Quick Start

Create a Data Object

Create a data object from one of the built-in datasets.

import WrightTools as wt
# get some example files
from WrightTools import datasets
ps = datasets.COLORS.v2p1_MoS2_TrEE_movie  # list of filepaths
# create data object
data = wt.data.from_COLORS(ps)

The data contains some helpful attributes that we can inspect now:

>>> data.channel_names
['ai0', 'ai1', 'ai2', 'ai3', 'ai4', 'array']
>>> data.axis_names
['w2', 'w1', 'd2']
>>> data.shape
(41, 41, 23)

Make a Plot

WrightTools strives to make data visualization as quick and painless as possible.

Axes, labels, and units are brought along implicitly.

WrightTools offers a few handy ways to quickly visualize a data object, shown below. For more information, check see Artists, or check out our gallery.

1D

artist = wt.artists.mpl_1D(data, 'w1', at={'w2': [2, 'eV'], 'd2': [-100, 'fs']})
artist.plot()

(Source code, png, pdf)

_images/quickstart-1.png

2D

artist = wt.artists.mpl_2D(data, 'w1', 'd2', at={'w2': [2, 'eV']})
artist.plot()

(Source code, png, pdf)

_images/quickstart-2.png

Interact with the Data

WrightTools has built in units support. For more information see Units.

Convert

>>> [a.units for a in data.axes]
['wn', 'wn', 'fs']
>>> data.convert('eV')
axis w2 converted
axis w1 converted
>>> [a.units for a in data.axes]
['eV', 'eV', 'fs']

Want fine control? You can always convert individual axes, e.g. data.w2.convert('nm').

Split

Use split to break your dataset into smaller pieces.

>>> data.split('d2', 0.)
split data into 2 pieces along d2:
  0 : -599.79 to -40.06 fs (length 15)
  1 : 39.91 to 279.70 fs (length 7)

Clip

Use clip to ignore points outside of a specific range.

data.clip('ai0', min=0.0, max=0.1)

(Source code, png, pdf)

_images/quickstart-3.png