def _blank_plot(domain, ran):
# make the plot
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
# thicken the axis lines
ax.axhline(linewidth=1.7, color="k")
ax.axvline(linewidth=1.7, color="k")
x_lower, x_upper = int(domain.left), int(
domain.right) # needs to be changed, is just a temporary type changer
y_lower, y_upper = int(ran.left), int(ran.right)
# remove tick lines on the axes
plt.xticks([])
plt.yticks([])
plt.ylim(y_lower, y_upper)
plt.xlim(x_lower, x_upper)
# add axes labels
ax.text(1.05,
0,
r'$x$',
transform=BlendedGenericTransform(ax.transAxes, ax.transData),
va='center')
ax.text(0,
1.05,
r'$y$',
transform=BlendedGenericTransform(ax.transData, ax.transAxes),
ha='center')
# end-of-axis arrows
x_width = (abs(plt.xlim()[0]) + abs(plt.xlim()[1]))
y_width = (abs(plt.ylim()[0]) + abs(plt.ylim()[1]))
plt.arrow(plt.xlim()[1],
-0.003,
0.00000000001,
0,
width=x_width * 0.0015 * 0.5,
color="k",
clip_on=False,
head_width=y_width * 0.12 / 7,
head_length=x_width * 0.024 * 0.5)
plt.arrow(0.003,
plt.ylim()[1],
0,
0.00000000001,
width=y_width * 0.0015 * 0.5,
color="k",
clip_on=False,
head_width=x_width * 0.12 / 7,
head_length=y_width * 0.024 * 0.5)
# only show cartesian axes
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
def _blank_plot(domain, ran):
# make the plot
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
# thicken the axis lines
ax.axhline(linewidth=1.7, color="k")
ax.axvline(linewidth=1.7, color="k")
x_lower, x_upper = int(domain.left), int(domain.right) # needs to be changed, is just a temporary type changer
y_lower, y_upper = int(ran.left), int(ran.right)
# remove tick lines on the axes
plt.xticks([])
plt.yticks([])
plt.ylim(y_lower, y_upper)
plt.xlim(x_lower, x_upper)
# add axes labels
ax.text(1.05, 0, r'$x$', transform=BlendedGenericTransform(ax.transAxes, ax.transData), va='center')
ax.text(0, 1.05, r'$y$', transform=BlendedGenericTransform(ax.transData, ax.transAxes), ha='center')
# end-of-axis arrows
x_width = (abs(plt.xlim()[0]) + abs(plt.xlim()[1]))
y_width = (abs(plt.ylim()[0]) + abs(plt.ylim()[1]))
plt.arrow(plt.xlim()[1], -0.003, 0.00000000001, 0,
width=x_width*0.0015*0.5, color="k", clip_on=False,
head_width=y_width*0.12/7, head_length=x_width*0.024*0.5)
plt.arrow(0.003, plt.ylim()[1], 0, 0.00000000001,
width=y_width*0.0015*0.5, color="k", clip_on=False,
head_width=x_width*0.12/7, head_length=y_width*0.024*0.5)
# only show cartesian axes
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
'C{}'.format(i),
label=label + r', $r_%i=%i$ mm' % (i + 1, r / 1000),
clip_on=False)
# draw measurement points
ax3.plot(foursphereParams['r'][:, 0],
foursphereParams['r'][:, 2],
'ko',
label='EEG/MEG sites')
for i, (x, y, z) in enumerate(foursphereParams['r']):
# theta = np.arcsin(x / foursphereParams['radii'][-1])
# if x >= 0:
# ax3.text(x, z+5000, r'${}\pi$'.format(theta / np.pi))
# else:
# ax3.text(x, z+5000, r'${}\pi$'.format(theta / np.pi), ha='right')
ax3.text(x, z + 2500, r'{}'.format(i + 1), ha='center')
# dipole location
ax3.plot([0], [dipole_position[-1]], 'k.', label='dipole site')
ax3.axis('equal')
ax3.set_xticks(np.r_[-np.array(foursphereParams['radii']), 0,
foursphereParams['radii']])
ax3.set_xticklabels([])
ax3.legend(loc=(0.25, 0.15), frameon=False)
# four-sphere volume conductor
sphere = LFPy.FourSphereVolumeConductor(**foursphereParams)
phi_p = sphere.calc_potential(cell.current_dipole_moment, rz=dipole_position)
# import example_parallel_network_plotting as plotting
vlimround = draw_lineplot(
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
theta = np.linspace(0, np.pi, 31)
# draw some circles:
for i, r, label in zip(range(4), PSET.foursphereParams['radii'], ['brain', 'CSF', 'skull', 'scalp']):
ax.plot(np.cos(theta)*r, np.sin(theta)*r, 'C{}'.format(i), label=label + r', $r_%i=%i$ mm' % (i+1, r / 1000), clip_on=False)
# draw measurement points
ax.plot(PSET.foursphereParams['r'][:, 0], PSET.foursphereParams['r'][:, 2], 'ko', label='EEG/MEG sites')
for i, (x, y, z) in enumerate(PSET.foursphereParams['r']):
ax.text(x, z+2500, r'{}'.format(i+1), ha='center')
# dipole location
ax.plot([0], [PSET.foursphereParams['radii'][0] + PSET.layer_data['center'][3]], 'k.', label='dipole site')
ax.axis('equal')
ax.set_ylim(top=max(PSET.foursphereParams['radii']) + 5000)
ax.set_xticks(np.r_[-np.array(PSET.foursphereParams['radii']), 0, PSET.foursphereParams['radii']])
ax.set_xticklabels([])
ax.legend(loc=(0.25, 0.05), frameon=False)
ax.text(-0.1, 1.05, alphabet[5],
horizontalalignment='center',
verticalalignment='center',
fig.add_subplot(ax1)
#
for direction in ["xzero", "yzero"]:
ax1.axis[direction].set_axisline_style("-|>")
ax1.axis[direction].set_visible(True)
#
for direction in ["left", "right", "bottom", "top"]:
ax1.axis[direction].set_visible(False)
ax1.set_aspect('equal')
ax1.set_xlim(-Sig_max, Sig_max)
ax1.set_ylim(-Sig_max, Sig_max)
ax1.text(0.,
1.05,
'y',
size=20,
transform=BlendedGenericTransform(ax1.transData, ax1.transAxes))
ax1.text(1.05,
-0.15,
'x',
size=20,
transform=BlendedGenericTransform(ax1.transAxes, ax1.transData))
vec_phi_xy = ax1.quiver(0,
0,
0,
0,
width=10,
scale=1,
units='x',
import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import numpy as np
if __name__ == '__main__':
fig = plt.figure(1)
ax = SubplotZero(fig, 1, 1, 1)
# fig.autofmt_xdate(bottom=0.2, rotation=30, ha='right')
fig.add_subplot(ax)
ax.text(-1.15, 0.99, 'y', transform=BlendedGenericTransform(ax.transData, ax.transAxes), ha='center')
ax.text(1., -0.25, 'x', transform=BlendedGenericTransform(ax.transAxes, ax.transData), va='center')
#
for direction in ["xzero", "left"]:
ax.axis[direction].set_axisline_style("-|>")
ax.axis[direction].set_visible(True)
for direction in ["right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
x = np.linspace(-1., +1., 1000) # x < 0
# print(x)
ax.plot(x, 3**((2*x)/(3*x+1)))
plt.show()
from mpl_toolkits.axes_grid.axislines import SubplotZero
x = linspace(-5 * pi, 5 * pi, 500)
y = (sin(x) / x)**2
fig = plt.figure(figsize=(8, 4))
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
ax.grid(True)
ax.set_xticks([
-5 * pi, -4 * pi, -3 * pi, -2 * pi, -pi, 0, pi, 2 * pi, 3 * pi, 4 * pi,
5 * pi
])
ax.set_xticklabels([
"$-5 \pi$", "$-4 \pi$", "$-3 \pi$", "$-2 \pi$", "$- \pi$", "0", "$\pi$",
"$2 \pi$", "$3 \pi$", "$4 \pi$", "$5 \pi$"
])
ax.set_ylim((-.3, 1.2))
ax.set_yticklabels([])
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_axisline_style("->")
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
ax.plot(x, y, label=r"$sinc^{2} \ x$", color="k", linewidth=3, alpha=0.8)
ax.text(5.5 * pi, 0., "x")
ax.text(0.1, 1, "1")
ax.legend()
plt.tight_layout()
plt.savefig("sinc.png")
plt.show()
from matplotlib.transforms import BlendedGenericTransform
import matplotlib.pyplot as plt
import numpy
if 1:
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
ax.axhline(linewidth=1.7, color="black")
ax.axvline(linewidth=1.7, color="black")
plt.xticks(range(5))
plt.yticks(range(1,5))
ax.text(0, 1.05, '$x_{2}$', transform=BlendedGenericTransform(ax.transData, ax.transAxes), ha='center')
ax.text(1.025, 0, '$x_{1}$', transform=BlendedGenericTransform(ax.transAxes, ax.transData), va='center')
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_axisline_style("-|>")
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
x = numpy.linspace(-1, 3.5, 1000)
y = (4 - 2*x)
ax.plot(x,y)
plt.annotate('$y=1$',xy=(1.75,1.5))
plt.annotate('$y=0$',xy=(0.5,1))
if __name__ == '__main__':
fig = plt.figure(1)
ax = SubplotZero(fig, 1, 1, 1)
fig.add_subplot(ax)
labels = range(-4,5)
plt.plot(labels, labels, color="w")
ax.axhline(linewidth=.7, color="black")
ax.axvline(linewidth=.7, color="black")
ax.text(0, 1.05, 'y', transform=BlendedGenericTransform(ax.transData, ax.transAxes), ha='center')
ax.text(1.05, 0, 'x', transform=BlendedGenericTransform(ax.transAxes, ax.transData), va='center')
#
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_axisline_style("-|>")
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
for label in ax.get_ymajorticklabels():
label.set_rotation(123)
x = np.linspace(-4, 0, 100) # x < 0
f1, = ax.plot(x, -(x), label="-x")
theta = np.linspace(0, np.pi, 31)
# draw some circles:
for i, r, label in zip(range(4), foursphereParams['radii'], ['brain', 'CSF', 'skull', 'scalp']):
ax3.plot(np.cos(theta)*r, np.sin(theta)*r, 'C{}'.format(i), label=label + r', $r_%i=%i$ mm' % (i+1, r / 1000), clip_on=False)
# draw measurement points
ax3.plot(foursphereParams['r'][:, 0], foursphereParams['r'][:, 2], 'ko', label='EEG/MEG sites')
for i, (x, y, z) in enumerate(foursphereParams['r']):
# theta = np.arcsin(x / foursphereParams['radii'][-1])
# if x >= 0:
# ax3.text(x, z+5000, r'${}\pi$'.format(theta / np.pi))
# else:
# ax3.text(x, z+5000, r'${}\pi$'.format(theta / np.pi), ha='right')
ax3.text(x, z+2500, r'{}'.format(i + 1), ha='center')
# dipole location
ax3.plot([0], [dipole_position[-1]], 'k.', label='dipole site')
ax3.axis('equal')
ax3.set_xticks(np.r_[-np.array(foursphereParams['radii']), 0, foursphereParams['radii']])
ax3.set_xticklabels([])
ax3.legend(loc=(0.25, 0.15), frameon=False)
# four-sphere volume conductor
sphere = LFPy.FourSphereVolumeConductor(
**foursphereParams
)
phi_p = sphere.calc_potential(cell.current_dipole_moment, rz=dipole_position)
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid.axislines import SubplotZero
import numpy as np
import fractions
# 改変箇所をまとめておく
FIGNUM = 1 # 0 or 1
if FIGNUM == 0:
t_max, step = 2, fractions.Fraction(1,3) # 傾きの最大、最小値の設定
# 傾きをいくつ刻みで変化させるか。分数のまま計算させるためにFraction()を利用した
if FIGNUM == 1:
t_max, step = 3, fractions.Fraction(1,2)
x_max = 7
y_max = 6
y_min = -5
def f(x, t):
return t*x-t**2
# 以上が改変箇所
t_min = -t_max # 対称性の利用
x_min = -x_max
if 1:
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_axisline_style("-|>")
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
for i, r, label in zip(range(4), PSET.foursphereParams['radii'],
['brain', 'CSF', 'skull', 'scalp']):
ax.plot(np.cos(theta) * r,
np.sin(theta) * r,
'C{}'.format(i),
label=label + r', $r_%i=%i$ mm' % (i + 1, r / 1000),
clip_on=False)
# draw measurement points
ax.plot(PSET.foursphereParams['r'][:, 0],
PSET.foursphereParams['r'][:, 2],
'ko',
label='EEG/MEG sites')
for i, (x, y, z) in enumerate(PSET.foursphereParams['r']):
ax.text(x, z + 2500, r'{}'.format(i + 1), ha='center')
# dipole location
ax.plot([0],
[PSET.foursphereParams['radii'][0] + PSET.layer_data['center'][3]],
'k.',
label='dipole site')
ax.axis('equal')
ax.set_ylim(top=max(PSET.foursphereParams['radii']) + 5000)
ax.set_xticks(np.r_[-np.array(PSET.foursphereParams['radii']), 0,
PSET.foursphereParams['radii']])
ax.set_xticklabels([])
ax.legend(loc=(0.25, 0.05), frameon=False)
def f(x, t):
return t * x - t**2 # 関数fの定義
if 1:
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
ax.axhline(linewidth=1.7, color="black")
ax.axvline(linewidth=1.7, color="black")
plt.xticks([])
plt.yticks([])
plt.ylim([-20,40])
ax.text(0, 1.05, '$y$', transform=BlendedGenericTransform(ax.transData, ax.transAxes), ha='center')
ax.text(1.05, 0, '$x$', transform=BlendedGenericTransform(ax.transAxes, ax.transData), va='center')
# 軸の書式設定(謎)
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_axisline_style("-|>")
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
x = np.linspace(-10, 10, 200)
for i in range(-5,6): # グラフを書く作業を繰り返す範囲
y = f(x, t=i)
ax.plot(x, y, 'black', linewidth=2)
plt.show()
def main():
opts, args = getopt.getopt(sys.argv[1:], 'u:', ['URL='])
print("Number of arguments: " + str(len(sys.argv)))
if len(sys.argv) > 1:
threadID = str(sys.argv[1])
else:
threadID = '3jms68'
print("Using thread: " + threadID)
r = praw.Reddit(user_agent='test script /u/Speff')
#r.set_oauth_app_info(client_id='aDjUAlJ0Cb17pA',
# client_secret='AeJjd7CLEUt7wyMmTVhP6kidhLc',
# redirect_uri='http://127.0.0.1:65010/'
# 'authorize_callback')
#url = r.get_authorize_url('uniqueKey', 'identity', True)
#print(url)
#access_information = r.get_access_information('lfJfhgKEDDUzgwY9a2tcVtVYMnc')
#r.set_access_credentials(**access_information)
#authenticated_user = r.get_me()
#print(authenticated_user.name, authenticated_user.link_karma)
start = float(time.time())
submission = r.get_submission(submission_id=threadID, comment_sort="confidence")
submission.replace_more_comments(limit=None, threshold=1)
print("Seconds to process thread: " + str(time.time()-start))
flat_comments = praw.helpers.flatten_tree(submission.comments)
submission_score = submission.score
submission_time = submission.created_utc
comment_score = []
comment_time = []
commentInfo = []
#comment_body = []
print("Number of comments: " + str(len(flat_comments)))
for x in flat_comments:
# print(x.body + "\n")
comment_score.append(abs(x.score-1)+1)
comment_time.append((x.created_utc - submission_time)/(60))
# comment_body.append(x.body)
data = np.column_stack((comment_time, comment_score))
uniques, count = np.unique(data[:,1], return_counts=True)
unvoted = 0.0
for x in range(0, len(uniques)):
if(uniques[x]) == 1:
unvoted = count[x]
unvoted = unvoted / len(comment_time)
if 1:
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
ax.axis["left"].set_label('Points')
ax.axis["bottom"].set_label('Time (minutes)')
xRange = np.amax(data[:,0]) - np.amin(data[:,0])
yRange = np.amax(data[:,1]) - np.amin(data[:,1])
plt.axhline(1, color='gray', linestyle='--')
plt.axhline(0, color='black')
plt.axvline(0, color='black')
xFit = np.linspace(np.amin(data[:,0]) - xRange*0.1, np.amax(data[:,0]) + xRange*0.1, 1000)
A, K, C = fit_exp_nonlinear(data[:,0], data[:,1])
fit_y = 2*model_func(xFit, A, K, C)
print("Best-fit polynomial coefficient(s): " + str((A, K, C)))
ax.axis([np.amin(data[:,0]) - xRange*0.1, np.amax(data[:,0]) + xRange*0.1, np.amin(data[:,1]) - yRange*0.1, np.amax(data[:,1]) + yRange*0.1])
ax.plot(data[:,0], data[:,1], '.')
ax.plot(xFit, fit_y, '-', color='darkred')
ax.text(0.75*xRange + np.amin(data[:,0]), 0.9*yRange + np.amin(data[:,1]), str(round(unvoted,3)*100) + '% unvoted \n', fontsize=15)
plt.show()
fig.add_subplot(ax)
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_visible(True)
ax.axis[direction].set_axisline_style("->")
for direction in ["top", "bottom", "left", "right"]:
ax.axis[direction].set_visible(False)
ax.axis["yzero"].set_axis_direction("left")
ax.grid(True)
ax.minorticks_on()
ax.contour(x,
y,
x**2 + 2. * x * y + y**2 - 8. * x, [0],
linewidths=1.5,
colors='r')
ax.text(1.75, -4.5, r'$x^2+2xy+y^2-8x=0$', color='r')
ax.arrow(.5, -1, 0, 5, color='orange', head_width=.1, head_length=.2)
ax.text(.75, 4, r'$\bar{y}$', color='orange')
ax.arrow(-2.5, 1.5, 5.5, 0, color='orange', head_width=.1, head_length=.2)
ax.text(3, 1, r'$\bar{x}$', color='orange')
ax.plot(.5, 1.5, 'ko')
ax.text(.25, 1.75, r'V')
ax.arrow(-4.5, -4.5, 9, 9, color='m', ls='dashed', lw=.5), ax.text(-4,
-4,
r'$x=y$',
color='m')
ax.arrow(-5.5, -4.5, 9, 9, color='grey', ls='dashed',
lw=.5), ax.text(-6, -3, r'$x=y-1$', color='grey')
ax.arrow(-2, -1, 5, 5, color='g', head_width=.2,
head_length=.2), ax.text(2.9, 4.2, r'$y$', color='g')
