Is there a way to create a 200x200 numpy array containing a circle with a radius of 80, centered at coordinates (100,100), and a stroke width of 3 pixels in Python 2.7 without using file operations? I am looking for a solution that utilizes geometry or i ...
Currently, I am faced with a challenge involving a 3D array of shape (3, 4, 3) and a 2D array of shape (3, 3). My objective is to multiply these arrays in such a way that the ith element of the resulting 3D array corresponds to the product of the ith eleme ...
I am facing a challenge with two arrays in my coding project. Array A represents 3124 models with 5 reference parameters, while array B represents 3124 models, 19 time steps per model, and 12288 temperature field data points per time step. My goal is to a ...
After successfully calibrating the camera using Matlab 2019a, I saved all the camera parameters in a variable called cameraParams. However, I am specifically interested in extracting the Intrinsic matrix and distortion coefficients from this data. How c ...
Being new to Python and its libraries like numpy and pandas, I have come across a plethora of documentation explaining how numpy ndarrays, pandas series, and python dictionaries operate. Despite this, my lack of experience with Python has made it challeng ...
I have developed a deep learning model to segment CT scans. The process involves reading the scan as a .nrrd file in python and converting it to a numpy array for training the model. After successfully predicting a numpy array with the model, I encounter ...
My dataset named temp is a timeseries data with 4 columns: Date, Minutes, Issues, Reason no. In this dataset: temp['REASON NO'].value_counts() produces the following output: R13 158 R14 123 R4 101 R7 81 R2 40 R3 35 R5 31 R8 ...
Consider having a 3D numpy array like the one below: matrices= numpy.array([[[1, 0, 0], #Level 0 [1, 1, 1], [0, 1, 1]], [[0, 1, 0], #Level 1 [1, 1, 0], [0, 0, 0]], [[0, 0, ...
I have a 100x100x100 numpy array that represents a 3D volume composed of 2D slices. My goal is to conduct cross correlation on the object in this volume across multiple volumes using a template derived from the volume with the best signal-to-noise ratio. ...
I am facing an issue with a code snippet that is supposed to generate a zero matrix based on a given size (m x n). However, my goal is to extract a specific value from a particular location within that matrix. Despite trying numerous approaches, I have not ...
I've encountered an issue while training a neural network using keras and tensorflow. Typically, I replace -np.inf and np.inf values with np.nan in order to clean up erroneous data before proceeding with operations such as: Data.replace([np.inf, -np. ...
import numpy as np File "/home/anirrudh/.virtualenvs/ml4t2/local/lib/python2.7/site-packages/numpy/__init__.py", line 180, in <module> from . import add_newdocs File "/home/anirrudh/.virtualenvs/ml4t2/local/lib/python2.7/site-packages/numpy/a ...
Below is the data that I am working with: 49907 87063 42003 51519 21301 46100 97578 26010 52364 86618 25783 71775 1617 29096 2662 47428 74888 54550 17182 35976 86973 5323 ...... My goal is to iterate through it using for line in file. I would like to s ...
Is there a way to enhance my password cracker function by utilizing numpy arrays instead of for-loops? How can I prevent the error shown in the code image while implementing improvements to my cracker function? Here is the code snippet for reference I a ...
I needed to determine the number of series contained within a specific dataset. The count of time-series information was required for analysis. https://i.stack.imgur.com/VHQvw.png Within this context, I wanted users to select how they wished to analyze ...
I am searching for a way to streamline the process of reconciling bank transactions. In this scenario, there are two tables - one from the bank and one from the system. However, there is a delay of a few days in the transactions recorded in the system tabl ...
I am faced with a challenge in Python. I have a matrix that needs to be returned with a specific rule applied. The rule states that if there are any elements in the matrix that are less than zero, their values must be multiplied by a constant before return ...
Currently, I am looping through a numpy array and performing a search operation which is taking approximately 60 seconds to complete for arrays (npArray1 and npArray2 in the sample code) containing around 300,000 values. To elaborate, I am seeking the ind ...
I need help transforming comma-delimited strings in a given pandas dataframe into separate rows. For example: COLUMN_1 COLUMN_2 COLUMN_3 "Marvel" "Hulk, Thor, Ironman" "1,7,8" "DC" ...
I am faced with two medium-sized datasets that are structured as follows: books_df.head() ISBN Book-Title Book-Author 0 0195153448 Classical Mythology Mark P. O. Morford 1 0002005018 Clara Callan Richard Bruce Wright 2 0060973129 ...
My aim with matplotlib is to create a scatter plot where both markers and colors vary. import matplotlib.pyplot as plt import numpy as np markers = np.array(["1","2","3","4","+",">"]) # Sample Data x = np.array([0, 2, 3, 4, 0, 1, 5, 6, 7, 8]) y = np.a ...
Consider two numpy arrays a and w, both with the same shape (d1,d2,..,dk,N). We can view them as N samples with shape (d1,d2,...,dk). Now, the goal is to sort arrays a and w along a's last axis. For instance, if a and w have a shape of (2,4): a = [[ ...
I need to pad the following array: [[1, 2] [3, 4]] so that it becomes: [[0, 0, 0] [0, 1, 2] [0, 3, 4]] I can easily achieve this with vstack and hsrack when working with a 2D input. However, I encounter an issue when adding an extra dimension to re ...
I am curious to estimate the worst-case scenario of an algorithm that relies on the number of iterations based on how many pixels in an image have neighboring pixels with differing values. Assuming the image is grayscale, I am seeking a method to create an ...
It seems like I might be making a mistake somewhere. I'm currently working on a project in Pycharm and when using the ndarray.max() function, a notification popped up saying that initial was undefined (parameter 'initial' unfilled). Checking the documentat ...
I need help with using NumPy broadcasting to calculate Rij = Aij x Bji/Cij. I also want to include an exception if the matrices are not the same size (n × n). Not sure if my approach is correct or if I should be performing element-wise or matrix-wise ope ...
In my dataset, there is a column labeled "brand" with different values: brand Brand1 Brand2 Brand3 data.brand = data.brand.astype(str) data.brand = data.brand.replace(r'^\s*$', np.nan, regex=True) data['branded'] ...
A repetitive signal with slight variations in each cycle occurs approximately every second. Each cycle differs slightly in duration and content within certain parameters. The signal data consists of a thousand x,y coordinates per second, with a small but s ...
I am looking to obtain the count of OK & NOK for each ITCD & Indicateur RDV, using a sample from my table: _ITCD_ | _Indicateur RDV_ | Week | Workers OK OK 41 John OK NOK 41 John NOK NOK ...
I have developed a function that takes a set of randomized cartesian coordinates and outputs the subset that falls within a specific spatial domain. For example: grid = np.ones((5,5)) grid = np.lib.pad(grid, ((10,10), (10,10)), 'constant') >> np.sh ...
Is there a way to draw a polygon from X, Y coordinates with rounded corners using the points I have? Below is my current code, but I am open to suggestions if there is another library that may work better. Displayed below is my output image generated by ...
Using a=np.square is a way to create an alias for the pow(x,2) function. Just like that, I am looking to create an alias for the pow(x,3) function as well. a = np.power(x2=3) But it appears that this method isn't working as intended. Is there any ...
I have multiple sets of data arranged in columns within a dataframe, totaling nine lists in all. My objective is to perform matrix operations on every row present across these columns. To illustrate, consider the following operation: O(G) = trace(G*transp ...
My application receives incoming signals with a fixed frequency, and I am trying to implement a filter for this signal without having to save N timesteps. I want to update my current state with each new observation, similar to a one-dimensional Kalman filt ...
Looking for a way to find the argmax over all axes except the first in a numpy array. I have come up with a solution, but I'm curious if there is a more efficient method. import numpy as np def argmax(array): ## Argmax along all axes except the ...
I am searching for a solution to efficiently read a zipfile into memory and extract its contents into a numpy array with numpy datatypes. The challenge lies in the fact that these files are large in size and there are numerous of them, making speed a cruci ...
I need assistance with adding a shifted version of an image to the original, while ensuring zeros are left intact. I attempted the following code but encountered some issues. Any help is greatly appreciated! import cv2 import numpy as np #Given image i ...
from scipy import * import matplotlib.pyplot as plt def plot_elines(x_grid, y_grid, potential, field): fig, ax = plt.subplots(figsize=(13, 13)) im_cs = ax.contour(x_grid, y_grid, potential, 18, cmap='inferno') plt.clabel(im_cs, inli ...
Displayed below is an image: HI00008918.png The goal is to implement a logarithmic function (f(x) = (1/a)*log(x + 1), with the value of a = 0.01), on the image... Here is the code segment: import numpy as np import matplotlib.pyplot as plt import skimage ...
a and b represent the datetime indexes for two sets of values, A Values and B Values, respectively. The size of A Values is larger than that of B Values. I am looking to create a code snippet where both sets are plotted on the same graph with numpy arrays ...
What makes numpy.angle() different from other numpy universal functions (ufuncs)? Although it seems to meet the criteria outlined in the numpy documentation, why is it not officially categorized as a ufunc? I initially speculated that its conversion of c ...
Struggling to get divisi2 up and running on Anaconda Python 2.7. I've gone through every method at my disposal: pip, easy_install, even installing from the Python source, but no luck. I’ve included a snippet of the process below. I apologize for the l ...
I am working with a dataframe structured like this: id amenities ... 1 "TV,Internet,Shower,..." ... 2 "TV,Hot tub,Internet,..." ... 3 "Internet,Heating,Shower..." ... ... My goal is to split the string by comm ...
I am looking to transform the data frame provided below: ID X Var1 Var2 Var3 A 1 52 16 17 A 2 73 0 20 A 3 60 42 16 A 4 15 87 73 A 5 0 18 63 B 1 66 42 0 B 3 13 28 64 B 4 ...
Is there a way to adjust the x and y axis label numbers by adding +2? In other words, I have created this image but I need the label numbers to start with 2: https://i.stack.imgur.com/LeHjF.png Here is the code I used: jacaardMatrix = 1.6628873771730914 ...
As a newcomer to Python and its libraries, I am exploring the conversion of HDR images to RGBM as outlined in WebGL Insights Chapter 16. import argparse import numpy import imageio import math # Handling arguments parser = argparse.ArgumentParser(descrip ...
I have been successfully replacing all the numbers in my dataframe with their current positive streak number. However, I find my code to be quite messy as I am doing it column by column and manually mentioning the column names each time. Can anyone suggest ...
Currently working with sympy and matplotlib, I am aiming to create a plot with multiple subplots in a similar fashion to how it's done using pylab.subplot while utilizing numpy. In theory, this task should be straightforward, but as I delved into it, ...
I have created a function that takes in a list of numbers such as [0.5, -0.5, 1] and then outputs a new list with each index containing the sum of the differences between the current value and all other values. For example, if the input is [0.5, -0.5, 1], ...
Just joined this site and excited to share my Python code for plotting vectors, eigenvectors, and their dot product with a matrix. I want to add a legend with colors for each vector/eigenvector on the subplots. Check out the code below: import numpy as n ...
Query: Given an ndarray: In [2]: a Out[2]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) I am searching for a method that would result in: array([7, 8, 9, 0, 1]) Example: Starting at index 8, crossing the array boundary and stopping at index 2 (included). When ...
I have a table T with two columns - 'ID' and 'Genes', which contain lists of genes (Strings). My goal is to generate a graph where each gene is represented as a node, connected by edges to genes that share one different ID. The challenge is that my table r ...
As I embark on training a neural network, I am faced with a significant challenge. I have a massive 212,243 × 2500 dense matrix labeled phi, along with vectors y (212243) and w (2500). These are stored as numpy arrays of double values. My goal is to calcu ...
Although the code provided is close to what I need, there is a minor adjustment required. I aim to replace c[1] with c[1:] in order to perform regression against all the x variables instead of just one. However, upon making this change and adding the neces ...
I am currently working on developing a polynomial calculator that allows me to input the largest coefficient. However, I am facing an issue with the xizes variable, which is producing multiple arrays representing the function image. As a result, the functi ...
Having a 3-dimensional Numpy array containing only 0s and 1s as shown below: array([[[ 1, 1, 0, 1], [ 0, 0, 1, 1]], [[ 1, 1, 1, 1], [ 0, 1, 0, 1]]]) The objective is to perform an "addition" operation on each value within a "line" ...
Can you abbreviate the following expression using shorthand: x = [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] to something like this? x = ([0.5]*12)? ...
I'm dealing with a NumPy array that looks like this: [[ 0 935] [ 0 331] [ 0 322] [ 1 339] [ 1 773] [ 2 124] [ 2 340] [ 3 810] [ 5 936] [ 5 252]] and I want to split it into separate arrays as follows: [[ 0 935] [ 0 331] [ 0 322 ...
When numpy einsum throws the error shown below, what is usually the underlying issue? Traceback (most recent call last): File "rmse_iter.py", line 30, in <module> rmse_out = np.sqrt(np.einsum('ij,ij->i',diffs,diffs)/3.0) TypeError: invalid ...
I'm interested in understanding the specific functionality of last() and first() when applied to resampling. My interpretation is that when numerical arguments are passed into these functions, like 3 for example, they return the first 3 months or years. I ...
Using the following initial array: x = range(30,60,2)[::-1]; x = np.asarray(x); x array([58, 56, 54, 52, 50, 48, 46, 44, 42, 40, 38, 36, 34, 32, 30]) You need to create a new array similar to this: (Note that the first item repeats) However, if there is ...
I have been working on validating a basic IDFT routine that I developed: ############################################################### #Custom IDFT Functions ############################################################### def simple_idft(data_f): dat ...
I am dealing with a pandas Series that contains one numpy array per entry, all of the same length. My goal is to convert this into a 2D numpy array. Despite knowing that Series and DataFrames don't handle containers well, when using np.histogram(.,.)[0] on ...
If you have a list called A that contains only 0's and 1's in the form of nested lists, what is the most pythonic (and efficient) method to calculate the product of A * A' without relying on numpy or scipy? One way to achieve this using num ...
Currently, I am studying the numpy package and have come across this code snippet: import numpy as np a = np.array([[1,2,3], [4,5,6]]) np.add.reduce(a) My confusion lies in the dot notation: np.add.reduce(a) This seems different from the more straightf ...
I'm really struggling to comprehend the meaning of this section of code. Can someone please explain why y.values is being compared to a tuple with two values, even though the array is just a single row (650,)? import pandas as pd import numpy as np i ...
Looking to speed up some calculations using Python's multiprocessing module alongside numpy. Here’s a basic example: import time import numpy from multiprocessing import Pool def test_func(i): a = numpy.random.normal(size=1000000) b = numpy.r ...
Working with a multi-dimensional np.array can be tricky. Knowing the shape of the first N dimensions and the last M dimensions is essential for proper indexing, as shown below: >>> n = (3,4,5) >>> m = (6,) >>> a = np.ones(n + m) ...
Looking to conduct a tolerance stack circuit analysis with Python instead of Excel. To start, I have the following resistor values structured as Minimum | Nominal | Maximum: R1 -> 5 | 10 | 15 R2 -> 5 | 10 | 15 Total_R = R1 + R2 Theoretically, this will ...
Seeking advice on improving style and efficiency of code, I am attempting to add a calculated data column to a pandas dataframe based on values from other columns in the same row. One method I tried involved using conditions that worked effectively with o ...
I have a DataFrame that includes columns for date, price, MA1, MA2, and MA3. After filtering the data based on a specific condition, I get a subset of rows where MA1, MA2, and MA3 are equal. date price MA1 MA2 MA3 date1 price1 11 11 11 date4 pri ...
I am currently using matplotlib and numpy to generate a polar plot within my project. Below is a snippet of the code I've been working with: import numpy as np import matplotlib.pyplot as plt angle = np.arange(0, 360, 10, dtype=float) * np.pi / 180.0 arb ...
#Issue with Python's append function when axis=1 in 2D array. import numpy as np arr = np.array([[11, 15, 10, 6], [10, 14, 11, 5], [12, 17, 12, 8], [15, 18, 14, 9]]) print(arr) ...
Currently, I am engaged in processing signals on an extensive dataset of images. This involves converting the images into large feature vectors that follow a specific structure (number_of_transforms, width, height, depth). Due to the size of these feature ...
As a Matlab user transitioning into Python, I attempted to code a minimal version of the de2bi function in Python. This function converts a decimal number into binary with the right-most significant bit first. However, I encountered some confusion when wor ...