Plots for poster

modeling.py

@@ -0,0 +1,31 @@
+import numpy as np
+def calc_upper(c: int, m: float, b: float) -> float:
+    return np.floor(c / 32) * 32 * m + b
+
+def calc_lower(c: int, m: float, b: float) -> float:
+    return np.ceil(c / 32) * 32 * m + b
+
+def calc_mean(c:int , m_u: float, b_u: float, m_l: float, b_l: float) -> float:
+    return (calc_upper(c, m_u, b_u) + calc_lower(c, m_l, b_l)) / 2
+
+def calc_rect(c:int , m_u: float, b_u: float, m_l: float, b_l: float) -> float:
+    if ((c - 1) % 8) < 4:
+        return calc_upper(c, m_u, b_u)
+    else:
+        return calc_lower(c, m_l, b_l)
+
+def lin_interpol(x0:float, x1:float, y0:float, y1:float) -> (float, float):
+    m = (y1 - y0) / (x1 - x0)
+    b = y1 - m * x1
+    return m, b
+
+def calculate_deltas(sweep:list[float]):
+    deltas = []
+    lv = sweep[0]
+    for meas in list(sweep)[1:]:
+        deltas.append((meas / lv))
+        lv = meas
+    return deltas
+
+def compute_absolute_percentage_errors(measurements: list[float], guesses: list[float]):
+    return [np.abs((guess - meas) / meas) * 100 for guess, meas in zip(guesses, measurements)]