def ontype(event):
if event.key=='enter':
#-- retrieve the sample data from the plot: the sample is plotted in white
for child in plt.gca().get_children():
if hasattr(child,'get_color') and child.get_color()=='1':
sample = np.array(child.get_data()).T # put it in the right format
break # make sure `child` is now set to the right artist
sample = evolve(sample,maxfunc,breed_crossover)
child.set_data(sample[:,0],sample[:,1])
if event.key=='i':
sample = np.random.uniform(size=(slider.val,2),low=0,high=1) # initialize sample
bkg = maxfunc(np.mgrid[0:1:500j,0:1:500j]) # make the background
plt.cla()
plt.plot(sample[:,0],sample[:,1],'o',color='1',mec='1')
plt.imshow(bkg,extent=[0,1,0,1],aspect='auto',cmap=plt.cm.spectral)
plt.gca().set_autoscale_on(False)
plt.draw()
if __name__ == "__main__":
axpop = plt.axes([0.20, 0.05, 0.65, 0.03], axisbg='lightgoldenrodyellow') # axis for the slide
slider = plt.Slider(axpop, 'Population', 10, 2000, valinit=500) # the slider
ax1 = plt.axes([0.1,0.15,0.85,0.77]) # main axis to plot the results
plt.gcf().canvas.mpl_connect('key_press_event',ontype) # connect the ontype function to the GUI
plt.show() # show the window
def makeSlider():
global data, plot
if plot.sliderAxes == []:
plot.sliderAxes = P.axes([0.2, 0.05, 0.6, 0.03], axisbg='lightgoldenrodyellow') # make place for a slider
if plot.slider == []:
plot.slider = P.Slider(plot.sliderAxes, 'time', data.t[0], data.t[-1], valinit=data.t[0]) # make a slider for the time
plot.slider.on_changed(updatePlots) # define the function to be executed when the slider value is changed
P.draw()
ax2.set_title('Y(K)')
ax2.set_xlabel('capital')
ax2.set_ylabel('yield')
ax2.grid(True)
# ax2.set_yscale('log')
ax2.legend()
axes = []
leftSpace = 0.2
startY = 0.05
deltaY = 0.04
axcolor = '#E4AC9A'
for name in axNames:
axes.append(plt.axes([leftSpace, startY, 0.65, 0.03], facecolor=axcolor))
startY += deltaY
# creating sliders with their names
sliderColor = '#755A57'
sliders = {}
for i in range(0, len(axes)):
leftB, rightB = axLimits[i]
sliders[axNames[i]] = pylab.Slider(axes[i],
axNames[i],
leftB,
rightB,
valinit=axInitVal[i],
color=sliderColor)
sliders[axNames[i]].on_changed(update)
plt.show()
def animate_interactive(data,
t=None,
dim_order=(0, 1, 2),
fps=10.0,
title=None,
xlabel='x',
ylabel='y',
font_size=24,
color_bar=0,
colorbar_label=None,
sloppy=True,
fancy=False,
range_min=None,
range_max=None,
extent=[-1, 1, -1, 1],
shade=False,
azdeg=0,
altdeg=65,
arrowsX=None,
arrowsY=None,
arrows_resX=10,
arrows_resY=10,
arrows_pivot='mid',
arrows_width=0.002,
arrows_scale=5,
arrows_color='black',
plot_arrows_grid=False,
movie_file=None,
bitrate=1800,
keep_images=False,
figsize=(8, 7),
dpi=300,
**kwimshow):
"""
Assemble a 2D animation from a 3D array.
call signature::
animate_interactive(data, t=None, dim_order=(0, 1, 2),
fps=10.0, title=None, xlabel='x', ylabel='y',
font_size=24, color_bar=0, colorbar_label=None,
sloppy=True, fancy=False,
range_min=None, range_max=None, extent=[-1, 1, -1, 1],
shade=False, azdeg=0, altdeg=65,
arrowsX=None, arrowsY=None, arrows_resX=10, arrows_resY=10,
arrows_pivot='mid', arrows_width=0.002, arrows_scale=5,
arrows_color='black', plot_arrows_grid=False,
movie_file=None, bitrate=1800, keep_images=False,
figsize=(8, 7), dpi=300,
**kwimshow)
Assemble a 2D animation from a 3D array. *data* has to be a 3D array of
shape [nt, nx, ny] and who's time index has the same dimension as *t*.
The time index of *data* as well as its x and y indices can be changed
via *dim_order*.
Keyword arguments:
*dim_order*:
Ordering of the dimensions in the data array (t, x, y).
*fps*:
Frames per second of the animation.
*title*:
Title of the plot.
*xlabel*:
Label of the x-axis.
*ylabel*:
Label of the y-axis.
*font_size*:
Font size of the title, x and y label.
The size of the x- and y-ticks is 0.5*font_size and the colorbar ticks'
font size is 0.5*font_size.
*color_bar*: [ 0 | 1 ]
Determines how the colorbar changes:
(0 - no cahnge; 1 - adapt extreme values).
*colorbar_label*:
Label of the color bar.
*sloppy*: [ True | False ]
If True the update of the plot lags one frame behind. This speeds up the
plotting.
*fancy*: [ True | False ]
Use fancy font style.
*range_min*, *range_max*:
Range of the colortable.
*extent*: [ None | (left, right, bottom, top) ]
Limits for the axes (domain).
*shade*: [ False | True ]
If True plot a shaded relief instead of the usual colormap.
Note that with this option cmap has to be specified like
cmap = plt.cm.hot instead of cmap = 'hot'. Shading cannot
be used with the color_bar = 0 option.
*azdeg*, *altdeg*:
Azimuth and altitude of the light source for the shading.
*arrowsX*:
Data containing the x-component of the arrows.
*arrowsY*:
Data containing the y-component of the arrows.
*arrows_resXY*:
Plot every arrows_resXY arrow in x and y.
*arrows_pivot*: [ 'tail' | 'middle' | 'tip' ]
The part of the arrow that is used as pivot point.
*arrows_width*:
Width of the arrows.
*arrows_scale*:
Scaling of the arrows.
*arrows_color*:
Color of the arrows.
*plot_arrows_grid*: [ False | True ]
If 'True' the grid where the arrows are aligned to is shown.
*movie_file*: [ None | string ]
The movie file where the animation should be saved to.
If 'None' no movie file is written. Requires 'ffmpeg' to be installed.
*bitrate*:
Bitrate of the movie file. Set to higher value for higher quality.
*keep_images*: [ False | True ]
If 'True' the images for the movie creation are not deleted.
*figsize*:
Size of the figure in inches.
*dpi*:
Dots per inch of the frame.
**kwimshow:
Remaining arguments are identical to those of pylab.imshow. Refer to that help.
"""
try:
import thread
except:
import _thread as thread
# We need to define these variables as globals, as they are being used
# by various functions.
global time_step, time_slider, pause
global fig, axes, image, colorbar, arrows, manager, n_times, movie_files
global rgb, plot_arrows
if title is None:
title = ''
def plot_frame():
"""
Plot the current frame.
"""
global time_step, axes, colorbar, arrows, manager, rgb
# Define the plot title.
if not movie_file is None:
axes.set_title(title + r'$\quad$' +
r'$t={0:.4e}$'.format(t[time_step]),
fontsize=font_size)
# Update the image data.
if not shade:
image.set_data(data[time_step, :, :])
else:
image.set_data(rgb[time_step, :, :, :])
# Update the colorbar.
if color_bar == 0:
pass
if color_bar == 1:
colorbar.set_clim(vmin=data[time_step, :, :].min(),
vmax=data[time_step, :, :].max())
colorbar.draw_all()
# Update the arrows data.
if plot_arrows:
arrows.set_UVC(U=arrowsX[time_step, ::arrows_resX, ::arrows_resY],
V=arrowsY[time_step, ::arrows_resX, ::arrows_resY])
if not sloppy or (not movie_file is None):
manager.canvas.draw()
def play(thread_name):
"""
Play the movie.
"""
import time
global time_step, time_slider, pause, fig, axes, n_times, movie_files
pause = False
while (time_step < n_times) and (not pause):
# Write the image files for the movie.
if not movie_file is None:
plot_frame()
frame_name = '{0}{1:06}.png'.format(movie_file, time_step)
fig.savefig(frame_name, dpi=dpi)
movie_files.append(frame_name)
else:
time_start = time.clock()
time_slider.set_val(t[time_step])
# Wait for the next frame (fps).
while (time.clock() - time_start < 1.0 / fps):
pass
time_step += 1
time_step -= 1
def play_thread(event):
"""
Call the play function as a separate thread (for GUI).
"""
global pause
if pause:
try:
thread.start_new_thread(play, ("play_thread", ))
except:
print("Error: unable to start play thread.")
def pausing(event):
global pause
pause = True
def reverse(event):
global time_step, time_slider
time_step -= 1
if time_step < 0:
time_step = 0
# Plot the frame and update the time slider.
time_slider.set_val(t[time_step])
def forward(event):
global time_step, time_slider
time_step += 1
if time_step > len(t) - 1:
time_step = len(t) - 1
# Plot the frame and update the time slider.
time_slider.set_val(t[time_step])
import numpy as np
import pylab as plt
pause = True
plot_arrows = False
# Check if the data has the right dimensions.
if (data.ndim != 3 and data.ndim != 4):
print("Error: data dimensions are invalid: {0} instead of 3.".format(
data.ndim))
return -1
# Transpose the data according to dim_order.
unordered_data = data
data = np.transpose(unordered_data, dim_order)
del (unordered_data)
# Check if arrows should be plotted.
if not (arrowsX is None) and not (arrowsY is None):
if (isinstance(arrowsX, np.ndarray)
and isinstance(arrowsY, np.ndarray)):
if arrowsX.ndim == 3:
# Transpose the data according to dim_order.
unordered_data = arrowsX
arrowsX = np.transpose(unordered_data, dim_order)
del (unordered_data)
if arrowsY.ndim == 3:
# Transpose the data according to dim_order.
unordered_data = arrowsY
arrowsY = np.transpose(unordered_data, dim_order)
unordered_data = []
# Check if the dimensions of the arrow arrays match each other.
if arrowsX.shape != arrowsY.shape:
print(
"Error: dimensions of arrowX do not match with dimensions of arrowY."
)
return -1
else:
plot_arrows = True
else:
print("Warning: arrowsX and/or arrowsY are of invalid type.")
# Check if time array has the right length.
n_times = len(t)
if n_times != data.shape[0]:
print(
"Error: length of time array does not match length of data array.")
return -1
if plot_arrows:
if (n_times != arrowsX.shape[0]) or (n_times != arrowsY.shape[0]):
print(
"error: length of time array does not match length of arrows array."
)
return -1
# Check if fps is positive.
if fps < 0:
print("Error: fps is not positive, fps = {0}.".format(fps))
return -1
# Determine the size of the data array.
nX = data.shape[1]
nY = data.shape[2]
# Determine the minimum and maximum values of the data set.
if not range_min:
range_min = np.min(data)
if not range_max:
range_max = np.max(data)
# Setup the plot.
if fancy:
plt.rc('text', usetex=True)
plt.rc('font', family='arial')
else:
plt.rc('text', usetex=False)
plt.rc('font', family='sans')
if not movie_file is None:
fig = plt.figure(figsize=figsize)
axes = plt.axes([0.15, 0.1, .70, .85])
else:
fig = plt.figure(figsize=figsize)
axes = plt.axes([0.1, 0.3, .80, .65])
# Set up canvas of the plot.
axes.set_title(title, fontsize=font_size)
axes.set_xlabel(xlabel, fontsize=font_size)
axes.set_ylabel(ylabel, fontsize=font_size)
plt.xticks(fontsize=0.5 * font_size)
plt.yticks(fontsize=0.5 * font_size)
if shade:
plane = np.zeros([nX, nY, 3])
else:
plane = np.zeros([nX, nY])
# Apply shading.
if shade:
from matplotlib.colors import LightSource
ls = LightSource(azdeg=azdeg, altdeg=altdeg)
rgb = []
# Shading can be only used with color_bar=1 or color_bar=2 at the moment.
if color_bar == 0:
color_bar = 1
# Check if colormap is set, if not set it to 'copper'.
if 'cmap' not in kwimshow.keys():
kwimshow['cmap'] = plt.cm.copper
for i in range(data.shape[0]):
tmp = ls.shade(data[i, :, :], kwimshow['cmap'])
rgb.append(tmp.tolist())
rgb = np.array(rgb)
del (tmp)
# Calibrate the displayed colors for the data range.
image = axes.imshow(plane,
vmin=range_min,
vmax=range_max,
origin='lower',
extent=extent,
**kwimshow)
colorbar = fig.colorbar(image)
colorbar.set_label(colorbar_label, fontsize=font_size, labelpad=10)
# Change the font size of the colorbar's ytickslabels.
cbytick_obj = plt.getp(colorbar.ax.axes, 'yticklabels')
plt.setp(cbytick_obj, fontsize=0.5 * font_size)
# Plot the arrows.
if plot_arrows:
# Prepare the mesh grid where the arrows will be drawn.
arrow_grid = np.meshgrid(
np.arange(
extent[0], extent[1],
float(extent[1] - extent[0]) * arrows_resX /
(data.shape[2] - 1)),
np.arange(
extent[2], extent[3],
float(extent[3] - extent[2]) * arrows_resY /
(data.shape[1] - 1)))
arrows = axes.quiver(arrow_grid[0],
arrow_grid[1],
arrowsX[0, ::arrows_resX, ::arrows_resY],
arrowsY[0, ::arrows_resX, ::arrows_resY],
units='width',
pivot=arrows_pivot,
width=arrows_width,
scale=arrows_scale,
color=arrows_color)
# Plot the grid for the arrows.
if plot_arrows_grid:
axes.plot(arrow_grid[0], arrow_grid[1], 'k.')
# For real-time image display.
if (not sloppy) or (not movie_file is None):
manager = plt.get_current_fig_manager()
manager.show()
time_step = 0
if not movie_file is None:
import os
movie_files = []
# Start the animation.
play('no_thread')
# Write the movie file.
ffmpeg_command = "ffmpeg -r {0} -i {1}%6d.png -vcodec mpeg4 -b:v {2} -q:v 0 {3}.avi".format(
fps, movie_file, bitrate, movie_file)
os.system(ffmpeg_command)
# Clean up the image files.
if not keep_images:
print("Cleaning up files.")
for fname in movie_files:
os.remove(fname)
else:
# Set up the gui.
plt.ion()
plt.subplots_adjust(bottom=0.2)
# axes_play = plt.axes([0.1, 0.05, 0.15, 0.05])
# button_play = plt.Button(axes_play, 'play', color='lightgoldenrodyellow',
# hovercolor='0.975')
# button_play.on_clicked(play_thread)
# axes_pause = plt.axes([0.3, 0.05, 0.15, 0.05])
# button_pause = plt.Button(axes_pause, 'pause', color='lightgoldenrodyellow',
# hovercolor='0.975')
# button_pause.on_clicked(pausing)
# axes_reverse = plt.axes([0.5, 0.05, 0.15, 0.05])
axes_reverse = plt.axes([0.1, 0.05, 0.3, 0.05])
button_reverse = plt.Button(axes_reverse,
'reverse',
color='lightgoldenrodyellow',
hovercolor='0.975')
button_reverse.on_clicked(reverse)
# axes_forward = plt.axes([0.7, 0.05, 0.15, 0.05])
axes_forward = plt.axes([0.5, 0.05, 0.3, 0.05])
button_forward = plt.Button(axes_forward,
'forward',
color='lightgoldenrodyellow',
hovercolor='0.975')
button_forward.on_clicked(forward)
# Create the time slider.
time_slider_axes = plt.axes([0.2, 0.12, 0.6, 0.03],
facecolor='lightgoldenrodyellow')
time_slider = plt.Slider(time_slider_axes,
'time',
t[0],
t[-1],
valinit=t[0])
def update(val):
global time_step
# Find the closest time step to the slider time value.
for i in range(len(t)):
if t[i] < time_slider.val:
time_step = i
if (time_step != len(t) - 1):
if (t[time_step + 1] - time_slider.val) < (time_slider.val -
t[time_step]):
time_step += 1
plot_frame()
time_slider.on_changed(update)
plt.show()
print("done")
# return button_play, button_pause, button_reverse, button_forward
return button_reverse, button_forward
def animate_interactive(data,
t=[],
dimOrder=(0, 1, 2),
fps=10.0,
title='',
xlabel='x',
ylabel='y',
fontsize=24,
cBar=0,
sloppy=True,
rangeMin=[],
rangeMax=[],
extent=[-1, 1, -1, 1],
shade=False,
azdeg=0,
altdeg=65,
arrowsX=np.array(0),
arrowsY=np.array(0),
arrowsRes=10,
arrowsPivot='mid',
arrowsWidth=0.002,
arrowsScale=5,
arrowsColor='black',
plotArrowsGrid=False,
movieFile='',
bitrate=1800,
keepImages=False,
figsize=(8, 7),
dpi=None,
**kwimshow):
"""
Assemble a 2D animation from a 3D array.
call signature::
animate_interactive(data, t = [], dimOrder = (0,1,2),
fps = 10.0, title = '', xlabel = 'x', ylabel = 'y',
fontsize = 24, cBar = 0, sloppy = True,
rangeMin = [], rangeMax = [], extent = [-1,1,-1,1],
shade = False, azdeg = 0, altdeg = 65,
arrowsX = np.array(0), arrowsY = np.array(0), arrowsRes = 10,
arrowsPivot = 'mid', arrowsWidth = 0.002, arrowsScale = 5,
arrowsColor = 'black', plotArrowsGrid = False,
movieFile = '', bitrate = 1800, keepImages = False,
figsize = (8, 7), dpi = None,
**kwimshow)
Assemble a 2D animation from a 3D array. *data* has to be a 3D array who's
time index has the same dimension as *t*. The time index of *data* as well
as its x and y indices can be changed via *dimOrder*.
Keyword arguments:
*dimOrder*: [ (i,j,k) ]
Ordering of the dimensions in the data array (t,x,y).
*fps*:
Frames per second of the animation.
*title*:
Title of the plot.
*xlabel*:
Label of the x-axis.
*ylabel*:
Label of the y-axis.
*fontsize*:
Font size of the title, x and y label.
The size of the x- and y-ticks is 0.7*fontsize and the colorbar ticks's
font size is 0.5*fontsize.
*cBar*: [ 0 | 1 | 2 ]
Determines how the colorbar changes:
(0 - no cahnge; 1 - keep extreme values constant; 2 - change extreme values).
*sloppy*: [ True | False ]
If True the update of the plot lags one frame behind. This speeds up the
plotting.
*rangeMin*, *rangeMax*:
Range of the colortable.
*extent*: [ None | scalars (left, right, bottom, top) ]
Data limits for the axes. The default assigns zero-based row,
column indices to the *x*, *y* centers of the pixels.
*shade*: [ False | True ]
If True plot a shaded relief plot instead of the usual colormap.
Note that with this option cmap has to be specified like
cmap = plt.cm.hot instead of cmap = 'hot'. Shading cannot
be used with the cBar = 0 option.
*azdeg*, *altdeg*:
Azimuth and altitude of the light source for the shading.
*arrowsX*:
Data containing the x-component of the arrows.
*arrowsy*:
Data containing the y-component of the arrows.
*arrowsRes*:
Plot every arrowRes arrow.
*arrowsPivot*: [ 'tail' | 'middle' | 'tip' ]
The part of the arrow that is at the grid point; the arrow rotates
about this point.
*arrowsWidth*:
Width of the arrows.
*arrowsScale*:
Scaling of the arrows.
*arrowsColor*:
Color of the arrows.
*plotArrowsGrid*: [ False | True ]
If 'True' the grid where the arrows are aligned to is shown.
*movieFile*: [ None | string ]
The movie file where the animation should be saved to.
If 'None' no movie file is written. Requires 'mencoder' to be installed.
*bitrate*:
Bitrate of the movie file. Set to higher value for higher quality.
*keepImages*: [ False | True ]
If 'True' the images for the movie creation are not deleted.
*figsize*:
Size of the figure in inches.
*dpi*:
Dots per inch of the frame.
**kwimshow:
Remaining arguments are identical to those of pylab.imshow. Refer to that help.
"""
global tStep, sliderTime, pause
# plot the current frame
def plotFrame():
global tStep, sliderTime
if movieFile:
ax.set_title(title + r'$\quad$' + r'$t={0}$'.format(t[tStep]),
fontsize=fontsize)
if shade == False:
image.set_data(data[tStep, :, :])
else:
image.set_data(rgb[tStep, :, :, :])
if (cBar == 0):
pass
if (cBar == 1):
colorbar.set_clim(vmin=data[tStep, :, :].min(),
vmax=data[tStep, :, :].max())
if (cBar == 2):
colorbar.set_clim(vmin=data[tStep, :, :].min(),
vmax=data[tStep, :, :].max())
colorbar.update_bruteforce(data[tStep, :, :])
if plotArrows:
arrows.set_UVC(U=arrowsX[tStep, ::arrowsRes, ::arrowsRes],
V=arrowsY[tStep, ::arrowsRes, ::arrowsRes])
if (sloppy == False) or (movieFile):
manager.canvas.draw()
# play the movie
def play(threadName):
global tStep, sliderTime, pause
pause = False
while (tStep < nT) & (pause == False):
# write the image files for the movie
if movieFile:
plotFrame()
frameName = movieFile + '%06d.png' % tStep
fig.savefig(frameName, dpi=dpi)
movieFiles.append(frameName)
else:
start = time.clock()
# time slider
sliderTime.set_val(t[tStep])
# wait for the next frame (fps)
while (time.clock() - start < 1.0 / fps):
pass # do nothing
tStep += 1
tStep -= 1
# call the play function as a separate thread (for GUI)
def play_thread(event):
global pause
if pause == True:
try:
thread.start_new_thread(play, ("playThread", ))
except:
print "Error: unable to start play thread"
def pausing(event):
global pause
pause = True
def reverse(event):
global tStep, sliderTime
tStep -= 1
if tStep < 0:
tStep = 0
# plot the frame and update the time slider
sliderTime.set_val(t[tStep])
def forward(event):
global tStep, sliderTime
tStep += 1
if tStep > len(t) - 1:
tStep = len(t) - 1
# plot the frame and update the time slider
sliderTime.set_val(t[tStep])
pause = True
plotArrows = False
# check if the data has the right dimensions
if (len(data.shape) != 3 and len(data.shape) != 4):
print 'error: data dimensions are invalid: {0} instead of 3'.format(
len(data.shape))
return -1
# transpose the data according to dimOrder
unOrdered = data
data = np.transpose(unOrdered, dimOrder)
unOrdered = []
# check if arrows should be plotted
if len(arrowsX.shape) == 3:
# transpose the data according to dimOrder
unOrdered = arrowsX
arrowsX = np.transpose(unOrdered, dimOrder)
unOrdered = []
if len(arrowsY.shape) == 3:
# transpose the data according to dimOrder
unOrdered = arrowsY
arrowsY = np.transpose(unOrdered, dimOrder)
unOrdered = []
# check if the dimensions of the arrow arrays match each other
if ((len(arrowsX[:, 0, 0]) != len(arrowsY[:, 0, 0]))
or (len(arrowsX[0, :, 0]) != len(arrowsY[0, :, 0]))
or (len(arrowsX[0, 0, :]) != len(arrowsY[0, 0, :]))):
print 'error: dimensions of arrowX do not match with dimensions of arrowY'
return -1
else:
plotArrows = True
# check if time array has the right length
nT = len(t)
if (nT != len(data[:, 0, 0])):
print 'error: length of time array doesn\'t match length of data array'
return -1
if plotArrows:
if (nT != len(arrowX[:, 0, 0]) or nT != len(arrowX[:, 0, 0])):
print 'error: length of time array doesn\'t match length of arrows array'
return -1
# check if fps is positive
if (fps < 0.0):
print 'error: fps is not positive, fps = {0}'.format(fps)
return -1
# determine the size of the array
nX = len(data[0, :, 0])
nY = len(data[0, 0, :])
# determine the minimum and maximum values of the data set
if not (rangeMin):
rangeMin = np.min(data)
if not (rangeMax):
rangeMax = np.max(data)
# setup the plot
if movieFile:
width = figsize[0]
height = figsize[1]
plt.rc("figure.subplot", bottom=0.15)
plt.rc("figure.subplot", top=0.95)
plt.rc("figure.subplot", right=0.95)
plt.rc("figure.subplot", left=0.15)
fig = plt.figure(figsize=figsize)
ax = plt.axes([0.1, 0.1, .90, .85])
else:
width = figsize[0]
height = figsize[1]
plt.rc("figure.subplot", bottom=0.05)
plt.rc("figure.subplot", top=0.95)
plt.rc("figure.subplot", right=0.95)
plt.rc("figure.subplot", left=0.15)
fig = plt.figure(figsize=figsize)
ax = plt.axes([0.1, 0.25, .85, .70])
ax.set_title(title, fontsize=fontsize)
ax.set_xlabel(xlabel, fontsize=fontsize)
ax.set_ylabel(ylabel, fontsize=fontsize)
plt.xticks(fontsize=0.7 * fontsize)
plt.yticks(fontsize=0.7 * fontsize)
if shade:
plane = np.zeros((nX, nY, 3))
else:
plane = np.zeros((nX, nY))
# apply shading if True
if shade:
ls = LightSource(azdeg=azdeg, altdeg=altdeg)
rgb = []
# shading can be only used with cBar = 1 or cBar = 2 at the moment
if cBar == 0:
cBar = 1
# check if colormap is set, if not set it to 'copper'
if kwimshow.has_key('cmap') == False:
kwimshow['cmap'] = plt.cm.copper
for i in range(len(data[:, 0, 0])):
tmp = ls.shade(data[i, :, :], kwimshow['cmap'])
rgb.append(tmp.tolist())
rgb = np.array(rgb)
tmp = []
# calibrate the displayed colors for the data range
image = ax.imshow(plane,
vmin=rangeMin,
vmax=rangeMax,
origin='lower',
extent=extent,
**kwimshow)
colorbar = fig.colorbar(image)
# change the font size of the colorbar's ytickslabels
cbytick_obj = plt.getp(colorbar.ax.axes, 'yticklabels')
plt.setp(cbytick_obj, fontsize=0.5 * fontsize)
# plot the arrows
# TODO: add some more options
if plotArrows:
# prepare the mash grid where the arrows will be drawn
arrowGridX, arrowGridY = np.meshgrid(
np.arange(
extent[0], extent[1],
float(extent[1] - extent[0]) * arrowsRes / len(data[0, :, 0])),
np.arange(
extent[2], extent[3],
float(extent[3] - extent[2]) * arrowsRes / len(data[0, 0, :])))
arrows = ax.quiver(arrowGridX,
arrowGridY,
arrowsX[0, ::arrowsRes, ::arrowsRes],
arrowsY[0, ::arrowsRes, ::arrowsRes],
units='width',
pivot=arrowsPivot,
width=arrowsWidth,
scale=arrowsScale,
color=arrowsColor)
# plot the grid for the arrows
if plotArrowsGrid == True:
ax.plot(arrowGridX, arrowGridY, 'k.')
# for real-time image display
if (sloppy == False) or (movieFile):
manager = plt.get_current_fig_manager()
manager.show()
tStep = 0
if movieFile:
movieFiles = []
# start the animation
play('noThread')
# write the movie file
mencodeCommand = "mencoder 'mf://" + movieFile + "*.png' -mf type=png:fps=" + np.str(
fps) + " -ovc lavc -lavcopts vcodec=mpeg4:vhq:vbitrate=" + np.str(
bitrate) + " -ffourcc MP4S -oac copy -o " + movieFile + ".mpg"
os.system(mencodeCommand)
# clean up the image files
if (keepImages == False):
print 'cleaning up files'
for fname in movieFiles:
os.remove(fname)
else:
# set up the gui
plt.ion()
axPlay = plt.axes([0.1, 0.05, 0.15, 0.05],
axisbg='lightgoldenrodyellow')
buttonPlay = plt.Button(axPlay,
'play',
color='lightgoldenrodyellow',
hovercolor='0.975')
buttonPlay.on_clicked(play_thread)
axPause = plt.axes([0.3, 0.05, 0.15, 0.05],
axisbg='lightgoldenrodyellow')
buttonPause = plt.Button(axPause,
'pause',
color='lightgoldenrodyellow',
hovercolor='0.975')
buttonPause.on_clicked(pausing)
axReverse = plt.axes([0.5, 0.05, 0.15, 0.05],
axisbg='lightgoldenrodyellow')
buttonReverse = plt.Button(axReverse,
'reverse',
color='lightgoldenrodyellow',
hovercolor='0.975')
buttonReverse.on_clicked(reverse)
axForward = plt.axes([0.7, 0.05, 0.15, 0.05],
axisbg='lightgoldenrodyellow')
buttonForward = plt.Button(axForward,
'forward',
color='lightgoldenrodyellow',
hovercolor='0.975')
buttonForward.on_clicked(forward)
# create the time slider
fig.subplots_adjust(bottom=0.2)
sliderTimeAxes = plt.axes([0.2, 0.12, 0.6, 0.03],
axisbg='lightgoldenrodyellow')
sliderTime = plt.Slider(sliderTimeAxes,
'time',
t[0],
t[-1],
valinit=0.0)
def update(val):
global tStep
# find the closest time step to the slider time value
for i in range(len(t)):
if t[i] < sliderTime.val:
tStep = i
if (tStep != len(t) - 1):
if (t[tStep + 1] - sliderTime.val) < (sliderTime.val -
t[tStep]):
tStep += 1
plotFrame()
sliderTime.on_changed(update)
plt.show()
print 'done'
def displayResults2(self):
""" show results with time slider
geneNames have to be unique!
"""
##
## import pylab
#### from matplotlib.widgets import Slider
## mi=1
## ma=self.results.shape[1]
## print(ma)# should be 101
##
## figure=pylab.figure()
##
## ax=pylab.Axes(figure,[0.15, 0.1, 0.65, 0.03])
## slider=pylab.Slider(ax=ax,label='time slider',valmin=mi,valmax=ma,valinit=1)
##
## def update():
## pylab.plot(self.results[:,slider.val,:])
## pylab.draw()
##
## slider.on_changed(update)
## pylab.show()
import pylab
import scipy
from matplotlib.widgets import Slider, Button, RadioButtons, CheckButtons
## test = pylab.plot(self.results[:,-1,:])
## pylab.show()
# results is a data cube [cell, time, gene]
miTime = 0
maTime = self.results.shape[1] - 1
## xdata=range(self.results.shape[0])
##ax = pylab.subplot(111)
pylab.subplots_adjust(left=0.25, bottom=0.25)
## t = scipy.arange(0.0, 1.0, 0.001)
## a0 = 5
## f0 = 3
## s = a0*scipy.sin(2*scipy.pi*f0*t)
## plot, = pylab.plot(t,s, lw=2, color='red')
selection = scipy.ones(len(self.geneNames)).astype(
bool) # select all on start
plots = pylab.plot(self.results[:, maTime, :]
) # apperently returns a plot for each line...
## pylab.axis([0, 1, -10, 10])
axcolor = 'lightgoldenrodyellow'
## axfreq = pylab.axes([0.25, 0.1, 0.65, 0.03], axisbg=axcolor)
## axamp = pylab.axes([0.25, 0.15, 0.65, 0.03], axisbg=axcolor)
## sfreq = Slider(axfreq, 'Freq', 0.1, 30.0, valinit=f0)
## samp = Slider(axamp, 'Amp', 0.1, 10.0, valinit=a0)
ax = pylab.axes([0.15, 0.1, 0.65, 0.03])
slider = pylab.Slider(ax=ax,
label='time slider',
valmin=miTime,
valmax=maTime,
valinit=maTime)
def update(val):
## amp = samp.val
## freq = sfreq.val
## l.set_ydata(amp*scipy.sin(2*scipy.pi*freq*t))
for i in range(len(plots)):
plots[i].set_ydata(self.results[:, slider.val, i])
plots[i].set_visible(selection[i])
pylab.draw()
## sfreq.on_changed(update)
## samp.on_changed(update)
slider.on_changed(update)
resetax = pylab.axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
def reset(event):
## sfreq.reset()
## samp.reset()
slider.reset()
button.on_clicked(reset)
rax = pylab.axes([0.025, 0.5, 0.15, 0.15], axisbg=axcolor)
checker = CheckButtons(rax, self.geneNames, actives=selection)
def selector(val):
## print(val)
## print(scipy.array(range(len(self.geneNames)))[self.geneNames==val][0])
geneNr = scipy.array(
range(len(self.geneNames))
)[self.geneNames == val][
0] # its retarded to check label names... but that is the way they like it....
selection[geneNr] = not (selection[geneNr])
update(slider.val)
checker.on_clicked(selector)
## print(checker.eventson)
## print(checker.drawon)
## radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)
##
## rax = pylab.axes([0.025, 0.5, 0.15, 0.15], axisbg=axcolor)
## radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)
## def colorfunc(label):
## for i in range(len(plots)):
## plots[i].set_color(label)
#### plots.set_color(label)
## pylab.draw()
## radio.on_clicked(colorfunc)
pylab.show()
def plot_3d_array(data,
axis=0,
title='3d',
cmap='gray',
interpolation='nearest',
vmin=None,
vmax=None,
**kwargs):
'''
plots 3d data with a slider to change the third dimension
unfortunately the number that the slider shows is rounded weirdly.. be careful!
TODO: fix that!
input:
- data: 3d numpy array containing the data
- axis: axis that should be changeable by the slider
author: Mathias Marschner
added: 30.10.2013
'''
fig = plt.figure()
ax = fig.add_subplot(111)
plt.title(title)
if vmin == None:
vmin = data.min()
if vmax == None:
vmax = data.max()
if axis == 0:
cax = ax.imshow(data[data.shape[0] / 2, :, :],
cmap=cmap,
vmin=vmin,
vmax=vmax,
interpolation=interpolation,
**kwargs)
elif axis == 1:
cax = ax.imshow(data[:, data.shape[1] / 2, :],
cmap=cmap,
vmin=vmin,
vmax=vmax,
interpolation=interpolation,
**kwargs)
elif axis == 2:
cax = ax.imshow(data[:, :, data.shape[2] / 2],
cmap=cmap,
vmin=vmin,
vmax=vmax,
interpolation=interpolation,
**kwargs)
cbar = fig.colorbar(cax)
axcolor = 'lightgoldenrodyellow'
ax4 = pylab.axes([0.1, 0.01, 0.8, 0.03], axisbg=axcolor)
sframe = pylab.Slider(ax4,
'',
0,
data.shape[axis] - 1,
valinit=data.shape[axis] / 2,
closedmin=True,
closedmax=True,
valfmt='%d')
def update(val):
frame = np.around(np.clip(sframe.val, 0, data.shape[axis] - 1))
if axis == 0:
cax.set_data(data[frame, :, :])
elif axis == 1:
cax.set_data(data[:, frame, :])
elif axis == 2:
cax.set_data(data[:, :, frame])
sframe.on_changed(update)
return ax
