I’ve met following statement in python numpy library Z = inputs @ self.weights[1:].T + + self.weights[0] I don’t understand exactly what does it mean in this line of code I’ve made researchtations and did not found proper explanation >Solution : There is no + + operator in Python. This is two separate operators, the unary… Read More what does mean + + operator in python numpy
I have a data frame containing two parameters, val1 and val2. val1 represents a point in a spectrum val2 the measured level of this point Now I want to cluster this spectrum with the following logic: Compare val1 with the previous value. If previous_row >= 1.3 * val1 | previous_row <= 0.7 * val1 it’s… Read More Calculate clusters within a spectrum
I have a pandas.DataFrame as given below you can read it as pd.DataFrame(data_dict): data_dict = {‘Elevation’: {0: 0, 1: 0, 2: 0, 3: 0, 4: 0, 5: 1, 6: 1, 7: 1, 8: 1, 9: 1}, ‘Azimuth’: {0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 0, 6: 1, 7: 2, 8: 3,… Read More Convert pandas Dataframe to 3D numpy matrix
I have a numpy array (shape : (256, 256, 3)) of image and I have numpy array for indexing as below. array([[ 3, 230], [ 3, 231], [ 3, 232], …, [114, 151], [115, 149], [115, 150]], dtype=int64) However, I want to get values of numpy array (shape : (256, 256, 3)) of image for… Read More How can I get values of specific indexes for numpy array?
I want have an array X, and I want to select, for example, the 1st, 5th, 7th, and all of the last 1000 columns (non-overlapping). I know I can get the 1st, 5th, 7th columns using X[:, [0,4,6]] and the last 1000 columns by X[:, -1000:]. But is there a quick and easy way to… Read More Python – Select a complex subset of columns from a np.array
I am trying to compare two lists of odds from two bookmakers. They look like this: List1 = [‘2.66’, ‘3.79’, ‘1.88’, ‘1.61’, ‘2.51’, ‘1.29’, ‘2.29’, ‘2.56’, ‘3.16’, ‘2.05’, ‘2.95’, ‘2.64’, ‘2.26’, ‘3.17’, ‘2.64’, ‘2.25’] List2 = [‘2.70’, ‘4.40’, ‘1.87’, ‘1.56’, ‘2.50’, ‘1.26’, ‘2.33’, ‘2.60’, ‘3.20’, ‘2.04’, ‘3.00’, ‘2.65’, ‘2.25’, ‘3.20’, ‘2.65’, ‘2.22’] I need to… Read More how to merge two lists and get names of lists with the highest value for each index?
When we call vectorized function for some vector, for some reason it is called twice for the first vector element. What is the reason, and can we get rid of this strange effect (e.g. when this function needs to have some side effect, e.g. counts some sum etc) Example: import numpy @numpy.vectorize def test(x): print(x)… Read More Why numpy.vectorize calls vectorized function more times than elements in the vector?
Let’s say I have an array of years created like years = np.arange(2024,2051,1) And I have an array of months created like months = np.arange(1,13,1) What is the most pythonic way of arriving at an elementwise concatenation such that the end result is [[2024,1],[2024,2],[2024,3]…[2024,12], [2025,1],[2025,2],[2025,3]…[2025,12], … ] ? Thanks >Solution : I’d say the most… Read More Elementwise insertion of array into array using numpy
I have numpy array with some values.I want the points with value 2,3 and 7 will remain same but others value will be nan. original nympy array looks like this [[0, 7, 2, …, 1, 6, 0], [5, 3, 0, …, 2, 5, 0], …, [8, 2, 0, …, 1, 0, 7], [0, 3, 2,… Read More how to set nan values to numpy array with multiple condition
I recently found a bug in my code that I was able to fix by replacing np.divide(x, y) with x / y. I was under the impression that np.divide(x, y) was equivalent to x / y (it says as much in the numpy documentation). Is this a bug in numpy or is it expected behaviour?… Read More What's the difference between np.divide(x, y) and x/y in Python3?