MPL (Matplotlib): The MPL colour maps (available at ref. 62) developed by Stéfan van der Walt and Nathaniel Smith. MPL maps aim for the most accurate perceptual uniformity with its widely applied colour maps being: viridis, magma, plasma and inferno. These maps have spearheaded the way towa...
This repository contains the handout (and the source of the handout) for the tutorial "Creating publication-quality with Python and Matplotlib", given at the Alife 2014 conference. Contributions are welcomed: feel free to clone and send pull requests. Goal Create nice figures for scientific paper...
The turbo colormap from matplotlib was used to assign amplitude values. A single s.d. projection was used to represent fluorescence intensity variance across CNO and 2MeSADP applications, which enabled the visualization of regions within the FOV capable of repetitive SF-iGluSnFR responses. The s...
Scikit-Learn is a Python module for machine learning built on top of SciPy, NumPy, and matplotlib, making it easier to apply robust and simple implementations of many popular machine learning algorithms. Weka is an open source machine learning software that can be accessed through a graphical use...
e2, Scheme of the effective spread of the electrical field (5 fish, 3 electrodes, 10 stimulations). f, Location of all stimulation sites investigated color-coded using the median forward index. The dashed line represents the MLR location covering all stimulation sites with a median forward ...
The Spatially Enabled Dataframe has a plot() method that uses a syntax and symbology similar to matplotlib for visualizing features on a map. With this functionality, you can easily visualize aspects of your data both on a map and on a matplotlib chart using the same symbology! Some unique ...
# Necessary Imports import os import cv2 import PIL import torch import numpy as np import matplotlib.pyplot as plt Next, we define a variable label_map, that contains an RGB color tuple for each class, as in the above image.label_map = np.array([ (0, 0, 0), # background (128, ...
To classify these transcriptomic samples within our proteomic PAULA scheme, we used published data on the correlations between proteins and their mRNAs across different tissue types35. These different biological states and cellular differentiations could be expected to represent maximum levels of ...
This repository contains the handout (and the source of the handout) for the tutorial "Creating publication-quality with Python and Matplotlib", given at the Alife 2014 conference.Contributions are welcomed: feel free to clone and send pull requests.Goal...
You're welcome to use the color palette and font styling if you'd like.The color scheme for this map was inspired by antique roadmaps, like this map of Nebraska from 1898. But this is the only map in the series without a dark background, and I wasn’t quite convinced that a ...