000000 | 0.000000 | 0.001719 | 0.002073 | 1.502726 | 1.456465 | 0.001053 | 0.002237 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 |
2955 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | -3.000000 | 0.000000 | 0.000000 | 0.001092 | 0.000905 | 0.789859 | -0.393909 | 0.000702 | 0.001228 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 9.0 | 0.0 | 0.0 | 0.0 | 0.0 |
2956 | 1.889882 | 1.800000 | 1.732051 | 1.682721 | 0.000117 | 0.000234 | 1.750000 | 1.500000 | 0.000000 | 0.000000 | 0.000994 | 0.000767 | 0.656099 | -0.015008 | 0.000877 | 0.000702 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2957 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000032 | 0.000101 | 2.846050 | 6.100000 | 0.000000 | 0.000000 | 0.000734 | 0.001180 | 1.550733 | 0.721971 | 0.000175 | 0.000614 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2958 | 1.894646 | 1.515152 | 1.394821 | 1.346303 | 0.000292 | 0.000769 | 2.870629 | 6.534866 | 0.000000 | 0.000088 | 0.002690 | 0.003907 | 2.014756 | 3.408791 | 0.000702 | 0.003596 | 9.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2959 | 1.889882 | 1.800000 | 1.732051 | 1.682721 | 0.000132 | 0.000244 | 1.564304 | 0.859521 | 0.000000 | 0.000088 | 0.001820 | 0.004163 | 2.246164 | 3.087603 | 0.000175 | 0.000702 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2960 | 1.979626 | 1.960000 | 1.941451 | 1.924217 | 0.000205 | 0.000359 | 1.244935 | -0.321653 | 0.000000 | 0.000175 | 0.001667 | 0.001574 | 1.137574 | 0.121591 | 0.001053 | 0.001360 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 |
2961 | 2.881688 | 2.765550 | 2.660207 | 2.570737 | 0.000070 | 0.000169 | 2.278160 | 3.903673 | 0.000000 | 0.000000 | 0.000951 | 0.001520 | 2.664484 | 6.654310 | 0.000351 | 0.000877 | 16.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2962 | 2.881688 | 2.765550 | 2.660207 | 2.570737 | 0.000053 | 0.000150 | 2.772300 | 6.555781 | 0.000000 | 0.000000 | 0.001242 | 0.002130 | 2.091138 | 3.432825 | 0.000175 | 0.001754 | 22.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2963 | 2.881688 | 2.765550 | 2.660207 | 2.570737 | 0.000095 | 0.000191 | 1.772157 | 1.732842 | 0.000000 | 0.000000 | 0.001353 | 0.001401 | 1.552474 | 1.796909 | 0.000965 | 0.001535 | 11.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2964 | 3.901299 | 3.826855 | 3.771871 | 3.731476 | 0.000139 | 0.000248 | 1.313330 | -0.139443 | 0.000000 | 0.000088 | 0.001349 | 0.001633 | 1.062855 | 0.109036 | 0.000439 | 0.002544 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 3.0 |
2965 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000044 | 0.000116 | 2.267787 | 3.142857 | 0.000000 | 0.000000 | 0.000395 | 0.000348 | 0.515952 | -0.872260 | 0.000351 | 0.000439 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2966 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000063 | 0.000218 | 3.175426 | 8.083333 | 0.000000 | 0.000000 | 0.002497 | 0.003743 | 2.167737 | 4.061917 | 0.001754 | 0.002982 | 12.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2967 | 1.994086 | 1.988235 | 1.982481 | 1.976854 | 0.000169 | 0.000317 | 1.363416 | -0.098577 | 0.000000 | 0.000000 | 0.001559 | 0.001912 | 1.307897 | 0.460538 | 0.000877 | 0.001754 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 |
2968 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000022 | 0.000085 | 3.614784 | 11.066667 | 0.000000 | 0.000000 | 0.000899 | 0.001581 | 2.378094 | 4.859731 | 0.000263 | 0.000746 | 15.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2969 | 3.000000 | 3.000000 | 3.000000 | 3.000000 | 0.000058 | 0.000131 | 1.788854 | 1.200000 | 0.000000 | 0.000000 | 0.001062 | 0.001542 | 1.848264 | 2.540460 | 0.000439 | 0.000833 | 15.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 |
2970 | 1.842023 | 1.724138 | 1.643990 | 1.591229 | 0.000073 | 0.000210 | 2.890997 | 7.070643 | 0.000000 | 0.000000 | 0.001009 | 0.000891 | 0.334558 | -1.147090 | 0.000965 | 0.001623 | 14.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2971 | 2.000000 | 2.000000 | 2.000000 | 2.000000 | 0.000064 | 0.000135 | 1.649916 | 0.722222 | 0.000000 | 0.000000 | 0.001850 | 0.001438 | 0.518579 | -0.843113 | 0.001404 | 0.001842 | 9.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 |
2972 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000035 | 0.000105 | 2.666667 | 5.111111 | 0.000000 | 0.000000 | 0.001947 | 0.002455 | 1.348559 | 0.535402 | 0.001140 | 0.002018 | 9.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2973 | 1.842023 | 1.724138 | 1.643990 | 1.591229 | 0.000090 | 0.000230 | 2.505827 | 4.888772 | 0.000000 | 0.000000 | 0.000958 | 0.000907 | 0.951738 | -0.257821 | 0.000702 | 0.000877 | 11.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2974 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000089 | 0.000218 | 2.041241 | 2.166667 | 0.000000 | 0.000000 | 0.001253 | 0.000717 | -0.052575 | -0.479478 | 0.001053 | 0.000702 | 6.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2975 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | -3.000000 | 0.000000 | 0.000000 | 0.001053 | 0.001129 | 0.996472 | -0.323020 | 0.000789 | 0.001140 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 14.0 | 0.0 | 0.0 | 0.0 | 0.0 |
2976 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000035 | 0.000105 | 2.666667 | 5.111111 | 0.000000 | 0.000000 | 0.001333 | 0.001825 | 1.279759 | 0.165674 | 0.000263 | 0.001623 | 9.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2977 | 3.930361 | 3.868132 | 3.813329 | 3.765478 | 0.000429 | 0.000443 | 0.178132 | -1.778206 | 0.000312 | 0.000848 | 0.002368 | 0.002921 | 1.354940 | 0.430297 | 0.000877 | 0.002500 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 1.0 | 1.0 |
2978 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | -3.000000 | 0.000000 | 0.000000 | 0.002180 | 0.001688 | 0.217264 | -1.254223 | 0.002456 | 0.002544 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 |
2979 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000044 | 0.000116 | 2.267787 | 3.142857 | 0.000000 | 0.000000 | 0.001513 | 0.002138 | 1.811553 | 1.913272 | 0.000702 | 0.001228 | 7.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2980 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | -3.000000 | 0.000000 | 0.000000 | 0.001306 | 0.001982 | 1.500482 | 0.708642 | 0.000351 | 0.001053 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 9.0 | 0.0 | 0.0 | 0.0 | 0.0 |
2981 | 1.796702 | 1.657534 | 1.571429 | 1.519038 | 0.000099 | 0.000259 | 2.620533 | 5.480239 | 0.000000 | 0.000000 | 0.001525 | 0.002029 | 1.288346 | 0.414861 | 0.000526 | 0.002807 | 11.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2982 | 2.000000 | 2.000000 | 2.000000 | 2.000000 | 0.000047 | 0.000119 | 2.157277 | 2.653846 | 0.000000 | 0.000000 | 0.000608 | 0.000659 | 1.089947 | -0.081328 | 0.000351 | 0.000614 | 13.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 |
2983 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000074 | 0.000235 | 2.846050 | 6.100000 | 0.000000 | 0.000000 | 0.000877 | 0.001291 | 1.347145 | 0.570627 | 0.000000 | 0.001491 | 10.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2984 | 1.922100 | 1.854599 | 1.799539 | 1.756363 | 0.000089 | 0.000197 | 1.969905 | 2.296288 | 0.000000 | 0.000000 | 0.001372 | 0.001608 | 1.268711 | 0.272599 | 0.000702 | 0.001579 | 9.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2985 | 3.571674 | 3.175824 | 2.878366 | 2.680003 | 0.000124 | 0.000250 | 2.191774 | 4.139892 | 0.000000 | 0.000088 | 0.001206 | 0.001681 | 1.500805 | 1.119854 | 0.000439 | 0.001491 | 12.0 | 0.0 | 0.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2986 | 1.842023 | 1.724138 | 1.643990 | 1.591229 | 0.000078 | 0.000216 | 2.768335 | 6.341795 | 0.000000 | 0.000000 | 0.000725 | 0.000665 | 0.820968 | -0.268607 | 0.000526 | 0.000965 | 13.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2987 | 1.510356 | 1.327452 | 1.259897 | 1.230239 | 0.001275 | 0.002637 | 1.930063 | 1.894532 | 0.000000 | 0.000643 | 0.001504 | 0.001296 | 1.375897 | 0.695327 | 0.001053 | 0.000877 | 5.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2988 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 0.000069 | 0.000196 | 2.474874 | 4.125000 | 0.000000 | 0.000000 | 0.001540 | 0.001234 | 0.419507 | -0.814330 | 0.001754 | 0.001404 | 8.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2989 | 1.915369 | 1.842943 | 1.784817 | 1.740004 | 0.001046 | 0.001571 | 1.043162 | -0.576269 | 0.000000 | 0.001667 | 0.001520 | 0.001584 | 0.707740 | -0.867743 | 0.001053 | 0.002237 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 |
2990 rows × 26 columns
## Here, estimate the best RF parameters to make a classifier that has the most power.
## also stole this chunk from Isaac
## We will be using this data to tune the classification parameters
ldir = "/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-1000/SIMOUT.txt"
df = pd.read_csv(ldir, sep="\t", header=0)
## asign data
y = df['community_assembly_model']
X = df.loc[:, "S":"SGD_9"]
## split data
Xtrain, Xtest, ytrain, ytest = train_test_split(X, y)
## get best RF params
n_estimators = [int(x) for x in np.linspace(start = 200, stop = 2000, num = 10)]
max_depth = [int(x) for x in np.linspace(10, 110, num = 11)]
max_depth.append(None)
min_samples_split = [2, 5, 10]
min_samples_leaf = [1, 2, 4]
bootstrap = [True, False]
random_grid = {'n_estimators': n_estimators,
'max_depth': max_depth,
'min_samples_split': min_samples_split,
'min_samples_leaf': min_samples_leaf,
'bootstrap': bootstrap}
## Randomly search 100 different parameter combinations and take the
# ## one that reduces CV error
rf_random = RandomizedSearchCV(estimator = RandomForestClassifier(),\
param_distributions = random_grid,
n_iter = 100, cv = 3, verbose=0, n_jobs = -1,
error_score=np.nan)
# ## fit the training data using best params for RF
#rf_random.fit(Xtrain, ytrain)
rf_random.fit(Xtrain, ytrain)
ypred = rf_random.predict(Xtest)
cm = metrics.confusion_matrix(ypred, ytest)
print(cm)
[[224 36 7] [ 25 212 3] [ 2 9 231]]
#print(cm)
print(rf_random.best_params_["n_estimators"])
ldir = "/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-1000/SIMOUT.txt"
df = pd.read_csv(ldir, sep="\t", header=0)
## asign data
y = df['community_assembly_model']
X = df.loc[:, "S":"SGD_9"]
## split data
Xtrain, Xtest, ytrain, ytest = train_test_split(X, y)
model = RandomForestClassifier(n_estimators=rf_random.best_params_["n_estimators"], \
n_jobs=-1, max_features='auto', max_depth=rf_random.best_params_["max_depth"], \
bootstrap=rf_random.best_params_["bootstrap"], \
min_samples_split=rf_random.best_params_["min_samples_split"], \
min_samples_leaf=rf_random.best_params_["min_samples_leaf"])
model.fit(Xtrain, ytrain)
ypred = model.predict(Xtest)
cm = metrics.confusion_matrix(ypred, ytest)
print(cm)
classify_model = RF_classify(df, rf_random)
print(classify_model)
#print(rf_random.cv_results_)
--------------------------------------------------------------------------- NameError Traceback (most recent call last) <ipython-input-4-4028d58a89d0> in <module>() 1 #print(cm) ----> 2 print(rf_random.best_params_["n_estimators"]) 3 4 ldir = "/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-1000/SIMOUT.txt" 5 df = pd.read_csv(ldir, sep="\t", header=0) NameError: name 'rf_random' is not defined
## This chunk is the function to perform RF and cross validation to asses
## the error rates for each model
def RF_classify(df, rf_random, genetic_flag = True, abund_flag = True, trait_flag = True):
#print(rf_random.best_params_)
## split up the sumstats into their type, join later if all flags == True
genX = pd.concat([df.loc[:, "pi_h1":"iqr_dxys"], df.loc[:, "SGD_0":"SGD_9"], df.loc[:,"dxy_pi_cor"]], axis=1)
#genX = df.loc[:, "pi_h1":"iqr_dxys"]
abundX = df.loc[:, "S":"abund_h4"]
traitX = df.loc[:, "trait_h1":"reg_loc_iqr_trait_dif"]
## correlation sum stats
gen_traitX = df.loc[:, "dxy_trait_cor":"pi_trait_cor"]
gen_abundX = df.loc[:, "abundance_dxy_cor":"abundance_pi_cor"]
abund_traitX = df.loc[:, "abundance_trait_cor"]
## y will always be this
y = df['community_assembly_model']
## begin X as this
X = df['community_assembly_model']
## add certain sumstats depending on which flag is on
if (genetic_flag == True):
X = pd.concat([X, genX], axis=1)
if (abund_flag == True):
X = pd.concat([X, abundX], axis=1)
if (trait_flag == True):
X = pd.concat([X, traitX], axis=1)
## add certain sumstats if multiple flags are on
if (genetic_flag == True & trait_flag == True)
X = pd.concat([X, gen_traitX])
if (genetic_flag == True & abund_flag == True)
X = pd.concat([X, gen_abundX])
if (abund_flag == True & trait_flag == True)
X = pd.concat([X, abund_traitX])
## drop that first column, you don't need it bc the info is in y
X = X.drop(['community_assembly_model'], axis=1)
#y = df['community_assembly_model']
#X = df.loc[:, "S":"SGD_9"]
# split data
Xtrain, Xtest, ytrain, ytest = train_test_split(X, y)
model = RandomForestClassifier(n_estimators=rf_random.best_params_["n_estimators"], \
n_jobs=-1, max_features='auto', max_depth=rf_random.best_params_["max_depth"], \
bootstrap=rf_random.best_params_["bootstrap"], \
min_samples_split=rf_random.best_params_["min_samples_split"], \
min_samples_leaf=rf_random.best_params_["min_samples_leaf"])
model.fit(Xtrain, ytrain)
ypred = model.predict(Xtest)
cm = metrics.confusion_matrix(ypred, ytest)
#print(cm)
err = []
for i in range(0,3):
#competition first, then filtering, then neutral, then average
acuracy = float(cm[i][i])
total = float(sum([cm[0][i], cm[1][i], cm[2][i]]))
z = int(total)-int(acuracy)
Accuracy_array = np.concatenate([np.ones(int(acuracy)), np.zeros(z)])
print(np.mean(Accuracy_array))
print(np.std(Accuracy_array))
err.append(acuracy/total)
#append avg error rate from our own external validation
err.append(np.mean(err))
# #also append average error rate from cv function
# scores = cross_val_score(model, Xtrain, ytrain, cv=5)
# err.append(scores.mean())
return err
## ! means run in the shell
## lists the number of lines in the $filename
!wc -l $ldir
2991 /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-2000/SIMOUT.txt
analysis_dir = "/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001"
ldir = analysis_dir + "/LocalComSize-1000/SIMOUT.txt"
print(ldir)
##Begin with No Speciation
loccom_500_df = pd.read_csv(ldir, sep="\t", header=0)
#print(loccom_500_df)
#print(loccom_500_df["community_assembly_model"])
print(len(loccom_500_df))
classify_model = RF_classify(loccom_500_df, rf_random)
print(classify_model)
/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-1000/SIMOUT.txt 2993 0.8438818565400844 0.3629673108456804 0.8764478764478765 0.32906989579401574 0.9565217391304348 0.20393111999232305 [0.8438818565400844, 0.8764478764478765, 0.9565217391304348, 0.8922838240394654]
## In this chunk, go through and run RF classifier on all data
analysis_dir = "/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/"
allErrorRates = []
specrates = np.array([0.0, 0.0001])
modnames = np.array(["neutral", "filtering", "competition"])
localcomsize = np.array([500, 1000, 2000])
params = [specrates, localcomsize]
params = list(itertools.product(*params))
for i, p in enumerate(params):
specrates, localcomsize = p
#print(specrates, localcomsize)
ldir = analysis_dir + "Speciation-{}/".format(specrates)
ldir = ldir + "LocalComSize-{}/".format(localcomsize)
ldir = ldir + "SIMOUT.txt"
print(ldir)
df = pd.read_csv(ldir, sep="\t", header=0)
classify_model = RF_classify(df, rf_random)
print(classify_model)
output = [specrates, localcomsize] + classify_model
allErrorRates.append(output)
print(allErrorRates)
csvData = allErrorRates
with open('/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/allErrorRates.csv', 'w') as csvFile:
writer = csv.writer(csvFile)
writer.writerows(csvData)
csvFile.close()
/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-500/SIMOUT.txt [0.8435114503816794, 0.7590361445783133, 0.8818565400843882, 0.8281347116814604] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-1000/SIMOUT.txt [0.8846153846153846, 0.8604651162790697, 0.9571984435797666, 0.9007596481580736] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-2000/SIMOUT.txt [0.8870292887029289, 0.9057377049180327, 0.9700374531835206, 0.9209348156014941] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-500/SIMOUT.txt [0.8582677165354331, 0.7215686274509804, 0.9163179916317992, 0.8320514452060709] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-1000/SIMOUT.txt [0.8888888888888888, 0.8450184501845018, 0.9426229508196722, 0.8921767632976877] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-2000/SIMOUT.txt [0.8917748917748918, 0.8841201716738197, 0.9776785714285714, 0.9178578782924275] [[0.0, 500, 0.8435114503816794, 0.7590361445783133, 0.8818565400843882, 0.8281347116814604], [0.0, 1000, 0.8846153846153846, 0.8604651162790697, 0.9571984435797666, 0.9007596481580736], [0.0, 2000, 0.8870292887029289, 0.9057377049180327, 0.9700374531835206, 0.9209348156014941], [0.0001, 500, 0.8582677165354331, 0.7215686274509804, 0.9163179916317992, 0.8320514452060709], [0.0001, 1000, 0.8888888888888888, 0.8450184501845018, 0.9426229508196722, 0.8921767632976877], [0.0001, 2000, 0.8917748917748918, 0.8841201716738197, 0.9776785714285714, 0.9178578782924275]]
## In this chunk, go through and run RF classifier with only Genetic and Abundance stats
analysis_dir = "/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/"
GA_ErrorRates = []
specrates = np.array([0.0, 0.0001])
modnames = np.array(["neutral", "filtering", "competition"])
localcomsize = np.array([500, 1000, 2000])
params = [specrates, localcomsize]
params = list(itertools.product(*params))
for i, p in enumerate(params):
specrates, localcomsize = p
#print(specrates, localcomsize)
ldir = analysis_dir + "Speciation-{}/".format(specrates)
ldir = ldir + "LocalComSize-{}/".format(localcomsize)
ldir = ldir + "SIMOUT.txt"
print(ldir)
df = pd.read_csv(ldir, sep="\t", header=0)
## trait flag on False
classify_model = RF_classify(df, rf_random, trait_flag=False)
print(classify_model)
output = [specrates, localcomsize] + classify_model
GA_ErrorRates.append(output)
print(GA_ErrorRates)
csvData = GA_ErrorRates
with open('/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/GA_ErrorRates.csv', 'w') as csvFile:
writer = csv.writer(csvFile)
writer.writerows(csvData)
csvFile.close()
/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-500/SIMOUT.txt [0.5409836065573771, 0.490272373540856, 0.9149797570850202, 0.648745245727751] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-1000/SIMOUT.txt [0.5795918367346938, 0.5955056179775281, 0.9367088607594937, 0.7039354384905718] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-2000/SIMOUT.txt [0.5975609756097561, 0.6823529411764706, 0.9598393574297188, 0.7465844247386485] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-500/SIMOUT.txt [0.5241635687732342, 0.5604838709677419, 0.8614718614718615, 0.6487064337376125] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-1000/SIMOUT.txt [0.5776892430278885, 0.5311203319502075, 0.9727626459143969, 0.6938574069641642] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-2000/SIMOUT.txt [0.5757575757575758, 0.6788990825688074, 0.9790794979079498, 0.7445787187447777] [[0.0, 500, 0.5409836065573771, 0.490272373540856, 0.9149797570850202, 0.648745245727751], [0.0, 1000, 0.5795918367346938, 0.5955056179775281, 0.9367088607594937, 0.7039354384905718], [0.0, 2000, 0.5975609756097561, 0.6823529411764706, 0.9598393574297188, 0.7465844247386485], [0.0001, 500, 0.5241635687732342, 0.5604838709677419, 0.8614718614718615, 0.6487064337376125], [0.0001, 1000, 0.5776892430278885, 0.5311203319502075, 0.9727626459143969, 0.6938574069641642], [0.0001, 2000, 0.5757575757575758, 0.6788990825688074, 0.9790794979079498, 0.7445787187447777]]
## In this chunk, go through and run RF classifier with only Genetic and Trait stats
analysis_dir = "/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/"
GT_ErrorRates = []
specrates = np.array([0.0, 0.0001])
modnames = np.array(["neutral", "filtering", "competition"])
localcomsize = np.array([500, 1000, 2000])
params = [specrates, localcomsize]
params = list(itertools.product(*params))
for i, p in enumerate(params):
specrates, localcomsize = p
#print(specrates, localcomsize)
ldir = analysis_dir + "Speciation-{}/".format(specrates)
ldir = ldir + "LocalComSize-{}/".format(localcomsize)
ldir = ldir + "SIMOUT.txt"
print(ldir)
df = pd.read_csv(ldir, sep="\t", header=0)
## trait flag on False
classify_model = RF_classify(df, rf_random, abund_flag=False, trait_flag=True)
print(classify_model)
output = [specrates, localcomsize] + classify_model
GT_ErrorRates.append(output)
print(GT_ErrorRates)
csvData = GT_ErrorRates
with open('/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/GT_ErrorRates.csv', 'w') as csvFile:
writer = csv.writer(csvFile)
writer.writerows(csvData)
csvFile.close()
/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-500/SIMOUT.txt [0.803347280334728, 0.7859922178988327, 0.8928571428571429, 0.8273988803635679] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-1000/SIMOUT.txt [0.8795180722891566, 0.83203125, 0.9672131147540983, 0.8929208123477516] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-2000/SIMOUT.txt [0.8689138576779026, 0.8775510204081632, 0.9621848739495799, 0.9028832506785486] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-500/SIMOUT.txt [0.825, 0.7340823970037453, 0.8713692946058091, 0.8101505638698514] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-1000/SIMOUT.txt [0.8674698795180723, 0.7992565055762082, 0.9134199134199135, 0.8600487661713979] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-2000/SIMOUT.txt [0.9054054054054054, 0.8590308370044053, 0.9790794979079498, 0.9145052467725868] [[0.0, 500, 0.803347280334728, 0.7859922178988327, 0.8928571428571429, 0.8273988803635679], [0.0, 1000, 0.8795180722891566, 0.83203125, 0.9672131147540983, 0.8929208123477516], [0.0, 2000, 0.8689138576779026, 0.8775510204081632, 0.9621848739495799, 0.9028832506785486], [0.0001, 500, 0.825, 0.7340823970037453, 0.8713692946058091, 0.8101505638698514], [0.0001, 1000, 0.8674698795180723, 0.7992565055762082, 0.9134199134199135, 0.8600487661713979], [0.0001, 2000, 0.9054054054054054, 0.8590308370044053, 0.9790794979079498, 0.9145052467725868]]
## In this chunk, go through and run RF classifier with only Genetic and Abundance stats
analysis_dir = "/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/"
AT_ErrorRates = []
specrates = np.array([0.0, 0.0001])
modnames = np.array(["neutral", "filtering", "competition"])
localcomsize = np.array([500, 1000, 2000])
params = [specrates, localcomsize]
params = list(itertools.product(*params))
for i, p in enumerate(params):
specrates, localcomsize = p
#print(specrates, localcomsize)
ldir = analysis_dir + "Speciation-{}/".format(specrates)
ldir = ldir + "LocalComSize-{}/".format(localcomsize)
ldir = ldir + "SIMOUT.txt"
print(ldir)
df = pd.read_csv(ldir, sep="\t", header=0)
## trait flag on False
classify_model = RF_classify(df, rf_random, genetic_flag=False, abund_flag=True, trait_flag=True)
print(classify_model)
output = [specrates, localcomsize] + classify_model
AT_ErrorRates.append(output)
print(AT_ErrorRates)
csvData = AT_ErrorRates
with open('/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/AT_ErrorRates.csv', 'w') as csvFile:
writer = csv.writer(csvFile)
writer.writerows(csvData)
csvFile.close()
/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-500/SIMOUT.txt [0.8352490421455939, 0.8163265306122449, 0.8471074380165289, 0.8328943369247893] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-1000/SIMOUT.txt [0.8643410852713178, 0.84251968503937, 0.9493670886075949, 0.8854092863060942] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0/LocalComSize-2000/SIMOUT.txt [0.888030888030888, 0.9109311740890689, 0.9549180327868853, 0.917960031635614] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-500/SIMOUT.txt [0.8307692307692308, 0.7398373983739838, 0.8801652892561983, 0.8169239727998043] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-1000/SIMOUT.txt [0.8864468864468864, 0.8986784140969163, 0.9397590361445783, 0.908294778896127] /mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-2000/SIMOUT.txt [0.8648648648648649, 0.9166666666666666, 0.9469026548672567, 0.9094780621329294] [[0.0, 500, 0.8352490421455939, 0.8163265306122449, 0.8471074380165289, 0.8328943369247893], [0.0, 1000, 0.8643410852713178, 0.84251968503937, 0.9493670886075949, 0.8854092863060942], [0.0, 2000, 0.888030888030888, 0.9109311740890689, 0.9549180327868853, 0.917960031635614], [0.0001, 500, 0.8307692307692308, 0.7398373983739838, 0.8801652892561983, 0.8169239727998043], [0.0001, 1000, 0.8864468864468864, 0.8986784140969163, 0.9397590361445783, 0.908294778896127], [0.0001, 2000, 0.8648648648648649, 0.9166666666666666, 0.9469026548672567, 0.9094780621329294]]
##stole from Isaac
features = sim_df.iloc[:, 22:].columns
## Parameters to estimate
targets = ["alpha", "J_m", "ecological_strength", "m", "speciation_prob", "_lambda"]
X = sim_df[features]
y = sim_df[targets]
## Split the data
Xtrain, Xtest, ytrain, ytest = train_test_split(X, y)
display(Xtrain[:5])
display(ytrain[:5])
## also stole this chunk from ISaac
ldir = "/mnt/lfs2/ruff6699/Mess2.0/git/ModelPerformance_2/Speciation-0.0001/LocalComSize-1000/SIMOUT.txt"
df = pd.read_csv(ldir, sep="\t", header=0)
print(len(df))
## asign data
y = df['community_assembly_model']
X = df.loc[:, "S":"SGD_9"]
## split data
Xtrain, Xtest, ytrain, ytest = train_test_split(X, y)
## get best RF params
n_estimators = [int(x) for x in np.linspace(start = 200, stop = 2000, num = 10)]
max_depth = [int(x) for x in np.linspace(10, 110, num = 11)]
max_depth.append(None)
min_samples_split = [2, 5, 10]
min_samples_leaf = [1, 2, 4]
bootstrap = [True, False]
random_grid = {'n_estimators': n_estimators,
'max_depth': max_depth,
'min_samples_split': min_samples_split,
'min_samples_leaf': min_samples_leaf,
'bootstrap': bootstrap}
## Randomly search 100 different parameter combinations and take the
# ## one that reduces CV error
rf_random = RandomizedSearchCV(estimator = RandomForestClassifier(),\
param_distributions = random_grid,
n_iter = 100, cv = 3, verbose=0, n_jobs = -1,
error_score=np.nan)
# ## fit the training data using best params for RF
rf_random.fit(Xtrain, ytrain)
2993
RandomizedSearchCV(cv=3, error_score=nan, estimator=RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini', max_depth=None, max_features='auto', max_leaf_nodes=None, min_impurity_decrease=0.0, min_impurity_split=None, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators='warn', n_jobs=None, oob_score=False, random_state=None, verbose=0, warm_start=False), fit_params=None, iid='warn', n_iter=100, n_jobs=-1, param_distributions={'n_estimators': [200, 400, 600, 800, 1000, 1200, 1400, 1600, 1800, 2000], 'min_samples_split': [2, 5, 10], 'bootstrap': [True, False], 'max_depth': [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, None], 'min_samples_leaf': [1, 2, 4]}, pre_dispatch='2*n_jobs', random_state=None, refit=True, return_train_score='warn', scoring=None, verbose=0)
model = rf_random.best_estimator_
ypred = model.predict(Xtest)
cm = metrics.confusion_matrix(ypred, ytest)
print(cm)
err = []
for i in range(0,3):
#competition first, then filtering, then neutral, then average
acuracy = float(cm[i][i])
total = float(sum([cm[0][i], cm[1][i], cm[2][i]]))
err.append(acuracy/total)
print(err)
#ypred = model.predict(Xtest)
# print(ytest)
# print(ypred)
# cm = metrics.confusion_matrix(ypred, ytest)
## Split the data
# Xtrain, Xtest, ytrain, ytest = train_test_split(X, y)
# model = RandomForestClassifier(n_estimators=100, n_jobs=-1, min_samples_split=5, min_samples_leaf=4,\
# max_features='auto', max_depth=None, bootstrap=True)
# model.fit(Xtrain, ytrain)
# ypred = model.predict(Xtest)
# cm = metrics.confusion_matrix(ypred, ytest)
# err = []
# for i in range(0,3):
# #competition first, then filtering, then neutral, then average
# acuracy = float(cm[i][i])
# total = float(sum([cm[0][i], cm[1][i], cm[2][i]]))
# err.append(acuracy/total)
# #append avg error rate from our own external validation
# err.append(np.mean(err))
# #also append average error rate from cv function
# scores = cross_val_score(model, Xtrain, ytrain, cv=5)
# err.append(scores.mean())
[[213 34 6] [ 30 216 9] [ 3 6 232]] [0.8658536585365854, 0.84375, 0.9392712550607287]
##plot example store from isaac
lims = {"m":0.01, "speciation_prob":0.001}
for i, p in enumerate(targets):
fig, ax = plt.subplots()
vscore = metrics.explained_variance_score(y.iloc[:, i], cv_preds[:, i])
r2 = metrics.r2_score(y.iloc[:, i], cv_preds[:, i])
print(p, vscore, r2)
ax.scatter(y.iloc[:, i], cv_preds[:, i], c='black', marker='.', s=2)
ax.set_title(p)
if p in ["m", "speciation_prob"]:
ax.set_xlim(0, lims[p])
ax.set_ylim(0, lims[p])