I try to replicate some easy examples in
matplotlib tutorial.
First, we need a float range function.
from __future__ import generators def arange(start, stop=None, step=None): if stop is None: stop = float(start) start = 0.0 if step is None: step = 1.0 cur = float(start) while cur < stop: yield cur cur += step
Then, a function to draw the axes and ticks.
In the future, this should be called automatically from plot().
from appuifw import * app.body = canvas = Canvas() width, height = canvas.size def axes(xyrange, position=[18, height-11, width-10, 10], formatter=lambda x:x): global left, bottom, right, top, min_x, min_y, scale_x, scale_y left, bottom, right, top = position min_x, max_x, step_x, min_y, max_y, step_y = xyrange scale_x = float(right-left)/(max_x-min_x) scale_y = float(bottom-top)/(max_y-min_y) canvas.clear() canvas.rectangle([(left,top), (right+1, bottom+1)], 0) for x in arange(min_x, max_x, step_x): canvas.text((14+scale_x*(x-min_x), height-1), unicode(formatter(x))) canvas.point((left+scale_x*(x-min_x), bottom-1), 0) canvas.point((left+scale_x*(x-min_x), top+1), 0) for y in arange(min_y, max_y, step_y): canvas.text((2, bottom+2-scale_y*(y-min_y)), unicode(formatter(y))) canvas.point((left+1, bottom-scale_y*(y-min_y)), 0) canvas.point((right-1, bottom-scale_y*(y-min_y)), 0)
And lastly, the plot function. Now it has only a few features.
More will be added depending on what is needed.
def plot(xs, ys=None): if ys==None: ys = xs xs = range(len(ys)) last = left+(xs[0]-min_x)*scale_x, bottom-(ys[0]-min_y)*scale_y for i in range(1, len(ys)): p = left+(xs[i]-min_x)*scale_x, bottom-(ys[i]-min_y)*scale_y canvas.line([last, p], 0x00000ff) last = p canvas.point(last, 0x0000ff)
When we want to plot a graph, we called both axes() and plot()
# a straight line >>> axes([0,3.1,.5, 1,4.1,.5]) >>> plot([1,2,3,4]) # a parabola y = x^2 >>> axes([1,4.1,1, 0,16.1,2], formatter=int) >>> plot([1,2,3,4], [1,4,9,16])
See the sreenshot of the first.