Python program to calculate Discrete Fast Fourier Transform (DFFT)

I am looking for assistance on writing a small Python program to calculate Discrete Fast Fourier Transform (DFFT) from given data in a file in .dat format. Hand-crafting the Fourier transform algorithm is not required. Use any existing modules or libraries in Python. Estimated time required for this is 4 hours. Must be delivered by Sunday 17th March 2019 night. As submission deadline is 12:00 AM midnight time in Germany. PM for details.



You are tasked with developing a production-ready python application which will calculate the Discrete Fast Fourier Transform (DFFT) of a time-series as well as relevant statistics about the output data. The application will read a file of binary data, calculate the DFFT values, write the spectrum values to an output text file and log statistics concerning the output data. You also should provide unit tests. You will create a docker image for the application which could be handed over to the production system.



• The application should load default configuration information from a [login to view URL] file (you create). This file should specify:

- Input filename and path

- Output filename and path

- Number bytes per value used to store the binary input data (provided data is stored as 4 bytes)

- Sampling rate of the input data (provided data is sampled at 2kHz)

• It should be possible to override any configuration values using environment variables. Naming of these EnvVars is up to you.

• The application should provide logging with some set of standard logging levels (e.g. DEBUG, INFO, WARNING, ERROR, CRITICAL)

• The application will calculate the following statistics and log them at the INFO level:

o Output FFT data:

▪ Mean

▪ Median

▪ Standard Deviation

• Use any existing modules or libraries as you see fit. We do not expect you to hand-craft the DFFT algorithm, config parsing or logging.

• You should provide unit tests for each of your classes.

• The DOCKER image should self-sufficient and for us ready to run

• Most importantly, this application should be production-ready, meaning it should be well-structured, maintainable, documented and have good exception handling.



• Input data is enclosed in the zip file in a file called: [login to view URL]

• The input file provided contains an acceleration trace (in G) from a train passing over a sensor located on a rail switch;

• 2 kHz is the sampling rate;

• binary data files storing G values as 32 bit floats.



Estimated time required for the task: 4 hours

The submitted solution will contain the following:

• A short report outlining your proposed approach and indicate how much time you have taken for the task.

• All python code

• Your default configuration file

• A [login to view URL] file containing a brief usage description and any environment variables that can be set to alter the default configuration

• The docker container and associated files

Happy Coding

Kemahiran: Algoritma, Matematik, Python, Kejuruteraan Perisian, Statistik

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Tentang Majikan:
( 4 ulasan ) Munich, United Arab Emirates

ID Projek: #18956783

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Hi, Hope my message finds you well. I have more than fours years expereience working as Full Stack Python developer. I have hands on experience with pandas and numpy using which we can perform data [login to view URL] i am Lagi

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