is set up to manipulate strings into an STL file that is quite different from how Grasshopper defines meshes, in that an STL seems to define each face by XYZ points, Grasshopper wants a single list of all vertex points and then has an allied lists of topological connectivity according to vertex number, so for now I just hacked it to spit out points minus so many duplicates it generates for STL:
Right now it has an internal 3D trigonometric function I added input sliders to control, that creates surfaces that look a lot like molecular orbitals.
So how do I make a mesh? I failed to make a single mesh face from each STL face since AddMesh seems to want a list, so I tried making a single list and matching it with a simple ((1,2,3),(4,5,6),(7,8,9)...) array of connectivity but it hasn't worked yet since the STL list of vertices has duplicates that won't work for Grasshopper and removing the duplicates scrambles the connectivity relation.
After some work on this and seeing the output, I figure I could just randomly populate the mathematical function with points instead, unless it really gives a better mesh result than other routines. I'm not sure what to do with it yet, even if I get the mesh figured out.
import rhinoscriptsyntaximport RhinoPOINTS_CONTAINER =[]POINTS = []class Vector: # struct XYZ def __init__(self,x,y,z): self.x=x self.y=y self.z=z def __str__(self): return str(self.x)+" "+str(self.y)+" "+str(self.z) class Gridcell: # struct GRIDCELL def __init__(self,p,n,val): self.p = p # p=[8] self.n = n # n=[8] self.val = val # val=[8] class Triangle: # struct TRIANGLE def __init__(self,p1,p2,p3): self.p = [p1, p2, p3] # vertices # HACK TO GRAB VERTICES FOR PYTHON OUTPUT POINTS_CONTAINER.append( (p1.x,p1.y,p1.z) ) POINTS_CONTAINER.append( (p2.x,p2.y,p2.z) ) POINTS_CONTAINER.append( (p3.x,p3.y,p3.z) )# return a 3d list of values def readdata(f=lambda x,y,z:x*x+y*y+z*z,size=5.0,steps=11): m=int(steps/2) ki = [] for i in range(steps): kj = [] for j in range(steps): kd=[] for k in range(steps): kd.append(f(size*(i-m)/m,size*(j-m)/m,size*(k-m)/m)) kj.append(kd) ki.append(kj) return ki from math import sin,cos,exp,atan2 def lobes(x,y,z): try: theta = atan2(x,y) # sin t = o except: theta = 0 try: phi = atan2(z,y) except: phi = 0 r = x*x+y*y+z*z ct=cos(PARAMETER_A * theta) cp=cos(PARAMETER_B * phi) return ct*ct*cp*cp*exp(-r/10) def main(): data = readdata(lobes,10,40) isolevel = 0.1 #print(data) triangles=[] for i in range(len(data)-1): for j in range(len(data[i])-1): for k in range(len(data[i][j])-1): p=[None]*8 val=[None]*8 #print(i,j,k) p[0]=Vector(i,j,k) val[0] = data[i][j][k] p[1]=Vector(i+1,j,k) val[1] = data[i+1][j][k] p[2]=Vector(i+1,j+1,k) val[2] = data[i+1][j+1][k] p[3]=Vector(i,j+1,k) val[3] = data[i][j+1][k] p[4]=Vector(i,j,k+1) val[4] = data[i][j][k+1] p[5]=Vector(i+1,j,k+1) val[5] = data[i+1][j][k+1] p[6]=Vector(i+1,j+1,k+1) val[6] = data[i+1][j+1][k+1] p[7]=Vector(i,j+1,k+1) val[7] = data[i][j+1][k+1] grid=Gridcell(p,[],val) triangles.extend(PolygoniseTri(grid,isolevel,0,2,3,7)) triangles.extend(PolygoniseTri(grid,isolevel,0,2,6,7)) triangles.extend(PolygoniseTri(grid,isolevel,0,4,6,7)) triangles.extend(PolygoniseTri(grid,isolevel,0,6,1,2)) triangles.extend(PolygoniseTri(grid,isolevel,0,6,1,4)) triangles.extend(PolygoniseTri(grid,isolevel,5,6,1,4)) def t000F(g, iso, v0, v1, v2, v3): return [] def t0E01(g, iso, v0, v1, v2, v3): return [Triangle( VertexInterp(iso,g.p[v0],g.p[v1],g.val[v0],g.val[v1]), VertexInterp(iso,g.p[v0],g.p[v2],g.val[v0],g.val[v2]), VertexInterp(iso,g.p[v0],g.p[v3],g.val[v0],g.val[v3])) ] def t0D02(g, iso, v0, v1, v2, v3): return [Triangle( VertexInterp(iso,g.p[v1],g.p[v0],g.val[v1],g.val[v0]), VertexInterp(iso,g.p[v1],g.p[v3],g.val[v1],g.val[v3]), VertexInterp(iso,g.p[v1],g.p[v2],g.val[v1],g.val[v2])) ] def t0C03(g, iso, v0, v1, v2, v3): tri=Triangle( VertexInterp(iso,g.p[v0],g.p[v3],g.val[v0],g.val[v3]), VertexInterp(iso,g.p[v0],g.p[v2],g.val[v0],g.val[v2]), VertexInterp(iso,g.p[v1],g.p[v3],g.val[v1],g.val[v3])) return [tri,Triangle( tri.p[2], VertexInterp(iso,g.p[v1],g.p[v2],g.val[v1],g.val[v2]), tri.p[1]) ] def t0B04(g, iso, v0, v1, v2, v3): return [Triangle( VertexInterp(iso,g.p[v2],g.p[v0],g.val[v2],g.val[v0]), VertexInterp(iso,g.p[v2],g.p[v1],g.val[v2],g.val[v1]), VertexInterp(iso,g.p[v2],g.p[v3],g.val[v2],g.val[v3])) ] def t0A05(g, iso, v0, v1, v2, v3): tri = Triangle( VertexInterp(iso,g.p[v0],g.p[v1],g.val[v0],g.val[v1]), VertexInterp(iso,g.p[v2],g.p[v3],g.val[v2],g.val[v3]), VertexInterp(iso,g.p[v0],g.p[v3],g.val[v0],g.val[v3])) return [tri,Triangle( tri.p[0], VertexInterp(iso,g.p[v1],g.p[v2],g.val[v1],g.val[v2]), tri.p[1]) ] def t0906(g, iso, v0, v1, v2, v3): tri=Triangle( VertexInterp(iso,g.p[v0],g.p[v1],g.val[v0],g.val[v1]), VertexInterp(iso,g.p[v1],g.p[v3],g.val[v1],g.val[v3]), VertexInterp(iso,g.p[v2],g.p[v3],g.val[v2],g.val[v3])) return [tri, Triangle( tri.p[0], VertexInterp(iso,g.p[v0],g.p[v2],g.val[v0],g.val[v2]), tri.p[2]) ] def t0708(g, iso, v0, v1, v2, v3): return [Triangle( VertexInterp(iso,g.p[v3],g.p[v0],g.val[v3],g.val[v0]), VertexInterp(iso,g.p[v3],g.p[v2],g.val[v3],g.val[v2]), VertexInterp(iso,g.p[v3],g.p[v1],g.val[v3],g.val[v1])) ] trianglefs = {7:t0708,8:t0708,9:t0906,6:t0906,10:t0A05,5:t0A05,11:t0B04,4:t0B04,12:t0C03,3:t0C03,13:t0D02,2:t0D02,14:t0E01,1:t0E01,0:t000F,15:t000F} def PolygoniseTri(g, iso, v0, v1, v2, v3): triangles = [] # Determine which of the 16 cases we have given which vertices # are above or below the isosurface triindex = 0; if g.val[v0] < iso: triindex |= 1 if g.val[v1] < iso: triindex |= 2 if g.val[v2] < iso: triindex |= 4 if g.val[v3] < iso: triindex |= 8 return trianglefs[triindex](g, iso, v0, v1, v2, v3) def VertexInterp(isolevel,p1,p2,valp1,valp2): if abs(isolevel-valp1) < 0.00001 : return(p1); if abs(isolevel-valp2) < 0.00001 : return(p2); if abs(valp1-valp2) < 0.00001 : return(p1); mu = (isolevel - valp1) / (valp2 - valp1) return Vector(p1.x + mu * (p2.x - p1.x), p1.y + mu * (p2.y - p1.y), p1.z + mu * (p2.z - p1.z)) if __name__ == "__main__": main() # GRASSHOPPER PYTHON OUTPUTPOINTS = rhinoscriptsyntax.AddPoints(POINTS_CONTAINER)POINTS = rhinoscriptsyntax.CullDuplicatePoints(POINTS)…
rring to the above image)
Area
effective
effective
Second
Elastic
Elastic
Plastic
Radius
Second
Elastic
Plastic
Radius
of
Vy shear
Vz shear
Moment
Modulus
Modulus
Modulus
of
Moment
Modulus
Modulus
of
Section
Area
Area
of Area
upper
lower
Gyration
of Area
Gyration
(strong axis)
(strong axis)
(strong axis)
(strong axis)
(strong axis)
(weak axis)
(weak axis)
(weak axis)
(weak axis)
A
Ay
Az
Iy
Wy
Wy
Wply
i_y
Iz
Wz
Wplz
i_z
cm2
cm2
cm2
cm4
cm3
cm3
cm3
cm
cm4
cm3
cm3
cm
I have a very similar table which I could import to the Karamba table. But I have i_v or i_u values as well as radius of inertia for instance.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
dimensjon
Masse
Areal
akse
Ix
Wpx
ix
akse
Iy
Wpy
iy
akse
Iv
Wpv
iv
Width
Thickness
Radius R
[kg/m]
[mm2]
[mm4]
[mm3]
[mm]
[mm4]
[mm3]
[mm]
[mm4]
[mm3]
[mm]
[mm]
[mm]
[mm]
L 20x3
0.89
113
x-x
4,000
290
5.9
y-y
4,000
290
5.9
v-v
1,700
200
3.9
20
3
4
L 20x4
1.15
146
x-x
5,000
360
5.8
y-y
5,000
360
5.8
v-v
2,200
240
3.8
20
4
4
L 25x3
1.12
143
x-x
8,200
460
7.6
y-y
8,200
460
7.6
v-v
3,400
330
4.9
25
3
4
L 25x4
1.46
186
x-x
10,300
590
7.4
y-y
10,300
590
7.4
v-v
4,300
400
4.8
25
4
4
L 30x3
1.37
175
x-x
14,600
680
9.1
y-y
14,600
680
9.1
v-v
6,100
510
5.9
30
3
5
L 30x4
1.79
228
x-x
18,400
870
9.0
y-y
18,400
870
9.0
v-v
7,700
620
5.8
30
4
5
L 36x3
1.66
211
x-x
25,800
990
11.1
y-y
25,800
990
11.1
v-v
10,700
760
7.1
36
3
5
L 36x4
2.16
276
x-x
32,900
1,280
10.9
y-y
32,900
1,280
10.9
v-v
13,700
930
7.0
36
4
5
L 36x5
2.65
338
x-x
39,500
1,560
10.8
y-y
39,500
1,560
10.8
v-v
16,500
1,090
7.0
36
5
5
I have diagonals (bracings) which can buckle in these "non-regular" directions too, and they do. If I could add those values then in the Karamba model I could assign specific buckling scenarios..... I can see another challenge which will be at the ModifyElement component, I will not be able to choose these buckling lengths, in these directions.
Do you think this functionality can be added within short, or should I try to find another way to model these members?
Br, Balazs
…
nd B) daylight autonomy for a single room. A and B are therefore the conflicting objectives, and are connected to the O of octopus component. The geometry iterated is that of a window, on one of the rooms' facades.
I have a grasshopper definition that iterates the window by changing:
1. Window height
2. Window sill height
3. Window width
4. Window position from one side of the wall
1,2,3,4 are therefore the genes. A combination of these genes is a complete window, which is the chromoshome, that i will from now on call solution. All genes are connected to the G of octopus component.
Now regarding the octopus settings, i have these questions so that i can properly calibrate the settings (mutarion rate, crossover rate etc):
1.In the beginning of the octopus simulation, how many are the random solutions generated? (By random i mean totally random, not resulting solutions from mutation or crossover of previous solutions, i am talking about the very first generation). Is this number connected to the population size? Is it 6? How is it defined by octopus? Can somebody control it?
2.The first generation finishes when the number of "individuals to be evaluated" is reached. Then octopus jumps to the second generation. To do so, it keeps a specific number of solutions of the first generation, the so called elite. What is the number of these elite? Is it elitism x population size?
3.The SPEA2 original paper describes step wise the algorithm loop. During the loop, a number of solutions is stored in the elite domain, and from that domain, a number of solutions is used for mating. There are therefore two numbers, one that defines the number of solutions to enter the elite domain, and one that defines the number of solutions to be inserted in the mating pool. In octopus i only see elitism as a setting, which i am guessing is what defines the number of solutions to enter the elite domain. Is that true? How do i define the number of solutions to be copied in the mating pool, where mutation and crossover will occur? This number should be called tournament size, but i can't seem to find it..
4.Why is it that DURING one generation, the number of "individuals to be evaluated" can decrease? Is it because octopus finds out that there are no more possible solutions? (i am using discrete values for the genes)
5.The gene of window width, represented by a grasshopper slider, has 4 possible values: 0,1,2,3. Assuming that the mutation rate is 0.5. Does this mean that mutation of the gene can happen to an extent of 0.5 x 4 = 2? Meaning that the slider position can change for 0 to 2 or from 3 to 1 etc?
6.The mutation probability is dictating whether or not a gene will be mutated, or whether or not the whole solution will be mutated? So for instance, with a mutation probability of 0.5, does it mean that 2 out of the 4 genes are going to be mutated, or 2 out of 4 solutions is going to be mutated. If its the second case, then how is mutation divided between the different genes? Meaning, which of the 4 genes is going to get mutated? Is it random? Is it for all 4 genes?
7.Crossover can occur between 2 subsequent solutions. Crossover rate dictates whether or not crossover will take place? If so, then, assuming that it was chosen for crossover to take place between 2 solutions, which of the genes are going to be exchanged. I mean how many, out of the 4 genes (height, sill height, width, position). Is it random?
8.After clarifying the previous 7 questions, i can run a simulation. Then, is there an indicative number that i can be monitoring, to see that no more generations are required? I know that a good pareto has to be short, with a lot of solutions and with a uniform distribution. But is there a specific number output somewhere, that can inform me that a good pareto has more or less been generated? If there is such indicator...
Thank you all,
i hope this can help others as well,
Iason
…
ng is deciding how and where to store your data. If you're writing textual code using any one of a huge number of programming languages there are a lot of different options, each with its own benefits and drawbacks. Sometimes you just need to store a single data point. At other times you may need a list of exactly one hundred data points. At other times still circumstances may demand a list of a variable number of data points.
In programming jargon, lists and arrays are typically used to store an ordered collection of data points, where each item is directly accessible. Bags and hash sets are examples of unordered data storage. These storage mechanisms do not have a concept of which data comes first and which next, but they are much better at searching the data set for specific values. Stacks and queues are ordered data structures where only the youngest or oldest data points are accessible respectively. These are popular structures for code designed to create and execute schedules. Linked lists are chains of consecutive data points, where each point knows only about its direct neighbours. As a result, it's a lot of work to find the one-millionth point in a linked list, but it's incredibly efficient to insert or remove points from the middle of the chain. Dictionaries store data in the form of key-value pairs, allowing one to index complicated data points using simple lookup codes.
The above is a just a small sampling of popular data storage mechanisms, there are many, many others. From multidimensional arrays to SQL databases. From readonly collections to concurrent k-dTrees. It takes a fair amount of knowledge and practice to be able to navigate this bewildering sea of options and pick the best suited storage mechanism for any particular problem. We did not wish to confront our users with this plethora of programmatic principles, and instead decided to offer only a single data storage mechanism.*
Data storage in Grasshopper
In order to see what mechanism would be optimal for Grasshopper, it is necessary to first list the different possible ways in which components may wish to access and store data, and also how families of data points flow through a Grasshopper network, often acquiring more complexity over time.
A lot of components operate on individual values and also output individual values as results. This is the simplest category, let's call it 1:1 (pronounced as "one to one", indicating a mapping from single inputs to single outputs). Two examples of 1:1 components are Subtraction and Construct Point. Subtraction takes two arguments on the left (A and B), and outputs the difference (A-B) to the right. Even when the component is called upon to calculate the difference between two collections of 12 million values each, at any one time it only cares about three values; A, B and the difference between the two. Similarly, Construct Point takes three separate numbers as input arguments and combines them to form a single xyz point.
Another common category of components create lists of data from single input values. We'll refer to these components as 1:N. Range and Divide Curve are oft used examples in this category. Range takes a single numeric domain and a single integer, but it outputs a list of numbers that divide the domain into the specified number of steps. Similarly, Divide Curve requires a single curve and a division count, but it outputs several lists of data, where the length of each list is a function of the division count.
The opposite behaviour also occurs. Common N:1 components are Polyline and Loft, both of which consume a list of points and curves respectively, yet output only a single curve or surface.
Lastly (in the list category), N:N components are also available. A fair number of components operate on lists of data and also output lists of data. Sort and Reverse List are examples of N:N components you will almost certainly encounter when using Grasshopper. It is true that N:N components mostly fall into the data management category, in the sense that they are mostly employed to change the way data is stored, rather than to create entirely new data, but they are common and important nonetheless.
A rare few components are even more complex than 1:N, N:1, or N:N, in that they are not content to operate on or output single lists of data points. The Divide Surface and Square Grid components want to output not just lists of points, but several lists of points, each of which represents a single row or column in a grid. We can refer to these components as 1:N' or N':1 or N:N' or ... depending on how the inputs and outputs are defined.
The above listing of data mapping categories encapsulate all components that ship with Grasshopper, though they do not necessarily minister to all imaginable mappings. However in the spirit of getting on with the software it was decided that a data structure that could handle individual values, lists of values, and lists of lists of values would solve at least 99% of the then existing problems and was thus considered to be a 'good thing'.
Data storage as the outcome of a process
If the problems of 1:N' mappings only occurred in those few components to do with grids, it would probably not warrant support for lists-of-lists in the core data structure. However, 1:N' or N:N' mappings can be the result of the concatenation of two or more 1:N components. Consider the following case: A collection of three polysurfaces (a box, a capped cylinder, and a triangular prism) is imported from Rhino into Grasshopper. The shapes are all exploded into their separate faces, resulting in 6 faces for the box, 3 for the cylinder, and 5 for the prism. Across each face, a collection of isocurves is drawn, resembling a hatching. Ultimately, each isocurve is divided into equally spaced points.
This is not an unreasonably elaborate case, but it already shows how shockingly quickly layers of complexity are introduced into the data as it flows from the left to the right side of the network.
It's no good ending up with a single huge list containing all the points. The data structure we use must be detailed enough to allow us to select from it any logical subset. This means that the ultimate data structure must contain a record of all the mappings that were applied from start to finish. It must be possible to select all the points that are associated with the second polysurface, but not the first or third. It must also be possible to select all points that are associated with the first face of each polysurface, but not any subsequent faces. Or a selection which includes only the fourth point of each division and no others.
The only way such selection sets can be defined, is if the data structure contains a record of the "history" of each data point. I.e. for every point we must be able to figure out which original shape it came from (the cube, the cylinder or the prism), which of the exploded faces it is associated with, which isocurve on that face was involved and the index of the point within the curve division family.
A flexible mechanism for variable history records.
The storage constraints mentioned so far (to wit, the requirement of storing individual values, lists of values, and lists of lists of values), combined with the relational constraints (to wit, the ability to measure the relatedness of various lists within the entire collection) lead us to Data Trees. The data structure we chose is certainly not the only imaginable solution to this problem, and due to its terse notation can appear fairly obtuse to the untrained eye. However since data trees only employ non-negative integers to identify both lists and items within lists, the structure is very amenable to simple arithmetic operations, which makes the structure very pliable from an algorithmic point of view.
A data tree is an ordered collection of lists. Each list is associated with a path, which serves as the identifier of that list. This means that two lists in the same tree cannot have the same path. A path is a collection of one or more non-negative integers. Path notation employs curly brackets and semi-colons as separators. The simplest path contains only the number zero and is written as: {0}. More complicated paths containing more elements are written as: {2;4;6}. Just as a path identifies a list within the tree, an index identifies a data point within a list. An index is always a single, non-negative integer. Indices are written inside square brackets and appended to path notation, in order to fully identify a single piece of data within an entire data tree: {2,4,6}[10].
Since both path elements and indices are zero-based (we start counting at zero, not one), there is a slight disconnect between the ordinality and the cardinality of numbers within data trees. The first element equals index 0, the second element can be found at index 1, the third element maps to index 2, and so on and so forth. This means that the "Eleventh point of the seventh isocurve of the fifth face of the third polysurface" will be written as {2;4;6}[10]. The first path element corresponds with the oldest mapping that occurred within the file, and each subsequent element represents a more recent operation. In this sense the path elements can be likened to taxonomic identifiers. The species {Animalia;Mammalia;Hominidea;Homo} and {Animalia;Mammalia;Hominidea;Pan} are more closely related to each other than to {Animalia;Mammalia; Cervidea;Rangifer}** because they share more codes at the start of their classification. Similarly, the paths {2;4;4} and {2;4;6} are more closely related to each other than they are to {2;3;5}.
The messy reality of data trees.
Although you may agree with me that in theory the data tree approach is solid, you may still get frustrated at the rate at which data trees grow more complex. Often Grasshopper will choose to add additional elements to the paths in a tree where none in fact is needed, resulting in paths that all share a lot of zeroes in certain places. For example a data tree might contain the paths:
{0;0;0;0;0}
{0;0;0;0;1}
{0;0;0;0;2}
{0;0;0;0;3}
{0;0;1;0;0}
{0;0;1;0;1}
{0;0;1;0;2}
{0;0;1;0;3}
instead of the far more economical:
{0;0}
{0;1}
{0;2}
{0;3}
{1;0}
{1;1}
{1;2}
{1;3}
The reason all these zeroes are added is because we value consistency over economics. It doesn't matter whether a component actually outputs more than one list, if the component belongs to the 1:N, 1:N', or N:N' groups, it will always add an extra integer to all the paths, because some day in the future, when the inputs change, it may need that extra integer to keep its lists untangled. We feel it's bad behaviour for the topology of a data tree to be subject to the topical values in that tree. Any component which relies on a specific topology will no longer work when that topology changes, and that should happen as seldom as possible.
Conclusion
Although data trees can be difficult to work with and probably cause more confusion than any other part of Grasshopper, they seem to work well in the majority of cases and we haven't been able to come up with a better solution. That's not to say we never will, but data trees are here to stay for the foreseeable future.
* This is not something we hit on immediately. The very first versions of Grasshopper only allowed for the storage of a single data point per parameter, making operations like [Loft] or [Divide Curve] impossible. Later versions allowed for a single list per parameter, which was still insufficient for all but the most simple algorithms.
** I'm skipping a lot of taxonometric classifications here to keep it simple.…
Added by David Rutten at 2:22pm on January 20, 2015
, Engineer and Researcher from France with broad programming experience. He is the author of the City in 3D Rhinoceros plugin for creation of buildings according to geojson file and with real elevation. Guillaume already created a new component: "Address to Location". It enables getting latitude and longitude values for the given address:
2) Support of Bathymetry data: automatic creation of underwater (sea/river/lake floor) terrain. This feature is now available through new source_ input of the "Terrain generator" component. Here is an example of terrain of the Loihi underwater volcano, of the coast of Hawaii:
3) A new terrain source has been added: ALOS World 3D 30m. ALOS is a Japanese global terrain data. Gismo "Terrain Generator" component has been using SRTM 30m terrain data, which hasn't been global and was limited to -56 to +60 latitude range. With this addition, it is possible to switch between SRTM and ALOS World 3D 30m models with the use of source_ input.
4) 9 new components have been added:
"Address To Location" - finds latitude and longitude coordinates for the given address.
"XY To Location" - finds latitude and longitude coordinates for the given Rhino XY coordinates. "Location To XY" - vice versa from the previous component: finds Rhino XY coordinates for the given latitude longitude coordinates. "Z To Elevation" - finds elevation for particular Rhino point. "Rhino text to number" - convert numeric text from Rhino to grasshopper number. "Rhino unit to meters" - convert Rhino units to meters. "Deconstruct location" - deconstructs .epw location. "New Component Example" - this component explains how to make a new Gismo component, in case you are interested to make one. We welcome new developers, even if you contribute a single component to Gismo! "Support Gismo" - gives some suggestions on how to make Gismo better, how to improve it and support it.
5) Ladybug "Terrain Generator" component now supports all units, not only Meters. So any Gismo example file which uses this component, can now use Rhino units other than Meters as well. Thank you Antonello Di Nunzio for making this happen!!
Basically just forget about this yellow panel:
This panel is not valid anymore, so just use any unit you want.
6) A number of bugs have been fixed, reported in topics for the last couple of weeks. We would like to thank members in the community who invested their time in testing, finding these bugs and reporting them: Rafat Ahmed, Peter Zatko, Mathieu Venot, Abraham Yezioro, Rafael Alonso. Thank you guys!!! Apologies if we forgot to mention someone.
The version 0.0.2 can be downloaded from here:
https://github.com/stgeorges/gismo/zipball/master
And example files from here:
https://github.com/stgeorges/gismo/tree/master/examples
Any new suggestions, testing and bug reports are welcome!!…
Added by djordje to Gismo at 5:13pm on March 1, 2017
) Course Fee: Professional EUR 825,- (+VAT), Student EUR 415,- (+VAT)
Led by plug-in developer and structural engineer Clemens Preisinger, along with Zeynep Aksoz and Matthew Tam from the expert Karamba3D team, this three-day workshop will focus on methods of setting up structural systems in the parametric environment of Grasshopper. The participants will be guided through the basics of analyzing and interpreting structural models, to optimization processes, and how to integrate Karamba3D into C# scripts.
This workshop is aimed towards beginner to intermediate users of Karamba3D. However, advanced users are also encouraged to apply. It is open to both professional and academic users. For beginner users of Rhino and Grasshopper, there will be an optional introductory course one day before the Karamba3D course.
Karamba3D 1is a parametric structural engineering tool which provides accurate analysis of spatial trusses, frames, and shells. Karamba3D is fully embedded in the parametric design environment of Grasshopper, a plug-in for the 3D modeling tool Rhinoceros. This makes it easy to combine parameterized geometric models, finite element calculations, and optimization algorithms like Galapagos.
Course Outline
Introduction and presentation of project examples
Optimization of cross sections of line-based and surface-based elements
Geometric optimization
Topological optimization
Structural performance informed form finding
Understanding analysis algorithms embedded in Karamba3D and visualizing results
Complex workflow processes in Rhino, Grasshopper, and Karamba3D
Places are limited to a maximum of 10 participants with limited educational places. A minimum of 4 participants is required for the workshop to take place. The workshop will be canceled if this quota is not filled by October 28. The workshop will be taught in English.
Course Requirements
Basic Rhino and Grasshopper knowledge is recommended. An introductory course is offered.
No knowledge of Karamba3D is needed. Participants should bring their own laptops with Grasshopper and either Rhino 5 or Rhino 6 installed. You can download a 90-day trial version of Rhino. Karamba3D ½ year licenses for non-commercial use will be provided to all participants.
Please register here……
Added by Matthew Tam at 6:38am on September 13, 2019
u can still find some wonky behaviour in GH related to datatrees. My experience is that new users quite quickly get the hang of it once they learn that a tree is in fact not a tree but in the first place set of lists, where the path shows how the pieces of data used to be grouped.
Branch Count checking A component has multiple tree inputs, but has different amount of branches, each having branch count > 2. (While I understand the logic of combining multiple trees, I've not once encounted once that combining a component with e.g. an input of 2 branches and an input of 4 branches to give any kind of sensible output.
Desired behaviour: If a component has branches (each being > 2 path count), the component should throw a warning. ("Strict branches behaviour?). For example: take an offset component, with 6 branches of curves and 5 branches of offsets. It is extremely likely that this is the result of an error earlier in the definition. This works however without a problem - the last branch is repeated again, and it's later on quite hard to discover something went wrong.
Checking branch Count The most important numeric is the amount of branches, and the amount of items in the tree. It's desired that the hovers show the amount of data and the amount of branches.
Desired behaviour
Trees with paths of different rank Trees that contain {0;0} and {0} and {0;0;1} is usually a sign of trouble of not well merged trees, faulty C# components, or just nasty coding habits.
Trim as undo graft instead of flatten Having the trim in the context menu would provide an easy way to undo a graft. Right now the easiest way for many people is to flatten it, and then start all over again - while just getting rid of the last index keeps the underlying history and makes it easier to write reuseable pieces of code when you prepend datatrees to it.
Component to get branch by index, not by path Would be great. Suppose you have a grid of points, grouped by row. It would help to show: "look, this is in the first path, it's called {0;0;1}, it's got 10 points, these points are the first row".
Analogue to using list item to show what is the first point, second point, and so on.
Semantic path names (maybe far fetched) But what if we can add a short name of each method that was executed to the path list, so it can show:
{Slider 0; Series 0; Point 0}{Slider 0; Series 0; Point 1}
{Slider 0; Series 0; Point 2}
{Slider 0; Series 0; Point 3}
{Slider 0; Series 1; Point 0}
{Slider 0; Series 1; Point 1}
{Slider 0; Series 1; Point 2}
{Slider 0; Series 1; Point 3}
Make the input/data matching inside components explicit Can we make it even more obvious that a component is not a black box that's executed once, but in fact an iteration machine that tries to make sense of the inputs that's fed to this box?
Show data combination. How data input A relates to data input B and data input C, is currently very implict and is just plain hard to learn., and required the ability to be able to relate the output back to the input. If we can textually or even graphically show what data matching occured inside a component, it would greatly help the understanding (and debugging) of "what's going on here in this component"
A verbose explanation of the data matching in component A
Iteration one: - Geometry: We take the data item from Branch 0, Position 0: (Point 0,0,0) - Motion: We take the data item from Branch 0, Position 0: (Vector 0,0,0)
Iteration two:
- Geometry: We take the data item from Branch 0, Position 0: (Point 0,0,0)
- Motion: We take the data item from Branch 0, Position 1: (Vector 10,0,0)
Iteration three:
- Geometry: We take the data item from Branch 0, Position 0: (Point 0,0,0)
- Motion: We take the data item from Branch 0, Position 1: (Vector 20,0,0)
etc.
A verbose explanation of the data matching in component B
Iteration one: - Geometry: We take the data item from Branch 0, Position 0: (Point 0,0,0) - Motion: We take the data item from Branch 0, Position 0: (Vector 0,0,0)
..
Iteration seven:
- Geometry: We take the data item from Branch 0, Position 0: (Point 0,0,0)
- Motion: We take the data item from Branch 7, Position 0: (Vector 0,70,0)
..
Iteration 27:
- Geometry: We take the data item from Branch 0, Position 7: (Point 80,0,0)
- Motion: We take the data item from Branch 2, Position 0: (Vector 0,20,0)
…
nd improvements. Many of the new features and components announced in the last release have become stable and have emerged from their WIP section. Additionally, after two years of work, we are happy to announce that we finally have full support of an OpenStudio connection within Honeybee, which has ushered in a whole host of new features, notably the modelling of detailed HVAC systems. As always you can download the new release from Food4Rhino. Make sure to remove the older version of Ladybug and Honeybee and update your scripts.
LADYBUG
1 - Solar Hot Water Components Out of WIP
After much beta-testing, bug-fixing, and general development, all of the Photovoltaic and Solar Hot Water components are now fully out of WIP! The main component is based on a Chengchu Yan's publication. Components have been added to Ladybug thanks to the efforts of Chengchu Yan and Djordje Spasic.. See Djorje’s original release post of the solar hot water components for more information on the components that just made it out of WIP.
2 - New Terrain Shading Mask Released in WIP
In addition to Djordje’s prolific addition of renewable energy components, he has also contributed a widely-useful component to generate terrain shading masks, which account for the shading of surrounding mountains/terrain in simulations. While initially added to assist the solar radiation radiation and renewable energy components, the component will undergo development to optimize it for energy and daylight simulations over the next few months. Another new component called Horizon Angles can be used to visualize and export horizon angles. You can test them out now by accessing them in the WIP section. For more information, see Djordje’s release post on the GH forum here.
3 - New Mesh Selector Component
After realizing that the Optimal Shade Creator component has applications to a whole range of analyses, it has now been re-branded as the Mesh Selector and has been optimized to work easily with these many analyses. Specifically, the component selects out the portion of a mesh that meets a given threshold. This can be the portion of a shade benefit analysis meeting a certain level of shade desirability, the portion of a radiation study meeting a certain level of fulx, the portion of a daylight analysis meeting a certain lux threshold, and much more!
4 - Solar Adjusted Temperature Now Includes Long Wave Radiation
Thanks to a question asked by Aymeric and a number of clarifications made by Djordje Spasic, the Solar Adjusted Temperature component now includes the ability to account for long-wave radiative loss to the sky in addition to it original capability to account for short wave radiation from the sun. As such, the component now includes all capabilities of similar outdoor comfort tools such as RayMan. The addition of this capability is also paralleled by the addition of a new horizontalInfraredRadiation output on the ImportEPW component. See the updated solar adjusted example file hereto see how to use the component properly.
5 - Support for both Log and Power Law Wind Profiles
In preparation for the future release of the Butterfly CFD-modelling insect, the Ladybug Wind Profile component now includes the option of either power law or log law wind profiles, which are both used extensively in CFD studies. Thanks goes to Theodoros Galanos for providing the formulas!
6 - New Radiant Asymmetry Comfort Components
Prompted by a suggestion from Christian Kongsgaard, Ladybug now includes components to calculate radiant asymmetry discomfort! For examples of how to use the components see this example file for spatial analysis of radiant asymmetry discomfort and this example for temporal analysis.
7 - Pedestrian Wind Comfort Component Released in WIP
In preparation for the impending release of the butterfly CFD-modelling insect, Djordje Spasic with assistance from Liam Harrington has contributed a component to evaluate outdoor discomfort and pedestrian safety. The component identifies if certain areas around the building are suitable for sitting, building entrances-exits, window shopping... based on its wind microclimate. Dangerous areas due to high wind speeds are also identified.You can check it out now in the WIP section.
HONEYBEE
1 - New HVAC Systems and Full OpenStudio Support
After a significant amount of development on the part of the OpenStudio team and two years of effort on the part of LB+HB developers, we (finally!) have full support for an OpenStudio connection within Honeybee. By this, we mean that any energy simulation property that can be assigned to a HBZone will be taken into account in the simulation run by the OpenStudio component. The connection to OpenStudio has brought with it several new capabilities. Most notably, you can now assign full HVAC systems and receive energy results in units of electricity and fuel instead of simple heating and cooling loads. This Honeybee release includes 14 built-in HVAC template systems that can be assigned to the zones, each of which can be customized:
0. Ideal Air Loads 1. PTAC | Residential 2. PTHP | Residential 3. Packaged Single Zone - AC 4. Packaged Single Zone - HP 5. Packaged VAV w/ Reheat 6. Packaged VAV w/ PFP Boxes 7. VAV w/ Reheat 8. VAV w/ PFP Boxes 9. Warm Air Furnace - Gas Fired 10.Warm Air Furnace - Electric 11.Fan Coil Units + DOAS 12.Active Chilled Beams + DOAS 13.Radiant Floors + DOAS 14.VRF + DOAS
Systems 1-10 are ASHRAE Baseline systems that represent much of what has been added to building stock over the last few decades while systems 11-14 are systems that are commonly being installed today to reduce energy use. Here is an example file showing how to assign these systems in Honeybee and interpret the results and here is an example showing how to customize the HVAC system specifications to a wide variety of cases. To run the file, you will need to have OpenStudio installed and you can download and install OpenStudio from here.
In addition to these template systems within Honeybee, the OpenStudio interface includes hundreds of HVAC components to build your own custom HVAC systems. OpenStudio also has a growing number of user-contributed HVAC system templates that have been integrated into a set of scripts called "Measures" that you can apply to your OpenStudio model within the OpenStudio interface. You can find these system templates by searching for them in the building components library. Here is a good tutorial video on how to apply measures to your model within the OpenStudio interface. Honeybee includes a component that runs these measures from Grasshopper (without having to use the OpenStudio interface), which you can see a demo video of here. However, this component is currently in WIP as OpenStudio team is still tweaking the file structure of measures and it is fairly safe to estimate that, by the next stable release of Honeybee, we will have full support of OpenStudio measures within GH.
2 - Phasing Out IDF Exporter
With the connection to OpenStudio now fully established, this release marks the start of a transition away from exporting directly to EnergyPlus and the beginning of Honeybee development that capitalizes on OpenStudio’s development. As such THIS WILL BE THE LAST STABLE RELEASE THAT INCLUDES THE HONEYBEE_RUN ENERGY SIMULATION COMPONENT.
The Export to OpenStudio component currently does everything that the Run Energy Simulation component does and, as such, it is intended that all GH definitions using the Run Energy Simulation component should replace it with the OpenStudio component. You can use the same Read EP Result components to import the results from the OpenStudio component and you can also use the same Energy Sim Par/Generate EP Output components to customize the parameters of the simulation. The only effective difference between the two components is that the OpenStudio component enables the modeling of HVAC and exports the HBZones to an .osm file before converting it to an EnergyPlus .idf.
For the sake of complete clarity, we should state that OpenStudio is simply an interface for EnergyPlus and, as such, the same calculation engine is under the hood of both the Export to OpenStudio component and the Run Energy Simulation component. At present, you should get matching energy simulation results between the Run Energy Simulation component and a run of the same zones with the OpenStudio component (using an ideal air system HVAC).
All of this is to say that you should convert your GH definitions that use the Run Energy Simulation component to have the OpenStudio component and this release is the best time to do it (while the two components are supported equally). Additionally, with this version of Honeybee you will no longer need to install EnergyPlus before using Honeybee and you will only need to install OpenStudio (which includes EnergyPlus in the install).
3 - New Schedule Generation Components
Thanks to the efforts of Antonello Di Nunzio, we now have 2 new components that ease the creation of schedule-generation in Honeybee. The new components make use of the native Grasshopper “Gener Pool” component to give a set of sliders for each hour of the day. Additionally, Antonello has included an annual schedule component that contains a dictionary of all holidays of every nearly every nation (phew!). Finally, this annual schedule component can output schedules in the text format recognized by EnergyPlus, which allows them to be written directly into the IDF instead of a separate CSV file. This will significantly reduce the size of files needed to run simulations and can even reduce the number of components on your canvas that are needed to add custom schedules. For more information, see Antonello’s explanatory images here and Antonello's example file here. You can also see a full example file of how to apply the schedules to energy simulations here.
4 - EnergyPlus Lookup Folder, Re-run OSM/IDF, and Read Result Dictionary
With the new capabilities of OpenStudio, we have also added a number of components to assist with managing all of the files that you get from the simulation. In particular, Abraham Yezioro has added a Lookup EnergyPlus Folder component that functions very similarly to the Lookup Daylight Folder component. This way, you can run an Energy simulation once and explore the results separately. Furthermore, we have added components to Re-Run OpenStudio .osm files or EnergyPlus .idf files within Grasshopper. These components are particularly useful if you edit these .osm or .idf files outside of Honeybee and want to re-run them to analyze their results in Grasshopper. Lastly, a component has been added to parse the .rdd (or Result Data Dictionary) file that EnergyPlus produces, enabling you to see all of the possible outputs that you can request from a given simulation.
5 - Electric Lighting Components Out of WIP
After Sarith Subramaniam’s initial components to model electric lights with Radiance in the last release, we are happy to report that they have been fully tested and are out of WIP. Improvements include support for all types of light fixture geometries and the ability to use the components in a more “Grasshoppery” list-like fashion. See Sarith’s original release post for more information and several example files showing how to use the components can be found here. 1 , 2 , 3 .
6 - Improvements to THERM Components
A number of bug fixes and improvements have been made to the THERM components in order to make their application more flexible and smooth. Special thanks is due to Derin Yilmaz , Mel King , Farnaz , Ben (@benmo1) , and Abraham Yezioro for all of the great feedback in the process of improving these components.
7 - HBObject Transform Components
After some demand for components that can ease the generation of buildings with modular zone types, two components to transform HBObjects with all of their properties have been added to the 00 | Honeybee section. The components allow you to produce copies of zones that are translated or rotated from the original position.
8 - Comfort Maps Supports PET and Integration of CFD Results
Thanks to the addition of the ‘Physiological Equivalent Temperature’ (PET) component by Djordje Spasic in the last stable release, it is now possible to make comfort maps of PET with Honeybee. PET is particularly helpful for evaluating OUTDOOR comfort with detailed wind fields at a high spatial resolution. As such, the new PET recipe has also been optimized for integration with CFD results. The windSpeed_ input can now accept the file path to a .csv file that is organized with 8760 values in each column and a number of columns that correspond to the number of test points. Components to generate this csv from Butterfly CFD results will be coming in later releases. Stay tuned!
As always let us know your comments and suggestions.
Enjoy!Ladybug Analysis Tools Development Team
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