Gmshcascade

.gitlab-ci.yml

@@ -8,20 +8,16 @@ variables:
     SREGISTRY_URL : "https://cloud.sylabs.io/"
     SREGISTRY_USERNAME : nyhuma
 
-# Pip's cache doesn't store the python packages
-# https://pip.pypa.io/en/stable/topics/caching/
-#
-# If you want to also cache the installed packages, you have to install
-# them in a virtualenv and cache it as well.
-cache:
-    paths:
-        - .cache/pip
-        - venv/
 
 
-.before_script_template: &build_test
+.before_script_template: &environment
  before_script:
-    - apt-get update -y && apt-get install libgl1-mesa-glx xvfb -y
+    - apt-get update -y
+    # graphics
+    - apt-get install libgl1-mesa-glx xvfb -y
+    # gmsh
+    - apt-get install libglu1-mesa libxcursor1 libxinerama1 -y
+    # repository
     - python -m pip install --upgrade pip
     - python --version  # For debugging
     - pip install virtualenv
@@ -35,43 +31,55 @@ stages: # List of stages for jobs, and their order of execution
     - docs
     - deploy
 
+cache:
+    paths:
+        - .cache/pip
+        - venv/
+        - /var/cache/apt/archives/
+
 build:
     stage: build
-    <<: *build_test
+    <<: *environment
     script:
         - pip install .
 
-
 test: # This job runs in the build stage, which runs first.
     stage: test
-    <<: *build_test
+    <<: *environment
     script:
         - pip install .
         - pip install -r requirements_dev.txt
         - pytest tests/.
+    dependencies:
+        - build
 
 lint_test: # This job also runs in the test stage.
     stage: quality
-    <<: *build_test    # It can run at the same time as unit-test-job (in parallel).
+    <<: *environment    # It can run at the same time as unit-test-job (in parallel).
     script:
         - pip install flake8
         - flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics --exclude='venv/'
         - flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics   --exclude='venv/'
+    dependencies:
+        - build
 
 jupyter_test:
   stage: quality
-  <<: *build_test
+  <<: *environment
   script:
     - apt-get install pandoc -y
     - apt-get install texlive-xetex texlive-fonts-recommended texlive-plain-generic -y
-    - pip install nbconvert
+    - pip install nbconvert ipykernel
+    - pip install . #todo: this should not be necessary
     - cd examples
     # Loop through .ipynb files in the examples directory
     - for file in *.ipynb; do echo "Converting $file to PDF..."; jupyter nbconvert --execute "$file" --to pdf; done
+  dependencies:
+    - build
 
 coverage_test:
   stage: quality
-  <<: *build_test
+  <<: *environment
   script:
         - pip install .
         - pip install -r requirements_dev.txt
@@ -81,11 +89,13 @@ coverage_test:
   artifacts:
     paths:
       - coverage.xml
-    when: always
+  dependencies:
+      - build
+
 
 pages:
   stage: docs
-  <<: *build_test
+  <<: *environment
   script:
     - pip install sphinx sphinx-rtd-theme
     - cd docs
@@ -95,7 +105,11 @@ pages:
     paths:
       - public
   rules:
-    - if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH
+    - exists:
+        - $CI_COMMIT_TAG
+    - exists:
+        - $CI_COMMIT_BRANCH
+        - $CI_DEFAULT_BRANCH
 
 build-singularity:
   image:
@@ -111,7 +125,7 @@ build-singularity:
 
 publish:
   stage: deploy
-  <<: *build_test
+  <<: *environment
   script:
     - pip install twine
     - python setup.py sdist bdist_wheel

CONTRIBUTING.rst

@@ -13,7 +13,7 @@ Types of Contributions
 Report Bugs
 ~~~~~~~~~~~
 
-Report bugs at  https://github.com/MaNyh/ntrfc/issues
+Report bugs at  https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC/-/issues
 
 If you are reporting a bug, please include:
 
@@ -24,7 +24,7 @@ If you are reporting a bug, please include:
 Fix Bugs
 ~~~~~~~~
 
-Look through the GitHub issues for bugs. Anything tagged with "bug" and "help
+Look through the issues for bugs. Anything tagged with "bug" and "help
 wanted" is open to whoever wants to implement it.
 
 Implement Features
@@ -43,7 +43,7 @@ NTRfC could always use more documentation, whether as part of the official NTRfC
 Submit Feedback
 ~~~~~~~~~~~~~~~
 
-The best way to send feedback is to file an issue at https://github.com/MaNyh/ntrfc/issues.
+The best way to send feedback is to file an issue at https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC/-/issues .
 
 If you are proposing a feature:
 
@@ -83,13 +83,13 @@ Ready to contribute? Here's how to set up `ntrfc` for local development.
 
    To get flake8 and tox, just pip install them into your virtualenv.
 
-6. Commit your changes and push your branch to GitHub::
+6. Commit your changes and push your branch to GitLab::
 
     $ git add .
     $ git commit -m "Your detailed description of your changes."
     $ git push origin name-of-your-bugfix-or-feature
 
-7. Submit a pull request through the GitHub website.
+7. Submit a pull request through the GitLab website.
 
 Pull Request Guidelines
 -----------------------

HISTORY.rst

@@ -2,6 +2,13 @@
 History
 =======
 
+0.1.5 (2023-07-04)
+------------------
+- bugfixes alphashape
+- initial gmsh intigration
+- jupyternotebook testing
+- improved codecov
+
 0.1.4 (2023-06-25)
 ------------------
 - cleaner structure, more reliability

README.rst

@@ -2,7 +2,7 @@
 NTRfC README
 ============
 
-Numerical Test Rig for Cascades.
+**Numerical Test Rig for Cascades.**
 
 
 * Free software: MIT license
@@ -11,14 +11,20 @@ Numerical Test Rig for Cascades.
 
 
 
-Features
+**Features**
 
 Easy geometry and post-processing visualization and manipulation with pyvista.
 Tested methods and functions for math, time-series, and mesh quality analysis.
 
-Dependencies
+**Dependencies**
 
-NTRfC v0.1.0 and any following version is based on Python 3.10. Only older versions can be used with older versions of Python. Library requirements will be installed with the package itself.
+- libgl1-mesa-glx (graphics driver)
+- xvfb (virtual Display)
+- libglu1-mesa (gmsh dependency)
+- libxcursor1 (gmsh dependency)
+- libxinerama1 (gmsh dependency)
+
+Current NTRfC versions are based on Python 3.10. Only versions <v0.1.0 can be used with older versions of Python. Library requirements will be installed with the package itself.
 Installation
 
 NTRfC is utilizing powerful and complex dependencies like pyvista and gmsh. We strongly recommend using virtual or conda environments for installation.
@@ -31,14 +37,21 @@ For more information, see:
     mamba: https://mamba.readthedocs.io/en/latest/installation.html
 
 
+**Installation**
+
+Installation from pypi
+
+```
+pip install ntrfc
+```
 
-### Installation from gitlab with pip
+Installation from gitlab with pip
 
 ```
 pip install git+https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC.git
 ```
 
-### Installation from source
+Installation from source
 
 After cloning the repository, go to the project root dir and type
 
@@ -46,8 +59,7 @@ After cloning the repository, go to the project root dir and type
 python setup.py install
 ```
 
-
-### Editable installation from source with pip
+Editable installation from source with pip
 
 After cloning the repository, go to the project root dir and type
 
@@ -59,12 +71,12 @@ This way you have NTRfC installed but the code is not installed, but linked to t
 You don't have to reinstall the package after your edits.
 This speeds up testing and will lead to less debugging time.
 
-### Singularity releases
+**Singularity releases**
 
-use a singularity container from ntrfc singularity releases:  https://cloud.sylabs.io/library/nyhuma/ntrflows/ntr.sif].
+Use a singularity container from ntrfc singularity releases:  https://cloud.sylabs.io/library/nyhuma/ntrflows/ntr.sif].
 The containers will come with a virtual graphics card and a xvfb display-server, enabling you to render on hpc-systems and any other unprepared system with limited graphics capability.
 
-## Credits
+**Credits**
 
 This package was created with Cookiecutter and the `audreyr/cookiecutter-pypackage` project template. It uses the following libraries:
 

docs/installation.rst

@@ -26,19 +26,19 @@ you through the process.
 From sources
 ------------
 
-The sources for NTRfC can be downloaded from the `Github repo`_.
+The sources for NTRfC can be downloaded from the `https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC repo`_.
 
 You can either clone the public repository:
 
 .. code-block:: console
 
-    $ git clone git://github.com/MaNyh/ntrfc
+    $ git clone https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC.git
 
 Or download the `tarball`_:
 
 .. code-block:: console
 
-    $ curl -OJL https://github.com/MaNyh/ntrfc/tarball/master
+    $ curl -OJL https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC/tarball/master
 
 Once you have a copy of the source, you can install it with:
 
@@ -47,5 +47,5 @@ Once you have a copy of the source, you can install it with:
     $ python setup.py install
 
 
-.. _Github repo: https://github.com/MaNyh/ntrfc
-.. _tarball: https://github.com/MaNyh/ntrfc/tarball/master
+.. _Github repo: https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC.git
+.. _tarball: https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC.git/tarball/master

ntrfc/cascade_case/domain.py

@@ -15,14 +15,20 @@ class CascadeDomain2D:
     casemeta: CaseMeta = CaseMeta(tempfile.mkdtemp())
     pressureside: pv.PolyData = None
     suctionside: pv.PolyData = None
+    profilepoints: pv.PolyData = None
+    le_index: int = None
+    te_index: int = None
     yperiodic_low: pv.PolyData = None
     yperiodic_high: pv.PolyData = None
     inlet: pv.PolyData = None
     outlet: pv.PolyData = None
 
+
     def generate_from_cascade_parameters(self, domainparams: DomainParameters):
         # Use params attributes to generate attributes of CascadeDomain2D
-
+        self.profilepoints = domainparams.profile_points
+        self.le_index = domainparams.leading_edge_index
+        self.te_index = domainparams.trailing_edge_index
         x_mids = domainparams.midspoly.points[::, 0]
         y_mids = domainparams.midspoly.points[::, 1]
         beta_leading = domainparams.beta_in

ntrfc/cascade_case/utils/domain_utils.py

 import tempfile
 from dataclasses import dataclass
-
+import os
 import pyvista as pv
 
 from ntrfc.turbo.pointcloud_methods import extract_geo_paras
@@ -50,6 +50,8 @@ class DomainParameters:
         Returns:
             pv.Plotter: The PyVista plotter object used for plotting.
         """
+        if os.getenv('DISPLAY') is None:
+            pv.start_xvfb()  # Start X virtual framebuffer (Xvfb)
         pv.set_plot_theme('document')
         plotter = pv.Plotter(off_screen=True)
         plotter.window_size = 1600, 1600

ntrfc/gmsh/turbo_cascade.py

+# Import modules:
+import gmsh
+
+# Initialize gmsh:
+
+import numpy as np
+import pyvista as pv
+from ntrfc.geometry.line import lines_from_points
+from ntrfc.math.vectorcalc import vecAbs_list
+
+def generate_turbocascade(sortedpoly, idx_le, idx_te, per_y_upper, per_y_lower, inletPoly, outletPoly, filename,
+                          verbose=False):
+
+
+    ###CONFIGURATION
+
+    min_lc = 0.000002
+    max_lc = 0.02
+
+    lc = 5e-2  # Characteristic length for blade region
+
+
+    # Initialize gmsh:
+    gmsh.initialize()
+    points = {}
+    splines = {}
+    lines = {}
+    curveloops = {}
+    surfaceloops = {}
+    surfaces = {}
+
+
+    sortedpoly_spline = lines_from_points(sortedpoly.points)
+    inlet_spline = lines_from_points(inletPoly.points)
+    per_y_upper_spline = lines_from_points(per_y_upper.points)
+    outlet_spline = lines_from_points(outletPoly.points[::-1])
+    per_y_lower_spline = lines_from_points(per_y_lower.points[::-1])
+
+    sortedpoly_spline["ids"] = np.arange(sortedpoly_spline.number_of_points)
+    inlet_spline["ids"] = np.arange(inlet_spline.number_of_points)
+    per_y_upper_spline["ids"] = np.arange(per_y_upper_spline.number_of_points)
+    outlet_spline["ids"] = np.arange(outlet_spline.number_of_points)
+    per_y_lower_spline["ids"] = np.arange(per_y_lower_spline.number_of_points)
+
+    if verbose:
+        p = pv.Plotter()
+        p.add_mesh(sortedpoly_spline, label="sortedpoly_spline")
+        p.add_mesh(sortedpoly_spline.points[idx_le], label="idx_le", color="green", point_size=20)
+        p.add_mesh(sortedpoly_spline.points[idx_te], label="idx_te", color="red", point_size=20)
+        p.add_mesh(inlet_spline, label="inlet_spline")
+        p.add_mesh(per_y_upper_spline, label="per_y_upper_spline")
+        p.add_mesh(outlet_spline, label="outlet_spline")
+        p.add_mesh(per_y_lower_spline, label="per_y_lower_spline")
+        p.add_legend()
+        p.show()
+
+    distance_leading_edge = vecAbs_list(sortedpoly_spline.points[idx_le] - sortedpoly_spline.points)
+    distance_trailing_edge = vecAbs_list(sortedpoly_spline.points[idx_te] - sortedpoly_spline.points)
+
+    lc_blade_new = np.min(np.stack([distance_leading_edge, distance_trailing_edge]).T,axis=1)
+    lc_blade_new_normalized = (lc_blade_new - min(lc_blade_new)) * (max_lc - min_lc) / (max(lc_blade_new) - min(lc_blade_new)) + min_lc
+
+    points["blade"] = [gmsh.model.occ.add_point(*pt, lcb) for pt,lcb in zip(sortedpoly_spline.points,lc_blade_new_normalized)]
+    points["per_y_upper"] = [gmsh.model.occ.add_point(*pt, lc) for pt in per_y_upper.points]
+    points["per_y_lower"] = [gmsh.model.occ.add_point(*pt, lc) for pt in per_y_lower.points[::-1]]
+    points["inlet"] = [points["per_y_lower"][-1], points["per_y_upper"][0]]
+    points["outlet"] = [points["per_y_upper"][-1], points["per_y_lower"][0]]
+
+    splines["blade"] = gmsh.model.occ.add_spline([*points["blade"], points["blade"][0]])
+    splines["inlet"] = gmsh.model.occ.add_spline(points["inlet"])
+    splines["per_y_upper"] = gmsh.model.occ.add_spline(points["per_y_upper"])
+    splines["outlet"] = gmsh.model.occ.add_spline(points["outlet"])
+    splines["per_y_lower"] = gmsh.model.occ.add_spline(points["per_y_lower"])
+
+    curveloops["blade"] = gmsh.model.occ.add_curve_loop([splines["blade"]])
+    curveloops["domain"] = gmsh.model.occ.add_curve_loop(
+        [splines["inlet"], splines["per_y_upper"], splines["outlet"], splines["per_y_lower"]])
+
+    #surfaces["blade"] = gmsh.model.occ.add_plane_surface([curveloops["blade"]])
+    surfaces["domain"] = gmsh.model.occ.add_plane_surface([curveloops["domain"], curveloops["blade"]])
+    f = gmsh.model.mesh.field.add('BoundaryLayer')
+    gmsh.model.mesh.field.setNumbers(f, 'CurvesList', [curveloops["blade"]])
+    gmsh.model.mesh.field.setNumber(f, 'Size', 1.7e-5)
+    gmsh.model.mesh.field.setNumber(f, 'Ratio', 1.2)
+    gmsh.model.mesh.field.setNumber(f, 'Quads', 1)
+    gmsh.model.mesh.field.setNumber(f, 'Thickness', 0.05)
+    gmsh.model.mesh.field.setAsBoundaryLayer(f)
+    # Extrude the domain surface in the z-direction
+    volume = gmsh.model.occ.extrude([(2, surfaces["domain"])], 0, 0, 0.6,numElements=[10],recombine=True)
+
+    gmsh.model.occ.synchronize()
+
+    gmsh.model.addPhysicalGroup(2, [1], 1, "The 1")
+    gmsh.model.addPhysicalGroup(2, [2], 2, "The 2")
+    gmsh.model.addPhysicalGroup(2, [3], 3, "The 3")
+    gmsh.model.addPhysicalGroup(2, [4], 4, "The 4")
+    gmsh.model.addPhysicalGroup(2, [5], 5, "The 5")
+    gmsh.model.addPhysicalGroup(2, [6], 6, "The 6")
+    gmsh.model.addPhysicalGroup(2, [7], 7, "The 7")
+    gmsh.model.addPhysicalGroup(3, [1], 1, "The volume")
+    gmsh.model.occ.synchronize()
+
+
+
+    # Generate mesh:
+    gmsh.model.mesh.generate(3)
+
+    # Write mesh data:
+    gmsh.write(filename)
+
+    return 0

requirements.txt

@@ -14,3 +14,4 @@ trame==2.5.0
 scikit-learn
 jupyter
 sphinx
+gmsh==4.11.1

setup.cfg

 [bumpversion]
-current_version = 0.1.4
+current_version = 0.1.5
 commit = True
 tag = True
 

setup.py

@@ -46,6 +46,6 @@ setup(
     test_suite='tests',
     tests_require=test_requirements,
     url='https://gitlab.uni-hannover.de/tfd_public/tools/NTRfC',
-    version='0.1.4',
+    version='0.1.5',
     zip_safe=False,
 )