[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': "Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:# %%\nimport plotly.graph_objects as go\nimport numpy as np\nimport pandas as pd\n\nnum_infected = []\nDay = []\nbatch_list = []\nfor batch in range(1, 4):\n    savefile = f'../input/simulation-scripts/outfile_s{batch}.npz'\n    container = np.load(savefile)\n    sim_result = [container[key] for key in container]\n    for t in range(len(sim_result)):\n        num_infected.append(len(np.where(sim_result[t] < 30)[0]))\n    Day.extend(np.arange(len(sim_result)).tolist())\n    batch_list.extend(np.repeat(batch, len(sim_result)))\n\ninfected_growth_df = pd.DataFrame(\n    {'num_infected': num_infected, 'Day': Day, 'batch': batch_list})\n\n# %%\n\n\n# Add data\n\nfig = go.Figure()\n# Create and style traces\nfig.add_trace(go.Scatter(x=infected_growth_df[infected_growth_df['batch'] == 1].Day, y=infected_growth_df[infected_growth_df['batch'] == 1].num_infected, name='Speed 0.01',\n                         line=dict(color='firebrick', width=4)))\nfig.add_trace(go.Scatter(x=infected_growth_df[infected_growth_df['batch'] == 2].Day, y=infected_growth_df[infected_growth_df['batch'] == 2].num_infected, name='Speed 0.1',\n                         line=dict(color='royalblue', width=4,\n                                   dash='dot')))\nfig.add_trace(go.Scatter(x=infected_growth_df[infected_growth_df['batch'] == 3].Day, y=infected_growth_df[infected_growth_df['batch'] == 3].num_infected, name='Speed 1',\n                         line=dict(color='green', width=4,\n                                   dash='dash')  # dash options include 'dash', 'dot', and 'dashdot'\n                         ))\n\n# Edit the layout\nfig.update_layout(title='The influence of government reaction speed on the pandemic development',\n                  xaxis_title='Day',\n                  yaxis_title='Number of infected cases',\n                  xaxis=dict(\n                        showline=True,\n                        showgrid=False,\n                        showticklabels=True,\n                        linecolor='rgb(204, 204, 204)',\n                        linewidth=2,\n                        ticks='outside',\n                        tickfont=dict(\n                            family='Arial',\n                            size=12,\n                            color='rgb(82, 82, 82)',\n                        ),\n                  ),\n                  yaxis=dict(\n                      showline=True,\n                      showgrid=False,\n                      showticklabels=True,\n                      linecolor='rgb(204, 204, 204)',\n                      linewidth=2,\n                      ticks='outside',\n                      tickfont=dict(\n                          family='Arial',\n                          size=12,\n                          color='rgb(82, 82, 82)',\n                      ),\n                  ),\n                  autosize=True,\n                  plot_bgcolor='white',\n                  height=600, width=800\n                  )\n\nfig.show()\n\n# %%\n"}, {'role': 'assistant', 'content': "['result_visualization']"}]