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Felix Stutz
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from global_types.parametric.Generators import ParametricKinds
from parser.InputParser import get_tplv_gt_from_file
import time
from math import trunc
import numpy as np
import glob
def write_avg_mst_results(folder_name):
write_mst_averages_to_file(ParametricKinds.LOAD_BALANCER, folder_name)
write_mst_averages_to_file(ParametricKinds.LOGGING, folder_name)
write_mst_averages_to_file(ParametricKinds.MAP_REDUCE, folder_name)
write_mst_averages_to_file(ParametricKinds.MEM_CACHE, folder_name)
write_mst_averages_to_file(ParametricKinds.P2P_BROADCAST, folder_name)
write_mst_averages_to_file(ParametricKinds.TREE_BROADCAST, folder_name)
def write_param_size(folder_name):
write_param_file_to_file(ParametricKinds.LOAD_BALANCER, folder_name)
write_param_file_to_file(ParametricKinds.LOGGING, folder_name)
write_param_file_to_file(ParametricKinds.MAP_REDUCE, folder_name)
write_param_file_to_file(ParametricKinds.MEM_CACHE, folder_name)
write_param_file_to_file(ParametricKinds.P2P_BROADCAST, folder_name)
write_param_file_to_file(ParametricKinds.TREE_BROADCAST, folder_name)
def write_mst_averages_to_file(directory, kind):
prefix = "*evaluation"
out_filename = directory + "a_summary_" + kind.value + ".txt"
pattern = directory + prefix + "*.txt"
files = glob.glob(pattern)
data = [np.loadtxt(f, skiprows=1) for f in files]
x = np.array([d[:, 2] for d in data])
# use mask to exclude max and min
# x_mask = np.logical_or(x == x.max(1, keepdims=1), x == x.min(1, keepdims=1))
# x_masked = np.ma.masked_array(x, x_mask)
# m = np.(x_masked, axis=0)
m = np.mean(x, axis=0)
snd = data[0][:, 1] # use [0, 1] instead of 1 for size of type
without_size = np.column_stack([snd, m])
np.savetxt(out_filename, without_size)
def write_param_file_to_file(directory, kind):
prefix = "*evaluation"
out_filename = directory + "a_mapping_" + kind.value + ".txt"
pattern = directory + prefix + "*.txt"
files = glob.glob(pattern)
file = files[0]
data = np.loadtxt(file, skiprows=1)
size = data[:, 0]
param = data[:, 1]
param_size = np.column_stack([param, size])
np.savetxt(out_filename, param_size)
# helper function
def get_unified_repr_floats(number):
return "%10.3f" % number