def plot_lapaz_elevation(PROJ, ax4, bar_legend, grid_style, lala_lp, levels,
lolo_lp, ncmap, tab10, topo_ds, white_grid_color, xs1,
xs2, ys1, ys2):
ax = ax4
fa.get_ax_lapaz(ax=ax,
chc_lp_legend=False,
plot_cities=False,
lalo_extent=[xs1, xs2, ys1, ys2],
lola_ticks=[lolo_lp, lala_lp],
draw_labels=False,
grid_alpha=1,
grid_color=white_grid_color,
grid_style=grid_style,
lake_face_color=crt.feature.COLORS['water'])
ax.set_xticks([-69, -68, -67], crs=PROJ)
slice_ = {
'lat': slice(
ys1,
ys2,
),
'lon': slice(
xs1,
xs2,
)
}
band_ = topo_ds['Band1'].loc[slice_] / 1000
band_.name = bar_legend
mappable = band_.plot(
cmap=ncmap,
ax=ax,
levels=levels,
subplot_kws={'transform': PROJ},
# center=2000,
norm=Normalize(0, 5),
add_colorbar=False,
rasterized=True)
ax.set_xlabel(None)
ax.set_ylabel(None)
ax.scatter([co.CHC_LON], [co.CHC_LAT],
facecolors='none',
edgecolors=tab10(0))
ax.scatter([co.LPB_LON], [co.LPB_LAT],
facecolors='none',
edgecolors=tab10(1))
return mappable
def plot_general_lapaz(ds1):
cl = co.CPer
c1 = ds1[cl].sum([co.RL, co.ZM])
c2 = ds1[cl].sum([co.ZM, co.RL, co.TH_CENTER])
ar = c1 / c2
# ar = c1
ar = ar.isel(**{co.R_CENTER: slice(0, -3)})
ax = fa.get_ax_lapaz(fig_args={'figsize': (5, 5)})
fa.logpolar_plot(ar, name=co.CPer, ax=ax, perM=.95, perm=.01)
# ax.set_xlim(-75, -60)
# ax.set_ylim(-25, -7)
return ax
def plot_clust_in_lapaz(_n, dscc):
for _f in range(_n):
ax = fa.get_ax_lapaz()
ax.set_title(str(_f))
_ds = dscc.loc[{co.CLUS_LENGTH_DIM: _n}][
{co.R_CENTER: slice(1, 23)}]
_ds = _ds.drop(co.KMEAN_OBJ)
_ds = _ds.where(_ds[co.FLAG] == _f)
_ds = _ds.sum([co.RL, co.ZM])
_ds = _ds[[co.CONC]]
_cm = fa.get_custom_cmap([*ucp.cc, *ucp.cc, *ucp.cc][_f][:3])
if _ds[co.CONC].max().item() != 0:
fa.logpolar_plot(_ds, ax=ax, patch_args={'cmap': _cm},
colorbar=False)
fa.add_chc_lpb(ax)
boo = self.merged_ds[co.ClusFlag] == clus
# fig,ax = plt.subplots()
import warnings
warnings.simplefilter('ignore')
ar = self.merged_ds.where(boo)[co.CPer].mean(dim=[co.RL])
fa.logpolar_plot(ar,
ax,
name=co.CPer,
perM=.15,
quantile=False,
colorbar=False,
patch_args={'cmap': fa.get_custom_cmap(FLP.COLORS[i])})
# %%
i = 0
ax = fa.get_ax_lapaz()
for i in range(len_clus):
clus = self.cluster_flags[i]
boo = self.merged_ds[co.ClusFlag] == clus
# fig,ax = plt.subplots()
import warnings
warnings.simplefilter('ignore')
ar = self.merged_ds.where(boo)[co.CCPer].mean(dim=[co.RL])
fa.logpolar_plot(ar,
ax,
name=co.CCPer,
perM=.05,
quantile=False,
colorbar=False,
patch_args={'cmap': fa.get_custom_cmap(FLP.COLORS[i])})
fa.add_chc_lpb(ax)
def plot_lapaz_domains(PROJ, ax3, dark_grid_color, grid_style, lala_lp,
lolo_lp, tab10, xs1, xs2, ys1, ys2):
ax = ax3
fa.get_ax_lapaz(ax=ax,
chc_lp_legend=False,
plot_cities=False,
lalo_extent=[xs1, xs2, ys1, ys2],
lola_ticks=[lolo_lp, lala_lp],
draw_labels=False,
grid_style=grid_style,
grid_color=dark_grid_color,
grid_alpha=1)
# noinspection PyArgumentList
ax.set_xticks([-69, -68, -67], crs=PROJ)
ax.set_xlabel(r'longitude [$\degree$]')
# noinspection PyArgumentList
ax.set_yticks([-16, -17], crs=PROJ)
ax: plt.Axes
ax.set_ylabel(r'latitude [$\degree$]')
# ax.set_ylabel('abc', rotation=0, fontsize=20, labelpad=20)
# ax.annotate('latitude',
# (0, 1),
# (-2, -2),
# xycoords='axes fraction',
# textcoords='offset points',
# horizontalalignment='right',
# verticalalignment='top',
# # color=ucp.cc[3]
# )
x1, x2, y1, y2 = -69, -67.3, -17.2, -15.6
map_add_rectangle(ax, x1, x2, y1, y2, color=ucp.cc[3])
# noinspection PyProtectedMember
ax.annotate('D04', (x1, y1), (0, -2),
xycoords=PROJ._as_mpl_transform(ax),
textcoords='offset points',
horizontalalignment='left',
verticalalignment='top',
color=ucp.cc[3])
ax.scatter([co.CHC_LON], [co.CHC_LAT], facecolor=tab10(0))
ax.scatter([co.LPB_LON], [co.LPB_LAT], facecolor=tab10(1))
# noinspection PyProtectedMember
ax.annotate(
'CHC',
[co.CHC_LON, co.CHC_LAT],
xytext=[1, 2],
xycoords=PROJ._as_mpl_transform(ax),
textcoords='offset points',
horizontalalignment='right',
verticalalignment='bottom',
)
# noinspection PyProtectedMember
ax.annotate(
'LPB',
[co.LPB_LON, co.LPB_LAT],
xytext=[0, -3],
xycoords=PROJ._as_mpl_transform(ax),
textcoords='offset points',
horizontalalignment='right',
verticalalignment='top',
)
ax: plt.Axes
# noinspection PyProtectedMember
ax.annotate('Lake TCC', [-69, -16],
xytext=[2, 4],
xycoords=PROJ._as_mpl_transform(ax),
textcoords='offset points',
horizontalalignment='left',
verticalalignment='bottom',
color=crt.feature.COLORS['water'])
def plot_pathways(geo_df,
lon_range=15,
lat_range=13,
centroid_to_plot=None,
chc_lp_legend=False,
ax_bolivia=True,
ax=None,
min_font_size=5,
labs_to_plot='all',
background_alpha=0):
npdf = geo_df
if centroid_to_plot is None:
centroid_to_plot = ['LR', 'MR']
if ax is None:
ucp.set_dpi(300)
f_width = 7.25
figsize = (f_width, f_width / 1.6)
_, ax = plt.subplots(subplot_kw=dict(projection=crt.crs.PlateCarree()),
figsize=figsize)
ax: plt.Axes
if ax_bolivia:
fa.get_ax_bolivia(
ax=ax,
plot_cities=False,
map_res='50m',
lake_face_color='none',
map_line_alpha=.5,
chc_lp_legend=chc_lp_legend,
grid_alpha=0,
draw_labels=False,
xlab_top=False,
xlab_bot=False,
ylab_left=False,
ylab_right=False,
)
else:
fa.get_ax_lapaz(ax=ax,
plot_cities=False,
lake_face_color='none',
map_line_alpha=.5,
chc_lp_legend=chc_lp_legend,
grid_alpha=0,
draw_labels=False,
y_left_lab=False)
npdf['text_xy'] = [[[0, 0]]] * len(npdf)
npdf.loc['07_LR', 'text_xy'] = [[[-5, -12]]]
npdf.loc['08_LR', 'text_xy'] = [[[-5, 7]]]
npdf.loc['10_LR', 'text_xy'] = [[[8, 0]]]
npdf.loc['11_MR', 'text_xy'] = [[[-13, 7]]]
npdf.loc['02_MR', 'text_xy'] = [[[-10, 7]]]
npdf.loc['04_MR', 'text_xy'] = [[[-10, 7]]]
npdf.loc['05_MR', 'text_xy'] = [[[5, 0]]]
npdf.loc['09_MR', 'text_xy'] = [[[-25, -8]]]
npdf.loc['08_SM', 'text_xy'] = [[[-25, -10]]]
npdf.loc['12_SM', 'text_xy'] = [[[-3, 7]]]
npdf.loc['03_SM', 'text_xy'] = [[[5, -4]]]
npdf.loc['06_SM', 'text_xy'] = [[[-7, -10]]]
npdf.loc['11_SR', 'text_xy'] = [[[-10, 7]]]
npdf.loc['02_SR', 'text_xy'] = [[[-3, 7]]]
npdf.loc['12_SR', 'text_xy'] = [[[-12, 7]]]
npdf.loc['04_SR', 'text_xy'] = [[[4, -10]]]
npdf.loc['07_SR', 'text_xy'] = [[[-17, -12]]]
npdf.loc['10_SR', 'text_xy'] = [[[-10, 5]]]
lrpdf = npdf[npdf['range'].isin(centroid_to_plot)]
for l, r in lrpdf.iterrows():
ax.scatter(r['lon'],
r['lat'],
s=40,
c=[r['range_color']],
marker=r['range_marker'],
zorder=20,
edgecolors=['k'],
linewidth=1)
if labs_to_plot == 'all':
lab_lrpdf = lrpdf
else:
lab_lrpdf = npdf[npdf['range'].isin(labs_to_plot)]
for l, r in lab_lrpdf.iterrows():
ax.annotate(
r.name,
xy=r[['lon', 'lat']],
xytext=r['text_xy'][0],
textcoords='offset points',
zorder=12,
backgroundcolor=[1, 1, 1, background_alpha],
# bbox=dict(boxstyle="round",
# alpha=0,
# linewidth=0,
# facecolor='w'
# ),
alpha=.5,
fontsize=min_font_size,
arrowprops=dict(arrowstyle='-', alpha=.5))
# ax.set_ylim(-15,15LR)
import cartopy.mpl.geoaxes
ax: crt.mpl.geoaxes.GeoAxesSubplot
_xx, _yy = lon_range, lat_range
extent = get_extent(_xx, _yy)
ax.set_extent(extent, crt.crs.PlateCarree())
# plt.show()
return ax
def plot_pathways(npdf,
dac_sum,
conc_name,
lon_range=15,
lat_range=13,
centroid_to_plot=None,
chc_lp_legend=False,
q_level=.8,
ax_bolivia=True,
ax=None,
min_fs=5,
add_patch=True,
labs_to_plot='all',
background_alpha=0):
if centroid_to_plot is None:
centroid_to_plot = ['LR', 'MR']
if ax is None:
ucp.set_dpi(300)
f_width = 7.25
figsize = (f_width, f_width / 1.6)
_, ax = plt.subplots(subplot_kw=dict(projection=crt.crs.PlateCarree()),
figsize=figsize)
ax: plt.Axes
if ax_bolivia:
fa.get_ax_bolivia(
ax=ax,
plot_cities=False,
map_res='50m',
lake_face_color='none',
map_line_alpha=.5,
chc_lp_legend=chc_lp_legend,
grid_alpha=0,
draw_labels=False,
)
else:
fa.get_ax_lapaz(ax=ax,
plot_cities=False,
lake_face_color='none',
map_line_alpha=.5,
chc_lp_legend=chc_lp_legend,
grid_alpha=0,
draw_labels=False,
y_left_lab=False)
# gpdf = npdf.groupby('range')
for l, r in npdf.iterrows():
_q = q_level
l = r['cluster_i']
res = get_res_quan(dac_sum, l, _q, conc_name=conc_name)
pols = res.apply(lambda r: sh_polygon_from_row(r), axis=1)
u = cascaded_union(pols)
patch = PolygonPatch(u,
alpha=.7,
facecolor=r['c6_colors'],
edgecolor=r['c6_colors'],
linewidth=1,
zorder=11)
if add_patch:
ax.add_patch(patch)
npdf['text_xy'] = [[[0, 0]]] * len(npdf)
npdf.loc['07_LR', 'text_xy'] = [[[-5, -12]]]
npdf.loc['08_LR', 'text_xy'] = [[[-5, 7]]]
npdf.loc['10_LR', 'text_xy'] = [[[8, 0]]]
npdf.loc['11_MR', 'text_xy'] = [[[-13, 7]]]
npdf.loc['02_MR', 'text_xy'] = [[[-10, 7]]]
npdf.loc['04_MR', 'text_xy'] = [[[-10, 7]]]
npdf.loc['05_MR', 'text_xy'] = [[[5, -10]]]
npdf.loc['09_MR', 'text_xy'] = [[[-25, -8]]]
npdf.loc['08_SM', 'text_xy'] = [[[-23, -15]]]
npdf.loc['12_SM', 'text_xy'] = [[[-3, 7]]]
npdf.loc['03_SM', 'text_xy'] = [[[5, -4]]]
npdf.loc['06_SM', 'text_xy'] = [[[-7, -10]]]
npdf.loc['11_SR', 'text_xy'] = [[[-10, 7]]]
npdf.loc['02_SR', 'text_xy'] = [[[-3, 7]]]
npdf.loc['12_SR', 'text_xy'] = [[[-12, 7]]]
npdf.loc['04_SR', 'text_xy'] = [[[4, -10]]]
npdf.loc['07_SR', 'text_xy'] = [[[-17, -12]]]
npdf.loc['10_SR', 'text_xy'] = [[[-30, 0]]]
_x = npdf[co.R_CENTER] * np.sin(npdf[co.TH_CENTER])
_y = npdf[co.R_CENTER] * np.cos(npdf[co.TH_CENTER])
npdf['lat'] = _y + co.CHC_LAT
npdf['lon'] = _x + co.CHC_LON
lrpdf = npdf[npdf['range'].isin(centroid_to_plot)]
for l, r in lrpdf.iterrows():
ax.scatter(r['lon'],
r['lat'],
s=40,
c=[r['range_color']],
marker=r['range_marker'],
zorder=20,
edgecolors=['k'],
linewidth=1)
if labs_to_plot == 'all':
lab_lrpdf = lrpdf
else:
lab_lrpdf = npdf[npdf['range'].isin(labs_to_plot)]
for l, r in lab_lrpdf.iterrows():
ax.annotate(
r.name,
xy=r[['lon', 'lat']],
xytext=r['text_xy'][0],
textcoords='offset points',
zorder=12,
backgroundcolor=[1, 1, 1, background_alpha],
# bbox=dict(boxstyle="round",
# alpha=0,
# linewidth=0,
# facecolor='w'
# ),
alpha=.5,
fontsize=min_fs,
arrowprops=dict(arrowstyle='-', alpha=.5))
# ax.set_ylim(-15,15LR)
import cartopy.mpl.geoaxes
ax: crt.mpl.geoaxes.GeoAxesSubplot
_xx, _yy = lon_range, lat_range
extent = get_extent(_xx, _yy)
ax.set_extent(extent, crt.crs.PlateCarree())
# plt.show()
return ax
def clus_plot(
i_lab, ds: xr.Dataset,
conc_lab=None,
ds_lab=None,
figure_size=15,
dpi=400,
fig_title: str = None,
conc_lab_ts=None,
df_prop=None
):
if conc_lab is None:
conc_lab = ds.attrs['chosen_smooth']
if conc_lab_ts is None:
conc_lab_ts = conc_lab
r_dis_km: xr.DataArray = ds[co.R_CENTER] * 100
r_dis_km = r_dis_km.assign_attrs({
'units': 'km',
'long_name': 'radial distance from CHC'
})
# return r_dis_km
ds = ds.assign_coords(**{R_DIS_KM: r_dis_km})
if ds_lab is None:
ds_lab = ds[[conc_lab_ts, conc_lab]].where(ds['lab'] == i_lab)
ds_lab = ds_lab.assign_coords(**{R_DIS_KM: r_dis_km})
# print(ds_lab.attrs)
cols = 10
rows = 10
f_len = figure_size
f: plt.Figure = plt.figure(
figsize=(f_len, cols / rows * f_len),
dpi=dpi
)
xn = 2
yn = 4
xp = .07
yp = .05
ww = (1 - xp * 3) / xn
hh = (1 - yp * 5) / yn
# yy = .29
# xx = .4
# xxL = .55
# ypos = .35
l_lpb = ((2 * xp) + ww, (2 * yp) + hh, .8 * ww, hh)
l_bol = ((2 * xp) + ww, yp, .8 * ww, hh)
l_ts = (xp, 1 - yp - hh, 1 - 2 * xp, hh)
l_per_inf = (xp, (3 * yp) + (2 * hh), ww, hh)
l_far = (xp, yp, 1.2 * ww, hh)
l_zoom = (xp, 2 * yp + hh, 1.2 * ww, hh)
ax_vertical_far_: plt.Axes = f.add_axes(l_far)
da_lab = ds_lab[conc_lab]
da_lab.load()
plot_vertical_ax(ax_vertical_far_, conc_lab, ds, da_lab)
ax_vertical_far_.scatter(0, 5240, c='blue', label='CHC')
ax_vertical_far_.legend()
ax_vertical_far_.grid(True)
ax_vertical_far_.set_axisbelow(False)
ax_vertical_zoom = f.add_axes(l_zoom)
plot_vertical_ax(ax_vertical_zoom, conc_lab, ds, da_lab,
xlim=(0, 200))
ax_vertical_zoom.scatter(0, 5240, c='blue', label='CHC')
ax_vertical_zoom.legend()
ax_vertical_zoom.grid(True)
ax_vertical_zoom.set_axisbelow(False)
carree = crt.crs.PlateCarree()
ax_lpb: cartopy.mpl.geoaxes.GeoAxesSubplot = \
f.add_axes(l_lpb, projection=carree)
cc_ = da_lab.sum([co.RL, co.ZM], keep_attrs=True)
ax_lpb = fa.get_ax_lapaz(ax=ax_lpb)
print(cc_.attrs)
fa.logpolar_plot(cc_, name=conc_lab, ax=ax_lpb)
ax_bol = f.add_axes(l_bol, projection=carree)
lo_la_bol_range = 15
lo_la_limits = [
co.CHC_LON - lo_la_bol_range,
co.CHC_LON + lo_la_bol_range,
co.CHC_LAT - lo_la_bol_range,
co.CHC_LAT + lo_la_bol_range,
]
ax_bol = fa.get_ax_bolivia(ax=ax_bol, lola_extent=lo_la_limits)
fa.logpolar_plot(cc_, name=conc_lab, ax=ax_bol)
# noinspection PyUnusedLocal
ax_ts = f.add_axes(l_ts)
plot_lab_time_series(da_lab=ds_lab[conc_lab_ts], ax_ts=ax_ts)
ax_per_inf = f.add_axes(l_per_inf)
if df_prop is not None:
plot_cluster_summary_figure(
df_prop,
'SRR [%]',
'distance from CHC [km]',
# save_fig=True,
fig_save_name='dis_vs_srr_influence.pdf',
xy_locs=([-30, 5], [0, 9], [500, 11], [950, 9]),
y_range=(0, 13),
add_vertical_lines=True,
add_cluster_group_label=False,
ax=ax_per_inf
)
y = df_prop.set_index('cluster_i')['SRR [%]'][i_lab]
x = df_prop.set_index('cluster_i')['distance from CHC [km]'][i_lab]
# ax_per_inf.scatter(x,y,c='k',s=10,marker='o')
ax_per_inf.scatter(x, y, s=200, marker='o', facecolors='none',
edgecolors='k')
# todo fix this
else:
plot_concentration_influence_div_by_cluster(
ds=ds, conc_lab=conc_lab, i_lab=i_lab,
ax=ax_per_inf
)
plt.show()
if fig_title is None:
f.suptitle(f'cluster: {i_lab}', y=.95)
else:
f.suptitle(fig_title, y=1)
f.tight_layout()
log.ger.debug('show plot')
f.show()
return f