Commitin

test-data/heat_equation/definition.py

@@ -0,0 +1,32 @@
+from collections import namedtuple
+
+import numpy as np
+
+# Number of grid-cells in x and y direction
+nx = 10
+
+# time steps
+k_start = 0
+k_end = 500
+
+# Define initial condition, i.e., the initial temperature distribution.
+# How you define initial conditions will effect the spread of results,
+# i.e., how similar different realisations are.
+u_init = np.zeros((k_end, nx, nx))
+u_init[:, 5:7, 5:7] = 100
+
+# Resolution in the x-direction (nothing to worry about really)
+dx = 1
+
+Coordinate = namedtuple("Coordinate", ["x", "y"])
+
+obs_coordinates = [
+    Coordinate(5, 3),
+    Coordinate(3, 5),
+    Coordinate(5, 7),
+    Coordinate(7, 5),
+    Coordinate(2, 2),
+    Coordinate(7, 2),
+]
+
+obs_times = np.linspace(10, k_end, 8, endpoint=False, dtype=int)

test-data/heat_equation/generate_files.py

@@ -2,14 +2,14 @@
 Contains code that was used to generate files expected by ert.
 """
 
-from collections import namedtuple
 from textwrap import dedent
 from typing import Callable, List
 
 import numpy as np
 import numpy.typing as npt
 import pandas as pd
 import xtgeo
+from definition import Coordinate, obs_coordinates, obs_times
 from heat_equation import heat_equation, sample_prior_conductivity
 
 rng = np.random.default_rng(11223344)
@@ -23,9 +23,6 @@ def create_egrid_file():
     grid.to_file("CASE.EGRID", "egrid")
 
 
-Coordinate = namedtuple("Coordinate", ["x", "y"])
-
-
 def make_observations(
     coordinates: List[Coordinate],
     times: npt.NDArray[np.int_],
@@ -101,16 +98,6 @@ def make_observations(
     dt = dx**2 / (4 * max(np.max(cond_truth), np.max(cond_truth)))
 
     u_t = heat_equation(u_init, cond_truth, dx, dt, k_start, k_end, rng=rng)
-    obs_coordinates = [
-        Coordinate(5, 3),
-        Coordinate(3, 5),
-        Coordinate(5, 7),
-        Coordinate(7, 5),
-        Coordinate(2, 2),
-        Coordinate(7, 2),
-    ]
-
-    obs_times = np.linspace(10, k_end, 8, endpoint=False, dtype=int)
 
     d = make_observations(
         obs_coordinates, obs_times, u_t, lambda value: abs(0.05 * value)

test-data/heat_equation/heat_equation.py

@@ -3,11 +3,12 @@
 
 from typing import Optional
 
+import geostat
 import numpy as np
+import numpy.typing as npt
+from definition import dx, k_end, k_start, nx, obs_coordinates, obs_times, u_init
 
 rng = np.random.default_rng(1234)
-import geostat
-import numpy.typing as npt
 
 
 def heat_equation(
@@ -57,22 +58,6 @@ def sample_prior_conductivity(ensemble_size, nx, rng):
 
 
 if __name__ == "__main__":
-    # Number of grid-cells in x and y direction
-    nx = 10
-
-    # time steps
-    k_start = 0
-    k_end = 500
-
-    # Define initial condition, i.e., the initial temperature distribution.
-    # How you define initial conditions will effect the spread of results,
-    # i.e., how similar different realisations are.
-    u_init = np.zeros((k_end, nx, nx))
-    u_init[:, 5:7, 5:7] = 100
-
-    # Resolution in the x-direction (nothing to worry about really)
-    dx = 1
-
     cond = sample_prior_conductivity(ensemble_size=1, nx=nx, rng=rng).reshape(nx, nx)
 
     # Write the array to a GRDECL formatted file
@@ -95,9 +80,7 @@ def sample_prior_conductivity(ensemble_size, nx, rng):
 
     response = heat_equation(u_init, cond, dx, dt, k_start, k_end, rng)
 
-    # Pick the responses where you have observations
-    index = [0, 2, 5]
-    with open("gen_data_0.out", "w", encoding="utf-8") as f:
-        for i in index:
-            for value in response[0][i]:
-                f.write(f"{value:.6f}\n")
+    index = sorted((obs.x, obs.y) for obs in obs_coordinates)
+    for time_step in obs_times:
+        with open(f"gen_data_{time_step}.out", "w", encoding="utf-8") as f:
+            f.write("\\n".join(str(response[time_step][i]) for i in index))