How to install and run spicker?

1, download and unpack spicker.tar.gz.
2, run ./spicker. If the program does not run, you may need
   to re-compile spicker.f in your computer. The current version
   is compiled by (depending on the compilers in your computer)
   >gfortran -static -O3 -ffast-math -lm -o $1 $1.f
   or
   >g77 -static -O3 -o -lm $1 $1.f


The following is the head of 'spicker.f', which can be helpful for you
to prepare your decoy inputs and explain the output results:

*******************************************************************************
*     SPICKER_3.0, released on Spril 21, 2016
*     
*     This program, Structure-PICKER (SPICKER), aims at selecting the 
*     best fold of lowest free-energy by clustering structural decoys
*     generated by I-TASSER or other protein structure assembly simulations. 
*     Comments and bug reports should be addressed to zhanglab@zhanggroup.org
*
*     Reference: 
*     Y Zhang, J Skolnick, Journal of Computational Chemistry, 2004 25: 865-871
*
*     Permission to use, copy, modify, and distribute this program for 
*     any purpose, with or without fee, is hereby granted, provided that
*     the notices on the head, the reference information, and this
*     copyright notice appear in all copies or substantial portions of 
*     the Software. It is provided "as is" without express or implied 
*     warranty.
******************* Updating history ************************************
*     2009/01/24: A bug with regard to the input format is fixed 
*     2010/08/02: SPICKER V2.0 is released. A new option is added to 
*                 automatically tune RMSD cutoff based on variation of
*                 decoy distributions. This option works best for decoys
*                 generated by ab initio simulations, such as QUARK.
*     2010/09/14: modified 'seq.dat' to a simplied format
*     2010/12/29: modified 'rmsinp' to a simplied format
*     2016/04/21: added an option to cluster decoys using 1/TM-score to replace
*                 RMSD as the distance scale. This part is written by
*                 Dr. Jens Thomas.
*************************************************************************
*
*     Input files includes:
*       'rmsinp'---Mandatory, length of protein & piece for RMSD calculation
*       'seq.dat'--Mandatory, sequence file, for output of PDB models
*       'tra.in'---Mandatory, list of trajectory names used for clustering
*                  In the first line of 'tra.in', there are 3 parameters:
*                  par1: number of decoy files
*                  par2: 1, default cutoff, best for clustering decoys from 
*                           template-based modeling; 
*                       -1, cutoff based on variation, best for clustering 
*                           decoys from ab initio modeling.
*                       -2, cluster based on 1/TM-scores
*                  par3: 1, select closc from all decoys; 
*                       -1, closc from clustered decoys (slighly faster)
*                  From second lines are file names which contain coordinates
*                  of 3D structure decoys. All these files are mandatory. See 
*                  attached 'rep1.tra1' etc for the format of decoys.
*       'rep1.tra1', 'rep2.tra1', ... ---decoy files     which should have the
*                  same name as those listed in 'tra.in'. In the first line, 
*                  the first number is the length of the decoy; the second 
*                  number is the energy of the decoy (if you donot know the 
*                  energy you can put any number there); the third and fourth 
*                  numbers are not necessary and useless. 
*	           Starting from the second line, the coordinates (x,y,z) of 
*	           C-alpha atoms are listed.
*       'CA'-------Optional, native structure, for comparison to native.
*
*     Output files includes:
*       'str.txt'-----list of structure in cluster;
*       'combo*.pdb'--PDB format of cluster centroids;
*       'closc*.pdb'--PDB format of structures closest to centroids;
*       'rst.dat'-----summary of clustering results;
*
*     Important data and explanations in 'rst.dat':
*     ------------ summary of clusers -------------------
*     i Size R_cut density R_cl_co   <E>    E_model  #str Trajectory    
*     B--------------------------------------------------
*     1   109  5.90    18.  1.67  -2200.5  -2272.2    57 rep2.tra1    
*     2    12  5.90     2.  0.70    505.6    580.4     5 rep1.tra1    
*     3    11  5.90     2.  0.97    742.9    926.9     1 rep1.tra1    
*     4    19  5.90     3.  0.66  -2062.5  -2057.1    26 rep1.tra1    
*     5     6  5.90     1.  0.44    219.5    215.0    13 rep1.tra1    
*     ---------------------  ---------------------
*     i  N_in  <R_in> <Rc_in>   N_ex  <R_ex> <Rc_ex>
*     C---------------------------------------------
*     1   109   3.31   2.75     109   3.31   2.75
*     2    12   1.54   0.92      12   1.54   0.92
*     3    11   1.72   1.19      11   1.72   1.19
*     4    19   1.27   1.15       9   1.10   1.03
*     5     6   0.96   0.69       6   0.96   0.69
*     
*     Size------number of decoy structures in the cluster
*     R_cut-----RMSD cutoff for defining the clusters
*     density---size/R_cut
*     R_cl_co---RMSD distance between combo and closc
*     <E>-------average energy of decoys in the cluster
*     #str & Trajectory----in this example, the cluster center of the first 
*                          cluster comes from 57th decoy in 'rep2.tra1'
*     N_in------number of structure decoys in the cluster (=size)
*     <R_in>----average RMSD of decoys to cluster center
*     <Rc_in>---average RMSD of decoys to cluster centroid
*               (in I-TASSER, cluster_density=N_in/<Rc_in>)
*     N_ex------number of structure decoys in the cluster, after excluding
*               decoys from previous clustering
*     <R_ex>----average RMSD of decoys to cluster center, after excluding
*               decoys from previous clustering
*     <Rc_ex>---average RMSD of decoys to cluster centroid, after excluding
*               decoys from previous clustering
*
*******************************************************************************