plotting.py

import numpy as np
import pandas as pd
import plotly.express as px
import streamlit as st


def plotly_line(x, y, column_names, y_label="", legend_label="", title=None, xliml=None, yliml=None):
    df = pd.DataFrame(data=np.column_stack((x, y)), columns=column_names)
    fig = px.line(df, x=column_names[0], y=column_names[1:], title=title,
                  labels={column_names[0]: column_names[0],
                          "value": y_label,
                          "variable": legend_label})
    fig.update_xaxes(range=xliml)
    fig.update_yaxes(range=yliml)
    return fig


def plot_wall_curves(n_component, z, z_plots, component):
    for plot_title, details in z_plots.items():
        y_col_labels = ["z"]
        fn_label = details["fn_label"]
        y_col_labels.extend(f"{fn_label}_w{component[i]}" for i in range(n_component))
        try:
            xliml = details["xlim"]
        except Exception:
            xliml = None
        try:
            yliml = details["ylim"]
        except Exception:
            yliml = None

        fig = plotly_line(z, details["plot_fn"], y_col_labels, y_label=details["plot_name"], legend_label="",
                          xliml=xliml, yliml=yliml, title=plot_title)
        #show(fig) - Jupyter
        st.plotly_chart(fig)


def plot_bulk_curves(n_component, r, r_plots, component):
    for plot_title, details in r_plots.items():
        y_col_labels = ["r"]
        fn_label = details["fn_label"]
        for i in range(n_component):
            y_col_labels.extend(
                f"{fn_label}_{component[i]}{component[j]}" for j in range(i, n_component))
        xliml = details["xlim"] if "xlim" in details.keys() else None
        yliml = details["ylim"] if "ylim" in details.keys() else None
 
        fig = plotly_line(r, details["plot_fn"], y_col_labels, y_label=details["plot_name"], legend_label="",
                          xliml=xliml, yliml=yliml, title=plot_title)
        #fig.show() - Jupyter
        st.plotly_chart(fig)


    
def plot_convergence(filename, log_y=True):
    with open(filename, "r") as solver_out:
        content = solver_out.readlines()
    conv_table = list(map(np.float32, [line.replace(":", ",").replace("|F(x)| = ", "").split(";")[0].split(",") for line in content if line != "\n"]))
    convergence_df = pd.DataFrame(conv_table, columns=["Iteration #", "|F(x)|"], dtype=np.float32)
    fig = plotly_line(x=convergence_df["Iteration #"], y=convergence_df["|F(x)|"], column_names=["Iteration #", "|F(x)|"])
    if log_y:
        fig.update_yaxes(type="log")
    st.plotly_chart(fig)