Merge pull request #151 from amishgog/changes_branch

Corrected english mistakes in documentation files

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 beacuse of the precision.
+1.1 If all absulute values are small. it is acceptable because of the precision.
 
-1.2 If some absulte 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
 
@@ -28,34 +28,34 @@ Check the jac value,
 2.1 Check the data.
 -------------------
 
-There a script (scripts/check_nan.py) to check it.
+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 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.
 
-3.2 Bad fit parameters: too wide width or two narrow width, reach the boundary and so on.
+3.2 Bad fit parameters: width too narrow or wide, reach the boundary and so on.
 
-3.3 Bad gradients. No gradients or the gradients is not corret for fit paramters.
+3.3 Bad gradients. No gradients or the gradients are not correct for fit paramters.
 
 4. Singular Matrix when getting params error
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -64,17 +64,17 @@ There a script (scripts/check_nan.py) to check it.
 
       numpy.linalg.LinAlgError: Singular matrix
 
-4.1 Free paramters are not used in model.
+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())
@@ -100,9 +100,9 @@ There 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 speical model required large memory (such as interpolation model), try other model.
+5.1.4 Some special models require large memory (such as an interpolation model), try another model.
 
 5.2 CPU
 -------------------
@@ -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 aviable, 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 aviable.
+6.3.2 Check the information in *remove decay chain*, see the reason why those decays are not available.
 
-*ls not aviable* means no possible LS combination allowed. Check the spin and parity. If allow parity voilate, add :code:`p_break: True` to decay.
+*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/amplitude.rst

@@ -6,7 +6,7 @@ Amplitude
 Helicity Formula
 ________________
 
-Each Decay has Amplitude like
+Each Decay has Amplitude defined like:
 
 .. math::
     A^{A \rightarrow B+C}_{\lambda_{A},\lambda_{B},\lambda_{C}} = H_{\lambda_{B},\lambda_{C}}^{A \rightarrow B+C} D^{J_{A}\star}_{\lambda_{A},\lambda_{B}-\lambda_{C}}(\phi,\theta,0)

docs/custom_model.rst

@@ -57,7 +57,7 @@ We can also add parameters in the `.Model` ``init_params`` using ``self.add_var(
            return tf.complex( m + self.a(), zeros)
 
 Then a parameters ``{particle_name}_a`` will appear in the parameters, we use ``self.a()`` to get the value in ``get_amp``.
-Note, the type of return value should be ``tf.complex``. All builtin model is located in ``tf_pwa/amp.py``.
+Note, the type of return value should be ``tf.complex``. All built in models are located in ``tf_pwa/amp.py``.
 
 
 
@@ -75,9 +75,9 @@ There is a simple method to define Resonance model, like
    def r_line(m, a: FloatParams = 1.0):
        return m + a
 
-Those code will build a class similar as Line model define before.
+Those code will build a class similar as Line model defined before.
 By using `inspect` module, we can get the `FullArgSpec` of a function.
-For a keyword arguments with type annotation as `FloatParams`, it will be treated as a fit paraments.
+For a keyword arguments with type annotation as `FloatParams`, it will be treated as a fit parameter.
 
 .. note::
     the first arguments have to be the invariant mass `m` of the resonance.

docs/decay_topology.rst

@@ -59,5 +59,5 @@ there are the three possible decay chains of A -> B,C,D ::
 
 the process is unique for different final particles
 
-Each inserting process delete a line and add three new line,
+Each process inserted, deletes a line and adds three new lines.
 So for decay process has :math:`n` final particles, there are :math:`(2n-3)!!` possible decay topology.

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 as normal install, only two extra things need to be done.
-
-The first things is writing tests, and tests your code.
-We use pytest (https://docs.pytest.org/en/stable/) framework, You should install it.
+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 things is `pre-commit`. it need for developing.
+The other thing is `pre-commit`. It is needed for development.
 
 1. You can install `pre-commit` as
 
@@ -29,24 +27,24 @@ 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
+You can check if pre-commit is working well by running:
 
 .. code::
 
     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 for the options.
+   For developers using an editor with a formatter, you should be careful about the options.
 
-The following are all commands needed
+The following are all commands needed:
 
 .. code::
 

docs/index.rst

@@ -20,7 +20,7 @@ A detailed configuration file sample (with all usable parameters) can be found *
    amplitude
    custom_model
    decay_topology
-   resonacnes_params
+   resonances_params
    phasespace
    resolution
    auto_examples/index
@@ -66,7 +66,7 @@ and then fit the data.
 
 Fitting is the major part of an analysis, and it could also be the most time-consuming part.
 For this example (the complexity of the amplitude expression matters a lot), the time for fitting is about xxx (running on xxxGPU).
-Then we can step further to complete the analysis, like calculating the fit fractions.
+Then we can go one step ahead to complete the analysis, and calculate the fit fractions.
 
 .. code-block:: python
 

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,
@@ -62,9 +62,9 @@ and then you can install packages in the conda environment
 
 .. code::
 
-   source ./tfpwa/bin/activete
+   source ./tfpwa/bin/activate
 
-- 1.2.5 You can  exit the environment by
+- 1.2.5 You can exit the environment by
 
 .. code::
 
@@ -104,10 +104,10 @@ When using `virtualenv`, there is also simple way to install tensorflow2
    You can use `-i https://pypi.tuna.tsinghua.edu.cn/simple` option to use pypi mirror site.
 
 
-3. Other dependences
---------------------
+3. Other dependencies
+---------------------
 
-Other dependences of TFPWA is simple.
+Other dependencies of TFPWA is simple.
 
 
 3.1 Get TFPWA package
@@ -124,16 +124,16 @@ Get the packages using
 3.2 conda
 `````````
 
-3.2.1 other dependences
+3.2.1 other dependencies
 
-In conda environment, go into the directory of `tf-pwa`, you can install the rest dependences by
+In conda environment, go into the directory of `tf-pwa`, you can install rest of the dependencies by
 
 .. code::
 
    conda install --file requirements-min.txt
 
 .. note::
-   we recommed Ampere card users to install with
+   we recommend Ampere card users to install with
    `tensorflow_2_6_requirements.txt` (see this
    `technical FAQ <https://tf-pwa.readthedocs.io/en/latest/tensorflow_version.html>`_).
 
@@ -156,7 +156,7 @@ Using `-e`, so it can be updated by `git pull` directly.
 3.3 virtualenv
 ``````````````
 
-In virtualenv, You can install dependences and TFPWA together.
+In virtualenv, You can install dependencies and TFPWA together.
 
 .. code::
 
@@ -165,10 +165,10 @@ In virtualenv, You can install dependences and TFPWA together.
 Using `-e`, so it can be updated by `git pull` directly.
 
 
-4. (option)  Other dependences.
--------------------------------
+4. (option)  Other dependencies.
+--------------------------------
 
-   There are some option packages, such as `uproot` for reading root file.
+   There are some optional packages, such as `uproot` for reading root file.
 
 4.1 conda
 `````````
@@ -200,7 +200,7 @@ We also provided other install method.
 5.1 conda channel (experimental)
 ````````````````````````````````
 
-A pre-built conda package (Linux only) is also provided, just run following
+A pre-built conda package (Linux only) is also provided, just run the following
 command to install it.
 
 .. code::
@@ -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 :

docs/phasespace.rst

@@ -19,7 +19,7 @@ by using the property of :math:`\delta`-function,
 
 where :math:`x_i` is the root of :math:`f(x)=0`.
 
-Phase space has the follow chain rule,
+Phase space has the following chain rule,
 
 .. math::
    \mathrm{d} \Phi(P;p_1,\cdots,p_n) =& (2\pi)^4\delta^4(P - \sum {p_i}) \prod \frac{1}{2E_i}\frac{\mathrm{d}^3 \vec{p_i}}{(2\pi)^{3}}  \\
@@ -48,14 +48,14 @@ where :math:`\mathrm{d} \Omega = \mathrm{d}(\cos\theta)\mathrm{d}\varphi` and
    |\vec{p}| = \frac{\sqrt{(M^2 - (m_1 + m_2)^2)(M^2 -(m_1 - m_2)^2)}}{2M}
 
 
-The three body decay in the center mass frame :math:`P=(M,0,0,0),q^\star=(m_{23},0,0,0)`,
+The three body decay in the center of mass frame :math:`P=(M,0,0,0),q^\star=(m_{23},0,0,0)`,
 
 .. math::
    \mathrm{d} \Phi(P;p_1,p_2,p_3) =& \mathrm{d}\Phi(P;p_1,q) \mathrm{d}\Phi(q^\star;p_2^\star,p_3^\star) \frac{\mathrm{d} q^2}{2\pi} \\
    =& \frac{|\vec{p_1}||\vec{p_2^\star}|}{(2\pi)^5 16 M m_{23}} \mathrm{d} m_{23}^2 \mathrm{d} \Omega_1 \mathrm{d}\Omega_2^\star \\
    =& \frac{|\vec{p_1}||\vec{p_2^\star}|}{(2\pi)^5 8 M} \mathrm{d} m_{23} \mathrm{d} \Omega_1 \mathrm{d}\Omega_2^\star
 
-The n body decay in the center mass frame :math:`P=(M,0,0,0)`,
+The N body decay in the center of mass frame :math:`P=(M,0,0,0)`,
 
 .. math::
    \mathrm{d} \Phi(P;p_1,\cdots,p_n) =& \mathrm{d}\Phi(P;p_1,q_1)\prod_{i=1}^{n-2} \frac{\mathrm{d} q_{i}^2}{2\pi}\mathrm{d}\Phi(q_{i},p_{i+1},p_{i+2})\\
@@ -75,7 +75,7 @@ with those limit
 Phase Space Generator
 ---------------------
 
-For n body phase space
+For N body phase space
 
 .. math::
    \mathrm{d} \Phi(P;p_1,\cdots,p_n) =