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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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  • numpy array C api

    - by wiso
    I have a C++ function returning a std::vector and I want to use it in python, so I'm using the C numpy api: static PyObject * py_integrate(PyObject *self, PyObject *args){ ... std::vector<double> integral; cpp_function(integral); // this change integral npy_intp size = {integral.size()}; PyObject *out = PyArray_SimpleNewFromData(1, &size, NPY_DOUBLE, &(integral[0])); return out; } when I call it from python, if I do import matplotlib.pyplot as plt a = py_integrate(parameters) print a fig = plt.figure() ax = fig.add_subplot(111) ax.plot(a) print a the first print is ok, the values are correct, but when I plot a they are not, and in particular in the second print I see very strange values like 1E-308 1E-308 ... or 0 0 0 ... as an unitialized memory. I don't understand why the first print is ok.

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  • Python Library installation

    - by MacPython
    Hi everybody I have two questions regarding python libraries: I would like to know if there is something like a "super" python library which lets me install ALL or at least all scientific useful python libraries, which I can install once and then I have all I need. There is a number of annoying problems when installing different libraries (pythonpath, cant import because it is not installed BUT it is installed). Is there any good documentation about common installation errors and how to avoid them. If there is no total solution I would be interested in numpy, scipy, matplotlib, PIL Thanks a lot for the attention and help Best Z

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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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  • Easiest way to plot values as symbols in scatter plot?

    - by AllenH
    In an answer to an earlier question of mine regarding fixing the colorspace for scatter images of 4D data, Tom10 suggested plotting values as symbols in order to double-check my data. An excellent idea. I've run some similar demos in the past, but I can't for the life of me find the demo I remember being quite simple. So, what's the easiest way to plot numerical values as the symbol in a scatter plot instead of 'o' for example? Tom10 suggested plt.txt(x,y,value)- and that is the implementation used in a number of examples. I however wonder if there's an easy way to evaluate "value" from my array of numbers? Can one simply say: str(valuearray) ? Do you need a loop to evaluate the values for plotting as suggested in the matplotlib demo section for 3D text scatter plots? Their example produces: However, they're doing something fairly complex in evaluating the locations as well as changing text direction based on data. So, is there a cute way to plot x,y,C data (where C is a value often taken as the color in the plot data- but instead I wish to make the symbol)? Again, I think we have a fair answer to this- I just wonder if there's an easier way?

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  • How can I link axes of imshow plots for zooming and panning?

    - by Adam Fraser
    Suppose I have a figure canvas with 3 plots... 2 are images of the same dimensions plotted with imshow, and the other is some other kind of subplot. I'd like to be able to link the x and y axes of the imshow plots so that when I zoom in one (using the zoom tool provided by the NavigationToolbar), the other zooms to the same coordinates, and when I pan in one, the other pans as well. Subplot methods such as scatter and histogram can be passed kwargs specifying an axes for sharex and sharey, but imshow has no such configuration. I started hacking my way around this by subclassing NavigationToolbar2WxAgg (shown below)... but there are several problems here. 1) This will link the axes of all plots in a canvas since all I've done is get rid of the checks for a.in_axes() 2) This worked well for panning, but zooming caused all subplots to zoom from the same global point, rather than from the same point in each of their respective axes. Can anyone suggest a workaround? Much thanks! -Adam from matplotlib.backends.backend_wxagg import NavigationToolbar2WxAgg class MyNavToolbar(NavigationToolbar2WxAgg): def __init__(self, canvas, cpfig): NavigationToolbar2WxAgg.__init__(self, canvas) # overrided # As mentioned in the code below, the only difference here from overridden # method is that this one doesn't check a.in_axes(event) when deciding which # axes to start the pan in... def press_pan(self, event): 'the press mouse button in pan/zoom mode callback' if event.button == 1: self._button_pressed=1 elif event.button == 3: self._button_pressed=3 else: self._button_pressed=None return x, y = event.x, event.y # push the current view to define home if stack is empty if self._views.empty(): self.push_current() self._xypress=[] for i, a in enumerate(self.canvas.figure.get_axes()): # only difference from overridden method is that this one doesn't # check a.in_axes(event) if x is not None and y is not None and a.get_navigate(): a.start_pan(x, y, event.button) self._xypress.append((a, i)) self.canvas.mpl_disconnect(self._idDrag) self._idDrag=self.canvas.mpl_connect('motion_notify_event', self.drag_pan) # overrided def press_zoom(self, event): 'the press mouse button in zoom to rect mode callback' if event.button == 1: self._button_pressed=1 elif event.button == 3: self._button_pressed=3 else: self._button_pressed=None return x, y = event.x, event.y # push the current view to define home if stack is empty if self._views.empty(): self.push_current() self._xypress=[] for i, a in enumerate(self.canvas.figure.get_axes()): # only difference from overridden method is that this one doesn't # check a.in_axes(event) if x is not None and y is not None and a.get_navigate() and a.can_zoom(): self._xypress.append(( x, y, a, i, a.viewLim.frozen(), a.transData.frozen())) self.press(event)

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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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  • A good matplot tutorial (from beginner to intermidiate)?

    - by morpheous
    Can anyone recommend a good matplot tutorial. I am a complete beginner - but have used similar software (matlab, R etc), in my halcyon days at University (i.e. a long time ago). A google search brings up a list of dubious quality, and the 'official' docs are too terse, or provide examples that are more 'edge case' (e.g. drawing dolphins swimming in a bubble), than one is likely to meet in practise. I want a manual that provides the following information in a well structured manner: Introduction to the data types Introduction to 2D plotting with some simple practical examples (simple 2D graphs) Introduction to 3D plotting with some simple practical examples (simple 2D graphs: contour and surface)

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  • Variable alpha blending in pylab

    - by Hooked
    How does one control the transparency over a 2D image in pylab? I'd like to give two sets of values (X,Y,Z,T) where X,Y are arrays of positions, Z is the color value, and T is the transparency to a function like imshow but it seems that the function only takes alpha as a scalar. As a concrete example, consider the code below that attempts to display two Gaussians. The closer the value is to zero, the more transparent I'd like the plot to be. from pylab import * side = linspace(-1,1,100) X,Y = meshgrid(side,side) extent = (-1,1,-1,1) Z1 = exp(-((X+.5)**2+Y**2)) Z2 = exp(-((X-.5)**2+(Y+.2)**2)) imshow(Z1, cmap=cm.hsv, alpha=.6, extent=extent) imshow(Z2, cmap=cm.hsv, alpha=.6, extent=extent) show() Note: I am not looking for a plot of Z1+Z2 (that would be trivial) but for a general way to specify the alpha blending across an image.

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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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  • Using PyLab to create a 2D graph from two separate lists

    - by user324333
    Hey Guys, This seems like a basic problem with an easy answer but I simply cannot figure it out no matter how much I try. I am trying to create a line graph based on two lists. For my x-axis, I want my list to be a set of strings. x_axis_list = ["Jan-06","Jul-06","Jan-07","Jul-07","Jan-08"] y_axis_list = [5,7,6,8,9] Any suggestions on how to best graph these items?

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  • reading csv files in scipy/numpy in Python

    - by user248237
    I am having trouble reading a csv file, delimited by tabs, in python. I use the following function: def csv2array(filename, skiprows=0, delimiter='\t', raw_header=False, missing=None, with_header=True): """ Parse a file name into an array. Return the array and additional header lines. By default, parse the header lines into dictionaries, assuming the parameters are numeric, using 'parse_header'. """ f = open(filename, 'r') skipped_rows = [] for n in range(skiprows): header_line = f.readline().strip() if raw_header: skipped_rows.append(header_line) else: skipped_rows.append(parse_header(header_line)) f.close() if missing: data = genfromtxt(filename, dtype=None, names=with_header, deletechars='', skiprows=skiprows, missing=missing) else: if delimiter != '\t': data = genfromtxt(filename, dtype=None, names=with_header, delimiter=delimiter, deletechars='', skiprows=skiprows) else: data = genfromtxt(filename, dtype=None, names=with_header, deletechars='', skiprows=skiprows) if data.ndim == 0: data = array([data.item()]) return (data, skipped_rows) the problem is that genfromtxt complains about my files, e.g. with the error: Line #27100 (got 12 columns instead of 16) I am not sure where these errors come from. Any ideas? Here's an example file that causes the problem: #Gene 120-1 120-3 120-4 30-1 30-3 30-4 C-1 C-2 C-5 genesymbol genedesc ENSMUSG00000000001 7.32 9.5 7.76 7.24 11.35 8.83 6.67 11.35 7.12 Gnai3 guanine nucleotide binding protein alpha ENSMUSG00000000003 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Pbsn probasin Is there a better way to write a generic csv2array function? thanks.

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  • pylab.savefig() and pylab.show() image difference

    - by Jack1990
    I'm making an script to automatically create plots from .xvg files, but there's a problem when I'm trying to use pylab's savefig() method. Using pylab.show() and saving from there, everything's fine. Using pylab.show() Using pylab.savefig() def producePlot(timestep, energy_values,type_line = 'r', jump = 1,finish = 100): fc = sp.interp1d(timestep[::jump], energy_values[::jump],kind='cubic') xnew = numpy.linspace(0, finish, finish*2) pylab.plot(xnew, fc(xnew),type_line) pylab.xlabel('Time in ps ') pylab.ylabel('kJ/mol') pylab.xlim(xmin=0, xmax=finish) def produceSimplePlot(timestep, energy_values,type_line = 'r', jump = 1,finish = 100): pylab.plot(timestep, energy_values,type_line) pylab.xlabel('Time in ps ') pylab.ylabel('kJ/mol') pylab.xlim(xmin=0, xmax=finish) def linearRegression(timestep, energy_values, type_line = 'g'): #, jump = 1,finish = 100): from scipy import stats import numpy #print 'fuck' timestep = numpy.asarray(timestep) slope, intercept, r_value, p_value, std_err = stats.linregress(timestep,energy_values) line = slope*timestep+intercept pylab.plot(timestep, line, type_line) def plottingTime(Title,file_name, timestep, energy_values ,loc, jump , finish): pylab.title(Title) producePlot(timestep,energy_values, 'b',jump, finish) linearRegression(timestep,energy_values) import numpy Average = numpy.average(energy_values) #print Average pylab.legend(("Average = %.2f" %(Average),'Linear Reg'),loc) #pylab.show() pylab.savefig('%s.jpg' %file_name[:-4], bbox_inches= None, pad_inches=0) #if __name__ == '__main__': #plottingTime(Title,timestep1, energy_values, jump =10, finish = 4800) def specialCase(Title,file_name, timestep, energy_values,loc, jump, finish): #print 'Working here ...?' pylab.title(Title) producePlot(timestep,energy_values, 'b',jump, finish) import numpy from pylab import * Average = numpy.average(energy_values) #print Average pylab.legend(("Average = %.2g" %(Average), Title),loc) locs,labels = yticks() yticks(locs, map(lambda x: "%.3g" % x, locs)) #pylab.show() pylab.savefig('%s.jpg' %file_name[:-4] , bbox_inches= None, pad_inches=0) Thanks in advance, John

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  • Return numerical array in python

    - by khan
    Okay..this is kind of an interesting question. I have a php form through which user enters values for x and y like this: X: [1,3,4] Y: [2,4,5] These values are stored into database as varchars. From there, these are called by a python program which is supposed to use them as numerical (numpy) arrays. However, these are called as plain strings, which means that calculation can not be performed over them. Is there a way to convert them into numerical arrays before processing or is there something else which is wrong? Helpp!!

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  • Setting `axes.linewidth` without changing the `rcParams` global dict

    - by mlvljr
    So, it seems one cannot do the following (it raises an error, since axes does not have a set_linewidth method): axes_style = {'linewidth':5} axes_rect = [0.1, 0.1, 0.9, 0.9] axes(axes_rect, **axes_style) and has to use the following old trick instead: rcParams['axes.linewidth'] = 5 # set the value globally ... # some code rcdefaults() # restore [global] defaults Is there an easy / clean way (may be one can set x- and y- axes parameters individually, etc)? P.S. If no, why?

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  • pyplot.scatter changes the data limits of the axis

    - by Erotemic
    I have some code which plots some points. I substituted ax.scatter for ax.plot so I could control the color of each point individually. However when I make this change the axis x and y ranges seem to increase. I can't pinpoint why this is happening. The only thing I've changed is plot to scatter. This code makes an axis that is too big ax.scatter(x, y, c=color_list, s=pts_size, marker='o', edgecolor='none') #ax.plot(x, y, linestyle='None', marker='o', markerfacecolor=pts_color, markersize=pts_size, markeredgewidth=0) This code does the right thing (but I can't control the color) #ax.scatter(x, y, c=color_list, s=pts_size, marker='o', edgecolor='none') ax.plot(x, y, linestyle='None', marker='o', markerfacecolor=pts_color, markersize=pts_size, markeredgewidth=0) Is there a way I can call scatter such that it doesn't mess with my current axis limits?

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  • Choosing randomly all the elements in the the list just once

    - by Dalek
    How is it possible to randomly choose a number from a list with n elements, n time without picking the same element of the list twice. I wrote a code to choose the sequence number of the elements in the list but it is slow: >>>redshift=np.array([0.92,0.17,0.51,1.33,....,0.41,0.82]) >>>redshift.shape (1225,) exclude=[] k=0 ng=1225 while (k < ng): flag1=0 sq=random.randint(0, ng) while (flag1<1): if sq in exclude: flag1=1 sq=random.randint(0, ng) else: print sq exclude.append(sq) flag1=0 z=redshift[sq] k+=1 It doesn't choose all the sequence number of elements in the list.

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  • Looking for a specific python gui module to perform the following task

    - by Sadaf Amouz
    I am looking for a GUI python module that is best suited for the following job: I am trying to plot a graph with many columns (perhaps hundreds), each column representing an individual. The user should be able to drag the columns around and drop them onto different columns to switch the two. Also, there are going to be additional dots drawn on the columns and by hovering over those dots, the user should see the values corresponding to those dots. What is the best way to approach this?

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  • python networkx

    - by krisdigitx
    hi, i am trying to use networkx with python, when i run this program, it get this error, is there anything missing? #!/usr/bin/env python import networkx as nx import matplotlib import matplotlib.pyplot import matplotlib.pyplot as plt G=nx.Graph() G.add_node(1) G.add_nodes_from([2,3,4,5,6,7,8,9,10]) #nx.draw_graphviz(G) #nx_write_dot(G, 'node.png') nx.draw(G) plt.savefig("/var/www/node.png") Traceback (most recent call last): File "graph.py", line 13, in <module> nx.draw(G) File "/usr/lib/pymodules/python2.5/networkx/drawing/nx_pylab.py", line 124, in draw cf=pylab.gcf() File "/usr/lib/pymodules/python2.5/matplotlib/pyplot.py", line 276, in gcf return figure() File "/usr/lib/pymodules/python2.5/matplotlib/pyplot.py", line 254, in figure **kwargs) File "/usr/lib/pymodules/python2.5/matplotlib/backends/backend_tkagg.py", line 90, in new_figure_manager window = Tk.Tk() File "/usr/lib/python2.5/lib-tk/Tkinter.py", line 1650, in __init__ self.tk = _tkinter.create(screenName, baseName, className, interactive, wantobjects, useTk, sync, use) _tkinter.TclError: no display name and no $DISPLAY environment variable

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  • PySide Qt script doesn't launch from Spyder but works from shell

    - by Maxim Zaslavsky
    I have a weird bug in my project that uses PySide for its Qt GUI, and in response I'm trying to test with simpler code that sets up the environment. Here is the code I am testing with: http://stackoverflow.com/a/6906552/130164 When I launch that from my shell (python test.py), it works perfectly. However, when I run that script in Spyder, I get the following error: Traceback (most recent call last): File "/home/test/Desktop/test/test.py", line 31, in <module> app = QtGui.QApplication(sys.argv) RuntimeError: A QApplication instance already exists. If it helps, I also get the following warning: /usr/lib/pymodules/python2.6/matplotlib/__init__.py:835: UserWarning: This call to matplotlib.use() has no effect because the the backend has already been chosen; matplotlib.use() must be called *before* pylab, matplotlib.pyplot, or matplotlib.backends is imported for the first time. Why does that code work when launched from my shell but not from Spyder? Update: Mata answered that the problem happens because Spyder uses Qt, which makes sense. For now, I've set up execution in Spyder using the "Execute in an external system terminal" option, which doesn't cause errors but doesn't allow debugging, either. Does Spyder have any built-in workarounds to this?

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  • pymatplotlib without xserver

    - by vigilant
    Is it possible to use networkx or pymatplotlib without an xserver running? I keep getting the following error with their first example (of networkx): Traceback (most recent call last): File "test.py", line 17, in <module> nx.draw(G,pos,node_color='#A0CBE2',edge_color=colors,width=4,edge_cmap=plt.cm.Blues,with_labels=False) File "/usr/local/lib/python2.6/dist-packages/networkx-1.3-py2.6.egg/networkx/drawing/nx_pylab.py", line 124, in draw cf=pylab.gcf() File "/usr/lib/pymodules/python2.6/matplotlib/pyplot.py", line 276, in gcf return figure() File "/usr/lib/pymodules/python2.6/matplotlib/pyplot.py", line 254, in figure **kwargs) File "/usr/lib/pymodules/python2.6/matplotlib/backends/backend_tkagg.py", line 90, in new_figure_manager window = Tk.Tk() File "/usr/lib/python2.6/lib-tk/Tkinter.py", line 1646, in __init__ self.tk = _tkinter.create(screenName, baseName, className, interactive, wantobjects, useTk, sync, use) _tkinter.TclError: couldn't connect to display ""

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  • Creating a new plugin for mpld3

    - by sjp14051
    Toward learning how to create a new mpld3 plugin, I took an existing example, LinkedDataPlugin (http://mpld3.github.io/examples/heart_path.html), and modified it slightly by deleting references to lines object. That is, I created the following: class DragPlugin(plugins.PluginBase): JAVASCRIPT = r""" mpld3.register_plugin("drag", DragPlugin); DragPlugin.prototype = Object.create(mpld3.Plugin.prototype); DragPlugin.prototype.constructor = DragPlugin; DragPlugin.prototype.requiredProps = ["idpts", "idpatch"]; DragPlugin.prototype.defaultProps = {} function DragPlugin(fig, props){ mpld3.Plugin.call(this, fig, props); }; DragPlugin.prototype.draw = function(){ var patchobj = mpld3.get_element(this.props.idpatch, this.fig); var ptsobj = mpld3.get_element(this.props.idpts, this.fig); var drag = d3.behavior.drag() .origin(function(d) { return {x:ptsobj.ax.x(d[0]), y:ptsobj.ax.y(d[1])}; }) .on("dragstart", dragstarted) .on("drag", dragged) .on("dragend", dragended); patchobj.path.attr("d", patchobj.datafunc(ptsobj.offsets, patchobj.pathcodes)); patchobj.data = ptsobj.offsets; ptsobj.elements() .data(ptsobj.offsets) .style("cursor", "default") .call(drag); function dragstarted(d) { d3.event.sourceEvent.stopPropagation(); d3.select(this).classed("dragging", true); } function dragged(d, i) { d[0] = ptsobj.ax.x.invert(d3.event.x); d[1] = ptsobj.ax.y.invert(d3.event.y); d3.select(this) .attr("transform", "translate(" + [d3.event.x,d3.event.y] + ")"); patchobj.path.attr("d", patchobj.datafunc(ptsobj.offsets, patchobj.pathcodes)); } function dragended(d, i) { d3.select(this).classed("dragging", false); } } mpld3.register_plugin("drag", DragPlugin); """ def __init__(self, points, patch): print "Points ID : ", utils.get_id(points) self.dict_ = {"type": "drag", "idpts": utils.get_id(points), "idpatch": utils.get_id(patch)} However, when I try to link the plugin to a figure, as in plugins.connect(fig, DragPlugin(points[0], patch)) I get an error, 'module' is not callable, pointing to this line. What does this mean and why doesn't it work? Thanks. I'm adding additional code to show that linking more than one Plugin might be problematic. But this may be entirely due to some silly mistake on my part, or there is a way around it. The following code based on LinkedViewPlugin generates three panels, in which the top and the bottom panel are supposed to be identical. Mouseover in the middle panel was expected to control the display in the top and bottom panels, but updates occur in the bottom panel only. It would be nice to be able to figure out how to reflect the changes in multiple panels. Thanks. import matplotlib import matplotlib.pyplot as plt import numpy as np import mpld3 from mpld3 import plugins, utils class LinkedView(plugins.PluginBase): """A simple plugin showing how multiple axes can be linked""" JAVASCRIPT = """ mpld3.register_plugin("linkedview", LinkedViewPlugin); LinkedViewPlugin.prototype = Object.create(mpld3.Plugin.prototype); LinkedViewPlugin.prototype.constructor = LinkedViewPlugin; LinkedViewPlugin.prototype.requiredProps = ["idpts", "idline", "data"]; LinkedViewPlugin.prototype.defaultProps = {} function LinkedViewPlugin(fig, props){ mpld3.Plugin.call(this, fig, props); }; LinkedViewPlugin.prototype.draw = function(){ var pts = mpld3.get_element(this.props.idpts); var line = mpld3.get_element(this.props.idline); var data = this.props.data; function mouseover(d, i){ line.data = data[i]; line.elements().transition() .attr("d", line.datafunc(line.data)) .style("stroke", this.style.fill); } pts.elements().on("mouseover", mouseover); }; """ def __init__(self, points, line, linedata): if isinstance(points, matplotlib.lines.Line2D): suffix = "pts" else: suffix = None self.dict_ = {"type": "linkedview", "idpts": utils.get_id(points, suffix), "idline": utils.get_id(line), "data": linedata} class LinkedView2(plugins.PluginBase): """A simple plugin showing how multiple axes can be linked""" JAVASCRIPT = """ mpld3.register_plugin("linkedview", LinkedViewPlugin2); LinkedViewPlugin2.prototype = Object.create(mpld3.Plugin.prototype); LinkedViewPlugin2.prototype.constructor = LinkedViewPlugin2; LinkedViewPlugin2.prototype.requiredProps = ["idpts", "idline", "data"]; LinkedViewPlugin2.prototype.defaultProps = {} function LinkedViewPlugin2(fig, props){ mpld3.Plugin.call(this, fig, props); }; LinkedViewPlugin2.prototype.draw = function(){ var pts = mpld3.get_element(this.props.idpts); var line = mpld3.get_element(this.props.idline); var data = this.props.data; function mouseover(d, i){ line.data = data[i]; line.elements().transition() .attr("d", line.datafunc(line.data)) .style("stroke", this.style.fill); } pts.elements().on("mouseover", mouseover); }; """ def __init__(self, points, line, linedata): if isinstance(points, matplotlib.lines.Line2D): suffix = "pts" else: suffix = None self.dict_ = {"type": "linkedview", "idpts": utils.get_id(points, suffix), "idline": utils.get_id(line), "data": linedata} fig, ax = plt.subplots(3) # scatter periods and amplitudes np.random.seed(0) P = 0.2 + np.random.random(size=20) A = np.random.random(size=20) x = np.linspace(0, 10, 100) data = np.array([[x, Ai * np.sin(x / Pi)] for (Ai, Pi) in zip(A, P)]) points = ax[1].scatter(P, A, c=P + A, s=200, alpha=0.5) ax[1].set_xlabel('Period') ax[1].set_ylabel('Amplitude') # create the line object lines = ax[0].plot(x, 0 * x, '-w', lw=3, alpha=0.5) ax[0].set_ylim(-1, 1) ax[0].set_title("Hover over points to see lines") linedata = data.transpose(0, 2, 1).tolist() plugins.connect(fig, LinkedView(points, lines[0], linedata)) # second set of lines exactly the same but in a different panel lines2 = ax[2].plot(x, 0 * x, '-w', lw=3, alpha=0.5) ax[2].set_ylim(-1, 1) ax[2].set_title("Hover over points to see lines #2") plugins.connect(fig, LinkedView2(points, lines2[0], linedata)) mpld3.show()

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  • Package system broken - E: Sub-process /usr/bin/dpkg returned an error code (1)

    - by delha
    After installing some packages and libraries I have an error on Package Manager, I can't run any update because it says: "The package system is broken If you are using third party repositories then disable them, since they are a common source of problems. Now run the following command in a terminal: apt-get install -f " I've tried to do what it says and it returns me: jara@jara-Aspire-5738:~$ sudo apt-get install -f Reading package lists... Done Building dependency tree Reading state information... Done Correcting dependencies... Done The following packages were automatically installed and are no longer required: libcaca-dev libopencv2.3-bin nite-dev python-bluez ps-engine libslang2-dev python-sphinx ros-electric-geometry-tutorials ros-electric-geometry-visualization python-matplotlib libzzip-dev ros-electric-orocos-kinematics-dynamics ros-electric-physics-ode libbluetooth-dev libaudiofile-dev libassimp2 libnetpbm10-dev ros-electric-laser-pipeline python-epydoc ros-electric-geometry-experimental libasound2-dev evtest python-matplotlib-data libyaml-dev ros-electric-bullet ros-electric-executive-smach ros-electric-documentation libgl2ps0 libncurses5-dev ros-electric-robot-model texlive-fonts-recommended python-lxml libwxgtk2.8-dev daemontools libxxf86vm-dev libqhull-dev libavahi-client-dev ros-electric-geometry libgl2ps-dev libcurl4-openssl-dev assimp-dev libusb-1.0-0-dev libopencv2.3 ros-electric-diagnostics-monitors libsdl1.2-dev libjs-underscore libsdl-image1.2 tipa libusb-dev libtinfo-dev python-tz python-sip libfltk1.1 libesd0 libfreeimage-dev ros-electric-visualization x11proto-xf86vidmode-dev python-docutils libvtk5.6 ros-electric-assimp x11proto-scrnsaver-dev libnetcdf-dev libidn11-dev libeigen3-dev joystick libhdf5-serial-1.8.4 ros-electric-joystick-drivers texlive-fonts-recommended-doc esound-common libesd0-dev tcl8.5-dev ros-electric-multimaster-experimental ros-electric-rx libaudio-dev ros-electric-ros-tutorials libwxbase2.8-dev ros-electric-visualization-common python-sip-dev ros-electric-visualization-tutorials libfltk1.1-dev libpulse-dev libnetpbm10 python-markupsafe openni-dev tk8.5-dev wx2.8-headers freeglut3-dev libavahi-common-dev python-roman python-jinja2 ros-electric-robot-model-visualization libxss-dev libqhull5 libaa1-dev ros-electric-eigen freeglut3 ros-electric-executive-smach-visualization ros-electric-common-tutorials ros-electric-robot-model-tutorials libnetcdf6 libjs-sphinxdoc python-pyparsing libaudiofile0 Use 'apt-get autoremove' to remove them. The following extra packages will be installed: libcv-dev The following NEW packages will be installed libcv-dev 0 upgraded, 1 newly installed, 0 to remove and 4 not upgraded. 2 not fully installed or removed. Need to get 0 B/3,114 kB of archives. After this operation, 11.1 MB of additional disk space will be used. Do you want to continue [Y/n]? y (Reading database ... 261801 files and directories currently installed.) Unpacking libcv-dev (from .../libcv-dev_2.1.0-7build1_amd64.deb) ... dpkg: error processing /var/cache/apt/archives/libcv-dev_2.1.0-7build1_amd64.deb (-- unpack): trying to overwrite '/usr/bin/opencv_haartraining', which is also in package libopencv2.3-bin 2.3.1+svn6514+branch23-12~oneiric dpkg-deb: error: subprocess paste was killed by signal (Broken pipe) Errors were encountered while processing: /var/cache/apt/archives/libcv-dev_2.1.0-7build1_amd64.deb E: Sub-process /usr/bin/dpkg returned an error code (1) I've tried everything people recommend on internet like: sudo apt-get clean sudo apt-get autoremove sudo apt-get update sudo apt-get upgrade sudo apt-get -f install Also I've tried to install the synaptic manager but it doesn't let me install anything.. As you can see nothing works so I'm desperate! I'm using ubuntu 11.10, 64 bits Thanks!!

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  • Need help starting with DSL for charts/graphs

    - by Rex M
    I am unaware of any established work into Domain Specific Languages for describing charts / graphs. I am looking for specific answers of "yes, something like that exists (here)". To help be clear, in case I am possibly using the wrong verbiage to describe it, to me a DSL for charts would most certainly include: A grammar for describing the shape of an expected data set A grammar for describing a pipeline of behaviors that render an output Abstract / high-level enough to be mappable to most tool-specific grammars, such as Excel, Highchart, matplotlib, etc.

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  • Interactive Data Language, IDL: Does anybody care?

    - by Alex
    Anyone use a language called Interactive Data Language, IDL? It is popular with scientists. I think it is a poor language because it is proprietary (every terminal running it has to have an expensive license purchased) and it has minimal support (try searching for IDL, the language, right now on stack) . I am trying to convince my colleagues to stop using it and learn C/C++/Python/Fortran/Java/Ruby. Does anybody know about or even care about IDL enough to have opinions on it? What do you think of it? Should I tell my colleagues to stop wasting their time on it now? How can I convince them? Edit: People are getting the impression that I don't know or use IDL. Also, I said IDL has minimal support which is true in one sense, so I must clarify that the scientific libraries are indeed large. I use IDL all the time, but this is exactly the problem: I am only using IDL because colleagues use it. There is a file format IDL uses, the .sav, which can only be opened in IDL. So I must use IDL to work with this data and transfer the data back to colleagues, but I know I would be more efficient in another language. This is like someone sending you a microsoft word file in an email attachment and if you don't understand how wrong that is then you probably write too many words not enough code and you bought microsoft word. Edit: As an alternative to IDL Python is popular. Here is a list of The Pros of IDL (and the cons) from AstroBetter: Pros of IDL Mature many numerical and astronomical libraries available Wide astronomical user base Numerical aspect well integrated with language itself Many local users with deep experience Faster for small arrays Easier installation Good, unified documentation Standard GUI run/debug tool (IDLDE) Single widget system (no angst about which to choose or learn) SAVE/RESTORE capability Use of keyword arguments as flags more convenient Cons of IDL Narrow applicability, not well suited to general programming Slower for large arrays Array functionality less powerful Table support poor Limited ability to extend using C or Fortran, such extensions hard to distribute and support Expensive, sometimes problem collaborating with others that don’t have or can’t afford licenses. Closed source (only RSI can fix bugs) Very awkward to integrate with IRAF tasks Memory management more awkward Single widget system (useless if working within another framework) Plotting: Awkward support for symbols and math text Many font systems, portability issues (v5.1 alleviates somewhat) not as flexible or as extensible plot windows not intrinsically interactive (e.g., pan & zoom) Pros of Python Very general and powerful programming language, yet easy to learn. Strong, but optional, Object Oriented programming support Very large user and developer community, very extensive and broad library base Very extensible with C, C++, or Fortran, portable distribution mechanisms available Free; non-restrictive license; Open Source Becoming the standard scripting language for astronomy Easy to use with IRAF tasks Basis of STScI application efforts More general array capabilities Faster for large arrays, better support for memory mapping Many books and on-line documentation resources available (for the language and its libraries) Better support for table structures Plotting framework (matplotlib) more extensible and general Better font support and portability (only one way to do it too) Usable within many windowing frameworks (GTK, Tk, WX, Qt…) Standard plotting functionality independent of framework used plots are embeddable within other GUIs more powerful image handling (multiple simultaneous LUTS, optional resampling/rescaling, alpha blending, etc) Support for many widget systems Strong local influence over capabilities being developed for Python Cons of Python More items to install separately Not as well accepted in astronomical community (but support clearly growing) Scientific libraries not as mature: Documentation not as complete, not as unified Not as deep in astronomical libraries and utilities Not all IDL numerical library functions have corresponding functionality in Python Some numeric constructs not quite as consistent with language (or slightly less convenient than IDL) Array indexing convention “backwards” Small array performance slower No standard GUI run/debug tool Support for many widget systems (angst regarding which to choose) Current lack of function equivalent to SAVE/RESTORE in IDL matplotlib does not yet have equivalents for all IDL 2-D plotting capability (e.g., surface plots) Use of keyword arguments used as flags less convenient Plotting: comparatively immature, still much development going on missing some plot type (e.g., surface) 3-d capability requires VTK (though matplotlib has some basic 3-d capability)

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