I am searching for a lib that helps me to use many sound properties.
I mean, I need something to get each frequency of sounds, get the sound waves length and width, get the peak and trough (in a measurement way) of the sounds.
I need something that leads me as close as possible to manipulate and measure sounds waves in some ways, this is something that I need more for a scientific research than for an application.
It is hard to find something like that, If you could help me with some links or anything, would be a great help for me.
If you have something even in other languages, it could help me.
I will keep this question updated as I find answers as well.
Thanks in advance.
The Python wiki page PythonInMusic has a lot of links, some of which will probably be useful to you. It includes a whole range of projects to input and output sound in different formats. A quick glance shows a couple of more specialised projects that might also be helpful:
audiolab - bridges the gap between numpy and sound formats
musickit - support for signal processing, and apparently used in 'scientific experiments'
These will probably give you the tools to read sounds in and convert them into a useful form for analysis.
After that, it seems to me that what you are describing is more about signal/waveform analysis, than sound per se, so that may be a more helpful direction to search in. I'm not aware of any Python package that does exactly what you're looking for. Measurement of things like wavelength, peak and trough doesn't sound particularly difficult to me though - you could look at coding your own routines for this using SciPy.
Related
I have following scenario:
I want to have a vector field simulation which shows the current of a fluid, lets say water. This current produces a certain noise, which can change when a solid object is submerged into the current.
Is there a way to somehow attach this noise/sound to the visuals of VTK?
I am not really experienced with VTK, so any point in the right direction is appreciated.
Thanks in advance!
This is a pretty general question on an esoteric topic. A good first step in these cases is to do a scientific journal review to see what researchers have attempted before, what tools they used and what success they had. After a quick search I found a few relevant journals that cover generating sound from simulations/data.
Sounding liquids: Automatic sound synthesis from fluid simulation
Visual to Sound: Generating Natural Sound for Videos in the Wild
Auditory Display and the VTK Sonification Toolkit
Listen to your data: Model-based sonification for data analysis
After reviewing these, you'll have a better idea of what's already been attempted and what's possible.
I have a project in which I should analyze the layout of a building in order to navigate inside it, and I was thinking about taking the blueprint of the building (or maybe an edited version of the blueprint, which should be modified in some way I am still thinking of), transforming it in some kind of object and then elaborate it.
Basically, I was thinking about doing something similar to OCR but limited (and I guess using limited sounds pretty silly to most of you, but still bear with me) to recognition of, for example, walls and doors. My idea was transforming the whole image into a matrix of points - I guess, a lower resolution version of the source - and then elaborating over the matrix the route from point A to point B.
This is the idea, but I guess that I'm actually looking at a problem way more complex than it looks to me, moreover I don't really know whether this is the best (read: easiest) way to proceed.
In short, my question is:
Is this framework feasible? Are there any libraries for, say, Python, with similar functions? Is the recognition doable by working in someway with a graphic design software (e.g. Photoshop)?
I'm the "programmer" of a team of pupils that aims to investigate satisfaction and general problems in my grammar school. We have a questionary that is built upon a scale from 1-6 and we interpret these answers by a diagram software that I wrote in python.
Now there's a <textarea> at the end of our questionary that one can use as he likes.
I'm currently thinking of ways to make this data usable (we don't want to read more than 800+ answers).
How can I use text analysis in Python to investigate what pupils write?
I was thinking of a way to "tag" any sentence that is written down, like:
I don't like being in school. [wellbeing][negative]
I have way too much homework. [homework][much]
I think there should be more interesting projects. [projects][more]
Are there any usable approaches to obtain that? Does it make sense to use an existing tokenizer?
Thanks for your help!
well, I am just throwing in ideas here..but one approach I can think of is,
to use a clustering algorithm to cluster the responses first. something like K-means
or you can do topic modelling using something like LDA.
Then you can use your tagging approach by doing text analysis to generate frequent/related keywords in each of the cluster/topic you get from step 1.
Why Step 1 would be a good idea? Well, in my opinion- while doing text analysis, if you arbitrarly go around tagging sentences, you could generate a lot of tags- a lot of them would be similar in context. Hence, your usability might go down that you still would have to analyze loads of tags for each sentence.
Using a clustering/topic modelling can help reduce the context problem to some level as well. Hence, more usable in my opinion.
"NLTK Sentiment Analysis" is a good place to start searching. The Natural Language Toolkit is the package for doing text analysis in Python but it is not exactly simple because the task is quite complex. The first few results had some compelling demos but I didn't look at them in detail.
I won't quite answer to your question. But if I understand you have a classic survey (with check boxes, ...) with a small text area question at the end...
So you will have about 800+ answers. But I guess the answers will not be too long. Usually it will a few lines or even a few words... I think that a manual QDA software will be better than an algorithms that won't be perfect. For instance you can use the open source RQDA (R project package) or commercials software such as Nvivio...
Thanks
This sounds a lot like AI programming just because of the way that they 'tag' questions and responses. Maybe take a look at http://pyaiml.sourceforge.net/ and the artificial intelligence markup language. I don't have much experience with it, but you might be able to tweak it to your needs instead of doing it from scratch.
I have a large number of GIS (latitude, longitude) coordinates, and I'd like to get the distance between them. Is there a service that will calculate the shortest path for me? I know about google maps, but I'd like something I can use from Python, and that can handle a large batch of requests at once.
I'm looking for the driving distance, so a straight distance won't do.
Thanks
So I take it based on your question and the answers posted that you are asking what program to use? If you can find a way to get a copy for free or cheap (like through work, school, etc) I'd recommend ArcGIS 9.x. It has its quirks, but it's highly supported by the user community and there are a lot of forums and help/training books available for it. Also, they have adopted Python as their official scripting language for the program (Sweeeet!).
Another option that is less expensive is GRASS. It's a free, open-source, well established, powerful and multiplatform GIS program. It might have a bit steeper learning-curve than ArcGIS, but I've heard very good things about it considering it's a free program.
This website lists info on free, open-source (FOS) GIS programs http://opensourcegis.org/ and could give you some good info on your other choices.
I couldn't tell if you were asking a question about how to measure the distance between two points and finding shortest travel distances in a GIS program or if you were just mentioning that's the kind of stuff you would need to do. Either way, ArcGIS is well suited for those tasks. Some of the tools in ArcGIS's ArcToolbox already have commands to help you find optimal transportation routes. This link lets you explore some of the tools available ArcToolbox Help. Most of the tools in ArcToolbox have a GUI batch processing option automatically included as well. Measuring point to point distances on an individual basis is easy in ArcGIS, and if you needed to measure a bunch of point to point pairs, you could write a quick Python script to easily do it for you.
I think I've answered all of your questions. Feel free to let me know if there is something I missed or that doesn't make sense. Hope this helps, buddy.
Check out OpenStreetMap. You can download their map data and have it lying around on your local system. http://wiki.openstreetmap.org/wiki/Routing discusses the various routing systems for their data.
You are aware that the traveling salesman problem is np-complete?
using Qgis:
Use the delimited text plugin to import the data
save the import as a shape file
Open the shape file
using the ftools plugin, calculate the matrix distance
If you have interconnections between the points you could use Dijkstra's algorithm for a 'shortest path from a single point' or Floyd's algorithm for an 'all pairs' shortest path computation.
Neither are particularly complicated, however they do assume you know the lengths of the roads between the points. You will need to have this data to compute a driving distance.
I took a scientific programming course this semester that I really enjoyed and experimented with a lot. We used python, and all the related modules. I am taking a physics lab next semester and I just wanted to hear from some of you how python can help me in ways that excel can't or in ways that are better than excel's capabilities. I use Mathematica for symbolic stuff so I would use python for data purposes.
Off the top of my head, here are the related things I can do:
All of the things you would expect in a intro course (loops, arrays, slicing arrays, etc).
Reading data from a text file.
Plotting scatter, line, and bar graphs.
Learning how to plot linear regression but haven't totally figured it out.
I have done 7 of the problems on Project Euler (nothing to brag about, but it might give you a better idea of where I stand in skills).
Looking forward to hearing from some of you. You don't have to explain how to use the things you mention, I could look up the documentation.
The paper Python all a scientist needs comes to mind. I hope you can make the needed transformations from Biology to Physics.
Scipy will also be useful to you, as it includes many more advanced analysis tools. For example, Scipy includes a linear regression, and gets more interesting from there. Along with the other tools you mentioned, you'll probably find most of your needs covered.
Other notes on tool selection:
Mathematica is a great tool, if you can afford it. I've played around with the other options, like Sympy, and sadly, they don't come close to being as useful as Mathematica.
I can't imagine using Excel for any serious scientific work. If you're planning to continue forward using the tools that you learn in class, you might as well start with tools that offer you that potential.
Don't reject Excel outright. It's still great for doing simple data analysis and plotting. Excel also has the considerable advantage of being installed on most engineer and scientist's computers, making it a lot easier to share your work with colleagues.
That said, I do use Python when Excel just won't cut it; times when I've had to:
color the points in a scatter plot based on a third column
plot a field of vectors
extract a few values from each of several thousand data files to do statistical process control
generate dozens of scatter plots over different dimensions of a large data set to find which variables are important
solve a nonlinear equation at several intermediate points of a calculation, not just as the final result.
accept variable length input from a user to define a problem
VBA in Excel can do a lot of those things too, but it becomes painful fast in such a primitive language. I dream that Microsoft will make IronPython a first-class scripting language in the next version of Excel. Until then, you might want to try Resolver One
I can recall 2 presentations by Jan Martinek on EuroScipy 2008, he's PhD candidate and presented some fun experiments with Physics in the background. Abstracts are here and I'm sure he would't mind to share more if you contact him directly. Also, take a look at other presentation from EuroScipy, there are some more Physics-related ones.