Improve subplot size/spacing with many subplots in matplotlib
Very similar to this question but with the difference that my figure can be as large as it needs to be.
Very similar to this question but with the difference that my figure can be as large as it needs to be.
I have a set of X,Y data points (about 10k) that are easy to plot as a scatter plot but that I would like to represent as a heatmap.
I am making an application in Python which collects data from a serial port and plots a graph of the collected data against arrival time. The time of arrival for the data is uncertain. I want the plot to be updated when data is received. I searched on how to do this and found two methods:
I am trying to make a scatter plot and annotate data points with different numbers from a list.
So, for example, I want to plot y vs x and annotate with corresponding numbers from n.
I have an array of timestamps in the format (HH:MM:SS.mmmmmm) and another array of floating point numbers, each corresponding to a value in the timestamp array.
I am currently trying to embed a graph I want to plot in a pyqt4 user interface I designed. As I am almost completely new to programming – I do not get how people did the embedding in the examples I found – this one (at the bottom) and that one.
Looking at the matplotlib documentation, it seems the standard way to add an AxesSubplot to a Figure is to use Figure.add_subplot:
I need to add two subplots to a figure. One subplot needs to be about three times as wide as the second (same height). I accomplished this using GridSpec and the colspan argument but I would like to do this using figure so I can save to PDF. I can adjust the first figure using the figsize argument in the constructor, but how do I change the size of the second plot?
So currently learning how to import data and work with it in matplotlib and I am having trouble even tho I have the exact code from the book.
I am trying to use IPython notebook on MacOS X with Python 2.7.2 and IPython 1.1.0.