Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/adelks/csv_manager

Python CSV plotter with matplotlib + Latex
https://github.com/adelks/csv_manager

Last synced: 26 days ago
JSON representation

Python CSV plotter with matplotlib + Latex

Awesome Lists containing this project

README 

        
## csv_manager



This is a python module that features three simple classes for reading (class `Reader`), plotting (class `Plotter`, using Matplotlib with Latex rendering enabled) for the plots) and managing (class `Database`) CSV files and also a method for writing CSVs.



By using this module, the user avoids the cumbersome repetition of coding a csv reader using the `csv` python library then making the data in a readable structure for `plt.plot(...)`.



#### Simple single graph example



```python

from csv_manager import Plotter, DataFile

# Plotter inherits the class Reader



plotter = Plotter()

# Number of rows and columns for plt.sublots



datafile = DataFile('data_file_1.csv')



datafile.get_column_names('dataset1')

# returns the list of column names of the file `data_file_1.csv`



######################################################



plotter.plot(datafile, 'time', 'position', label='position $x(t)$', color='red', linestyle=':')

# Starting from " label='save' [...]" the arguments are the **kwargs in https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html

plotter.plot(datafile, 'time', 'speed', label='speed $v(t)$', color='blue', linestyle='--')



plotter.plot(datafile, 'time', 'position + sqrt(2/10 * speed)', 0, 1, label='dummy curve from expression')

# Mathematical expressions involving column names can be used



plotter.plot_data([0, 1, 2], [0, 1, 2], label='dummy data')



plotter.set(xlabel='Time ', ylabel='Position')

# the options that can be set are the **kwargs in https://matplotlib.org/api/axes_api.html



plotter.show()

```



The file `data_file_1.csv` can be the followin (Note that the default column separator is a single space):



```csv

time position speed

0 0 0

1 5 3

2 20 3.6

3 45 2

4 80 5

5 125 8

6 180 9

7 245 10

8 320 9.2

9 405 8

10 500 7

```



#### Using `Database`



If you have a folder with lots of CSV files and find it too cumbersome to find the correct ones to plot or read. The class `Databse` is made for you!



Requirements:

- Have all your CSV files in a folder (still works if they are in a subfolder of that folder)

- One of the following (or both):

    - Follow a specific naming scheme on your CSV files: `filename|var1=val1|var2=val2|...|varN=valN.csv` where `|` is a separator that can be different (any string of characters).

    - Have `sim_setting_name` and `sim_setting_value` columns in your datafile (names can be changed), that contains the variables that define the simulation settings, _e.g._:

        ```

        time speed sim_setting_name sim_setting_value

        0 1 wind_speed 2.4

        1 2 temp 25

        2 4

        3 5

        ...

        ```



##### Filtering



Then, what you can do is to create a `Database` instance with the folder path, and then you can use its method `filter_datafiles`:



```python

def filter_datafiles(self, file_name_base: str, filter_dict : dict) -> List[DataFile]:

```

where:

- `file_name_base` is a string that the file should contain in its filename (the text before the start of the variable definitions)

- `filter_dict` is a dictionary that contains `(key, val)` pairs, both strings, that correspond to `varN=valN` in the csv files you are looking for.



And this method will return all the files that match your filters. The retrieve a single datafile interactively, you can use the `file_selection_prompt` method from `Database`.



## Dependencies:



- Python Matplotlib

- Python [py_expression_eval](https://github.com/Axiacore/py-expression-eval), can be installed with `pip install py_expression_eval`

- Latex distribution installed in your computer, can be deactivated in csv_plotter.py by changing the following line `plt.rcParams['text.usetex'] = True` to `plt.rcParams['text.usetex'] = False`