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Merge pull request #132 from valeriupredoi/dev_amoc_reverse
Several developments for the AMOC analysis
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| #!/usr/bin/ipython | ||
| # | ||
| # Copyright 2024, Plymouth Marine Laboratory | ||
| # | ||
| # This file is part of the bgc-val library. | ||
| # | ||
| # bgc-val is free software: you can redistribute it and/or modify it | ||
| # under the terms of the Revised Berkeley Software Distribution (BSD) 3-clause license. | ||
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| # bgc-val is distributed in the hope that it will be useful, but | ||
| # without any warranty; without even the implied warranty of merchantability | ||
| # or fitness for a particular purpose. See the revised BSD license for more details. | ||
| # You should have received a copy of the revised BSD license along with bgc-val. | ||
| # If not, see <http://opensource.org/licenses/BSD-3-Clause>. | ||
| # | ||
| # Address: | ||
| # Plymouth Marine Laboratory | ||
| # Prospect Place, The Hoe | ||
| # Plymouth, PL1 3DH, UK | ||
| # | ||
| # Email: | ||
| # [email protected] | ||
| # | ||
| """ | ||
| .. module:: generic_map_legend | ||
| :platform: Unix | ||
| :synopsis: Tool to make a plot showing a regions. | ||
| .. moduleauthor:: Lee de Mora <[email protected]> | ||
| .. active:: No | ||
| """ | ||
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| # implement correct import of params if module in use | ||
| # from ..Paths.paths import orcaGridfn, WOAFolder_annual | ||
| import matplotlib | ||
| matplotlib.use('Agg') | ||
| import os | ||
| from netCDF4 import Dataset | ||
| import numpy as np | ||
| from bgcval2.bgcvaltools import bv2tools as bvt | ||
| from bgcval2.bgcvaltools.pftnames import getLongName | ||
| from bgcval2.bgcvaltools.makeMask import makeMask | ||
| from matplotlib import pyplot | ||
| import cartopy | ||
| import cartopy.crs as ccrs | ||
| from cartopy import img_transform, feature as cfeature | ||
| from bgcval2._runtime_config import get_run_configuration | ||
| from bgcval2.Paths.paths import paths_setter | ||
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| # Functions# | ||
| # Make a single plot for each region. | ||
| # one pane for global map centered on the middle of the region. | ||
| # One pane zoomed in on center of region | ||
| # One pane global map. | ||
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| def plot_globe(ax): | ||
| pyplot.sca(ax) | ||
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| # if quick: | ||
| ax.add_feature(cfeature.OCEAN, zorder=0) | ||
| ax.add_feature(cfeature.LAND, zorder=0, edgecolor='black') | ||
| # else: | ||
| # nc = Dataset(bathy_fn, 'r') | ||
| # lats = nc.variables['lat'][::binning] | ||
| # lons = nc.variables['lon'][::binning] | ||
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| # data = nc.variables['elevation'][::binning, ::binning] | ||
| # nc.close() | ||
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| # data = np.ma.masked_where(data>0., data) | ||
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| # pyplot.pcolormesh( | ||
| # lons, | ||
| # lats, | ||
| # data, | ||
| # #transform=proj, | ||
| # transform=ccrs.PlateCarree(), | ||
| # cmap=cmap, | ||
| # vmin=vmin, vmax=vmax, | ||
| # ) | ||
| # ax.coastlines() | ||
| # ax.add_feature(cfeature.LAND, edgecolor='black', facecolor=land_color, linewidth=0.5, zorder=9) | ||
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| ax.set_global() | ||
| ax.gridlines() | ||
| return ax | ||
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| def plot_platcarre(ax): | ||
| pyplot.sca(ax) | ||
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| # if quick: | ||
| ax.add_feature(cfeature.OCEAN, zorder=0) | ||
| # else: | ||
| # nc = Dataset(bathy_fn, 'r') | ||
| # lats = nc.variables['lat'][::binning] | ||
| # lons = nc.variables['lon'][::binning] | ||
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| # data = nc.variables['elevation'][::binning, ::binning] | ||
| # nc.close() | ||
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| # data = np.ma.masked_where(data>0., data) | ||
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| # pyplot.pcolormesh( | ||
| # lons, | ||
| # lats, | ||
| # data, | ||
| # #transform=proj, | ||
| # transform=ccrs.PlateCarree(), | ||
| # cmap=cmap, | ||
| # vmin=vmin, vmax=vmax, | ||
| # ) | ||
| # ax.coastlines() | ||
| # ax.add_feature(cfeature.LAND, edgecolor='black', facecolor=land_color, linewidth=0.5, zorder=9) | ||
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| ax.set_global() | ||
| ax.gridlines() | ||
| return ax | ||
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| def add_region(fig, ax, lons, lats, data): | ||
| #im = ax.scatter(lons, lats, c=data) | ||
| pyplot.sca(ax) | ||
| #im = ax.contourf(lons, lats, data, zorder=1000) | ||
| im = ax.pcolormesh(lons, lats, data, zorder=1, transform=ccrs.PlateCarree(),) | ||
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| #pyplot.colorbar() | ||
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| ax.add_feature(cfeature.LAND, zorder=10, edgecolor='black') | ||
| return fig, ax, im | ||
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| def make_figure(region): | ||
| fig_fn = bvt.folder('images/regions')+region+'.png' | ||
| #if os.path.exists(fig_fn): return | ||
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| fig = pyplot.figure() | ||
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| paths_dict, config_user = get_run_configuration("defaults") | ||
| # filter paths dict into an object that's usable below | ||
| paths = paths_setter(paths_dict) | ||
| #ncfn = paths.orcaGridfn | ||
| ncfn = 'mesh_mask_eORCA1_wrk.nc' | ||
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| nc = Dataset(ncfn, 'r') | ||
| print(ncfn) | ||
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| dat = nc.variables['mbathy'][:].squeeze() | ||
| lats = nc.variables['nav_lat'][:].squeeze() | ||
| lons = nc.variables['nav_lon'][:].squeeze() | ||
| lons = bvt.makeLonSafeArr(lons) | ||
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| old_mask = np.ma.masked_where(dat.mask + dat ==0, dat).mask | ||
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| xd = np.ma.masked_where(old_mask, dat).flatten() | ||
| xt = np.ones_like(xd) | ||
| xz = xt | ||
| xy = np.ma.masked_where(old_mask, lats).flatten() | ||
| xx = np.ma.masked_where(old_mask, lons).flatten() | ||
| old_mask_flat = old_mask.flatten() | ||
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| region_mask = makeMask('bathy', region, xt, xz, xy, xx, xd, debug=True) | ||
| #print('done makeMask') | ||
| #assert 0 | ||
| new_dat = np.ma.masked_where(region_mask + old_mask_flat, xd) | ||
| new_lon = np.ma.masked_where(region_mask+ old_mask_flat, xx) | ||
| new_lat = np.ma.masked_where(region_mask+ old_mask_flat, xy) | ||
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| new_dat = new_dat.reshape(dat.shape) | ||
| #new_lat = lats # new_lat.reshape(lats.shape) | ||
| #new_lon = lons # new_lon.reshape(lons.shape) | ||
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| fig.set_size_inches(12, 8) | ||
| widths = [1, 1, 1] | ||
| heights = [1, 1.75] | ||
| spec2 = matplotlib.gridspec.GridSpec( | ||
| ncols=len(widths), | ||
| nrows=len(heights), | ||
| figure=fig, | ||
| width_ratios=widths, | ||
| height_ratios=heights, | ||
| hspace=0.30, | ||
| wspace=0.30,) | ||
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| print('lats:', new_lat.mean(), 'lon:', new_lon.mean(), 'data:', new_dat.min(), new_dat.max()) | ||
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| ortho_pro=ccrs.Orthographic(new_lon.mean(), new_lat.mean(),) | ||
| ax_globe = fig.add_subplot(spec2[0, 0], projection=ortho_pro) | ||
| ax_globe = plot_globe(ax_globe) | ||
| fig, ax_globe, im = add_region(fig, ax_globe, lons, lats, new_dat) | ||
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| ortho_pro=ccrs.Orthographic(new_lon.mean()+120., new_lat.mean(),) | ||
| ax_globe1 = fig.add_subplot(spec2[0, 1], projection=ortho_pro) | ||
| ax_globe1 = plot_globe(ax_globe1) | ||
| fig, ax_globe1, im1 = add_region(fig, ax_globe1, lons, lats, new_dat) | ||
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| ortho_pro=ccrs.Orthographic(new_lon.mean()-120., new_lat.mean(),) | ||
| ax_globe2 = fig.add_subplot(spec2[0, 2], projection=ortho_pro) | ||
| ax_globe2 = plot_globe(ax_globe2) | ||
| fig, ax_globe2, im2 = add_region(fig, ax_globe2, lons, lats, new_dat) | ||
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| pc_proj=cartopy.crs.PlateCarree(central_longitude=new_lon.mean()) | ||
| ax_pc = fig.add_subplot(spec2[1, :], projection=pc_proj) | ||
| ax_pc = plot_platcarre(ax_pc) | ||
| fig, ax_pc, im3 = add_region(fig, ax_pc, lons, lats, new_dat) | ||
| #cbar = pyplot.colorbar(ax=ax_pc, cax=im3) | ||
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| pyplot.suptitle(region+': '+getLongName(region)) | ||
| print('saving:', fig_fn) | ||
| pyplot.savefig(fig_fn,dpi=300.) | ||
| pyplot.savefig(fig_fn.replace('.png', '_trans.png'), transparent=True) | ||
| pyplot.close() | ||
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| def main(): | ||
| regions = [ | ||
| 'Ascension', | ||
| 'ITCZ', | ||
| 'TristandaCunha', | ||
| 'Pitcairn', | ||
| 'Cornwall', | ||
| 'SubtropicNorthAtlantic', | ||
| 'SPNA', | ||
| 'STNA', | ||
| 'SouthernOcean', | ||
| 'ArcticOcean', | ||
| 'Equator10', | ||
| 'NorthPacificOcean', | ||
| 'SouthPacificOcean', | ||
| 'NorthAtlanticOcean', | ||
| 'SouthAtlanticOcean', | ||
| 'GINseas', | ||
| 'LabradorSea', | ||
| 'EquatorialAtlanticOcean', | ||
| 'Global', | ||
| 'ignoreInlandSeas', | ||
| ] | ||
| for region in regions[:]: | ||
| make_figure(region) | ||
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| if __name__ == "__main__": | ||
| main() |
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