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• How do you compare two strings and ignore the case in Scheme?

  - by kunjaan

  I want to write a function like equalp, which gives #t for (equalp "Xy" "xY").

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• Extra line breaks inserted in MrEd text%

  - by Jesse Millikan

  In a DrScheme project, I'm using a MrEd editor-canvas% with text% and inserting a string from a literal in a Scheme file. This results in an extra blank line in the editor for each line of text I'm trying to insert. Is this a Windows vs. Unix linebreak problem? I can't find anything about text% treats line breaks in the documentation. ; Inside a class definition: (define/public (edit-pattern p j b d h) (send input-beat set-value (number->string b)) (send input-dwell set-value (number->string d)) (send hold-beats set-value (number->string h)) (send juggler-t erase) ; Why do these add extra newlines (send juggler-t insert j) (send pattern-t erase) (send pattern-t insert p)) (define juggler-ec (new editor-canvas% [parent this] [line-count 12])) (define juggler-t (new text%)) (send juggler-ec set-editor juggler-t) (define pattern-ec (new editor-canvas% [parent this] [line-count 20])) (define pattern-t (new text%)) (send pattern-ec set-editor pattern-t) ; Lots of other stuff...

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• async handler deleted by the wrong thread in django

  - by user3480706

  I'm run this algorithm in my django application.when i run several time from my GUI django local server will stopped and i got this error Exception RuntimeError: RuntimeError('main thread is not in main loop',) in ignored Tcl_AsyncDelete: async handler deleted by the wrong thread Aborted (core dumped) code print "Learning the sin function" network =MLP.MLP(2,10,1) samples = np.zeros(2000, dtype=[('x', float, 1), ('y', float, 1)]) samples['x'] = np.linspace(-5,5,2000) samples['y'] = np.sin(samples['x']) #samples['y'] = np.linspace(-4,4,2500) for i in range(100000): n = np.random.randint(samples.size) network.propagate_forward(samples['x'][n]) network.propagate_backward(samples['y'][n]) plt.figure(figsize=(10,5)) # Draw real function x = samples['x'] y = samples['y'] #x=np.linspace(-6.0,7.0,50) plt.plot(x,y,color='b',lw=1) samples1 = np.zeros(2000, dtype=[('x1', float, 1), ('y1', float, 1)]) samples1['x1'] = np.linspace(-4,4,2000) samples1['y1'] = np.sin(samples1['x1']) # Draw network approximated function for i in range(samples1.size): samples1['y1'][i] = network.propagate_forward(samples1['x1'][i]) plt.plot(samples1['x1'],samples1['y1'],color='r',lw=3) plt.axis([-2,2,-2,2]) plt.show() plt.close() return HttpResponseRedirect('/charts/charts') how can i fix this error ?need a quick help

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• python how to put data on y-axis when plotting histogram

  - by user3041107

  I don't quite understand how to control y - axis when using plt.hist plot in python. I read my .txt data file - it contains 10 columns with various data. If I want to plot distribution of strain on x axis I take column n.5. But what kind of value appears on y axis ??? Don't understand that. here is the code: import numpy import matplotlib.pyplot as plt from pylab import * from scipy.stats import norm import sys strain = [] infile = sys.argv[1] for line in infile: ret = numpy.loadtxt(infile) strain += list(ret[:,5]) fig = plt.figure() plt.hist(strain, bins = 20) plt.show() Thanks for help!

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• Unable to plot graph using matplotlib

  - by Aman Deep Gautam

  I have the following code which searches all the directory in the current directory and then takes data from those files to plot the graph. The data is read correctly as verified by printing but there are no points plotted on graph. import argparse import os import matplotlib.pyplot as plt #find the present working directory pwd=os.path.dirname(os.path.abspath(__file__)) #find all the folders in the present working directory. dirs = [f for f in os.listdir('.') if os.path.isdir(f)] plt.figure() plt.xlim(0, 20000) plt.ylim(0, 1) for directory in dirs: os.chdir(os.path.join(pwd, directory)); chd_dir = os.path.dirname(os.path.abspath(__file__)) files = [ fl for fl in os.listdir('.') if os.path.isfile(fl) ] print files for f in files: f_obj = open(os.path.join(chd_dir, f), 'r') list_x = [] list_y = [] for i in xrange(0,4): f_obj.next() for line in f_obj: temp_list = line.split() print temp_list list_y.append(temp_list[0]) list_x.append(temp_list[1]) print 'final_lsit' print list_x print list_y plt.plot(list_x, list_y, 'r.') f_obj.close() os.chdir(pwd) plt.savefig("test.jpg") The input files look like the following: 5 865 14709 15573 14709 1.32667e-06 664 0.815601 14719 1.55333e-06 674 0.813277 14729 1.82667e-06 684 0.810185 14739 1.4e-06 694 0.808459 Can anybody help me with why this is happening? Being new I would like to know some tutorial where I can get help with kind of plotting as the tutorial I was following made me end up here. Any help appreciated.

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• Why do I get rows of zeros in my 2D fft?

  - by Nicholas Pringle

  I am trying to replicate the results from a paper. "Two-dimensional Fourier Transform (2D-FT) in space and time along sections of constant latitude (east-west) and longitude (north-south) were used to characterize the spectrum of the simulated flux variability south of 40degS." - Lenton et al(2006) The figures published show "the log of the variance of the 2D-FT". I have tried to create an array consisting of the seasonal cycle of similar data as well as the noise. I have defined the noise as the original array minus the signal array. Here is the code that I used to plot the 2D-FT of the signal array averaged in latitude: import numpy as np from numpy import ma from matplotlib import pyplot as plt from Scientific.IO.NetCDF import NetCDFFile ### input directory indir = '/home/nicholas/data/' ### get the flux data which is in ### [time(5day ave for 10 years),latitude,longitude] nc = NetCDFFile(indir + 'CFLX_2000_2009.nc','r') cflux_southern_ocean = nc.variables['Cflx'][:,10:50,:] cflux_southern_ocean = ma.masked_values(cflux_southern_ocean,1e+20) # mask land nc.close() cflux = cflux_southern_ocean*1e08 # change units of data from mmol/m^2/s ### create an array that consists of the seasonal signal fro each pixel year_stack = np.split(cflux, 10, axis=0) year_stack = np.array(year_stack) signal_array = np.tile(np.mean(year_stack, axis=0), (10, 1, 1)) signal_array = ma.masked_where(signal_array > 1e20, signal_array) # need to mask ### average the array over latitude(or longitude) signal_time_lon = ma.mean(signal_array, axis=1) ### do a 2D Fourier Transform of the time/space image ft = np.fft.fft2(signal_time_lon) mgft = np.abs(ft) ps = mgft**2 log_ps = np.log(mgft) log_mgft= np.log(mgft) Every second row of the ft consists completely of zeros. Why is this? Would it be acceptable to add a randomly small number to the signal to avoid this. signal_time_lon = signal_time_lon + np.random.randint(0,9,size=(730, 182))*1e-05 EDIT: Adding images and clarify meaning The output of rfft2 still appears to be a complex array. Using fftshift shifts the edges of the image to the centre; I still have a power spectrum regardless. I expect that the reason that I get rows of zeros is that I have re-created the timeseries for each pixel. The ft[0, 0] pixel contains the mean of the signal. So the ft[1, 0] corresponds to a sinusoid with one cycle over the entire signal in the rows of the starting image. Here are is the starting image using following code: plt.pcolormesh(signal_time_lon); plt.colorbar(); plt.axis('tight') Here is result using following code: ft = np.fft.rfft2(signal_time_lon) mgft = np.abs(ft) ps = mgft**2 log_ps = np.log1p(mgft) plt.pcolormesh(log_ps); plt.colorbar(); plt.axis('tight') It may not be clear in the image but it is only every second row that contains completely zeros. Every tenth pixel (log_ps[10, 0]) is a high value. The other pixels (log_ps[2, 0], log_ps[4, 0] etc) have very low values.

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• Creating a Colormap Legend in Matplotlib

  - by Vince

  Hi fellow Stackers! I am using imshow() in matplotlib like so: import numpy as np import matplotlib.pyplot as plt mat = '''SOME MATRIX''' plt.imshow(mat, origin="lower", cmap='gray', interpolation='nearest') plt.show() How do I add a legend showing the numeric value for the different shades of gray. Sadly, my googling has not uncovered an answer :( Thank you in advance for the help. Vince

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• Pyplot connect to timer event?

  - by Baron Yugovich

  The same way I now have plt.connect('button_press_event', self.on_click) I would like to have something like plt.connect('each_five_seconds_event', self.on_timer) How can I achieve this in a way that's most similar to what I've shown above? EDIT: I tried fig = plt.subplot2grid((num_cols, num_rows), (col, row), rowspan=rowspan, colspan=colspan) timer = fig.canvas.new_timer(interval=100, callbacks=[(self.on_click)]) timer.start() And got AttributeError: 'AxesSubplot' object has no attribute 'canvas'

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• pyplot: really slow creating heatmaps

  - by cvondrick

  I have a loop that executes the body about 200 times. In each loop iteration, it does a sophisticated calculation, and then as debugging, I wish to produce a heatmap of a NxM matrix. But, generating this heatmap is unbearably slow and significantly slow downs an already slow algorithm. My code is along the lines: import numpy import matplotlib.pyplot as plt for i in range(200): matrix = complex_calculation() plt.set_cmap("gray") plt.imshow(matrix) plt.savefig("frame{0}.png".format(i)) The matrix, from numpy, is not huge --- 300 x 600 of doubles. Even if I do not save the figure and instead update an on-screen plot, it's even slower. Surely I must be abusing pyplot. (Matlab can do this, no problem.) How do I speed this up?

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• Putting newline in matplotlib label with TeX in Python?

  - by user248237

  How can I add a newline to a plot's label (e.g. xlabel or ylabel) in Matplotlib? For example, plt.bar([1, 2], [4, 5]) plt.xlabel("My x label") plt.ylabel(r"My long label with $\Sigma_{C}$ math \n continues here") Ideally i'd like the y-labeled to be centered too. Is there a way to do this? It's important that the label have both tex (enclosed in '$') and the newline. thanks.

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• matplotlib and python multithread file processing

  - by Napseis

  I have a large number of files to process. I have written a script that get, sort and plot the datas I want. So far, so good. I have tested it and it gives the desired result. Then I wanted to do this using multithreading. I have looked into the doc and examples on the internet, and using one thread in my program works fine. But when I use more, at some point I get random matplotlib error, and I suspect some conflict there, even though I use a function with names for the plots, and iI can't see where the problem could be. Here is the whole script should you need more comment, i'll add them. Thank you. #!/usr/bin/python import matplotlib matplotlib.use('GTKAgg') import numpy as np from scipy.interpolate import griddata import matplotlib.pyplot as plt import matplotlib.colors as mcl from matplotlib import rc #for latex import time as tm import sys import threading import Queue #queue in 3.2 and Queue in 2.7 ! import pdb #the debugger rc('text', usetex=True)#for latex map=0 #initialize the map index. It will be use to index the array like this: array[map,[x,y]] time=np.zeros(1) #an array to store the time middle_h=np.zeros((0,3)) #x phi c #for the middle of the box current_file=open("single_void_cyl_periodic_phi_c_middle_h_out",'r') for line in current_file: if line.startswith('# === time'): map+=1 np.append(time,[float(line.strip('# === time '))]) elif line.startswith('#'): pass else: v=np.fromstring(line,dtype=float,sep=' ') middle_h=np.vstack( (middle_h,v[[1,3,4]]) ) current_file.close() middle_h=middle_h.reshape((map,-1,3)) #3d array: map, x, phi,c ##### def load_and_plot(): #will load a map file, and plot it along with the corresponding profile loaded before while not exit_flag: print("fecthing work ...") #try: if not tasks_queue.empty(): map_index=tasks_queue.get() print("----> working on map: %s" %map_index) x,y,zp=np.loadtxt("single_void_cyl_growth_periodic_post_map_"+str(map_index),unpack=True, usecols=[1, 2,3]) for i,el in enumerate(zp): if el<0.: zp[i]=0. xv=np.unique(x) yv=np.unique(y) X,Y= np.meshgrid(xv,yv) Z = griddata((x, y), zp, (X, Y),method='nearest') figure=plt.figure(num=map_index,figsize=(14, 8)) ax1=plt.subplot2grid((2,2),(0,0)) ax1.plot(middle_h[map_index,:,0],middle_h[map_index,:,1],'*b') ax1.grid(True) ax1.axis([-15, 15, 0, 1]) ax1.set_title('Profiles') ax1.set_ylabel(r'$\phi$') ax1.set_xlabel('x') ax2=plt.subplot2grid((2,2),(1,0)) ax2.plot(middle_h[map_index,:,0],middle_h[map_index,:,2],'*r') ax2.grid(True) ax2.axis([-15, 15, 0, 1]) ax2.set_ylabel('c') ax2.set_xlabel('x') ax3=plt.subplot2grid((2,2),(0,1),rowspan=2,aspect='equal') sub_contour=ax3.contourf(X,Y,Z,np.linspace(0,1,11),vmin=0.) figure.colorbar(sub_contour,ax=ax3) figure.savefig('single_void_cyl_'+str(map_index)+'.png') plt.close(map_index) tasks_queue.task_done() else: print("nothing left to do, other threads finishing,sleeping 2 seconds...") tm.sleep(2) # except: # print("failed this time: %s" %map_index+". Sleeping 2 seconds") # tm.sleep(2) ##### exit_flag=0 nb_threads=2 tasks_queue=Queue.Queue() threads_list=[] jobs=list(range(map)) #each job is composed of a map print("inserting jobs in the queue...") for job in jobs: tasks_queue.put(job) print("done") #launch the threads for i in range(nb_threads): working_bee=threading.Thread(target=load_and_plot) working_bee.daemon=True print("starting thread "+str(i)+' ...') threads_list.append(working_bee) working_bee.start() #wait for all tasks to be treated tasks_queue.join() #flip the flag, so the threads know it's time to stop exit_flag=1 for t in threads_list: print("waiting for threads %s to stop..."%t) t.join() print("all threads stopped")

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• How to draw line inside a scatter plot

  - by ruffy

  I can't believe that this is so complicated but I tried and googled for a while now. I just want to analyse my scatter plot with a few graphical features. For starters, I want to add simply a line. So, I have a few (4) points and like in this plot [1] I want to add a line to it. http://en.wikipedia.org/wiki/File:ROC_space-2.png [1] Now, this won't work. And frankly, the documentation-examples-gallery combo and content of matplotlib is a bad source for information. My code is based upon a simple scatter plot from the gallery: # definitions for the axes left, width = 0.1, 0.85 #0.65 bottom, height = 0.1, 0.85 #0.65 bottom_h = left_h = left+width+0.02 rect_scatter = [left, bottom, width, height] # start with a rectangular Figure fig = plt.figure(1, figsize=(8,8)) axScatter = plt.axes(rect_scatter) # the scatter plot: p1 = axScatter.scatter(x[0], y[0], c='blue', s = 70) p2 = axScatter.scatter(x[1], y[1], c='green', s = 70) p3 = axScatter.scatter(x[2], y[2], c='red', s = 70) p4 = axScatter.scatter(x[3], y[3], c='yellow', s = 70) p5 = axScatter.plot([1,2,3], "r--") plt.legend([p1, p2, p3, p4, p5], [names[0], names[1], names[2], names[3], "Random guess"], loc = 2) # now determine nice limits by hand: binwidth = 0.25 xymax = np.max( [np.max(np.fabs(x)), np.max(np.fabs(y))] ) lim = ( int(xymax/binwidth) + 1) * binwidth axScatter.set_xlim( (-lim, lim) ) axScatter.set_ylim( (-lim, lim) ) xText = axScatter.set_xlabel('FPR / Specificity') yText = axScatter.set_ylabel('TPR / Sensitivity') bins = np.arange(-lim, lim + binwidth, binwidth) plt.show() Everything works, except the p5 which is a line. Now how is this supposed to work? What's good practice here?

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• Python Least-Squares Natural Splines

  - by Eldila

  I am trying to find a numerical package which will fit a natural which minimizes weighted least squares. There is a package in scipy which does what I want for unnatural splines. import numpy as np import matplotlib.pyplot as plt from scipy import interpolate import random x = np.arange(0,5,1.0/2) xs = np.arange(0,5,1.0/500) y = np.sin(x+1) for i in range(len(y)): y[i] += .2*random.random() - .1 knots = np.array([1,2,3,4]) tck = interpolate.splrep(x,y,s=1,k=3,t=knots,task=-1) ynew = interpolate.splev(xs,tck,der=0) plt.figure() plt.plot(xs,ynew,x,y,'x')

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• Confusion Matrix with number of classified/misclassified instances on it (Python/Matplotlib)

  - by Pinkie

  I am plotting a confusion matrix with matplotlib with the following code: from numpy import * import matplotlib.pyplot as plt from pylab import * conf_arr = [[33,2,0,0,0,0,0,0,0,1,3], [3,31,0,0,0,0,0,0,0,0,0], [0,4,41,0,0,0,0,0,0,0,1], [0,1,0,30,0,6,0,0,0,0,1], [0,0,0,0,38,10,0,0,0,0,0], [0,0,0,3,1,39,0,0,0,0,4], [0,2,2,0,4,1,31,0,0,0,2], [0,1,0,0,0,0,0,36,0,2,0], [0,0,0,0,0,0,1,5,37,5,1], [3,0,0,0,0,0,0,0,0,39,0], [0,0,0,0,0,0,0,0,0,0,38] ] norm_conf = [] for i in conf_arr: a = 0 tmp_arr = [] a = sum(i,0) for j in i: tmp_arr.append(float(j)/float(a)) norm_conf.append(tmp_arr) plt.clf() fig = plt.figure() ax = fig.add_subplot(111) res = ax.imshow(array(norm_conf), cmap=cm.jet, interpolation='nearest') cb = fig.colorbar(res) savefig("confmat.png", format="png") But I want to the confusion matrix to show the numbers on it like this graphic (the right one): http://i48.tinypic.com/2e30kup.jpg How can I plot the conf_arr on the graphic?

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• Plot smooth line with PyPlot

  - by Paul

  I've got the following simple script that plots a graph: import matplotlib.pyplot as plt import numpy as np T = np.array([6, 7, 8, 9, 10, 11, 12]) power = np.array([1.53E+03, 5.92E+02, 2.04E+02, 7.24E+01, 2.72E+01, 1.10E+01, 4.70E+00]) plt.plot(T,power) plt.show() As it is now, the line goes straight from point to point which looks ok, but could be better in my opinion. What I want is to smooth the line between the points. In Gnuplot I would have plotted with smooth cplines. Is there an easy way to do this in PyPlot? I've found some tutorials, but they all seem rather complex.

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• matplotlib.pyplot, preserve aspect ratio of the plot

  - by Headcrab

  Assuming we have a polygon coordinates as polygon = [(x1, y1), (x2, y2), ...], the following code displays the polygon: import matplotlib.pyplot as plt plt.fill(*zip(*polygon)) plt.show() By default it is trying to adjust the aspect ratio so that the polygon (or whatever other diagram) fits inside the window, and automatically changing it so that it fits even after resizing. Which is great in many cases, except when you are trying to estimate visually if the image is distorted. How to fix the aspect ratio to be strictly 1:1? (Not sure if "aspect ratio" is the right term here, so in case it is not - I need both X and Y axes to have 1:1 scale, so that (0, 1) on both X and Y takes an exact same amount of screen space. And I need to keep it 1:1 no matter how I resize the window.)

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• Plotting 3D Polygons in python-matplotlib

  - by Developer

  I was unsuccessful browsing web for a solution for the following simple question: How to draw 3D polygon (say a filled rectangle or triangle) using vertices values? I have tried many ideas but all failed, see: from mpl_toolkits.mplot3d import Axes3D from matplotlib.collections import PolyCollection import matplotlib.pyplot as plt fig = plt.figure() ax = Axes3D(fig) x = [0,1,1,0] y = [0,0,1,1] z = [0,1,0,1] verts = [zip(x, y,z)] ax.add_collection3d(PolyCollection(verts),zs=z) plt.show() I appreciate in advance any idea/comment. Updates based on the accepted answer: import mpl_toolkits.mplot3d as a3 import matplotlib.colors as colors import pylab as pl import scipy as sp ax = a3.Axes3D(pl.figure()) for i in range(10000): vtx = sp.rand(3,3) tri = a3.art3d.Poly3DCollection([vtx]) tri.set_color(colors.rgb2hex(sp.rand(3))) tri.set_edgecolor('k') ax.add_collection3d(tri) pl.show() Here is the result:

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• Python. Draw rectangle in basemap

  - by user2928318

  I need to add several rectangles in my basemap. I nee four rectangles with lat and log ranges as below. 1) llcrnrlon=-10, urcrnrlon=10, llcrnrlat=35,urcrnrlat=60 2) llcrnrlon=10.5, urcrnrlon=35, llcrnrlat=35,urcrnrlat=60 3) llcrnrlon=35.5, urcrnrlon=52, llcrnrlat=30,urcrnrlat=55 4) llcrnrlon=-20, urcrnrlon=35, llcrnrlat=20,urcrnrlat=34.5 My script is below. I found "polygon" packages to add lines but I do not exactly know how to do. Please help me!! Thanks a lot for your help in advance! from mpl_toolkits.basemap import Basemap m=basemaputpart.Basemap(llcrnrlon=-60, llcrnrlat=20, urcrnrlon=60, urcrnrlat=70, resolution='i', projection='cyl', lon_0=0, lat_0=45) lon1=np.array([[-180.+j*0.5 for j in range(721)] for i in range(181)]) lat1=np.array([[i*0.5 for j in range(721)] for i in range(181) ]) Nx1,Ny1=m(lon1,lat1,inverse=False) toplot=data[:,:] toplot[data==0]=np.nan toplot=np.ma.masked_invalid(toplot) plt.pcolor(Nx1,Ny1,np.log(toplot),vmin=0, vmax=5) cbar=plt.colorbar() m.drawcoastlines(zorder=2) m.drawcountries(zorder=2) plt.show()

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• How to sort a boxplot by the median values in pandas

  - by Chris

  I've got a dataframe outcome2 that I generate a grouped boxplot with in the following manner: In [11]: outcome2.boxplot(column='Hospital 30-Day Death (Mortality) Rates from Heart Attack',by='State') plt.ylabel('30 Day Death Rate') plt.title('30 Day Death Rate by State') Out [11]: What I'd like to do is sort the plot by the median for each state, instead of alphabetically. Not sure how to go about doing so.

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• Matplotlib pick event order for overlapping artists

  - by Ajean

  I'm hitting a very strange issue with matplotlib pick events. I have two artists that are both pickable and are non-overlapping to begin with ("holes" and "pegs"). When I pick one of them, during the event handling I move the other one to where I just clicked (moving a "peg" into the "hole"). Then, without doing anything else, a pick event from the moved artist (the peg) is generated even though it wasn't there when the first event was generated. My only explanation for it is that somehow the event manager is still moving through artist layers when the event is processed, and therefore hits the second artist after it is moved under the cursor. So then my question is - how do pick events (or any events for that matter) iterate through overlapping artists on the canvas, and is there a way to control it? I think I would get my desired behavior if it moved from the top down always (rather than bottom up or randomly). I haven't been able to find sufficient enough documentation, and a lengthy search on SO has not revealed this exact issue. Below is a working example that illustrates the problem, with PathCollections from scatter as pegs and holes: import matplotlib.pyplot as plt import sys class peg_tester(): def __init__(self): self.fig = plt.figure(figsize=(3,1)) self.ax = self.fig.add_axes([0,0,1,1]) self.ax.set_xlim([-0.5,2.5]) self.ax.set_ylim([-0.25,0.25]) self.ax.text(-0.4, 0.15, 'One click on the hole, and I get 2 events not 1', fontsize=8) self.holes = self.ax.scatter([1], [0], color='black', picker=0) self.pegs = self.ax.scatter([0], [0], s=100, facecolor='#dd8800', edgecolor='black', picker=0) self.fig.canvas.mpl_connect('pick_event', self.handler) plt.show() def handler(self, event): if event.artist is self.holes: # If I get a hole event, then move a peg (to that hole) ... # but then I get a peg event also with no extra clicks! offs = self.pegs.get_offsets() offs[0,:] = [1,0] # Moves left peg to the middle self.pegs.set_offsets(offs) self.fig.canvas.draw() print 'picked a hole, moving left peg to center' elif event.artist is self.pegs: print 'picked a peg' sys.stdout.flush() # Necessary when in ipython qtconsole if __name__ == "__main__": pt = peg_tester() I have tried setting the zorder to make the pegs always above the holes, but that doesn't change how the pick events are generated, and particularly this funny phantom event.

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• how to handle an asymptote/discontinuity with Matplotlib

  - by Geddes

  Hello all. Firstly - thanks again for all your help. Sorry not to have accepted the responses to my previous questions as I did not know how the system worked (thanks to Mark for pointing that out!). I have since been back and gratefully acknowledged the kind help I have received. My question: when plotting a graph with a discontinuity/asymptote/singularity/whatever, is there any automatic way to prevent Matplotlib from 'joining the dots' across the 'break'? (please see code/image below). I read that Sage has a [detect_poles] facility that looked good, but I really want it to work with Matplotlib. Thanks and best wishes, Geddes import matplotlib.pyplot as plt import numpy as np from sympy import sympify, lambdify from sympy.abc import x fig = plt.figure(1) ax = fig.add_subplot(111) # set up axis ax.spines['left'].set_position('zero') ax.spines['right'].set_color('none') ax.spines['bottom'].set_position('zero') ax.spines['top'].set_color('none') ax.xaxis.set_ticks_position('bottom') ax.yaxis.set_ticks_position('left') # setup x and y ranges and precision xx = np.arange(-0.5,5.5,0.01) # draw my curve myfunction=sympify(1/(x-2)) mylambdifiedfunction=lambdify(x,myfunction,'numpy') ax.plot(xx, mylambdifiedfunction(xx),zorder=100,linewidth=3,color='red') #set bounds ax.set_xbound(-1,6) ax.set_ybound(-4,4) plt.show()

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• Unexpected performance curve from CPython merge sort

  - by vkazanov

  I have implemented a naive merge sorting algorithm in Python. Algorithm and test code is below: import time import random import matplotlib.pyplot as plt import math from collections import deque def sort(unsorted): if len(unsorted) <= 1: return unsorted to_merge = deque(deque([elem]) for elem in unsorted) while len(to_merge) > 1: left = to_merge.popleft() right = to_merge.popleft() to_merge.append(merge(left, right)) return to_merge.pop() def merge(left, right): result = deque() while left or right: if left and right: elem = left.popleft() if left[0] > right[0] else right.popleft() elif not left and right: elem = right.popleft() elif not right and left: elem = left.popleft() result.append(elem) return result LOOP_COUNT = 100 START_N = 1 END_N = 1000 def test(fun, test_data): start = time.clock() for _ in xrange(LOOP_COUNT): fun(test_data) return time.clock() - start def run_test(): timings, elem_nums = [], [] test_data = random.sample(xrange(100000), END_N) for i in xrange(START_N, END_N): loop_test_data = test_data[:i] elapsed = test(sort, loop_test_data) timings.append(elapsed) elem_nums.append(len(loop_test_data)) print "%f s --- %d elems" % (elapsed, len(loop_test_data)) plt.plot(elem_nums, timings) plt.show() run_test() As much as I can see everything is OK and I should get a nice N*logN curve as a result. But the picture differs a bit: Things I've tried to investigate the issue: PyPy. The curve is ok. Disabled the GC using the gc module. Wrong guess. Debug output showed that it doesn't even run until the end of the test. Memory profiling using meliae - nothing special or suspicious. ` I had another implementation (a recursive one using the same merge function), it acts the similar way. The more full test cycles I create - the more "jumps" there are in the curve. So how can this behaviour be explained and - hopefully - fixed? UPD: changed lists to collections.deque UPD2: added the full test code UPD3: I use Python 2.7.1 on a Ubuntu 11.04 OS, using a quad-core 2Hz notebook. I tried to turn of most of all other processes: the number of spikes went down but at least one of them was still there.

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• How to map coordinates in AxesImage to coordinates in saved image file?

  - by Vebjorn Ljosa

  I use matplotlib to display a matrix of numbers as an image, attach labels along the axes, and save the plot to a PNG file. For the purpose of creating an HTML image map, I need to know the pixel coordinates in the PNG file for a region in the image being displayed by imshow. I have found an example of how to do this with a regular plot, but when I try to do the same with imshow, the mapping is not correct. Here is my code, which saves an image and attempts to print the pixel coordinates of the center of each square on the diagonal: import numpy as np import matplotlib.pyplot as plt fig = plt.figure() ax = fig.add_axes([0.1, 0.1, 0.8, 0.8]) axim = ax.imshow(np.random.random((27,27)), interpolation='nearest') for x, y in axim.get_transform().transform(zip(range(28), range(28))): print int(x), int(fig.get_figheight() * fig.get_dpi() - y) plt.savefig('foo.png', dpi=fig.get_dpi()) Here is the resulting foo.png, shown as a screenshot in order to include the rulers: The output of the script starts and ends as follows: 73 55 92 69 111 83 130 97 149 112 … 509 382 528 396 547 410 566 424 585 439 As you see, the y-coordinates are correct, but the x-coordinates are stretched: they range from 73 to 585 instead of the expected 135 to 506, and they are spaced 19 pixels o.c. instead of the expected 14. What am I doing wrong?

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• Increasing figure size in Matplotlib

  - by Anirudh

  I am trying to plot a graph from a distance matrix. The code words fine and gives me a image in 800 * 600 pixels. The image being too small, All the nodes are packed together. I want increase the size of the image. so I added the following line to my code - figure(num=None, figsize=(10, 10), dpi=80, facecolor='w', edgecolor='k') After this all I get is a blank 1000 * 1000 image file. My overall code - import networkx as nx import pickle import matplotlib.pyplot as plt print "Reading from pickle." p_file = open('pickles/names') Names = pickle.load(p_file) p_file.close() p_file = open('pickles/distance') Dist = pickle.load(p_file) p_file.close() G = nx.Graph() print "Inserting Nodes." for n in Names: G.add_node(n) print "Inserting Edges." for i in range(601): for j in range(601): G.add_edge(Names[i],Names[j],weight=Dist[i][j]) print "Drawing Graph." nx.draw(G) print "Saving Figure." #plt.figure(num=None, figsize=(10, 10)) plt.savefig('new.png') print "Success!"

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• How to stop Python program execution in IDLE

  - by joaoc

  I have a python script that uses plt.show() as it's last instruction. When it runs IDLE just hangs after the last instruction. I get the image but I don't get the prompt back. On other scripts I typically use ctrl-c to break the program (sometimes doesn't work immediately) but how do I get the prompt back with the plt.show()? Ctrl-c doesn't work... Are there other ways to stop the program? This is IDLE on Windows, if it makes any difference.

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