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cytolysis-0.0.9b0
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مشاهده بیشترتوضیحات
An API to analyze cytosim simulations
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | cytolysis-0.0.9b0 |
| نام | cytolysis |
| نسخه کتابخانه | 0.0.9b0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Serge Dmitrieff |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | https://gitlab.com/SergeDmi/cytosim_analysis |
| آدرس اینترنتی | https://pypi.org/project/cytolysis/ |
| مجوز | - |
# Cytolysis
A python module to facilitate the automatic analysis cytosim simulations.
By itself, it does not include many analysis functions but mostly an API.
## Installation
```bash
pip3 install cytolysis
```
## Requirements
Requires Python3 and modules numpy, pandas.
To visualize the simulation in iPython (Jupyter Notebook),
you should install [ipyvolume](https://ipyvolume.readthedocs.io/en/latest/install.html) :
```bash
conda install -c conda-forge ipyvolume
```
## Practical examples
We provide several examples where we analyze the result of a simulation for an example [config file](example_data/example.cym).
This simulation has two asters of microtubules brought to the center by the rigidity of the microtubules and by the activity of dyneins.
An example counting the number of fiber points for each filament, and at each time:
```bash
python3 examples/example_fibers.py
```
An example where we compute the fiber bending energy as a function of time
```bash
python3 examples/example_fiber_curvature.py
```
We can also analyze any cytosim class that can be reported, by creating custom objects.
For example, this is done here for solids and spaces :
```bash
python3 examples/example_solid.py
```
Several ipython notebooks are also available in the notebook folder.
## Interface (examples)
Import the module :
```python
from cytolysis import cytosim_analysis as ana
```
The main class is *Simulation*, a list of time frames. Create an instance of a simulation analysis via :
```python
microtubule_reports={'points' : 'fiber_points.txt' }
simul = ana.Simulation(reports={'microtubule': microtubule_reports},
config='config.cym')
```
You can specify analysis functions for the different simulation objects, specifying by object name :
```python
def count_points(fiber):
return fiber.shape[0]
def count_fibers(frame):
return len(frame.fibers)
analyzer={}
analyzer['microtubule'] = {'pts_number': count_points}
analyzer['frame'] = {'fib_number': count_fibers}
```
You can then run the analysis :
```python
simul.make_analysis(analyzer=analyzer)
```
The analysis of objects is stored as pandas dataframes in the frames. For exemple, the analysis of microtubules for frame *5* is stored in :
```python
simul[5].analysis['microtubule']
```
Similarly, the analysis for couples 'arp_2_3' at frame 10 is stored in :
```python
simul[10].analysis['arp_2_3']
```
Simul is a set of frames, and the results of the analysis of all frames can be accessed in :
```python
simul.frames_analysis
```
While a global analysis of the simulation is available in :
```python
simul.analysis
```
The module contains a function to export analysis dataframes into csv files :
```python
ana.export_analysis(simul.frames_analysis, 'frames.csv')
```
There is also experimental support for showing the system in 3D in notebooks :
```python
simul.show(frame_number)
```
## Components
### Simulation
The class *Simulation* is a set of *frames*, instances of the class [Frame](#frame). Input arguments :
- reports : a dictionary of dictionaries of pathes to report files.
- options : a dictionary of dictionaries of options.
- config : path to the config file
- dim : dimensionality of the simulation (by default, 3)
Simulation has a method *make_analysis* to perform the analysis.
This takes as option *analyzer*, a dictionary of dictionaries of analysis functions.
*simulation.make_analysis* performs the analysis specified in *analyzer["simulation"]*,
and the result is stored in *simulation.analysis*.
As a set of frames , simulation implements *simulation.analyze(frame, analyzer=..., ... )* (see [Object_set](#object_set)).
This performs the analysis specified in *analyzer['frame']*. The results are stored in *simulation.frames_analysis*
### Frame
Each frame contains several types of dictionaries of object_sets.
Each dictionary is of the type : { name : [object_set](#object_set) }.
For instance, if fibers have been loaded, they are available in *frame.objects["fibers"]*.
Once the analysis has been performed, the analysis results are stored in :
- *frame.analysis[object_type]*, e.g. *frame.analysis["fibers"]*.
Frame implements the analysis method *frame.make_analysis(...)* that calls the *object_set.analyze(object, ...)* method of all object sets.
### Object_set
Object set is a class derived from list. *Fibers_set* and *Couples_set* are derived from *Object_set*. Input arguments :
- *name* : name of the object (e.g. "microtubule")
- *type* : type of the object (e.g. "fiber")
Optional input arguments :
- *config* : the pile read from the configuration file
- *build* : a function to build the object set from the reports
Beyond the initialization (*__init__*) method, object set need to implement the methods :
- *object_set.analyze(object, ... )* : a function that analyzes *object*, a given item from the object set
- *object_set.type* : object type
- *object_set.name* : object name
- *object_set.id* : object id (a number)
- *object_set.properties* : a dictionary of properties read from the config file
- *object_set.show* : a way to plot the object set in 3D using iPyVolume
### Analysis
All the analysis results (*simulation.analysis*, *frame.analysis["fibers"]*, etc.) are stored as Pandas dataframes
and, by default, exported as csv files. Examples:
- *frame.analysis["fiber"][fiber_name]* is a dataframe with as many rows as there are fibers.
- *simulation.frame_analysis* is a dataframe with as many rows as there are frames.
- *simulation.analysis* is a dataframe with a single row.
Therefore, if one wants to look at the distribution of some property among objects for a given frame,
one would export *frame.analysis[object_type][object_name]*.
If one wants to analyze something over time, one would export *simulation.frame_analysis*.
If one wants a single line to sumarize the simulation, for instance in order to compare different simulations, one would
export *simulation.analysis*.
### Plotting
When used in iPython, cytolysis can represent the system in 3D,
and allows to plot objects differently according to their properties,
see this [example](notebooks/display_examples.ipynb).
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy |
| - | pandas |
نحوه نصب
نصب پکیج whl cytolysis-0.0.9b0:
pip install cytolysis-0.0.9b0.whl
نصب پکیج tar.gz cytolysis-0.0.9b0:
pip install cytolysis-0.0.9b0.tar.gz