def run(parser):
x1 = []
y1 = []
z1 = []
args = parser.parse_args()
subprocess.call(
"bedtools intersect -a %s -b %s -wo |grep -v e|bedtools groupby -i - -g 1,2,3,4 -c 8,9 -o mean,sum |awk '{print $1,$2,$3,$4,$5,$6/($3-$2)}'| sed 's/ /\t/g' > DMRs-Histone.diff"
% (args.DMRs, args.DiffHistPeaks),
shell=True)
try:
formatfile1 = open("DMRs-Histone.diff", 'r')
except IOError:
print >> sys.stderr, 'cannot open', filename
raise SystemExit
for line in formatfile1:
rows = line.strip().split("\t")
x1.append(rows[3])
y1.append(rows[4])
z1.append(rows[5])
arrayx = [float(m) for m in x1]
arrayy = [np.log2(float(m)) for m in y1]
arrayz = [float(m) for m in z1]
mean_x = np.mean(arrayx)
mean_y = np.mean(arrayy)
mean_z = np.mean(arrayz)
#print mean_x
#print mean_y
#print mean_z
fig = plt.figure()
#ax = fig.gca(projection='3d')
#for c,m in [('r','o'),('b','^')]:
# ax = fig.gca(projection='3d')
#ax = fig.add_subplot(111, projection='3d')
ax = Axes3D(fig)
ax.scatter(arrayx, arrayy, arrayz, c='b', marker='^')
ax.scatter(arrayx, arrayy, zs=0, marker='x', c='r', zdir='z')
ax.scatter(arrayx, arrayz, zs=4.5, marker='x', c='k', zdir='y')
ax.scatter(arrayy, arrayz, zs=-1, marker='x', c='g', zdir='x')
#ax.plot(arrayx, arrayz, 'r+', zdir='y', zs=4.5)
ax.plot(arrayy, arrayz, 'g+', zdir='x', zs=-1)
l1 = a3d.Line3D((0, 0, 0), (4, 0, 0), (0, 0, 0), c='k', ls='--')
l2 = a3d.Line3D((0, 0, -0.5), (0, 0, 0), (0, 0, 0), c='g', ls='--')
l3 = a3d.Line3D((0, 0, 0), (0, 0, 0), (0, 0.2, 0), c='r', ls='--')
ax.add_line(l1)
ax.add_line(l2)
ax.add_line(l3)
ax.add_line(l3)
ax.set_xlim([-1, 1])
ax.set_ylim([-12.5, 4.5])
ax.set_zlim([0, 1])
ax.set_xlabel('mCG/CG(WT-3aKO)')
ax.set_ylabel('H3K4me3.Log2(WT/3aKO)')
ax.set_zlabel('Overlap Ratio')
fig.savefig(args.outFile + ".png")
def plot_signals_3d(signals, filepath):
xlim = [-1, 7]
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')
ax.view_init(20, 250)
for i in range(signals.shape[0]):
depth = 0.2 * (i - 1)
for j in range(signals.shape[1]):
line = art3d.Line3D(*zip((j, depth, 0), (j, depth, signals[i, j])),
marker='o',
markevery=(1, 1),
linestyle='-',
color=COLORS[i])
ax.add_line(line)
plt.xlim(xlim)
plt.xlabel('$n$')
# plt.ylim([-1.1, 1.1])
ax.set_yticklabels([])
ax.set_ylim([-0.4, 0.5])
ax.set_zlim([0, 0.6])
# ax.set_zticks(np.arange(-1,1.1,0.25))
# ax.set_zticklabels(['-1','','','','0','','','','1'])
plt.savefig(filepath.absolute(), bbox_inches='tight', dpi=300)
def draw_line3D(origin=[(0, 0, 0)],
pmom=[(1, 1, 1)],
color='red',
ls='-',
lw=2.0):
lines = []
#print pmom
for o, p in zip(origin, pmom):
#x1 = p[0]
#y1 = p[1]
#z1 = p[2]
x1 = p[2]
y1 = p[0]
z1 = p[1]
#print x1,y1,z1
line = a3.Line3D((o[0], x1), (o[1], y1), (o[0], z1),
lw=lw,
ls=ls,
alpha=0.9,
color=color,
markeredgecolor=color)
lines.append(line)
return lines
def plot_line(line):
line_width = 2.0
x1x2, y1y2, z1z2, color = line
ax.add_line(art3d.Line3D(x1x2, y1y2, z1z2, lw=line_width, color=color))
box = {'alpha': 0.1, 'pad': 1}
text_args = {'size': 10, 'zorder': 1, 'bbox': box}
ax.text(x1x2[0], y1y2[0], z1z2[0], '0', color='black', **text_args)
def stemcf3d(gridu, gridv, phase, modulus, darken=None, fig=None, markerp="o", **kwargs):
r"""Stemplot the modulus of a complex valued function :math:`f:I\times I -> \mathbb{C}` together with its
phase in a color coded fashion. Additional keyword arguments are passed to the plot function.
:param gridu: The x components of the grid nodes of the real domain grid :math:`\Gamma`
:param gridv: The y components of the grid nodes of the real domain grid :math:`\Gamma`
:param phase: The phase of the complex domain result :math:`f(\Gamma)`
:param modulus: The modulus of the complex domain result :math:`f(\Gamma)`
:param darken: Whether to take into account the modulus of the data to darken colors.
:param fig: The figure instance used for plotting.
:param markerp: The shape of the stemmed markers.
"""
# Color mapping
rgb_colors = squeeze(color_map(gridv, phase=phase, modulus=modulus, darken=darken))
# Plot to the given axis instance or retrieve the current one
if fig is None:
fig = gcf()
axes = fig.add_subplot(1, 1, 1, projection='3d')
for ui, vi, wi, col in zip(gridu, gridv, modulus, rgb_colors):
line = art3d.Line3D(*list(zip((ui, vi, 0), (ui, vi, wi))), marker=markerp, markevery=(1, 1), color=col)
axes.add_line(line)
axes.set_xlim3d(real(gridu).min(), real(gridu).max())
axes.set_ylim3d(real(gridv).min(), real(gridv).max())
axes.set_zlim3d(real(modulus).min(), real(modulus).max())
def plot_lines(lines):
for line in lines:
line_width = 2.0
x1x2, y1y2, z1z2, color = line
ax.add_line(art3d.Line3D(x1x2, y1y2, z1z2, lw=line_width, color=color))
text_args = {'size' : 10, 'zorder' : 1, 'bbox' : box}
ax.text(x1x2[0], y1y2[0], z1z2[0]+0.5, '0', color='black', **text_args)
def threed_plot(df, commod):
fig = plt.figure()
ax = plt.axes(projection='3d')
# Data for a three-dimensional line
x = [int(i) for i in list(df.index.get_level_values(0).values)]
y = [int(i) for i in list(df.index.get_level_values(1).values)]
z = [float(i) for i in list(df[commod].values)]
for xi, yi, zi in zip(x, y, z):
line = art3d.Line3D(*zip((xi, yi, min(z)), (xi, yi, zi)),
marker='o',
markevery=(1, 1))
ax.add_line(line)
ax.set_xlim3d(x[0], x[-1])
ax.set_ylim3d(y[0], y[-1])
ax.set_zlim3d(min(z), max(z))
ax.xaxis.set_major_locator(MaxNLocator(integer=True))
ax.yaxis.set_major_locator(MaxNLocator(integer=True))
ax.zaxis.set_major_locator(MaxNLocator(5))
ax.set_title('3D plot of ' + commod)
ax.set_xlabel(df.index.names[0] + ' [%]')
ax.set_ylabel(df.index.names[1] + ' [yr]')
ax.set_zlabel(commod + ' [kg]')
ax.dist = 11
fig.savefig(commod, bbox_inches='tight')
return
def __init__(self, ax):
self.link = art3d.Line3D(
[ ],
[ ],
[ ],
color="k",
linewidth=1
)
ax.add_line(self.link)
def draw_boundary(X, Y, Z, ax, N, m, t1, t2, l1, l2, marker, color):
if t2 < 1:
ax.view_init(25, 345)
else:
ax.view_init(30, 330)
if N is 1:
ax.plot_surface(X, Y, Z, linewidth=1, vmin=0, vmax=4)
else:
ax.plot_surface(X, Y, Z, linewidth=1, vmin=0, vmax=6)
coords = [(t1, l1, l2[0]), (t1, l1, l2[1])]
line_coords = [[(t1, t1), (l1, l1), (0, l2[0])],
[(t1, t1), (l1, 4), (l2[0], l2[0])],
[(t1, t1), (l1, l1), (l2[0], l2[1])],
[(t1, t1), (l1, 4), (l2[1], l2[1])]]
for idx, (x, y, z) in enumerate(coords):
ax.scatter3D(x,
y,
z,
marker=marker[idx],
s=150,
color=color,
edgecolor=None)
for idx, line in enumerate(line_coords):
ax.add_line(
art3d.Line3D(line[0], line[1], line[2], color=color, ls="dashed"))
ax.set_xticks([3, 4, 5, t1])
ax.set_yticks([1, 2, 3])
ax.set_zticks([1, 2, 3, 4, 5])
xticks = ["3", "", "5", ""]
yticks = [" $10^{1}$", "", " $10^{3}$"]
zticks = [" $10^{1}$", "", " $10^{3}$", "", " $10^{5}$"]
ax.set_xticklabels(xticks)
ax.set_yticklabels(yticks)
ax.set_zticklabels(zticks)
ax.tick_params(direction='in', pad=-5)
ax.xaxis.set_rotate_label(False)
ax.yaxis.set_rotate_label(False)
ax.zaxis.set_rotate_label(False)
ax.set_xlabel('$\\tau_1$\n\n', fontsize=10)
ax.set_ylabel('$L_1$\n\n\n', fontsize=10) # (agonist)
ax.set_zlabel('$L_2$ ', fontsize=10) # (antagonist)
ax.set_xlim3d(3, t1 - 0.1)
ax.set_ylim3d(0.1, 3.9)
ax.set_zlim3d(0.1, 5)
def plot_3d(Q, title=None):
"""
Draws a 3d plot of a Qnet graph
Parameters
:param Q: Qnet Graph
:param title: Title of Graph
:return:
"""
# Create new matplotlib figure and add axes
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
for node in Q.nodes:
x, y, z = node.coords[0], node.coords[1], node.coords[2]
# Dictionary between colours and node types
qnode_color = {
QNET.Qnode: 'r',
QNET.Ground: 'y',
QNET.Swapper: 'c',
QNET.Satellite: 'b'
}
ax.scatter(x, y, z, c=qnode_color[type(node)], marker='o')
ax.text(x, y, z, '%s' % node.name, size=12, zorder=1)
# Draw arrow for satellite velocity
if isinstance(node, QNET.Satellite):
v = node.velocity
ax.quiver(x, y, z, v[0], v[1], 0, length=1.5)
for edge in Q.edges:
xs = [edge[0].coords[0], edge[1].coords[0]]
ys = [edge[0].coords[1], edge[1].coords[1]]
zs = [edge[0].coords[2], edge[1].coords[2]]
if isinstance(edge[0], QNET.Satellite) or isinstance(
edge[1], QNET.Satellite):
line = art3d.Line3D(xs, ys, zs, linestyle='--')
else:
line = art3d.Line3D(xs, ys, zs)
ax.add_line(line)
if title is not None:
plt.title(f"{title}")
fig.show()
def animate(i):
z = trace_all[:, i]
for idx, line in enumerate(lines):
ax.lines[len(edge_list)].remove()
for idx, line in enumerate(lines):
line = art3d.Line3D((x[idx], x[idx]), (y[idx], y[idx]),
(0, z[idx]),
marker='D',
markevery=(1, 1),
markerfacecolor='b',
color='b',
alpha=1)
ax.add_line(line)
return lines
def stem3d(u, v, w, fig=None, markerp="o"):
r"""This function makes a three dimensional stem plot.
"""
# Plot to the given axis instance or retrieve the current one
if fig is None:
fig = gcf()
axes = fig.add_subplot(1, 1, 1, projection='3d')
for ui, vi, wi in zip(u, v, w):
line = art3d.Line3D(*list(zip((ui, vi, 0), (ui, vi, wi))), marker=markerp, markevery=(1, 1))
axes.add_line(line)
axes.set_xlim3d(u.min(), u.max())
axes.set_ylim3d(v.min(), v.max())
axes.set_zlim3d(w.min(), w.max())
def plot_times_vs_changes_3d(rows):
fig, ax = base_plot((6, 6, 6), "Parse time vs. change size", "Change size (bytes)", "Change size (chunks)", "Parse time (ms)",
{"projection": "3d"})
x, y, z = zip(*((int(row["Added"]) + int(row["Removed"]), int(row["Changes"]), float(row["Incremental"]))
for row in rows if row["Incremental"]))
# ax.plot(x, y, z, COLORS["Incremental"], label="Incremental", markersize=3)
for xi, yi, zi in zip(x, y, z):
ax.add_line(art3d.Line3D(*zip((xi, yi, 0), (xi, yi, zi)), color='g', marker='o', markersize=3, markevery=(1, 1)))
# We need to manually set the upper limit here, because we don't call a proper plot function but manually draw lines
ax.set_xlim3d(0, max(1, *x))
ax.set_ylim3d(0, max(1, *y))
ax.set_zlim3d(0, max(1, *z))
ax.view_init(elev=30, azim=-45)
return fig
def _stem3(self, X, ax=None):
"""
Draw an image X using 3D stem plot on the given axe object.
Note that this routine will automatically do a horizontal mirror
operation given the difference between the image coordinate system and
the normal Euclidean system. So it does not work for normal stem3
plotting.
Parameters
----------
X : numpy.array
2D matrix to draw.
ax : matplotlib.axes._subplots.Axes3DSubplot
The axe object.
"""
assert len(X.shape) is 2, \
"Only gray level images are supported. The input's shape is"\
" {}".format(X.shape)
# Setup coordinates.
h, w = X.shape
x = np.linspace(0, w-1, w)
y = np.linspace(0, h-1, h)
xv, yv = np.meshgrid(x, y)
# If no axis object is given, we need to create it here.
if ax is None:
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')
# Draw.
for row in range(h):
for x_, y_, z_ in zip(xv[row, :], yv[row, :], X[h-1-row, :]):
line = art3d.Line3D(*list(zip((x_, y_, 0), (x_, y_, z_))),
marker='o')
ax.add_line(line)
ax.set_xlim3d(0, w)
ax.set_ylim3d(0, h)
ax.set_zlim3d(min(0, X.min()), X.max() * 1.3)
plt.show()
def draw_geo_vector_3d(self, vec, ax=None, **kwargs):
"""Draw a :class:`GeoVector3D` into 3D map
:param GeoVector3D vec: the vector
.. note::
Anchor must be set in the :class:`GeoVector3D` object
"""
if ax is None:
ax = self.ax
try:
if not isinstance(ax, Axes3D):
raise ValueError("Need :class:`Axes3D` object as input...")
elif not vec.type() == "GeoVector3D":
raise AttributeError("Wrong input, need :class:`GeoVector3D` "
"object")
elif not vec.anchor.type() == "GeoPoint":
raise AttributeError("Vector anchor not set or wrong type..")
if not any([x in kwargs for x in ["ls", "linestyle"]]):
kwargs["ls"] = "--"
a = vec.anchor
pf = a + vec
x0, y0 = self(a.longitude, a.latitude)
z0 = a.altitude #*1000
x1, y1 = self(pf.longitude, pf.latitude)
z1 = pf.altitude #*1000
l = a3d.Line3D((x0, x1), (y0, y1), (z0, z1), **kwargs)
handle = ax.add_line(l)
self.lines[vec.name] = handle
return pf
except:
print(vec.anchor.type())
raise
def Graph3d(x, y, z, **kwargs):
xmin = kwargs.setdefault('xmin', x.min())
xmax = kwargs.setdefault('xmax', x.max())
ymin = kwargs.setdefault('ymin', y.min())
ymax = kwargs.setdefault('ymax', y.max())
zmin = kwargs.setdefault('zmin', z.min())
zmax = kwargs.setdefault('zmax', z.max())
if 'fig' in kwargs:
fig = kwargs['fig']
else:
fig = plt.figure(figsize=(6,6))
if 'ax' in kwargs:
ax = kwargs['ax']
else:
ax = fig.add_subplot(1, 1, 1, projection='3d')
ax._axis3don = False
for xi, yi, zi in zip(x, y, z):
if zi >= 0:
color = 'b'
else:
color = 'r'
line = art3d.Line3D(*zip((xi, yi, 0), (xi, yi, zi)), marker='o',
markersize=2, markevery=(1, 1), color=color)
ax.add_line(line)
if 'lc' in kwargs:
ax.add_collection3d(kwargs['lc'])
ax.set_xlim3d(xmin, xmax)
ax.set_ylim3d(ymin, ymax)
ax.set_zlim3d(zmin, zmax)
ax.set_facecolor('white')
ax.view_init(elev=30., azim=300)
plt.tight_layout()
def plot_A_3D(
Xdata,
Ydata,
Zdata,
colormap="RdBu",
x_min=None,
x_max=None,
y_min=None,
y_max=None,
z_min=None,
z_max=None,
title="",
xlabel="",
ylabel="",
zlabel="",
xticks=None,
yticks=None,
fig=None,
subplot_index=None,
is_logscale_x=False,
is_logscale_y=False,
is_logscale_z=False,
is_disp_title=True,
type="stem",
save_path=None,
):
"""Plots a 3D graph ("stem", "surf" or "pcolor")
Parameters
----------
Xdata : ndarray
array of x-axis values
Ydata : ndarray
array of y-axis values
Zdata : ndarray
array of z-axis values
colormap : colormap object
colormap prescribed by user
x_min : float
minimum value for the x-axis (no automated scaling in 3D)
x_max : float
maximum value for the x-axis (no automated scaling in 3D)
y_min : float
minimum value for the y-axis (no automated scaling in 3D)
y_max : float
maximum value for the y-axis (no automated scaling in 3D)
z_min : float
minimum value for the z-axis (no automated scaling in 3D)
z_max : float
maximum value for the z-axis (no automated scaling in 3D)
title : str
title of the graph
xlabel : str
label for the x-axis
ylabel : str
label for the y-axis
zlabel : str
label for the z-axis
xticks : list
list of ticks to use for the x-axis
fig : Matplotlib.figure.Figure
existing figure to use if None create a new one
subplot_index : int
index of subplot in which to plot
is_logscale_x : bool
boolean indicating if the x-axis must be set in logarithmic scale
is_logscale_y : bool
boolean indicating if the y-axis must be set in logarithmic scale
is_logscale_z : bool
boolean indicating if the z-axis must be set in logarithmic scale
is_disp_title : bool
boolean indicating if the title must be displayed
type : str
type of 3D graph : "stem", "surf", "pcolor" or "scatter"
"""
# Set figure/subplot
is_show_fig = True if fig is None else False
is_3d = False
if type != "pcolor" and type != "scatter":
is_3d = True
fig, ax = init_subplot(fig=fig, subplot_index=subplot_index, is_3d=is_3d)
# Plot
if type == "stem":
for xi, yi, zi in zip(Xdata, Ydata, Zdata):
line = art3d.Line3D(*zip((xi, yi, 0), (xi, yi, zi)),
linewidth=3.0,
marker="o",
markersize=5.0,
markevery=(1, 1),
color=COLORS[0])
ax.add_line(line)
ax.set_xlim3d(x_max, x_min)
ax.set_ylim3d(y_min, y_max)
ax.set_zlim3d(z_min, z_max)
# set correct angle
ax.view_init(elev=20.0, azim=45)
ax.zaxis.set_rotate_label(False)
ax.set_zlabel(zlabel, rotation=0)
ax.xaxis.labelpad = 30
ax.yaxis.labelpad = 30
ax.zaxis.labelpad = 30
if xticks is not None:
ax.xaxis.set_ticks(xticks)
if yticks is not None:
ax.yaxis.set_ticks(yticks)
# white background
ax.xaxis.pane.fill = False
ax.yaxis.pane.fill = False
ax.zaxis.pane.fill = False
ax.xaxis.pane.set_edgecolor("w")
ax.yaxis.pane.set_edgecolor("w")
ax.zaxis.pane.set_edgecolor("w")
if is_logscale_z:
ax.zscale("log")
elif type == "surf":
ax.plot_surface(Xdata, Ydata, Zdata, cmap=colormap)
ax.set_xlim3d(x_max, x_min)
ax.set_ylim3d(y_min, y_max)
ax.set_zlim3d(z_min, z_max)
ax.zaxis.set_rotate_label(False)
ax.set_zlabel(zlabel, rotation=0)
ax.xaxis.labelpad = 30
ax.yaxis.labelpad = 30
ax.zaxis.labelpad = 30
if xticks is not None:
ax.xaxis.set_ticks(xticks)
if yticks is not None:
ax.yaxis.set_ticks(yticks)
# white background
ax.xaxis.pane.fill = False
ax.yaxis.pane.fill = False
ax.zaxis.pane.fill = False
ax.xaxis.pane.set_edgecolor("w")
ax.yaxis.pane.set_edgecolor("w")
ax.zaxis.pane.set_edgecolor("w")
if is_logscale_z:
ax.zscale("log")
elif type == "pcolor":
c = ax.pcolormesh(Xdata,
Ydata,
Zdata,
cmap=colormap,
vmin=z_min,
vmax=z_max)
clb = fig.colorbar(c, ax=ax)
clb.ax.set_title(zlabel, fontsize=18, fontname=FONT_NAME)
clb.ax.tick_params(labelsize=18)
for l in clb.ax.yaxis.get_ticklabels():
l.set_family(FONT_NAME)
if xticks is not None:
ax.xaxis.set_ticks(xticks)
if yticks is not None:
ax.yaxis.set_ticks(yticks)
elif type == "scatter":
c = ax.scatter(Xdata,
Ydata,
c=Zdata,
marker="s",
cmap=colormap,
vmin=z_min,
vmax=z_max)
clb = fig.colorbar(c, ax=ax)
clb.ax.set_title(zlabel, fontsize=18, fontname=FONT_NAME)
clb.ax.tick_params(labelsize=18)
for l in clb.ax.yaxis.get_ticklabels():
l.set_family(FONT_NAME)
if xticks is not None:
ax.xaxis.set_ticks(xticks)
if yticks is not None:
ax.yaxis.set_ticks(yticks)
ax.set_xlabel(xlabel)
ax.set_ylabel(ylabel)
if is_logscale_x:
ax.xscale("log")
if is_logscale_y:
ax.yscale("log")
if is_disp_title:
ax.set_title(title)
if is_3d:
for item in ([ax.xaxis.label, ax.yaxis.label, ax.zaxis.label] +
ax.get_xticklabels() + ax.get_yticklabels() +
ax.get_zticklabels()):
item.set_fontsize(22)
else:
for item in ([ax.xaxis.label, ax.yaxis.label] + ax.get_xticklabels() +
ax.get_yticklabels()):
item.set_fontsize(22)
item.set_fontname(FONT_NAME)
ax.title.set_fontsize(24)
ax.title.set_fontname(FONT_NAME)
if save_path is not None:
fig.savefig(save_path)
plt.close()
if is_show_fig:
fig.show()
plt.draw()
plt.pause(.01)
fig = plt.figure()
fig.set_size_inches(15, 15)
ax = fig.add_subplot(111, projection='3d', aspect='equal')
ax.view_init(azim=17,elev = 17)
ax.grid(False)
ax.set_xlim(16, 0)
ax.set_ylim(0, 16)
ax.set_zlim(0, 16)
ax.set_xticklabels('')
ax.set_ylabel('Time')
ax.set_yticklabels(list(range(0,9)))
ax.set_zticklabels(['', 'P_3', '', '', 'P_2', '', '', 'P_1'])
ax.set_title('Lamport\'s Clocks (Multicast System)', fontsize=16)
for line in lines:
x1x2, y1y2, z1z2, line_width, color = line
ax.add_line(art3d.Line3D(x1x2, y1y2, z1z2, lw=line_width, color=color))
ax.text(x1x2[0], y1y2[0], z1z2[0]+0.5, 0, size=10, zorder=1,
color='black', bbox={'alpha': 0.1, 'pad': 1})
for arrow in points1:
plot_process(arrow)
plt.show()
# rotation_view(ax,plt)
nentries=x_chmap.shape[0]
ncolors=x_chmap[0].shape[3]
xcenter=x_chmap[0].shape[0]/2
xmax=x_chmap[0].shape[0]
ycenter=x_chmap[0].shape[1]/2
ymax=x_chmap[0].shape[1]
zcenter=x_chmap[0].shape[2]/2
print(ncolors)
for i in range(nentries):
print(x_chmap[i].shape)
for j in [0]: #range(ncolors):
ax,plot,x,y,z,c=plot4d(x_chmap[i][:,:,:,j:j+1],'','etabin','layer','phibin')
l = a3d.Line3D((xcenter,xcenter),(0,0),(0,ymax),c = 'k', ls = '--')
ax.add_line(l)
l2 = a3d.Line3D((0,xmax),(0,0),(ycenter,ycenter),c = 'k', ls = '--')
ax.add_line(l2)
#ax.view_init(0,90)
#ax.plot(x, y, 'r+', zdir='y')#, zs=1.5)
#ax.plot(z, y, 'g+', zdir='x')#, zs=-0.5)
#ax.plot(x, z, 'b+', zdir='z')#, zs=-1.5)
plot.show()
#input("Press [enter] to continue.")
plot.close()
detection_xs.append(repeat)
else:
detection_xs.append(ext_offset)
detection_ys.append(width)
detection_zs.append(offset)
results_table.append(
[f, total_samples, successes_total,
len(results['detections'])])
else:
results_table.append([f, total_samples, successes_total, 0])
for idx in range(len(xs)):
l = a3d.Line3D((xs[idx], xs[idx]), (ys[idx], ys[idx]),
(min(results['parameters']['offsets']) - 2, zs[idx]),
color='gray',
ls='--',
linewidth=.5)
l.set_alpha(0.5)
ax.add_line(l)
for idx in range(len(detection_xs)):
l = a3d.Line3D(
(detection_xs[idx], detection_xs[idx]),
(detection_ys[idx], detection_ys[idx]),
(min(results['parameters']['offsets']) - 2, detection_zs[idx]),
color='red',
ls='--',
linewidth=.5)
l.set_alpha(0.5)
ax.add_line(l)
def axes3d(fig, reflevel, xr, yr, zr, xsize, ysize, zsize):
# get 3d axes
ax = fig.gca(projection='3d')
# create 3d coordinate axes lines which cuts the point at xr, yr and zr
line=art3d.Line3D(*zip((0, yr, zr), (xsize*2**reflevel, yr, zr)),
color='black', linewidth=0.8, alpha=0.25, zorder=100)
ax.add_line(line)
line=art3d.Line3D(*zip((xr, 0, zr), (xr, ysize*2**reflevel, zr)),
color='black', linewidth=0.8, alpha=0.25, zorder=100)
ax.add_line(line)
line=art3d.Line3D(*zip((xr, yr, 0), (xr, yr, ysize*2**reflevel)),
color='black', linewidth=0.8, alpha=0.25, zorder=100)
ax.add_line(line)
# spacing between ticks
s = int((xsize*2**reflevel)/20)
# widths of the ticks
l = int((xsize*2**reflevel)/100)
###################
# plot ticks STARTS
# plot the first ticks which position > xr or in the others yr or zr
i = 1
while xr+i*s < xsize*2**reflevel:
line=art3d.Line3D(*zip((xr+i*s, yr-l, zr), (xr+i*s, yr+l, zr)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
line=art3d.Line3D(*zip((xr+i*s, yr, zr-l), (xr+i*s, yr, zr+l)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
i += 1
# plot the last ticks which position < xr or in the others yr or zr
i = 1
while xr-i*s > 0:
line=art3d.Line3D(*zip((xr-i*s, yr-l, zr), (xr-i*s, yr+l, zr)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
line=art3d.Line3D(*zip((xr-i*s, yr, zr-l), (xr-i*s, yr, zr+l)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
i += 1
i = 1
while yr+i*s < ysize*2**reflevel:
line=art3d.Line3D(*zip((xr-l, yr+i*s, zr), (xr+l, yr+i*s, zr)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
line=art3d.Line3D(*zip((xr, yr+i*s, zr-l), (xr, yr+i*s, zr+l)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
i += 1
i = 1
while yr-i*s > 0:
line=art3d.Line3D(*zip((xr-l, yr-i*s, zr), (xr+l, yr-i*s, zr)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
line=art3d.Line3D(*zip((xr, yr-i*s, zr-l), (xr, yr-i*s, zr+l)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
i += 1
i = 1
while zr+i*s < zsize*2**reflevel:
line=art3d.Line3D(*zip((xr, yr-l, zr+i*s), (xr, yr+l, zr+i*s)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
line=art3d.Line3D(*zip((xr-l, yr, zr+i*s), (xr+l, yr, zr+i*s)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
i += 1
i = 1
while zr-i*s > 0:
line=art3d.Line3D(*zip((xr, yr-l, zr-i*s), (xr, yr+l, zr-i*s)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
line=art3d.Line3D(*zip((xr-l, yr, zr-i*s), (xr+l, yr, zr-i*s)),
color='black', linewidth=0.7, alpha=0.25, zorder=100+i)
ax.add_line(line)
i += 1
# plot ticks ENDS
#################
# set the basic 3d coordinate axes off
ax.set_axis_off()
# return axes
return ax
def plot_decays(decay_positions, four_vecs_lab_particle1, four_vecs_lab_particle2, z_detector, r=5):
fig = plt.figure()
ax = fig.gca(projection='3d')
decay_plot_count = 0
for decay_pos, fv1, fv2 in zip(decay_positions, four_vecs_lab_particle1, four_vecs_lab_particle2):
x, y, z = decay_pos
if z > z_detector:
continue
decay_plot_count += 1
if decay_plot_count > max_decays_to_plot:
break
p1 = fv1[1:]
p2 = fv2[1:]
direction1 = p1/np.linalg.norm(p1)
direction2 = p2/np.linalg.norm(p2)
scale_factor1 = (z_detector - z)/direction1[2]
scale_factor2 = (z_detector - z)/direction2[2]
dx1, dy1, dz1 = direction1 * abs(scale_factor1)
dx2, dy2, dz2 = direction2 * abs(scale_factor2)
if double_hit(decay_pos, fv1, fv2, z_detector, r):
ax.plot([z, z+dz1], [y, y+dy1], [x, x+dx1], color="green")
ax.plot([z, z+dz2], [y, y+dy2], [x, x+dx2], color="green")
continue
if single_hit(decay_pos, fv1, z_detector, r):
ax.plot([z, z+dz1], [y, y+dy1], [x, x+dx1], color="orange")
ax.plot([z, z+dz2], [y, y+dy2], [x, x+dx2], color="orange")
continue
if single_hit(decay_pos, fv2, z_detector, r):
ax.plot([z, z+dz1], [y, y+dy1], [x, x+dx1], color="orange")
ax.plot([z, z+dz2], [y, y + dy2], [x, x+dx2], color="orange")
continue
ax.plot([z, z + dz1], [y, y + dy1], [x, x + dx1], color="red")
ax.plot([z, z + dz2], [y, y + dy2], [x, x + dx2], color="red")
ax.plot([0, z_detector], [0, 0], [0, 0])
ax.scatter([0], [0], [0], s=60, label='origin')
#Mald Zentrum des Detektors
ax.scatter([z_detector], [0], [0], "y",s=60, label='detector', color="red")
#Malt den Detektorumfang, check nicht wie man die Achsen richtig skaliert
edge_steps = 300
edge = np.zeros((edge_steps, 3))
for counter in range(edge_steps):
angle = 2*np.pi*counter/edge_steps
edge[counter] = [z_detector, r*np.sin(angle), r*np.cos(angle)]
ax.scatter(edge[:,0], edge[:,1], edge[:,2], s=20, color="red")
#setzt die Axen fest
ax.set_ylim3d(-2.5, 2.5)
ax.set_zlim3d(-2.5, 2.5)
#zeichnet eine schoene legende
green_line = art3d.Line3D(0, 0, 0, color="green")
red_line = art3d.Line3D(0, 0, 0, color="red")
orange_line = art3d.Line3D(0, 0, 0, color="orange")
ax.legend([green_line, red_line, orange_line],
["hit, both particles", "miss, both particles", "1 hit, 1 missed"])
plt.show()
def plot_3D(
Xdata,
Ydata,
Zdata,
colormap="RdBu_r",
color_list=None,
x_min=None,
x_max=None,
y_min=None,
y_max=None,
z_min=None,
z_max=None,
title="",
xlabel="",
ylabel="",
zlabel="",
xticks=None,
yticks=None,
fig=None,
ax=None,
is_logscale_x=False,
is_logscale_y=False,
is_logscale_z=False,
is_disp_title=True,
type_plot="stem",
is_contour=False,
save_path=None,
is_show_fig=None,
is_switch_axes=False,
win_title=None,
font_name="arial",
font_size_title=12,
font_size_label=10,
font_size_legend=8,
):
"""Plots a 3D graph ("stem", "surf" or "pcolor")
Parameters
----------
Xdata : ndarray
array of x-axis values
Ydata : ndarray
array of y-axis values
Zdata : ndarray
array of z-axis values
colormap : colormap object
colormap prescribed by user
x_min : float
minimum value for the x-axis (no automated scaling in 3D)
x_max : float
maximum value for the x-axis (no automated scaling in 3D)
y_min : float
minimum value for the y-axis (no automated scaling in 3D)
y_max : float
maximum value for the y-axis (no automated scaling in 3D)
z_min : float
minimum value for the z-axis (no automated scaling in 3D)
z_max : float
maximum value for the z-axis (no automated scaling in 3D)
title : str
title of the graph
xlabel : str
label for the x-axis
ylabel : str
label for the y-axis
zlabel : str
label for the z-axis
xticks : list
list of ticks to use for the x-axis
fig : Matplotlib.figure.Figure
existing figure to use if None create a new one
ax : Matplotlib.axes.Axes object
ax on which to plot the data
is_logscale_x : bool
boolean indicating if the x-axis must be set in logarithmic scale
is_logscale_y : bool
boolean indicating if the y-axis must be set in logarithmic scale
is_logscale_z : bool
boolean indicating if the z-axis must be set in logarithmic scale
is_disp_title : bool
boolean indicating if the title must be displayed
type_plot : str
type of 3D graph : "stem", "surf", "pcolor" or "scatter"
is_contour : bool
True to show contour line if type_plot = "pcolor"
save_path : str
full path including folder, name and extension of the file to save if save_path is not None
is_show_fig : bool
True to show figure after plot
is_switch_axes : bool
to switch x and y axes
"""
# Set if figure must be shown if is_show_fig is None
if is_show_fig is None:
is_show_fig = True if fig is None else False
# Set if figure is 3D
if type_plot not in ["pcolor", "pcolormesh", "scatter"]:
is_3d = True
else:
is_3d = False
# Set figure if needed
if fig is None and ax is None:
(fig, ax, _, _) = init_fig(fig=None, shape="rectangle", is_3d=is_3d)
if color_list is None:
color_list = COLORS
# Calculate z limits
if z_min is None:
z_min = np_min(Zdata)
if z_max is None:
z_max = np_max(Zdata)
# Check logscale on z axis
if is_logscale_z:
Zdata = 10 * log10(np_abs(Zdata))
clb_format = "%0.0f"
else:
clb_format = "%.4g"
# Switch axes
if is_switch_axes:
Xdata, Ydata = Ydata, Xdata
if len(Xdata.shape) > 1:
Xdata = Xdata.T
if len(Ydata.shape) > 1:
Ydata = Ydata.T
if len(Zdata.shape) > 1:
Zdata = Zdata.T
x_min, y_min = y_min, x_min
x_max, y_max = y_max, x_max
xlabel, ylabel = ylabel, xlabel
xticks, yticks = yticks, xticks
is_logscale_x, is_logscale_y = is_logscale_y, is_logscale_x
# Plot
if type_plot == "stem":
cmap = matplotlib.cm.get_cmap(colormap)
for xi, yi, zi in zip(Xdata, Ydata, Zdata):
line = art3d.Line3D(*zip((xi, yi, 0), (xi, yi, zi)),
linewidth=2.0,
marker="o",
markersize=3.0,
markevery=(1, 1),
color=cmap(0))
ax.add_line(line)
ax.set_xlim3d(x_max, x_min)
ax.set_ylim3d(y_min, y_max)
ax.set_zlim3d(z_min, z_max)
# set correct angle
ax.view_init(elev=20.0, azim=45)
ax.zaxis.set_rotate_label(False)
ax.set_zlabel(zlabel, rotation=0)
ax.xaxis.labelpad = 5
ax.yaxis.labelpad = 5
ax.zaxis.labelpad = 5
if xticks is not None:
ax.xaxis.set_ticks(xticks)
if yticks is not None:
ax.yaxis.set_ticks(yticks)
# white background
ax.xaxis.pane.fill = False
ax.yaxis.pane.fill = False
ax.zaxis.pane.fill = False
ax.xaxis.pane.set_edgecolor("w")
ax.yaxis.pane.set_edgecolor("w")
ax.zaxis.pane.set_edgecolor("w")
if is_logscale_z:
ax.zscale("log")
elif type_plot == "surf":
ax.plot_surface(Xdata, Ydata, Zdata, cmap=colormap)
ax.set_xlim3d(x_max, x_min)
ax.set_ylim3d(y_min, y_max)
ax.set_zlim3d(z_min, z_max)
ax.zaxis.set_rotate_label(False)
ax.set_zlabel(zlabel, rotation=0)
ax.xaxis.labelpad = 5
ax.yaxis.labelpad = 5
ax.zaxis.labelpad = 5
if xticks is not None:
ax.xaxis.set_ticks(xticks)
if yticks is not None:
ax.yaxis.set_ticks(yticks)
# white background
ax.xaxis.pane.fill = False
ax.yaxis.pane.fill = False
ax.zaxis.pane.fill = False
ax.xaxis.pane.set_edgecolor("w")
ax.yaxis.pane.set_edgecolor("w")
ax.zaxis.pane.set_edgecolor("w")
if is_logscale_z:
ax.zscale("log")
elif type_plot == "pcolor":
Zdata[Zdata < z_min] = z_min
Zdata[Zdata > z_max] = z_max
# Handle descending order axes (e.g. spectrogram of run-down in freq/rpm map)
if Ydata[-1] < Ydata[0]:
Ydata = Ydata[::-1]
Zdata = Zdata[:, ::-1]
if Xdata[-1] < Xdata[0]:
Xdata = Xdata[::-1]
Zdata = Zdata[::-1, :]
im = NonUniformImage(
ax,
interpolation="bilinear",
extent=(x_min, x_max, y_max, y_min),
cmap=colormap,
picker=10,
)
im.set_data(Xdata, Ydata, Zdata.T)
im.set_clim(z_min, z_max)
ax.images.append(im)
if is_contour:
ax.contour(Xdata, Ydata, Zdata.T, colors="black", linewidths=0.8)
clb = fig.colorbar(im, ax=ax, format=clb_format)
clb.ax.set_title(zlabel, fontsize=font_size_legend, fontname=font_name)
clb.ax.tick_params(labelsize=font_size_legend)
for l in clb.ax.yaxis.get_ticklabels():
l.set_family(font_name)
if xticks is not None:
ax.xaxis.set_ticks(xticks)
if yticks is not None:
ax.yaxis.set_ticks(yticks)
ax.set_xlim([x_min, x_max])
ax.set_ylim([y_min, y_max])
elif type_plot == "pcolormesh":
c = ax.pcolormesh(Xdata,
Ydata,
Zdata,
cmap=colormap,
shading="gouraud",
antialiased=True)
clb = fig.colorbar(c, ax=ax)
clb.ax.set_title(zlabel, fontsize=font_size_legend, fontname=font_name)
clb.ax.tick_params(labelsize=font_size_legend)
for l in clb.ax.yaxis.get_ticklabels():
l.set_family(font_name)
if xticks is not None:
ax.xaxis.set_ticks(xticks)
if yticks is not None:
ax.yaxis.set_ticks(yticks)
ax.set_xlim([x_min, x_max])
ax.set_ylim([y_min, y_max])
elif type_plot == "scatter":
c = ax.scatter(
Xdata,
Ydata,
# s=10,
c=Zdata,
marker=".",
cmap=colormap,
vmin=z_min,
vmax=z_max,
picker=True,
pickradius=5,
)
clb = fig.colorbar(c, ax=ax)
clb.ax.set_title(zlabel, fontsize=font_size_legend, fontname=font_name)
clb.ax.tick_params(labelsize=font_size_legend)
for l in clb.ax.yaxis.get_ticklabels():
l.set_family(font_name)
if xticks is not None:
ax.xaxis.set_ticks(xticks)
if yticks is not None:
ax.yaxis.set_ticks(yticks)
ax.set_xlabel(xlabel)
ax.set_ylabel(ylabel)
if is_logscale_x:
ax.xscale("log")
if is_logscale_y:
ax.yscale("log")
if is_disp_title:
ax.set_title(title)
if is_3d:
for item in ([ax.xaxis.label, ax.yaxis.label, ax.zaxis.label] +
ax.get_xticklabels() + ax.get_yticklabels() +
ax.get_zticklabels()):
item.set_fontsize(font_size_label)
else:
for item in ([ax.xaxis.label, ax.yaxis.label] + ax.get_xticklabels() +
ax.get_yticklabels()):
item.set_fontsize(font_size_label)
item.set_fontname(font_name)
ax.title.set_fontsize(font_size_title)
ax.title.set_fontname(font_name)
if save_path is not None:
save_path = save_path.replace("\\", "/")
fig.savefig(save_path)
plt.close()
if is_show_fig:
fig.show()
if win_title:
manager = plt.get_current_fig_manager()
if manager is not None:
manager.set_window_title(win_title)
def _draw_line3D(self, X, Y, Z, *args, **kwargs):
artist = art3d.Line3D(X, Y, Z, *args, **kwargs)
self.main_ax.add_line(artist)
return artist
color2 = [0, 0, 255]
ax.plot([color1[0]], [color1[1]], [color1[2]],
color='r',
label='color1',
marker='o',
markersize=20)
ax.plot([color2[0]], [color2[1]], [color2[2]],
color='b',
label='color2',
marker='o',
markersize=20)
ax.legend()
# Draw a line
import mpl_toolkits.mplot3d.art3d as art3d
line = art3d.Line3D([2, 3, 4, 5, 6, 7, 8], [2, 3, 4, 5, 6, 7, 8],
[3, 5, 3, 5, 3, 5, 3],
color='g')
ax.add_line(line)
ax.set_title("Color distance", fontsize=16)
ax.set_xlabel(r'$R$', fontsize=20, color='r')
ax.set_ylabel(r'$G$', fontsize=20, color='g')
ax.set_zlabel(r'$B$', fontsize=20, color='b')
ax.set_xticklabels([0, 50, 100, 150, 200, 250], fontsize=10)
ax.set_yticklabels([0, 50, 100, 150, 200, 250], fontsize=10)
ax.set_zticklabels([0, 50, 100, 150, 200, 250], fontsize=10)
plt.show()
# v_y = []
# v_z = []
# for z in flr:
# for v in z:
# v_x.append(v[1])
# v_y.append(v[2])
# v_z.append(v[3])
# line = art3d.Line3D(v_x, v_y, v_z, color='gray')
# ax.add_line(line)
# Plot all connections
for c in c_set:
x_edge = [c[0][1], c[1][1]]
y_edge = [c[0][2], c[1][2]]
z_edge = [c[0][3], c[1][3]]
line = art3d.Line3D(x_edge, y_edge, z_edge, color='black')
ax.add_line(line)
# Make arrays for the edges of the path to plot
e_x = []
e_y = []
e_z = []
for i in path:
e_x.append(v_set[i][1])
e_y.append(v_set[i][2])
e_z.append(v_set[i][3])
line = art3d.Line3D(e_x, e_y, e_z, color='red')
ax.add_line(line)
plt.show()
def plot_node_3d(self,
pos_coordinates,
edge_list,
node_values,
view_angle,
nodeIdx,
figIdx=0,
save_fig=False):
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')
[elev, azim] = view_angle
ax.view_init(elev, azim)
x = pos_coordinates[:, 0]
y = pos_coordinates[:, 1]
z = node_values
# plot a zero-plane
Sx = np.linspace(min(x), max(x), 100)
Sy = np.linspace(min(y), max(y), 100)
SurfaceX, SurfaceY = np.meshgrid(Sx, Sy)
SurfaceZ = np.zeros((len(Sx), ))
ax.plot_surface(SurfaceX,
SurfaceY,
SurfaceZ,
rstride=8,
cstride=8,
alpha=0.05)
for edge in edge_list:
n0_idx = next(
(item['loc'] for item in nodeIdx if item['node'] == edge[0]))
n1_idx = next(
(item['loc'] for item in nodeIdx if item['node'] == edge[1]))
lx = np.array((x[n0_idx], x[n1_idx]))
ly = np.array((y[n0_idx], y[n1_idx]))
line = art3d.Line3D(lx,
ly,
np.zeros((2, )),
marker='o',
markevery=(0, 1),
markerfacecolor='r',
color='k',
linewidth=0.5)
ax.add_line(line)
# plot node and node-attributes in stem plot
for xi, yi, zi in zip(x, y, z):
line = art3d.Line3D(*zip((xi, yi, 0), (xi, yi, zi)),
marker='D',
markevery=(1, 1),
markerfacecolor='b',
color='b',
alpha=1)
ax.add_line(line)
ax.set_xlim3d(min(x), max(x))
ax.set_ylim3d(min(y), max(y))
ax.set_zlim3d(min([min(z), -1]), max([max(z), 1]))
plt.show()
#filename = "../figures/" + strftime("%d%m%Y_%H%M%S", gmtime()) + "_netNode"+ str(figIdx) +".eps"
#fig.savefig(filename, format='eps', dpi=1000)
if save_fig == True:
filename = "../figures/" + strftime(
"%d%m%Y_%H%M%S", gmtime()) + "_netNode" + str(figIdx) + ".png"
fig.savefig(filename)
def make_animate(self, G, view_angle, save_anime=False):
pos_coordinates, edge_list, trace_all, nodeIdx = self.draw_data_prepare(
G)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')
[elev, azim] = view_angle
ax.view_init(elev, azim)
x = pos_coordinates[:, 0]
y = pos_coordinates[:, 1]
z = trace_all[:, 0]
# plot a zero-plane
Sx = np.linspace(min(x), max(x), 100)
Sy = np.linspace(min(y), max(y), 100)
SurfaceX, SurfaceY = np.meshgrid(Sx, Sy)
SurfaceZ = np.zeros((len(Sx), ))
ax.plot_surface(SurfaceX,
SurfaceY,
SurfaceZ,
rstride=8,
cstride=8,
alpha=0.05)
for edge in edge_list:
n0_idx = next(
(item['loc'] for item in nodeIdx if item['node'] == edge[0]))
n1_idx = next(
(item['loc'] for item in nodeIdx if item['node'] == edge[1]))
lx = np.array((x[n0_idx], x[n1_idx]))
ly = np.array((y[n0_idx], y[n1_idx]))
#line=ax.quiver(x[n0_idx], y[n0_idx], 0, (x[n1_idx]- x[n0_idx]), (y[n1_idx]- y[n0_idx]), 0 , marker='o', markevery=(0, 1), markerfacecolor='r', color='k', linewidth=0.5)
line = art3d.Line3D(lx,
ly,
np.zeros((2, )),
marker='o',
markevery=(0, 1),
markerfacecolor='r',
color='k',
linewidth=0.5)
ax.add_line(line)
# plot node and node-attributes in stem plot
lines = [] #record line objects
for xi, yi, zi in zip(x, y, z):
line = art3d.Line3D(*zip((xi, yi, 0), (xi, yi, zi)),
marker='D',
markevery=(1, 1),
markerfacecolor='b',
color='b',
alpha=1)
ax.add_line(line)
lines.append(line)
ax.set_xlim3d(min(x), max(x))
ax.set_ylim3d(min(y), max(y))
ax.set_zlim3d(min([min(z), -1]), max([max(z), 1]))
def animate(i):
z = trace_all[:, i]
for idx, line in enumerate(lines):
ax.lines[len(edge_list)].remove()
for idx, line in enumerate(lines):
line = art3d.Line3D((x[idx], x[idx]), (y[idx], y[idx]),
(0, z[idx]),
marker='D',
markevery=(1, 1),
markerfacecolor='b',
color='b',
alpha=1)
ax.add_line(line)
return lines
def init():
for line in lines:
line.set_data([], [])
return lines
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig,
animate,
init_func=init,
frames=trace_all.shape[1],
interval=30,
blit=True)
if save_anime == True:
filename = "../figures/" + strftime(
"%d%m%Y_%H%M%S", gmtime()) + "_netAnime" + ".mp4"
anim.save(filename, fps=10, extra_args=['-vcodec', 'libx264'])
def scatter3d(self,
x,
y,
z,
filename=None,
spot_cols=None,
label=False,
stem=True,
label_font_size=6,
rotation=134,
elevation=48,
squish_scales=False,
spot_size=40,
depthshade=True,
**kargs):
"""
**Purpose**
plot a scatter plot of PCx against PCy against PCz
This is the 3D variant
**Arguments**
x, y, z (Required)
PC dimension to plot as scatter
Note that PC begin at 1 (and not at zero, as might be expected)
spot_cols (Optional, default="black" or self.set_cols())
list of colours for the samples, should be the same length as
the number of conditions.
spot_size (Optional, default=40)
The relative spot size.
label (Optional, default=False)
label each spot with the name of the condition
label_font_size (Optional, default=6)
label font size.
stem (Optional, default=False)
Draw stems from the spot down to the base of the graph. (i.e. z=0)
rotation (Optional, default=134)
The rotation along the X, Y plane
elevation (Optional, default=48
The rotation along the Z plane.
depthshade (Optional, default=True)
turn on or off matplotlib depth shading of the points in the 3D acise
**Returns**
None
"""
assert filename, "scatter: Must provide a filename"
xdata = self.__transform[:, x - 1]
ydata = self.__transform[:, y - 1]
zdata = self.__transform[:, z - 1]
perc_weights = self.get_loading_percents()
fig = self.__draw.getfigure(**kargs)
ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=elevation, azim=rotation)
cols = self.cols
if spot_cols:
cols = spot_cols
sc = ax.scatter(
xdata,
ydata,
zdata,
#edgecolors="none",
c=cols,
s=spot_size,
depthshade=depthshade)
sc.set_edgecolor('none')
if label:
for i, lab in enumerate(self.labels):
ax.text(xdata[i],
ydata[i],
zdata[i],
lab,
size=label_font_size,
ha="center",
va="bottom")
if stem: # stem must go after scatter for sorting. Actually, not true right? matplotlib uses zorder for that...
z_min = min(zdata)
for x_, y_, z_ in zip(xdata, ydata, zdata):
line = art3d.Line3D(*list(zip((x_, y_, z_min), (x_, y_, z_))),
marker=None,
c="grey",
alpha=0.1)
ax.add_line(line)
ax.set_xlabel(
"PC%s (%.1f%%)" %
(x, perc_weights[x - 1])) # can be overridden via do_common_args()
ax.set_ylabel("PC%s (%.1f%%)" % (y, perc_weights[y - 1]))
ax.set_zlabel("PC%s (%.1f%%)" % (z, perc_weights[z - 1]))
if "logx" in kargs and kargs["logx"]:
ax.set_xscale("log", basex=kargs["logx"])
if "logy" in kargs and kargs["logy"]:
ax.set_yscale("log", basey=kargs["logy"])
# squish_scales must be True as there seems to be a bug in 3D plots in guessing the scales
# Don't worry about kargs, do_common_args will overwrite.
ax.set_xlim([min(xdata), max(xdata)])
ax.set_ylim([min(ydata), max(ydata)])
ax.set_zlim([min(zdata), max(zdata)])
#self.__draw.do_common_args(ax, **kargs)
real_filename = self.__draw.savefigure(fig, filename)
config.log.info(
"scatter3d(): Saved 'PC%s' vs 'PC%s' vs 'PC%s' scatter to '%s'" %
(x, y, z, real_filename))
def scatter3d(self,
x,
y,
z,
filename=None,
spot_cols=None,
label=False,
stem=False,
label_font_size=6,
rotation=134,
elevation=48,
interactive=False,
squish_scales=False,
spot_size=40,
**kargs):
"""
**Purpose**
plot a scatter plot of PCx against PCy against PCz
This is the 3D variant
**Arguments**
x, y, z (Required)
PC dimension to plot as scatter
Note that PC begin at 1 (and not at zero, as might be expected)
spot_cols (Optional, default="black" or self.set_cols())
list of colours for the samples, should be the same length as
the number of conditions.
spot_size (Optional, default=40)
The relative spot size.
label (Optional, default=False)
label each spot with the name of the condition
label_font_size (Optional, default=6)
label font size.
stem (Optional, default=False)
Draw stems from the spot down to the base of the graph. (i.e. z=0)
rotation (Optional, default=134)
The rotation along the X, Y plane
elevation (Optional, default=48
The rotation along the Z plane.
interactive (Optional, default=False)
if True then spawn the matplotlib show() view. Note that this will pause
execution of your script.
Note that by default glbase uses a non-GUI matplotlib setting.
You will need to fiddle around with matplotlib.use() before importing glbase
squish_scales (Optional, default=False)
set the limits very aggressively to [minmax(x), minmax(y), minmax(z)]
**Returns**
None
You can get PC data from pca.get_uvd()
"""
assert filename, "scatter(): Must provide a filename"
xdata = self.__v[x - 1]
ydata = self.__v[y - 1]
zdata = self.__v[z - 1]
fig = self.__draw.getfigure(**kargs)
ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=elevation, azim=rotation)
cols = self.cols
if spot_cols:
cols = spot_cols
ax.scatter(xdata, ydata, zdata, edgecolors="none", c=cols, s=spot_size)
if label:
for i, lab in enumerate(self.labels):
ax.text(xdata[i],
ydata[i],
zdata[i],
lab,
size=label_font_size,
ha="center",
va="bottom")
if stem: # stem must go after scatter for sorting. Actually, not true right? matplotlib uses zorder for that...
z_min = min(zdata)
for x_, y_, z_ in zip(xdata, ydata, zdata):
line = art3d.Line3D(*list(zip((x_, y_, z_min), (x_, y_, z_))),
marker=None,
c="grey",
alpha=0.1)
ax.add_line(line)
ax.set_xlabel("PC%s" % (x, )) # can be overridden via do_common_args()
ax.set_ylabel("PC%s" % (y, ))
ax.set_zlabel("PC%s" % (z, ))
if "logx" in kargs and kargs["logx"]:
ax.set_xscale("log", basex=kargs["logx"])
if "logy" in kargs and kargs["logy"]:
ax.set_yscale("log", basey=kargs["logy"])
if squish_scales:
# Don't worry about kargs, do_common_args will overwrite.
ax.set_xlim([min(xdata), max(xdata)])
ax.set_ylim([min(ydata), max(ydata)])
ax.set_zlim([min(zdata), max(zdata)])
self.__draw.do_common_args(ax, **kargs)
if "zlims" in kargs:
ax.set_zlim([kargs["zlim"][0], kargs["zlim"][1]])
if interactive:
fig.show() # hope you are not on a cluster!
real_filename = self.__draw.savefigure(fig, filename)
config.log.info(
"scatter3d(): Saved 'PC%s' vs 'PC%s' vs 'PC%s' scatter to '%s'" %
(x, y, z, real_filename))