I have the same problem when i try to scale my image to a log scale first it flips the image and then then it exceeds the range that i have chosen.
Log scale mat.
Additionally custom scales may be registered using matplotlib scale register scale these scales can then also be used here.
To get to negative y you would have to go further than infinity down.
Where my axis ranges are x 1 1000 and y 0 1 10 for the picture.
In science and engineering a log log graph or log log plot is a two dimensional graph of numerical data that uses logarithmic scales on both the horizontal and vertical axes.
By default matplotlib supports the above mentioned scales.
Remember when you use log there is an infinite distance in log scale between y 1 and y 0 since it has to pass through y exp 1 y exp 2 y exp 3 and so on each of which needs to be allocated the same screen distance as between y exp 0 and y exp 1.
However if the axes hold state is on before you call loglog those properties do not change and the plot might display on a linear or semilog scale.
Monomials relationships of the form appear as straight lines in a log log graph with the power term corresponding to the slope and the constant term corresponding to the intercept of the line.
This table describes the most common situations.
Type of plot how to specify coordinates.
By default matplotlib supports the above mentioned scales.
As illustrated in this picture.
Y log x returns the natural logarithm ln x of each element in array x.
The loglog function plots coordinates on a log scale by setting the xscale and yscale properties of the axes to log.
For negative and complex numbers z u i w the complex logarithm log z returns.
Additionally custom scales may be registered using matplotlib scale register scale these scales can then also be used here.
The size and shape of x depends on the shape of your data and the type of plot you want to create.