def sample_variation(gameParameters, modelParameters, model, n_samples=100):
print('Obtaining', n_samples, 'samples (please be patient!)...')
nombre = 'Simulations/Sample_size/' + model + '/sample'
for i in range(n_samples):
E = DL.Experiment(gameParameters, modelParameters)
E.run_simulation()
data = M.get_measures(E.df, '0')
archivo = nombre + str(i + 1) + '.csv'
data.to_csv(archivo, index=False)
def parameter_sweep_2(gameParameters, modelParameters):
# Sweep epsilon vs zeta
print("****************************")
print('Starting parameter sweep')
print("****************************")
print('--- Game parameters ---')
print('Probabilit of a unicorn: ', gameParameters[0])
print('Number of players: ', gameParameters[1])
print('Grid size: ',
str(gameParameters[2]) + ' x ' + str(gameParameters[2]))
print('Number of rounds: ', gameParameters[3])
print('Number of dyads: ', gameParameters[4])
print("\n")
print('--- Fixed parameters ----')
print('Focal: ', modelParameters[0])
print('alpha: ', modelParameters[1])
print('beta: ', modelParameters[2])
print('gamma: ', modelParameters[3])
print('delta: ', modelParameters[4])
# print('epsilon: ', modelParameters[5])
# print('zeta: ', modelParameters[6])
print('eta: ', modelParameters[7])
print('FOCAL: ', modelParameters[8])
print("\n")
print("Sweeping epsilon and zeta parameters...")
# Intervals for sweep
forEpsilon = [1]
forZeta = [20]
print('--- Sweep parameters ----')
print('epsilon: ', forEpsilon)
print('zeta: ', forZeta)
for i in list(forEpsilon):
for j in list(forZeta):
print('\n----------')
print('Sweep ' + str(i) + ', ' + str(j))
modelParameters[5] = i
modelParameters[6] = j
E = DL.Experiment(gameParameters, modelParameters)
E.run_simulation()
E.get_measures()
E.df['Epsilon'] = [i] * len(E.df['Dyad'])
E.df['Zeta'] = [j] * len(E.df['Dyad'])
outputFile = 'Sweeps/out_Epsilon' + str(i) + '-Zeta' + str(
j) + '.csv'
E.df.to_csv(outputFile, index=False)
print("Results saved to " + outputFile)
def sensitivityModelRecovery(gameParameters, modelParameters, badApples):
print("****************************")
print('Starting simulation')
print("****************************")
print('--- Model parameters ----')
print('w: ', modelParameters[0])
print('alpha: ', modelParameters[1])
print('beta: ', modelParameters[2])
print('gamma: ', modelParameters[3])
print('delta: ', modelParameters[4])
print('epsilon: ', modelParameters[5])
print('zeta: ', modelParameters[6])
print('eta: ', modelParameters[7])
print("\n")
print('--- Game parameters ---')
print('Probabilit of a unicorn: ', gameParameters[0])
print('Number of players: ', gameParameters[1])
print('Grid size: ',
str(gameParameters[2]) + ' x ' + str(gameParameters[2]))
print('Number of rounds: ', gameParameters[3])
print('Number of dyads: ', gameParameters[4])
print('Number of bad apples: ', badApples)
print("\n")
E = DL.Experiment(gameParameters, modelParameters)
Total_Dyads = gameParameters[4]
print("\n")
print('Including ' + str(badApples) + ' bad apples...')
for j in range(Total_Dyads - badApples):
print("****************************")
print("Running dyad no. ", j + 1, "--GOOD")
print("****************************\n")
E.run_dyad()
for j in range(badApples):
print("****************************")
print("Running dyad no. ", j + 1 + Total_Dyads - badApples, "--BAD")
print("****************************\n")
E.run_dyad_with_parameters(0.1, 10)
E.get_measures()
f = 'Sweeps/sensitivity_' + str(badApples) + '.csv'
E.df.to_csv(f, index=False)
print('Data saved to', f)
def parameter_sweep_Zeta(gameParameters, modelParameters):
# Sweep RS
print("****************************")
print('Starting parameter sweep')
print("****************************")
print('--- Game parameters ---')
print('Probabilit of a unicorn: ', gameParameters[0])
print('Number of players: ', gameParameters[1])
print('Grid size: ',
str(gameParameters[2]) + ' x ' + str(gameParameters[2]))
print('Number of rounds: ', gameParameters[3])
print('Number of dyads: ', gameParameters[4])
print("\n")
print('--- Fixed parameters ----')
print('Focal: ', modelParameters[0])
print('alpha: ', modelParameters[1])
print('beta: ', modelParameters[2])
print('gamma: ', modelParameters[3])
print('delta: ', modelParameters[4])
print('epsilon: ', modelParameters[5])
# print('zeta: ', modelParameters[6])
print('eta: ', modelParameters[7])
print("\n")
print("Sweeping Zeta...")
# Intervals for sweep
forSweep = [0, 1, 10]
print('--- Sweep parameters ----')
print('zeta: ', forSweep)
for i in list(forSweep):
print('\n----------')
print('Sweep zeta=' + str(i))
modelParameters[6] = i
E = DL.Experiment(gameParameters, modelParameters)
E.run_simulation()
E.get_measures()
E.df['Zeta'] = [i] * len(E.df['Dyad'])
outputFile = 'Sweeps/out_Zeta_' + str(i) + '.csv'
E.df.to_csv(outputFile, index=False)
print("Results saved to " + outputFile)
def standard_simulation(gameParameters,
modelParameters,
medidas,
shaky_hand=1,
TO_FILE=True):
print("****************************")
print('Starting simulation')
print("****************************")
print('--- Model parameters ----')
print('wALL: ', modelParameters[0])
print('wNOTHING: ', modelParameters[1])
print('wLEFT: ', modelParameters[2])
print('wIN: ', modelParameters[3])
print('alpha: ', modelParameters[4])
print('beta: ', modelParameters[5])
print('gamma: ', modelParameters[6])
print('delta: ', modelParameters[7])
print('epsilon: ', modelParameters[8])
print('zeta: ', modelParameters[9])
print("\n")
print("****************************")
print('--- Game parameters ---')
print('Probabilit of a unicorn: ', gameParameters[0])
print('Number of players: ', gameParameters[1])
print('Grid size: ',
str(gameParameters[2]) + ' x ' + str(gameParameters[2]))
print('Number of rounds: ', gameParameters[3])
print('Number of dyads: ', gameParameters[4])
print("\n")
E = DL.Experiment(gameParameters, modelParameters, shaky_hand)
if TO_FILE:
with open('temp.csv', 'w') as dfile:
dfile.write(
'index,Dyad,Round,Player,Answer,Time,a11,a12,a13,a14,a15,a16,a17,a18,a21,a22,a23,a24,a25,a26,a27,a28,a31,a32,a33,a34,a35,a36,a37,a38,a41,a42,a43,a44,a45,a46,a47,a48,a51,a52,a53,a54,a55,a56,a57,a58,a61,a62,a63,a64,a65,a66,a67,a68,a71,a72,a73,a74,a75,a76,a77,a78,a81,a82,a83,a84,a85,a86,a87,a88,Score,Joint,Is_there,where_x,where_y,Strategy\n'
)
dfile.close()
E.df = pd.read_csv('temp.csv')
E.run_simulation()
if TO_FILE:
E.df = pd.read_csv('temp.csv')
M = Measures.Measuring(data=E.df, Num_Loc=8, TOLERANCIA=0)
E.df = M.get_measures(medidas)
E.save()
def data_conf_mtrx(gameParameters, modelParameters, model, count):
print("****************************")
print('Starting simulation with model', model)
print("****************************")
print('--- Model parameters ----')
print('wALL: ', modelParameters[0])
print('wNOTHING: ', modelParameters[1])
print('wLEFT: ', modelParameters[2])
print('wIN: ', modelParameters[3])
print('alpha: ', modelParameters[4])
print('beta: ', modelParameters[5])
print('gamma: ', modelParameters[6])
print('delta: ', modelParameters[7])
print('epsilon: ', modelParameters[8])
print('zeta: ', modelParameters[9])
print("****************************")
print('--- Game parameters ---')
print('Probabilit of a unicorn: ', gameParameters[0])
print('Number of players: ', gameParameters[1])
print('Grid size: ',
str(gameParameters[2]) + ' x ' + str(gameParameters[2]))
print('Number of rounds: ', gameParameters[3])
print('Number of dyads: ', gameParameters[4])
print("\n")
E = DL.Experiment(gameParameters, modelParameters, shaky_hand=1)
with open('temp.csv', 'w') as dfile:
dfile.write(
'index,Dyad,Round,Player,Answer,Time,a11,a12,a13,a14,a15,a16,a17,a18,a21,a22,a23,a24,a25,a26,a27,a28,a31,a32,a33,a34,a35,a36,a37,a38,a41,a42,a43,a44,a45,a46,a47,a48,a51,a52,a53,a54,a55,a56,a57,a58,a61,a62,a63,a64,a65,a66,a67,a68,a71,a72,a73,a74,a75,a76,a77,a78,a81,a82,a83,a84,a85,a86,a87,a88,Score,Joint,Is_there,where_x,where_y,Strategy\n'
)
dfile.close()
E.df = pd.read_csv('temp.csv')
E.run_simulation()
E.df = pd.read_csv('temp.csv')
M = Measures.Measuring(data=E.df, Num_Loc=8, TOLERANCIA=0)
E.df = M.get_measures('1')
archivo = './Data/Confusion/sim_conf_mtx_'
E.save(archivo)
E.df.to_csv(archivo, index=False)
rel_data_sim = [count] + [str(model)] + modelParameters[:10]
dfAux = pd.DataFrame([rel_data_sim])
with open('./Data/Confusion/sim_data_rel.csv', 'a') as f:
dfAux.to_csv(f, header=False, index=False)
def exploreSampleSizeEffect(gameParameters, modelParameters, lst):
for l in lst:
gameParameters = gameParameters[:4] + [l]
print("****************************")
print('Starting simulation', l)
print("****************************")
print('--- Model parameters ----')
print('wALL: ', modelParameters[0])
print('wNOTHING: ', modelParameters[0])
print('wDOWN: ', modelParameters[0])
print('wIN: ', modelParameters[0])
print('alpha: ', modelParameters[1])
print('beta: ', modelParameters[2])
print('gamma: ', modelParameters[3])
print('delta: ', modelParameters[4])
print('epsilon: ', modelParameters[5])
print('zeta: ', modelParameters[6])
print('eta: ', modelParameters[7])
print('FOCAL: ', modelParameters[8])
print("\n")
print('--- Game parameters ---')
print('Probabilit of a unicorn: ', gameParameters[0])
print('Number of players: ', gameParameters[1])
print('Grid size: ',
str(gameParameters[2]) + ' x ' + str(gameParameters[2]))
print('Number of rounds: ', gameParameters[3])
print('Number of dyads: ', gameParameters[4])
print("\n")
E = DL.Experiment(gameParameters, modelParameters)
E.run_simulation()
E.get_measures()
f = 'Sweeps/output_' + str(l) + '.csv'
E.df.to_csv(f, index=False)
print('Data saved to', f)
print('beta: ', playerParameters2['beta'])
print('gamma: ', playerParameters2['gamma'])
print('delta: ', playerParameters2['delta'])
print('epsilon: ', playerParameters2['epsilon'])
print('zeta: ', playerParameters2['zeta'])
print("****************************")
print('--- Game parameters ---')
print('Probability of unicorn: ', gameParameters[0])
print('Number of players: ', gameParameters[1])
print('Grid size: ',
str(gameParameters[2]) + ' x ' + str(gameParameters[2]))
print('Number of rounds: ', gameParameters[3])
print('Number of dyads: ', gameParameters[4])
print("\n")
E = DL.Experiment(gameParameters, [playerParameters1, playerParameters2],
non_shaky_hand=non_shaky_hand)
if TO_FILE:
with open('temp.csv', 'w') as dfile:
dfile.write(
'index,Dyad,Round,Player,Answer,a11,a12,a13,a14,a15,a16,a17,a18,a21,a22,a23,a24,a25,a26,a27,a28,a31,a32,a33,a34,a35,a36,a37,a38,a41,a42,a43,a44,a45,a46,a47,a48,a51,a52,a53,a54,a55,a56,a57,a58,a61,a62,a63,a64,a65,a66,a67,a68,a71,a72,a73,a74,a75,a76,a77,a78,a81,a82,a83,a84,a85,a86,a87,a88,Score,Joint,Is_there,Strategy\n'
)
dfile.close()
E.df = pd.read_csv('temp.csv')
E.run_simulation()
if TO_FILE:
E.df = pd.read_csv('temp.csv')
M = Measures.Measuring(data=E.df, Num_Loc=Num_Loc, TOLERANCE=0)
E.df = M.get_measures(measures)
if TO_FILE: os.remove("temp.csv")
archivo = f'./Simulations/MB{contador}.csv'
E.save(archivo)
print('Starting simulation')
print("****************************")
print('--- Model parameters ----')
print('alpha: ', playerParameters['alpha'])
print('beta: ', playerParameters['beta'])
print('gamma: ', playerParameters['gamma'])
print('delta: ', playerParameters['delta'])
print('epsilon: ', playerParameters['epsilon'])
print('zeta: ', playerParameters['zeta'])
print("\n")
print("****************************")
print('--- Game parameters ---')
print('Threshold: ', gameParameters[0])
print('Number of players: ', gameParameters[1])
print('Number of rounds: ', gameParameters[2])
print('Number of groups: ', gameParameters[3])
print("\n")
E = DL.Experiment(gameParameters, playerParameters)
if TO_FILE:
with open('temp.csv', 'w') as dfile:
head = 'index,Group,Round,Player,Decision,Score,Strategy\n'
dfile.write(head)
E.df = pd.read_csv('temp.csv')
E.run_simulation()
if TO_FILE:
E.df = pd.read_csv('temp.csv')
os.remove("temp.csv")
#M = Measures.Measuring(data=E.df, Num_Loc=rounds, TOLERANCE=0)
#E.df = M.get_measures(measures)
E.save()
def parameter_sweep_delta(gameParameters, modelParameters, forSweep):
# Sweep delta
print("****************************")
print('Starting parameter sweep')
print("****************************")
print('--- Game parameters ---')
print('Probabilit of a unicorn: ', gameParameters[0])
print('Number of players: ', gameParameters[1])
print('Grid size: ',
str(gameParameters[2]) + ' x ' + str(gameParameters[2]))
print('Number of rounds: ', gameParameters[3])
print('Number of dyads: ', gameParameters[4])
print("\n")
print('--- Fixed parameters ----')
print('--- Player 1 ----')
print('wALL: ', modelParameters[0])
print('wNOTHING: ', modelParameters[1])
print('wLEFT: ', modelParameters[2])
print('wIN: ', modelParameters[3])
print('alpha: ', modelParameters[4])
print('beta: ', modelParameters[5])
print('gamma: ', modelParameters[6])
# print('delta: ', modelParameters[7])
print('epsilon: ', modelParameters[8])
print('zeta: ', modelParameters[9])
print('eta:', modelParameters[10])
print('theta:', modelParameters[11])
print('iota:', modelParameters[12])
print("\n")
print('--- Player 2 ----')
print('wALL: ', modelParameters[13])
print('wNOTHING: ', modelParameters[14])
print('wLEFT: ', modelParameters[15])
print('wIN: ', modelParameters[16])
print('alpha: ', modelParameters[17])
print('beta: ', modelParameters[18])
print('gamma: ', modelParameters[19])
# print('delta: ', modelParameters[20])
print('epsilon: ', modelParameters[21])
print('zeta: ', modelParameters[22])
print('eta:', modelParameters[23])
print('theta:', modelParameters[24])
print('iota:', modelParameters[25])
print('--- Sweep parameters ----')
print('delta in', forSweep)
print('\n----------')
for i in forSweep:
print("Sweeping delta...")
print('alpha=' + str(i))
modelParameters[7] = i
modelParameters[20] = i
E = DL.Experiment(gameParameters, modelParameters)
with open('temp.csv', 'w') as dfile:
dfile.write(
'index,Dyad,Round,Player,Answer,Time,a11,a12,a13,a14,a15,a16,a17,a18,a21,a22,a23,a24,a25,a26,a27,a28,a31,a32,a33,a34,a35,a36,a37,a38,a41,a42,a43,a44,a45,a46,a47,a48,a51,a52,a53,a54,a55,a56,a57,a58,a61,a62,a63,a64,a65,a66,a67,a68,a71,a72,a73,a74,a75,a76,a77,a78,a81,a82,a83,a84,a85,a86,a87,a88,Score,Joint,Is_there,where_x,where_y,Strategy\n'
)
dfile.close()
with open('output_Prev.csv', 'w') as dfile:
dfile.write(
'index,Dyad,Round,Player,Answer,Time,a11,a12,a13,a14,a15,a16,a17,a18,a21,a22,a23,a24,a25,a26,a27,a28,a31,a32,a33,a34,a35,a36,a37,a38,a41,a42,a43,a44,a45,a46,a47,a48,a51,a52,a53,a54,a55,a56,a57,a58,a61,a62,a63,a64,a65,a66,a67,a68,a71,a72,a73,a74,a75,a76,a77,a78,a81,a82,a83,a84,a85,a86,a87,a88,Score,Joint,Is_there,where_x,where_y,Strategy,Is_there_LEAD,Category,Category1,RegionGo\n'
)
dfile.close()
E.run_simulation()
E.df = pd.read_csv('temp.csv')
E.df = M.get_measures(E.df, '05')
E.df['Delta'] = i
outputFile = '../Data/Sweeps/out_Delta_' + str(i) + '.csv'
E.df.to_csv(outputFile, index=False)
print("Results saved to " + outputFile)