Default Nodes¶
code¶
CodeNode¶
Custom python coding node.
Input Terminals¶
- arguments (list of strings):
- comma separated list of terminal names which dynamically create input terminals
Output Terminals¶
- functionOut (python function):
- returns the function which consists of the custom code
- returnOut (any):
- the value of returnOut
general¶
BooleanComparatorNode¶
Compares two inputs
Input Terminals¶
- a (object):
- a single input object of any type
- b (object):
- a single input object of any type
Output Terminals¶
- out (bool):
- a single output boolean that is the result of the operation selected in the operation terminal
User Terminals¶
- operation:
- a user selection that determines the comparison to be made
BrowseDirectoryNode¶
Browse to a directory and return the path as a string to that directory.
Output Terminals¶
- directory (str):
- Path to the directory. If the directory at the path does not exist, returns the string ‘Does Not Exist’.
BrowseFileNode¶
Browse to a File and return the path as a string to that file.
Output Terminals¶
- file (str):
- Path to the file. If the file at the path does not exist, returns the string ‘Does Not Exist’.
PathJoin¶
This node will join two path elements
Input Terminals¶
- path1 (str):
- The first part of the path to join
- path2 (str):
- the secont part of the path to join
Output Terminals¶
- output (str):
- the joined path
PeriodTriggerNode¶
Checks if a monotonically increasing float pass a defined period and returns a True trigger whenever the float passes the trigger period. Useful for limiting a task only to equally spaced values.
Input Terminals¶
- Value (float):
- a single input float that is expected to increase monotonically
- Period (float):
- the period between desired event triggers
Output Terminals¶
- Trigger (bool):
- a single output boolean which can be used to trigger other events
- Delta (float):
- The true period between the last trigger and the current.
PickleObjectsNode¶
Uses pickle to save and load objects to file
Input Terminals¶
- In (serializable object):
- an input object that is able to be serialized and saved
- filepath (str):
- a string which is the filepath for the file to be saved or loaded
Output Terminals¶
- Out (python object):
- an object that was deserialized from file
User Terminals¶
- Pickler (str):
- a string that defines the type of pickler to use on the object
- mode (str):
- a string that switches between saving and loading of the object
PrintNode¶
Print an object to stout (i.e. print(object))
Input Terminals¶
- object (object):
- An object to print.
PrintTypeNode¶
Print the type of an object to stout (i.e. print(type(object))).
Input Terminals¶
- object (object):
- An object to print the type of.
SliceNode¶
This node will slice an iterable
Input Terminals¶
- iterable (object):
- An iterable object that you wish to slice
- slice (str):
- a string descrbing a slice of the iterable (i.e. [2:5, 4])
Output Terminals¶
- output (object):
- the resulting slice
StopNode¶
This node will stop the loop that it is placed inside.
Input Terminals¶
- stop (bool):
- Set the value to True to emit a stop signal to the loop. If you want the loop to continue, this value should be False (default)
StringJoin¶
This node will join two path elements
Input Terminals¶
- path1 (str):
- The first part of the path to join
- path2 (str):
- the secont part of the path to join
Output Terminals¶
- output (str):
- the joined path
TestOutput¶
Node dedicated to simplifying test harness testing. Attach to desired output and reference in the test method.
math¶
AddNode¶
Sum the inputs
Input Terminals¶
- input (numerical):
- multi input of numeric values to be summed
Output Terminals¶
- result (numerical):
- the value of those summed inputs
DivideNode¶
Divide the inputs
Input Terminals¶
- numerator (numerical):
- number to be divided
- denominator (numerical):
- number to divide by
Output Terminals¶
- result (numerical):
- the value of those divided inputs
FactorialNode¶
calculate the factorial of a number.
Input Terminals¶
- input (numerical):
- number to calculate the factorial of
Output Terminals¶
- result (numerical):
- the resulting factorial
MultiplyNode¶
Multiply the inputs
Input Terminals¶
- input (numerical):
- multi input of numeric values to be multiplied
Output Terminals¶
- result (numerical):
- the value of those multiplied inputs
PowerNode¶
Raise base to a power
Input Terminals¶
- base (numerical):
- number to be multiplied
- exponent (numerical):
- the power to be raised
Output Terminals¶
- result (numerical):
- the value of those multiplied inputs
matplotlib¶
BasePlotNode¶
base node for all the seaborn nodes, not meant to be used directly
numpy¶
ABSNode¶
Calculate the absolute value of the input array
Input Terminals¶
- array (iterable):
- an iterable to calculate the FFT of
Output Terminals¶
- abs(array) (np.array):
- the absolute value of the array
ArrayNode¶
Create an array
Input Terminals¶
- shape (str):
- a string of comma seporated integers defining the array extents
- type (str):
- a string selecting the data format of the array
- value (float):
- an initial value to fill the array with
Output Terminals¶
- array (np.ndarray):
- the resulting array
AsArrayNode¶
Create an array from an iterable
Input Terminals¶
- input (iterable):
- an iterable that can be converted to an array
Output Terminals¶
- array (np.ndarray):
- the resulting array
ConditionalIndexNode¶
Create an array of zeros witht he same shape as the inout array
Input Terminals¶
- array (np.array):
- an array to copy the shape of
Output Terminals¶
- zeros (np.array):
- an array with the same shape, but filled with zeros
DivideNode¶
Divide numpy arrays that have the same shape, connection order matters
Input Terminals¶
- array (np.ndarray):
- array to divide
Output Terminals¶
- result (np.ndarray):
- the resulting array
FFTNode¶
Calculate the FFT of the input array
Input Terminals¶
- array (iterable):
- an iterable to calculate the FFT of
- rate(float):
- sample rate to determine the freuency range (Hz)
Output Terminals¶
- frequency (np.array):
- the calculated frequency range (Hz)
- fft (np.array):
- the fft
HistogramNode¶
Compute the histogram of a set of data
Input Terminals¶
- array (np.ndarray):
- Input data. The histogram is computed over the flattened array.
- bins (int):
- the number of bins
Output Terminals¶
- hist (np.ndarray):
- the values of the histogram
- edges(np.ndarray):
- the bin edges (length(hist)+1)
- centers (np.ndarray):
- the bin centers
IndexNode¶
Indexes into an array. Click the plus or minus button to add dimension arguments
Input Terminals¶
- array (np.ndarray):
- the input array to be indexed
- assign (np.ndarray):
- an array, float, or int to assign to the indexed region. Note: an array needs to have the same dimensions as the index.
Output Terminals¶
- array (np.ndarray):
- the indexed array
- array (np.ndarray):
- the input array with the assignment if provided
LoadTXT¶
Loads an array from a text file
Input Terminals¶
- file (str):
- path to the file of interest
- skiprows (str):
- skip the first skiprows lines; default: 0.
Output Terminals¶
- array (numpy.array):
- the array read from the file
MeanNode¶
Calculate the mean of the input array
Input Terminals¶
- array (iterable):
- an iterable to calculate the mean of
Output Terminals¶
- mean (float):
- the calculated mean
MultiplyNode¶
Multiply numpy arrays that have the same shape
Input Terminals¶
- array (np.ndarray):
- array to multiply
Output Terminals¶
- result (np.ndarray):
- the resulting array
RandomNode¶
Generate an array of random values
Input Terminals¶
- shape (str):
- a string of comma seporated integer values (i.e. 3,6,3,4) defining the shape of the array
Output Terminals¶
- array (np.ndarray):
- the randomly generated array
RangeNode¶
Generate an array of floats given a starting value, ending value, and a step.
Input Terminals¶
- start (float):
- the starting value
- stop (float):
- the ending value
- step (float):
- the step between values
- type (str):
- the dtype of the resulting array
Output Terminals¶
- range (np.ndarray):
- the resulting range
SubtractNode¶
Subtract numpy arrays that have the same shape, connection order matters.
Input Terminals¶
- array (np.ndarray):
- array to subtract
Output Terminals¶
- result (np.ndarray):
- the resulting array
SumNode¶
Add numpy arrays that have the same shape
Input Terminals¶
- array (np.ndarray):
- array to add
Output Terminals¶
- result (np.ndarray):
- the resulting array
TransposeNode¶
Transpose the input array
Input Terminals¶
- input (np.ndarray):
- the input array
Output Terminals¶
- array (np.ndarray):
- the resulting array
TrigNode¶
Compute the selected trig function of the input one dimensional array
Input Terminals¶
- input (np.ndarray):
- the input one dimensional array
- operation (str):
- trig function
Output Terminals¶
- array (np.ndarray):
- the resulting array
optimization toolset¶
DOENode¶
Used to construct a Design of Experiments. The node is designed to work both inside and outside of the MFIX GUI and has special capabilities in both environments. See the Optimization examples for detailed explanations and use cases.
FunctionFit¶
Fit the provided function to the provided data
Input Terminals¶
- function (str):
- function to fit to the data
- data (np.ndarray):
- a 1D array to fit the function to
Output Terminals¶
- parameters (np.ndarray):
- the resulting parameters for the best fit
GeneralOptimizer¶
Optimization of scalar function of one or more variables
Input Terminals¶
- function (str):
- the function to be minimized
- initialGuess (list):
- initial guess
Output Terminals¶
- result (str):
- the solution
ResponseSurfaceModel¶
Fits a Response Surface Model (RSM) to a dataset created with the design of experiments node and a response generated from that dataset and provides tools to evaluate the RSM, optimize, conduct sensitivity studies, and do forward propigation of uncertainty. See the Optimization examples for detailed explanations and use cases.
SplineFit¶
Fit a univariate spline to the data
Input Terminals¶
- x (np.ndarray):
- a 1D array of x values, must be increasing
- y (np.ndarray):
- a 1D array that the spline is fit to or a 2D array where [:, 0] are the x values and [:, 1] are the y values.
- degree (int):
- degree of the spline, must be <= 5 (default: 3)
- smoothness (float):
- Positive smoothing factor used to choose the number of knots. Number of knots will be increased until the smoothing condition is satisfied. If 0, spline will interpolate through all data points (default: None)
Output Terminals¶
- spline (np.ndarray):
- the resulting spline function
- spline (np.ndarray):
- the spline evaluated at x
pandas¶
CsvNode¶
Read a csv file into a Pandas DataFrame
Input Terminals¶
- file (str):
- path to a file
- sep (str):
- seporation character (i.e. ,)
- dates (bool):
- attempt to convert strings to datetime objects
- column (str):
- the column to use as the index of the DataFrame
Output Terminals¶
- dataframe (pd.DataFrame):
- the resulting Pandas DataFrame
shell¶
types¶
ListNode¶
List Type
Input Terminals¶
- <dynamic>(any)
- the values to put in the list
Output Terminals¶
- list(list):
- the list of input values
RangeNode¶
Range Type
Input Terminals¶
- start(int):
- the start value of the range
- stop(int):
- the ending value of the range
- step(int):
- the number of steps between start and stop
Output Terminals¶
- range(list):
- the list of int values created