Opened 22 months ago

Closed 21 months ago

Last modified 21 months ago

#6066 closed defect (fixed)

OpenModelica bitmap wrong way around

Reported by: lukas.koenemann@… Owned by: adeas31
Priority: high Milestone: 1.16.0
Component: OMEdit Version:
Keywords: bitmap Cc:

Description

Hello,
I changed my OpenModelica (OMEdit) to the newest version. Now I have the problem that all my bitmaps in my self-made library are the wrong way around. How can I fix that problem?
Kind Regards,
Lukas

Change History (13)

comment:1 Changed 22 months ago by casella

  • Milestone changed from Future to 1.17.0

Can you please attach a minimal working example to reproduce the issue?

Thanks!

comment:2 Changed 22 months ago by adeas31

This might be related to #5878. I am guessing your bitmaps were displayed wrong previously and are shown correct now. Can you try your library with some other Modelica tools like Dymola or System Modeler.

comment:3 Changed 22 months ago by casella

BTW, I'm not sure if the Specification is 100% good with this thing. Yesterday I flipped a step signal source, because I wanted the output connector on the left hand side, and the Cartesian plot that is shown in the icon was also flipped, as in a mirror. I don't think that makes much sense, we should have an annotation to say whether or not the image should be flipped.

comment:4 follow-up: Changed 22 months ago by adeas31

But that one is not a bitmap. Anyways what you are saying will change the whole 2D dynamics of Modelica tools. Basically you want to ignore the transformations to be applied on the nested/child shapes.

comment:5 Changed 22 months ago by ceraolo

I think Francesco's comment makes much sense.
The use of a special annotation (with a default value miming present behaviour) would avoid any unwanted side effects with the existing models.

comment:6 in reply to: ↑ 4 Changed 22 months ago by casella

Replying to adeas31:

But that one is not a bitmap. Anyways what you are saying will change the whole 2D dynamics of Modelica tools. Basically you want to ignore the transformations to be applied on the nested/child shapes.

Not really. For example, if you rotate a shape, I guess that should be applied literally. The question is, does it make sense to "flip" icons (bitmaps or vectorize) that have a definite left-to-right semantics, like Cartesian axes or actual text, or should we give the option to the libray developer to say, hey, don't mirror this, because it makes no sense?

Anyway, the discussion is completely out of the scope of this ticket. I guess comment:2 is right. You can download Dymola's demo version and try to open your model. You won't be able to simulate it, but you can check how the diagrams and icons look like.

comment:7 Changed 22 months ago by lukas.koenemann@…

So I tried to open the model in dymola and there is no flip of the bitmap when i drag and drop the model into another one. How can I solve this problem in OMEdit?

To explane the problem in detail. I build up an library for energy conversion technologies. For each technology i choose an icon and load it into OMEdit via bitmap. In the technology-model the bitmap is right, but if i drag and drop it into an system model, the bitmap is the wrong way around..

comment:8 Changed 22 months ago by adeas31

Can you provide a testcase? I will try to take a look at it.

comment:9 Changed 22 months ago by lukas.koenemann@…

Example

model technology_xy
  extends Modelica.Icons.Package;
equation

annotation(
    Icon(graphics = {Bitmap(origin = {2, 0}, extent = {{-90, 84}, {90, -84}}, imageSource = "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")}));
end technology_xy;
model systemmodel
  technology_xy technology_xy annotation(
    Placement(visible = true, transformation(origin = {-8, 26}, extent = {{-10, -10}, {10, 10}}, rotation = 0)));
equation

end systemmodel;

In this example the Bitmap is in "technology_xy" already the wrong way around and in "systemmodel" right.

comment:10 Changed 22 months ago by adeas31

  • Status changed from new to accepted

I see what the problem is. I will try to fix it.

comment:11 Changed 21 months ago by adeas31

  • Milestone changed from 1.17.0 to 1.16.0
  • Resolution set to fixed
  • Status changed from accepted to closed

comment:12 Changed 21 months ago by lukas.koenemann@…

Do i have to update OMEdit to 1.16.0-dev0.3? Or how can i fix my problem?

comment:13 Changed 21 months ago by adeas31

No 1.16.0-dev.03 is old. The fix will be available in tomorrow's nightly build and you can download it from https://build.openmodelica.org/omc/builds/windows/nightly-builds/64bit/ in case you are using Windows.

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