Fix CI

.github/workflows/python-publish.yml

@@ -3,50 +3,24 @@ name: Publish to PyPI
 on: push
 
 jobs:
-  build:
-    name: Build distribution 📦
+  deploy:
     runs-on: ubuntu-latest
-
-    steps:
-    - uses: actions/checkout@v4
-    - name: Set up Python
-      uses: actions/setup-python@v4
-      with:
-        python-version: "3.x"
-    - name: Install pypa/build
-      run: >-
-        python3 -m
-        pip install
-        build
-        --user
-    - name: Build a binary wheel and a source tarball
-      run: python3 -m build
-    - name: Store the distribution packages
-      uses: actions/upload-artifact@v3
-      with:
-        name: python-package-distributions
-        path: dist/
-
-  publish-to-pypi:
-    name: >-
-      Publish to PyPI
-    if: startsWith(github.ref, 'refs/tags/')  # only publish to PyPI on tag pushes
-    needs:
-    - build
-    runs-on: ubuntu-latest
-    environment:
-      name: pypi
-      url: https://pypi.org/p/<acoustipy>  # Replace <package-name> with your PyPI project name
-    permissions:
-      username: __token__
-      password: ${{ secrets.PYPI_TOKEN }}
-
     steps:
-    - name: Download all the dists
-      uses: actions/download-artifact@v3
-      with:
-        name: python-package-distributions
-        path: dist/
-    - name: Publish to PyPI
-      uses: pypa/gh-action-pypi-publish@release/v1
+      - uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.x'
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install -r requirements
+          pip install build
+      - name: Build package
+        run: python -m build
+      - name: Publish package
+        uses: pypa/gh-action-pypi-publish@v1
+        with:
+          user: __token__ 
+          password: ${{ secrets.PYPI_PASSWORD }}
 

.gitignore

@@ -68,8 +68,6 @@ instance/
 # Scrapy stuff:
 .scrapy
 
-# Sphinx documentation
-docs/_build/
 
 # PyBuilder
 target/
@@ -127,5 +125,3 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
-
-docs/

docs/AcoustiBase.md

@@ -0,0 +1,2 @@
+# AcoustiBase
+::: src.acoustipy.Database

docs/AcousticID.md

@@ -0,0 +1,2 @@
+# AcousticID
+::: src.acoustipy.Params

docs/AcousticTMM.md

@@ -0,0 +1,3 @@
+# AcousticTMM
+::: src.acoustipy.TMM
+    handler: python

docs/Examples/Hybrid.md

@@ -0,0 +1,48 @@
+# Hybrid Characterization
+Use a hybrid characterization method to identify parameters of the Johnson-Champoux-Allard model given data obtained from an impedance tube.
+
+```python
+from acoustipy import AcousticTMM, AcousticID
+
+# Create an AcousticTMM object to generate toy impedance tube data
+structure = AcousticTMM(incidence='Normal',air_temperature = 20)
+
+# Define the JCA and air gap material parameters for the toy data
+layer1 = structure.Add_JCA_Layer(30, 46182,.917,2.1,83,128)
+air = structure.Add_Air_Layer(thickness = 100)
+
+# Generate rigid backed reflection data and save to a csv file
+s1 = structure.assemble_structure(layer1)
+A1 = structure.reflection(s1)
+structure.to_csv('no_gap',A1)
+
+# Generate air backed reflection data and save to a csv file
+s2 = structure.assemble_structure(layer1,air)
+A2 = structure.reflection(s2)
+structure.to_csv('gap',A2)
+
+# Create an AcousticID object, specifying to mount types, data files, and data types
+inv = AcousticID(mount_type='Dual',no_gap_file="no_gap.csv",gap_file = "gap.csv",input_type='reflection',air_temperature=20)
+
+# Call the Hybrid method to find the tortuosity, viscous, and thermal characteristic lengths of the material
+res = inv.Hybrid(30,.917,air_gap=95,uncertainty = .15)
+
+# print the identified parameters
+print(res)
+
+# Plot the absorption curves using the actual parameters vs those identified from the Indirect method
+inv.plot_comparison(res)
+
+res >>> {'thickness': 29.982,
+         'flow resistivity': 46209.81,
+         'porosity': 0.918,
+         'tortuosity': 2.103,
+         'viscous characteristic length': 83.0,
+         'thermal characteristic length': 128.0,
+         'air gap': 100.0,
+         'error': 1.3018228618069009e-17}
+```
+
+<br></br>
+
+![](../assets/ex_material_identification_hybrid.png)

docs/Examples/Indirect.md

@@ -0,0 +1,48 @@
+# Indirect Characterization
+Use an indirect characterization method to identify parameters of the Johnson-Champaux-Allard model given data obtained from an impedance tube.
+
+```python
+from acoustipy import AcousticTMM, AcousticID
+
+# Create an AcousticTMM object to generate toy impedance tube data
+structure = AcousticTMM(incidence='Normal',air_temperature = 20)
+
+# Define the JCA and air gap material parameters for the toy data
+layer1 = structure.Add_JCA_Layer(30, 46182,.917,2.1,83,128)
+air = structure.Add_Air_Layer(thickness = 100)
+
+# Generate rigid backed reflection data and save to a csv file
+s1 = structure.assemble_structure(layer1)
+A1 = structure.reflection(s1)
+structure.to_csv('no_gap',A1)
+
+# Generate air backed reflection data and save to a csv file
+s2 = structure.assemble_structure(layer1,air)
+A2 = structure.reflection(s2)
+structure.to_csv('gap',A2)
+
+# Create an AcousticID object, specifying to mount types, data files, and data types
+inv = AcousticID(mount_type='Dual',no_gap_file="no_gap.csv",gap_file = "gap.csv",air_temperature=20,input_type='reflection')
+
+# Call the Indirect method to find the flow resistivity, tortuosity, and viscous, and thermal characteristic lengths of the material
+res = inv.Indirect(30,.917,air_gap=100)
+
+# Plot the absorption curves using the actual parameters vs those identified from the Indirect method
+inv.plot_comparison(res)
+
+# print the identified parameters
+print(res)
+
+res >> {'thickness': 30,
+        'flow resistivity': 46182.79193470273, 
+        'porosity': 0.9326784023844896,
+        'tortuosity': 2.1373594528548225,
+        'viscous characteristic length': 83.16500367154856,
+        'thermal characteristic length': 115.12539138619321,
+        'air gap': 100}
+
+```
+
+<br></br>
+
+![](../assets/ex_material_identification_indirect.png)

docs/Examples/Inverse.md

@@ -0,0 +1,45 @@
+# Inverse JCA Characterization
+Use an inverse characterization method to identify parameters of the Johnson-Champaux-Allard model given data obtained from an impedance tube.
+
+```python
+from acoustipy import acousticTMM, AcousticID
+
+# Create an AcousticTMM object to generate toy impedance tube data
+structure = acousticTMM(incidence='Normal',air_temperature = 20)
+
+# Define the JCA and air gap material parameters for the toy data
+layer1 = structure.Add_JCA_Layer(thickness = 30, flow_resistivity = 46879, porosity = .93, tortuosity = 1.7, viscous_characteristic_length = 80, thermal_characteristic_length = 105)
+air = structure.Add_Air_Layer(thickness = 375)
+
+# Generate rigid backed absorption data and save to a csv file
+s1 = structure.assemble_structure(layer1)
+A1 = structure.absorption(s1)
+structure.to_csv('no_gap',A1)
+
+# Generate air backed absorption data and save to a csv file
+s2 = structure.assemble_structure(layer1,air)
+A2 = structure.absorption(s2)
+structure.to_csv('gap',A2)
+
+# Create an AcousticID object, specifying to mount types, data files, and data types
+inv = AcousticID(mount_type='Dual',no_gap_file="no_gap.csv", gap_file = 'gap.csv',air_temperature=20,input_type='absorption')
+
+# Call the Inverse method to find the tortuosity, viscous, and thermal characteristic lengths of the material
+res = inv.Inverse(30, 47000,.926,air_gap=375,uncertainty=.2,verbose=True)
+
+# Display summary statistics about the optimization
+stats = inv.stats(res)
+print(stats)
+
+# Plot the results of the found parameters compared to the toy input data
+inv.plot_comparison(res)
+
+# Save the optimization results to a csv
+inv.to_csv("params.csv",res)
+
+stats = {'slope': 1.000037058594857, 'intercept': 9.276088883464206e-05, 'r_value': 0.9999999674493408, 'p_value': 0.0, 'std_err': 8.732362148426126e-06}
+```
+
+<br></br>
+
+![](../assets/ex_material_identification_inverse.png)

docs/Examples/impedance_tube.md

@@ -0,0 +1,69 @@
+# Using impedance tube data
+Estimate the diffuse sound field absorption coefficients of a structure
+using the normal incidence reflection coefficients obtained via impedance
+tube. 
+
+```python
+from acoustipy import AcousticTMM
+
+# Generate synthetic "impedance tube" data
+structure = AcousticTMM(incidence='Normal', air_temperature = 20)
+
+# Define the JCA and air gap material parameters for the synthetic data
+layer1 = structure.Add_JCA_Layer(25.4, 60000, .91, 1.3, 85, 110)
+air = structure.Add_Air_Layer(thickness = 100)
+
+# Generate rigid backed reflection data and save to a csv file
+s1 = structure.assemble_structure(layer1)
+r1 = structure.reflection(s1)
+structure.to_csv('no_gap_tube',r1)
+
+# Generate air backed absorption data and save to a csv file
+s2 = structure.assemble_structure(layer1,air)
+r2 = structure.reflection(s2)
+structure.to_csv('gap_tube',r2)
+
+# Create a new structure to estimate the diffuse field absorption coefficients
+estimated_structure = AcousticTMM(incidence='Diffuse', air_temperature = 20)
+
+# Load the synthetic impedance tube data and define a new air layer
+estimated_layer = estimated_structure.Add_Layer_From_Tube(no_gap_file = 'no_gap_tube.csv', gap_file='gap_tube.csv', sample_thickness=25.4, air_gap_thickness=100)
+air2 = estimated_structure.Add_Air_Layer(thickness = 400)
+
+# Generate narrow band absorption data for the new structure
+s3 = estimated_structure.assemble_structure(estimated_layer,air2)
+absorption = structure.absorption(s3)
+
+# Calculate the 3rd octave bands absorption coefficients
+bands = structure.octave_bands(absorption)
+
+# Calculate the four frequency average absorption
+ffa_estimate = structure.FFA(bands)
+print(ffa_estimate)
+
+>>> 0.717
+
+# Compare the estimated FFA to that calculated from the original layer data
+air3 = structure.Add_Air_Layer(thickness = 400)
+s4 = structure.assemble_structure(layer1,air3)
+abs1 = structure.absorption(s4)
+bands1 = structure.octave_bands(abs1)
+ffa_original = structure.FFA(bands1)
+print(ffa_original)
+
+>>> 0.717
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+

docs/Examples/layer_to_database.md

@@ -0,0 +1,26 @@
+# Saving layers to a database
+Save the parameters of individual layers to a built-in SQLite database.
+
+```python
+from acoustipy import AcousticTMM, AcoustiBase
+
+
+structure = AcousticTMM(incidence='Normal',air_temperature = 20)
+
+# For each Add_XXX_Layer method, enable the save_layer parameter and give it a unique layer name
+db = structure.Add_DB_Layer(25.4, 50000,save_layer=True,layer_name='test_DB')
+dbm = structure.Add_DBM_Layer(25.4, 50000,save_layer=True,layer_name='test_DBM')
+jca = structure.Add_JCA_Layer(25.4, 50000,.90,1.2,80,110,save_layer=True,layer_name='test_JCA')
+jcal = structure.Add_JCAL_Layer(25.4, 50000,.90,1.2,80,110,50,save_layer=True,layer_name='test_JCAL')
+jcapl = structure.Add_JCAPL_Layer(25.4, 50000, .90, 1.2, 80, 110, 50, 70, 65,save_layer=True,layer_name='test_JCAPL')
+horoshenkov = structure.Add_Horoshenkov_Layer(40, .90, 147, .325, save_layer=True, layer_name='test_horoshenkov')
+biot_limp = structure.Add_Biot_Limp_Layer('JCA',25.4, 50000,200, .90, 1.2, 80, 110,save_layer=True,layer_name='test_biot_limp')
+biot_rigid = structure.Add_Biot_Rigid_Layer('JCA',25.4, 50000,200, .90, 1.2, 80, 110,save_layer=True,layer_name='test2_biot_rigid')
+screen = structure.Add_Resistive_Screen(2.54, 50000, .90,save_layer=True,layer_name='test_screen')
+maa = structure.Add_MAA_MPP_Layer(2.54, .5, 1,save_layer=True,layer_name='test_maa_mpp')
+ef_mpp = structure.Add_MPP_EF_Layer(2.54, .5, 1,save_layer=True,layer_name='test_ef_mpp')
+
+# Pull the layer information from the database and save to a .csv file
+s = AcoustiBase()
+s.summarize_layers()
+```

docs/Examples/layers_from_database.md

@@ -0,0 +1,32 @@
+# Load layers from a database
+Load the previously saved layers from the database and calculate the transmission loss
+of one of the layers.
+
+```python
+from acoustipy import AcousticTMM
+
+structure = AcousticTMM(incidence='Normal',air_temperature = 20)
+
+# Add layers from the database
+db = structure.Add_Layer_From_Database('test_DB')
+dbm = structure.Add_Layer_From_Database('test_DBM')
+jca = structure.Add_Layer_From_Database('test_JCA')
+jcal = structure.Add_Layer_From_Database('test_JCAL')
+jcapl = structure.Add_Layer_From_Database('test_JCAPL')
+horoshenkov = structure.Add_Layer_From_Database('test_horoshenkov')
+biot_limp = structure.Add_Layer_From_Database('test_biot_limp')
+biot_rigid = structure.Add_Layer_From_Database('test2_biot_rigid')
+screen = structure.Add_Layer_From_Database('test_screen')
+maa = structure.Add_Layer_From_Database('test_maa_mpp')
+ef_mpp = structure.Add_Layer_From_Database('test_ef_mpp')
+
+# Calculate th narrow band transmission coefficients for the JCA layer
+s = structure.assemble_structure(jca)
+tl = structure.transmission_loss(s)
+
+# Plot the transmission coefficients
+structure.plot_curve([tl])
+```
+<br>
+
+![](../assets/ex_layers_from_database.png)