3. dataList¶
dataList contain a list of dataArray.
List of dataArrays allowing variable sizes and attributes.
Basic list routines as read/save, appending, selection, filter, sort, prune, interpolate, spline…
Multidimensional least square fit that uses the attributes of the dataArray elements.
Read/Write in human readable ASCII text of multiple files in one run (gzip possible) or pickle.
A file may contain several datasets and several files can be read.
For programmers: Subclass of list
For Beginners:
Create a dataList and use the methods from this object in point notations.:
data=js.dL('filename.dat'). data.prune(number=100) data.attr data.save('newfilename.dat')
The dataList methods should not be used directly from this module.
See dataList
for details.
Example:
p=js.grace()
dlist2=js.dL()
x=np.r_[0:10:0.5]
D,A,q=0.45,0.99,1.2
for q in np.r_[0.1:2:0.2]:
dlist2.append(js.dA(np.vstack([x,np.exp(-q**2*D*x),np.random.rand(len(x))*0.05])) )
dlist2[-1].q=q
p.clear()
p.plot(dlist2,legend='Q=$q')
p.legend()
dlist2.save('test.dat.gz')
The dataarray module can be run standalone in a new project.
3.1. dataList Class¶
dataList creating by dataL=js.dL(‘filename.dat’) or from numpy arrays.
List columns can be accessed as automatic generated attributes like .X,.Y,.eY (see protectedNames). or by indexing as *dataL[:,0] -> .X * for all list elements.
Corresponding column indices are set by
setColumnIndex()
(default X,Y,eY = 0,1,2).Multidimensional fitting of 1D,2D,3D (.X,.Z,.W) data including additional attributes. .Y (scalar) are used as function values at coordinates.
Attributes can be set like: dataL.aName= 1.2345 or dataL[2].aName= 1.2345
Individual elements and dataArray methods can be accessed by indexing data[2].bName
Methods are used as dataL.methodname(arguments)
3.2. Attribute Methods¶
3.3. Fit Methods¶
Least square fit
Prediction