Python dims_padua_set Exemples

Exemple #1

Fichier : tuningresults_lin_5.py Projet : riddhisw/nmqa

    SIMULATIONSDICT[padua_order] = {}
    
    if padua_order == "no_padua":
        SIMULATIONSDICT[padua_order]["max_iterations"] = GRIDSIZE * MULTIPLIER
        SIMULATIONSDICT[padua_order]["num_of_nodes"] = GRIDSIZE
    
    if padua_order == "regcoarse":
        SIMULATIONSDICT[padua_order]["max_iterations"] = COARSEGRID * MULTIPLIER
        SIMULATIONSDICT[padua_order]["num_of_nodes"] = GRIDSIZE + COARSEGRID # 16 sensor qubits + 25 data qubits; mutually exclusive 

    if padua_order == "regfine":
        SIMULATIONSDICT[padua_order]["max_iterations"] = (FINEGRID - REMOVE_DUPLICATES) * MULTIPLIER # RED0
        SIMULATIONSDICT[padua_order]["num_of_nodes"] = FINEGRID # 56 unique sensor qubits + 25 data qubits; after overlapping sensor qubits are removed

    if not isinstance(padua_order, str):
        SIMULATIONSDICT[padua_order]["max_iterations"] = dims_padua_set(padua_order) * MULTIPLIER
        SIMULATIONSDICT[padua_order]["num_of_nodes"] = dims_padua_set(padua_order) + GRIDSIZE
    
    SIMULATIONSDICT[padua_order]["linear"] = False # WTF is this
    SIMULATIONSDICT[padua_order]["repts"] = 50
    SIMULATIONSDICT[padua_order]["functype"]= 'lin'
    
    for idx_expandtype in ["Uniform", "TruncGauss"]:
    
        SIMULATIONSDICT[padua_order][idx_expandtype] = {}
        SIMULATIONSDICT[padua_order][idx_expandtype]["optimal"] = {}
        SIMULATIONSDICT[padua_order][idx_expandtype]["optimal"]["idx_1"] = None
        SIMULATIONSDICT[padua_order][idx_expandtype]["optimal"]["idx_2"] = None   
        SIMULATIONSDICT[padua_order][idx_expandtype]["optimal"]["idx_3"] = None  
    
        SIMULATIONSDICT[padua_order][idx_expandtype]["zerolambda"] = {}

Exemple #2

Fichier : extract_optimal_params_v2.py Projet : riddhisw/nmqa

########################
# Taking in bash parameters
########################
padua_order = int(sys.argv[1]) # Padua order. 1, 2, 3, 4, 5,...

idx_functype = int(sys.argv[2])
if idx_functype ==0:
    true_function_type = 'cheb2fun'
    MULTIPLIER=5
if idx_functype ==1:
    true_function_type = 'lin'
    MULTIPLIER=5
    

data_qubit_num = 25
max_iterations = int(dims_padua_set(padua_order) * MULTIPLIER)

########################
# Save to path 
########################

path = '/scratch/QCL_RG/qslam_padua_paper/' # on Artemis './data/'

########################
# Set Defaults
########################

particleconfigs = [ [3,2], [9,6], [15,10], [21,14], [30, 20]]

prefix = true_function_type+'_padua_ord_'+str(padua_order)+'_'
lambda_paris_2 = np.load('lambda_pairs_2.npz')