In [3]:
%matplotlib inline
from mpl_toolkits.mplot3d.axes3d import Axes3D
import matplotlib.pyplot as plt
# imports specific to the plots in this example
import numpy as np
from matplotlib import cm
from mpl_toolkits.mplot3d.axes3d import get_test_data
# Twice as wide as it is tall.
fig = plt.figure(figsize=plt.figaspect(0.5))
#---- First subplot
ax = fig.add_subplot(1, 2, 1, projection='3d')
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
linewidth=0, antialiased=False)
ax.set_zlim3d(-1.01, 1.01)
fig.colorbar(surf, shrink=0.5, aspect=10)
#---- Second subplot
ax = fig.add_subplot(1, 2, 2, projection='3d')
X, Y, Z = get_test_data(0.05)
ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
plt.show()
In [5]:
from math import log
list = [2, 4, 8, 16]
for i in range(len(list)):
list[i] = log(list[i], 2)
list
Out[5]:
[1.0, 2.0, 3.0, 4.0]
In [18]:
X = data['L1']
Y = data['L2']
Z = data['200000_test_acc']
Out[18]:
array(['0.136719', '0.0546875', '0.0859375', '0.109375', '0.0898438',
'0.109375', '0.289062', '0.207031', '0.0742188', '0.847656',
'0.121094', '0.0898438', '0.0546875', '0.0859375', '0.136719',
'0.355469', '0.503906', '0.804688', '0.902344', '0.863281',
'0.109375', '0.121094', '0.09375', '0.0742188', '0.136719',
'0.0742188', '0.207031', '0.917969', '0.902344', '0.964844',
'0.121094', '0.132812', '0.09375', '0.136719', '0.132812',
'0.132812', '0.160156', '0.921875', '0.941406', '0.949219',
'0.0742188', '0.0859375', '0.121094', '0.136719', '0.0585938',
'0.25', '0.316406', '0.273438', '0.941406', '0.953125', '0.101562',
'0.101562', '0.136719', '0.121094', '0.121094', '0.191406',
'0.261719', '0.574219', '0.894531', '0.976562', '0.136719',
'0.0742188', '0.132812', '0.101562', '0.132812', '0.167969',
'0.101562', '0.285156', '0.910156', '0.933594', '0.0742188',
'0.0742188', '0.121094', '0.0859375', '0.121094', '0.0703125',
'0.203125', '0.261719', '0.101562', '0.929688', '0.0742188',
'0.132812', '0.136719', '0.09375', '0.0546875', '0.136719',
'0.144531', '0.261719', '0.53125', '0.96875', '0.09375', '0.136719',
'0.0546875', '0.132812', '0.117188', '0.136719', '0.171875',
'0.164062', '0.25', '0.933594', '0.132812', '0.0742188', '0.128906',
'0.121094', '0.144531', '0.125', '0.0898438', '0.222656',
'0.121094', '0.925781', '0.0546875', '0.125', '0.109375', '0.125',
'0.0898438', '0.3125', '0.148438', '0.867188', '0.890625',
'0.898438', '0.0859375', '0.0898438', '0.121094', '0.0546875',
'0.152344', '0.148438', '0.109375', '0.84375', '0.960938',
'0.949219', '0.09375', '0.136719', '0.09375', '0.0546875',
'0.0859375', '0.0820312', '0.21875', '0.160156', '0.96875',
'0.964844', '0.121094', '0.09375', '0.140625', '0.09375',
'0.140625', '0.117188', '0.128906', '0.175781', '0.894531',
'0.96875', '0.121094', '0.109375', '0.121094', '0.121094',
'0.132812', '0.140625', '0.25', '0.257812', '0.910156', '0.960938',
'0.0742188', '0.136719', '0.132812', '0.078125', '0.113281',
'0.0546875', '0.273438', '0.5', '0.621094', '0.972656', '0.0742188',
'0.109375', '0.09375', '0.0859375', '0.132812', '0.113281',
'0.101562', '0.449219', '0.277344', '0.972656', '0.121094',
'0.136719', '0.136719', '0.09375', '0.136719', '0.113281', '0.125',
'0.144531', '0.492188', '0.964844', '0.0898438', '0.0742188',
'0.0742188', '0.113281', '0.136719', '0.078125', '0.179688', '0.25',
'0.257812', '0.367188', '0.0546875', '0.0546875', '0.0546875',
'0.113281', '0.132812', '0.164062', '0.136719', '0.0898438',
'0.101562', '0.234375', '0.0859375', '0.121094', '0.136719',
'0.136719', '0.0546875', '0.121094', '0.558594', '0.890625',
'0.917969', '0.609375', '0.0898438', '0.0859375', '0.132812',
'0.0898438', '0.113281', '0.140625', '0.714844', '0.902344',
'0.945312', '0.941406', '0.0898438', '0.0859375', '0.0898438',
'0.09375', '0.113281', '0.136719', '0.0898438', '0.46875',
'0.960938', '0.960938', '0.125', '0.0859375', '0.09375', '0.113281',
'0.144531', '0.136719', '0.160156', '0.894531', '0.976562',
'0.960938', '0.132812', '0.0898438', '0.136719', '0.136719',
'0.09375', '0.140625', '0.167969', '0.199219', '0.972656',
'0.984375', '0.136719', '0.0898438', '0.0898438', '0.136719',
'0.109375', '0.140625', '0.179688', '0.226562', '0.933594',
'0.960938', '0.136719', '0.09375', '0.136719', '0.109375',
'0.09375', '0.09375', '0.101562', '0.238281', '0.792969',
'0.972656', '0.136719', '0.121094', '0.09375', '0.0546875', '0.125',
'0.078125', '0.199219', '0.164062', '0.894531', '0.945312',
'0.101562', '0.0859375', '0.109375', '0.109375', '0.121094',
'0.136719', '0.125', '0.136719', '0.242188', '0.9375', '0.0546875',
'0.121094', '0.0546875', '0.0859375', '0.078125', '0.0625', '0.125',
'0.113281', '0.179688', '0.136719', '0.132812', '0.136719',
'0.136719', '0.0898438', '0.125', '0.175781', '0.183594',
'0.0976562', '0.0898438', '0.429688', '0.0742188', '0.136719',
'0.101562', '0.136719', '0.140625', '0.0898438', '0.820312',
'0.910156', '0.871094', '0.90625', '0.136719', '0.132812',
'0.121094', '0.144531', '0.121094', '0.128906', '0.128906',
'0.921875', '0.964844', '0.976562', '0.136719', '0.136719',
'0.09375', '0.09375', '0.128906', '0.152344', '0.09375', '0.523438',
'0.941406', '1', '0.128906', '0.101562', '0.136719', '0.136719',
'0.121094', '0.09375', '0.132812', '0.773438', '0.921875',
'0.976562', '0.109375', '0.109375', '0.0742188', '0.09375',
'0.0898438', '0.132812', '0.164062', '0.210938', '0.941406',
'0.988281', '0.132812', '0.132812', '0.136719', '0.09375',
'0.101562', '0.0585938', '0.15625', '0.207031', '0.863281',
'0.976562', '0.0859375', '0.136719', '0.121094', '0.136719',
'0.09375', '0.109375', '0.15625', '0.1875', '0.308594', '0.972656',
'0.132812', '0.0859375', '0.0898438', '0.0859375', '0.0898438',
'0.136719', '0.136719', '0.121094', '0.324219', '0.992188',
'0.132812', '0.0859375', '0.136719', '0.136719', '0.136719',
'0.117188', '0.171875', '0.0898438', '0.195312', '0.132812',
'0.0742188', '0.136719', '0.113281', '0.105469', '0.117188',
'0.148438', '0.0742188', '0.148438', '0.132812', '0.0976562',
'0.101562', '0.0742188', '0.136719', '0.101562', '0.0859375',
'0.140625', '0.199219', '0.785156', '0.902344', '0.890625',
'0.0898438', '0.109375', '0.0859375', '0.109375', '0.136719',
'0.101562', '0.125', '0.6875', '0.945312', '0.957031', '0.136719',
'0.0898438', '0.09375', '0.136719', '0.15625', '0.128906',
'0.179688', '0.421875', '0.953125', '0.988281', '0.136719',
'0.0859375', '0.136719', '0.0859375', '0.0859375', '0.101562',
'0.144531', '0.628906', '0.957031', '0.984375', '0.136719',
'0.121094', '0.0898438', '0.132812', '0.0546875', '0.125',
'0.109375', '0.226562', '0.957031', '0.976562', '0.06445315',
'0.121094', '0.109375', '0.132812', '0.132812', '0.109375',
'0.148438', '0.144531', '0.941406', '0.980469', '0.11132825',
'0.136719', '0.121094', '0.136719', '0.109375', '0.0585938',
'0.09375', '0.15625', '0.3125', '0.980469', '0.097656', '0.09375',
'0.0859375', '0.0546875', '0.132812', '0.09375', '0.136719',
'0.125', '0.339844', '0.964844', '0.136719', '0.0898438',
'0.136719', '0.0546875', '0.261719', '0.0898438', '0.121094',
'0.195312', '0.210938', '0.0976562', '0.109375', '0.136719',
'0.0546875', '0.136719', '0.0898438', '0.195312', '0.183594',
'0.0859375', '0.132812', '0.160156', '0.101562', '0.109375',
'0.136719', '0.136719', '0.0898438', '0.136719', '0.183594',
'0.175781', '0.15625', '0.34375', '0.0546875', '0.136719',
'0.136719', '0.0898438', '0.09375', '0.113281', '0.167969',
'0.921875', '0.984375', '0.933594', '0.101562', '0.132812',
'0.101562', '0.0898438', '0.132812', '0.140625', '0.113281',
'0.933594', '0.957031', '0.988281', '0.09375', '0.136719',
'0.136719', '0.101562', '0.09375', '0.136719', '0.101562',
'0.929688', '0.972656', '0.984375', '0.0546875', '0.132812',
'0.121094', '0.136719', '0.136719', '0.109375', '0.121094',
'0.207031', '0.964844', '0.980469', '0.136719', '0.0859375',
'0.0742188', '0.0742188', '0.121094', '0.0898438', '0.128906',
'0.207031', '0.933594', '0.976562', '0.0859375', '0.0898438',
'0.109375', '0.0546875', '0.09375', '0.128906', '0.15625',
'0.132812', '0.550781', '0.976562', '0.0898438', '0.136719',
'0.136719', '0.109375', '0.09375', '0.121094', '0.0898438',
'0.0859375', '0.390625', '0.960938', '0.0898438', '0.136719',
'0.136719', '0.117188', '0.136719', '0.136719', '0.136719',
'0.121094', '0.132812', '0.136719', '0.132812', '0.136719',
'0.121094', '0.136719', '0.136719', '0.0898438', '0.0898438',
'0.101562', '0.09375', '0.0859375', '0.0898438', '0.121094',
'0.101562', '0.09375', '0.0546875', '0.0898438', '0.136719',
'0.195312', '0.136719', '0.132812', '0.136719', '0.101562',
'0.0546875', '0.136719', '0.09375', '0.132812', '0.140625',
'0.109375', '0.140625', '0.960938', '0.109375', '0.113281',
'0.09375', '0.0546875', '0.0859375', '0.144531', '0.148438',
'0.945312', '0.960938', '0.976562', '0.121094', '0.132812',
'0.136719', '0.109375', '0.0859375', '0.121094', '0.140625',
'0.238281', '0.96875', '0.988281', '0.0898438', '0.136719',
'0.0546875', '0.09375', '0.125', '0.09375', '0.140625', '0.210938',
'0.964844', '0.984375', '0.121094', '0.0742188', '0.109375',
'0.136719', '0.109375', '0.125', '0.136719', '0.175781', '0.609375',
'0.980469', '0.0859375', '0.136719', '0.136719', '0.132812',
'0.136719', '0.132812', '0.136719', '0.195312', '0.335938',
'0.972656', '0.136719', '0.101562', '0.0546875', '0.109375',
'0.132812', '0.121094', '0.164062', '0.125', '0.230469', '0.972656',
'0.09375', '0.128906', '0.0898438', '0.09375', '0.121094',
'0.0898438', '0.0742188', '0.121094', '0.136719', '0.0742188',
'0.101562', '0.0742188', '0.136719', '0.113281', '0.121094',
'0.136719', '0.0898438', '0.136719', '0.117188', '0.136719',
'0.132812', '0.132812', '0.121094', '0.132812', '0.0742188',
'0.136719', '0.0898438', '0.0742188', '0.0898438', '0.136719',
'0.121094', '0.132812', '0.09375', '0.101562', '0.121094',
'0.164062', '0.0742188', '0.136719', '0.136719', '0.835938',
'0.109375', '0.136719', '0.109375', '0.109375', '0.136719',
'0.140625', '0.148438', '0.9375', '0.957031', '0.949219',
'0.136719', '0.136719', '0.136719', '0.0898438', '0.136719',
'0.125', '0.0898438', '0.925781', '0.976562', '0.964844',
'0.136719', '0.0898438', '0.101562', '0.09375', '0.136719',
'0.144531', '0.0859375', '0.1875', '0.96875', '0.988281', '0.09375',
'0.132812', '0.0898438', '0.0859375', '0.136719', '0.0742188',
'0.0976562', '0.140625', '0.945312', '0.976562', '0.0859375',
'0.0859375', '0.109375', '0.136719', '0.136719', '0.148438',
'0.128906', '0.164062', '0.578125', '0.984375', '0.136719',
'0.09375', '0.0898438', '0.0742188', '0.0820312', '0.113281',
'0.121094', '0.132812', '0.246094', '0.960938', '0.132812',
'0.0898438', '0.0898438', '0.121094', '0.0859375', '0.132812',
'0.121094', '0.09375', '0.121094', '0.136719', '0.132812',
'0.0898438', '0.0859375', '0.148438', '0.0546875', '0.09375',
'0.0898438', '0.136719', '0.0898438', '0.0898438', '0.136719',
'0.109375', '0.0898438', '0.109375', '0.109375', '0.140625',
'0.0898438', '0.136719', '0.0546875', '0.0859375', '0.101562',
'0.0898438', '0.101562', '0.132812', '0.0546875', '0.0742188',
'0.128906', '0.0859375', '0.121094', '0.0859375', '0.0898438',
'0.132812', '0.121094', '0.0859375', '0.160156', '0.0976562',
'0.871094', '0.933594', '0.921875', '0.96875', '0.109375',
'0.0859375', '0.0859375', '0.136719', '0.0898438', '0.125',
'0.113281', '0.503906', '0.984375', '0.976562', '0.0859375',
'0.09375', '0.136719', '0.121094', '0.0976562', '0.117188',
'0.0976562', '0.214844', '0.984375', '0.996094', '0.109375',
'0.136719', '0.109375', '0.136719', '0.109375', '0.140625',
'0.105469', '0.183594', '0.984375', '0.992188', '0.109375',
'0.132812', '0.0859375', '0.136719', '0.0546875', '0.101562',
'0.117188', '0.160156', '0.339844', '0.976562', '0.109375',
'0.09375', '0.136719', '0.0742188', '0.136719', '0.09375',
'0.144531', '0.183594', '0.234375', '0.976562', '0.132812',
'0.0859375', '0.09375', '0.136719', '0.09375', '0.109375',
'0.09375', '0.09375', '0.0898438', '0.136719', '0.101562',
'0.101562', '0.0898438', '0.140625', '0.09375', '0.136719',
'0.0742188', '0.125', '0.101562', '0.109375', '0.0898438',
'0.136719', '0.09375', '0.136719', '0.140625', '0.09375', '0.09375',
'0.109375', '0.113281', '0.078125', '0.136719', '0.132812',
'0.136719', '0.105469', '0.136719', '0.136719', '0.109375',
'0.136719', '0.0898438', '0.136719', '0.0742188', '0.109375',
'0.136719', '0.136719', '0.140625', '0.121094', '0.0585938',
'0.125', '0.136719', '0.078125', '0.136719', '0.136719', '0.136719',
'0.0742188', '0.0859375', '0.0585938', '0.15625', '0.925781',
'0.976562', '0.960938', '0.0898438', '0.0859375', '0.101562',
'0.136719', '0.0585938', '0.136719', '0.128906', '0.242188',
'0.972656', '0.984375', '0.136719', '0.0742188', '0.136719',
'0.09375', '0.0898438', '0.117188', '0.113281', '0.152344',
'0.960938', '0.992188', '0.0546875', '0.09375', '0.0742188',
'0.136719', '0.109375', '0.121094', '0.160156', '0.144531',
'0.597656', '0.976562', '0.101562', '0.09375', '0.109375',
'0.136719', '0.09375', '0.0976562', '0.109375', '0.136719',
'0.140625', 'NA'],
dtype='|S10')
In [20]:
%matplotlib inline
data = np.genfromtxt('../log/mnist-cnn-2-tidy.csv', delimiter=',', names=True, unpack=True, dtype=None)
X = data['L1']
Y = data['L2']
Z = data['200000_test_acc']
fig = plt.figure(figsize=plt.figaspect(1))
ax = fig.add_subplot(1, 2, 2, projection='3d')
ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
plt.show()
ValueErrorTraceback (most recent call last)
<ipython-input-20-ae98ee35f2fa> in <module>()
6 fig = plt.figure(figsize=plt.figaspect(1))
7 ax = fig.add_subplot(1, 2, 2, projection='3d')
----> 8 ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
9
10 plt.show()
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/axes3d.pyc in plot_wireframe(self, X, Y, Z, *args, **kwargs)
1805 linec = art3d.Line3DCollection(lines, *args, **kwargs)
1806 self.add_collection(linec)
-> 1807 self.auto_scale_xyz(X, Y, Z, had_data)
1808
1809 return linec
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/axes3d.pyc in auto_scale_xyz(self, X, Y, Z, had_data)
473 self.xy_dataLim.update_from_data_xy(np.array([x, y]).T, not had_data)
474 if z is not None:
--> 475 self.zz_dataLim.update_from_data_xy(np.array([z, z]).T, not had_data)
476
477 # Let autoscale_view figure out how to use this data.
/usr/local/lib/python2.7/dist-packages/matplotlib/transforms.pyc in update_from_data_xy(self, xy, ignore, updatex, updatey)
951 return
952
--> 953 path = Path(xy)
954 self.update_from_path(path, ignore=ignore,
955 updatex=updatex, updatey=updatey)
/usr/local/lib/python2.7/dist-packages/matplotlib/path.pyc in __init__(self, vertices, codes, _interpolation_steps, closed, readonly)
135 vertices = vertices.astype(np.float_).filled(np.nan)
136 else:
--> 137 vertices = np.asarray(vertices, np.float_)
138
139 if (vertices.ndim != 2) or (vertices.shape[1] != 2):
/usr/local/lib/python2.7/dist-packages/numpy/core/numeric.pyc in asarray(a, dtype, order)
480
481 """
--> 482 return array(a, dtype, copy=False, order=order)
483
484 def asanyarray(a, dtype=None, order=None):
ValueError: could not convert string to float: NA
Error in callback <function post_execute at 0x7f84912e6d70> (for post_execute):
TypeErrorTraceback (most recent call last)
/usr/local/lib/python2.7/dist-packages/matplotlib/pyplot.pyc in post_execute()
145 def post_execute():
146 if matplotlib.is_interactive():
--> 147 draw_all()
148
149 # IPython >= 2
/usr/local/lib/python2.7/dist-packages/matplotlib/_pylab_helpers.pyc in draw_all(cls, force)
148 for f_mgr in cls.get_all_fig_managers():
149 if force or f_mgr.canvas.figure.stale:
--> 150 f_mgr.canvas.draw_idle()
151
152 atexit.register(Gcf.destroy_all)
/usr/local/lib/python2.7/dist-packages/matplotlib/backend_bases.pyc in draw_idle(self, *args, **kwargs)
2024 if not self._is_idle_drawing:
2025 with self._idle_draw_cntx():
-> 2026 self.draw(*args, **kwargs)
2027
2028 def draw_cursor(self, event):
/usr/local/lib/python2.7/dist-packages/matplotlib/backends/backend_agg.pyc in draw(self)
472
473 try:
--> 474 self.figure.draw(self.renderer)
475 finally:
476 RendererAgg.lock.release()
/usr/local/lib/python2.7/dist-packages/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
59 def draw_wrapper(artist, renderer, *args, **kwargs):
60 before(artist, renderer)
---> 61 draw(artist, renderer, *args, **kwargs)
62 after(artist, renderer)
63
/usr/local/lib/python2.7/dist-packages/matplotlib/figure.pyc in draw(self, renderer)
1157 dsu.sort(key=itemgetter(0))
1158 for zorder, a, func, args in dsu:
-> 1159 func(*args)
1160
1161 renderer.close_group('figure')
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/axes3d.pyc in draw(self, renderer)
269 # Calculate projection of collections and zorder them
270 zlist = [(col.do_3d_projection(renderer), col) \
--> 271 for col in self.collections]
272 zlist.sort(key=itemgetter(0), reverse=True)
273 for i, (z, col) in enumerate(zlist):
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/art3d.pyc in do_3d_projection(self, renderer)
227 xyslist = [
228 proj3d.proj_trans_points(points, renderer.M) for points in
--> 229 self._segments3d]
230 segments_2d = [list(zip(xs, ys)) for (xs, ys, zs) in xyslist]
231 LineCollection.set_segments(self, segments_2d)
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/proj3d.pyc in proj_trans_points(points, M)
214 def proj_trans_points(points, M):
215 xs, ys, zs = list(zip(*points))
--> 216 return proj_transform(xs, ys, zs, M)
217
218 def proj_trans_clip_points(points, M):
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/proj3d.pyc in proj_transform(xs, ys, zs, M)
197 """
198 vec = vec_pad_ones(xs, ys, zs)
--> 199 return proj_transform_vec(vec, M)
200
201 def proj_transform_clip(xs, ys, zs, M):
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/proj3d.pyc in proj_transform_vec(vec, M)
156
157 def proj_transform_vec(vec, M):
--> 158 vecw = np.dot(M, vec)
159 w = vecw[3]
160 # clip here..
TypeError: Cannot cast array data from dtype('float64') to dtype('S32') according to the rule 'safe'
TypeErrorTraceback (most recent call last)
/usr/local/lib/python2.7/dist-packages/IPython/core/formatters.pyc in __call__(self, obj)
337 pass
338 else:
--> 339 return printer(obj)
340 # Finally look for special method names
341 method = _safe_get_formatter_method(obj, self.print_method)
/usr/local/lib/python2.7/dist-packages/IPython/core/pylabtools.pyc in <lambda>(fig)
226
227 if 'png' in formats:
--> 228 png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
229 if 'retina' in formats or 'png2x' in formats:
230 png_formatter.for_type(Figure, lambda fig: retina_figure(fig, **kwargs))
/usr/local/lib/python2.7/dist-packages/IPython/core/pylabtools.pyc in print_figure(fig, fmt, bbox_inches, **kwargs)
117
118 bytes_io = BytesIO()
--> 119 fig.canvas.print_figure(bytes_io, **kw)
120 data = bytes_io.getvalue()
121 if fmt == 'svg':
/usr/local/lib/python2.7/dist-packages/matplotlib/backend_bases.pyc in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, **kwargs)
2178 orientation=orientation,
2179 dryrun=True,
-> 2180 **kwargs)
2181 renderer = self.figure._cachedRenderer
2182 bbox_inches = self.figure.get_tightbbox(renderer)
/usr/local/lib/python2.7/dist-packages/matplotlib/backends/backend_agg.pyc in print_png(self, filename_or_obj, *args, **kwargs)
525
526 def print_png(self, filename_or_obj, *args, **kwargs):
--> 527 FigureCanvasAgg.draw(self)
528 renderer = self.get_renderer()
529 original_dpi = renderer.dpi
/usr/local/lib/python2.7/dist-packages/matplotlib/backends/backend_agg.pyc in draw(self)
472
473 try:
--> 474 self.figure.draw(self.renderer)
475 finally:
476 RendererAgg.lock.release()
/usr/local/lib/python2.7/dist-packages/matplotlib/artist.pyc in draw_wrapper(artist, renderer, *args, **kwargs)
59 def draw_wrapper(artist, renderer, *args, **kwargs):
60 before(artist, renderer)
---> 61 draw(artist, renderer, *args, **kwargs)
62 after(artist, renderer)
63
/usr/local/lib/python2.7/dist-packages/matplotlib/figure.pyc in draw(self, renderer)
1157 dsu.sort(key=itemgetter(0))
1158 for zorder, a, func, args in dsu:
-> 1159 func(*args)
1160
1161 renderer.close_group('figure')
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/axes3d.pyc in draw(self, renderer)
269 # Calculate projection of collections and zorder them
270 zlist = [(col.do_3d_projection(renderer), col) \
--> 271 for col in self.collections]
272 zlist.sort(key=itemgetter(0), reverse=True)
273 for i, (z, col) in enumerate(zlist):
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/art3d.pyc in do_3d_projection(self, renderer)
227 xyslist = [
228 proj3d.proj_trans_points(points, renderer.M) for points in
--> 229 self._segments3d]
230 segments_2d = [list(zip(xs, ys)) for (xs, ys, zs) in xyslist]
231 LineCollection.set_segments(self, segments_2d)
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/proj3d.pyc in proj_trans_points(points, M)
214 def proj_trans_points(points, M):
215 xs, ys, zs = list(zip(*points))
--> 216 return proj_transform(xs, ys, zs, M)
217
218 def proj_trans_clip_points(points, M):
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/proj3d.pyc in proj_transform(xs, ys, zs, M)
197 """
198 vec = vec_pad_ones(xs, ys, zs)
--> 199 return proj_transform_vec(vec, M)
200
201 def proj_transform_clip(xs, ys, zs, M):
/usr/local/lib/python2.7/dist-packages/mpl_toolkits/mplot3d/proj3d.pyc in proj_transform_vec(vec, M)
156
157 def proj_transform_vec(vec, M):
--> 158 vecw = np.dot(M, vec)
159 w = vecw[3]
160 # clip here..
TypeError: Cannot cast array data from dtype('float64') to dtype('S32') according to the rule 'safe'
<matplotlib.figure.Figure at 0x7f848efb2c50>
Content source: hyunghunny/tf-hpo
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