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[all data analysis] plots work for old and new matplotlib

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This commit is contained in:
Jan Benda 2020-10-27 23:59:14 +01:00
parent d1c6174ae2
commit 2a4c7ff038
13 changed files with 145 additions and 270 deletions
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2
bootstrap/lecture/bootstrapsem.py
View File

@ -38,7 +38,7 @@ ax.annotate('sampling\ndistribution',
connectionstyle="angle3,angleA=20,angleB=120") )
ax.annotate('bootstrap\ndistribution',
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),
connectionstyle="angle3,angleA=20,angleB=60") )
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") )
ax.annotate('95% percentile',
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),
connectionstyle="angle3,angleA=30,angleB=70") )
connectionstyle="angle3,angleA=30,angleB=80") )
ax.annotate('Distribution of\nuncorrelated\nsamples',
xy=(-0.08, 3.6), xycoords='data',
xytext=(-0.22, 5.0), textcoords='data', ha='left',
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][b[:-1]>=rq], h[b[:-1]>=rq], width=b[1]-b[0], **fsB)
ax.plot( [rd, rd], [0, 1], **lsA)
ax.set_xlim(-0.25, 0.35)
ax.set_xlabel('Correlation coefficient')
ax.set_ylabel('Probability density of H0')
ax.set_ylabel('Prob. density of H0')
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_yticks(np.arange(0, 0.9, 0.2))
ax.set_xlabel('x')
ax.set_ylabel('Probability density')
ax.set_ylabel('Prob. density')
s = 1
for mu in mus :
r = 5.0*rng.rand()+2.0
@ -35,11 +35,11 @@ for mu in mus :
ax.annotate('', xy=(mu, 0.02), xycoords='data',
xytext=(mu, 0.75), textcoords='data',
arrowprops=dict(arrowstyle="->", relpos=(0.5,0.5),
connectionstyle=cs), zorder=1)
connectionstyle=cs), zorder=10)
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 :
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]) :
ax.plot(x, g[:,k], zorder=5, **ls)
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_yticks(np.arange(0, 0.42, 0.1))
ax1.set_xlabel('x')
ax1.set_ylabel('Probability density')
ax1.set_ylabel('Prob. density')
ax1.plot(xx, yy, label='pdf', **lsB)
ax1.plot(xx, yf, label='mle', **lsCm)
kernel = st.gaussian_kde(xd)
@ -54,7 +54,7 @@ ax2.set_xticks(np.arange(0, 11, 2))
ax2.set_xlabel('x')
ax2.set_ylim(0.0, 0.42)
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, yc, label='fit', **lsCm)
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()
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)
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(xx, yy, label='original', zorder=5, **lsB)
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.show_spines('l')

2
plotstyle.py
View File

@ -277,7 +277,7 @@ def axis_label(label, unit=None):
if not unit:
return label
elif xkcd_style:
return '%s / %s' % (label, unit)
return '%s/%s' % (label, unit)
else:
return '%s [%s]' % (label, unit)

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.vlines(times[times < (100000*dt)], ymin=0, ymax=1, color=colors['blue'], lw=1.5)
#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')
ax1.set_xlim(2.5, 3.5)
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.text(1.0, 1.0, 'instantaneous rate', transform=ax2.transAxes, ha='right')
#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')
ax2.set_xlim(2.5, 3.5)
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.text(1.0, 1.0, 'binned rate', transform=ax3.transAxes, ha='right')
#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')
ax3.set_xlim(2.5, 3.5)
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.set_xlabel('Time', 's')
#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')
ax4.set_xlim(2.5, 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.set_yticks([])
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_xticklabels([])
#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')
rate_ax.set_xlabel('Time', 'ms')
#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')
rate_ax.set_xlim(0, 500)
#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 = 1000*spike_times[i]
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,
"{0:.0f}".format((t - t_start)),
color=colors['red'], ha='center')

105
pointprocesses/lecture/pointprocessscetchA.eps
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@ -1,7 +1,7 @@
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pointprocesses/lecture/pointprocessscetchA.pdf
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pointprocesses/lecture/pointprocessscetchB.eps
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/Title (pointprocessscetchB.tex)
/Subject (gnuplot plot)
/Creator (gnuplot 5.0 patchlevel 5)
/Author (benda)
/Creator (gnuplot 4.6 patchlevel 4)
/Author (jan)
% /Producer (gnuplot)
% /Keywords ()
/CreationDate (Tue Jan 7 10:05:38 2020)
/CreationDate (Tue Oct 27 23:58:04 2020)
/DOCINFO pdfmark
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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_xticks(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:
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.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.text(-0.8, -1.5, '$\partial f/\partial x$', ha='center', zorder=20)
ax.text(-1.55, -0.8, '$\partial f/\partial y$', va='center', rotation='vertical', zorder=20)
ax.text(-0.4, -0.8, r'$\nabla f$', ha='left', zorder=20)
ax.text(-0.8, -1.4, '$\partial f/\partial x$', ha='center', zorder=20)
ax.text(-1.45, -0.8, '$\partial f/\partial y$', va='center', rotation='vertical', zorder=20)
ax.text(-0.5, -0.8, r'$\nabla f$', ha='left', zorder=20)
plt.savefig('gradient.pdf')