Demographics.py and build_and_test.yml

.github/workflows/build_and_test.yml

@@ -4,29 +4,31 @@ on: [push, pull_request]
 
 jobs:
   build:
-    runs-on: ubuntu-latest
+    runs-on: ${{ matrix.os }}
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
         python-version: ["3.9", "3.10"]
 
     steps:
       - name: Checkout
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
         with:
           persist-credentials: false
 
-      - name: Setup Python
-        uses: actions/setup-python@v4
+      - name: Setup Miniconda using Python ${{ matrix.python-version }}
+        uses: conda-incubator/setup-miniconda@v2
         with:
+          miniforge-variant: Mambaforge
+          auto-update-conda: true
+          activate-environment: ogusa-dev
+          environment-file: environment.yml
           python-version: ${{ matrix.python-version }}
+          auto-activate-base: false
 
       - name: Build
         shell: bash -l {0}
         run: |
-          conda init bash
-          conda env create
-          conda activate ogusa-dev
           pip install -e .
           pip install pytest-cov
           pip install pytest-pycodestyle

ogusa/demographics.py

@@ -152,25 +152,26 @@ def get_fert(
     #     pp.plot_fert_rates(fert_rates, age_midp, totpers, min_age, max_age,
     #                        fert_rates, fert_rates, output_dir=OUTPUT_DIR)
 
-    output_dir = OUTPUT_DIR
-    # Using pyplot here until update to OG-Core mort rates plotting function
-    plt.plot(
-        np.arange(totpers),
-        fert_rates,
-    )
-    plt.xlabel(r"Age $s$")
-    plt.ylabel(r"Fertility rate")
-    plt.legend(loc="upper left")
-    # plt.text(
-    #     -5,
-    #     -0.2,
-    #     "Source: United Nations Population Prospects.",
-    #     fontsize=9,
-    # )
-    plt.tight_layout(rect=(0, 0.03, 1, 1))
-    output_path = os.path.join(output_dir, "fert_rates")
-    plt.savefig(output_path)
-    plt.close()
+    if graph:
+        output_dir = OUTPUT_DIR
+        # Using pyplot here until update to OG-Core mort rates plotting function
+        plt.plot(
+            np.arange(totpers),
+            fert_rates,
+        )
+        plt.xlabel(r"Age $s$")
+        plt.ylabel(r"Fertility rate")
+        plt.legend(loc="upper left")
+        # plt.text(
+        #     -5,
+        #     -0.2,
+        #     "Source: United Nations Population Prospects.",
+        #     fontsize=9,
+        # )
+        plt.tight_layout(rect=(0, 0.03, 1, 1))
+        output_path = os.path.join(output_dir, "fert_rates")
+        plt.savefig(output_path)
+        plt.close()
 
     return fert_rates
 
@@ -182,7 +183,7 @@ def get_mort(
     country_id=UN_COUNTRY_CODE,
     start_year=START_YEAR,
     end_year=END_YEAR,
-    graph=True,
+    graph=False,
 ):
     """
     This function generates a vector of mortality rates by model period
@@ -297,6 +298,7 @@ def get_imm_rates(
     country_id=UN_COUNTRY_CODE,
     start_year=START_YEAR,
     end_year=END_YEAR,
+    graph=False,
 ):
     """
     Calculate immigration rates by age as a residual given population
@@ -380,26 +382,27 @@ def get_imm_rates(
     # Final estimated immigration rates are the averages over 3 years
     imm_rates = imm_mat.mean(axis=0)
 
-    output_dir = OUTPUT_DIR
-    # Using pyplot here until update to OG-Core mort rates plotting function
-    plt.plot(
-        np.arange(totpers),
-        imm_rates,
-        label="Estimated",
-    )
-    plt.xlabel(r"Age $s$")
-    plt.ylabel(r"Immigration Rates")
-    plt.legend(loc="upper left")
-    plt.text(
-        -5,
-        -0.2,
-        "Source: United Nations Population Prospects.",
-        fontsize=9,
-    )
-    plt.tight_layout(rect=(0, 0.03, 1, 1))
-    output_path = os.path.join(output_dir, "imm_rates_w_un_data.png")
-    plt.savefig(output_path)
-    plt.close()
+    if graph:
+        output_dir = OUTPUT_DIR
+        # Using pyplot here until update to OG-Core mort rates plotting function
+        plt.plot(
+            np.arange(totpers),
+            imm_rates,
+            label="Estimated",
+        )
+        plt.xlabel(r"Age $s$")
+        plt.ylabel(r"Immigration Rates")
+        plt.legend(loc="upper left")
+        plt.text(
+            -5,
+            -0.2,
+            "Source: United Nations Population Prospects.",
+            fontsize=9,
+        )
+        plt.tight_layout(rect=(0, 0.03, 1, 1))
+        output_path = os.path.join(output_dir, "imm_rates_w_un_data.png")
+        plt.savefig(output_path)
+        plt.close()
 
     return imm_rates