Multiple errors attempting to solve a function with fsolve and sym solve in python

I am trying to solve the function below. I've attempted to use a symbolic solver and fsolve. Both are causing me trouble. First time posting, I apologize in advance if I'm missing something in my question.

I am trying to solve the function below. I've attempted to use a symbolic solver and fsolve. Both are causing me trouble. First time posting, I apologize in advance if I'm missing something in my question.

Does anyone have a suggestion on how to solve this? I am solving for y, everything else is a known variable.

cos(y) + ((xi - tdd) / y) * sin(y)) - exp(xi - tii)

I attempted this in python using two ways, both did not work. The first is:

import numpy as np
from scipy.optimize import fsolve
import sympy as sym
from sympy import *

def fi(y):
return (cos(y) + ((xi - tdd) / y) * sin(y)) - exp(xi - tii))
y=fsolve(fi,0.01)`

With this code I get this error:

AttributeError: 'ImmutableDenseNDimArray' object has no attribute 'could_extract_minus_sign'

I also tried this:

y= symbols('y')
init_printing(use_unicode=True)
yi=solve(cos(y) + ((xi - tdd) / y) * sin(y)) - exp(xi - tii))

And got this error:

NotImplementedError: multiple generators [y, tan(y/2)] No algorithms are implemented to solve equation y*(10000000000000000*(-tan(y/2)**2 + 1)/(tan(y/2)**2 + 1) - 9849605264665270) - 300789470669454*tan(y/2)/(tan(y/2)**2 + 1)

This is how I solved it in Matlab (i and j because I have x values in a matrix that need to be solve):

fi= @(y,x) (cos(y) + (((x-tdd)/y)*sin (y))) - exp((x - tii));
yi(i)=fzero(@(y) fi(y,xi(i,j)),.01);


Python GUI Programming Projects using Tkinter and Python 3

Python GUI Programming Projects using Tkinter and Python 3

Python GUI Programming Projects using Tkinter and Python 3

Description
Learn Hands-On Python Programming By Creating Projects, GUIs and Graphics

Python is a dynamic modern object -oriented programming language
It is easy to learn and can be used to do a lot of things both big and small
Python is what is referred to as a high level language
Python is used in the industry for things like embedded software, web development, desktop applications, and even mobile apps!
SQL-Lite allows your applications to become even more powerful by storing, retrieving, and filtering through large data sets easily
If you want to learn to code, Python GUIs are the best way to start!

I designed this programming course to be easily understood by absolute beginners and young people. We start with basic Python programming concepts. Reinforce the same by developing Project and GUIs.

Why Python?

The Python coding language integrates well with other platforms – and runs on virtually all modern devices. If you’re new to coding, you can easily learn the basics in this fast and powerful coding environment. If you have experience with other computer languages, you’ll find Python simple and straightforward. This OSI-approved open-source language allows free use and distribution – even commercial distribution.

When and how do I start a career as a Python programmer?

In an independent third party survey, it has been revealed that the Python programming language is currently the most popular language for data scientists worldwide. This claim is substantiated by the Institute of Electrical and Electronic Engineers, which tracks programming languages by popularity. According to them, Python is the second most popular programming language this year for development on the web after Java.

Python Job Profiles
Software Engineer
Research Analyst
Data Analyst
Data Scientist
Software Developer
Python Salary

The median total pay for Python jobs in California, United States is $74,410, for a professional with one year of experience
Below are graphs depicting average Python salary by city
The first chart depicts average salary for a Python professional with one year of experience and the second chart depicts the average salaries by years of experience
Who Uses Python?

This course gives you a solid set of skills in one of today’s top programming languages. Today’s biggest companies (and smartest startups) use Python, including Google, Facebook, Instagram, Amazon, IBM, and NASA. Python is increasingly being used for scientific computations and data analysis
Take this course today and learn the skills you need to rub shoulders with today’s tech industry giants. Have fun, create and control intriguing and interactive Python GUIs, and enjoy a bright future! Best of Luck
Who is the target audience?

Anyone who wants to learn to code
For Complete Programming Beginners
For People New to Python
This course was designed for students with little to no programming experience
People interested in building Projects
Anyone looking to start with Python GUI development
Basic knowledge
Access to a computer
Download Python (FREE)
Should have an interest in programming
Interest in learning Python programming
Install Python 3.6 on your computer
What will you learn
Build Python Graphical User Interfaces(GUI) with Tkinter
Be able to use the in-built Python modules for their own projects
Use programming fundamentals to build a calculator
Use advanced Python concepts to code
Build Your GUI in Python programming
Use programming fundamentals to build a Project
Signup Login & Registration Programs
Quizzes
Assignments
Job Interview Preparation Questions
& Much More

Guide to Python Programming Language

Guide to Python Programming Language

Guide to Python Programming Language

Description
The course will lead you from beginning level to advance in Python Programming Language. You do not need any prior knowledge on Python or any programming language or even programming to join the course and become an expert on the topic.

The course is begin continuously developing by adding lectures regularly.

Please see the Promo and free sample video to get to know more.

Hope you will enjoy it.

Basic knowledge
An Enthusiast Mind
A Computer
Basic Knowledge To Use Computer
Internet Connection
What will you learn
Will Be Expert On Python Programming Language
Build Application On Python Programming Language

Tutorial How to write MatLab functions in Python

Tutorial How to write MatLab functions in Python

A tutorial on writing MatLab-like functions using the Python language and the NumPy library.

Overview

Recently in my work, I was re-writing algorithms developed in MatLab to Python, some functions are not so simple to adapt, especially the array functions that are called Cell Arrays.

MatLab has an API where you can call MatLab functions via Python. The idea, however, was not to use MatLab, but the same algorithm works the same way using only Python and NumPy, and the GNU Octave also has an API similar to that of MatLab.

To maintain compatibility, I have created functions with the same name that are used in MatLab that is encapsulated in a class called Precision.

1. Testing

Make the repository clone and follow the instructions in the README file:

Below I will show some examples, these are contained in the unit tests.

1.1 Start Stopwatch Time

Measuring the time spent in processing.

from precision import Precision

p = Precision()
p.tic()
for i in range(0, 1000): print(i)
p.toc()

The output will look something like this:

: > Elapsed time is 0:0:2 secounds.

1.2 Percentiles of a Data Set

This is used to get a percentile. In the example below, we are creating a range of ordinal dates by cutting 5% from the left and 5% from the right.

from datetime import datetime
from precision import Precision

p = Precision()
d = [i for i in p.dtrange(datetime(2018, 6, 12), 
                          datetime(2059, 12, 12), 
                          {'days':1, 'hours':2})]
x = [p.datenum(i.date()) for i in d]

x1 = p.prctile(x, 5)
x2 = p.prctile(x, 95)
r = (x2 - x1)

The output will look something like this:

5% lower: 737980.1
5% higher: 751621.9
delta: 13641.800000000047

1.3 Cell Array (cell2mat)

This converts a cell array to an ordinary array of the underlying data type.

from precision import Precision

p = Precision()
p.cell2mat([[1, 2], [3, 4]])
p.cell2mat('1 2; 3 4')

The output will look something like this:

matrix([[1, 2],
        [3, 4]])

1.4 Cell Array (num2cell)

Convert array to cell array with consistently sized cells.

import numpy
from precision import Precision

p = Precision()
x = numpy.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], numpy.int64)
p.num2cell(x)

The output will look something like this:

[[1, 2, 3], [4, 5, 6], [7, 8, 9]]

1.5 Concatenate Strings (strcat)

This concatenates strings horizontally using strcat.

import pandas
from precision import Precision

p = Precision()
df = pandas.DataFrame(data={'A': [1, 2], 'B': [3, 4]}, dtype=numpy.int8)
p.strcat(df, 'B')

The output will look something like this:

['3', '4']

1.6 Histogram (histc)

This counts the number of values in x that are within each specified bin range. The input, binranges, determines the endpoints for each bin. The output, bincounts, contains the number of elements from x in each bin.

import numpy 
from precision import Precision

p = Precision()
v = numpy.array([[1.5, 2.0, 3], [4, 5.9, 6]], numpy.int64)
p.histc(v, numpy.amax(v) + 1)

The output will look something like this:

(array([1, 1, 1, 0, 1, 1, 1]), array([1., 1.71428571, 2.42857143, 
       3.14285714, 3.85714286, 4.57142857, 5.28571429, 6.]))

1.7 Unique

Looking for unique values in an array and returning the indexes, inverse, and counts.

import numpy 
from precision import Precision

p = Precision()
x = [0, 1, 1, 2, 3, 4, 4, 5, 5, 6, 7, 7, 7]
p.unique(numpy.array([x]))

The output will look something like this:

array([[array([0, 1, 2, 3, 4, 5, 6, 7]),
        array([[ 0,  1,  3,  4,  5,  7,  9, 10]]),
        array([0, 1, 1, 2, 3, 4, 4, 5, 5, 6, 7, 7, 7]),
        array([1, 2, 1, 1, 2, 2, 1, 3])]], dtype=object)

1.8 Overlaps

Looking for the overlays between two arrays returning the index.

import numpy 
from precision import Precision

p = Precision()
x, y = p.overlap2d(numpy.array(['A','B','B','C']), 
                   numpy.array(['C','A','B','C','D']))

The output will look something like this:

(array([0, 1, 2, 3]), array([1, 2, 0, 3]))

Considerations

There are functions that are not exactly MatLab but will serve as support, I hope it can help someone. There is an interesting article in NumPy for users who are migrating from MatLab to Python.

Further Reading

MATLAB vs Python: Why and How to Make the Switch

Creating a Plot Charts in Python with Matplotlib

Python Tutorial - Python GUI Programming - Python GUI Examples (Tkinter Tutorial)

Essential Python 3 code for lists

*Originally published by Ederson Corbari   at *dzone.com

=============================================================

Thanks for reading :heart: If you liked this post, share it with all of your programming buddies! Follow me on Facebook | Twitter