Merge pull request SALib#446 from schmitts/sample_with_power_of_two

Sample with power of two to avoid warning
willu47 · Jul 8, 2021 · 4012c13 · 4012c13
2 parents 9fba0aa + d4e1dee
commit 4012c13
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Showing 5 changed files with 10 additions and 10 deletions.
diff --git a/README-advanced.md b/README-advanced.md
@@ -17,7 +17,7 @@ Parameter files can also be comma-delimited if your parameter names or group nam
 **Generate samples** (the `-p` flag is the parameter file)
 ```
 salib sample saltelli \
-     -n 1000 \
+     -n 1024 \
      -p ./src/SALib/test_functions/params/Ishigami.txt \
      -o model_input.txt
 ```
@@ -68,7 +68,7 @@ problem = {
 `groups` is a list of strings specifying the group name to which each variable belongs. The rest of the code stays the same:
 
 ```python
-param_values = saltelli.sample(problem, 1000)
+param_values = saltelli.sample(problem, 1024)
 Y = Ishigami.evaluate(param_values)
 Si = sobol.analyze(problem, Y, print_to_console=True)
 ```
@@ -109,7 +109,7 @@ problem = {
                [-3.14159265359, 3.14159265359]]
 }
 
-param_values = saltelli.sample(problem, 1000)
+param_values = saltelli.sample(problem, 1024)
 ```
 
 SALib is also capable of generating alternate sampling distributions by 

diff --git a/README.rst b/README.rst
@@ -74,7 +74,7 @@ Procedural approach
     }
 
     # Generate samples
-    param_values = saltelli.sample(problem, 1000)
+    param_values = saltelli.sample(problem, 1024)
 
     # Run model (example)
     Y = Ishigami.evaluate(param_values)
@@ -128,7 +128,7 @@ Chaining calls is supported from SALib v1.4
       'outputs': ['Y']               # name of outputs in expected order
     })
 
-    (sp.sample_saltelli(1000, calc_second_order=True)
+    (sp.sample_saltelli(1024, calc_second_order=True)
        .evaluate(Ishigami.evaluate)
        .analyze_sobol(print_to_console=True))
 

diff --git a/docs/advanced.rst b/docs/advanced.rst
@@ -33,7 +33,7 @@ Or in the `problem` dictionary:
 
 .. code:: python
 
-    param_values = saltelli.sample(problem, 1000)
+    param_values = saltelli.sample(problem, 1024)
     Y = Ishigami.evaluate(param_values)
     Si = sobol.analyze(problem, Y, print_to_console=True)
 
@@ -69,7 +69,7 @@ In :ref:`basics`, we generate a uniform sample of parameter space.
                    [-3.14159265359, 3.14159265359]]
     }
 
-    param_values = saltelli.sample(problem, 1000)
+    param_values = saltelli.sample(problem, 1024)
 
 SALib is also capable of generating alternate sampling distributions by 
 specifying a :code:`dists` entry in the :code:`problem` specification.

diff --git a/docs/basics.rst b/docs/basics.rst
@@ -104,12 +104,12 @@ below.
 
 .. code:: python
 
-    param_values = saltelli.sample(problem, 1000)
+    param_values = saltelli.sample(problem, 1024)
 
 Here, :code:`param_values` is a NumPy matrix.  If we run
 :code:`param_values.shape`, we see that the matrix is 8000 by 3.  The Saltelli
 sampler generated 8000 samples.  The Saltelli sampler generates
-:math:`N*(2D+2)` samples, where in this example N is 1000 (the argument we
+:math:`N*(2D+2)` samples, where in this example N is 1024 (the argument we
 supplied) and D is 3 (the number of model inputs). The keyword argument :code:`calc_second_order=False` will exclude second-order indices, resulting in a smaller sample matrix with :math:`N*(D+2)` rows instead.
 
 Run Model

diff --git a/docs/getting-started.rst b/docs/getting-started.rst
@@ -73,7 +73,7 @@ and copy/paste the code below.
     }
 
     # Generate samples
-    param_values = saltelli.sample(problem, 1000)
+    param_values = saltelli.sample(problem, 1024)
 
     # Run model (example)
     Y = Ishigami.evaluate(param_values)