From 3f81169f5742c52a1542b97c93a3321b30fe7690 Mon Sep 17 00:00:00 2001
From: John Stachurski <john.stachurski@gmail.com>
Date: Wed, 3 Oct 2018 09:07:06 -0400
Subject: [PATCH] misc

---
 infinite_horizon_job_search/lininterp.py | 49 ++++++++++++++++++++++++
 1 file changed, 49 insertions(+)
 create mode 100644 infinite_horizon_job_search/lininterp.py

diff --git a/infinite_horizon_job_search/lininterp.py b/infinite_horizon_job_search/lininterp.py
new file mode 100644
index 0000000..407e9b8
--- /dev/null
+++ b/infinite_horizon_job_search/lininterp.py
@@ -0,0 +1,49 @@
+import numpy as np
+from numba import jit
+
+@jit(nopython=True)
+def interp1d(grid, vals, x):
+    """
+    Linearly interpolate (grid, vals) to evaluate at x.
+
+    Parameters
+    ----------
+        grid and vals are numpy arrays, x is a float
+
+    Returns
+    -------
+        a float, the interpolated value
+
+    """
+
+    a, b, G = np.min(grid), np.max(grid), len(grid)
+
+    s = (x - a) / (b - a)
+
+    q_0 = max(min(int(s * (G - 1)), (G - 2)), 0)
+    v_0 = vals[q_0]
+    v_1 = vals[q_0 + 1]
+
+    λ = s * (G - 1) - q_0
+
+    return (1 - λ) * v_0 + λ * v_1
+
+
+@jit(nopython=True)
+def interp1d_vectorized(grid, vals, x_vec):
+    """
+    Linearly interpolate (grid, vals) to evaluate at x_vec.
+
+    All inputs are numpy arrays.
+
+    Return value is a numpy array of length len(x_vec).
+    """
+
+    out = np.empty_like(x_vec)
+
+    for i, x in enumerate(x_vec):
+        out[i] = interp1d(grid, vals, x)
+
+    return out
+
+