Begin Python with TCLab
Main.CourseProjects History
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%width=30px%Attach:classroom.png [[https://classroom.google.com/c/NDM2MTQ5NjEyODc4?cjc=xhdzu2z|Begin Python 🐍 in Google Classroom]]
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speedup = 100
to:
speedup = 100 # Emulator (digital twin) speed-up
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!!!! TCLab Digital Twin
If no hardware is available, use ''TCLabModel()'' in the place of ''TCLab()''. The emulator (digital twin) can be run faster than real-time as shown below:
(:source lang=python:)
import tclab
import numpy as np
tclab_hardware = False
if tclab_hardware:
mlab = tclab.TCLab # Physical hardware
else:
speedup = 100
mlab = tclab.setup(connected=False, speedup=speedup)
n = 500
tm = np.linspace(0,2*n,n+1)
# Connect to TCLab
with mlab() as lab:
# set heater values
lab.Q1(70)
lab.Q2(20)
for t in tclab.clock(tm[-1]+1, 2):
print('Time: ' + str(t) + \
' T1: ' + str(round(lab.T1,2)) + \
' T2: ' + str(round(lab.T2,2)))
(:sourceend:)
Change ''tclab_hardware'' from ''False'' to ''True'' to use the physical hardware.
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----
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Attach:download.png [[https://github.com/APMonitor/begin_python|Begin Python 🐍 with TCLab]]
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Attach:download.png [[https://github.com/APMonitor/begin_python|Begin Python 🐍 with TCLab (GitHub)]]
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[[Main/DataScience|🎓 Introduction to Data Science]]
[[https://apmonitor.com/pdc|🎓 Process Dynamics and Control]]
[[https://apmonitor.com/do|🎓 Machine Learning and Dynamic Optimization]]
[[https://apmonitor.com/pdc|🎓 Process Dynamics and Control]]
[[https://apmonitor.com/do|🎓 Machine Learning and Dynamic Optimization]]
to:
-> [[Main/DataScience|🎓 Introduction to Data Science]]
-> [[https://apmonitor.com/pdc|🎓 Process Dynamics and Control]]
-> [[https://apmonitor.com/do|🎓 Machine Learning and Dynamic Optimization]]
-> [[https://apmonitor.com/pdc|🎓 Process Dynamics and Control]]
-> [[https://apmonitor.com/do|🎓 Machine Learning and Dynamic Optimization]]
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After completing this course, there are more advanced courses including:
* [[Main/DataScience|Introduction to Data Science]]
*[[https://apmonitor.com/pdc|Process Dynamics and Control]]
* [[https://apmonitor.com/do|Machine Learning and Dynamic Optimization]]
* [[Main/DataScience|Introduction to Data Science]]
*
to:
After completing this course, there are next courses that build upon the basic Python programming experience.
[[Main/DataScience|🎓 Introduction to Data Science]]
[[https://apmonitor.com/pdc|🎓 Process Dynamics and Control]]
[[https://apmonitor.com/do|🎓 Machine Learning and Dynamic Optimization]]
[[Main/DataScience|🎓 Introduction to Data Science]]
[[https://apmonitor.com/pdc|🎓 Process Dynamics and Control]]
[[https://apmonitor.com/do|🎓 Machine Learning and Dynamic Optimization]]
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The '''Begin Python with TCLab''' is an introduction and review of basic Python programming and a tutorial on using the TCLab with 12 lessons that can be completed in 2-3 hours (15-20 minutes each). It has a challenge project to design temperature control for an egg incubator.
to:
The '''Begin Python with TCLab''' is an introduction and review of basic Python programming with 12 lessons that can be completed in 2-3 hours (15-20 minutes each).
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The egg incubator simulator is a preliminary project in preparation for the [[Main/DataScience|Data Science]] material.
to:
The course is designed to start from no programming experience and guide a self-paced learner through the basics of Python. The 12 modules are IPython notebooks that are run from a Jupyter Notebook. The tutorials start with how to install Anaconda and use the hands-on lab kit. The exercises are interactive and there are solution videos for each module for those who need additional help.
# [[https://github.com/APMonitor/begin_python/blob/master/01.%20Overview.ipynb|Overview]]
# [[https://github.com/APMonitor/begin_python/blob/master/02.%20Debugging.ipynb|Debugging]]
# [[https://github.com/APMonitor/begin_python/blob/master/03.%20Variables.ipynb|Variables]]
# [[https://github.com/APMonitor/begin_python/blob/master/04.%20Printing.ipynb|Printing]]
# [[https://github.com/APMonitor/begin_python/blob/master/05.%20Classes%20and%20Objects.ipynb|Classes and Objects]]
# [[https://github.com/APMonitor/begin_python/blob/master/06.%20Functions.ipynb|Functions]]
# [[https://github.com/APMonitor/begin_python/blob/master/07.%20Loops.ipynb|Loops]]
# [[https://github.com/APMonitor/begin_python/blob/master/08.%20Input.ipynb|Input]]
# [[https://github.com/APMonitor/begin_python/blob/master/09.%20If%20Statements.ipynb|If Statements]]
# [[https://github.com/APMonitor/begin_python/blob/master/10.%20Lists%20and%20Tuples.ipynb|Lists and Tuples]]
# [[https://github.com/APMonitor/begin_python/blob/master/11.%20Dictionaries.ipynb|Dictionaries]]
# [[https://github.com/APMonitor/begin_python/blob/master/12.%20Plotting.ipynb|Plotting]]
After completing this course, there are more advanced courses including:
* [[Main/DataScience|Introduction to Data Science]]
* [[https://apmonitor.com/pdc|Process Dynamics and Control]]
* [[https://apmonitor.com/do|Machine Learning and Dynamic Optimization]]
# [[https://github.com/APMonitor/begin_python/blob/master/01.%20Overview.ipynb|Overview]]
# [[https://github.com/APMonitor/begin_python/blob/master/02.%20Debugging.ipynb|Debugging]]
# [[https://github.com/APMonitor/begin_python/blob/master/03.%20Variables.ipynb|Variables]]
# [[https://github.com/APMonitor/begin_python/blob/master/04.%20Printing.ipynb|Printing]]
# [[https://github.com/APMonitor/begin_python/blob/master/05.%20Classes%20and%20Objects.ipynb|Classes and Objects]]
# [[https://github.com/APMonitor/begin_python/blob/master/06.%20Functions.ipynb|Functions]]
# [[https://github.com/APMonitor/begin_python/blob/master/07.%20Loops.ipynb|Loops]]
# [[https://github.com/APMonitor/begin_python/blob/master/08.%20Input.ipynb|Input]]
# [[https://github.com/APMonitor/begin_python/blob/master/09.%20If%20Statements.ipynb|If Statements]]
# [[https://github.com/APMonitor/begin_python/blob/master/10.%20Lists%20and%20Tuples.ipynb|Lists and Tuples]]
# [[https://github.com/APMonitor/begin_python/blob/master/11.%20Dictionaries.ipynb|Dictionaries]]
# [[https://github.com/APMonitor/begin_python/blob/master/12.%20Plotting.ipynb|Plotting]]
After completing this course, there are more advanced courses including:
* [[Main/DataScience|Introduction to Data Science]]
* [[https://apmonitor.com/pdc|Process Dynamics and Control]]
* [[https://apmonitor.com/do|Machine Learning and Dynamic Optimization]]
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The project is a review of all course material with real data from temperature sensors in the Temperature Control Lab (TCLab). The temperatures are adjusted with heaters that are adjusted with the TCLab. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]].
to:
The final project is a review of all course material with real data from temperature sensors in the Temperature Control Lab (TCLab). The temperatures are adjusted with heaters that are adjusted with the TCLab. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]].
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The projects are a review of all course material with real data from temperature sensors in the Temperature Control Lab (TCLab). The temperatures are adjusted with heaters that are adjusted with the TCLab. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]].
to:
The project is a review of all course material with real data from temperature sensors in the Temperature Control Lab (TCLab). The temperatures are adjusted with heaters that are adjusted with the TCLab. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]].
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(:title Course Projects:)
(:keywordshomework, nonlinear, optimization, engineering optimization, Excel, Mathcad, Visual Basic, Python, MATLAB, differential, algebraic, modeling language, university course:)
(:descriptionProjects for Problem-Solving Techniques for Chemical Engineers at Brigham Young University:)
The purpose of the projects is to help integrate the individual programming skills learned this semester to solve engineering problems.
!!!! Project 1: Begin Python with TCLab
(:keywords
(:description
The purpose of the projects is to help integrate the individual programming skills learned this semester to solve engineering problems
!!!! Project 1
to:
(:title Begin Python with TCLab:)
(:keywords python, beginner, introduction, newbie, engineer, start, basic, Jupyter, notebook, IPython, course:)
(:description Introduction to Python with an Arduino Temperature Control Lab. The hands-on exercises reinforce programming skills with the computer controlling heaters, an LED, and measuring temperature.:)
(:keywords python, beginner, introduction, newbie, engineer, start, basic, Jupyter, notebook, IPython, course:)
(:description Introduction to Python with an Arduino Temperature Control Lab. The hands-on exercises reinforce programming skills with the computer controlling heaters, an LED, and measuring temperature.:)
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The egg incubator simulator is a preliminary project for the engineering data analysis project below.
!!!!Project 2: Data Science
The second project is an introduction to data science. The final project of the short course is to do the data analysis to estimate thermal conductivity.
Attach:download.png [[https://github.com/APMonitor/begin_python|Data Science 🐍 with Python]]
(:html:)
<iframe width="560" height="315" src="https://www.youtube.com/embed/videoseries?list=PLLBUgWXdTBDg1Qgmwt4jKtVn9BWh5-zgy" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
(:htmlend:)
The 12 modules step through the basics of data science. They give the skills needed to work on the final project. In the final project, metal coins, plastic, and cardboard are inserted in between the two heaters so that there is a conduction path for heat between the two sensors. The temperature difference and temperature levels are affected by the ability of the material to conduct heat from heater 1 and temperature sensor {`(T_1)`} to the other temperature sensor {`(T_2)`}.
%height=125px%Attach:tclab_copper.jpg %height=125px%Attach:tclab_plastic.jpg %height=125px%Attach:tclab_cardboard.jpg
You may not always know how to solve the problems initially or how to construct the algorithms. You may not know the function that you need or the name of the property associated with an object. This is by design. You are to search out the information that you might need using help resources, online resources, textbooks, etc.
You will be assessed not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help you and others when reviewing your code.
!!!!
The second project is an introduction to data science. The final project of the short course is to do the data analysis to estimate thermal conductivity.
Attach:download.png [[https://github.com/APMonitor/begin_python|Data Science 🐍
(:html:)
<iframe width="560" height="315" src="
(:htmlend:)
The 12 modules step through the basics of data science
%height=125px%Attach:tclab_copper.jpg %height=125px%Attach:tclab_plastic.jpg %height=125px%Attach:tclab_cardboard.jpg
You may not always know how to solve the problems initially or how to construct the algorithms. You may not know the function that you need or the name of the property associated with an object. This is by design. You are to search out the information that you might need using help resources, online resources, textbooks, etc.
You will be assessed not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help you and others when reviewing your code.
to:
The egg incubator simulator is a preliminary project in preparation for the [[Main/DataScience|Data Science]] material.
!!!! Temperature Control Lab
The projects are a review of all course material with real data from temperature sensors in the Temperature Control Lab (TCLab). The temperatures are adjusted with heaters that are adjusted with the TCLab. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]].
!!!! Temperature Control Lab
The projects are a review of all course material with real data from temperature sensors in the Temperature Control Lab (TCLab). The temperatures are adjusted with heaters that are adjusted with the TCLab. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]].
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The second project is an introduction to data science. The final project of the short course is to do the data analysis to estimate thermal conductivity.
Attach:download.png [[https://github.com/APMonitor/begin_python|Data Science 🐍 with Python]]
Attach:download.png [[https://github.com/APMonitor/begin_python|Data Science 🐍 with Python]]
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The second project is an introduction to data science. The final project of the short course is to do the data analysis to estimate thermal conductivity.
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_A.ipynb|TCLab A: Build Loops, Plots, and Regressions]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B: Interpolate and Solve Equations]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C.ipynb|TCLab C: Determine Thermal Conductivity]]
Metal coins, plastic, and cardboard are inserted in between the two heaters so that there is a conduction path for heat between the two sensors. The temperature difference and temperature levels are affected by the ability of the material to conduct heat from heater 1 and temperature sensor {`(T_1)`} to the other temperature sensor {`(T_2)`}.
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_A.ipynb|TCLab A: Build Loops, Plots, and Regressions]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B: Interpolate and Solve Equations]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C.ipynb|TCLab C: Determine Thermal Conductivity]]
Metal
to:
The 12 modules step through the basics of data science. They give the skills needed to work on the final project. In the final project, metal coins, plastic, and cardboard are inserted in between the two heaters so that there is a conduction path for heat between the two sensors. The temperature difference and temperature levels are affected by the ability of the material to conduct heat from heater 1 and temperature sensor {`(T_1)`} to the other temperature sensor {`(T_2)`}.
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You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help you and others when reviewing your code.
to:
You will be assessed not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help you and others when reviewing your code.
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<iframe width="560" height="315" src="https://www.youtube.com/embed/videoseries?list=PLLBUgWXdTBDg1Qgmwt4jKtVn9BWh5-zgy" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
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<iframe width="560" height="315" src="https://www.youtube.com/embed/EO_YpBs8cs0" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
(:htmlend:)
The second project is an introduction to data science. The final project of the short course is to do the data analysis to estimate thermal conductivity.
<iframe width="560" height="315" src="https://www.youtube.com/embed/EO_YpBs8cs0" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
(:htmlend:)
The second project is an introduction to data science. The final project of the short course is to do the data analysis to estimate thermal conductivity.
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!!!! Project 2: Introduction to Data Science
to:
!!!! Project 2: Data Science
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The projects are a review of all course material with real data from temperature sensors in the Temperature Control Lab (TCLab). The temperatures are adjusted with heaters that are adjusted with the TCLab. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]] but for automatic control.
to:
The projects are a review of all course material with real data from temperature sensors in the Temperature Control Lab (TCLab). The temperatures are adjusted with heaters that are adjusted with the TCLab. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]].
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The egg incubator simulator is a preliminary project for the engineering data analysis project below. Labs A-C are a review of all course material with real data from temperature sensors. The temperatures are adjusted with heaters that are adjusted with an Arduino micro-controller. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]] but for automatic control.
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(:html:)
<a href='https://apmonitor.com/pdc/index.php/Main/PurchaseLabKit'>
<button class="button"><span>Get Lab Kit</span></button>
</a>
(:htmlend:)
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(:html:)
<a href='https://apmonitor.com/pdc/index.php/Main/PurchaseLabKit'>
<button class="button"><span>Get Lab Kit</span></button>
</a>
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The egg incubator simulator is a preliminary project for the engineering data analysis project below.
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!!!! Temperature Control Lab
The projects are a review of all course material with real data from temperature sensors in the Temperature Control Lab (TCLab). The temperatures are adjusted with heaters that are adjusted with the TCLab. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]] but for automatic control.
%width=550px%Attach:arduino_lab_kit2.png
(:html:)
<a href='https://apmonitor.com/pdc/index.php/Main/PurchaseLabKit'>
<button class="button"><span>Get Lab Kit</span></button>
</a>
(:htmlend:)
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!!!! Project 2:
to:
!!!! Project 2: Introduction to Data Science
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The purpose of the project is to help integrate the individual programming skills learned this semester to solve engineering problems. The '''Begin Python with TCLab''' is an introduction and review of basic Python programming and a tutorial on using the TCLab with 12 lessons that can be completed in 2-3 hours (15-20 minutes each). It has a challenge project to design temperature control for an egg incubator.
to:
The purpose of the projects is to help integrate the individual programming skills learned this semester to solve engineering problems.
!!!! Project 1: Begin Python with TCLab
The '''Begin Python with TCLab''' is an introduction and review of basic Python programming and a tutorial on using the TCLab with 12 lessons that can be completed in 2-3 hours (15-20 minutes each). It has a challenge project to design temperature control for an egg incubator.
!!!! Project 1: Begin Python with TCLab
The '''Begin Python with TCLab''' is an introduction and review of basic Python programming and a tutorial on using the TCLab with 12 lessons that can be completed in 2-3 hours (15-20 minutes each). It has a challenge project to design temperature control for an egg incubator.
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!!!! Project 2:
The second project is a review of the course material. The final part of the project is to do the data analysis to estimate thermal conductivity.
The second project is a review of the course material. The final part of the project is to do the data analysis to estimate thermal conductivity.
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(:title Course Project:)
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(:title Course Projects:)
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The egg incubator simulator is a warm-up project for the engineering data analysis project below. Labs A-C are a review of all course material with real data from temperature sensors. The temperatures are adjusted with heaters that are adjusted with an Arduino micro-controller. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]] but for automatic control.
to:
The egg incubator simulator is a preliminary project for the engineering data analysis project below. Labs A-C are a review of all course material with real data from temperature sensors. The temperatures are adjusted with heaters that are adjusted with an Arduino micro-controller. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]] but for automatic control.
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Attach:download.png [[https://github.com/APMonitor/begin_python|Begin Python with TCLab]]
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Attach:download.png [[https://github.com/APMonitor/begin_python|Begin Python 🐍 with TCLab]]
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(:html:)
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The purpose of the project is to help integrate the individual programming skills learned this semester to solve engineering problems. Because these projects are meant to help develop problem-solving skills, the tasks are more involved than typical homework problems.
The project is a review of all course material but with real data from temperature sensors. The temperatures are adjusted with heaters that are adjusted with an Arduino micro-controller. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]] but for automatic control.
The project is a review of all course material but
to:
The purpose of the project is to help integrate the individual programming skills learned this semester to solve engineering problems. The '''Begin Python with TCLab''' is an introduction and review of basic Python programming and a tutorial on using the TCLab with 12 lessons that can be completed in 2-3 hours (15-20 minutes each). It has a challenge project to design temperature control for an egg incubator.
Attach:download.png [[https://github.com/APMonitor/begin_python|Begin Python with TCLab]]
The egg incubator simulator is a warm-up project for the engineering data analysis project below. Labs A-C are a review of all course material with real data from temperature sensors. The temperatures are adjusted with heaters that are adjusted with an Arduino micro-controller. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]] but for automatic control.
Attach:download.png [[https://github.com/APMonitor/begin_python|Begin Python with TCLab]]
The egg incubator simulator is a warm-up project for the engineering data analysis project below. Labs A-C are a review of all course material with real data from temperature sensors. The temperatures are adjusted with heaters that are adjusted with an Arduino micro-controller. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]] but for automatic control.
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The project is a review of all course material but with real data from temperature sensors. The temperatures are adjusted with heaters that are adjusted with an Arduino micro-controller. This lab hardware is also used in the [[https://apmonitor.com/pdc/index.php/Main/ArduinoTemperatureControl|Process Dynamics and Control Course]] and the [[https://apmonitor.com/do/index.php/Main/AdvancedTemperatureControl|Dynamic Optimization Course]] but for automatic control.
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%height=125px%Attach:tclab_copper.png %height=125px%Attach:tclab_plastic.png %height=125px%Attach:tclab_cardboard.png
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Metal (coin), plastic, and cardboard are inserted in between the two heaters. The temperature difference and temperature levels are affected by the ability of the material to conduct heat from heater 1 and temperature sensor {`(T_1)`} to the other temperature sensor {`(T_2)`}.
to:
Metal coins, plastic, and cardboard are inserted in between the two heaters so that there is a conduction path for heat between the two sensors. The temperature difference and temperature levels are affected by the ability of the material to conduct heat from heater 1 and temperature sensor {`(T_1)`} to the other temperature sensor {`(T_2)`}.
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Metal (coin), plastic, and cardboard are inserted in between the two heaters. The temperature difference and temperature levels are affected by the ability of the material to conduct heat from one temperature heat sink {`(T_1)`} to the other {`(T_2)`}.
to:
Metal (coin), plastic, and cardboard are inserted in between the two heaters. The temperature difference and temperature levels are affected by the ability of the material to conduct heat from heater 1 and temperature sensor {`(T_1)`} to the other temperature sensor {`(T_2)`}.
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Metal (coin), plastic, and cardboard are inserted in between the two heaters. The temperature difference and temperature levels are affected by the ability of the material to conduct heat from one temperature heat sink {`(T_1)`} to the other {`(T_2)`}.
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%height=100px%Attach:tclab_copper.png %height=100px%Attach:tclab_plastic.png %height=100px%Attach:tclab_cardboard.png
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png
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%width=200px%Attach:tclab_copper.png Metal
%width=200px%Attach:tclab_plastic.png Plastic
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_A.ipynb|TCLab A: Loops, Plotting, and Regression]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B:Interpolation and Solve Equations]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B:
to:
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_A.ipynb|TCLab A: Build Loops, Plots, and Regressions]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B: Interpolate and Solve Equations]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B: Interpolate and Solve Equations]]
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B: Interpolation, Solve Equations (Linear, Nonlinear, Differential)]]
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B: Interpolation and Solve Equations]]
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B: Interpolation and Solve Equations (Linear, Nonlinear, Differential)]]
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B: Interpolation, Solve Equations (Linear, Nonlinear, Differential)]]
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B|TCLab B: Linear / Nonlinear Equations and Differential Equations]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C|TCLab C: Determine Thermal Conductivity]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C|TCLab C: Determine Thermal Conductivity]]
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B.ipynb|TCLab B: Interpolation and Solve Equations (Linear, Nonlinear, Differential)]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C.ipynb|TCLab C: Determine Thermal Conductivity]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C.ipynb|TCLab C: Determine Thermal Conductivity]]
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B|TCLab B: Linear / Nonlinear Equations and Differential Equation Solutions]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C|TCLab C:Estimate Thermal Conductivity]]
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B|TCLab B: Linear / Nonlinear Equations and Differential Equations]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C|TCLab C: Determine Thermal Conductivity]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C|TCLab C: Determine Thermal Conductivity]]
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You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help others when reviewing your code.
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_A.ipynb|TCLab A (Jupyter Notebook)]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B|TCLab B(Jupyter Notebook)]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C|TCLab C (Jupyter Notebook)]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B|TCLab B
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Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_A.ipynb|TCLab A: Loops, Plotting, and Regression]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B|TCLab B: Linear / Nonlinear Equations and Differential Equation Solutions]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C|TCLab C: Estimate Thermal Conductivity]]
You may not always know how to solve the problems initially or how to construct the algorithms. You may not know the function that you need or the name of the property associated with an object. This is by design. You are to search out the information that you might need using help resources, online resources, textbooks, etc.
You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help you and others when reviewing your code.
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B|TCLab B: Linear / Nonlinear Equations and Differential Equation Solutions]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C|TCLab C: Estimate Thermal Conductivity]]
You may not always know how to solve the problems initially or how to construct the algorithms. You may not know the function that you need or the name of the property associated with an object. This is by design. You are to search out the information that you might need using help resources, online resources, textbooks, etc.
You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help you and others when reviewing your code.
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----
!!!! Candidate Project - Heat Exchanger Design
A sample project is a program for the design of heat exchangers to transfer heat between process streams. The equations are contained in the problem statement and data should be retrieved from the DIPPR database or the tables below.
* [[Attach:heat_exchanger_project.pdf|Heat Exchanger Project]]
** [[Attach:project_thermophysical_properties.zip|Thermophysical Property Information (Excel)]]
!!!! Project Help Resources
* [[Attach:heat_exchanger_sample_solution.pdf|Project Sample Solution]]
* [[Attach:heat_exchanger_report_solution.zip|Report at 7 Test Conditions (Excel)]]
Because the project is well-defined, students who choose the heat exchanger project will have a maximum of B grade for this project.
!!!! Student Defined Project
The second option for a project is that it is selected by the students. The project should consist of retrieving data from an external source or [[PythonWidgets|from a user]], processing that data into useful information, and presenting the results in an actionable form. In most cases, students are too ambitious with the project scope. To help manage expectations and limit the amount of work to a reasonable time, each project should be approved by the instructor or TA. The heat exchanger project listed above is an example of an appropriate scope for a programming project.
!!!! Final Report (2 page) and Video (5 min)
The final report is an executive summary with the following recommended sections:
* Abstract (overview of the entire project, summarized in one paragraph)
* Introduction (1-2 paragraphs introducing the problem)
* Results (present program features with details on inputs and outputs)
* Discussion (why is the program innovative or significant?)
* Conclusion (summarize the results, what future work can be done?)
The final report should be accompanied by a 5 minute video. Please include a link to the video in the 2 page report.
(:html:)
<iframe width="560" height="315" src="https://www.youtube.com/embed/S1ayo1n7AsM" frameborder="0" allowfullscreen></iframe>
(:htmlend:)
----
!!!! Leadership Assessments
You are also required to individually generate a leadership evaluation that will be turned in with your project. This leadership assessment is composed of individual goals and an assessment on improvement. Instructions and examples are provided below.
* [[Attach:leadership_assessment.pdf|Leadership Assessment]]
The leadership evaluation is for the project team work. Below is an overview of the timeline:
# Solicit feedback from your team members during the project
# Summarize the feedback and write an improvement statement by the first progress report
# Implement changes and report back on improvements by the project due date
Submit the leadership assessment to Learning Suite (see Leadership Assessment Assignment) when the project is due.
to:
You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help others when reviewing your code.
The final project is divided into multiple parts that are turned in apart from the regularly scheduled homework and are due every week on Friday.
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_A.ipynb|TCLab A (Jupyter Notebook)]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B|TCLab B (Jupyter Notebook)]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C|TCLab C (Jupyter Notebook)]]
----
The final project is divided into multiple parts that are turned in apart from the regularly scheduled homework and are due every week on Friday.
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_A.ipynb|TCLab A (Jupyter Notebook)]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_B|TCLab B (Jupyter Notebook)]]
Attach:download.png [[https://nbviewer.jupyter.org/url/apmonitor.com/che263/uploads/Main/TCLab_C|TCLab C (Jupyter Notebook)]]
----
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The leadership evaluation is for both projects. Below is an overview of the timeline:
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The leadership evaluation is for the project team work. Below is an overview of the timeline:
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!!!! Final Report (2 page) and Video (5 min)
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(:title Course Project:)
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The final report is an executive summary with the following recommended sections:
* Abstract (overview of the entire project, summarized in one paragraph)
* Introduction (1-2 paragraphs introducing the problem)
* Results (present program features with details on inputs and outputs)
* Discussion (why is the program innovative or significant?)
* Conclusion (summarize the results, what future work can be done?)
The final report should be accompanied by a 5 minute video. Please include a link to the video in the 2 page report.
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The second option for a project is that it is selected by the students. The project should consist of retrieving data from an external source, processing that data into useful information, and presenting the results in a useful form. In most cases, students are too ambitious with the project scope. To help manage expectations and limit the amount of work to a reasonable time, each project should be approved by the instructor or TA. The heat exchanger project listed above is an example of an appropriate scope for a programming project.
to:
The second option for a project is that it is selected by the students. The project should consist of retrieving data from an external source or [[PythonWidgets|from a user]], processing that data into useful information, and presenting the results in an actionable form. In most cases, students are too ambitious with the project scope. To help manage expectations and limit the amount of work to a reasonable time, each project should be approved by the instructor or TA. The heat exchanger project listed above is an example of an appropriate scope for a programming project.
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The purpose of the project is to help integrate the individual programming skills learned this semester to solve engineering problems. Because these project are meant to help develop problem-solving skills, the tasks are more involved than typical homework problems.
to:
The purpose of the project is to help integrate the individual programming skills learned this semester to solve engineering problems. Because these projects are meant to help develop problem-solving skills, the tasks are more involved than typical homework problems.
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Because the project is well-defined, students who choose the heat exchanger project will have a maximum of 90% of the total credit for this project.
to:
Because the project is well-defined, students who choose the heat exchanger project will have a maximum of B grade for this project.
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The purpose of these projects are to help you integrate the individual programming skills that you have learned this semester to solve engineering problems. You can solve the problems within the constraints of the requirements of the assignment in any programming language. Because these project are meant to help you develop problem-solving skills, the tasks are more involved than typical homework problems. You will find that you do not always know how to solve the problems initially or how to construct the algorithms. You may not know the function that you need or the name of the property associated with an object. This is by design. You are to search out the information that you might need using help menus, online resources, textbooks, etc.
You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help others when reviewing your code. You will work in teams of 2-3 people. On the first project you should not consult with any other students except the TA and the instructor. For the second project you will be able to select your own programming assignment.
You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help others when reviewing your code. You will work in teams of 2-3 people. On the first project you should not consult with any other students except the TA and the instructor. For the second project you will be able to select your own programming assignment
to:
The purpose of the project is to help integrate the individual programming skills learned this semester to solve engineering problems. Because these project are meant to help develop problem-solving skills, the tasks are more involved than typical homework problems.
You may not always know how to solve the problems initially or how to construct the algorithms. You may not know the function that you need or the name of the property associated with an object. This is by design. You are to search out the information that you might need using help resources, online resources, textbooks, etc.
You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help others when reviewing your code. You will work in teams of 2-3 people.
You may not always know how to solve the problems initially or how to construct the algorithms. You may not know the function that you need or the name of the property associated with an object. This is by design. You are to search out the information that you might need using help resources, online resources, textbooks, etc.
You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help others when reviewing your code. You will work in teams of 2-3 people.
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!!!! Project #1 - Heat Exchanger Design
The first project takes the place of an exam on programming. It is a program for the design of heat exchangers to transfer heat between process streams. The equations are contained in the problem statement and data should be retrieved from the DIPPR database or the tables below.
to:
!!!! Candidate Project - Heat Exchanger Design
A sample project is a program for the design of heat exchangers to transfer heat between process streams. The equations are contained in the problem statement and data should be retrieved from the DIPPR database or the tables below.
A sample project is a program for the design of heat exchangers to transfer heat between process streams. The equations are contained in the problem statement and data should be retrieved from the DIPPR database or the tables below.
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Because the project is well-defined, students who choose the heat exchanger project will have a maximum of 90% of the total credit for this project.
!!!! Student Defined Project
The second option for a project is that it is selected by the students. The project should consist of retrieving data from an external source, processing that data into useful information, and presenting the results in a useful form. In most cases, students are too ambitious with the project scope. To help manage expectations and limit the amount of work to a reasonable time, each project should be approved by the instructor or TA. The heat exchanger project listed above is an example of an appropriate scope for a programming project.
!!!! Student Defined Project
The second option for a project is that it is selected by the students. The project should consist of retrieving data from an external source, processing that data into useful information, and presenting the results in a useful form. In most cases, students are too ambitious with the project scope. To help manage expectations and limit the amount of work to a reasonable time, each project should be approved by the instructor or TA. The heat exchanger project listed above is an example of an appropriate scope for a programming project.
Deleted lines 33-38:
The second project is selected by the group. The project should consist of retrieving data from an external source, processing that data into useful information, and presenting the results in a useful form. In most cases, students are too ambitious with the project scope. To help manage expectations and limit the amount of work to a reasonable time, each project should be approved by the instructor or TA.
----
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You are also required to individually generate a leadership evaluation that will be turned in with your projects. This leadership assessment is composed of individual goals and an assessment on improvement. Instructions and examples are provided below.
to:
You are also required to individually generate a leadership evaluation that will be turned in with your project. This leadership assessment is composed of individual goals and an assessment on improvement. Instructions and examples are provided below.
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# Solicit feedback from your team members
#
For Project 2
# Implement changes for
# Redo the leadership assessment for project 2 (solicit feedback from team members and write a summary and improvement plan).
For the first project, turn in the leadership assessment with the project (zipped archive) to Learning Suite. For the second project, submit the leadership assessment to Learning Suite (see Leadership Assessment Assignment)
to:
# Solicit feedback from your team members during the project
# Summarize the feedback and write an improvement statement by the first progress report
# Implement changes and report back on improvements by the project due date
Submit the leadership assessment to Learning Suite (see Leadership Assessment Assignment) when the project is due.
# Summarize the feedback and write an improvement statement by the first progress report
# Implement changes and report back on improvements by the project due date
Submit the leadership assessment to Learning Suite (see Leadership Assessment Assignment) when the project is due.
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You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help others when reviewing your code. You will work in teams of 2-3 people.
As part of your grade, please sent an email to the TA by the due date and rate each student (including yourself) in your group by contribution from 0 to 10 (don’t forget to include the group number in your email). With 0 being no contribution, 5 being expected contribution where the student was a good contributor and performed their part, and 10 being this student did the project themselves. Also explain in your email any special circumstances or reasons why someone is below 5 or above 5. As a clarification you are not grading their competency, but that they tried equally hard and performed their responsibility. There is no outsourcing of the project and it must be completed by your group members. On the first project you may
As part of your grade, please sent an email to the TA by the due date and rate each student (including yourself) in your group by contribution from 0 to 10 (don’t forget to include the group number in your email). With 0 being no contribution, 5 being expected contribution where the student was a good contributor and performed their part, and 10 being this student did the project themselves. Also explain in your email any special circumstances or reasons why someone is below 5 or above 5. As a clarification you are not grading their competency, but that they tried equally hard and performed their responsibility. There is no outsourcing of the project and it must be completed by your group members. On the first project you may
to:
You will be graded not only on the ability of the program to give the correct output, but also on good programming practices such as ease of use, code readability and simplicity, modular programming, and adequate, useful comments. Just remember that comments, indentation, and modular programming can really help others when reviewing your code. You will work in teams of 2-3 people. On the first project you should not consult with any other students except the TA and the instructor. For the second project you will be able to select your own programming assignment.
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* [[Attach:leadership_assessment.pdf|Leadership Assessment]]
The leadership evaluation is only required for the first project.
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----
!!!! Leadership Assessments
You are also required to individually generate a leadership evaluation that will be turned in with your projects. This leadership assessment is composed of individual goals and an assessment on improvement. Instructions and examples are provided below.
* [[Attach:leadership_assessment.pdf|Leadership Assessment]]
The leadership evaluation is for both projects. Below is an overview of the timeline:
For Project 1
# Solicit feedback from your team members
# Summarize the feedback and write a statement of what you'd like to do differently on the next project
For Project 2
# Implement changes for the second project
# Redo the leadership assessment for project 2 (solicit feedback from team members and write a summary and improvement plan).
For the first project, turn in the leadership assessment with the project (zipped archive) to Learning Suite. For the second project, submit the leadership assessment to Learning Suite (see Leadership Assessment Assignment).
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* [[Attach:heat_exchanger_report_solution.zip|Report at 7 Test Conditions (Excel)]]
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* [[Attach:hw10_class_exercise.pdf|Preliminary Assignment (HW 10, Problem 1)]]
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* [[Attach:hw10_class_exercise.pdf|Preliminary Assignment (HW 10)]]
to:
* [[Attach:hw10_class_exercise.pdf|Preliminary Assignment (HW 10, Problem 1)]]
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(:html:)
<iframe width="560" height="315" src="https://www.youtube.com/embed/ouyg_TQGI2Q" frameborder="0" allowfullscreen></iframe>
(:htmlend:)
!!!! Source Code
import sys
import time
import numpy as np
import matplotlib.pyplot as plt
units = raw_input("Inputs units (F, R, C, K): ")
units = units.upper()
u = units # to shorten the name
if not(u=="F" or u=="R" or u=="C" or u=="K"):
print("Invalid units: " + u)
print("Terminating program...")
sys.exit()
print("Enter temperatures, blank when done")
stime = np.array([])
stemp = np.array([])
while True:
# ask for new temperature
temp=raw_input("Input temperature in "+u+": ")
# validate temperature input
try:
temp = float(temp)
except:
break
# convert the units to K
if units == "C":
temp = temp + 273.15
elif units == "F":
temp = (temp-32.0) * 5.0/9.0 + 273.15
elif units == "R":
temp = (temp-32.0) * 5.0/9.0
newTime = time.clock()
# store the values
stime = np.append(stime,newTime)
stemp = np.append(stemp,temp)
plt.plot(stime,stemp,'ro')
plt.xlabel("Time (sec)")
plt.ylabel("Temperature (K)")
plt.show()
print("Max: " + str(np.max(stemp)))
print("Min: " + str(np.min(stemp)))
print("Avg: " + str(np.mean(stemp)))
to:
* [[Attach:hw10_class_exercise.pdf|Preliminary Assignment (HW 10)]]
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to:
<iframe width="560" height="315" src="https://www.youtube.com/embed/ouyg_TQGI2Q" frameborder="0" allowfullscreen></iframe>
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print(
to:
u = units # to shorten the name
if not(u=="F" or u=="R" or u=="C" or u=="K"):
print("Invalid units: " + u)
if not(u=="F" or u=="R" or u=="C" or u=="K"):
print("Invalid units: " + u)
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temp = raw_input("Input temperature in " + units + ": ")
to:
temp=raw_input("Input temperature in "+u+": ")
Deleted lines 84-88:
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You are also required to individually generate a leadership evaluation that will be turned in with your project. This leadership assessment is composed of individual goals and an assessment on improvement. Instructions and examples are provided below.
* [[Attach:leadership_assessment.pdf|Leadership Assessment]]
The leadership evaluation is only required for the first project.
* [[Attach:leadership_assessment.pdf|Leadership Assessment]]
The leadership evaluation is only required for the first project.
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* [[Attach:heat_exchanger_sample_solution.pdf|Project Sample Solution]]
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* [[Attach:heat_exchanger_sample_solution.pdf|Project Sample Solution]]
You are also required to individually generate a leadership evaluation that will be turned in with your project. This leadership assessment is composed of individual goals and an assessment on improvement. Instructions and examples are provided below.
* [[Attach:leadership_assessment.pdf|Leadership Assessment]]
The leadership evaluation is only required for the first project.
to:
(:html:)
(:htmlend:)
!!!! Source Code
import sys
import time
import numpy as np
import matplotlib.pyplot as plt
units = raw_input("Inputs units (F, R, C, K): ")
units = units.upper()
if not(units=="F" or units=="R" or units=="C" or units=="K"):
print("Invalid units: " + units)
print("Terminating program...")
sys.exit()
print("Enter temperatures, blank when done")
stime = np.array([])
stemp = np.array([])
while True:
# ask for new temperature
temp = raw_input("Input temperature in " + units + ": ")
# validate temperature input
try:
temp = float(temp)
except:
break
# convert the units to K
if units == "C":
temp = temp + 273.15
elif units == "F":
temp = (temp-32.0) * 5.0/9.0 + 273.15
elif units == "R":
temp = (temp-32.0) * 5.0/9.0
newTime = time.clock()
# store the values
stime = np.append(stime,newTime)
stemp = np.append(stemp,temp)
plt.plot(stime,stemp,'ro')
plt.xlabel("Time (sec)")
plt.ylabel("Temperature (K)")
plt.show()
print("Max: " + str(np.max(stemp)))
print("Min: " + str(np.min(stemp)))
print("Avg: " + str(np.mean(stemp)))
(:htmlend:)
!!!! Source Code
import sys
import time
import numpy as np
import matplotlib.pyplot as plt
units = raw_input("Inputs units (F, R, C, K): ")
units = units.upper()
if not(units=="F" or units=="R" or units=="C" or units=="K"):
print("Invalid units: " + units)
print("Terminating program...")
sys.exit()
print("Enter temperatures, blank when done")
stime = np.array([])
stemp = np.array([])
while True:
# ask for new temperature
temp = raw_input("Input temperature in " + units + ": ")
# validate temperature input
try:
temp = float(temp)
except:
break
# convert the units to K
if units == "C":
temp = temp + 273.15
elif units == "F":
temp = (temp-32.0) * 5.0/9.0 + 273.15
elif units == "R":
temp = (temp-32.0) * 5.0/9.0
newTime = time.clock()
# store the values
stime = np.append(stime,newTime)
stemp = np.append(stemp,temp)
plt.plot(stime,stemp,'ro')
plt.xlabel("Time (sec)")
plt.ylabel("Temperature (K)")
plt.show()
print("Max: " + str(np.max(stemp)))
print("Min: " + str(np.min(stemp)))
print("Avg: " + str(np.mean(stemp)))
Changed lines 19-21 from:
*
to:
!!!! Project Help Resources
* [[Attach:project_preliminary_assignment.pdf|Preliminary Assignment]]
* [[Attach:heat_exchanger_sample_solution.pdf|Project Sample Solution]]
Added lines 20-21:
** [[Attach:project_preliminary_assignment.pdf|Preliminary Assignment]]
