ndarray | 📈 Multidimensional arrays for JavaScript | Functional Programming library
kandi X-RAY | ndarray Summary
kandi X-RAY | ndarray Summary
ndarrays provide higher dimensional views of 1D arrays. For example, here is how you can turn a length 4 typed array into an nd-array:.
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ndarray Key Features
ndarray Examples and Code Snippets
Lines of Code : 254License : Non-SPDX (Apache License 2.0)
Copydef gather_nd(params, indices, name=None, batch_dims=0):
r"""Gather slices from `params` into a Tensor with shape specified by `indices`.
`indices` is a `Tensor` of indices into `params`. The index vectors are
arranged along the last axis of ` def MakeNdarray(tensor):
"""Create a numpy ndarray from a tensor.
Create a numpy ndarray with the same shape and data as the tensor.
For example:
```python
# Tensor a has shape (2,3)
a = tf.constant([[1,2,3],[4,5,6]])
proto_tensor = def ndtr(x, name="ndtr"):
"""Normal distribution function.
Returns the area under the Gaussian probability density function, integrated
from minus infinity to x:
```
1 / x
ndtr(x) = ---------- | exp(-0.5 import io
import numpy as np
import pandas as pd
from sqlalchemy import String, LargeBinary
df = pd.DataFrame([file_path],columns=["filename"])
f = io.BytesIO()
np.save(f, blob_data)
f.seek(0)
blob = f.read()
df['image'] = [blob]
Help on function _lambdifygenerated:
_lambdifygenerated(x)
Created with lambdify. Signature:
func(x)
Expression:
Max(1, x)
Source code:
def _lambdifygenerated(x):
return (amax((1,x)public NDarray VectorizeSequences(NDarray sequence, int dimension = 10000)
{
NDarray output = np.zeros((sequence.size, dimension));
// get the first line of the NDarray
NDarray line0 = sequence[0];
int[] int_value>>> import colour
>>> import numpy as np
>>> RGB = np.array([100, 80, 20]) / 255
>>> D50 = colour.CCS_ILLUMINANTS['cie_2_1931']['D50']
>>> XYZ = colour.sRGB_to_XYZ(RGB, illuminant=D50)
>>&arr = justify(df.to_numpy(), invalid_val=np.nan)
df = pd.DataFrame(arr).dropna(axis=1, how='all')
print (df)
0 1 2 3
0 3.0 74.0 NaN NaN
1 4.0 2.0 NaN NaN
2 -9.0 NaN NaN NaN
3 -1.0 2.0 -16.0 -21.0
def window_nd(a, window, steps = None, axis = None, generator = False):
"""
Create a windowed view over `n`-dimensional input that uses an
`m`-dimensional window, with `m <= n`
Parameters
------np = py.importlib.import_module('numpy');
sp = py.importlib.import_module('scipy.fftpack');
% Create a double array in python:
arrC = sp.fftn(np.random.rand(uint8(4), uint8(3), uint8(2)));
%{
arrC =
Python ndarray with properties:
Community Discussions
Trending Discussions on ndarray
QUESTION
I want to change all specific values in a 3D Ndarray image file.
I'm working on mapping a colormap to an image file.
For example :
...ANSWER
Answered 2021-Jun-14 at 12:23You can speed up the process by getting rid of the two for loops. If you used np.where or np.all inside the loop, then this is no wonder it took time.
I mostly have the feeling that you don't use numpy at its best... But whatever... So to remove the for loops I would advise you to do something like:
QUESTION
My GUI is able to play videos automatically when selected in the QListWidget. However, instead of normal speed, the videos play very fast. I use 720p Mp4 videos as examples and are placed in a certain folder. I tried using cv2.CAP_PROP_FPS and cv2.CAP_PROP_BUFFERSIZE, but they are both not working. I am using pyqtSignal in the QThread and the convert_cv_qt function which I saw in other guides. How do I play the videos in normal speed / frame rate?
ANSWER
Answered 2021-Jun-14 at 10:44When you use VideoCapture with a file if you call "cap.read()" you will obtain the next frame on the video, regardless of its actual framerate. Hence, you should use a "msleep" every time you capture a frame:
QUESTION
I want to create a PNG image file with palette information in Python using Pillow and/or pypng.
The input is:
Palette information
...
ANSWER
Answered 2021-Jun-14 at 09:38Here's some demonstration code to convert an existing RGB image to some indexed color image. Please keep in mind, that Pillow only allows storing 256 different colors in some color palette, cf. Image.putpalette. So, make sure to have your input images not containing more than 256 different colors.
Also, I will assume, that the palette is known before, and that all colors in the existing RGB image are exclusively from that palette. Otherwise, you'd need to add code for extracting all colors, and setting up a proper palette beforehand.
QUESTION
I am have a time series data and I am trying to build and train an LSTM model over it. I have 1 input and 1 Output corresponding to my model. I am trying to build a Many to Many model where Input length is exactly equal to output length.
The shape of my inputs are X --> (1700,70,401) (examples, Timestep, Features)
Shape of my output is Y_1-->(1700,70,3) (examples, Timestep, Features)
Now When I am trying to approach this problem via sequential API everything is running fine.
...ANSWER
Answered 2021-Jun-13 at 18:26I made a mistake in the code itself while executing the Model part of in the functional API version.
QUESTION
I tried following code but "numpy.ndarray' object has no attribute 'append' " this error comes I tried replace the append with other attributes , but any of those methods didnt work for me . can someone run the codes in your pc and suggest me a way to fix this.
...ANSWER
Answered 2021-Jun-13 at 04:41You can define your class e.g. as:
QUESTION
I'm trying to slice an Ndarray a with a list b. But the behaviour is not as I would expect it. What do I have to change to get the wanted result?
ANSWER
Answered 2021-Jun-11 at 18:42Try replacing : with slice(None) and unpacking b:
QUESTION
Suppose I have a list that contains a bunch of numpy ndarrays (or even torch Tensors):
ANSWER
Answered 2021-Feb-15 at 22:57I would use numpy arrays the whole way through:
QUESTION
Based on the guide Implementing PCA in Python, by Sebastian Raschka I am building the PCA algorithm from scratch for my research purpose. The class definition is:
...ANSWER
Answered 2021-Jun-11 at 12:52When calculating an eigenvector you may change its sign and the solution will also be a valid one.
So any PCA axis can be reversed and the solution will be valid.
Nevertheless, you may wish to impose a positive correlation of a PCA axis with one of the original variables in the dataset, inverting the axis if needed.
QUESTION
The data is basically in CSV format, which is a fasta/genome sequence, basically the whole sequence is a string. To pass this data into a CNN model I convert the data into numeric. The genome/fasta sequence, which I want to change into tensor acceptable format so I convert this string into float e.g., "AACTG,...,AAC.." to [[0.25,0.25,0.50,1.00,0.75],....,[0.25,0.25,0.50.....]]. But the conversion data shows like this (see #data show 2). But, when I run tf.convert_to_tensor(train_data) it gives me an error of Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray). But in order to pass the data into CNN model, it has to be a tensor, but I don't know why it gives an error! What will be the solution to it?
...ANSWER
Answered 2021-Jun-10 at 21:47The problem is probably in your numpy array dtype.
Using array with dtype float32 should fix problem: tf.convert_to_tensor(train_data.astype(np.float32))
QUESTION
I have this 4D array (numpy.ndarray) that I need to save in a way that its format does not change as I save it (since it should remain unchanged), and then reuse it in my Google Colab file. I have tried saving it in different formats and when I upload it and preview it within my code, the previous format is no longer preserved even when I save it in the .npy format. I have also tried importing the date using the raw link from my GitHub repository or uploading it from my local device, but still no chance. I would appreciate your comments regarding the issue!
Further elaboration:
Here is the code that I use to generate my 4D array:
...ANSWER
Answered 2021-Jun-10 at 17:43Usual np.save, np.load works
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