After doing some processing on an audio or image array, it needs to be normalized within a range before it can be written back to a file. This can be done like so: # Normalize audio channels to between -1.0 and +1.0 audio[:,0] = audio[:,0]/abs(audio[:,0]).max() audio[:,1] = audio[:,1]/abs(audio[:,1]).max() # Normalize image to between 0 and … Read more
Closed. This question is opinion-based. It is not currently accepting answers. Want to improve this question? Update the question so it can be answered with facts and citations by editing this post. Closed 6 years ago. Improve this question They both seem exceedingly similar and I’m curious as to which package would be more beneficial … Read more
It is possible to install NumPy with pip using pip install numpy. Is there a similar possibility with SciPy? (Doing pip install scipy does not work.) Update The package SciPy is now available to be installed with pip! 15 Answers 15
I have a set of data and I want to compare which line describes it best (polynomials of different orders, exponential or logarithmic). I use Python and Numpy and for polynomial fitting there is a function polyfit(). But I found no such functions for exponential and logarithmic fitting. Are there any? Or how to solve … Read more
Say I have an image of size 3841 x 7195 pixels. I would like to save the contents of the figure to disk, resulting in an image of the exact size I specify in pixels. No axis, no titles. Just the image. I don’t personally care about DPIs, as I only want to specify the … Read more
Using standard Python arrays, I can do the following: arr = [] arr.append([1,2,3]) arr.append([4,5,6]) # arr is now [[1,2,3],[4,5,6]] However, I cannot do the same thing in numpy. For example: arr = np.array([]) arr = np.append(arr, np.array([1,2,3])) arr = np.append(arr, np.array([4,5,6])) # arr is now [1,2,3,4,5,6] I also looked into vstack, but when I use … Read more
I am looking for a function that takes as input two lists, and returns the Pearson correlation, and the significance of the correlation. 17 Answers 17
I know I could implement a root mean squared error function like this: def rmse(predictions, targets): return np.sqrt(((predictions – targets) ** 2).mean()) What I’m looking for if this rmse function is implemented in a library somewhere, perhaps in scipy or scikit-learn? 14 Answers 14
Is there a SciPy function or NumPy function or module for Python that calculates the running mean of a 1D array given a specific window? 30 Answers 30
Lets assume we have a dataset which might be given approximately by import numpy as np x = np.linspace(0,2*np.pi,100) y = np.sin(x) + np.random.random(100) * 0.2 Therefore we have a variation of 20% of the dataset. My first idea was to use the UnivariateSpline function of scipy, but the problem is that this does not … Read more
