I’m working with the following scipy code. The global minimum of this function is at 0, but this isn’t what basin hopping returns. Depending on the start position x0, it returns different local minima – not the global one at 0. If we set x_0 = -6, it returns a minima at -7.7, if we set x0 = 1, then
Tag: numpy
Python: How do I read the data in this multipage TIFF file to produce the desired image?
I am working with TIFF files that represent the readings of detectors in electron microscopy, and I know how this particular image should look, but I’m unsure how to get that result from the raw data in question. The TIFF files in question have several pages corresponding to frames on which data was taken, but when I look at each
Numpy Delete not deleting rows
I’ve been trying to write some code to delete rows from my 2d array according to the following criteria: every lone entry, so that no patient only has one entry (the mriindex ticks up by 1 for every entry of the same patient in the array) every entry above the 4th one. Should either of those criteria be fulfilled, np.delete
Updating values within python column based on date
I have a dataset where I would like to replace and update values within a column when a data condition is met. Data Desired Doing Still researching, any suggestion is appreciated- Perhaps I need to convert quarters to datetime longdate and base the condition off of this column. Answer here is one way to do it to apply the condition,
All possible combinations of arrays in python
I have a problem finding all combinations of a 2D array. Let’s suggest I have an array as follwoing: Now I need to get all possible combninations such as I’ve managed to get it with numpy and meshgrids with single arrays: But with a 2D array I cant’t get it to work. This doesn’t give me the expected result but
Get the sum of each column, with recursive values in each cell
Given a parameter p, be any float or integer. For example, let p=4 time 1 2 3 4 5 Numbers a1 a1*(0.5)^(1/p)^(2-1) a1*(0.5)^(1/p)^(2-1) a1*(0.5)^(1/p)^(3-1) a1*(0.5)^(1/p)^(4-1) Numbers nan a2 a2*(0.5)^(1/p)^(3-2) a2*(0.5)^(1/p)^(4-2) a2*(0.5)^(1/p)^(5-2) Numbers nan nan a3 a3*(0.5)^(1/p)^(4-3) a3*(0.5)^(1/p)^(5-3) Numbers nan nan nan a4 a4*(0.5)^(1/p)^(5-4) Number nan nan nan nan a5 Final Results a1 sum of column 2 sum of column 3
Convert Array to dataframe with Longitude, Lattitude coordinates
Imported Libraries I am trying to creat a Heatmap out of my strava dataset ( which turns to be a csv file of 155479 rows with Georaphical cooridnates) I tried first to display the whole dataset on Folium using python, the problem is that Folium seemed to crash when i tried to upload the whole dataset ( it was working
Changing graph dataset matrices from sparse format to dense
I am trying to use the CoRA dataset to train a graph neural network on tensorflow for the first time. The features and adjacency matrices provided by the dataset comes in a sparse representation but I don’t need it here. Thus, I want to use numpy’s todense() but it turns out it doesn’t exist. For your reference, here is the
Python argmax of dot product of weighted matrix and vector (mnist)
What does argmax mean in this context? I am following the tutorial in this colab notebook: https://colab.research.google.com/github/chokkan/deeplearningclass/blob/master/mnist.ipynb It looks like this is saying that for every record x and its truth value y, in the vectors Xtrain and Ytrain, take the max value of the dot product of the weighted matrix W and the record x. Does this mean it
Slice multidimensional numpy array from max in a given axis
I have a 3-dimensional array a of shape (n, m, l). I extract one column j from it’s last axis and compute the maximum index along the first axis like follows: Now I’d like to slice the original array a to get all the information based on the index where the column j is maximal. I.e. I’d like an numpythonic