Utilities for plotting lines using matplotlib.
Available functions are
- New colormaps;
- Replacement for default fonts;
- Better-looking legends and ticks. Legend outside subplot;
- Labeling on subplots;
- Auto figure resizing by square subplots;
- Simple plotting from command line (
python -m lineutil);
Requirements:
Pandas
Numpy
Matplotlib
PRL style (serif fonts):
Nature style (sans-serif fonts):
Shell:
python -m lineutil -x [column_x] -y [column_y] [filename]
By defaults, the separator of file is any white characters (use --sep to change.) column_x and column_y may be integers (starting from 1) or string. column_y may also be slices ("1:5"). By default, column_x = 1, column_y = "2:".
Shell (line + scatter):
python -m lineutil -x [column_x] -y [column_y] -s 'pt=o' [filename]
Shell (plotting two contrast sets of data):
python -m lineutil -x [column_x] -y [column_y] -cm -cm "line.lighter" -s -s "linestyle=--" [file1] [file2]
Shell (plotting two data sequentially)
python -m lineutil -x [x_file1] -y [y_file1] -x [x_file2] -y [y_file2] --append [file1] [file2]
Script:
import lineutil
lineutil.preset_prl()
lineutil.set_prop_cycle() # Setting the line color loop
# normal plotting
...
lineutil.render_resized()
Script (plotting two contrast sets of data):
import lineutil
lineutil.preset_prl()
lineutil.set_prop_cycle()
# plotting dataset 1
...
lineutil.set_prop_cycle(colormap='line.lighter', linestyle='--')
# plotting dataset 2
...
lineutil.render_resized()
The leftmost one is reference color, and will not be enabled by default (unless use lineutil.set_prop_cycle(skip_header=False)).
