Data Appearance

 I have redone the two parity checks from yesterday, only this time the parity

result is odd: the two qubits are not in the same state.

One interesting thing I have discovered is that, although qiskit.visualization is

a qiskit module, giving one a choice between matplotlib and LaTex(circuit_drawer),

a choice of Matplotlib comes with the usual layout functions. One can specify title,

and - adding title=title in a plot-histogram call will make a title appear. Below:

the first specifies just what is wanted, the second calls the seaborn style overall.

seaborn is just one style available from matplotlib, and one can tweak it at will. 

If using conda, one needs to have conda install the seaborn module in the environment

one is using...

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The second code script is from Gemini.

Qiskit visualization; what does fig, ax do?

In the provided code snippet, `fig` and `ax` are used to handle and manipulate the figure and axes objects in a Matplotlib visualization. Here's a breakdown of their roles:

1. **`fig`**: This is the figure object that holds everything in the plot. It serves as a canvas where all the elements (like axes, labels, titles, etc.) are drawn. You can think of it as the overall window or frame for your plotting.

2. **`ax`**: This is the axes object that represents a single plot within the figure. It is where the actual data is plotted. Multiple axes can exist in a single figure, allowing for complex plots with multiple graphs.

### In the Code

- `fig, ax = plt.subplots(figsize=figsize)`: This line creates a new figure and a single axes in that figure. The `figsize` parameter defines the dimensions of the figure in inches.

- `plot_histogram(data, legend=legend, title=title, color=color, ax=ax)`: This line plots the histogram onto the specified axes (`ax`). 

- `ax.set_title(title, fontsize=20)`: This sets the title of the axes, customizing the font size to make it visually appealing.

By structuring the plotting this way, you gain control over various elements of the visualization easily. 

Is plot_histogram() a matplotlib function?

No, `plot_histogram()` is not a standard Matplotlib function. It is a specific function provided by Qiskit, a quantum computing framework, to visualize the results of quantum computations. 

In the context of Qiskit, `plot_histogram()` is used to display histogram representations of the counts from quantum circuit execution. It allows you to visualize how often each measurement outcome occurred, making it easier to interpret results from quantum simulations or experiments.

If you need to create histograms with Matplotlib directly, you would typically use `plt.hist()` or `ax.hist()` instead.