### Install Termplotlib

Source: https://github.com/nschloe/termplotlib/blob/main/README.md

Use this command to install the termplotlib library using pip.

```bash
pip install termplotlib
```

--------------------------------

### Get Gnuplot Version

Source: https://context7.com/nschloe/termplotlib/llms.txt

Retrieves the installed gnuplot version as a tuple of integers. Useful for checking compatibility or enabling version-specific features.

```python
import termplotlib as tpl

# Get gnuplot version
version = tpl.get_gnuplot_version()
print(version)  # e.g., (5, 4, 2)
```

--------------------------------

### Gnuplot Version Checking

Source: https://context7.com/nschloe/termplotlib/llms.txt

Demonstrates how to check the gnuplot version for conditional execution of code or feature availability. Handles potential RuntimeError if gnuplot is not installed.

```python
import termplotlib as tpl

# Version checking for features
major, minor, patch = tpl.get_gnuplot_version()
if (major, minor) >= (5, 4):
    print("Advanced features available")

# Use in conditional code
try:
    version = tpl.get_gnuplot_version()
    print(f"gnuplot {version[0]}.{version[1]} patchlevel {version[2]}")
except RuntimeError:
    print("gnuplot not installed or version not detected")
```

--------------------------------

### Create and Display a Line Plot

Source: https://github.com/nschloe/termplotlib/blob/main/README.md

Use this snippet to generate a line plot in the terminal. Requires numpy for data generation and gnuplot to be installed.

```python
import termplotlib as tpl
import numpy as np

x = np.linspace(0, 2 * np.pi, 10)
y = np.sin(x)

fig = tpl.figure()
fig.plot(x, y, label="data", width=50, height=15)
fig.show()
```

--------------------------------

### get_gnuplot_version

Source: https://context7.com/nschloe/termplotlib/llms.txt

Returns the installed gnuplot version as a tuple of integers.

```APIDOC
## get_gnuplot_version

### Description
Returns the installed gnuplot version as a tuple of integers (major, minor, patch) for version checking.

### Response
- **version** (tuple) - A tuple of integers representing the gnuplot version.
```

--------------------------------

### Get Plot as String

Source: https://context7.com/nschloe/termplotlib/llms.txt

Retrieves the rendered figure content as a string, without printing it directly. Useful for logging, testing, or file operations.

```python
import termplotlib as tpl
import numpy as np

# Get plot as string
fig = tpl.figure()
x = np.linspace(0, 2 * np.pi, 10)
y = np.sin(x)
fig.plot(x, y, width=50, height=15)

# Get string output
output = fig.get_string()
print(type(output))  # <class 'str'>
```

--------------------------------

### Get Plot String Preserving Whitespace

Source: https://context7.com/nschloe/termplotlib/llms.txt

Retrieves the figure content as a string, with an option to preserve trailing whitespace. This can be important for exact output matching or specific formatting needs.

```python
import termplotlib as tpl
import numpy as np

fig = tpl.figure()
x = np.linspace(0, 2 * np.pi, 10)
y = np.sin(x)
fig.plot(x, y, width=50, height=15)

# Option to preserve trailing whitespace
output_with_spaces = fig.get_string(remove_trailing_whitespace=False)
```

--------------------------------

### Histogram with All Options

Source: https://context7.com/nschloe/termplotlib/llms.txt

Demonstrates a vertical histogram with various customization options including bar width, max width, and strip mode. Requires pre-computed histogram data.

```python
import termplotlib as tpl

# Assuming counts and bin_edges are already computed from np.histogram
# counts, bin_edges = np.histogram(sample, bins=40)
fig = tpl.figure()
fig.hist(
    counts,                     # Pre-computed histogram counts
    bin_edges,                  # Bin edge values from np.histogram
    orientation="vertical",     # "vertical" or "horizontal"
    max_width=40,               # Max width for horizontal bars
    grid=[15, 25],              # Grid line positions for vertical
    bar_width=2,                # Width of each bar
    strip=True,                 # Remove leading/trailing empty rows
    force_ascii=False           # Use ASCII instead of Unicode
)
fig.show()
```

--------------------------------

### Create a basic figure

Source: https://context7.com/nschloe/termplotlib/llms.txt

Create a new Figure object, which is the main entry point for plotting operations. Figures can be created with default settings or with specified width and padding.

```python
import termplotlib as tpl
import numpy as np

# Create a basic figure
fig = tpl.figure()
```

```python
# Create a figure with fixed width and padding
fig = tpl.figure(width=80, padding=2)
```

```python
# Create figure, add content, and display
fig = tpl.figure()
x = np.linspace(0, 2 * np.pi, 10)
y = np.sin(x)
fig.plot(x, y, label="sine wave", width=50, height=15)
fig.show()
```

--------------------------------

### Run Unit Tests

Source: https://github.com/nschloe/termplotlib/blob/main/README.md

Execute the unit tests for termplotlib by running pytest in the repository directory.

```bash
pytest
```

--------------------------------

### Configure advanced horizontal bar chart options

Source: https://context7.com/nschloe/termplotlib/llms.txt

Create a horizontal bar chart with advanced customization, including maximum bar width, individual bar height, displaying values next to bars, custom value formatting, and forcing ASCII output.

```python
import termplotlib as tpl

# All barh options
fig = tpl.figure()
fig.barh(
    vals=[3, 10, 5, 2],         # Bar values
    labels=["A", "B", "C", "D"], # Optional labels
    max_width=40,               # Maximum bar width in characters
    bar_width=1,                # Height of each bar in lines
    show_vals=True,             # Display values next to bars
    val_format="{:5d}",         # Custom value format string
    force_ascii=False           # Use ASCII instead of Unicode
)
fig.show()
```

--------------------------------

### Create and display a line plot

Source: https://context7.com/nschloe/termplotlib/llms.txt

Generate a basic line plot using the plot() method. Ensure numpy is imported for data generation. The plot is displayed directly in the terminal.

```python
import termplotlib as tpl
import numpy as np

# Basic line plot
x = np.linspace(0, 2 * np.pi, 10)
y = np.sin(x)

fig = tpl.figure()
fig.plot(x, y, width=50, height=15)
fig.show()
```

--------------------------------

### Figure Creation

Source: https://context7.com/nschloe/termplotlib/llms.txt

The `figure()` function initializes a Figure object, which acts as a container for plots. It can be configured with specific dimensions and padding.

```APIDOC
## figure()

### Description
Creates a new Figure object that serves as a container for plots. The Figure class is the main entry point for all plotting operations.

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```python
import termplotlib as tpl

# Create a basic figure
fig = tpl.figure()

# Create a figure with fixed width and padding
fig = tpl.figure(width=80, padding=2)
```

### Response
#### Success Response (200)
Returns a Figure object.

#### Response Example
```python
# Figure object instance
<Figure object>
```
```

--------------------------------

### Create and Display a Horizontal Bar Chart

Source: https://github.com/nschloe/termplotlib/blob/main/README.md

Creates a horizontal bar chart with labels. `force_ascii=True` uses basic ASCII characters for plotting.

```python
import termplotlib as tpl

fig = tpl.figure()
fig.barh([3, 10, 5, 2], ["Cats", "Dogs", "Cows", "Geese"], force_ascii=True)
fig.show()
```

--------------------------------

### Log Plot String

Source: https://context7.com/nschloe/termplotlib/llms.txt

Shows how to log the string output of a plot using Python's logging module. This allows for capturing plot details in logs.

```python
import termplotlib as tpl
import numpy as np
import logging

fig = tpl.figure()
x = np.linspace(0, 2 * np.pi, 10)
y = np.sin(x)
fig.plot(x, y, width=50, height=15)

# Use in logging
logging.info(f"Plot output:\n{fig.get_string()}")
```

--------------------------------

### Create a basic horizontal bar chart

Source: https://context7.com/nschloe/termplotlib/llms.txt

Generate a basic horizontal bar chart with labels for each bar. The chart uses Unicode block characters by default for a higher-resolution display.

```python
import termplotlib as tpl

# Basic horizontal bar chart with labels
fig = tpl.figure()
fig.barh([3, 10, 5, 2], ["Cats", "Dogs", "Cows", "Geese"])
fig.show()
```

--------------------------------

### Create and Display a Horizontal Histogram

Source: https://github.com/nschloe/termplotlib/blob/main/README.md

Generates a horizontal histogram from sample data. Requires numpy for histogram calculation. `force_ascii=False` allows for more detailed character plotting.

```python
import termplotlib as tpl
import numpy as np

rng = np.random.default_rng(123)
sample = rng.standard_normal(size=1000)
counts, bin_edges = np.histogram(sample)

fig = tpl.figure()
fig.hist(counts, bin_edges, orientation="horizontal", force_ascii=False)
fig.show()
```

--------------------------------

### Create an ASCII horizontal bar chart

Source: https://context7.com/nschloe/termplotlib/llms.txt

Generate a horizontal bar chart using ASCII characters for compatibility with basic terminals. This is achieved by setting the `force_ascii` parameter to `True`.

```python
import termplotlib as tpl

# ASCII mode for basic terminal compatibility
fig = tpl.figure()
fig.barh([3, 10, 5, 2], ["Cats", "Dogs", "Cows", "Geese"], force_ascii=True)
fig.show()
```

--------------------------------

### Configure and display a detailed line plot

Source: https://context7.com/nschloe/termplotlib/llms.txt

Create a line plot with extensive customization options including legend labels, axis limits, axis labels, plot title, tick scale, and additional gnuplot arguments. The plot can be displayed or retrieved as a string.

```python
import termplotlib as tpl
import numpy as np

# Line plot with all options
fig = tpl.figure()
fig.plot(
    x, y,
    label="data",           # Legend label
    width=50,               # Plot width in characters
    height=15,              # Plot height in characters
    xlim=[-1, 7],           # X-axis limits as (min, max)
    ylim=[-1.5, 1.5],       # Y-axis limits as (min, max)
    xlabel="x values",      # X-axis label
    title="Sine Wave",      # Plot title
    ticks_scale=0,          # Tick mark scale
    extra_gnuplot_arguments=["set grid"]  # Additional gnuplot commands
)
fig.show()
```

```python
# Get plot as string instead of printing
string_output = fig.get_string()
```

--------------------------------

### Create a horizontal bar chart with float values

Source: https://context7.com/nschloe/termplotlib/llms.txt

Create a horizontal bar chart where the bar values are represented as floating-point numbers. The library automatically scales the bars based on these values.

```python
import termplotlib as tpl

# Bar chart with float values
fig = tpl.figure()
fig.barh([0.3, 0.4, 0.6, 0.2], ["Cats", "Dogs", "Cows", "Geese"])
fig.show()
```

--------------------------------

### Figure.get_string

Source: https://context7.com/nschloe/termplotlib/llms.txt

Returns the figure content as a string.

```APIDOC
## Figure.get_string

### Description
Returns the figure content as a string instead of printing, useful for logging, testing, or further processing.

### Parameters
#### Request Body
- **remove_trailing_whitespace** (boolean) - Optional - Whether to remove trailing whitespace from the output string.

### Response
- **output** (string) - The string representation of the figure.
```

--------------------------------

### Figure.hist

Source: https://context7.com/nschloe/termplotlib/llms.txt

Creates a histogram in the terminal using pre-computed counts and bin edges.

```APIDOC
## Figure.hist

### Description
Generates a vertical or horizontal histogram in the terminal.

### Parameters
#### Request Body
- **counts** (array) - Required - Pre-computed histogram counts.
- **bin_edges** (array) - Required - Bin edge values from np.histogram.
- **orientation** (string) - Optional - "vertical" or "horizontal".
- **max_width** (int) - Optional - Max width for horizontal bars.
- **grid** (list) - Optional - Grid line positions for vertical histograms.
- **bar_width** (int) - Optional - Width of each bar.
- **strip** (boolean) - Optional - Remove leading/trailing empty rows.
- **force_ascii** (boolean) - Optional - Use ASCII instead of Unicode.
```

--------------------------------

### Create and Display a Vertical Histogram

Source: https://github.com/nschloe/termplotlib/blob/main/README.md

Generates a vertical histogram with specified grid dimensions. Requires numpy for histogram calculation. `force_ascii=False` enables extended character plotting.

```python
import termplotlib as tpl
import numpy as np

rng = np.random.default_rng(123)
sample = rng.standard_normal(size=1000)
counts, bin_edges = np.histogram(sample, bins=40)
fig = tpl.figure()
fig.hist(counts, bin_edges, grid=[15, 25], force_ascii=False)
fig.show()
```

--------------------------------

### Write Plot String to File

Source: https://context7.com/nschloe/termplotlib/llms.txt

Demonstrates saving the string representation of a plot to a text file. Requires the figure content to be obtained using `get_string()`.

```python
import termplotlib as tpl
import numpy as np

fig = tpl.figure()
x = np.linspace(0, 2 * np.pi, 10)
y = np.sin(x)
fig.plot(x, y, width=50, height=15)

output = fig.get_string()
# Write to file
with open("plot.txt", "w") as f:
    f.write(output)
```

--------------------------------

### 1x2 Grid with Double Borders

Source: https://context7.com/nschloe/termplotlib/llms.txt

Creates a 1x2 subplot grid using the 'double' border style. The width parameter affects the overall size.

```python
import termplotlib as tpl

# Border style options: "thin", "thin rounded", "thick", "double", "ascii", None
grid = tpl.subplot_grid((1, 2), width=20, border_style="double")
grid[0, 0].aprint("Double")
grid[0, 1].aprint("Border")
grid.show()
```

--------------------------------

### Basic 1x2 Subplot Grid

Source: https://context7.com/nschloe/termplotlib/llms.txt

Creates a simple 1x2 grid layout and prints text into each cell. The width parameter controls the overall figure width.

```python
import termplotlib as tpl

# Basic 1x2 subplot grid
grid = tpl.subplot_grid((1, 2), width=20)
grid[0, 0].aprint("Left panel")
grid[0, 1].aprint("Right panel")
grid.show()
```

--------------------------------

### Figure.aprint

Source: https://context7.com/nschloe/termplotlib/llms.txt

Appends arbitrary text content to a figure.

```APIDOC
## Figure.aprint

### Description
Appends arbitrary text content to a figure, useful for adding custom labels or combining text with plots.

### Parameters
#### Request Body
- **text** (string) - Required - The text content to append to the figure.
```

--------------------------------

### Create a horizontal histogram

Source: https://context7.com/nschloe/termplotlib/llms.txt

Generate a horizontal histogram from pre-computed counts and bin edges. The `orientation` parameter defaults to 'horizontal'. Sample data can be generated using numpy.

```python
import termplotlib as tpl
import numpy as np

# Generate sample data
rng = np.random.default_rng(123)
sample = rng.standard_normal(size=1000)
counts, bin_edges = np.histogram(sample)

# Horizontal histogram (default bins=10)
fig = tpl.figure()
fig.hist(counts, bin_edges, orientation="horizontal")
fig.show()
```

--------------------------------

### 2x3 Grid with Thick Borders

Source: https://context7.com/nschloe/termplotlib/llms.txt

Constructs a 2x3 subplot grid with a 'thick' border style. Allows for multi-line text within cells.

```python
import termplotlib as tpl

# 2x3 grid with different border styles
grid = tpl.subplot_grid((2, 3), width=40, border_style="thick")
grid[0, 0].aprint("Cell 1")
grid[0, 1].aprint("Cell 2\nLine 2")
grid[0, 2].aprint("Cell 3")
grid[1, 0].aprint("Cell 4")
grid[1, 1].aprint("Cell 5")
grid[1, 2].aprint("Cell 6")
grid.show()
```

--------------------------------

### Subplot Grid with Custom Column Widths

Source: https://context7.com/nschloe/termplotlib/llms.txt

Configures a 1x3 subplot grid with explicitly defined widths for each column, allowing for varied cell sizes.

```python
import termplotlib as tpl

# Custom column widths
grid = tpl.subplot_grid((1, 3), column_widths=(30, 15, 20))
grid[0, 0].aprint("Wide column")
grid[0, 1].aprint("Medium")
grid[0, 2].aprint("Normal")
grid.show()
```

--------------------------------

### Vertical Histogram with Grid Lines

Source: https://context7.com/nschloe/termplotlib/llms.txt

Displays a vertical histogram with specified grid line positions. Assumes counts and bin_edges are pre-computed.

```python
import termplotlib as tpl

# Assuming counts and bin_edges are already computed from np.histogram
# counts, bin_edges = np.histogram(sample, bins=40)
fig = tpl.figure()
fig.hist(counts, bin_edges, grid=[15, 25])  # Grid at positions 15 and 25
fig.show()
```

--------------------------------

### Create an ASCII horizontal histogram

Source: https://context7.com/nschloe/termplotlib/llms.txt

Generate a horizontal histogram using ASCII characters by setting the `force_ascii` parameter to `True`. This ensures compatibility with terminals that do not support Unicode block characters.

```python
import termplotlib as tpl
import numpy as np

# Generate sample data
rng = np.random.default_rng(123)
sample = rng.standard_normal(size=1000)
counts, bin_edges = np.histogram(sample)

# Horizontal histogram with ASCII
fig = tpl.figure()
fig.hist(counts, bin_edges, orientation="horizontal", force_ascii=True)
fig.show()
```

--------------------------------

### Line Plotting with fig.plot

Source: https://context7.com/nschloe/termplotlib/llms.txt

The `plot()` method generates line plots using gnuplot. It allows customization of labels, axis limits, titles, and dimensions.

```APIDOC
## fig.plot()

### Description
Creates line plots using gnuplot. Supports labels, axis limits, titles, and custom dimensions.

### Method
`plot(x, y, **kwargs)`

### Endpoint
N/A (Method of a Figure object)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters (kwargs)
- **x** (array-like) - X-axis data points.
- **y** (array-like) - Y-axis data points.
- **label** (str, optional) - Legend label for the plot.
- **width** (int, optional) - Plot width in characters. Defaults to terminal width.
- **height** (int, optional) - Plot height in characters. Defaults to terminal height.
- **xlim** (tuple, optional) - X-axis limits as (min, max).
- **ylim** (tuple, optional) - Y-axis limits as (min, max).
- **xlabel** (str, optional) - X-axis label.
- **title** (str, optional) - Plot title.
- **ticks_scale** (int, optional) - Tick mark scale.
- **extra_gnuplot_arguments** (list of str, optional) - Additional gnuplot commands.

### Request Example
```python
import termplotlib as tpl
import numpy as np

x = np.linspace(0, 2 * np.pi, 10)
y = np.sin(x)

fig = tpl.figure()
fig.plot(x, y, label="sine wave", width=50, height=15)
fig.show()

# With all options:
fig.plot(
    x, y,
    label="data",
    width=50,
    height=15,
    xlim=[-1, 7],
    ylim=[-1.5, 1.5],
    xlabel="x values",
    title="Sine Wave",
    ticks_scale=0,
    extra_gnuplot_arguments=["set grid"]
)
fig.show()

# Get plot as string
string_output = fig.get_string()
```

### Response
#### Success Response (200)
Displays the plot in the terminal or returns a string representation if `get_string()` is used.

#### Response Example
```
# Terminal Output Example:
    1 +---------------------------------------+
  0.8 |    **     **                          |
  0.6 |   *         **      sine wave ******* |
  0.4 | **                                    |
  0.2 |*              **                      |
    0 |                 **                    |
      |                                   *   |
 -0.2 |                   **            **    |
 -0.4 |                     **         *      |
 -0.6 |                              **       |
 -0.8 |                       **** **         |
   -1 +---------------------------------------+
      0     1    2     3     4     5    6     7
```
```

--------------------------------

### Vertical Histogram with More Bins

Source: https://context7.com/nschloe/termplotlib/llms.txt

Generates a vertical histogram using pre-computed counts and bin edges. Requires numpy for histogram calculation.

```python
import numpy as np
import termplotlib as tpl

sample = np.random.randn(1000)
counts, bin_edges = np.histogram(sample, bins=40)
fig = tpl.figure()
fig.hist(counts, bin_edges, orientation="vertical")
fig.show()
```

--------------------------------

### subplot_grid

Source: https://context7.com/nschloe/termplotlib/llms.txt

Creates a grid layout for arranging multiple plots or text content.

```APIDOC
## subplot_grid

### Description
Creates a grid layout for arranging multiple plots or text content with customizable borders.

### Parameters
#### Request Body
- **shape** (tuple) - Required - Grid dimensions (rows, columns).
- **width** (int) - Optional - Total width of the grid.
- **border_style** (string) - Optional - Style of borders: "thin", "thin rounded", "thick", "double", "ascii", or None.
- **column_widths** (tuple) - Optional - Custom widths for each column.
```

--------------------------------

### Horizontal Bar Chart with fig.barh

Source: https://context7.com/nschloe/termplotlib/llms.txt

The `barh()` method generates horizontal bar charts. It supports labels, displaying values, and customizable bar dimensions, with an option to force ASCII output.

```APIDOC
## fig.barh()

### Description
Creates horizontal bar charts with optional labels, value display, and customizable width.

### Method
`barh(vals, labels=None, **kwargs)`

### Endpoint
N/A (Method of a Figure object)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters (kwargs)
- **vals** (list of numbers) - Bar values.
- **labels** (list of str, optional) - Optional labels for each bar.
- **max_width** (int, optional) - Maximum bar width in characters. Defaults to terminal width.
- **bar_width** (int, optional) - Height of each bar in lines. Defaults to 1.
- **show_vals** (bool, optional) - Display values next to bars. Defaults to False.
- **val_format** (str, optional) - Custom value format string (e.g., `"{:.2f}"`).
- **force_ascii** (bool, optional) - Use ASCII characters instead of Unicode. Defaults to False.

### Request Example
```python
import termplotlib as tpl

fig = tpl.figure()
fig.barh([3, 10, 5, 2], ["Cats", "Dogs", "Cows", "Geese"])
fig.show()

# ASCII mode:
fig.barh([3, 10, 5, 2], ["Cats", "Dogs", "Cows", "Geese"], force_ascii=True)
fig.show()

# With all options:
fig.barh(
    vals=[3, 10, 5, 2],
    labels=["A", "B", "C", "D"],
    max_width=40,
    bar_width=1,
    show_vals=True,
    val_format="{:5d}",
    force_ascii=False
)
fig.show()
```

### Response
#### Success Response (200)
Displays the horizontal bar chart in the terminal.

#### Response Example
```
# Unicode Output Example:
Cats   [ 3]  ████████████
Dogs   [10]  ████████████████████████████████████████
Cows   [ 5]  ██████████████████
Geese  [ 2]  ██████

# ASCII Output Example:
Cats   [ 3]  ************
Dogs   [10]  ****************************************
Cows   [ 5]  ********************
Geese  [ 2]  ********
```
```

--------------------------------

### 2x2 Subplot Grid with No Borders

Source: https://context7.com/nschloe/termplotlib/llms.txt

Generates a 2x2 subplot grid without any visible borders by setting `border_style=None`. Useful for tightly packed content.

```python
import termplotlib as tpl

# No borders
grid = tpl.subplot_grid((2, 2), width=30, border_style=None)
grid[0, 0].aprint("A")
grid[0, 1].aprint("B")
grid[1, 0].aprint("C")
grid[1, 1].aprint("D")
grid.show()
```

--------------------------------

### Combine Text with Plot

Source: https://context7.com/nschloe/termplotlib/llms.txt

Integrates custom text with a plot within the same figure. Text can be added before or after the plot.

```python
import termplotlib as tpl
import numpy as np

fig = tpl.figure()
fig.aprint("=== Data Visualization ===")
x = np.linspace(0, 2 * np.pi, 10)
y = np.sin(x)
fig.plot(x, y, width=40, height=10)
fig.aprint("Generated with termplotlib")
fig.show()
```

--------------------------------

### Histogram with fig.hist

Source: https://context7.com/nschloe/termplotlib/llms.txt

The `hist()` method generates histograms from pre-computed counts and bin edges. It supports both horizontal and vertical orientations and can be forced to use ASCII characters.

```APIDOC
## fig.hist()

### Description
Creates histograms from pre-computed counts and bin edges, supporting both horizontal and vertical orientations.

### Method
`hist(counts, bin_edges, **kwargs)`

### Endpoint
N/A (Method of a Figure object)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters (kwargs)
- **counts** (list of numbers) - Pre-computed counts for each bin.
- **bin_edges** (list of numbers) - The edges of the bins.
- **orientation** (str, optional) - Orientation of the histogram ('horizontal' or 'vertical'). Defaults to 'horizontal'.
- **force_ascii** (bool, optional) - Use ASCII characters instead of Unicode. Defaults to False.

### Request Example
```python
import termplotlib as tpl
import numpy as np

# Generate sample data
rng = np.random.default_rng(123)
sample = rng.standard_normal(size=1000)
counts, bin_edges = np.histogram(sample)

# Horizontal histogram
fig = tpl.figure()
fig.hist(counts, bin_edges, orientation="horizontal")
fig.show()

# Horizontal histogram with ASCII
fig.hist(counts, bin_edges, orientation="horizontal", force_ascii=True)
fig.show()

# Vertical histogram (example data)
counts_v, bin_edges_v = np.histogram(sample, bins=5)
fig_v = tpl.figure()
fig_v.hist(counts_v, bin_edges_v, orientation="vertical")
fig_v.show()
```

### Response
#### Success Response (200)
Displays the histogram in the terminal.

#### Response Example
```
# Horizontal Histogram Output Example (Unicode):
-3.30e+00 - -2.66e+00  [  8]  █▎
-2.66e+00 - -2.03e+00  [ 22]  ███▌
-2.03e+00 - -1.39e+00  [ 50]  ████████
-1.39e+00 - -7.56e-01  [123]  ███████████████████▋
...

# Horizontal Histogram Output Example (ASCII):
-3.30e+00 - -2.66e+00  [  8]  * 
-2.66e+00 - -2.03e+00  [ 22]  ***
-2.03e+00 - -1.39e+00  [ 50]  ******
-1.39e+00 - -7.56e-01  [123]  **********
...
```
```

--------------------------------

### Add Multi-line Text to Figure

Source: https://context7.com/nschloe/termplotlib/llms.txt

Appends multiple lines of text to a figure. Newlines within the string are preserved.

```python
import termplotlib as tpl

# Multi-line text
fig = tpl.figure()
fig.aprint("Line 1\nLine 2\nLine 3")
fig.show()
```

--------------------------------

### Subplot Grid with Plots

Source: https://context7.com/nschloe/termplotlib/llms.txt

Adds plots to cells within a subplot grid. Requires numpy for data generation. Each plot can have its own dimensions.

```python
import termplotlib as tpl
import numpy as np

x = np.linspace(0, 2 * np.pi, 10)

grid = tpl.subplot_grid((1, 2), width=80)
grid[0, 0].plot(x, np.sin(x), width=35, height=10)
grid[0, 1].plot(x, np.cos(x), width=35, height=10)
grid.show()
```

--------------------------------

### Add Text to Figure

Source: https://context7.com/nschloe/termplotlib/llms.txt

Appends arbitrary text to a termplotlib figure. This is useful for adding titles, labels, or custom messages alongside plots.

```python
import termplotlib as tpl

# Add text to figure
fig = tpl.figure()
fig.aprint("Custom header text")
fig.show()
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.