Series of Plots to Analyze Long Ariane Timeseries: Forward North¶
In [12]:
import arrow
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.cm as cmx
import matplotlib.colorbar as mcb
from matplotlib.patches import Ellipse
from matplotlib import gridspec
import netCDF4 as nc
import numpy as np
import os
import pandas as pd
from salishsea_tools import viz_tools
%matplotlib inline
SUBDIR_TMPL = '{:%d%b%y}'
results_dir = '/ocean/sallen/allen/research/MEOPAR/Ariane/Fluxes/StatsFiles/'
other_nan = ['********************']
In [13]:
startdate = []
runlength = []
startdate.append('2014-10-27')
runlength.append(5+30+31+365+31+29+13)
NUM = 5+30+31+365+31+29+13
Read the Results¶
In [14]:
rawstats = ['sn', 's0max', 's0min', 's0x', 's0x2', 's1max', 's1min', 's1x', 's1x2']
stat = {}
FraserRidge = pd.DataFrame(data=None, index=None,
columns=['date', 'longitude-mean', 'longitude-std', 'depth-mean', 'depth-stdev',
'salinity-mean', 'salinity-std', 'age-mean', 'age-stdev', 'flux'],
dtype=None, copy=False)
FraserRidgeIn = pd.DataFrame(data=None, index=None,
columns=['date', 'latitude-mean', 'latitude-std', 'depth-mean', 'depth-stdev',
'salinity-mean', 'salinity-std'],
dtype=None, copy=False)
Lost = pd.DataFrame(data=None, index=None,
columns=['date', 'flux'],
dtype=None, copy=False)
Discovery= pd.DataFrame(data=None, index=None,
columns=['date', 'flux'],
dtype=None, copy=False)
thedays = []
mean = np.zeros((5))
stdev = np.zeros((4))
In [15]:
line = 0
for segment in range(len(startdate)):
startrundate = arrow.get(startdate[segment], 'YYYY-MM-DD')
for nday in range(runlength[segment]):
rundate = startrundate.replace(days=+nday)
for stattype in rawstats:
stat[stattype] = pd.read_csv(os.path.join(results_dir,
stattype+'.'+SUBDIR_TMPL.format(rundate.datetime).lower()),
index_col=0, na_values=other_nan)
stat[stattype].index = [x.strip() for x in stat[stattype].index]
for i, parameter in enumerate(['depth', 'longitude', 'sal', 'age']):
themean = stat['s1x'][parameter]/stat['sn']['sn']
thestdev = np.sqrt(np.abs((stat['s1x2'][parameter] -
stat['s1x'][parameter]**2 / stat['sn']['sn'])
/ (stat['sn']['sn']-1)))
mean[i] = themean.FraserRidge
stdev[i] = thestdev.FraserRidge
mean[4] = stat['sn']['flux'].FraserRidge
lost = (stat['sn']['flux'].total - stat['sn']['flux'].meanders - mean[4]
- stat['sn']['flux'].Discovery)
FraserRidge.loc[line] = [rundate, mean[1], stdev[1], mean[0], stdev[0],
mean[2], stdev[2], mean[3], stdev[3], mean[4]]
Lost.loc[line] = [rundate, lost]
Discovery.loc[line] = [rundate, stat['sn']['flux'].Discovery]
for i, parameter in enumerate(['depth', 'latitude', 'sal']):
themean = stat['s0x'][parameter]/stat['sn']['sn']
thestdev = np.sqrt(np.abs((stat['s0x2'][parameter] -
stat['s0x'][parameter]**2 / stat['sn']['sn'])
/ (stat['sn']['sn']-1)))
mean[i] = themean.FraserRidge
stdev[i] = thestdev.FraserRidge
FraserRidgeIn.loc[line] = [rundate, mean[1], stdev[1], mean[0], stdev[0], mean[2], stdev[2]]
line = line + 1
FraserRidge =FraserRidge.set_index('date')
FraserRidgeIn =FraserRidgeIn.set_index('date')
Lost = Lost.set_index('date')
Discovery = Discovery.set_index('date')
In [16]:
times = np.array([FraserRidgeIn.index[i].datetime for i in range(NUM)])
dmax=190; dmin=0
vmax=31.5; vmin=28
fig, ax = plt.subplots(3,2, figsize=(15,15))
ax[0,0].plot_date(times, FraserRidgeIn['salinity-mean'],'-', linewidth=3)
ax[0,0].plot_date(times, FraserRidgeIn['salinity-mean']+FraserRidgeIn['salinity-std'],'g-')
ax[0,0].plot_date(times, FraserRidgeIn['salinity-mean']-FraserRidgeIn['salinity-std'],'g-')
ax[0,0].set_title('Salnity In')
ax[0,0].set_ylim(vmin, vmax)
ax[0,0].set_ylabel('Practical Salinity')
ax[0,1].plot_date(times, FraserRidge['salinity-mean'], '-', linewidth=3)
ax[0,1].plot_date(times, FraserRidge['salinity-mean']+FraserRidge['salinity-std'], 'g-')
ax[0,1].plot_date(times, FraserRidge['salinity-mean']-FraserRidge['salinity-std'], 'g-')
ax[0,1].set_title('Salinity at Fraser Ridge')
ax[0,1].set_ylim(vmin, vmax)
ax[1,0].plot_date(times, FraserRidgeIn['depth-mean'], '-', linewidth=3)
ax[1,0].plot_date(times, FraserRidgeIn['depth-mean']+FraserRidgeIn['depth-stdev'], 'g-')
ax[1,0].plot_date(times, FraserRidgeIn['depth-mean']-FraserRidgeIn['depth-stdev'], 'g-')
ax[1,0].set_title('Depth In')
ax[1,0].set_ylim(dmax, dmin)
ax[1,0].set_ylabel('Depth (m)')
ax[1,1].plot_date(times, FraserRidge['depth-mean'],'-', linewidth=3)
ax[1,1].plot_date(times, FraserRidge['depth-mean']+FraserRidge['depth-stdev'], 'g-')
ax[1,1].plot_date(times, FraserRidge['depth-mean']-FraserRidge['depth-stdev'], 'g-')
ax[1,1].set_title('Depth at Fraser Ridge')
ax[1,1].set_ylim(dmax, dmin)
ax[2,0].plot_date(times, FraserRidge['flux'],'-', linewidth=4, label='Fraser Ridge')
ax[2,0].plot_date(times, Lost['flux'], '-', label='Lost')
ax[2,0].plot_date(times, Discovery['flux'], '-', label='Discovery')
ax[2,0].legend()
ax[2,0].set_title('Flux')
ax[2,0].set_ylabel('Flux (m$^3$ s$^{-1}$)')
ax[2,1].plot_date(times, FraserRidge['age-mean']*15, '-', linewidth=3)
ax[2,1].plot_date(times, (FraserRidge['age-mean']+FraserRidge['age-stdev'])*15, 'g-')
ax[2,1].plot_date(times, (FraserRidge['age-mean']-FraserRidge['age-stdev'])*15, 'g-')
ax[2,1].set_title('Days from Boundary Pass')
ax[2,1].set_ylabel('Age (days)')
fig.autofmt_xdate()
In [17]:
times = np.array([FraserRidgeIn.index[i].datetime for i in range(NUM)])
fig, ax = plt.subplots(1,1, figsize=(15,5))
ax.plot_date(times, FraserRidge['flux'],'-', linewidth=2, label='Fraser Ridge')
#ax.plot_date(times, Discovery['flux'], '-', label='Rosario Strait', linewidth=2)
#ax.plot_date(times, Lost['flux'], '-', label='Lost')
#ax.legend(fontsize=14, loc='upper left')
ax.set_title('Flux from Boundary Pass to Fraser Ridge', fontsize=20)
ax.set_ylabel('Flux (m$^3$ s$^{-1}$)', fontsize=14)
ax.tick_params(labelsize=14)
fig.autofmt_xdate()
In [6]:
bathy = nc.Dataset('/ocean/sallen/allen/research/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc')
depths_raw = bathy.variables['Bathymetry'][:]
lons = bathy.variables['nav_lon'][:]
lats = bathy.variables['nav_lat'][:]
depths = depths_raw.filled(fill_value=0)
In [7]:
fig, ax = plt.subplots(1, 1, figsize=(10, 8))
aspect = viz_tools.set_aspect(ax, coords='map', lats=lats)
cmap = plt.get_cmap('winter_r')
cmap.set_bad('burlywood')
mesh = ax.pcolormesh(lons[:], lats[:], depths_raw[:], cmap=cmap)
cbar = fig.colorbar(mesh)
plt.axis((-123.7, -122.5, 48.5, 49.2))
ax.plot(lons[417-1,244-1:311-1], lats[417-1,244-1:311-1], 'or')
ax.plot(lons[320-1:348-1,283-1], lats[320-1:348-1,283-1], 'or')
ax.plot(lons[312-1,314-1:339-1], lats[312-1,314-1:339-1], 'or', alpha=0.3)
Out[7]:
[<matplotlib.lines.Line2D at 0x7f54726421d0>]
In [8]:
xlims = (-123.518, -123.2)
depthmax = 250
emin = 0; emax=11e4
cNorm = colors.Normalize(vmin=vmin, vmax=vmax)
eNorm = colors.Normalize(vmin=emin, vmax=emax)
cmap = 'plasma'
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cmap)
eMap = cmx.ScalarMappable(norm=eNorm, cmap=cmap)
Z = [[vmin,vmin],[vmax,vmax]]
strick = plt.contourf(Z, cmap=cmap)
plt.clf()
Z = [[emin,emin],[emax,emax]]
etrick = plt.contourf(Z, cmap=cmap)
plt.clf()
fig, ax = plt.subplots(1, 2, figsize=(20,10))
ax[0].fill_between(lons[417-1,:], depthmax, depths[417-1,:], color='burlywood')
ax[1].fill_between(lons[417-1,:], depthmax, depths[417-1,:], color='burlywood')
ells = [Ellipse(xy=(FraserRidge['longitude-mean'][i], FraserRidge['depth-mean'][i]),
width=2*FraserRidge['longitude-std'][i],
height=2*FraserRidge['depth-stdev'][i],
alpha=(FraserRidge['salinity-mean'][i]-vmin)/(vmax-vmin),
facecolor=scalarMap.to_rgba(FraserRidge['salinity-mean'][i])
)
for i in range(NUM)]
for e in ells:
ax[0].add_artist(e)
ells = [Ellipse(xy=(FraserRidge['longitude-mean'][i], FraserRidge['depth-mean'][i]),
width=2*FraserRidge['longitude-std'][i],
height=2*FraserRidge['depth-stdev'][i],
alpha=(FraserRidge['flux'][i]-emin)/(emax-emin),
facecolor=eMap.to_rgba(FraserRidge['flux'][i])
)
for i in range(NUM)]
for e in ells:
ax[1].add_artist(e)
ax[0].set_ylim((0, 250))
ax[0].set_xlim(xlims)
ax[0].invert_yaxis()
fig.colorbar(strick, ax=ax[0], label='Practical Salinity')
ax[1].set_ylim((0, 250))
ax[1].set_xlim(xlims)
ax[1].invert_yaxis()
fig.colorbar(etrick, ax=ax[1], label='Flux (m$^3$ s$^{-1}$)')
for ax in [ax[0], ax[1]]:
ax.set_ylabel('Depth (m)')
ax.set_xlabel('Longitude at Fraser Ridge')
<matplotlib.figure.Figure at 0x7f547255ce48>
In [13]:
smax=32.; smin=27.5
cNorm = colors.Normalize(vmin=smin, vmax=smax)
cmap = 'viridis_r'
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cmap)
Z = [[smin,smin],[smax,smax]]
strick = plt.contourf(Z, cmap=cmap)
plt.clf()
ax = []
fig = plt.figure(figsize=(20*3.1/4.7*0.92, 7.5))
gs = gridspec.GridSpec(1, 2, width_ratios=[1, 1.5/2.3*6.5/5.*0.95])
ax.append(plt.subplot(gs[0]))
ax.append(plt.subplot(gs[1]))
ax[0].fill_between(lons[417-1,:], depthmax, depths[417-1,:], color='burlywood')
ells = Ellipse(xy=(np.mean(FraserRidge['longitude-mean']), np.mean(FraserRidge['depth-mean'][i])),
width=2*np.mean(FraserRidge['longitude-std']),
height=2*np.mean(FraserRidge['depth-stdev']),
facecolor=scalarMap.to_rgba(np.mean(FraserRidge['salinity-mean'])))
ax[0].add_artist(ells)
print (np.mean(FraserRidge['salinity-mean']))
print (np.mean(FraserRidge['flux']), np.mean(FraserRidge['flux'])/3500.)
ax[0].set_ylim((0, 250))
xlims = (-123.518, -123.2)
print (xlims[1]-xlims[0])
print (5.2/3.3, 2.3/1.5)
ax[0].set_xlim(xlims)
ax[0].invert_yaxis()
ax[1].fill_between(lats[:,283-1], depthmax, depths[:,283-1], color='burlywood')
ells = Ellipse(xy=(np.mean(FraserRidgeIn['latitude-mean']), np.mean(FraserRidgeIn['depth-mean'])),
width=2*np.mean(FraserRidgeIn['latitude-std']),
height=2*np.mean(FraserRidgeIn['depth-stdev']),
facecolor = scalarMap.to_rgba(np.mean(FraserRidgeIn['salinity-mean'])))
ax[1].add_artist(ells)
print (np.mean(FraserRidgeIn['salinity-mean']))
cbar = fig.colorbar(strick, ax=ax[1], label='Practical Salinity')
xlims = (48.65, 48.78)
print (xlims[1]-xlims[0])
ax[1].set_ylim((0, 250))
ax[1].set_xlim(xlims)
ax[1].invert_yaxis()
ax[0].tick_params(labelsize=14)
ax[1].tick_params(labelsize=14)
cbar.ax.tick_params(labelsize=14)
ax[1].set_xlabel('Latitude', fontsize=14)
ax[0].set_xlabel('Longitude', fontsize=14)
ax[0].set_xticks([-123.5, -123.4, -123.3])
ax[0].set_xticklabels(['-123.5', '-123.4', '-123.3'])
ax[0].set_ylabel('Depth (m)', fontsize=14)
ax[0].set_title('Fraser Ridge', fontsize=20)
ax[1].set_title('Boundary Pass', fontsize=20)
ax[1].set_xticks([48.65, 48.7, 48.75])
ax[1].set_xticklabels(['48.65', '48.7', '48.75'])
print (np.mean(FraserRidge['age-mean'])*15.)
print (np.mean(Discovery['flux'])/3500.)
print ('depth', np.mean(FraserRidge['depth-mean']))
print ('depth, std', np.mean(FraserRidge['depth-stdev']))
print ('depthin', np.mean(FraserRidgeIn['depth-mean']))
print ('depthin, std', np.mean(FraserRidgeIn['depth-stdev']))
29.56911177985771 43248.23420734126 12.356638344954645 0.31799999999999784 1.575757575757576 1.5333333333333332 29.86031706636325 0.13000000000000256 6.827391450683564 5.950144105385482 depth 86.08588258013523 depth, std 34.66652817449455 depthin 83.38029862965736 depthin, std 47.91091419866756
<matplotlib.figure.Figure at 0x7f5472e9bb00>
In [ ]:
In [10]:
fig, ax = plt.subplots(1, 2, figsize=(20,10))
xlims = (48.65, 48.78)
depthmax = 250
ax[0].fill_between(lats[:,283-1], depthmax, depths[:,283-1], color='burlywood')
ax[1].fill_between(lats[:,283-1], depthmax, depths[:,283-1], color='burlywood')
ells = [Ellipse(xy=(FraserRidgeIn['latitude-mean'][i], FraserRidgeIn['depth-mean'][i]),
width=2*FraserRidgeIn['latitude-std'][i],
height=2*FraserRidgeIn['depth-stdev'][i],
alpha=(FraserRidgeIn['salinity-mean'][i]-vmin)/(vmax-vmin),
facecolor = scalarMap.to_rgba(FraserRidgeIn['salinity-mean'][i])
)
for i in range(NUM)]
for e in ells:
ax[0].add_artist(e)
ells = [Ellipse(xy=(FraserRidgeIn['latitude-mean'][i], FraserRidgeIn['depth-mean'][i]),
width=2*FraserRidgeIn['latitude-std'][i],
height=2*FraserRidgeIn['depth-stdev'][i],
alpha=(FraserRidge['flux'][i]-emin)/(emax-emin),
facecolor=eMap.to_rgba(FraserRidge['flux'][i])
)
for i in range(NUM)]
for e in ells:
ax[1].add_artist(e)
ax[0].set_ylim((0, 250))
ax[0].set_xlim(xlims)
ax[0].invert_yaxis()
fig.colorbar(strick, ax=ax[0], label='Practical Salinity')
ax[0].plot(lats[341-1, 283-1], 10.,'go', markersize=10)
print (lats[341-1, 283-1])
ax[1].set_ylim((0, 250))
ax[1].set_xlim(xlims)
ax[1].invert_yaxis()
fig.colorbar(etrick, ax=ax[1], label='Flux (m$^3$ s$^{-1}$)')
for ax in [ax[0], ax[1]]:
ax.set_ylabel('Depth (m)')
ax.set_xlabel('Latitude Across Boundary Pass')
48.7403106689
In [11]:
at = 5+30+31+31+28+31+30; mt=at+31+3; st=mt+3; et=-1
fig, ax = plt.subplots(3, 3, figsize=(15,15))
ax[0,0].plot(FraserRidge['flux'][st:et], FraserRidge['depth-mean'][st:et], 'o')
ax[0,0].plot(FraserRidge['flux'][:at], FraserRidge['depth-mean'][:at], 'g^')
ax[0,0].plot(FraserRidge['flux'][at:mt], FraserRidge['depth-mean'][at:mt], 'ro')
ax[0,0].plot(FraserRidge['flux'][mt:st], FraserRidge['depth-mean'][mt:st], 'g>')
ax[0,0].invert_yaxis()
ax[0,0].set_ylabel('Depth at Fraser Ridge(m)')
ax[1,0].plot(FraserRidge['flux'][st:et], FraserRidge['salinity-mean'][st:et], 'o')
ax[1,0].plot(FraserRidge['flux'][:at], FraserRidge['salinity-mean'][:at], 'g^')
ax[1,0].plot(FraserRidge['flux'][at:mt], FraserRidge['salinity-mean'][at:mt], 'ro')
ax[1,0].plot(FraserRidge['flux'][mt:st], FraserRidge['salinity-mean'][mt:st], 'g>')
ax[2,0].set_xlabel('Flux (m$^3$ s$^{-1}$)')
ax[1,0].set_ylabel('Practical Salinity at Fraser Ridge')
ax[0,1].plot(FraserRidge['age-mean'][st:et]*15, FraserRidge['depth-mean'][st:et], 'o')
ax[0,1].plot(FraserRidge['age-mean'][:at]*15, FraserRidge['depth-mean'][:at], 'g^')
ax[0,1].plot(FraserRidge['age-mean'][at:mt]*15, FraserRidge['depth-mean'][at:mt], 'ro')
ax[0,1].plot(FraserRidge['age-mean'][mt:st]*15, FraserRidge['depth-mean'][mt:st], 'g>')
ax[0,1].invert_yaxis()
ax[1,1].plot(FraserRidge['age-mean'][st:et]*15, FraserRidge['salinity-mean'][st:et], 'o')
ax[1,1].plot(FraserRidge['age-mean'][:at]*15, FraserRidge['salinity-mean'][:at], 'g^')
ax[1,1].plot(FraserRidge['age-mean'][at:mt]*15, FraserRidge['salinity-mean'][at:mt], 'ro')
ax[1,1].plot(FraserRidge['age-mean'][mt:st]*15, FraserRidge['salinity-mean'][mt:st], 'g>')
ax[1,1].set_xlabel('Age (days)')
ax[0,2].plot(FraserRidge['salinity-mean'][st:et], FraserRidge['depth-mean'][st:et], 'o')
ax[0,2].plot(FraserRidge['salinity-mean'][:at], FraserRidge['depth-mean'][:at], 'g^')
ax[0,2].plot(FraserRidge['salinity-mean'][at:mt], FraserRidge['depth-mean'][at:mt], 'ro')
ax[0,2].plot(FraserRidge['salinity-mean'][mt:st], FraserRidge['depth-mean'][mt:st], 'g>')
ax[0,2].set_xlabel('Practical Salinity at Fraser Ridge')
ax[0,2].invert_yaxis()
ax[2,0].plot(FraserRidge['flux'][st:et], FraserRidge['age-mean'][st:et]*15, 'o')
ax[2,0].plot(FraserRidge['flux'][:at], FraserRidge['age-mean'][:at]*15, 'g^')
ax[2,0].plot(FraserRidge['flux'][at:mt], FraserRidge['age-mean'][at:mt]*15, 'ro')
ax[2,0].plot(FraserRidge['flux'][mt:st], FraserRidge['age-mean'][mt:st]*15, 'g>')
ax[2,0].set_ylabel('Age (days)')
ax[1,2].axis('off')
ax[2,1].axis('off')
ax[2,2].axis('off')
Out[11]:
(0.0, 1.0, 0.0, 1.0)
In [ ]: