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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 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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  • AS 3.0 reference problem

    - by vasion
    I am finding it hard to fugure out the reference system in AS 3.0. this is the code i have (i have trimmed it down in order to find the problem but to no avail) package rpflash.ui { import flash.display.Sprite; import flash.display.MovieClip; import flash.display.Stage; import nowplaying; import flash.text.TextField; public class RPUserInterface extends Sprite{ var np:nowplaying; public function RPUserInterface(){ } public function init(){ var np:nowplaying = new nowplaying(); this.addChild(np) } public function updateplayer(xml:XML){ var artist: String = xml.nowplaying.artist.toString(); var title: String = xml.nowplaying.title.toString(); trace("UI:update"); trace(this.np);// this gives me a null reference } } } and still i cannot access np!!! trace this.np gives me a null reference. i am not even trying to access it from a subling class. (btw i def want to know how to do that as well.)

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  • ndarray field names for both row and column?

    - by Graham Mitchell
    I'm a computer science teacher trying to create a little gradebook for myself using NumPy. But I think it would make my code easier to write if I could create an ndarray that uses field names for both the rows and columns. Here's what I've got so far: import numpy as np num_stud = 23 num_assign = 2 grades = np.zeros(num_stud, dtype=[('assign 1','i2'), ('assign 2','i2')]) #etc gv = grades.view(dtype='i2').reshape(num_stud,num_assign) So, if my first student gets a 97 on 'assign 1', I can write either of: grades[0]['assign 1'] = 97 gv[0][0] = 97 Also, I can do the following: np.mean( grades['assign 1'] ) # class average for assignment 1 np.sum( gv[0] ) # total points for student 1 This all works. But what I can't figure out how to do is use a student id number to refer to a particular student (assume that two of my students have student ids as shown): grades['123456']['assign 2'] = 95 grades['314159']['assign 2'] = 83 ...or maybe create a second view with the different field names? np.sum( gview2['314159'] ) # total points for the student with the given id I know that I could create a dict mapping student ids to indices, but that seems fragile and crufty, and I'm hoping there's a better way than: id2i = { '123456': 0, '314159': 1 } np.sum( gv[ id2i['314159'] ] ) I'm also willing to re-architect things if there's a cleaner design. I'm new to NumPy, and I haven't written much code yet, so starting over isn't out of the question if I'm Doing It Wrong. I am going to be needing to sum all the assignment points for over a hundred students once a day, as well as run standard deviations and other stats. Plus, I'll be waiting on the results, so I'd like it to run in only a couple of seconds. Thanks in advance for any suggestions.

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  • Using ROBOCOPY to MOVE data around, not copy it

    - by Nate Bross
    I have the following powershell script, which executes a few robocopy commands: ROBOCOPY.exe $q3 $q4 /R:5 /W:15 /S /NP /MT:32 /XA:SH /XJD ROBOCOPY.exe $q2 $q3 /R:5 /W:15 /S /NP /MT:32 /XA:SH /XJD ROBOCOPY.exe $q1 $q2 /R:5 /W:15 /S /NP /MT:32 /XA:SH /XJD ROBOCOPY.exe $src $q1 /R:5 /W:15 /S /NP /MT:32 /XA:SH /XJD This works fine, but it takes a really long time, I'm wondering, if there is a way that I can have robocopy do a "cut + paste" instead of a "copy + paste" so windows will move the NTFS pointer to the file, instead of actually copying all of the bits of each file?

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  • python numpy roll with padding

    - by Marshall Ward
    I'd like to roll a 2D numpy in python, except that I'd like pad the ends with zeros rather than roll the data as if its periodic. Specifically, the following code import numpy as np x = np.array([[1, 2, 3],[4, 5, 6]]) np.roll(x,1,axis=1) returns array([[3, 1, 2],[6, 4, 5]]) but what I would prefer is array([[0, 1, 2], [0, 4, 5]]) I could do this with a few awkward touchups, but I'm hoping that there's a way to do it with fast built-in commands. Thanks

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  • String comparison in Numpy

    - by Morgoth
    In the following example In [8]: import numpy as np In [9]: strings = np.array(['hello ', 'world '], dtype='|S10') In [10]: strings == 'hello' Out[10]: array([False, False], dtype=bool) The comparison fails because of the whitespace. Is there a Numpy built-in function that does the equivalent of In [12]: np.array([x.strip()=='hello' for x in strings]) Out[12]: array([ True, False], dtype=bool) which does give the correct result?

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  • Filestream in Sql Server 2008 Express

    - by Xaitec
    i tried to get it to work but i never seem to have to luck, i go a code snippet for a blog and still no dice. This is the code. EXEC sp_configure filestream_access_level, 1 GO RECONFIGURE GO CREATE DATABASE NorthPole ON PRIMARY ( NAME = NorthPoleDB, FILENAME = 'C:\Temp\NP\NorthPoleDB.mdf' ), FILEGROUP NorthPoleFS CONTAINS FILESTREAM( NAME = NorthPoleFS, FILENAME = 'C:\Temp\NP\NorthPoleFS') LOG ON ( NAME = NorthPoleLOG, FILENAME = 'C:\Temp\NP\NorthPoleLOG.ldf') GO

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  • Using numpy.apply

    - by andylei
    What's wrong with this snippet of code? import numpy as np from scipy import stats d = np.arange(10.0) cutoffs = [stats.scoreatpercentile(d, pct) for pct in range(0, 100, 20)] f = lambda x: np.sum(x > cutoffs) fv = np.vectorize(f) # why don't these two lines output the same values? [f(x) for x in d] # => [0, 1, 2, 2, 3, 3, 4, 4, 5, 5] fv(d) # => array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) Any ideas?

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  • Searching Natural Language Sentence Structure

    - by Cerin
    What's the best way to store and search a database of natural language sentence structure trees? Using OpenNLP's English Treebank Parser, I can get fairly reliable sentence structure parsings for arbitrary sentences. What I'd like to do is create a tool that can extract all the doc strings from my source code, generate these trees for all sentences in the doc strings, store these trees and their associated function name in a database, and then allow a user to search the database using natural language queries. So, given the sentence "This uploads files to a remote machine." for the function upload_files(), I'd have the tree: (TOP (S (NP (DT This)) (VP (VBZ uploads) (NP (NNS files)) (PP (TO to) (NP (DT a) (JJ remote) (NN machine)))) (. .))) If someone entered the query "How can I upload files?", equating to the tree: (TOP (SBARQ (WHADVP (WRB How)) (SQ (MD can) (NP (PRP I)) (VP (VB upload) (NP (NNS files)))) (. ?))) how would I store and query these trees in a SQL database? I've written a simple proof-of-concept script that can perform this search using a mix of regular expressions and network graph parsing, but I'm not sure how I'd implement this in a scalable way. And yes, I realize my example would be trivial to retrieve using a simple keyword search. The idea I'm trying to test is how I might take advantage of grammatical structure, so I can weed-out entries with similar keywords, but a different sentence structure. For example, with the above query, I wouldn't want to retrieve the entry associated with the sentence "Checks a remote machine to find a user that uploads files." which has similar keywords, but is obviously describing a completely different behavior.

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  • Solving linear system over integers with numpy

    - by A. R. S.
    I'm trying to solve an overdetermined linear system of equations with numpy. Currently, I'm doing something like this (as a simple example): a = np.array([[1,0], [0,1], [-1,1]]) b = np.array([1,1,0]) print np.linalg.lstsq(a,b)[0] [ 1. 1.] This works, but uses floats. Is there any way to solve the system over integers only? I've tried something along the lines of print map(int, np.linalg.lstsq(a,b)[0]) [0, 1] in order to convert the solution to an array of ints, expecting [1, 1], but clearly I'm missing something. Could anyone point me in the right direction?

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  • numpy array mapping and take average

    - by user566653
    Dear all, I have three array value = np.array ([1, 3, 3, 5, 5, 7, 3]) index = np.array ([1, 1, 3, 3, 6, 6, 6]) data = np.array ([1, 2, 3, 4, 5, 6]) and want to take average for item of "value" by array "index", and assign a new array with value of "data", such as [2, nan, 4, nan, nan, 5] first value is the average of 1st and 2nd of "value" second value is nan because there is not any key in "index" third value is the average of 3rd and 4th of "value" ... Thanks for your help!!! Regards, Roy

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  • Class.Class vs Namespace.Class for top level general use class libraries?

    - by Joan Venge
    Which one is more acceptable (best-practice)?: namespace NP public static class IO public static class Xml ... // extension methods using NP; IO.GetAvailableResources (); vs public static class NP public static class IO public static class Xml ... // extension methods NP.IO.GetAvailableResources (); Also for #2, the code size is managed by having partial classes so each nested class can be in a separate file, same for extension methods (except that there is no nested class for them) I prefer #2, for a couple of reasons like being able to use type names that are already commonly used, like IO, that I don't want to replace or collide. Which one do you prefer? Any pros and cons for each? What's the best practice for this case? EDIT: Also would there be a performance difference between the two?

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  • How detect length of a numpy array with only one element?

    - by mishaF
    I am reading in a file using numpy.genfromtxt which brings in columns of both strings and numeric values. One thing I need to do is detect the length of the input. This is all fine provided there are more than one value read into each array. But...if there is only one element in the resulting array, the logic fails. I can recreate an example here: import numpy as np a = np.array(2.3) len(a) returns an error saying: TypeError: len() of unsized object however, If a has 2 or more elements, len() behaves as one would expect. import numpy as np a = np.array([2.3,3.6]) len(a) returns 2 My concern here is, if I use some strange exception handling, I can't distinguish between a being empty and a having length = 1.

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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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  • Indexing and Searching Over Word Level Annotation Layers in Lucene

    - by dmcer
    I have a data set with multiple layers of annotation over the underlying text, such as part-of-tags, chunks from a shallow parser, name entities, and others from various natural language processing (NLP) tools. For a sentence like The man went to the store, the annotations might look like: Word POS Chunk NER ==== === ===== ======== The DT NP Person man NN NP Person went VBD VP - to TO PP - the DT NP Location store NN NP Location I'd like to index a bunch of documents with annotations like these using Lucene and then perform searches across the different layers. An example of a simple query would be to retrieve all documents where Washington is tagged as a person. While I'm not absolutely committed to the notation, syntactically end-users might enter the query as follows: Query: Word=Washington,NER=Person I'd also like to do more complex queries involving the sequential order of annotations across different layers, e.g. find all the documents where there's a word tagged person followed by the words arrived at followed by a word tagged location. Such a query might look like: Query: "NER=Person Word=arrived Word=at NER=Location" What's a good way to go about approaching this with Lucene? Is there anyway to index and search over document fields that contain structured tokens?

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  • Better way to compare neighboring cells in matrix

    - by HyperCube
    Suppose I have a matrix of size 100x100 and I would like to compare each pixel to its direct neighbor (left, upper, right, lower) and then do some operations on the current matrix or a new one of the same size. A sample code in Python/Numpy could look like the following: (the comparison 0.5 has no meaning, I just want to give a working example for some operation while comparing the neighbors) import numpy as np my_matrix = np.random.rand(100,100) new_matrix = np.array((100,100)) my_range = np.arange(1,99) for i in my_range: for j in my_range: if my_matrix[i,j+1] > 0.5: new_matrix[i,j+1] = 1 if my_matrix[i,j-1] > 0.5: new_matrix[i,j-1] = 1 if my_matrix[i+1,j] > 0.5: new_matrix[i+1,j] = 1 if my_matrix[i-1,j] > 0.5: new_matrix[i-1,j] = 1 if my_matrix[i+1,j+1] > 0.5: new_matrix[i+1,j+1] = 1 if my_matrix[i+1,j-1] > 0.5: new_matrix[i+1,j-1] = 1 if my_matrix[i-1,j+1] > 0.5: new_matrix[i-1,j+1] = 1 This can get really nasty if I want to step into one neighboring cell and start from it to do a similar task... Do you have some suggestions how this can be done in a more efficient manner? Is this even possible?

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  • Is it possible to auto update only selected properties on an existent entity object without touching the others

    - by LaserBeak
    Say I have a bunch of boolean properties on my entity class public bool isActive etc. Values which will be manipulated by setting check boxes in a web application. I will ONLY be posting back the one changed name/value pair and the primary key at a time, say { isActive : true , NewsPageID: 34 } and the default model binder will create a NewsPage object with only those two properties set. Now if I run the below code it will not only update the values for the properties that have been set on the NewsPage object created by the model binder but of course also attempt to null all the other non set values for the existent entity object because they are not set on NewsPage object created by the model binder. Is it possible to somehow tell entity framework not to look at the properties that are set to null and attempt to persist those changes back to the retrieved entity object and hence database ? Perhaps there's some code I can write that will only utilize the non-null values and their property names on the NewsPage object created by model binder and only attempt to update those particular properties ? [HttpPost] public PartialViewResult SaveNews(NewsPage Np) { Np.ModifyDate = DateTime.Now; _db.NewsPages.Attach(Np); _db.ObjectStateManager.ChangeObjectState(Np, System.Data.EntityState.Modified); _db.SaveChanges(); _db.Dispose(); return PartialView("MonthNewsData"); } I can of course do something like below, but I have a feeling it's not the optimal solution. Especially considering that I have like 6 boolean properties that I need to set. [HttpPost] public PartialViewResult SaveNews(int NewsPageID, bool isActive, bool isOnFrontPage) { if (isActive != null) { //Get entity and update this property } if (isOnFontPage != null) { //Get entity and update this property } }

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  • CentOS: revert python version back to original

    - by NP
    Hi all, I installed python 2.6 using the instructions here on CentOS 5.4. However I realized it was a bad move and I need to revert back to 2.4, which was there originally. Can anyone guide me on how to undo what I did here? In particular, I am not sure how to undo this: Configure ld to find your shared libs: $ cat /etc/ld.so.conf.d/opt-python2.5.conf /opt/python2.5/lib (hit enter) (hit ctrl-d to return to shell) $ ldconfig I tried removing the alias and the symlink and even re-aliasing python to /usr/bin/python, but when I try to install an RPM i get this error: error: Failed dependencies: libpython2.4.so.1.0 is needed by ... Thanks in advance.

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  • scp to remote server with sudo

    - by NP
    I have a file on server A which needs to get to server B in an area which I only have sudo access (i.e. I have a user account that has root privileges with sudo). what is the syntax for the scp command?

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  • Converting python objects for rpy2

    - by bgbg
    The following code is supposed to created a heatmap in rpy2 import numpy as np from rpy2.robjects import r data = np.random.random((10,10)) r.heatmap(data) However, it results in the following error Traceback (most recent call last): File "z.py", line 8, in <module> labRow=rowNames, labCol=colNames) File "C:\Python25\lib\site-packages\rpy2\robjects\__init__.py", line 418, in __call__ new_args = [conversion.py2ri(a) for a in args] File "C:\Python25\lib\site-packages\rpy2\robjects\__init__.py", line 93, in default_py2ri raise(ValueError("Nothing can be done for the type %s at the moment." %(type(o)))) ValueError: Nothing can be done for the type <type 'numpy.ndarray'> at the moment. From the documentation I learn that r.heatmap expects "a numeric matrix". How do I convert np.array to the required data type?

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  • How can I plot NaN values as a special color with imshow in matplotlib?

    - by Adam Fraser
    example: import numpy as np import matplotlib.pyplot as plt f = plt.figure() ax = f.add_subplot(111) a = np.arange(25).reshape((5,5)).astype(float) a[3,:] = np.nan ax.imshow(a, interpolation='nearest') f.canvas.draw() The resultant image is unexpectedly all blue (the lowest color in the jet colormap). However, if I do the plotting like this: ax.imshow(a, interpolation='nearest', vmin=0, vmax=24) --then I get something better, but the NaN values are drawn the same color as vmin... Is there a graceful way that I can set NaNs to be drawn with a special color (eg: gray or transparent)?

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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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  • Python Imaging: YCbCr problems

    - by daver
    Hi, I'm doing some image processing in Python using PIL, I need to extract the luminance layer from a series of images, and do some processing on that using numpy, then put the edited luminance layer back into the image and save it. The problem is, I can't seem to get any meaningful representation of my Image in a YCbCr format, or at least I don't understand what PIL is giving me in YCbCr. PIL documentation claims YCbCr format gives three channels, but when I grab the data out of the image using np.asarray, I get 4 channels. Ok, so I figure one must be alpha. Here is some code I'm using to test this process: import Image as im import numpy as np pengIm = im.open("Data\\Test\\Penguins.bmp") yIm = pengIm.convert("YCbCr") testIm = np.asarray(yIm) grey = testIm[:,:,0] grey = grey.astype('uint8') greyIm = im.fromarray(grey, "L") greyIm.save("Data\\Test\\grey.bmp") I'm expecting a greyscale version of my image, but what I get is this jumbled up mess: http://i.imgur.com/zlhIh.png Can anybody explain to me where I'm going wrong? The same code in matlab works exactly as I expect.

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