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  • Sort and limit queryset by comment count and date using queryset.extra() (django)

    - by thornomad
    I am trying to sort/narrow a queryset of objects based on the number of comments each object has as well as by the timeframe during which the comments were posted. Am using a queryset.extra() method (using django_comments which utilizes generic foreign keys). I got the idea for using queryset.extra() (and the code) from here. This is a follow-up question to my initial question yesterday (which shows I am making some progress). Current Code: What I have so far works in that it will sort by the number of comments; however, I want to extend the functionality and also be able to pass a time frame argument (eg, 7 days) and return an ordered list of the most commented posts in that time frame. Here is what my view looks like with the basic functionality in tact: import datetime from django.contrib.comments.models import Comment from django.contrib.contenttypes.models import ContentType from django.db.models import Count, Sum from django.views.generic.list_detail import object_list def custom_object_list(request, queryset, *args, **kwargs): '''Extending the list_detail.object_list to allow some sorting. Example: http://example.com/video?sort_by=comments&days=7 Would get a list of the videos sorted by most comments in the last seven days. ''' try: # this is where I started working on the date business ... days = int(request.GET.get('days', None)) period = datetime.datetime.utcnow() - datetime.timedelta(days=int(days)) except (ValueError, TypeError): days = None period = None sort_by = request.GET.get('sort_by', None) ctype = ContentType.objects.get_for_model(queryset.model) if sort_by == 'comments': queryset = queryset.extra(select={ 'count' : """ SELECT COUNT(*) AS comment_count FROM django_comments WHERE content_type_id=%s AND object_pk=%s.%s """ % ( ctype.pk, queryset.model._meta.db_table, queryset.model._meta.pk.name ), }, order_by=['-count']).order_by('-count', '-created') return object_list(request, queryset, *args, **kwargs) What I've Tried: I am not well versed in SQL but I did try just to add another WHERE criteria by hand to see if I could make some progress: SELECT COUNT(*) AS comment_count FROM django_comments WHERE content_type_id=%s AND object_pk=%s.%s AND submit_date='2010-05-01 12:00:00' But that didn't do anything except mess around with my sort order. Any ideas on how I can add this extra layer of functionality? Thanks for any help or insight.

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  • How to call Twiter's Streaming/Filter Feed with urllib2/httplib?

    - by Simon
    Update: I switched this back from answered as I tried the solution posed in cogent Nick's answer and switched to Google's urlfetch: logging.debug("starting urlfetch for http://%s%s" % (self.host, self.url)) result = urlfetch.fetch("http://%s%s" % (self.host, self.url), payload=self.body, method="POST", headers=self.headers, allow_truncated=True, deadline=5) logging.debug("finished urlfetch") but unfortunately finished urlfetch is never printed - I see the timeout happen in the logs (it returns 200 after 5 seconds), but execution doesn't seem tor return. Hi All- I'm attempting to play around with Twitter's Streaming (aka firehose) API with Google App Engine (I'm aware this probably isn't a great long term play as you can't keep the connection perpetually open with GAE), but so far I haven't had any luck getting my program to actually parse the results returned by Twitter. Some code: logging.debug("firing up urllib2") req = urllib2.Request(url="http://%s%s" % (self.host, self.url), data=self.body, headers=self.headers) logging.debug("called urlopen for %s %s, about to call urlopen" % (self.host, self.url)) fobj = urllib2.urlopen(req) logging.debug("called urlopen") When this executes, unfortunately, my debug output never shows the called urlopen line printed. I suspect what's happening is that Twitter keeps the connection open and urllib2 doesn't return because the server doesn't terminate the connection. Wireshark shows the request being sent properly and a response returned with results. I tried adding Connection: close to my request header, but that didn't yield a successful result. Any ideas on how to get this to work? thanks -Simon

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  • Django templates check condition

    - by Hulk
    If there are are no values in the table how can should the code be to indicate no name found else show the drop down box in the below code {% for name in dict.names %} <option value="{{name.id}}" {% for selected_id in selected_name %}{% ifequal name.id selected_id %} {{ selected }} {% endifequal %} {% endfor %}>{{name.firstname}}</option>{% endfor %} </select> Thanks..

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  • stdout and stderr anomalies

    - by momo
    from the interactive prompt: >>> import sys >>> sys.stdout.write('is the') is the6 what is '6' doing there? another example: >>> for i in range(3): ... sys.stderr.write('new black') ... 9 9 9 new blacknew blacknew black where are the numbers coming from?

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  • Google App Engine + Form Validation

    - by Iwona
    Hi, I would like to do google app engine form validation but I dont know how to do it? I tried like this: from google.appengine.ext.db import djangoforms from django import newforms as forms class SurveyForm(forms.Form): occupations_choices = ( ('1', ""), ('2', "Undergraduate student"), ('3', "Postgraduate student (MSc)"), ('4', "Postgraduate student (PhD)"), ('5', "Lab assistant"), ('6', "Technician"), ('7', "Lecturer"), ('8', "Other" ) ) howreach_choices = ( ('1', ""), ('2', "Typed the URL directly"), ('3', "Site is bookmarked"), ('4', "A search engine"), ('5', "A link from another site"), ('6', "From a book"), ('7', "Other") ) boxes_choices = ( ("des", "Website Design"), ("svr", "Web Server Administration"), ("com", "Electronic Commerce"), ("mkt", "Web Marketing/Advertising"), ("edu", "Web-Related Education") ) name = forms.CharField(label='Name', max_length=100, required=True) email = forms.EmailField(label='Your Email Address:') occupations = forms.ChoiceField(choices=occupations_choices, label='What is your occupation?') howreach = forms.ChoiceField(choices=howreach_choices, label='How did you reach this site?') # radio buttons 1-5 rating = forms.ChoiceField(choices=range(1,6), label='What is your occupation?', widget=forms.RadioSelect) boxes = forms.ChoiceField(choices=boxes_choices, label='Are you involved in any of the following? (check all that apply):', widget=forms.CheckboxInput) comment = forms.CharField(widget=forms.Textarea, required=False) And I wanted to display it like this: template_values = { 'url' : url, 'url_linktext' : url_linktext, 'userName' : userName, 'item1' : SurveyForm() } And I have this error message: Traceback (most recent call last): File "C:\Program Files\Google\google_appengine\google\appengine\ext\webapp_init_.py", line 515, in call handler.get(*groups) File "C:\Program Files\Google\google_appengine\demos\b00213576\main.py", line 144, in get self.response.out.write(template.render(path, template_values)) File "C:\Program Files\Google\google_appengine\google\appengine\ext\webapp\template.py", line 143, in render return t.render(Context(template_dict)) File "C:\Program Files\Google\google_appengine\google\appengine\ext\webapp\template.py", line 183, in wrap_render return orig_render(context) File "C:\Program Files\Google\google_appengine\lib\django\django\template_init_.py", line 168, in render return self.nodelist.render(context) File "C:\Program Files\Google\google_appengine\lib\django\django\template_init_.py", line 705, in render bits.append(self.render_node(node, context)) File "C:\Program Files\Google\google_appengine\lib\django\django\template_init_.py", line 718, in render_node return(node.render(context)) File "C:\Program Files\Google\google_appengine\lib\django\django\template\defaulttags.py", line 209, in render return self.nodelist_true.render(context) File "C:\Program Files\Google\google_appengine\lib\django\django\template_init_.py", line 705, in render bits.append(self.render_node(node, context)) File "C:\Program Files\Google\google_appengine\lib\django\django\template_init_.py", line 718, in render_node return(node.render(context)) File "C:\Program Files\Google\google_appengine\lib\django\django\template_init_.py", line 768, in render return self.encode_output(output) File "C:\Program Files\Google\google_appengine\lib\django\django\template_init_.py", line 757, in encode_output return str(output) File "C:\Program Files\Google\google_appengine\lib\django\django\newforms\util.py", line 26, in str return self.unicode().encode(settings.DEFAULT_CHARSET) File "C:\Program Files\Google\google_appengine\lib\django\django\newforms\forms.py", line 73, in unicode return self.as_table() File "C:\Program Files\Google\google_appengine\lib\django\django\newforms\forms.py", line 144, in as_table return self._html_output(u'%(label)s%(errors)s%(field)s%(help_text)s', u'%s', '', u'%s', False) File "C:\Program Files\Google\google_appengine\lib\django\django\newforms\forms.py", line 129, in _html_output output.append(normal_row % {'errors': bf_errors, 'label': label, 'field': unicode(bf), 'help_text': help_text}) File "C:\Program Files\Google\google_appengine\lib\django\django\newforms\forms.py", line 232, in unicode value = value.str() File "C:\Program Files\Google\google_appengine\lib\django\django\newforms\util.py", line 26, in str return self.unicode().encode(settings.DEFAULT_CHARSET) File "C:\Program Files\Google\google_appengine\lib\django\django\newforms\widgets.py", line 246, in unicode return u'\n%s\n' % u'\n'.join([u'%s' % w for w in self]) File "C:\Program Files\Google\google_appengine\lib\django\django\newforms\widgets.py", line 238, in iter yield RadioInput(self.name, self.value, self.attrs.copy(), choice, i) File "C:\Program Files\Google\google_appengine\lib\django\django\newforms\widgets.py", line 212, in init self.choice_value = smart_unicode(choice[0]) TypeError: 'int' object is unsubscriptable Do You have any idea how I can do this validation in different case? I have tried to do it using this kind of: class ItemUserAnswer(djangoforms.ModelForm): class Meta: model = UserAnswer But I dont know how to add extra labels to this form and it is displayed in one line. Do You have any suggestions? Thanks a lot as it making me crazy why it is still not working:/

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  • cannot output a json encoded dict containing accents (noob inside)

    - by user296546
    Hi all, here is a fairly simple example wich is driving me nuts since a couple of days. Considering the following script: # -*- coding: utf-8 -* from json import dumps as json_dumps machaine = u"une personne émérite" print(machaine) output = {} output[1] = machaine jsonoutput = json_dumps(output) print(jsonoutput) The result of this from cli: une personne émérite {"1": "une personne \u00e9m\u00e9rite"} I don't understand why their such a difference between the two strings. i have been trying all sorts of encode, decode etc but i can't seem to be able to find the right way to do it. Does anybody has an idea ? Thanks in advance. Matthieu

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  • Writing a blocking wrapper around twisted's IRC client

    - by Andrey Fedorov
    I'm trying to write a dead-simple interface for an IRC library, like so: import simpleirc connection = simpleirc.Connect('irc.freenode.net', 6667) channel = connection.join('foo') find_command = re.compile(r'google ([a-z]+)').findall for msg in channel: for t in find_command(msg): channel.say("http://google.com/search?q=%s" % t) Working from their example, I'm running into trouble (code is a bit lengthy, so I pasted it here). Since the call to channel.__next__ needs to be returned when the callback <IRCClient instance>.privmsg is called, there doesn't seem to be a clean option. Using exceptions or threads seems like the wrong thing here, is there a simpler (blocking?) way of using twisted that would make this possible?

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  • Group Chat XMPP with Google App Engine

    - by David Shellabarger
    Google App Engine has a great XMPP service built in. One of the few limitations it has is that it doesn't support receiving messages from a group chat. That's the one thing I want to do with it. :( Can I run a 3rd party XMPP/Jabber server on App Engine that supports group chat? If so, which one?

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  • Reliable and fast way to convert a zillion ODT files in PDF?

    - by Marco Mariani
    I need to pre-produce a million or two PDF files from a simple template (a few pages and tables) with embedded fonts. Usually, I would stay low level in a case like this, and compose everything with a library like ReportLab, but I joined late in the project. Currently, I have a template.odt and use markers in the content.xml files to fill with data from a DB. I can smoothly create the ODT files, they always look rigth. For the ODT to PDF conversion, I'm using openoffice in server mode (and PyODConverter w/ named pipe), but it's not very reliable: in a batch of documents, there is eventually a point after which all the processed files are converted into garbage (wrong fonts and letters sprawled all over the page). Problem is not predictably reproducible (does not depend on the data), happens in OOo 2.3 and 3.2, in Ubuntu, XP, Server 2003 and Windows 7. My Heisenbug detector is ticking. I tried to reduce the size of batches and restarting OOo after each one; still, a small percentage of the documents are messed up. Of course I'll write about this on the Ooo mailing lists, but in the meanwhile, I have a delivery and lost too much time already. Where do I go? Completely avoid the ODT format and go for another template system. Suggestions? Anything that takes a few seconds to run is way too slow. OOo takes around a second and it sums to 15 days of processing time. I had to write a program for clustering the jobs over several clients. Keep the format but go for another tool/program for the conversion. Which one? There are many apps in the shareware or commercial repositories for windows, but trying each one is a daunting task. Some are too slow, some cannot be run in batch without buying it first, some cannot work from command line, etc. Open source tools tend not to reinvent the wheel and often depend on openoffice. Converting to an intermediate .DOC format could help to avoid the OOo bug, but it would double the processing time and complicate a task that is already too hairy. Try to produce the PDFs twice and compare them, discarding the whole batch if there's something wrong. Although the documents look equal, I know of no way to compare the binary content. Restart OOo after processing each document. it would take a lot more time to produce them it would lower the percentage of the wrong files, and make it very hard to identify them. Go for ReportLab and recreate the pages programmatically. This is the approach I'm going to try in a few minutes. Learn to properly format bulleted lists Thanks a lot.

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  • VS2010 patce: why it's take so muce time to install it?

    - by Mendy
    Visual Studio 2010 RC has a few of patches release. For more information about them take a look here. What I'm expect from patch program, is to replace a few dll's of the program to a new fixed version of them. But when I run each of this 3 patches, they take a lot of time (5 minutes each), and you think that the program was frozen because the progress bar stay on the begging. This is question may not be so important, but it really interesting me to know, why this happens? It's really confusing to see that each VS2010 (or Microsoft in general) is frozen to 4-5 minutes.

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  • Perceptron Classification and Model Training

    - by jake pinedo
    I'm having an issue with understanding how the Perceptron algorithm works and implementing it. cLabel = 0 #class label: corresponds directly with featureVectors and tweets for m in range(miters): for point in featureVectors: margin = answers[cLabel] * self.dot_product(point, w) if margin <= 0: modifier = float(lrate) * float(answers[cLabel]) modifiedPoint = point for x in modifiedPoint: if x != 0: x *= modifier newWeight = [modifiedPoint[i] + w[i] for i in range(len(w))] w = newWeight self._learnedWeight = w This is what I've implemented so far, where I have a list of class labels in answers and a learning rate (lrate) and a list of feature vectors. I run it for the numbers of iterations in miter and then get the final weight at the end. However, I'm not sure what to do with this weight. I've trained the perceptron and now I have to classify a set of tweets, but I don't know how to do that. EDIT: Specifically, what I do in my classify method is I go through and create a feature vector for the data I'm given, which isn't a problem at all, and then I take the self._learnedWeight that I get from the earlier training code and compute the dot-product of the vector and the weight. My weight and feature vectors include a bias in the 0th term of the list so I'm including that. I then check to see if the dotproduct is less than or equal to 0: if so, then I classify it as -1. Otherwise, it's 1. However, this doesn't seem to be working correctly.

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  • JSON serialization of Google App Engine models

    - by user111677
    I've been search for quite a while with no success. My project isn't using Django, is there a simple way to serialize App Engine models (google.appengine.ext.db.Model) into JSON or do I need to write my own serializer? My model class is fairly simple. For instance: class Photo(db.Model): filename = db.StringProperty() title = db.StringProperty() description = db.StringProperty(multiline=True) date_taken = db.DateTimeProperty() date_uploaded = db.DateTimeProperty(auto_now_add=True) album = db.ReferenceProperty(Album, collection_name='photo') Thanks in advance.

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  • Django: How to create a model dynamically just for testing

    - by muhuk
    I have a Django app that requires a settings attribute in the form of: RELATED_MODELS = ('appname1.modelname1.attribute1', 'appname1.modelname2.attribute2', 'appname2.modelname3.attribute3', ...) Then hooks their post_save signal to update some other fixed model depending on the attributeN defined. I would like to test this behaviour and tests should work even if this app is the only one in the project (except for its own dependencies, no other wrapper app need to be installed). How can I create and attach/register/activate mock models just for the test database? (or is it possible at all?) Solutions that allow me to use test fixtures would be great.

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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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  • Added tagging to existing model, now how does its admin work?

    - by Oli
    I wanted to add a StackOverflow-style tag input to a blog model of mine. This is a model that has a lot of data already in it. class BlogPost(models.Model): # my blog fields try: tagging.register(BlogPost) except tagging.AlreadyRegistered: pass I thought that was all I needed so I went through my old database of blog posts (this is a newly ported blog) and copied the tags in. It worked and I could display tags and filter by tag. However, I just wrote a new BlogPost and realise there's no tag field there. Reading the documentation (coincidentally, dry enough to be used as an antiperspirant), I found the TagField. Thinking this would just be a manager-style layer over the existing tagging register, I added it. It complained about there not being a Tag column. I'd rather not denormalise on tags just to satisfy create an interface for inputting them. Is there a TagManager class that I can just set on the model? tags = TagManager() # or somesuch

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  • socket.shutdown vs socket.close

    - by Jason Baker
    I recently saw a bit of code that looked like this (with sock being a socket object of course): sock.shutdown(socket.SHUT_RDWR) sock.close() What exactly is the purpose of calling shutdown on the socket and then closing it? If it makes a difference, this socket is being used for non-blocking IO.

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  • do I need to use partial?

    - by wiso
    I've a general function, for example (only a simplified example): def do_operation(operation, a, b, name): print name do_something_more(a,b,name, operation(a,b)) def operation_x(a,b): return a**2 + b def operation_y(a,b): return a**10 - b/2. and some data: data = {"first": {"name": "first summation", "a": 10, "b": 20, "operation": operation_x}, "second": {"name": "second summation", "a": 20, "b": 50, "operation": operation_y}, "third": {"name": "third summation", "a": 20, "b": 50, "operation": operation_x}, # <-- operation_x again } now I can do: what_to_do = ("first", "third") # this comes from command line for sum_id in what_to_do: do_operation(data["operation"], data["a"], data["b"], data["name"]) or maybe it's better if I use functools.partial? from functools import partial do_operation_one = do_operation(name=data["first"]["name"], operation=data["first"]["operation"], a=data["first"]["a"], b=data["first"]["b"]) do_operation_two = do_operation(name=data["second"]["name"], operation=data["second"]["operation"] a=data["second"]["a"], b=data["second"]["b"]) do_operation_three = do_operation(name=data["third"]["name"], operation=data["third"]["operation"] a=data["third"]["a"], b=data["third"]["b"]) do_dictionary = { "first": do_operation_one, "second": do_operation_two, "third": do_operation_three } for what in what_to_do: do_dictionary[what]()

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  • Graphing a line and scatter points using Matplotlib?

    - by Patrick O'Doherty
    Hi guys I'm using matplotlib at the moment to try and visualise some data I am working on. I'm trying to plot around 6500 points and the line y = x on the same graph but am having some trouble in doing so. I can only seem to get the points to render and not the line itself. I know matplotlib doesn't plot equations as such rather just a set of points so I'm trying to use and identical set of points for x and y co-ordinates to produce the line. The following is my code from matplotlib import pyplot import numpy from pymongo import * class Store(object): """docstring for Store""" def __init__(self): super(Store, self).__init__() c = Connection() ucd = c.ucd self.tweets = ucd.tweets def fetch(self): x = [] y = [] for t in self.tweets.find(): x.append(t['positive']) y.append(t['negative']) return [x,y] if __name__ == '__main__': c = Store() array = c.fetch() t = numpy.arange(0., 0.03, 1) pyplot.plot(array[0], array[1], 'ro', t, t, 'b--') pyplot.show() Any suggestions would be appreciated, Patrick

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  • SQL Alchemy MVC and cross controller joins

    - by Khorkrak
    When using SQL Alchemy for abstracting your data access layer and using controllers as the way to access objects from that abstraction layer, how should joins be handled? So for example, say you have an Orders controller class that manages Order objects such that it provides getOrder, saveOrder, etc methods and likewise a similar controller for User objects. First of all do you even need these controllers? Should you instead just treat SQL Alchemy as "the" thing for handling data access. Why bother with object oriented controller stuff there when you instead have a clean declarative way to obtain and persist objects without having to write SQL directly either. Well one reason could be that perhaps you may want to replace SQL Alchemy with direct SQL or Storm or whatever else. So having controller classes there to act as an intermediate layer helps limit what would need to change then. Anyway - back to the main question - so assuming you have these two controllers, now lets say you want the list of orders for a certain set of users meeting some criteria. How do you go about doing this? Generally you don't want the controllers crossing domains - the Orders controllers knows only about Orders and the User controller just about Users - they don't mess with each other. You also don't want to go fetch all the Users that match and then feed a big list of user ids to the Orders controller to go find the matching Orders. What's needed is a join. Here's where I'm stuck - that seems to mean either the controllers must cross domains or perhaps they should be done away with altogether and you simply do the join via SQL Alchemy directly and get the resulting User and / or Order objects as needed. Thoughts?

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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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