This package is a inspired from Imri Goldberg's ASCII-Plotter 1.0 (https://pypi.python.org/pypi/ASCII-Plotter/1.0)
At a time I was enoyed by security not giving me direct access to my computer, and thus to quickly make figures from python, I looked at how I could make quick and dirty ASCII figures. But if I were to develop something, I wanted something that can be used with just python and possible standard-ish packages (numpy, scipy).
So I came up with this package after many iterations based of ASCII-plotter. I added the feature to show multiple curves on one plot with different markers. And I also made the usage, close to matplotlib, such that there is a plot, hist, hist2d and imshow functions.
- imshow does not plot axis yet.
- make a correct documentation
- publish on github
|marker | repr | unicode | description |
|--------|---------|-------------|---------------------------------|
|'-' | | u'None' | solid line style |
|',' | ∙ | u'\u2219' | point marker |
|'.' | ∘ | u'\u2218' | pixel marker |
|'o' | ○ | u'\u25CB' | circle marker |
|'of' | ● | u'\u25CF' | circle marker |
|'v' | ▽ | u'\u25BD' | triangle_down marker |
|'vf' | ▼ | u'\u25BC' | filler triangle_down marker |
|'^' | △ | u'\u25B3' | triangle_up marker |
|'^f' | ▲ | u'\u25B2' | filled triangle_up marker |
|'<' | ◁ | u'\u25C1' | triangle_left marker |
|'<f' | ◀ | u'\u25C0' | filled triangle_left marker |
|'>' | ▷ | u'\u25B7' | triangle_right marker |
|'>f' | ▶ | u'\u25B6' | filled triangle_right marker |
|'s' | ◽ | u'\u25FD' | square marker |
|'sf' | ◼ | u'\u25FC' | square marker |
|'*' | ☆ | u'\u2606' | star marker |
|'*f' | ★ | u'\u2605' | star marker |
|'+' | ✚ | u'\u271A' | plus marker |
|'x' | ❌ | u'\u274C' | x marker |
|'d' | ◇ | u'\u25C7' | diamond marker |
|'df' | ◆ | u'\u25C6' | filled diamond marker |
- plot
In [1]: import ap
In [2]: import numpy as np
In [3]: p = AFigure()
In [4]: x = np.arange(10)
In [5]: y = x ** 2
In [6]: _ = p.plot(x, y, marker='_o')
In [7]: print p.plot(x, 30. - y, marker='_s')
│
┼+79.548 ○
│
│ ○
│
│ ○
│
│ ○
◽ ◽ ◽ ○
│ ◽ ○
│ ○ ◽
──┼────○────○──────────────◽───────────────────┼──
│+0.046 ◽ +8.97638
│
│ ◽
│
│ ◽
┼-48.228
│ ◽
│- hist
In [1]: import ap, numpy as np
In [2]: x = np.random.normal(0, 1, 1e6)
In [3]: ap.hist(x, 20)
│
∘┼+180303
|│ ∘
|│ |
∘ |│ |
| |│ | ∘
| |│ | |
| |│ | |
| |│ | |
∘ | |│ | |
| | |│ | | ∘
| | |│ | | |
| | |│ | | |
∘ | | |│ | | |
| | | |│ | | | ∘
| | | |│ | | | |
∘ | | | |│ | | | | ∘
∘ | | | | |┼+3828.47| | ∘
──┼--------------------------------------------┼──
-4.39861 │ +4.48165
In [4]: y = np.random.normal(0, 1, 1e6)
In [5]: ap.hist2d(x, y, bins=[20,20], width=30)
....
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..
- imshow
In [1]: import ap
In [2]: from scipy import misc
In [3]: im = misc.lena()
In [4]: ap.imshow(im.T)
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