Testing pre-commit

docs/FAQ.rst

@@ -3,7 +3,7 @@
 FAQ
 =================
 
-1. Precission Loss
+1. Precision Loss
 ^^^^^^^^^^^^^^^^^^
 
   ::
@@ -12,9 +12,9 @@ FAQ
 
 Check the jac value,
 
-1.1 If all absulute value is small. it is acceptable because of the precision.
+1.1 If all absulute values are small. it is acceptable because of the precision.
 
-1.2 If some absolute value is large. It is the bad parameters or problem in models.
+1.2 If some absolute values are large. It is due to the bad parameters or some problem in the models.
 
 1.3 Avoid negative weights
 
@@ -30,26 +30,26 @@ Check the jac value,
 
 There is a script (scripts/check_nan.py) to check it.
 
-2.1.1 No stange value in data, (nan, infs ...).
+2.1.1 No strange value in data, (nan, infs ...).
 
 2.1.2 The data order should be :math:`E, p_x, p_y,p_z`, :math:`E` is the first.
 
-2.1.3 The mass should be valid, :math:`E^2 - p_x^2 - p_y^2 - p_z^2 > 0`, and for any combinations of final particles, mab > ma  + mb.
+2.1.3 The mass should be valid, :math:`E^2 - p_x^2 - p_y^2 - p_z^2 > 0`, and for any combination of final particles, mab > ma  + mb.
 
-2.1.4 Avoid 0 in weights.
+2.1.4 Avoid including 0 in the weights.
 
 
 2.2 Check the model.
 --------------------
 
-2.2.1 The resonaces mass should be valid, for example in the mass range (m1+m2, m0-m3), out of the threshold required for special options.
+2.2.1 The resonances mass should be valid, for example in the mass range (m1+m2, m0-m3), out of the threshold required for special options.
 
 3. NaN value when getting params error.
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
   ::
 
-      numpy.linalg.LinAlgError: Array must not contain infs or NaN.
+      numpy.linalg.LinAlgError: Arrays must not contain infs or NaN.
 
 3.1 Similar as sec 2.2.
 
@@ -66,15 +66,15 @@ There is a script (scripts/check_nan.py) to check it.
 
 4.1 Free parameters are not used in the model.
 
-4.2 Used numpy for calculation of variable. The calculation have to be done in get_amp with TensorFlow.
+4.2 Used numpy for calculation of variable. The calculations have to be done in get_amp with TensorFlow.
 
   .. code::
 
     ...
       def init_params(self):
          self.a = self.add_var("a")
       def get_amp(self, data, *args, **kwargs):
-         # avoid use numpy for varible as
+         # avoid using numpy for variable as
          a = np.sin(self.a())
          # use tensorflow instead
          a = tf.sin(self.a())
@@ -100,7 +100,7 @@ There is a script (scripts/check_nan.py) to check it.
      data:
         lazy_call: True
 
-5.1.3 Try to use small data sample, or simple cases (less final particles).
+5.1.3 Try to use a small data sample, or simpler cases (less final particles).
 
 5.1.4 Some special models require large memory (such as an interpolation model), try another model.
 
@@ -134,18 +134,18 @@ Check the yaml file (see https://yaml.org): the indent, speical chars :code:`,:}
 
       AssertionError: not only one top particle
 
-The decay chain should be complete. All the item in decay should decay from initial to finals.
+The decay chain should be complete. All the item in decay chain should decay from initial to final state.
 
 
 6.3 Decay chain 2
 -----------------
 
   ::
 
-      RuntimeError: not decay chain available, check you config.yml
+      RuntimeError: not decay chain available, check your config.yml
 
 6.3.1 Similar as sec 6.2.
 
-6.3.2 Check the information in *remove decay chain*, see the reson why those decays are not available.
+6.3.2 Check the information in *remove decay chain*, see the reason why those decays are not available.
 
 *ls not available* means no possible LS combination allowed. Check the spin and parity. If parity is allowed to be violated, add :code:`p_break: True` to decay.

docs/developer.rst

@@ -1,21 +1,19 @@
-Setup for Developer Enveriment
-------------------------------
+Setup for Developer Environment
+-------------------------------
 
 .. note::
-   Before the developing, creating a standalone enveriment is recommanded (see https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-with-commands for more).
+   Before developing, creating a standalone environment is recommended (see https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-with-commands for more).
 
+The main steps are similar to the normal installation process; however, two additional steps are to be performed here.
 
-The main steps are similar to the normal installtion process, however two additonal steps are to be performed here.
-
-The first thing is writing tests, and testing your code.
+The first thing is writing tests and then testing your code.
 We use pytest (https://docs.pytest.org/en/stable/) framework for the same, it should be installed as well.
 
 .. code::
 
     conda install pytest pytest-cov pytest-benchmark
 
-
-The other thing is `pre-commit`. it is needed for developing.
+The other thing is `pre-commit`. It is needed for development.
 
 1. You can install `pre-commit` as
 
@@ -29,7 +27,7 @@ and
 
 .. code::
 
-    conda install pylint # local dependences
+    conda install pylint # local dependencies
     pre-commit install
 
 You can check if pre-commit is working well by running:
@@ -38,13 +36,13 @@ You can check if pre-commit is working well by running:
 
     pre-commit run -a
 
-It may take some time to install required package.
+It may take some time to install required packages.
 
 .. note::
    If there are some `GLIBC_XXX` errors at this step, you can try to install `node.js`.
 
 .. note::
-   For developer using editor with formatter, you should be careful about the options.
+   For developers using an editor with a formatter, you should be careful about the options.
 
 The following are all commands needed:
 

docs/install.rst

@@ -4,7 +4,7 @@ Install
 To use TFPWA, we need some dependent packages. There are two main ways,
 `conda` and `virtualenv` you can choose *one* of them. *Or* you can choose other method in :ref:`other-method`
 
-1. vitrual environment
+1. virtual environment
 ----------------------
 
 To avoid conflict of dependence, we recommed to use vitrual environment. there are two main vitrual environment for python packages,
@@ -64,7 +64,7 @@ and then you can install packages in the conda environment
 
    source ./tfpwa/bin/activate
 
-- 1.2.5 You can  exit the environment by
+- 1.2.5 You can exit the environment by
 
 .. code::
 
@@ -105,7 +105,7 @@ When using `virtualenv`, there is also simple way to install tensorflow2
 
 
 3. Other dependencies
---------------------
+---------------------
 
 Other dependencies of TFPWA is simple.
 
@@ -126,7 +126,7 @@ Get the packages using
 
 3.2.1 other dependencies
 
-In conda environment, go into the directory of `tf-pwa`, you can install the rest dependencies by
+In conda environment, go into the directory of `tf-pwa`, you can install rest of the dependencies by
 
 .. code::
 
@@ -166,7 +166,7 @@ Using `-e`, so it can be updated by `git pull` directly.
 
 
 4. (option)  Other dependencies.
--------------------------------
+--------------------------------
 
    There are some optional packages, such as `uproot` for reading root file.
 
@@ -209,7 +209,7 @@ command to install it.
    conda install tf-pwa
 
 5.2  pip
-````````
+``````````
 
 When using `pip`, you will need to install CUDA to use GPU. Just run the
 following command :