ex-6: generated plots
All the usefull plots were generated and the codes were suitably modified for this purpose.
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@ -6,7 +6,8 @@ import sys
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n = int(input())
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a, b, f = loadtxt(sys.stdin, unpack=True)
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figure(figsize=(6.3, 3))
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figure(figsize=(6.3, 2.5))
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plt.rcParams['font.size'] = 8
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subplot(131)
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title('FFT')
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@ -29,4 +30,6 @@ hist(a[2*n:], insert(b[2*n:], 0, a[2*n]), weights=f[2*n:],
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ticklabel_format(style='sci', axis='x', scilimits=(0, 0), useMathText=True)
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tight_layout()
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show()
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name = (sys.argv[1] if len(sys.argv) > 1 else "prova")
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savefig('notes/images/' + name + '.pdf' )
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@ -3,7 +3,8 @@
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from pylab import *
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import sys
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rcParams['font.size'] = 12
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plt.figure(figsize=(5, 3))
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rcParams['font.size'] = 8
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a, b, f = loadtxt(sys.stdin, unpack=True)
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title(sys.argv[1] if len(sys.argv) > 1 else "", loc='right')
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@ -11,5 +12,7 @@ hist(a, np.insert(b, 0, a[0]), weights=100*f/sum(f),
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histtype='stepfilled', color='#e3c5ca', edgecolor='#92182b')
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xlabel(r'$\theta$ (radians)')
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ylabel(r'$I(\theta)$ (a.u.)')
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tight_layout()
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show()
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name = sys.argv[2] if len(sys.argv) > 2 else "prova"
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savefig('notes/images/' + name + '.pdf' )
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75
ex-6/plots/emd-round-conv.txt
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75
ex-6/plots/emd-round-conv.txt
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@ -0,0 +1,75 @@
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#rounds mean stddev skew
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#σ = 1
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1 1.88e-04 1.4e-05 0.26
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2 3.17e-04 1.4e-05 0.19
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3 1.80e-04 1.4e-05 0.27
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4 2.02e-04 1.5e-05 0.21
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5 1.70e-04 1.4e-05 0.27
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6 1.64e-04 1.4e-05 0.27
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7 1.75e-04 1.4e-05 0.27
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8 1.67e-04 1.4e-05 0.27
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9 1.61e-04 1.4e-05 0.26
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10 1.57e-04 1.4e-05 0.25
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11 1.59e-04 1.4e-05 0.26
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12 1.56e-04 1.4e-05 0.25
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13 1.54e-04 1.4e-05 0.25
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14 1.53e-04 1.4e-05 0.25
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15 1.51e-04 1.4e-05 0.25
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16 1.50e-04 1.3e-05 0.25
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17 1.49e-04 1.3e-05 0.25
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18 1.48e-04 1.3e-05 0.25
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19 1.46e-04 1.3e-05 0.25
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20 1.47e-04 1.3e-05 0.25
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40 1.35e-04 1.3e-05 0.29
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60 1.28e-04 1.3e-05 0.31
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80 1.24e-04 1.3e-05 0.33
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100 1.21e-04 1.3e-05 0.35
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400 1.02e-04 1.2e-05 0.40
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800 9.37e-05 1.1e-05 0.36
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1600 8.61e-05 1.0e-05 0.27
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3800 7.98e-05 9.2e-06 0.26
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7600 7.97e-05 9.2e-06 0.28
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10000 8.06e-05 9.2e-06 0.26
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15000 8.16e-05 9.2e-06 0.25
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#σ = 0.5
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1 1.17e-04 8.0e-06 0.25
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2 2.47e-05 3.0e-06 0.32
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3 3.65e-05 3.8e-06 0.35
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4 5.85e-05 5.4e-06 0.34
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5 1.48e-05 3.3e-06 0.51
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6 1.82e-05 3.0e-06 0.44
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7 1.22e-05 3.8e-06 0.42
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8 1.31e-05 3.6e-06 0.47
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9 1.19e-05 3.9e-06 0.38
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10 1.17e-05 3.9e-06 0.36
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11 1.16e-05 4.0e-06 0.35
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12 1.16e-05 4.0e-06 0.34
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13 1.16e-05 4.0e-06 0.34
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14 1.16e-05 4.0e-06 0.34
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15 1.16e-05 4.0e-06 0.34
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16 1.16e-05 4.0e-06 0.34
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17 1.16e-05 4.0e-06 0.34
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18 1.16e-05 4.0e-06 0.34
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19 1.16e-05 4.0e-06 0.34
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20 1.16e-05 4.0e-06 0.34
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#σ = 0.1
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1 4.23e-16 3.1e-16 0.81
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2 4.23e-16 3.2e-16 0.85
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3 4.24e-16 3.1e-16 0.87
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4 4.24e-16 3.1e-16 0.88
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5 4.25e-16 3.2e-16 0.82
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6 4.25e-16 3.2e-16 0.82
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7 4.24e-16 3.1e-16 0.87
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8 4.24e-16 3.1e-16 0.87
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9 4.24e-16 3.1e-16 0.87
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10 4.25e-16 3.2e-16 0.82
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11 4.25e-16 3.2e-16 0.82
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12 4.24e-16 3.1e-16 0.87
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13 4.25e-16 3.2e-16 0.82
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14 4.24e-16 3.1e-16 0.87
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15 4.25e-16 3.2e-16 0.82
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16 4.24e-16 3.1e-16 0.87
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17 4.25e-16 3.2e-16 0.82
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18 4.24e-16 3.1e-16 0.87
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19 4.25e-16 3.2e-16 0.82
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20 4.24e-16 3.1e-16 0.87
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@ -3,10 +3,11 @@ import matplotlib.pyplot as plt
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def plot(table, title='', log=False):
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plt.figure(figsize=(6.3, 6))
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plt.figure(figsize=(5, 2))
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plt.rcParams['font.size'] = 8
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plt.suptitle(title)
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plt.subplot(211)
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plt.subplot(111)
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if log:
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plt.xscale('log')
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plt.title('EMD' + ' '*10, loc='right')
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@ -24,20 +25,22 @@ def plot(table, title='', log=False):
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twin.ticklabel_format(style='sci', axis='y',
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scilimits=(0, 0), useMathText=True)
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plt.subplot(212)
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if log:
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plt.xscale('log')
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plt.title('skewness', loc='right')
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plt.xlabel('RL rounds')
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plt.plot(table[0], table[3], color='xkcd:gray')
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# plt.subplot(212)
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# if log:
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# plt.xscale('log')
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# plt.title('skewness', loc='right')
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# plt.xlabel('RL rounds')
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# plt.plot(table[0], table[3], color='xkcd:gray')
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plt.tight_layout()
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table = np.loadtxt('ex-6/plots/emd-round.txt')
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table = np.loadtxt('ex-6/plots/emd-round-noise.txt')
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plot(table[:27].T, title='noiseless', log=True)
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plot(table[27:47].T, title=r'noise at $\sigma=0.005$')
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plot(table[47:67].T, title=r'noise at $\sigma=0.01$')
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plot(table[67:].T, title=r'noise at $\sigma=0.05$')
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plt.show()
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# plot(table[:27].T, title='noiseless', log=True)
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plot(table[27:47].T, title=r'noise at $\sigma_N = 0.005$')
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plt.savefig('notes/images/6-rounds-noise-0.005.pdf')
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plot(table[47:67].T, title=r'noise at $\sigma_N = 0.01$')
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plt.savefig('notes/images/6-rounds-noise-0.01.pdf')
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plot(table[67:].T, title=r'noise at $\sigma_N = 0.05$')
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plt.savefig('notes/images/6-rounds-noise-0.05.pdf')
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notes/images/6-noise-rounds-0.01.pdf
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notes/images/6-noisy.pdf
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notes/images/6-noisy.pdf
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notes/images/6-nonoise-emd-0.1.pdf
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notes/images/6-nonoise-emd-0.1.pdf
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notes/images/6-nonoise-emd-0.5.pdf
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notes/images/6-nonoise-emd-0.5.pdf
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notes/images/6-nonoise-emd-1.pdf
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notes/images/6-nonoise-emd-1.pdf
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notes/images/6-nonoise-rounds-1.pdf
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notes/images/6-nonoise-rounds-1.pdf
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