semvec/pypi-packages huggingface dataset:
tempmailio 0.0.4
python wrapper for tempmail.io
Requires Python: >=3.5

# tempmailio

![python_version](https://img.shields.io/static/v1?label=Python&message=3.5%20|%203.6%20|%203.7&color=blue) [![PyPI downloads/month](https://img.shields.io/pypi/dm/tempmailio?logo=pypi&logoColor=white)](https://pypi.python.org/pypi/tempmailio)

## Description

python wrapper for tempmail.io

## Install

````bash
pip install tempmailio
# or
pip3 install tempmailio
````

## Usage

```python
import time

from tempmailio import *

mail = TempMailI0(
    user_name='test',
    domain=Domain.cloudmail()
)

success = mail.create_email()

print(mail.email_address)

while True:
    inbox = mail.get_inbox()

    if len(inbox) > 0mermaid :
        inbox[0].jsonprint()
        exit(0)

    time.sleep(2.5)
```
ThermCoeff 0.2
Module for thermoelastic coefficient identification

ThermCoeff - Thermoelastic coefficent evaluation
------------------------------------

Thermoelastic coefficent evaluation for Thermoelastic Stress Analysis (TSA)


Simple examples
---------------

Here is a simple example on how to use the code:

.. code-block:: python

	pip install ThermCoeff

Import packages:

.. code-block:: python

	import numpy as np
	import pysfmov as sfmov
	import ThermCoeff
	
Thermoelastic coefficient of standard materials is available as:

.. code-block:: python

	s = 'steel'                         # Steel material is chosen
	km = ThermCoeff.from_material(s)    # Thermoelastic coefficient of steel is obtained
	
The following materials are available: aluminium, epoxy, glass, magnesium, steel, titanium

If strain gauge calibration is performed and the strain is acquired externally during the experiment:

.. code-block:: python
	
	# Uniaxial strain-gauge					
	eps = np.random.rand(1000)		# Simulated strain from strain-gauge
	strain = ThermCoeff.get_strain(eps)	# Obtain strain
	
	# Strain-gauge rosette
	eps = np.random.rand(1000, 3)				# Simulated strain from rosette
	configuration = '90' 					# Angular configuration of the rosette
	strain = ThermCoeff.get_strain(eps, configuration)	# Obtain strain
	
Once the strain is obtained (or already known):

.. code-block:: python

	filename = './data/rec.sfmov'   # Path to the thermal video
	data = sfmov.get_data(filename) # Load the data
	fs = 400			# Sampling frequency [Hz]
	fl = 40				# Load frequency [Hz]
	location = 56, 38, 30, 70	# Location of the strain-gauge on the camera field of view

	E = 75 * 10**9 			# Young Modulus [Pa]
	ni = 0.33 			# Poisson's ratio
	
	km = ThermCoeff.from_strain_gauge(data, fs, fl, E, ni, strain, location)


Reference:
<https://www.sciencedirect.com/science/article/pii/S0142112320301924>