ocbe-uio / trajpy Goto Github PK

./home/runner/work/trajpy/trajpy/trajpy/traj_generator.py:127:
DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future.
Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
y[i_step, i_sample] = sub_y[-1]

Affected code:

Implement default parameters for opening csv files in order to make it easier.

params = { 'skip_header':1, 'delimiter':',' }

Scikit-learn is only used for fitting the mean squared displacements (MSD) in order to obtain the anomalous exponent. This is easily replaced by scipy.stats.linregress (OLS) or by a custom function. This is important to keep the project maintainability high with fewer external dependencies.

This function should be removed:

Shall not forget to remove every reference to the function from tests and compute_features().

When processing several trajectories, show the progress status.

Simple: write "n/len(trajectories)" in the text box.
Advanced: implement a progress bar.

• Rename the "Open" button to "Open file" and create "Open directory" button
• Add an argument to action "get_file" that distinguishes if we are opening file or directory
• Add partial(self.get_file, file_or_dir) to find_bt and to the new button find_dir_bt
• Write a function to process the csv files in the directory path.

Previously I left dependencies only required to run the GUI out of the requirements list because the main intended usage for trajpy was via scripting. However, as the GUI matured and is minimally functional I think it makes sense to deliver the GUI as the main method for using the package.

The packages ttkthemes and Pillow are required to run the GUI and are not listed in requirements.txt.

ttkthemes>=2.4.0
Pillow>=8.1.0

We should write in the documentation how to generate the synthetic data and refer to the dataset available at https://zenodo.cern.ch/record/3627650 .

The calculation of the diffusion coefficient should be moved to a new @staticmethod (see bellow).
https://github.com/phydev/trajpy/blob/562415b0f35976c726df7fc8daa773dacca7fb2c/trajpy/trajpy.py#L74

@staticmethod
def diffusivity_(msd, timelag, ndim):
    """"
        :param msd: ensemble averaged mean squared displacement
        :param timelag: time-lag
        :param ndim: number of dimensions
        :return diffusivity: short-time diffusion coefficient D 
    """"
    diffusivity = Trajectory.anomalous_exponent_(msd[:10], timelag[:10]) / (2*n)
    return diffusivity

When we started coding TrajPy we only thought about processing spatial trajectories like $\vec{r}(t)$ with $\vec{r} = (x,y,z)$. However, we are also interested on providing a tool that can be applied to abstract trajectory spaces, such as blood pressure (BP) over time, where the temporal component should be processed as part of the trajectory.

Therefore, the early implementation for initialising Trajectory() where time is stored in the variable Trajectory()._t is not a good design approach for user experience. We need to deprecate this variable and store all components of the trajectory in Trajectory()._r

Considerations for the back-end:

1. If only 2 dimensions are provided, the code will assume that time must be processed together with the abstract dimension $x$
2. If 3 or more dimensions are provided as input, then the time component should not be used for computing the trajectory features
3. This is likely to break previous tests and examples, careful implementation is required.

Variables in Portuguese in the file trajpy.py should be translated to English: poder, limite, etc...

There is not a single comment in this file. Please add at least one small description for each function and comments about the input and output.

Currently the class trajpy accepts either a csv file or a numpy array for initialising the object. However, we can improve this by implementing a parser with functools.singledispatch.

Since trajpy's aims to be a general framework for trajectory analysis, it is critical to put more work on the parser for providing broad support for different file formats. singledispatch offers an elegant way for this implementation.

A parser for different file formats is needed, especially for processing csv files that contain several trajectories.

.xyz file

Nparticles [integer]
comment [character]
X Y Z [repeat Nparticles]
[repeat Nframes] 

CSV with several trajectories - format definition

The csv should contain 5 columns: time t, 3 spatial (x, y, z) components and the trajectory identifier id.

LAMMPS data file format

Large-scale Atomic/Molecular Massively Parallel Simulator is a molecular dynamics program from Sandia National Laboratories.

More details about the file format: https://docs.lammps.org/read_data.html

The LAMMPS data dump file format is written in yaml with the following structure:

---
creator: LAMMPS
timestep: 0
units: lj
time: 0
natoms: 3
boundary: [ p, p, p, p, p, p, ]
thermo:
  - keywords: [ Step, Temp, E_pair, E_mol, TotEng, Press, ]
  - data: [ 0, 0, -27093.472213010766, 0, 0, 0, ]
box:
  - [ 0, 16.795961913825074 ]
  - [ 0, 16.795961913825074 ]
  - [ 0, 16.795961913825074 ]
  - [ 0, 0, 0 ]
keywords: [ id, type, x, y, z, vx, vy, vz, ix, iy, iz,  ]
data:
  - [     1 , 1 ,  0.000000e+00 ,  0.000000e+00 ,  0.000000e+00 ,  -1.841579e-01 , -9.710036e-01 , -2.934617e+00 , 0 , 0 , 0, ]
  - [     2 , 1 ,  8.397981e-01 ,  8.397981e-01 ,  0.000000e+00 ,  -1.799591e+00 ,  2.127197e+00 ,  2.298572e+00 , 0 , 0 , 0, ]
  - [     3 , 1 ,  8.397981e-01 ,  0.000000e+00 ,  8.397981e-01 ,  -1.807682e+00 , -9.585130e-01 ,  1.605884e+00 , 0 , 0 , 0, ]
---
timestep: 100
...
---

A parser for this file format is straightforward with yaml.load_all() function.

Protein Data Bank (PDB) format

Standard file format for protein structures containing several atoms each file at different time steps. Each pdb file can contain a screenshot of the system or several trajectories, so we need to process several pdb files at once to extract trajectories.

A possible workflow would be:

1. Read each pdb file and extract the trajectories per atom
2. Write a CSV file using the format (y, x, y, z, id), where id is the atom identifier.
3. Use the CSV file to compute the features using trajpy

More information about pdb file format: https://en.wikipedia.org/wiki/Protein_Data_Bank_(file_format)

Currently we have a plotting feature in the GUI. This feature is unnecessary and increase the number of dependencies.

Code that should be removed:

• in trajpy/gui.py
  

  trajpy/trajpy/gui.py

  Lines 6 to 10 in 2b74234

  	from matplotlib.backends.backend_tkagg import (
  	FigureCanvasTkAgg, NavigationToolbar2Tk)
  	# Implement the default Matplotlib key bindings.
  	from matplotlib.backend_bases import key_press_handler
  	from matplotlib.figure import Figure

  
  

  trajpy/trajpy/gui.py

  Line 34 in 2b74234

  self.plot_bt = tk.Button(self.app, text="Plot", command=self.show_plot)

  
  

  trajpy/trajpy/gui.py

  Line 110 in 2b74234

  self.plot_bt.place(x=440, y=130)

  
  

  trajpy/trajpy/gui.py

  Lines 266 to 271 in 2b74234

  	def show_plot(self) -> None:
  	self._fig = Figure(figsize=(3, 3), dpi=100)
  	self._canvas = FigureCanvasTkAgg(self._fig, master=self.app)
  	self._fig.add_subplot(111).plot(self.r._t, self.r._r, ls='-.')
  	self._canvas.draw()
  	self._canvas.get_tk_widget().place(x=200, y=200)

• in requirements.txt
  

  trajpy/requirements.txt

  Line 3 in 2b74234

  matplotlib >= 3.3.2

After removal we should organise the GUI buttons in a better way. We can reduce the windows size and increase text size for improved accessibility.

Write documentation about the supported file formats.

1. Add how to open the GUI:

python3 -m trajpy.gui

2. Make a screen recording tutorial.

The eigen values must be ordered by descending order (eigen[0] > eigen[1] > eigen[2]), otherwise the values for anisotropy and asymmetry are not computed correctly.

Just a friendly post-meeting reminder to address this. 😃

• Change repo URL at TravisCI from phydev/trajpy to ocbe-uio/trajpy
• Adjust README.md badge accordingly

Rewrite the function compute_features() with the possibility to pass a list of features to be computed.

def compute_features(self, features_list):

travis-ci is not working due to some change of policies regarding free plans. Therefore we should implement a github actions workflow to test, build and deploy.

The following new features need to be included in the GUI:

• velocity
• velocity description
  • mean, median, mode, standard deviation, variance, range, kurtosis, skewness
• frequency spectrum

I've made a mess in the latest commit. The equations in the docstrings must be fixed.

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The bot created this issue to inform you that pyup.io has been set up on this repo.
Once you have closed it, the bot will open pull requests for updates as soon as they are available.

Type hints improve documentation, usability and maintainability. We should use this feature whenever possible.

Python documentation:
https://docs.python.org/3/library/typing.html

Fix the docs modindex.

The functions are wrongly defined and they must be switched:
msd_ensemble_averaged <-> msd_time_averaged

There are several warnings that should be fixed with regards to PEP8 standard.

See deployment report:
https://github.com/ocbe-uio/trajpy/actions/runs/4413645266/jobs/7734356182#step:5:1

We should start using black.

Several new functions were implemented for object tracking and analysis of live animal trajectories.

We need to write unit tests for these functions.