Create art module

.gitignore

@@ -4,6 +4,10 @@
 .vscode/*
 log/
 output/
+SAS_OUTPUTS/
+SASGRAPHS/
+HIVPY_OUTPUTS/
+GRAPHS/
 
 # Compiled and packaged files
 *.egg-info/
@@ -13,3 +17,8 @@ __pycache__/
 
 # Generated documentation
 _build
+
+*.png
+*.sas7bdat
+*.csv
+*.sh

hivpy.yaml

@@ -1,5 +1,5 @@
 EXPERIMENT:
-  population: 1000
+  population: 100000
   start_year: 1989
   end_year: 2021
   time_interval_days: 90

plots.py

@@ -0,0 +1,98 @@
+from itertools import product
+
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+
+# files = ["output\simulation_output_20240205-230047\simulation_output_20240205-230047.csv",
+#          "output\simulation_output_20240205-231331\simulation_output_20240205-231331.csv",
+#          "output\simulation_output_20240206-104041\simulation_output_20240206-104041.csv",
+#          "output\simulation_output_20240206-104444\simulation_output_20240206-104444.csv",
+#          "output\simulation_output_20240206-104524\simulation_output_20240206-104524.csv",
+#          "output\simulation_output_20240206-104650\simulation_output_20240206-104650.csv",
+#          "output\simulation_output_20240206-105003\simulation_output_20240206-105003.csv",
+#          "output\simulation_output_20240206-134436\simulation_output_20240206-134436.csv",
+#          "output\simulation_output_20240206-135429\simulation_output_20240206-135429.csv",
+#          "output\simulation_output_20240206-135605\simulation_output_20240206-135605.csv"]
+files = ["output\simulation_output_20240220-154213\simulation_output_20240220-154213.csv"]
+data = [pd.read_csv(file) for file in files]
+
+men_15_24 = np.array([d["Short term partners (15-64)"] for d in data]).transpose()
+medians = np.array([np.median(tstep) for tstep in men_15_24])
+plt.plot(medians)
+plt.show()
+
+def psb(i, sex):
+    if(sex == 0):
+        sex_string = "male"
+    else:
+        sex_string = "female"
+    return f"Partner sex balance ({i}-{i+9}, {sex_string})"
+
+def pps(i, sex):
+    if(sex == 0):
+        sex_string = "male"
+    else:
+        sex_string = "female"
+    return f"Short term partners ({i}-{i+9}, {sex})"
+
+sexes = [0, 1]
+ages = [15, 25, 35, 45, 55]
+
+for (a,s) in product(ages, sexes):
+    for d in data:
+        plt.plot(1989 + 0.25 * d["Time Step"], d[psb(a, s)])
+    plt.plot(1989 + 0.25 * data[0]["Time Step"], np.zeros(len(data[0])))
+    print(psb(a,s), f"mean = {np.mean(d[psb(a,s)])}", f"std = {np.std(d[psb(a,s)])}", 10**(np.mean(d[psb(a,s)])))
+    plt.title(psb(a, s))
+    plt.show()
+
+# Create a figure with subplots
+fig, axs = plt.subplots(len(ages), len(sexes), figsize=(12, 8))
+fig.suptitle("Short Term Partners and Partner Sex Balance")
+
+# Iterate over ages and sexes
+# for i, a in enumerate(ages):
+#     for j, s in enumerate(sexes):
+#         ax = axs[i, j]
+#         ax.plot(1989 + 0.25 * data[0]["Time Step"], data[0][psb(a, s)], label=pps(a, s))
+#         ax.plot(1989 + 0.25 * data[0]["Time Step"], np.zeros(len(data[0])), linestyle="--", color="gray")
+#         ax.set_title(f"{psb(a, s)}")
+#         ax.set_xlabel("Year")
+#         ax.set_ylabel("Log Partner Balance")
+#         ax.set_aspect(1.0 / ax.get_data_ratio(), adjustable='box')
+#         vals = np.ma.masked_invalid(data[0][psb(a,s)])
+#         print(psb(a,s), f"mean = {np.mean(vals)}", f"std = {np.std(vals)}", f"average unbalance = {np.round((10**(np.mean(vals))-1)*100,2)}%")
+
+# Add legend
+axs[0, 0].legend()
+
+# Adjust spacing between subplots
+plt.tight_layout()
+
+# Show the combined plot
+plt.show()
+
+# for (a,s) in product(ages, sexes):
+#     for d in data:
+#         plt.scatter(1989 + 0.25 * d["Time Step"], d[pps(a, s)])
+#     plt.plot(1989 + 0.25 * data[0]["Time Step"], np.zeros(len(data[0])))
+#     print(pps(a,s), np.mean(d[pps(a,s)]), np.std(d[pps(a,s)]), np.exp(np.mean(d[pps(a,s)])))
+#     plt.title(pps(a, s))
+#     plt.show()
+
+# for d in data:
+#     plt.scatter(d["Time Step"], d["Partner sex balance (15-24, male)"])
+# plt.plot(data[0]["Time Step"], np.zeros(len(data[0])))
+# plt.show()
+# 
+# for d in data:
+#     plt.scatter(d["Time Step"], d["Partner sex balance (25-34, male)"])
+# plt.plot(data[0]["Time Step"], np.zeros(len(data[0])))
+# plt.show()
+# 
+# for d in data:
+#     plt.scatter(d["Time Step"], d["Partner sex balance (35-44, male)"])
+# plt.plot(data[0]["Time Step"], np.zeros(len(data[0])))
+# plt.show()
+

setup.cfg

@@ -17,13 +17,15 @@ package_dir =
 packages = find:
 python_requires = >=3.7
 install_requires =
-    pandas<1.4
-    numpy<2.0.0
+    pandas
+    numpy
     scipy
     pyyaml
     matplotlib
     titlecase
     sas7bdat
+    pytest
+    pytest-mock
 
 [options.packages.find]
 where = src