[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': 'Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:loc_yrs_ghd = np.where((yr>=yr1) & (yr<=yr2))[0];\nloc_yrs_cru = np.where((yr_cru>=yr1) & (yr_cru<=yr2))[0];\nreg_GHDvTemp_site  = np.zeros((8,6))\nreg_GHDvPrec_site  = np.zeros((8,6))\nreg_GHDvPDSI_site  = np.zeros((8,6))\nreg_TempvPrec_site = np.zeros((8,6))\nreg_TempvPDSI_site = np.zeros((8,6))\nreg_PDSIvPrec_site = np.zeros((8,6))\nfor ifile in enumerate(ghd_all_names[2:]):\nghd=df[ifile[1]]; ghd=ghd[loc_yrs_ghd];\ntmp_series  = tmp_coswtmean[loc_yrs_cru,ifile[0]+2]\npre_series  = pre_coswtmean[loc_yrs_cru,ifile[0]+2]\npdsi_series = pdsi_coswtmean[loc_yrs_cru,ifile[0]+2]\ndel df_siteclim\ndf_siteclim = pd.DataFrame(index=yr_cru[loc_yrs_cru], columns=[\'GHD\',\'Temp\',\'Prec\',\'PDSI\'])\ndf_siteclim.GHD =  copy.deepcopy(np.float64(ghd))\ndf_siteclim.Temp = copy.deepcopy(np.float64(tmp_series))\ndf_siteclim.Prec = copy.deepcopy(np.float64(pre_series))\ndf_siteclim.PDSI = copy.deepcopy(np.float64(pdsi_series))\ndf_siteclim=df_siteclim[df_siteclim.GHD.notnull()];\nseries_name = ifile[1]\nsns.set(style="darkgrid")\nsns.set_context("notebook", font_scale=1.5)\nsns.set_context( font_scale=1.5,rc={\'lines.markeredgewidth\': 0.1})\nsns.plt.figure(figsize=[20,12])\nsns.plt.suptitle(series_name+\' (\'+np.str(yr1[0])+\'-\'+np.str(yr2[0])+\', \'+mons_ave_txt+\')\',fontsize=25)\nsns.plt.subplot(2,3,1),sns.regplot("Temp","GHD",df_siteclim,scatter=True,marker=\'o\')\nslope, intercept, r_value, p_value, std_err = scipy.stats.linregress(df_siteclim.Temp,df_siteclim.GHD)\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nsns.plt.annotate("R2="+np.str(R2)+", beta="+np.str(beta)+", p="+np.str(pval),\\\nxy=(0.05,0.95),xycoords="axes fraction",fontsize=15)\nreg_GHDvTemp_site[ifile[0],0] = slope; reg_GHDvTemp_site[ifile[0],2] = R2; reg_GHDvTemp_site[ifile[0],4] = p_value;\nslope, intercept, r_value, p_value, std_err = \\\nscipy.stats.linregress(scipy.signal.detrend(df_siteclim.Temp),scipy.signal.detrend(df_siteclim.GHD))\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nreg_GHDvTemp_site[ifile[0],1] = slope; reg_GHDvTemp_site[ifile[0],3] = R2; reg_GHDvTemp_site[ifile[0],5] = p_value;\nsns.plt.subplot(2,3,2),sns.regplot("Prec","GHD",df_siteclim,scatter=True,marker=\'o\')\nslope, intercept, r_value, p_value, std_err = scipy.stats.linregress(df_siteclim.Prec,df_siteclim.GHD)\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nsns.plt.annotate("R2="+np.str(R2)+", beta="+np.str(beta)+", p="+np.str(pval),\\\nxy=(0.05,0.95),xycoords="axes fraction",fontsize=15)\nreg_GHDvPrec_site[ifile[0],0] = slope; reg_GHDvPrec_site[ifile[0],2] = R2; reg_GHDvPrec_site[ifile[0],4] = p_value;\nslope, intercept, r_value, p_value, std_err = \\\nscipy.stats.linregress(scipy.signal.detrend(df_siteclim.Prec),scipy.signal.detrend(df_siteclim.GHD))\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nreg_GHDvPrec_site[ifile[0],1] = slope; reg_GHDvPrec_site[ifile[0],3] = R2; reg_GHDvPrec_site[ifile[0],5] = p_value;\nsns.plt.subplot(2,3,3),sns.regplot("PDSI","GHD",df_siteclim,scatter=True,marker=\'o\')\nslope, intercept, r_value, p_value, std_err = scipy.stats.linregress(df_siteclim.PDSI,df_siteclim.GHD)\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nsns.plt.annotate("R2="+np.str(R2)+", beta="+np.str(beta)+", p="+np.str(pval),\\\nxy=(0.05,0.95),xycoords="axes fraction",fontsize=15)\nreg_GHDvPDSI_site[ifile[0],0] = slope; reg_GHDvPDSI_site[ifile[0],2] = R2; reg_GHDvPDSI_site[ifile[0],4] = p_value;\nslope, intercept, r_value, p_value, std_err = \\\nscipy.stats.linregress(scipy.signal.detrend(df_siteclim.PDSI),scipy.signal.detrend(df_siteclim.GHD))\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nreg_GHDvPDSI_site[ifile[0],1] = slope; reg_GHDvPDSI_site[ifile[0],3] = R2; reg_GHDvPDSI_site[ifile[0],5] = p_value;\nsns.plt.subplot(2,3,4),sns.regplot("Prec","Temp",df_siteclim,scatter=True,marker=\'o\')\nslope, intercept, r_value, p_value, std_err = scipy.stats.linregress(df_siteclim.Prec,df_siteclim.Temp)\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nsns.plt.annotate("R2="+np.str(R2)+", beta="+np.str(beta)+", p="+np.str(pval),\\\nxy=(0.05,0.95),xycoords="axes fraction",fontsize=15)\nreg_TempvPrec_site[ifile[0],0] = slope; reg_TempvPrec_site[ifile[0],2] = R2; reg_TempvPrec_site[ifile[0],4] = p_value;\nslope, intercept, r_value, p_value, std_err = \\\nscipy.stats.linregress(scipy.signal.detrend(df_siteclim.Prec),scipy.signal.detrend(df_siteclim.Temp))\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nreg_TempvPrec_site[ifile[0],1] = slope; reg_TempvPrec_site[ifile[0],3] = R2; reg_TempvPrec_site[ifile[0],5] = p_value;\nsns.plt.subplot(2,3,5),sns.regplot("PDSI","Temp",df_siteclim,scatter=True,marker=\'o\')\nslope, intercept, r_value, p_value, std_err = scipy.stats.linregress(df_siteclim.PDSI,df_siteclim.Temp)\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nsns.plt.annotate("R2="+np.str(R2)+", beta="+np.str(beta)+", p="+np.str(pval),\\\nxy=(0.05,0.95),xycoords="axes fraction",fontsize=15)\nreg_TempvPDSI_site[ifile[0],0] = slope; reg_TempvPDSI_site[ifile[0],2] = R2; reg_TempvPDSI_site[ifile[0],4] = p_value;\nslope, intercept, r_value, p_value, std_err = \\\nscipy.stats.linregress(scipy.signal.detrend(df_siteclim.PDSI),scipy.signal.detrend(df_siteclim.Temp))\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nreg_TempvPDSI_site[ifile[0],1] = slope; reg_TempvPDSI_site[ifile[0],3] = R2; reg_TempvPDSI_site[ifile[0],5] = p_value;\nsns.plt.subplot(2,3,6),sns.regplot("Prec","PDSI",df_siteclim,scatter=True,marker=\'o\')\nslope, intercept, r_value, p_value, std_err = scipy.stats.linregress(df_siteclim.Prec,df_siteclim.PDSI)\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nsns.plt.annotate("R2="+np.str(R2)+", beta="+np.str(beta)+", p="+np.str(pval),\\\nxy=(0.05,0.95),xycoords="axes fraction",fontsize=15)\nreg_PDSIvPrec_site[ifile[0],0] = slope; reg_PDSIvPrec_site[ifile[0],2] = R2; reg_PDSIvPrec_site[ifile[0],4] = p_value;\nslope, intercept, r_value, p_value, std_err = \\\nscipy.stats.linregress(scipy.signal.detrend(df_siteclim.Prec),scipy.signal.detrend(df_siteclim.PDSI))\nR2 = np.round(r_value**2,decimals=3); pval = np.round(p_value, decimals=5); beta = np.round(slope,decimals=3)\nreg_PDSIvPrec_site[ifile[0],1] = slope; reg_PDSIvPrec_site[ifile[0],3] = R2; reg_PDSIvPrec_site[ifile[0],5] = p_value;\nsns.plt.tight_layout'}, {'role': 'assistant', 'content': 'result_visualization'}]