![]() annotate ( 'Labor Day', xy = ( '', 4850 ), xycoords = 'data', ha = 'center', xytext = ( 0, - 20 ), textcoords = 'offset points' ) ax. annotate ( "Independence Day", xy = ( '', 4250 ), xycoords = 'data', bbox = dict ( boxstyle = "round", fc = "none", ec = "gray" ), xytext = ( 10, - 40 ), textcoords = 'offset points', ha = 'center', arrowprops = dict ( arrowstyle = "->" )) ax. annotate ( "New Year's Day", xy = ( '', 4100 ), xycoords = 'data', xytext = ( 50, - 30 ), textcoords = 'offset points', arrowprops = dict ( arrowstyle = "->", connectionstyle = "arc3,rad=-0.2" )) ax. plot ( ax = ax ) # Add labels to the plot ax. subplots ( figsize = ( 12, 4 )) births_by_date. ![]() Here let's look at an example of drawing text at various locations using these transforms:įig, ax = plt. fig.transFigure: Transform associated with the figure (in units of figure dimensions).ax.transAxes: Transform associated with the axes (in units of axes dimensions).ax.transData: Transform associated with data coordinates.There are three pre-defined transforms that can be useful in this situation: The average user rarely needs to worry about the details of these transforms, but it is helpful knowledge to have when considering the placement of text on a figure. Mathematically, such coordinate transformations are relatively straightforward, and Matplotlib has a well-developed set of tools that it uses internally to perform them (these tools can be explored in the ansforms submodule). ![]() In Matplotlib, this is done by modifying the transform.Īny graphics display framework needs some scheme for translating between coordinate systems.įor example, a data point at $(x, y) = (1, 1)$ needs to somehow be represented at a certain location on the figure, which in turn needs to be represented in pixels on the screen. Sometimes it's preferable to anchor the text to a position on the axes or figure, independent of the data. In the previous example, we have anchored our text annotations to data locations. set ( title = 'USA births by day of year (1969-1988)', ylabel = 'average daily births' ) # Format the x axis with centered month labels ax. text ( '', 3850, "Christmas ", ha = 'right', ** style ) # Label the axes ax. text ( '', 4250, "Independence Day", ha = 'center', ** style ) ax. plot ( ax = ax ) # Add labels to the plot style = dict ( size = 10, color = 'gray' ) ax.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |