Reference¶
spectraplotpy is made up of four decoupled building blocks, the first one is the Dataset, the Importers, the Spectra and the Exporters.
The Importers take data from several different formated files, and populate a Dataset, then the the Dataset can be passed around to the Spectra in order to do some processing and plotting or directly to the Exporters.
Dataset¶
The dataset module defines the datastructure shared among the spectraplotpy classes, you need to implement a similar interface in order to leverage the class.
The users are encouraged to directly access the data members of this class, and is up to them to keep the data consistently.
import spectrapotpy as spp
import numpy as np
ds = spp.Dataset()
ds.x = np.arrange(0, np.pi, 1000)
ds.y = np.sin(x)
Importers¶
The importers functionalities to parse input from several file types, it also allows you to easily create new importers for your own formats subclasing the Importer class and overriding some methods.
The library provides several importer for several formats, and the users are encouraged to create their own.
Examples¶
Importing from an Aviv file,
import spectraplotpy as spp
avii = AvivImporter('filename.cd')
# then you can access the dataset and pass it around
print avii.dataset.x, avii,dataset.y
Creating a custom importer,
import spectraplotpy as spp
class XRDPanalithicalImporter(spp.Importer):
def parse_metadata(self, metadata_txt):
# override this function to get the
pass
def parse_data(self, data_txt):
# override this to parse your custom data
pass
Spectra¶
The Spectrum class provides some functionalities that allow the users to operate their data in a very intuitive fashion.