fastlib

Installation

Either download the repository to your computer and install, e.g. by pip

pip install .

or install directly from github.

pip install git+https://www.github.com/gunnstein/fastlib.git@master

Usage

Working with data from FAST binary files

The package contains functions to read and work with data from FAST binary output files. The ReadFASTBinary function returns the channel data, names and units exactly the same as the NREL distributed MATLAB function. Additionally, the package provides DataSet and DataArray classes to simplify working with FAST output data. See code below:

import fastlib
import matplotlib.pyplot as plt

# Assuming a FAST binary output file "Test18.outb" is located in the folder
filename = "Test18.outb"

# Read data, channel names and units from with the ReadFASTBinary function.
channels, chan_names, chan_units, filefmtid, desc_str = fastlib.ReadFASTBinary(filename)

# Alternatively, use the DataSet class to work with FAST simulation data.
dset = fastlib.DataSet()
dset.load(filename)

# Show all available DataArrays
print(dset.names)

#   ['Time', 'Wind1VelX', 'Wind1VelY', 'Wind1VelZ',
#    'OoPDefl1', 'IPDefl1', 'TwstDefl1', 'BldPitch1',
#    'Azimuth', ...]

# DataArrays can be accessed as properties of the DataSet
t = dset.Time
y = dset.Azimuth

# DataArrays are numpy arrays with extra properties. Use them
# as numpy arrays to plot... or access any of the standard
# numpy methods (mean, std, ...)

plt.plot(t, y)
print("Azimuth mean:", y.mean())
print("Azimuth std:", y.std())
print("Azimuth min:", y.min())
print("Azimuth max:", y.max())


# Each FAST simulation channel has a name and unit,
# Access them in the DataArray object as properties
# `name` and `unit`.
plt.xlabel(t.name + " " + t.unit)

#  y.label (= y.name + " " + y.unit) is another useful property
plt.ylabel(y.label)

# It is also possible to set a user defined label
y.label = "Azimuth with unit (deg)"
print("User defined label:", y.label)

# and resetting a user defined label
y.label = None
print("Reset label:", y.label)

plt.show(block=True)

The resulting image from the example above is given below, see example.py

Parametrizing FAST input files

The package contains template formatters to help parametrize FAST simulations. The TemplateStringFormatter class takes in a template string and substitute template keys (${}) with instance properties, see below.

 import fastlib

 template_str = """------- FAST v8.16.* INPUT FILE ------------------------------------------------
${description}
---------------------- SIMULATION CONTROL --------------------------------------
${Echo}         Echo            - Echo input data to <RootName>.ech (flag)
"FATAL"       AbortLevel      - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"}
${TMax}   TMax            - Total run time (s)
      0.005   DT              - Recommended module time step (s)
         2   InterpOrder     - Interpolation order for input/output time history (-) {1=linear, 2=quadratic}
         0   NumCrctn        - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections}
      99999   DT_UJac         - Time between calls to get Jacobians (s)
      1E+06   UJacSclFact     - Scaling factor used in Jacobians (-)
 """

 fmter = fastlib.TemplateStringFormatter(template_str)
 fmter.description = "This is a demonstration of the TemplateStringFormatter class"
 fmter.Echo = False
 fmter.TMax = 90

 print(fmter.substitute())

which yields the following output:

------- FAST v8.16.* INPUT FILE ------------------------------------------------
This is a demonstration of the TemplateStringFormatter class
---------------------- SIMULATION CONTROL --------------------------------------
False         Echo            - Echo input data to <RootName>.ech (flag)
"FATAL"       AbortLevel      - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"}
         90   TMax            - Total run time (s)
      0.005   DT              - Recommended module time step (s)
          2   InterpOrder     - Interpolation order for input/output time history (-) {1=linear, 2=quadratic}
          0   NumCrctn        - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections}
      99999   DT_UJac         - Time between calls to get Jacobians (s)
      1E+06   UJacSclFact     - Scaling factor used in Jacobians (-)

Note that the TemplateStringFormatter.write(fname) can write the substituted string directly to a file fname. There also exists a TemplateFileFormatter class that can read in a template string from a separate file rather than a template string defined within the code.

Multiprocessing

The multiprocessing module provides the MultiProcessHandler class to help submit a series of FAST input files to a specified number of cpus.

import fastlib

# Assume that we have four FAST input files in the working directory
fst_files = ["Test18.fst", "Test19.fst", "Test20.fst", "Test21.fst"]

# Create a handler with 4 cpus to process the input files with the "fast" executable.
mphdlr = fastlib.multiprocessing.MultiProcessHandler(fst_files, ncpu=4, binary_name="fast")

# Start the handler, all files in the list fst_files are now run in cmd line with the
# command: fast <fst_file> on the four cpus.
mphdlr.start()

Support

Please open an issue for support.

Contributing

Please contribute using Github Flow. Create a branch, add commits, and open a pull request.

Gunnstein / fastlib