$ python
from SigProfilerMatrixGenerator import install as genInstall
genInstall.install('GRCh37')

importdata(datatype="matrix")

from SigProfilerExtractor import sigpro as sig
path_to_example_table = sig.importdata("matrix")
data = path_to_example_table 
# This "data" variable can be used as a parameter of the "project" argument of the sigProfilerExtractor function.

# To get help on the parameters and outputs of the "importdata" function, please use the following:
help(sig.importdata)

sigProfilerExtractor(input_type, out_put, input_data, reference_genome="GRCh37", opportunity_genome = "GRCh37", context_type = "default", exome = False, 
                         minimum_signatures=1, maximum_signatures=10, nmf_replicates=100, resample = True, batch_size=1, cpu=-1, gpu=False, 
                         nmf_init="random", precision= "single", matrix_normalization= "gmm", seeds= "random", 
                         min_nmf_iterations= 10000, max_nmf_iterations=1000000, nmf_test_conv= 10000, nmf_tolerance= 1e-15,nnls_add_penalty=0.05,
                         nnls_remove_penalty=0.01, initial_remove_penalty=0.05, de_novo_fit_penalty=0.02,get_all_signature_matrices= False)

from SigProfilerExtractor import sigpro as sig
def main_function():
    # to get input from vcf files
    path_to_example_folder_containing_vcf_files = sig.importdata("vcf")
    data = path_to_example_folder_containing_vcf_files # you can put the path to your folder containing the vcf     samples
    sig.sigProfilerExtractor("vcf", "example_output", data, minimum_signatures=1, maximum_signatures=3)
if __name__="__main__":
   main_function()

#Wait untill the excecution is finished. The process may a couple of hours based on the size of the data.
#Check the current working directory for the "example_output" folder.

def main_function():    
   # to get input from table format (mutation catalog matrix)
   path_to_example_table = sig.importdata("matrix")
   data = path_to_example_table # you can put the path to your tab delimited file containing the mutational catalog matrix/table
   sig.sigProfilerExtractor("matrix", "example_output", data, opportunity_genome="GRCh38", minimum_signatures=1,            maximum_signatures=3)
if __name__="__main__":
   main_function()

ebs.estimate_solution(base_csvfile="All_solutions_stat.csv", 
          All_solution="All_Solutions", 
          genomes="Samples.txt", 
          output="results", 
          title="Selection_Plot",
          stability=0.8, 
          min_stability=0.2, 
          combined_stability=1.25)

from SigProfilerExtractor import estimate_best_solution as ebs
ebs.estimate_solution(base_csvfile="All_solutions_stat.csv", 
          All_solution="All_Solutions", 
          genomes="Samples.txt", 
          output="results", 
          title="Selection_Plot",
          stability=0.8, 
          min_stability=0.2, 
          combined_stability=1.25)

decompose(signatures, activities, samples,  output, signature_database=None, nnls_add_penalty=0.05, nnls_remove_penalty=0.01, initial_remove_penalty=0.05, de_novo_fit_penalty=0.02, genome_build="GRCh37", refit_denovo_signatures=True, make_decomposition_plots=True, connected_sigs=True, verbose=False,collapse_to_SBS96=True,newsignature_threshold=0.8)

from SigProfilerExtractor import decomposition as decomp
signatures = "path/to/De_Novo_Solution_Signatures.txt"
activities="path/to/De_Novo_Solution_Activities.txt"
samples="path/to/Samples.txt"
output="name or path/to/output"
decomp.decompose(signatures, activities, samples, output, genome_build="GRCh37", signature_database=None, verbose=False,collapse_to_SBS96=True)

plotActivity(activity_file, output_file = "Activity_in_samples.pdf", bin_size = 50, log = False)