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Merge branch 'master' of https://whale.am28.uni-tuebingen.de/git/teaching/scientificComputing

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This commit is contained in:
Jan Grewe 2020-10-28 09:09:06 +01:00
commit e7679d72d8
18 changed files with 211 additions and 310 deletions
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2
bootstrap/lecture/bootstrapsem.py
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@ -38,7 +38,7 @@ ax.annotate('sampling\ndistribution',
connectionstyle="angle3,angleA=20,angleB=120") ) connectionstyle="angle3,angleA=20,angleB=120") )
ax.annotate('bootstrap\ndistribution', ax.annotate('bootstrap\ndistribution',
xy=(0.13, 3.3), xycoords='data', xy=(0.13, 3.3), xycoords='data',
xytext=(0.25, 4), textcoords='data', xytext=(0.22, 4), textcoords='data',
arrowprops=dict(arrowstyle="->", relpos=(0.0,0.5), arrowprops=dict(arrowstyle="->", relpos=(0.0,0.5),
connectionstyle="angle3,angleA=20,angleB=60") ) connectionstyle="angle3,angleA=20,angleB=60") )
ax.bar(bins[:-1]-0.25*db, hmusrs, 0.5*db, **fsB) ax.bar(bins[:-1]-0.25*db, hmusrs, 0.5*db, **fsB)

8
bootstrap/lecture/permutecorrelation.py
View File

@ -44,19 +44,19 @@ ax.annotate('Measured\ncorrelation\nis significant!',
connectionstyle="angle3,angleA=10,angleB=80") ) connectionstyle="angle3,angleA=10,angleB=80") )
ax.annotate('95% percentile', ax.annotate('95% percentile',
xy=(0.14, 0.9), xycoords='data', xy=(0.14, 0.9), xycoords='data',
xytext=(0.2, 4.0), textcoords='data', ha='left', xytext=(0.18, 4.0), textcoords='data', ha='left',
arrowprops=dict(arrowstyle="->", relpos=(0.1,0.0), arrowprops=dict(arrowstyle="->", relpos=(0.1,0.0),
connectionstyle="angle3,angleA=30,angleB=70") ) connectionstyle="angle3,angleA=30,angleB=80") )
ax.annotate('Distribution of\nuncorrelated\nsamples', ax.annotate('Distribution of\nuncorrelated\nsamples',
xy=(-0.08, 3.6), xycoords='data', xy=(-0.08, 3.6), xycoords='data',
xytext=(-0.22, 5.0), textcoords='data', ha='left', xytext=(-0.22, 5.0), textcoords='data', ha='left',
arrowprops=dict(arrowstyle="->", relpos=(0.5,0.0), arrowprops=dict(arrowstyle="->", relpos=(0.5,0.0),
connectionstyle="angle3,angleA=150,angleB=100") ) connectionstyle="angle3,angleA=150,angleB=110") )
ax.bar(b[:-1], h, width=b[1]-b[0], **fsC) ax.bar(b[:-1], h, width=b[1]-b[0], **fsC)
ax.bar(b[:-1][b[:-1]>=rq], h[b[:-1]>=rq], width=b[1]-b[0], **fsB) ax.bar(b[:-1][b[:-1]>=rq], h[b[:-1]>=rq], width=b[1]-b[0], **fsB)
ax.plot( [rd, rd], [0, 1], **lsA) ax.plot( [rd, rd], [0, 1], **lsA)
ax.set_xlim(-0.25, 0.35) ax.set_xlim(-0.25, 0.35)
ax.set_xlabel('Correlation coefficient') ax.set_xlabel('Correlation coefficient')
ax.set_ylabel('Probability density of H0') ax.set_ylabel('Prob. density of H0')
plt.savefig('permutecorrelation.pdf') plt.savefig('permutecorrelation.pdf')

8
likelihood/lecture/mlemean.py
View File

@ -26,7 +26,7 @@ ax.set_ylim(-0.02, 0.85)
ax.set_xticks(np.arange(0, 5)) ax.set_xticks(np.arange(0, 5))
ax.set_yticks(np.arange(0, 0.9, 0.2)) ax.set_yticks(np.arange(0, 0.9, 0.2))
ax.set_xlabel('x') ax.set_xlabel('x')
ax.set_ylabel('Probability density') ax.set_ylabel('Prob. density')
s = 1 s = 1
for mu in mus : for mu in mus :
r = 5.0*rng.rand()+2.0 r = 5.0*rng.rand()+2.0
@ -35,11 +35,11 @@ for mu in mus :
ax.annotate('', xy=(mu, 0.02), xycoords='data', ax.annotate('', xy=(mu, 0.02), xycoords='data',
xytext=(mu, 0.75), textcoords='data', xytext=(mu, 0.75), textcoords='data',
arrowprops=dict(arrowstyle="->", relpos=(0.5,0.5), arrowprops=dict(arrowstyle="->", relpos=(0.5,0.5),
connectionstyle=cs), zorder=1) connectionstyle=cs), zorder=10)
if mu > rmu : if mu > rmu :
ax.text(mu-0.1, 0.04, '?', zorder=1, ha='right') ax.text(mu-0.1, 0.04, '?', zorder=10, ha='right')
else : else :
ax.text(mu+0.1, 0.04, '?', zorder=1) ax.text(mu+0.1, 0.04, '?', zorder=10)
for k, ls in enumerate([lsCm, lsBm, lsDm]) : for k, ls in enumerate([lsCm, lsBm, lsDm]) :
ax.plot(x, g[:,k], zorder=5, **ls) ax.plot(x, g[:,k], zorder=5, **ls)
ax.plot(xd, 0.05*rng.rand(len(xd))+0.2, zorder=10, **psAm) ax.plot(xd, 0.05*rng.rand(len(xd))+0.2, zorder=10, **psAm)

4
likelihood/lecture/mlepdf.py
View File

@ -29,7 +29,7 @@ ax1.set_ylim(0.0, 0.42)
ax1.set_xticks(np.arange(0, 11, 2)) ax1.set_xticks(np.arange(0, 11, 2))
ax1.set_yticks(np.arange(0, 0.42, 0.1)) ax1.set_yticks(np.arange(0, 0.42, 0.1))
ax1.set_xlabel('x') ax1.set_xlabel('x')
ax1.set_ylabel('Probability density') ax1.set_ylabel('Prob. density')
ax1.plot(xx, yy, label='pdf', **lsB) ax1.plot(xx, yy, label='pdf', **lsB)
ax1.plot(xx, yf, label='mle', **lsCm) ax1.plot(xx, yf, label='mle', **lsCm)
kernel = st.gaussian_kde(xd) kernel = st.gaussian_kde(xd)
@ -54,7 +54,7 @@ ax2.set_xticks(np.arange(0, 11, 2))
ax2.set_xlabel('x') ax2.set_xlabel('x')
ax2.set_ylim(0.0, 0.42) ax2.set_ylim(0.0, 0.42)
ax2.set_yticks(np.arange(0, 0.42, 0.1)) ax2.set_yticks(np.arange(0, 0.42, 0.1))
ax2.set_ylabel('Probability density') ax2.set_ylabel('Prob. density')
ax2.plot(xx, yy, label='pdf', **lsB) ax2.plot(xx, yy, label='pdf', **lsB)
ax2.plot(xx, yc, label='fit', **lsCm) ax2.plot(xx, yc, label='fit', **lsCm)
ax2.bar(b[:-1], h, np.diff(b), **fsA) ax2.bar(b[:-1], h, np.diff(b), **fsA)

4
likelihood/lecture/mlepropline.py
View File

@ -6,7 +6,7 @@ from plotstyle import *
fig = plt.figure() fig = plt.figure()
spec = gridspec.GridSpec(nrows=1, ncols=2, wspace=0.3, spec = gridspec.GridSpec(nrows=1, ncols=2, wspace=0.3,
**adjust_fs(fig, left=5.5)) **adjust_fs(fig, left=5.5, top=1))
spec1 = gridspec.GridSpecFromSubplotSpec(1, 2, spec[0, 0], width_ratios=[3, 1], wspace=0.0) spec1 = gridspec.GridSpecFromSubplotSpec(1, 2, spec[0, 0], width_ratios=[3, 1], wspace=0.0)
spec2 = gridspec.GridSpecFromSubplotSpec(1, 2, spec[0, 1], width_ratios=[3, 1], wspace=0.0) spec2 = gridspec.GridSpecFromSubplotSpec(1, 2, spec[0, 1], width_ratios=[3, 1], wspace=0.0)
@ -34,7 +34,7 @@ ax.set_ylabel('y')
ax.plot(x, y, label='data', zorder=10, **psAm) ax.plot(x, y, label='data', zorder=10, **psAm)
ax.plot(xx, yy, label='original', zorder=5, **lsB) ax.plot(xx, yy, label='original', zorder=5, **lsB)
ax.plot(xx, yf, label='fit', zorder=7, **lsCm) ax.plot(xx, yf, label='fit', zorder=7, **lsCm)
ax.legend(loc='upper left', bbox_to_anchor=(0.0, 1.15)) ax.legend(loc='upper left', bbox_to_anchor=(-0.05, 1.2))
ax = fig.add_subplot(spec1[0, 1]) ax = fig.add_subplot(spec1[0, 1])
ax.show_spines('l') ax.show_spines('l')

35
plotstyle.py
View File

@ -2,7 +2,11 @@ import matplotlib as mpl
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D from mpl_toolkits.mplot3d import Axes3D
xkcd_style = False # Set to true if you want xkcd-type sketchy plots:
xkcd_style = True
# matplotlib major version:
mpl_major = int(mpl.__version__.split('.')[0])
# default size of figure: # default size of figure:
figure_width = 15.0 # cm, should be set according to \textwidth in the latex document figure_width = 15.0 # cm, should be set according to \textwidth in the latex document
@ -26,7 +30,7 @@ colors['white'] = '#FFFFFF'
#colors_bendalab_vivid['green'] = '#30D700' #colors_bendalab_vivid['green'] = '#30D700'
#colors_bendalab_vivid['blue'] = '#0020C0' #colors_bendalab_vivid['blue'] = '#0020C0'
# line styles for plot(): # general settings for plot styles:
lwthick = 3.0 lwthick = 3.0
lwthin = 1.8 lwthin = 1.8
mainline = {'linestyle': '-', 'linewidth': lwthick} mainline = {'linestyle': '-', 'linewidth': lwthick}
@ -35,9 +39,12 @@ largemarker = {'marker': 'o', 'markersize': 9, 'markeredgecolor': colors['white'
smallmarker = {'marker': 'o', 'markersize': 6, 'markeredgecolor': colors['white'], 'markeredgewidth': 1} smallmarker = {'marker': 'o', 'markersize': 6, 'markeredgecolor': colors['white'], 'markeredgewidth': 1}
largelinepoints = {'linestyle': '-', 'linewidth': lwthick, 'marker': 'o', 'markersize': 10, 'markeredgecolor': colors['white'], 'markeredgewidth': 1} largelinepoints = {'linestyle': '-', 'linewidth': lwthick, 'marker': 'o', 'markersize': 10, 'markeredgecolor': colors['white'], 'markeredgewidth': 1}
smalllinepoints = {'linestyle': '-', 'linewidth': 1.4, 'marker': 'o', 'markersize': 7, 'markeredgecolor': colors['white'], 'markeredgewidth': 1} smalllinepoints = {'linestyle': '-', 'linewidth': 1.4, 'marker': 'o', 'markersize': 7, 'markeredgecolor': colors['white'], 'markeredgewidth': 1}
filllw = 1 filllw = 1.0
fillec = colors['white'] fillec = colors['white']
fillalpha = 0.4 fillalpha = 0.4
filledge = {'linewidth': filllw, 'joinstyle': 'round'}
if int(mpl.__version__.split('.')[0]) < 2:
del filledge['joinstyle']
# helper lines: # helper lines:
lsSpine = {'c': colors['black'], 'linestyle': '-', 'linewidth': 1, 'clip_on': False} lsSpine = {'c': colors['black'], 'linestyle': '-', 'linewidth': 1, 'clip_on': False}
@ -71,7 +78,7 @@ psA = dict({'color': colors['blue'], 'linestyle': 'none'}, **largemarker)
psAm = dict({'color': colors['blue'], 'linestyle': 'none'}, **smallmarker) psAm = dict({'color': colors['blue'], 'linestyle': 'none'}, **smallmarker)
lpsA = dict({'color': colors['blue']}, **largelinepoints) lpsA = dict({'color': colors['blue']}, **largelinepoints)
lpsAm = dict({'color': colors['blue']}, **smalllinepoints) lpsAm = dict({'color': colors['blue']}, **smalllinepoints)
fsA = {'facecolor': colors['blue'], 'edgecolor': fillec, 'linewidth': filllw} fsA = dict({'facecolor': colors['blue'], 'edgecolor': fillec}, **filledge)
fsAs = {'facecolor': colors['blue'], 'edgecolor': 'none'} fsAs = {'facecolor': colors['blue'], 'edgecolor': 'none'}
fsAa = {'facecolor': colors['blue'], 'edgecolor': 'none', 'alpha': fillalpha} fsAa = {'facecolor': colors['blue'], 'edgecolor': 'none', 'alpha': fillalpha}
@ -81,7 +88,7 @@ psB = dict({'color': colors['red'], 'linestyle': 'none'}, **largemarker)
psBm = dict({'color': colors['red'], 'linestyle': 'none'}, **smallmarker) psBm = dict({'color': colors['red'], 'linestyle': 'none'}, **smallmarker)
lpsB = dict({'color': colors['red']}, **largelinepoints) lpsB = dict({'color': colors['red']}, **largelinepoints)
lpsBm = dict({'color': colors['red']}, **smalllinepoints) lpsBm = dict({'color': colors['red']}, **smalllinepoints)
fsB = {'facecolor': colors['red'], 'edgecolor': fillec, 'linewidth': filllw} fsB = dict({'facecolor': colors['red'], 'edgecolor': fillec}, **filledge)
fsBs = {'facecolor': colors['red'], 'edgecolor': 'none'} fsBs = {'facecolor': colors['red'], 'edgecolor': 'none'}
fsBa = {'facecolor': colors['red'], 'edgecolor': 'none', 'alpha': fillalpha} fsBa = {'facecolor': colors['red'], 'edgecolor': 'none', 'alpha': fillalpha}
@ -89,7 +96,7 @@ lsC = dict({'color': colors['lightorange']}, **mainline)
lsCm = dict({'color': colors['lightorange']}, **minorline) lsCm = dict({'color': colors['lightorange']}, **minorline)
psC = dict({'color': colors['lightorange'], 'linestyle': 'none'}, **largemarker) psC = dict({'color': colors['lightorange'], 'linestyle': 'none'}, **largemarker)
psCm = dict({'color': colors['lightorange'], 'linestyle': 'none'}, **smallmarker) psCm = dict({'color': colors['lightorange'], 'linestyle': 'none'}, **smallmarker)
fsC = {'facecolor': colors['lightorange'], 'edgecolor': fillec, 'linewidth': filllw} fsC = dict({'facecolor': colors['lightorange'], 'edgecolor': fillec}, **filledge)
fsCs = {'facecolor': colors['lightorange'], 'edgecolor': 'none'} fsCs = {'facecolor': colors['lightorange'], 'edgecolor': 'none'}
fsCa = {'facecolor': colors['lightorange'], 'edgecolor': 'none', 'alpha': fillalpha} fsCa = {'facecolor': colors['lightorange'], 'edgecolor': 'none', 'alpha': fillalpha}
@ -97,17 +104,17 @@ lsD = dict({'color': colors['orange']}, **mainline)
lsDm = dict({'color': colors['orange']}, **minorline) lsDm = dict({'color': colors['orange']}, **minorline)
psD = dict({'color': colors['orange'], 'linestyle': 'none'}, **largemarker) psD = dict({'color': colors['orange'], 'linestyle': 'none'}, **largemarker)
psDm = dict({'color': colors['orange'], 'linestyle': 'none'}, **smallmarker) psDm = dict({'color': colors['orange'], 'linestyle': 'none'}, **smallmarker)
fsD = {'facecolor': colors['orange'], 'edgecolor': fillec, 'linewidth': filllw} fsD = dict({'facecolor': colors['orange'], 'edgecolor': fillec}, **filledge)
fsDs = {'facecolor': colors['orange'], 'edgecolor': 'none'} fsDs = {'facecolor': colors['orange'], 'edgecolor': 'none'}
lsE = dict({'color': colors['yellow']}, **mainline) lsE = dict({'color': colors['yellow']}, **mainline)
lsEm = dict({'color': colors['yellow']}, **minorline) lsEm = dict({'color': colors['yellow']}, **minorline)
psE = dict({'color': colors['yellow'], 'linestyle': 'none'}, **largemarker) psE = dict({'color': colors['yellow'], 'linestyle': 'none'}, **largemarker)
psEm = dict({'color': colors['yellow'], 'linestyle': 'none'}, **smallmarker) psEm = dict({'color': colors['yellow'], 'linestyle': 'none'}, **smallmarker)
fsE = {'facecolor': colors['yellow'], 'edgecolor': fillec, 'linewidth': filllw} fsE = dict({'facecolor': colors['yellow'], 'edgecolor': fillec}, **filledge)
fsEs = {'facecolor': colors['yellow'], 'edgecolor': 'none'} fsEs = {'facecolor': colors['yellow'], 'edgecolor': 'none'}
fsF = {'facecolor': colors['green'], 'edgecolor': fillec, 'linewidth': filllw} fsF = dict({'facecolor': colors['green'], 'edgecolor': fillec}, **filledge)
fsFs = {'facecolor': colors['green'], 'edgecolor': 'none'} fsFs = {'facecolor': colors['green'], 'edgecolor': 'none'}
# factor for scaling widths of bars in a bar plot: # factor for scaling widths of bars in a bar plot:
@ -270,7 +277,7 @@ def axis_label(label, unit=None):
if not unit: if not unit:
return label return label
elif xkcd_style: elif xkcd_style:
return '%s / %s' % (label, unit) return '%s/%s' % (label, unit)
else: else:
return '%s [%s]' % (label, unit) return '%s [%s]' % (label, unit)
@ -326,7 +333,7 @@ def set_zlabel(ax, label, unit=None, **kwargs):
ax.set_zlabel_orig(axis_label(label, unit), **kwargs) ax.set_zlabel_orig(axis_label(label, unit), **kwargs)
def common_format(): def common_style():
""" Set some rc parameter. """ Set some rc parameter.
""" """
mpl.rcParams['figure.figsize'] = cm_size(figure_width, figure_height) mpl.rcParams['figure.figsize'] = cm_size(figure_width, figure_height)
@ -337,6 +344,8 @@ def common_format():
mpl.rcParams['figure.subplot.wspace'] = 0.4 mpl.rcParams['figure.subplot.wspace'] = 0.4
mpl.rcParams['figure.subplot.hspace'] = 0.6 mpl.rcParams['figure.subplot.hspace'] = 0.6
mpl.rcParams['figure.facecolor'] = 'white' mpl.rcParams['figure.facecolor'] = 'white'
mpl.rcParams['figure.edgecolor'] = 'none'
mpl.rcParams['figure.frameon'] = False
mpl.rcParams['xtick.direction'] = 'out' mpl.rcParams['xtick.direction'] = 'out'
mpl.rcParams['ytick.direction'] = 'out' mpl.rcParams['ytick.direction'] = 'out'
mpl.rcParams['xtick.major.width'] = 1.25 mpl.rcParams['xtick.major.width'] = 1.25
@ -380,7 +389,7 @@ def sketch_style():
global bar_fac global bar_fac
bar_fac = 0.9 bar_fac = 0.9
plt.xkcd() plt.xkcd()
common_format() common_style()
mpl.rcParams['legend.fontsize'] = 'medium' mpl.rcParams['legend.fontsize'] = 'medium'
mpl.rcParams['xtick.labelsize'] = 'medium' mpl.rcParams['xtick.labelsize'] = 'medium'
mpl.rcParams['ytick.labelsize'] = 'medium' mpl.rcParams['ytick.labelsize'] = 'medium'
@ -394,7 +403,7 @@ def plain_style():
global bar_fac global bar_fac
bar_fac = 1.0 bar_fac = 1.0
plt.rcdefaults() plt.rcdefaults()
common_format() common_style()
mpl.rcParams['font.family'] = 'sans-serif' mpl.rcParams['font.family'] = 'sans-serif'
mpl.rcParams['legend.fontsize'] = 'x-small' mpl.rcParams['legend.fontsize'] = 'x-small'
mpl.rcParams['xtick.labelsize'] = 'small' mpl.rcParams['xtick.labelsize'] = 'small'

8
pointprocesses/lecture/firingrates.py
View File

@ -149,7 +149,7 @@ def plot_comparison(spike_times, bin_width, sigma, max_t=30., dt=1e-4):
ax1.show_spines('b') ax1.show_spines('b')
ax1.vlines(times[times < (100000*dt)], ymin=0, ymax=1, color=colors['blue'], lw=1.5) ax1.vlines(times[times < (100000*dt)], ymin=0, ymax=1, color=colors['blue'], lw=1.5)
#ax1.set_ylabel('Spikes') #ax1.set_ylabel('Spikes')
ax1.text(-0.105, 0.5, 'Spikes', transform=ax1.transAxes, ax1.text(-0.13, 0.5, 'Spikes', transform=ax1.transAxes,
rotation='vertical', va='center') rotation='vertical', va='center')
ax1.set_xlim(2.5, 3.5) ax1.set_xlim(2.5, 3.5)
ax1.set_ylim(-0.2, 1) ax1.set_ylim(-0.2, 1)
@ -159,7 +159,7 @@ def plot_comparison(spike_times, bin_width, sigma, max_t=30., dt=1e-4):
ax2.plot(time, inst_rate, color=colors['orange'], lw=2) ax2.plot(time, inst_rate, color=colors['orange'], lw=2)
ax2.text(1.0, 1.0, 'instantaneous rate', transform=ax2.transAxes, ha='right') ax2.text(1.0, 1.0, 'instantaneous rate', transform=ax2.transAxes, ha='right')
#ax2.set_ylabel('Rate', 'Hz') #ax2.set_ylabel('Rate', 'Hz')
ax2.text(-0.105, 0.5, axis_label('Rate', 'Hz'), transform=ax2.transAxes, ax2.text(-0.13, 0.5, axis_label('Rate', 'Hz'), transform=ax2.transAxes,
rotation='vertical', va='center') rotation='vertical', va='center')
ax2.set_xlim(2.5, 3.5) ax2.set_xlim(2.5, 3.5)
ax2.set_ylim(0, 300) ax2.set_ylim(0, 300)
@ -170,7 +170,7 @@ def plot_comparison(spike_times, bin_width, sigma, max_t=30., dt=1e-4):
ax3.plot(time, binn_rate, color=colors['orange'], lw=2) ax3.plot(time, binn_rate, color=colors['orange'], lw=2)
ax3.text(1.0, 1.0, 'binned rate', transform=ax3.transAxes, ha='right') ax3.text(1.0, 1.0, 'binned rate', transform=ax3.transAxes, ha='right')
#ax3.set_ylabel('Rate', 'Hz') #ax3.set_ylabel('Rate', 'Hz')
ax3.text(-0.105, 0.5, axis_label('Rate', 'Hz'), transform=ax3.transAxes, ax3.text(-0.13, 0.5, axis_label('Rate', 'Hz'), transform=ax3.transAxes,
rotation='vertical', va='center') rotation='vertical', va='center')
ax3.set_xlim(2.5, 3.5) ax3.set_xlim(2.5, 3.5)
ax3.set_ylim(0, 300) ax3.set_ylim(0, 300)
@ -182,7 +182,7 @@ def plot_comparison(spike_times, bin_width, sigma, max_t=30., dt=1e-4):
ax4.text(1.0, 1.0, 'convolved rate', transform=ax4.transAxes, ha='right') ax4.text(1.0, 1.0, 'convolved rate', transform=ax4.transAxes, ha='right')
ax4.set_xlabel('Time', 's') ax4.set_xlabel('Time', 's')
#ax4.set_ylabel('Rate', 'Hz') #ax4.set_ylabel('Rate', 'Hz')
ax4.text(-0.105, 0.5, axis_label('Rate', 'Hz'), transform=ax4.transAxes, ax4.text(-0.13, 0.5, axis_label('Rate', 'Hz'), transform=ax4.transAxes,
rotation='vertical', va='center') rotation='vertical', va='center')
ax4.set_xlim(2.5, 3.5) ax4.set_xlim(2.5, 3.5)
ax4.set_xticks([2.5, 2.75, 3.0, 3.25, 3.5]) ax4.set_xticks([2.5, 2.75, 3.0, 3.25, 3.5])

6
pointprocesses/lecture/isimethod.py
View File

@ -31,7 +31,7 @@ def setup_axis(spikes_ax, rate_ax):
spikes_ax.show_spines('') spikes_ax.show_spines('')
spikes_ax.set_yticks([]) spikes_ax.set_yticks([])
spikes_ax.set_ylim(-0.2, 1.0) spikes_ax.set_ylim(-0.2, 1.0)
spikes_ax.text(-0.1, 0.5, 'Spikes', transform=spikes_ax.transAxes, rotation='vertical', va='center') spikes_ax.text(-0.11, 0.5, 'Spikes', transform=spikes_ax.transAxes, rotation='vertical', va='center')
spikes_ax.set_xlim(-1, 500) spikes_ax.set_xlim(-1, 500)
spikes_ax.set_xticklabels([]) spikes_ax.set_xticklabels([])
#spikes_ax.set_xticklabels(np.arange(0., 600, 100)) #spikes_ax.set_xticklabels(np.arange(0., 600, 100))
@ -39,7 +39,7 @@ def setup_axis(spikes_ax, rate_ax):
spikes_ax.show_spines('lb') spikes_ax.show_spines('lb')
rate_ax.set_xlabel('Time', 'ms') rate_ax.set_xlabel('Time', 'ms')
#rate_ax.set_ylabel('Firing rate', 'Hz') #rate_ax.set_ylabel('Firing rate', 'Hz')
rate_ax.text(-0.1, 0.5, axis_label('Rate', 'Hz'), transform=rate_ax.transAxes, rate_ax.text(-0.11, 0.5, axis_label('Rate', 'Hz'), transform=rate_ax.transAxes,
rotation='vertical', va='center') rotation='vertical', va='center')
rate_ax.set_xlim(0, 500) rate_ax.set_xlim(0, 500)
#rate_ax.set_xticklabels(np.arange(0., 600, 100)) #rate_ax.set_xticklabels(np.arange(0., 600, 100))
@ -126,7 +126,7 @@ def plot_isi_method():
t_start = 1000*spike_times[i-1] t_start = 1000*spike_times[i-1]
t = 1000*spike_times[i] t = 1000*spike_times[i]
spikes_ax.plot([t_start, t_start], [0., 1.], color=colors['blue'], lw=2) spikes_ax.plot([t_start, t_start], [0., 1.], color=colors['blue'], lw=2)
spikes_ax.annotate(s='', xy=(t_start, 0.5), xytext=(t,0.5), arrowprops=dict(arrowstyle='<->'), color=colors['red']) spikes_ax.annotate('', xy=(t_start, 0.5), xytext=(t,0.5), arrowprops=dict(arrowstyle='<->'), color=colors['red'])
spikes_ax.text(0.5*(t_start+t), 1.05, spikes_ax.text(0.5*(t_start+t), 1.05,
"{0:.0f}".format((t - t_start)), "{0:.0f}".format((t - t_start)),
color=colors['red'], ha='center') color=colors['red'], ha='center')

105
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@ -650,60 +598,47 @@ LCb setrgbcolor
0 272 V 0 272 V
5685 1907 M 5685 1907 M
0 272 V 0 272 V
1.000 UP
stroke stroke
LTw
% End plot #1
2.000 UL 2.000 UL
LTb LTb
LCb setrgbcolor LCb setrgbcolor
[] 0 setdash
1.000 UP
2.000 UL
LTb
0.00 0.00 0.00 C 2.000 UL 0.00 0.00 0.00 C 2.000 UL
LTb LTb
LCb setrgbcolor LCb setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 528 268 M 0.00 0.00 0.00 C 528 268 M
-63 0 V -63 0 V
stroke stroke
LTb LTb
LCb setrgbcolor LCb setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 528 460 M 0.00 0.00 0.00 C 528 460 M
-63 0 V -63 0 V
stroke stroke
LTb LTb
LCb setrgbcolor LCb setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 528 652 M 0.00 0.00 0.00 C 528 652 M
-63 0 V -63 0 V
stroke stroke
LTb LTb
LCb setrgbcolor LCb setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 528 844 M 0.00 0.00 0.00 C 528 844 M
-63 0 V -63 0 V
stroke stroke
LTb LTb
LCb setrgbcolor LCb setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 528 1036 M 0.00 0.00 0.00 C 528 1036 M
-63 0 V -63 0 V
stroke stroke
LTb LTb
LCb setrgbcolor LCb setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 528 1228 M 0.00 0.00 0.00 C 528 1228 M
-63 0 V -63 0 V
stroke stroke
LTb LTb
LCb setrgbcolor LCb setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 2.000 UL 0.00 0.00 0.00 C 2.000 UL
LTb LTb
LCb setrgbcolor LCb setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 528 1276 M 0.00 0.00 0.00 C 528 1276 M
528 220 L 528 220 L
5801 0 R 5801 0 R
@ -711,7 +646,9 @@ LCb setrgbcolor
-5801 0 R -5801 0 R
1.000 UP 1.000 UP
stroke stroke
LTb
LCb setrgbcolor LCb setrgbcolor
LTb
1.000 UL 1.000 UL
LTb LTb
gsave 6208 268 N 0 -32 V 121 32 V -121 32 V 0 -32 V 1 PolyFill gsave 6208 268 N 0 -32 V 121 32 V -121 32 V 0 -32 V 1 PolyFill
@ -725,11 +662,9 @@ gsave 6208 268 N 0 -32 V 121 32 V -121 32 V 0 -32 V 1 PolyFill
stroke stroke
2.000 UL 2.000 UL
LTb LTb
0.00 0.00 0.00 C % Begin plot #1 0.00 0.00 0.00 C 3.000 UL
3.000 UL LT0
LTb LC0 setrgbcolor
LCb setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 528 268 M 0.00 0.00 0.00 C 528 268 M
382 0 V 382 0 V
0 96 R 0 96 R
@ -750,15 +685,11 @@ LCb setrgbcolor
1035 0 V 1035 0 V
0 96 R 0 96 R
533 0 V 533 0 V
stroke
LTw
% End plot #1
% Begin plot #2
1.500 UP 1.500 UP
stroke
2.000 UL 2.000 UL
LTb LT0
LCb setrgbcolor LC0 setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 910 268 CircleF 0.00 0.00 0.00 C 910 268 CircleF
1412 364 CircleF 1412 364 CircleF
2123 460 CircleF 2123 460 CircleF
@ -768,14 +699,10 @@ LCb setrgbcolor
4033 844 CircleF 4033 844 CircleF
4650 940 CircleF 4650 940 CircleF
5685 1036 CircleF 5685 1036 CircleF
LTw
% End plot #2
% Begin plot #3
1.000 UP 1.000 UP
2.000 UL 2.000 UL
LTb LT0
LCb setrgbcolor LC0 setrgbcolor
[] 0 setdash
1.00 1.00 1.00 C 910 268 CircleF 1.00 1.00 1.00 C 910 268 CircleF
1412 364 CircleF 1412 364 CircleF
2123 460 CircleF 2123 460 CircleF
@ -785,14 +712,10 @@ LCb setrgbcolor
4033 844 CircleF 4033 844 CircleF
4650 940 CircleF 4650 940 CircleF
5685 1036 CircleF 5685 1036 CircleF
LTw
% End plot #3
% Begin plot #4
1.500 UP 1.500 UP
2.000 UL 2.000 UL
LTb LT0
LCb setrgbcolor LC0 setrgbcolor
[] 0 setdash
0.00 0.00 0.00 C 910 364 CircleF 0.00 0.00 0.00 C 910 364 CircleF
1412 460 CircleF 1412 460 CircleF
2123 556 CircleF 2123 556 CircleF
@ -802,15 +725,10 @@ LCb setrgbcolor
4033 940 CircleF 4033 940 CircleF
4650 1036 CircleF 4650 1036 CircleF
5685 1132 CircleF 5685 1132 CircleF
LTw
% End plot #4
2.000 UL
LTb
LCb setrgbcolor
[] 0 setdash
1.000 UP 1.000 UP
2.000 UL 2.000 UL
LTb LTb
LCb setrgbcolor
0.00 0.00 0.00 C stroke 0.00 0.00 0.00 C stroke
grestore grestore
end end

BIN
pointprocesses/lecture/pointprocessscetchB.pdf
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Binary file not shown.

8
regression/lecture/gradient.py
View File

@ -24,7 +24,7 @@ ax.set_xlabel('x')
ax.set_ylabel('y', rotation='horizontal') ax.set_ylabel('y', rotation='horizontal')
ax.set_xticks(np.arange(x1, x2+0.1, 1.0)) ax.set_xticks(np.arange(x1, x2+0.1, 1.0))
ax.set_yticks(np.arange(x1, x2+0.1, 1.0)) ax.set_yticks(np.arange(x1, x2+0.1, 1.0))
ax.contour(X, Y, Z, linewidths=2, zorder=0) ax.contour(X, Y, Z, linewidths=2, cmap='jet', zorder=0)
# gradients: # gradients:
xxg = [-1.1, 1.4, -1.0] xxg = [-1.1, 1.4, -1.0]
@ -35,8 +35,8 @@ for xg, yg in zip(xxg, yyg) :
ax.scatter(xg, yg, c='k', s=100, zorder=10) ax.scatter(xg, yg, c='k', s=100, zorder=10)
ax.quiver([xg, xg], [yg, yg], [g[0], 0.0], [0.0, g[1]], units='xy', angles='uv', scale_units='x', scale=0.5, zorder=10) ax.quiver([xg, xg], [yg, yg], [g[0], 0.0], [0.0, g[1]], units='xy', angles='uv', scale_units='x', scale=0.5, zorder=10)
ax.quiver([xg], [yg], [g[0]], [g[1]], units='xy', angles='uv', scale_units='x', scale=0.5, zorder=10, lw=2) ax.quiver([xg], [yg], [g[0]], [g[1]], units='xy', angles='uv', scale_units='x', scale=0.5, zorder=10, lw=2)
ax.text(-0.8, -1.5, '$\partial f/\partial x$', ha='center', zorder=20) ax.text(-0.8, -1.4, '$\partial f/\partial x$', ha='center', zorder=20)
ax.text(-1.55, -0.8, '$\partial f/\partial y$', va='center', rotation='vertical', zorder=20) ax.text(-1.45, -0.8, '$\partial f/\partial y$', va='center', rotation='vertical', zorder=20)
ax.text(-0.4, -0.8, r'$\nabla f$', ha='left', zorder=20) ax.text(-0.5, -0.8, r'$\nabla f$', ha='left', zorder=20)
plt.savefig('gradient.pdf') plt.savefig('gradient.pdf')

6
statistics/lecture/diehistograms.py
View File

@ -2,7 +2,6 @@ import numpy as np
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from plotstyle import * from plotstyle import *
sketch_style()
# roll the die: # roll the die:
rng = np.random.RandomState(57281) rng = np.random.RandomState(57281)
x1 = rng.randint(1, 7, 100) x1 = rng.randint(1, 7, 100)
@ -27,6 +26,9 @@ ax2.set_xlabel('x')
ax2.set_ylim(0, 0.23) ax2.set_ylim(0, 0.23)
ax2.set_ylabel('Probability') ax2.set_ylabel('Probability')
ax2.plot([0.2, 6.8], [1.0/6.0, 1.0/6.0], zorder=-10, **lsAm) ax2.plot([0.2, 6.8], [1.0/6.0, 1.0/6.0], zorder=-10, **lsAm)
ax2.hist([x2, x1], bins, density=True, zorder=-5, **fs) if mpl_major > 1:
ax2.hist([x2, x1], bins, density=True, zorder=-5, **fs)
else:
ax2.hist([x2, x1], bins, normed=True, zorder=-5, **fs)
fig.subplots_adjust(left=0.125) fig.subplots_adjust(left=0.125)
fig.savefig('diehistograms.pdf') fig.savefig('diehistograms.pdf')

28
statistics/lecture/displayunivariatedata.py
View File

@ -4,7 +4,6 @@ import matplotlib.gridspec as gridspec
from scipy.stats import gaussian_kde from scipy.stats import gaussian_kde
from plotstyle import * from plotstyle import *
sketch_style()
#rng = np.random.RandomState(981) #rng = np.random.RandomState(981)
#data = rng.randn(40, 1) + 4.0 #data = rng.randn(40, 1) + 4.0
rng = np.random.RandomState(1981) rng = np.random.RandomState(1981)
@ -19,9 +18,11 @@ fig = plt.figure(figsize=cm_size(figure_width, 1.1*figure_height))
spec = gridspec.GridSpec(nrows=1, ncols=2, width_ratios=[3, 1], wspace=0.1, spec = gridspec.GridSpec(nrows=1, ncols=2, width_ratios=[3, 1], wspace=0.1,
**adjust_fs(fig, left=4.0)) **adjust_fs(fig, left=4.0))
ax = fig.add_subplot(spec[0, 0]) ax = fig.add_subplot(spec[0, 0], label='1')
wh = ax.boxplot( data, positions=[boxpos], widths=[barwidth], whis=100.0, patch_artist=True) wh = ax.boxplot( data, positions=[boxpos], widths=[barwidth], whis=100.0, patch_artist=True)
mediancolor = 'k'
wh['medians'][0].set_linewidth(4) wh['medians'][0].set_linewidth(4)
wh['medians'][0].set_color(mediancolor)
wh['whiskers'][0].set_linewidth(2) wh['whiskers'][0].set_linewidth(2)
wh['whiskers'][1].set_linewidth(2) wh['whiskers'][1].set_linewidth(2)
wh['whiskers'][0].set_linestyle('-') wh['whiskers'][0].set_linestyle('-')
@ -34,6 +35,16 @@ wh['caps'][1].set_color(whiskercolor)
wh['boxes'][0].set_facecolor('#99ff00') wh['boxes'][0].set_facecolor('#99ff00')
ax.set_xlim(0.0, 4.8) ax.set_xlim(0.0, 4.8)
ax.set_ylim( 0.0, 8.0) ax.set_ylim( 0.0, 8.0)
ax.set_xticklabels([])
ax = fig.add_subplot(spec[0, 0], label='2')
ax.set_xlim(0.0, 4.8)
ax.set_xticks([scatterpos, barpos, boxpos])
ax.set_xticklabels(['(1) data', '(2) bar\n plot', '(3) box-\nwhisker'], fontsize='medium')
ax.set_ylabel('x')
ax.set_ylim( 0.0, 8.0)
# annotate box whisker:
ax.annotate('maximum', ax.annotate('maximum',
xy=(boxpos, 6.5), xycoords='data', xy=(boxpos, 6.5), xycoords='data',
xytext=(boxpos-1*barwidth, 7.6), textcoords='data', ha='left', xytext=(boxpos-1*barwidth, 7.6), textcoords='data', ha='left',
@ -49,14 +60,6 @@ ax.annotate('median',
xytext=(boxpos+0.1*barwidth, 4.2), textcoords='data', ha='left', xytext=(boxpos+0.1*barwidth, 4.2), textcoords='data', ha='left',
arrowprops=dict(arrowstyle="->", relpos=(0.8,0.0), arrowprops=dict(arrowstyle="->", relpos=(0.8,0.0),
connectionstyle="angle3,angleA=-60,angleB=20") ) connectionstyle="angle3,angleA=-60,angleB=20") )
ax.set_xticklabels([])
ax = fig.add_subplot(spec[0, 0])
ax.set_xlim(0.0, 4.8)
ax.set_xticks([scatterpos, barpos, boxpos])
ax.set_xticklabels(['(1) data', '(2) bar\n plot', '(3) box-\nwhisker'], fontsize='medium')
ax.set_ylabel('x')
ax.set_ylim( 0.0, 8.0)
# scatter data points according to their density: # scatter data points according to their density:
kernel = gaussian_kde(data) kernel = gaussian_kde(data)
@ -67,7 +70,10 @@ ax.plot(scatterpos+barwidth*x*(rng.rand(len(data))-0.5), data, **psA)
barmean = np.mean(data) barmean = np.mean(data)
barstd = np.std(data) barstd = np.std(data)
ew = 0.2 ew = 0.2
ax.bar([barpos-0.5*barwidth], [barmean], barwidth, **fsC) if mpl_major > 1:
ax.bar([barpos], [barmean], barwidth, **fsC)
else:
ax.bar([barpos-0.5*barwidth], [barmean], barwidth, **fsC)
ax.plot([barpos, barpos], [barmean-barstd, barmean+barstd], **lsMarker) ax.plot([barpos, barpos], [barmean-barstd, barmean+barstd], **lsMarker)
ax.plot([barpos-0.5*ew, barpos+0.5*ew], [barmean-barstd, barmean-barstd], **lsMarker) ax.plot([barpos-0.5*ew, barpos+0.5*ew], [barmean-barstd, barmean-barstd], **lsMarker)
ax.plot([barpos-0.5*ew, barpos+0.5*ew], [barmean+barstd, barmean+barstd], **lsMarker) ax.plot([barpos-0.5*ew, barpos+0.5*ew], [barmean+barstd, barmean+barstd], **lsMarker)

27
statistics/lecture/kerneldensity.py
View File

@ -1,6 +1,7 @@
import numpy as np import numpy as np
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec import matplotlib.gridspec as gridspec
import matplotlib.ticker as ticker
from plotstyle import * from plotstyle import *
# normal distribution: # normal distribution:
@ -37,35 +38,39 @@ spec = gridspec.GridSpec(nrows=2, ncols=2, wspace=0.35, hspace=0.3,
**adjust_fs(fig, left=5.5, top=0.2, bottom=2.7)) **adjust_fs(fig, left=5.5, top=0.2, bottom=2.7))
ax = fig.add_subplot(spec[0, 0]) ax = fig.add_subplot(spec[0, 0])
ax.set_xlabel('x')
ax.set_xlim(-3.2, 3.2) ax.set_xlim(-3.2, 3.2)
ax.set_xticks(np.arange(-3.0, 3.1, 1.0)) ax.xaxis.set_major_locator(ticker.MultipleLocator(1.0))
ax.xaxis.set_major_formatter(ticker.NullFormatter())
ax.set_ylabel('p(x)') ax.set_ylabel('p(x)')
ax.set_ylim(0.0, 0.49) ax.set_ylim(0.0, 0.49)
ax.set_yticks(np.arange(0.0, 0.41, 0.1)) ax.yaxis.set_major_locator(ticker.MultipleLocator(0.2))
#ax.plot(x, g, '-b', lw=2, zorder=-1) if mpl_major > 1:
ax.hist(r, np.arange(-4.1, 4, 0.4), density=True, zorder=-5, **fsC) ax.hist(r, np.arange(-4.1, 4, 0.4), density=True, zorder=-5, **fsC)
else:
ax.hist(r, np.arange(-4.1, 4, 0.4), normed=True, zorder=-5, **fsC)
ax = fig.add_subplot(spec[1, 0]) ax = fig.add_subplot(spec[1, 0])
ax.set_xlabel('x') ax.set_xlabel('x')
ax.set_xlim(-3.2, 3.2) ax.set_xlim(-3.2, 3.2)
ax.set_xticks(np.arange(-3.0, 3.1, 1.0)) ax.xaxis.set_major_locator(ticker.MultipleLocator(1.0))
ax.set_ylabel('p(x)') ax.set_ylabel('p(x)')
ax.set_ylim(0.0, 0.49) ax.set_ylim(0.0, 0.49)
ax.set_yticks(np.arange(0.0, 0.41, 0.1)) ax.yaxis.set_major_locator(ticker.MultipleLocator(0.2))
#ax.plot(x, g, '-b', lw=2, zorder=-1) if mpl_major > 1:
ax.hist(r, np.arange(-4.3, 4, 0.4), density=True, zorder=-5, **fsC) ax.hist(r, np.arange(-4.3, 4, 0.4), density=True, zorder=-5, **fsC)
else:
ax.hist(r, np.arange(-4.3, 4, 0.4), normed=True, zorder=-5, **fsC)
ax = fig.add_subplot(spec[:, 1]) ax = fig.add_subplot(spec[:, 1])
ax.set_xlabel('x') ax.set_xlabel('x')
ax.set_xlim(-3.2, 3.2) ax.set_xlim(-3.2, 3.2)
ax.set_xticks(np.arange(-3.0, 3.1, 1.0)) ax.xaxis.set_major_locator(ticker.MultipleLocator(1.0))
ax.set_ylabel('Prob. density p(x)') ax.set_ylabel('Prob. density p(x)')
ax.set_ylim(0.0, 0.49) ax.set_ylim(0.0, 0.49)
ax.set_yticks(np.arange(0.0, 0.41, 0.1)) ax.set_yticks(np.arange(0.0, 0.41, 0.1))
kd, xx = kerneldensity(r, -3.2, 3.2, 0.2) kd, xx = kerneldensity(r, -3.2, 3.2, 0.2)
ax.fill_between(xx, 0.0, kd, zorder=-5, **fsDs) ax.fill_between(xx, 0.0, kd, zorder=-5, **fsDs)
ax.plot(xx, kd, '-', zorder=-1, **lsB) ax.plot(xx, kd, '-', zorder=-1, **lsB)
fig.subplots_adjust(left=0.15)
fig.savefig('kerneldensity.pdf') fig.savefig('kerneldensity.pdf')

10
statistics/lecture/pdfhistogram.py
View File

@ -8,7 +8,7 @@ x = np.arange(-4.0, 4.0, 0.01)
g = np.exp(-0.5*x*x)/np.sqrt(2.0*np.pi) g = np.exp(-0.5*x*x)/np.sqrt(2.0*np.pi)
r = rng.randn(100) r = rng.randn(100)
fig, (ax1, ax2) = plt.subplots(1, 2) fig, (ax1, ax2) = plt.subplots(1, 2, figsize=cm_size(figure_width, 1.1*figure_height))
ax1.set_xlabel('x') ax1.set_xlabel('x')
ax1.set_xlim(-3.2, 3.2) ax1.set_xlim(-3.2, 3.2)
ax1.set_xticks(np.arange(-3.0, 3.1, 1.0)) ax1.set_xticks(np.arange(-3.0, 3.1, 1.0))
@ -24,8 +24,12 @@ ax2.set_ylabel('Probab. density p(x)')
ax2.set_ylim(0.0, 0.44) ax2.set_ylim(0.0, 0.44)
ax2.set_yticks(np.arange(0.0, 0.41, 0.1)) ax2.set_yticks(np.arange(0.0, 0.41, 0.1))
ax2.plot(x, g, zorder=-1, **lsA) ax2.plot(x, g, zorder=-1, **lsA)
ax2.hist(r, 5, density=True, zorder=-10, **fsB) if mpl_major > 1:
ax2.hist(r, 20, density=True, zorder=-5, **fsC) ax2.hist(r, 5, density=True, zorder=-10, **fsB)
ax2.hist(r, 20, density=True, zorder=-5, **fsC)
else:
ax2.hist(r, 5, normed=True, zorder=-10, **fsB)
ax2.hist(r, 20, normed=True, zorder=-5, **fsC)
fig.savefig('pdfhistogram.pdf') fig.savefig('pdfhistogram.pdf')

2
statistics/lecture/pdfprobabilities.py
View File

@ -10,7 +10,7 @@ x2=1.0
fig, ax = plt.subplots(figsize=cm_size(figure_width, 1.2*figure_height)) fig, ax = plt.subplots(figsize=cm_size(figure_width, 1.2*figure_height))
ax.set_xlabel('x') ax.set_xlabel('x')
ax.set_ylabel('Probability density p(x)') ax.set_ylabel('Prob. density p(x)')
ax.set_ylim(0.0, 0.46) ax.set_ylim(0.0, 0.46)
ax.set_yticks(np.arange(0.0, 0.45, 0.1)) ax.set_yticks(np.arange(0.0, 0.45, 0.1))
ax.annotate('Gaussian', ax.annotate('Gaussian',