Interactive Terminal Utilities
Project description
Interactive Terminal Utilities
import itrm
This library offers several functions for visualizing data within the terminal. This project does not exist just because it is cool. It exists because it fills some needs which few other tools do. For many developers, engineers, and scientists, the terminal is where much of their time is spent. Having to switch contexts every time a plot is generated can be time consuming and annoying. Furthermore, most plotting tools have fairly limited analysis capabilities. They are great for generating final, beautiful figures, but not great at quickly inspecting and understanding the data. Also, if you are working with a remote server through SSH, visualizing the data with conventional tools can be very tedious: save the data to a file, transfer the data to a local machine, write a script just to read and plot the data, plot the data, repeat. This library lets you directly visualize and interact with the data, skipping all the tedium.
Example scripts using this library can be found here. If you would like to contribute, please submit an issue here.
Configuration
This library uses the following default configuration settings:
Setting | Default | Description |
---|---|---|
uni |
True |
flag to use Unicode characters |
ar |
0.47 |
aspect ratio of characters |
cmap |
spectrum |
color map |
bold |
True |
flag to use bold plot characters |
A configuration file called config.ini can be used to override those defaults in the following locations:
Platform | Location |
---|---|
Windows | C:\Users\{username}\AppData\Local\itrm\config.ini |
macOS | ~/.config/itrm/config.ini |
(or) | ~/Library/Application Support/itrm/config.ini |
Linux | ~/.config/itrm/config.ini |
The config file should have the following format:
[render]
uni = True
ar = 0.47
cmap = "spectrum"
bold = True
You can also define an environment variable called ITRM_CONFIG_PATH
to
redirect itrm to look for a configration file there. Finally, you can also
directly modify the configuration parameters in your Python script (e.g.,
itrm.Config.uni = False
).
Unicode
Much of the plotting in the terminal performed by itrm
relies on Unicode
characters. However, properly displaying those characters requires having a
monospace font with those specific glyphs defined. In fact, the default plotting
mode relies on braille characters, and relatively few fonts define those. If you
are looking for a good terminal font which supports all the Unicode used by this
library, try out JuliaMono. However, you might not be interested in
downloading fonts, so this library can also forego all Unicode characters and
only rely on ASCII characters. This is the purpose of the uni
configuration.
Aspect Ratio
Because all the plotting by this library uses text, the aspect ratio (ratio of
width to height) of the characters affects the apparent aspect ratio of curves.
So, a circle might look perfectly round or squashed depending on the font
chosen. This does not mean you need a new font, you just need to adjust the
aspect ratio, ar
, configuration setting.
Color Map
By default, the color map used is spectrum
. Setting the cmap
parameter, you
can pick any of the following color maps:
Name | Description |
---|---|
spectrum | rainbow colors from blue to magenta |
viridis | yellow to green to violet |
grays | shades of gray from light to dark |
reds | shades of red from light to dark |
greens | shades of green from light to dark |
blues | shades of blue from light to dark |
4bit | terminal-defined blue to magenta |
All but the last color map use platform-independent, 8-bit colors. The last
color map, 4bit
, lets you control the colors with your terminal settings
instead. Each color map is a set of six distinct colors. When more than six
curves are shown in one plot, the colors will recycle.
Interactive Plots
itrm.iplot(x, y=None, label=None, rows=1, cols=1,
lg=None, overlay=False, cmap=None, uni=None)
This function will create an interactive plot with a cursor. The cursor is used to pan, zoom, and identify values in the plot.
Parameters
X and Y Data
The iplot
function will render all the data points defined by x
and y
to
the terminal. The inputs x
and y
can be vectors, matrices, or lists of such
arrays. Each row of a matrix is treated as a separate curve. Note, this is
different from MatPlotLib, in which each column is treated as a separate row.
(This difference is intentional, as in the author's opinion varying time along
columns means each column in a matrix can be treated as a vector. This
arrangement works very well in linear algebra, especially matrix multiplication
with a "set" of vectors over time.)
The shapes of x
and y
do not have to be the same, but they must be
compatible. So, x
could be a vector and y
could be a matrix as long as the
length of x
equals the number of columns of y
.
If only x
is given, it will be interpreted as the y
values, and the x
values will be an array of indices equal in length to y
.
Labels
If a label
is given, this will be printed in the bottom right of the plot box.
It can also be a list of strings. If the length of the list is the same as the
number of data sets (each row of a matrix is a different data set), then each
string in the list will be displayed with the respective data set. If the length
of the list is one greater, the first string will be displayed for the whole
plot.
Size
The rows
and cols
parameters let you specify the number of terminal text
rows and columns to use for the plot, respectively. For each of these, if the
value is less than or equal to 1, it represents a portion of the available space
to use. For example, if rows
is 0.5
, then half the number of rows of the
current terminal window will be used for the plot. If the value is greater than
1, it represents the absolute number of rows or columns to use. Also, if the
size of the current terminal cannot be obtained, the available space will
default to predefined, fixed values: 60 columns by 20 rows.
Log Scale
You can set the x or y axes to logarithmic scaling by setting the lg
parameter
to one of "x"
, "y"
, or "xy"
. Note that the values reported for the view
and the cursor will be in the original scaling, not logarithmic.
Overlay
To prevent your terminal history from extending each time a new plot is
rendered, you can print a new plot over a previous plot by setting the overlay
parameter to True
. This can be especially useful when there are multiple plots
to render (like for an animation) but you do not want your terminal history to
fill up quickly.
Color Map
For an individual plot, you can override the color map defined in
itrm.Config.cmap
by setting the cmap
parameter in the function call.
Unicode
For an individual plot, you can override the setting to use or not use Unicode
characters defined in itrm.Config.uni
by setting the uni
parameter in the
function call.
Information Bar
At the bottom of the plot, as part of the border, various information sets are listed:
- View
X:
range of the x axis within viewY:
range of the y axis within view
- Cursor
n:
index of the value the cursor is currently centered on. This is visible only when a specific data set is selected.x:
x-axis value corresponding to the current location of the cursor.y:
y-axis value or range of values corresponding to the current location of the cursor.
- Metrics (only visible when a ghost cursor exists)
Δn:
difference of indices between ghost cursor and current cursor. This is visible only when a specific data set is selected.Δx:
difference of x values between ghost cursor and current cursor.Δy:
difference of y values between ghost cursor and current cursor. This is visible only when a specific data set is selected.μ:
mean of y values from ghost cursor to current cursor. This is visible only when a specific data set is selected.σ:
standard deviation of y values from ghost cursor to current cursor. This is visible only when a specific data set is selected.
- Label
When not all of these information sets will fit in the currently available width
of the plot, they will be separated into different groups. You can cycle through
these groups by pressing the m
or M
key.
Keybindings
The iplot
function provides interactivity through a vertical cursor. You can
move the cursor left and right, at normal speed or fast speed. You can zoom in
and out. And, you can cycle through which rows of the x
and y
data to focus
on. Note, iplot
is designed for monotonically-increasing x
values, and,
consequently, does not support equal axis scaling.
The following table details the shortcut keys:
Keys | Function | Keys | Function | |
---|---|---|---|---|
q , ⌫ , ↵ |
exit interactive plot | j , s , ↓ |
zoom in | |
h , a , ← |
move cursor left | k , w , ↑ |
zoom out | |
l , d , → |
move cursor right | J , S , ⇧↓ |
zoom in fast | |
H , A , ⇧← |
move cursor left fast | K , W , ⇧↑ |
zoom out fast | |
L , D , ⇧→ |
move cursor right fast | n |
select next data set | |
g |
move cursor to start | N , p |
select previous data set | |
G |
move cursor to end | m |
next info set | |
c , z |
center view on cursor | M |
previous info set | |
x |
toggle x log scaling | v |
toggle ghost cursor | |
y |
toggle y log scaling | f |
start function | |
i |
toggle individual view | F |
restore original data |
Note that in Windows terminal emulators, there is no support for shift-arrow keys. Instead, use alt-arrow keys.
Individual Data Sets
When many data sets are being plotted simultaneously, it can be helpful to hide
all other data sets with the i
key in order to isolate just the selected data
set.
Ghost Cursor
If you want to make a comparison between two points, you can use the ghost
cursor. First, position the cursor at the start position. Then, press the v
key. Immediately, you should see in the information bar at the bottom several
metrics (only the Δx
metric if the cursor is white and there are multiple data
sets). These metrics are detailed in the Information Bar section above. Moving
the cursor will leave behind a ghost. As the cursor moves, the metrics will
update to reflect the range of values from the ghost cursor to the current
cursor.
Functions
Without writing any code, you can run a number of functions on the data and see
the results. First, press the f
key. Then, follow that with other keys to get
the specific function applied to the data. The following table shows the full
key sequences:
Keys | Description |
---|---|
fab |
Get the absolute value of y-axis values |
fac |
Get the autocorrelation of the data |
fav |
Get the Allan variance of the data |
fd |
Differentiate data |
ff |
Get the FFT of the data |
fi |
Integrate data |
fn |
Show data as finite or non-finite |
ftl |
Trim left |
ftr |
Trim right |
fu |
Show only unique points (to 9th decimal place) |
f#a |
Apply weighted moving average of width # |
f#d |
De-trend data with polynomial of degree # |
f#l |
Apply 2nd-order, low-pass filter at frequency # |
f#p |
Get the y-axis value to the power of # |
f#s |
Apply simple moving average of width # |
f#u |
Show only unique points (to #th decimal place) |
(Other functions are planned for the future.) When one of the functions has been
applied, the sides of the plotting box will turn gray to signal that the data
has been altered. You can restore the original data by pressing the F
key.
Plots
itrm.plot(x, y=None, label=None, rows=1, cols=1,
ea=False, lg=None, overlay=False, cmap=None, uni=None)
The plot
function is a non-interactive version of the iplot
function. All of
the same parameters are provided, with the addition of the equal-axes (ea
)
parameter, which enables plotting things like circles without them rendering as
ellipses. This function does not require monotonicity of the x-axis data.
Single curve | Multiple curves |
---|---|
Bars
itrm.bars(x, labels=None, cols=1, uni=None)
It can be convenient to plot a simple bar graph. The x
input is the vector of
values. The labels
input is a list of strings corresponding to the labels to
print before the bar of each value in x
. If the cols
input is greater than
1, it is the total width of characters including the labels. If it is less than
or equal to 1, it is the portion of the terminal window width which will be used
for the graph. The uni
parameter allows you to override the default
configuration setting for using Unicode characters.
Heat maps
itrm.heat(matrix, uni=None)
The heat
function will generate a heat map of the matrix
input using 24
shades of gray. Black is used for the lowest value and white for the highest
value. The uni
parameter allows you to override the default setting for using
Unicode characters. If uni
is True
, half-block characters from the Unicode
table will be used. If it is False
, two spaces per element of the matrix will
be used (unless that would not fit the available width of the terminal window).
With Unicode | Without Unicode |
---|---|
Tables
itrm.table(matrix, head=None, left=None, width=10, sep=' ', uni=None)
You can print a nicely spaced table of the matrix
data. The head
and left
inputs are lists of header and left-most column labels, respectively, to print
around the matrix
. The uni
parameter allows you to override the default
setting for using Unicode characters.
The width
parameter is the width in characters of each cell. The sep
parameter is the string separating columns of the body of the table.
Sparsity
itrm.spy(matrix, uni=None)
To view the sparsity of a matrix
, use the spy
function. The uni
parameter
allows you to override the default setting for using Unicode characters.
With Unicode | Without Unicode |
---|---|
Progress bars
bar = itrm.Progress(K, cols=1, uni=None)
bar.update(k)
There are many progress bar libraries available for Python. But, many of them
seem to be extremely over-complicated. TQDM, for example, includes over 20
source files. The implementation of a progress bar in itrm
is a single class.
The k
input is the counter of whatever for loop the progress bar is reporting
on. The K
input is one greater than the largest possible value of k
, as in
for k in range(K)
. When the process is completed, the total elapsed time will
be displayed. If cols
is not provided, the full width of the current terminal
window will be used. The uni
parameter allows you to override the default
configuration setting for using Unicode characters.
Command-line Interface
You can directly call the itrm.iplot
function on a data set without even
writing a Python script or using the REPL:
python -m itrm data.bin
python -m itrm data.csv
python -m itrm data.txt
The first column in the data file will be treated as the x
axis data and all
subsequent columns will be treated as the y
data. You can specify the file
type with the -t
option, but itrm will automatically check the file extension
(bin
, csv
, or txt
) if you do not. For the binary file type, you can
specify the number of column with the -c
option, but if you do not specify
this, itrm will automatically try all possible integer factors of the length of
the data set and determine the most likely number of columns. Binary files are
expected to be in double-precision, row-major format.
Installation
For instructions on using pip, visit https://pip.pypa.io/en/stable/getting-started/.
pip install itrm
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