of course. Here it is Il giorno lun 18 set 2023 alle ore 18:10 Jaime Lopez <jalop...@gmail.com> ha scritto:
> Hi,
>
> Same error, maybe it could be related to the database I got from github
> (iris.xlsx), could you share yours?.
>
> [image: image.png]
>
> JL
>
> On Mon, Sep 18, 2023 at 1:57 AM Ulderico Santarelli <
> ulderico.santare...@gmail.com> wrote:
>
>> *I think it better to send you the script in its integrity. I ran now and
>> it works. *
>> *about work it is*
>> work
>> array([[ 5.63011247],
>> [-2.31453939],
>> [22.23122848],
>> [15.37678101]])
>> np.shape(work)
>> (4, 1)
>>
>> *my best regards. *
>> *Ulderico.*
>>
>> _________________________________________________________________________________
>> import numpy as np
>> import pandas as pd
>> dataraw = pd.read_excel("C:\Pyth\iris.xlsx")
>> #standardize data --- dataraw is a DataFrame
>> #locate data in the DataFrame
>> datar = dataraw.iloc[:,1:5]
>> means = datar.mean(axis = 0)
>> stdev = datar.std(axis = 0)
>> data = (datar-means)/stdev
>> #keep just quantitative variables
>> #CENTRALITY INDEX
>> scalar = pd.merge(data, data, how = 'cross')
>> point1 = scalar.loc[:, 'sepal length _x':'petal width _x']
>> point2 = scalar.loc[:, 'sepal length _y':'petal width _y']
>> apoint1 = point1.to_numpy(dtype = float)
>> apoint2 = point2.to_numpy(dtype = float)
>> delta = (apoint1 - apoint2)
>> force = 0
>> if delta.any() != 0:
>> force = np.exp(-abs(delta))
>> sig = np.sign(delta)
>> sforce = sig*force
>> dsforce = pd.DataFrame(sforce)
>> #dsforce.to_excel('C:\Pyth\dsforce.xlsx')
>> arr = np.ones((150, 1),)
>> sforcet = sforce.T
>> sum_force =np.zeros((1, 4),) #do not use empty arrays
>> start = 0
>> end = 150
>> for i in range(150):
>> s_forcet = sforcet[:, start:end]
>> work = np.matmul(s_forcet, arr)
>> sum_force =np.concatenate((sum_force, work.reshape(1, 4)), axis = 0)
>> start = end
>> end +=150
>> sumforce = sum_force[1:, :]
>> dsumforce = pd.DataFrame(sumforce)
>> dsumforce.to_excel('C:\Pyth\sumforce_sqc.xlsx')
>> sum_force_square = sumforce**2
>> ssT = np.ones((4, 1),)
>> T_w_ = np.sqrt(np.matmul(sum_force_square, ssT))
>> dT_w_ = pd.DataFrame(T_w_, )
>> dT_w_.to_excel('C:\Pyth\T_w_.xlsx')
>>
>> Il giorno dom 17 set 2023 alle ore 18:14 Jaime Lopez <jalop...@gmail.com>
>> ha scritto:
>>
>>> Hi there,
>>>
>>> I got interested in your project, but I found this error from the
>>> beginning (see attached image).
>>> The work array cannot be reshaped to (1,4), cause it has shape (2,1),
>>> any suggestions?
>>>
>>> JL
>>>
>>> [image: image.png]
>>>
>>> On Thu, Sep 14, 2023 at 11:29 AM Ulderico Santarelli <
>>> ulderico.santare...@gmail.com> wrote:
>>>
>>>> *I am an old guy who started programming around the seventies of
>>>> the last century* with ASSEMBLER 360, then FORTRAN, PL1, APL, IBM
>>>> APPLICATION SYSTEM and, last, the marvelous SAS. Having heard around about
>>>> the powerful, flexible, functionally complete PYTHON UNIVERSE”,
>>>> encompassing an advanced Object-Oriented Language and a very wide family of
>>>> packages, I decided to run an exercise about a problem I've been
>>>> tackling since my youth (have a look at the Bibliography). I succeeded in
>>>> completing it in a few days and I'm attaching my solution to the problem of
>>>> finding the points in a sample that are "central" in a surrounding
>>>> topological neighborhood. They are eligible as centroids for a Cluster
>>>> Analysis after the aggregation of "too near points'. The solution is based
>>>> on the search of potential wells in a suitable potential field, similar to
>>>> the one all of us studied in high school. Therefore, too near points may be
>>>> in the same potential well.
>>>> No more words, have a look at the attachment.
>>>> My coding is that of a beginner. I'm sure everybody would find more
>>>> efficient coding. As a comment: I started studying Python around May 15th
>>>> 2023.
>>>> My best regards.
>>>> Ulderico Santarelli.
>>>> _______________________________________________
>>>> scikit-learn mailing list
>>>> scikit-learn@python.org
>>>> https://mail.python.org/mailman/listinfo/scikit-learn
>>>>
>>>
>>>
>>> --
>>>
>>> *Jaime Lopez Carvajal*
>>> _______________________________________________
>>> scikit-learn mailing list
>>> scikit-learn@python.org
>>> https://mail.python.org/mailman/listinfo/scikit-learn
>>>
>> _______________________________________________
>> scikit-learn mailing list
>> scikit-learn@python.org
>> https://mail.python.org/mailman/listinfo/scikit-learn
>>
>
>
> --
>
> *Jaime Lopez Carvajal*
> _______________________________________________
> scikit-learn mailing list
> scikit-learn@python.org
> https://mail.python.org/mailman/listinfo/scikit-learn
>
iris.xlsx
Description: MS-Excel 2007 spreadsheet
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