Note exceptions for one-primary-test-per-function

Author: honno

README.md

@@ -60,12 +60,13 @@ so as to not unexpectedly fail the suite.
 
 ### Primary tests
 
-Every function—including array object methods—has a respective test method. We
-use [Hypothesis](https://hypothesis.readthedocs.io/en/latest/) to generate a
-diverse set of valid inputs. This means array inputs will cover different dtypes
-and shapes, as well as contain interesting elements. These examples generate
-with interesting arrangements of non-array positional arguments and keyword
-arguments.
+Every function—including array object methods—has a respective test
+method<sup>1</sup>. We use
+[Hypothesis](https://hypothesis.readthedocs.io/en/latest/)
+to generate a diverse set of valid inputs. This means array inputs will cover
+different dtypes and shapes, as well as contain interesting elements. These
+examples generate with interesting arrangements of non-array positional
+arguments and keyword arguments.
 
 Each test case will cover the following areas if relevant:
 
@@ -179,7 +180,7 @@ many utilities that parralel NumPy's own test utils in the `*_helpers.py` files.
 
 ### Tools
 
-Hypothesis should always be used for the primary tests, and can be useful
+Hypothesis should almost always be used for the primary tests, and can be useful
 elsewhere. Effort should be made so drawn arguments are labeled with their
 respective names. For
 [`st.data()`](https://hypothesis.readthedocs.io/en/latest/data.html#hypothesis.strategies.data),
@@ -254,3 +255,23 @@ come across.
   for output values (particularly epsilons for floating-point outputs), so we
   need to review these and either implement assertions or properly note the lack
   thereof.
+
+---
+
+<sup>1</sup>The only exceptions to having just one primary test per function are:
+
+* [`asarray()`](https://data-apis.org/array-api/latest/API_specification/generated/signatures.creation_functions.asarray.html),
+  which is tested by `test_asarray_scalars` and `test_asarray_arrays` in
+  `test_creation_functions.py`. Testing `asarray()` works with scalars (and
+  nested sequences of scalars) is fundamental to testing that it works with
+  arrays, as said arrays can only be generated by passing scalar sequences to
+  `asarray()`.
+
+* Indexing methods
+  ([`__getitem__()`](https://data-apis.org/array-api/latest/API_specification/generated/signatures.array_object.array.__getitem__.html)
+  and
+  [`__setitem__()`](https://data-apis.org/array-api/latest/API_specification/generated/signatures.array_object.array.__setitem__.html)),
+  which respectively have both a test for non-array indices and a test for
+  boolean array indices. This is because [masking is
+  opt-in](https://data-apis.org/array-api/latest/API_specification/indexing.html#boolean-array-indexing)
+  (and boolean arrays need to be generated by indexing arrays anyway).