From b152ec0627e23d4c15b866ae8ccaea0b0d5a2864 Mon Sep 17 00:00:00 2001 From: giomba Date: Sat, 28 Dec 2019 12:13:22 +0100 Subject: [PATCH] cleanup: removed unused python scripts --- simulation/drawplot.sh | 5 --- simulation/plot.py | 39 ----------------------- simulation/pretty.py | 63 ------------------------------------- simulation/requirements.txt | 10 ------ 4 files changed, 117 deletions(-) delete mode 100755 simulation/drawplot.sh delete mode 100644 simulation/plot.py delete mode 100644 simulation/pretty.py delete mode 100644 simulation/requirements.txt diff --git a/simulation/drawplot.sh b/simulation/drawplot.sh deleted file mode 100755 index 67c8c37..0000000 --- a/simulation/drawplot.sh +++ /dev/null @@ -1,5 +0,0 @@ -#!/bin/bash - -python pretty.py | sort -n > pretty.csv -python plot.py - diff --git a/simulation/plot.py b/simulation/plot.py deleted file mode 100644 index 873de68..0000000 --- a/simulation/plot.py +++ /dev/null @@ -1,39 +0,0 @@ -import matplotlib.pyplot as plt -import matplotlib.patches as mpatches -import numpy as numpy -import pandas as pd - -def getcolor(n): - return ['#aa0000', '#00aa00', '#0000aa', '#aaaa00', '#aa00aa'][int((i - 12) / 2)] - -df = pd.read_csv('pretty.csv', delimiter='\s', engine='python') - -x = df['k'].unique() - -for i in df['i_min'].unique(): - rows = df.loc[df['i_min'] == i] - plt.errorbar( - x, - rows['mean'], - yerr=rows['ci'], - marker='.', - capsize=4, - ms=3, - mec='r', - mfc='r', - linestyle='-', - linewidth=1, - color=getcolor(i), - ecolor='red' - ) - -handles = [] -for i in df['i_min'].unique(): - handles.append(mpatches.Patch(color=getcolor(i), label='Imin = ' + str(i))) - -plt.ylim([0, 1400]) - -plt.legend(handles=handles) - -plt.show() - diff --git a/simulation/pretty.py b/simulation/pretty.py deleted file mode 100644 index 039ba1e..0000000 --- a/simulation/pretty.py +++ /dev/null @@ -1,63 +0,0 @@ -import matplotlib.pyplot as plt -import numpy as np -import pandas as pd -import csv -import os -import re -import statistics - -### PARAMETERS ### -RESULTSDIR='results/' - -### FUNCTIONS ### -def compute_confidence_interval(samples): # 95% - stdev = statistics.stdev(samples) - ci = 1.96 * stdev / np.sqrt(len(samples)) - return ci - -### GLOBAL VARIABLES ### -all_route_discovery = dict() - -### MAIN ### -for filename in os.listdir(RESULTSDIR): - df = pd.read_csv(RESULTSDIR + '/' + filename, - delimiter='\s|\t', - index_col=0, - nrows=4, - engine='python', - header=None).T - - kappa = int(df['KAPPA'].to_string().split()[1]) - i_min = int(df['I_MIN'].to_string().split()[1]) - key = str(kappa) + ':' + str(i_min) - - if (not key in all_route_discovery): - all_route_discovery[key] = { 'samples': [], 'k': kappa, 'i_min': i_min, 'count': 0 } - - all_route_discovery[key]['count'] += 1 - - with open(RESULTSDIR + '/' + filename) as file: - for line in file: - if (re.match('ALL-ROUTE-DISCOVERY', line)): - t = int(line.split()[1]) / (10**6) - all_route_discovery[key]['samples'].append(t) - break - -# now, for every k, i_min, i_max -# all_route_discovery contains an array with all samples of the measured value - -print('k i_min count mean ci') -for simulation in all_route_discovery: - all_route_discovery[simulation]['mean'] = np.mean(all_route_discovery[simulation]['samples']) - all_route_discovery[simulation]['ci'] = compute_confidence_interval(all_route_discovery[simulation]['samples']) - - print( - all_route_discovery[simulation]['k'], - all_route_discovery[simulation]['i_min'], - all_route_discovery[simulation]['count'], - all_route_discovery[simulation]['mean'], - all_route_discovery[simulation]['ci'] - ) - -exit(0) - diff --git a/simulation/requirements.txt b/simulation/requirements.txt deleted file mode 100644 index cfb5eff..0000000 --- a/simulation/requirements.txt +++ /dev/null @@ -1,10 +0,0 @@ -cycler==0.10.0 -kiwisolver==1.1.0 -matplotlib==3.1.2 -numpy==1.17.4 -pandas==0.25.3 -pkg-resources==0.0.0 -pyparsing==2.4.5 -python-dateutil==2.8.1 -pytz==2019.3 -six==1.13.0