{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n# NCL_panel_10.py\nThis script illustrates the following concepts:\n - Drawing Hovmueller plots\n - Attaching plots along the Y axis\n - Using a blue-white-red color map\n - Drawing zonal average plots\n - Paneling attached plots\n\nSee following URLs to see the reproduced NCL plot & script:\n - Original NCL script: https://www.ncl.ucar.edu/Applications/Scripts/panel_10.ncl and https://www.ncl.ucar.edu/Applications/Scripts/panel_attach_10.ncl\n - Original NCL plot: https://www.ncl.ucar.edu/Applications/Images/panel_10_lg.png and https://www.ncl.ucar.edu/Applications/Images/panel_attach_10_lg.png\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import packages:\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import numpy as np\nimport xarray as xr\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.axes_grid1.inset_locator import inset_axes\nimport matplotlib.gridspec as gridspec\nfrom cartopy.mpl.gridliner import LongitudeFormatter, LatitudeFormatter\nimport warnings\n\nimport geocat.datafiles as gdf\nimport geocat.viz.util as gvutil\nfrom geocat.viz import cmaps as gvcmaps" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Read in data:\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Open a netCDF data file using xarray default engine\n# and load the data into xarrays\nfilename = 'chi200_ud_smooth.nc'\nds = xr.open_dataset(gdf.get('netcdf_files/' + filename))\n\nlon = ds.lon\ntimes = ds.time\nscale = 1000000\nchi = ds.CHI\nchi = chi / scale\n\n# Calculate zonal mean\nwith warnings.catch_warnings(): # This is not needed but is supressing a warning thrown by numpy checking for NaN values\n warnings.simplefilter(\"ignore\")\n mean = chi.mean(dim='lon')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create Single Plot:\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "fig, (ax1, ax2) = plt.subplots(nrows=1,\n ncols=2,\n sharey=True,\n figsize=(12, 9),\n gridspec_kw=dict(wspace=0,\n width_ratios=[0.75, 0.25],\n left=0.15,\n right=0.85,\n top=0.85,\n bottom=0.15))\n# Create inset axes for color bar\ncax1 = inset_axes(ax1,\n width='100%',\n height='7%',\n loc='lower left',\n bbox_to_anchor=(0, -0.15, 1, 1),\n bbox_transform=ax1.transAxes,\n borderpad=0)\n\n# Draw contour lines\nax1.contour(lon,\n times,\n chi,\n levels=np.arange(-12, 13, 2),\n colors='black',\n linestyles='solid',\n linewidths=.5)\n\n# Draw filled contours\ncf = ax1.contourf(lon,\n times,\n chi,\n levels=np.arange(-12, 13, 2),\n cmap=gvcmaps.BlWhRe)\n\n# Draw colorbar with larger tick labels\ncbar = plt.colorbar(cf,\n cax=cax1,\n orientation='horizontal',\n ticks=np.arange(-10, 11, 2))\ncbar.ax.tick_params(labelsize=12)\n\n# Use geocat.viz.util convenience function to set axes limits & tick values\ngvutil.set_axes_limits_and_ticks(ax1,\n xlim=[100, 220],\n ylim=[0, 1.55 * 1e16],\n xticks=[135, 180],\n yticks=np.linspace(0, 1.55 * 1e16, 7),\n xticklabels=['135E', '180'],\n yticklabels=np.arange(0, 181, 30))\n\n# Use geocat.viz.util convenience function to add minor and major tick lines\ngvutil.add_major_minor_ticks(ax1,\n x_minor_per_major=3,\n y_minor_per_major=3,\n labelsize=12)\n\n# Remove tick marks on right side of ax1\nax1.tick_params('y', which='both', right=False)\n\n# Use geocat.viz.util convenience function to add titles\ngvutil.set_titles_and_labels(ax1,\n maintitle=\"Pacific Region\",\n lefttitle=\"Velocity Potential\",\n righttitle=\"m2/s\",\n ylabel=\"elapsed time\")\n\n# Format axes for zonal average plot\n# Use geocat.viz.util convenience function to set axes limits & tick values\ngvutil.set_axes_limits_and_ticks(ax2,\n xlim=[-0.6, 0.9],\n ylim=[0, 1.55 * 1e16],\n xticks=np.arange(-0.3, 0.7, 0.3),\n yticks=np.linspace(0, 1.55 * 1e16, 7),\n xticklabels=['-0.30', '', '0.30', ''],\n yticklabels=np.arange(0, 181, 30))\n\n# Use geocat.viz.util convenience function to add minor and major tick lines\ngvutil.add_major_minor_ticks(ax2,\n x_minor_per_major=1,\n y_minor_per_major=3,\n labelsize=12)\n\n# Remove tick marks on left side of ax2\nax2.tick_params('y', which='both', left=False)\n\n# Use geocat.viz.util convenience function to add titles\ngvutil.set_titles_and_labels(ax2,\n maintitle=\"Zonal Ave\",\n maintitlefontsize=12)\n\n# Plot zonal average\nax2.plot(mean, times, linewidth=0.5, color='black')\n\nplt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Define helper function to create the four subplots\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "def make_subplot(fig, gridspec, xlim):\n # Create axes for the contour plot and the zonal average plot\n ax1 = fig.add_subplot(gridspec[0])\n ax2 = fig.add_subplot(gridspec[1])\n\n # Draw contour lines\n ax1.contour(lon,\n times,\n chi,\n levels=np.arange(-12, 13, 2),\n colors='black',\n linestyles='solid',\n linewidths=.5)\n\n # Draw filled contours, save the mappable to create colorbar later\n color_mappable = ax1.contourf(lon,\n times,\n chi,\n levels=np.arange(-12, 13, 2),\n cmap=gvcmaps.BlWhRe)\n\n # Use geocat.viz.util convenience function to add longitude tick labels\n gvutil.add_lat_lon_ticklabels(ax1)\n\n # Remove degree symbol from tick labels\n ax1.xaxis.set_major_formatter(LongitudeFormatter(degree_symbol=''))\n\n # Use geocat.viz.util convenience function to set axes limits & tick values\n gvutil.set_axes_limits_and_ticks(ax1,\n xlim=xlim,\n ylim=[0, 1.55 * 1e16],\n xticks=np.arange(xlim[0], xlim[1], 30),\n yticks=np.linspace(0, 1.55 * 1e16, 7),\n yticklabels=[])\n\n # Use geocat.viz.util convenience function to add minor and major tick lines\n gvutil.add_major_minor_ticks(ax1,\n x_minor_per_major=2,\n y_minor_per_major=3,\n labelsize=10)\n\n # Remove tick marks on right side of ax1\n ax1.tick_params('y', which='both', right=False)\n\n # Use geocat.viz.util convenience function to add titles\n gvutil.set_titles_and_labels(ax1,\n lefttitle=\"Velocity Potential\",\n righttitle=\"m2/s\",\n lefttitlefontsize=10,\n righttitlefontsize=10)\n\n # Format axes for zonal average plot\n # Use geocat.viz.util convenience function to set axes limits & tick values\n gvutil.set_axes_limits_and_ticks(ax2,\n xlim=[-0.6, 0.9],\n ylim=[0, 1.55 * 1e16],\n xticks=np.arange(-0.3, 0.7, 0.3),\n yticks=np.linspace(0, 1.55 * 1e16, 7),\n xticklabels=['-0.30', '', '0.30', ''],\n yticklabels=[])\n\n # Use geocat.viz.util convenience function to add minor and major tick lines\n gvutil.add_major_minor_ticks(ax2,\n x_minor_per_major=1,\n y_minor_per_major=3,\n labelsize=8)\n\n # Remove tick marks on left side of ax2\n ax2.tick_params('y', which='both', left=False)\n\n # Use geocat.viz.util convenience function to add titles\n gvutil.set_titles_and_labels(ax2,\n maintitle=\"Zonal Ave\",\n maintitlefontsize=8)\n\n # Plot zonal average\n ax2.plot(mean, times, linewidth=0.5, color='black')\n return color_mappable" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create the four panel plot\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "fig = plt.figure(figsize=(10, 10))\n\n# Create a three by two grid to hold the four plots and the colorbar\nouter_grid = gridspec.GridSpec(3, 2,\n figure=fig,\n hspace=0.35,\n height_ratios=[0.475, 0.475, 0.05])\n\n# Create an array to hold the internal gridspecs\ninner_grids = np.empty(4, dtype=gridspec.GridSpec)\n\n# Create the gridspecs for each of the four plots\nfor i in range(0, 4):\n inner_grids[i] = gridspec.GridSpecFromSubplotSpec(1, 2,\n subplot_spec=outer_grid[i],\n wspace=0,\n width_ratios=[0.75, 0.25])\nmake_subplot(fig, inner_grids[0], [0, 90])\nmake_subplot(fig, inner_grids[1], [90, 180])\nmake_subplot(fig, inner_grids[2], [180, 270])\ncolor_mappable = make_subplot(fig, inner_grids[3], [270, 360])\n\n# Create axes for colorbar and then draw colorbar\ncax = fig.add_subplot(outer_grid[2, :])\nplt.colorbar(color_mappable,\n cax=cax,\n ticks=np.arange(-10, 12, 2),\n orientation='horizontal',\n drawedges=True)\n\n# Add figure title\nfig.suptitle(filename, fontsize=18, y=0.95)\nplt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" } }, "nbformat": 4, "nbformat_minor": 0 }