In [1]:

%reset
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import xarray as xr

%matplotlib inline
plt.rcParams['image.cmap'] = 'jet'

Once deleted, variables cannot be recovered. Proceed (y/[n])? y

In [2]:

nowcast_tracer_path = "/results/SalishSea/nowcast-green/12apr16/SalishSea_1h_20160412_20160412_ptrc_T.nc"
diat_iopt_84_tracer_path = "/data/jpetrie/MEOPAR/SalishSea/results/apr12_double_iopt_diat/SalishSea_1h_20160412_20160412_ptrc_T.nc"
diat_iopt_55_tracer_path = "/data/jpetrie/MEOPAR/SalishSea/results/april12_55_iopt_diat/SalishSea_1h_20160412_20160412_ptrc_T.nc"

n_grid_t = xr.open_dataset(nowcast_tracer_path)
#m_grid_t = xr.open_dataset(diat_iopt_84_tracer_path)
m_grid_t = xr.open_dataset(diat_iopt_55_tracer_path)

In [6]:

n_grid_t.votemper

Out[6]:

<xarray.DataArray 'votemper' (time_counter: 24, deptht: 40, y: 898, x: 398)>
[343107840 values with dtype=float64]
Coordinates:
  * deptht         (deptht) float32 0.5 1.5 2.50001 3.50003 4.50007 5.50015 ...
    nav_lat        (y, x) float32 46.8597 46.8615 46.8634 46.8653 46.8672 ...
    nav_lon        (y, x) float32 -123.429 -123.424 -123.419 -123.413 ...
    time_centered  (time_counter) datetime64[ns] 2016-04-12T00:30:00 ...
  * time_counter   (time_counter) datetime64[ns] 2016-04-12T00:30:00 ...
  * x              (x) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 ...
  * y              (y) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 ...
Attributes:
    standard_name: sea_water_potential_temperature
    long_name: temperature
    units: degC
    online_operation: average
    interval_operation: 40 s
    interval_write: 1 h
    cell_methods: time: mean (interval: 40 s)
    cell_measures: area: area

In [ ]:

m_grid_t.PHY

In [ ]:

NO3_subset_20m = ((m_grid_t["NO3"] - n_grid_t["NO3"]).where(m_grid_t["O2"] != 0).isel(deptht = 18, time_counter = 23))

In [ ]:

fig, ax = plt.subplots(1,1, figsize = (15,15))
NO3_subset_20m.plot(ax = ax, cmap = "jet", robust = True)
plt.title("NO3(Iopt_diat=55) - NO3(Iopt_diat=42) After 1 Day at Depth=20m ", size = 35)

In [ ]:

NO3_subset_0m = ((m_grid_t["NO3"] - n_grid_t["NO3"]).where(m_grid_t["O2"] != 0).isel(deptht = 0, time_counter = 23))

In [ ]:

fig, ax = plt.subplots(1,1, figsize = (15,15))
NO3_subset_0m.plot(ax = ax, cmap = "jet", robust = True)
plt.title("NO3(Iopt_diat=55) - NO3(Iopt_diat=42) After 1 Day at Depth=0m ", size = 35)

In [ ]:

PHY2_subset_20m = ((m_grid_t["PHY2"] - n_grid_t["PHY2"]).where(m_grid_t["O2"] != 0).isel(deptht = 19, time_counter = 23))

In [ ]:

fig, ax = plt.subplots(1,1, figsize = (15,15))
PHY2_subset_20m.plot(ax = ax, cmap = "jet", robust = True)
plt.title("PHY2(Iopt_diat=55) - PHY2(Iopt_diat=42) After 1 Day at Depth=20m ", size = 35)

In [ ]:

PHY2_subset_0m = ((m_grid_t["PHY2"] - n_grid_t["PHY2"]).where(m_grid_t["O2"] != 0).isel(deptht = 0, time_counter = 23))

In [ ]:

fig, ax = plt.subplots(1,1, figsize = (15,15))
PHY2_subset_0m.plot(ax = ax, cmap = "jet", robust = True)
plt.title("PHY2(Iopt_diat=55) - PHY2(Iopt_diat=42) After 1 Day at Depth=0m ", size = 35)

In [4]:

# Have to keep this and the next cell apart or it fails with memory error. Something to do with 
# Jupyter notebook caching
tracer = "PHY2"
mod_tracer_depth_time =  m_grid_t[tracer].where(m_grid_t[tracer] != 0).mean(dim = ["x","y"]).to_dataframe(name = "MEAN_" + tracer)

In [5]:

now_tracer_depth_time =  n_grid_t[tracer].where(n_grid_t[tracer] != 0).mean(dim = ["x","y"]).to_dataframe(name = "MEAN_" + tracer)
var_name = "MEAN_" + tracer

In [6]:

mod_tracer_depth_time["DATA_SOURCE"] = "IOPT DIAT = 55"
now_tracer_depth_time["DATA_SOURCE"] = "IOPT DIAT = 42"
combined = pd.concat([mod_tracer_depth_time, now_tracer_depth_time])
combined.reset_index(inplace=True)

In [7]:

%load_ext rpy2.ipython

In [9]:

%%R 
require(ggplot2)
require(data.table)
library(repr)

---------------------------------------------------------------------------
RRuntimeError                             Traceback (most recent call last)
<ipython-input-9-2765bc9a58c7> in <module>()
----> 1 get_ipython().run_cell_magic('R', '', 'require(ggplot2)\nrequire(data.table)\nlibrary(repr)')

/home/jpetrie/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py in run_cell_magic(self, magic_name, line, cell)
   2118             magic_arg_s = self.var_expand(line, stack_depth)
   2119             with self.builtin_trap:
-> 2120                 result = fn(magic_arg_s, cell)
   2121             return result
   2122 

<decorator-gen-128> in R(self, line, cell, local_ns)

/home/jpetrie/anaconda3/lib/python3.5/site-packages/IPython/core/magic.py in <lambda>(f, *a, **k)
    191     # but it's overkill for just that one bit of state.
    192     def magic_deco(arg):
--> 193         call = lambda f, *a, **k: f(*a, **k)
    194 
    195         if callable(arg):

/home/jpetrie/anaconda3/lib/python3.5/site-packages/rpy2/ipython/rmagic.py in R(self, line, cell, local_ns)
    663                     ro.r.assign(input, localconverter.py2ri(val))
    664 
--> 665         tmpd = self.setup_graphics(args)
    666 
    667         text_output = ''

/home/jpetrie/anaconda3/lib/python3.5/site-packages/rpy2/ipython/rmagic.py in setup_graphics(self, args)
    413                 # Note: that %% is to pass into R for interpolation there
    414                 ro.r.png("%s/Rplots%%03d.png" % tmpd_fix_slashes,
--> 415                         **argdict)
    416             elif self.device == 'svg':
    417                 self.cairo.CairoSVG("%s/Rplot.svg" % tmpd_fix_slashes,

/home/jpetrie/anaconda3/lib/python3.5/site-packages/rpy2/robjects/functions.py in __call__(self, *args, **kwargs)
    176                 v = kwargs.pop(k)
    177                 kwargs[r_k] = v
--> 178         return super(SignatureTranslatedFunction, self).__call__(*args, **kwargs)
    179 
    180 pattern_link = re.compile(r'\\link\{(.+?)\}')

/home/jpetrie/anaconda3/lib/python3.5/site-packages/rpy2/robjects/functions.py in __call__(self, *args, **kwargs)
    104         for k, v in kwargs.items():
    105             new_kwargs[k] = conversion.py2ri(v)
--> 106         res = super(Function, self).__call__(*new_args, **new_kwargs)
    107         res = conversion.ri2ro(res)
    108         return res

RRuntimeError: Error in .External2(C_X11, paste("png::", filename, sep = ""), g$width,  : 
  unable to start device PNG

In [18]:

%%R -i combined,var_name -h 1200 -w 1500 -r 400
combined = data.table(combined)
ggplot(combined[deptht < 25 & time_counter == max(time_counter) ], aes_string(y = "deptht", x = var_name, colour = "DATA_SOURCE")) + 
    geom_path() + ylim(25,0) +
    facet_wrap(~time_counter) +
    ylab("Depth (m)") + 
    xlab("Phytoplankton (mmolN/m^3)")

In [3]:

# Have to keep this and the next cell apart or it fails with memory error. Something to do with 
# Jupyter notebook caching
tracer = "NO3"
mod_tracer_depth_time =  m_grid_t[tracer].where(m_grid_t["O2"] != 0).mean(dim = ["x","y"]).to_dataframe(name = "MEAN_" + tracer)

In [4]:

now_tracer_depth_time =  n_grid_t[tracer].where(m_grid_t["O2"] != 0).mean(dim = ["x","y"]).to_dataframe(name = "MEAN_" + tracer)
var_name = "MEAN_" + tracer

In [17]:

mod_tracer_depth_time["DATA_SOURCE"] = "IOPT_DIAT_55"
now_tracer_depth_time["DATA_SOURCE"] = "IOPT_DIAT_42"
combined = pd.concat([mod_tracer_depth_time, now_tracer_depth_time])
combined.reset_index(inplace=True)

In [10]:

fg = sns.FacetGrid(data=combined, hue="DATA_SOURCE")
fg.map(plt.plot,"deptht", var_name).add_legend()

Out[10]:

<seaborn.axisgrid.FacetGrid at 0x7f24d81a0048>

In [29]:

%%R
ggplot(combined, aes(x = ))

---------------------------------------------------------------------------
RRuntimeError                             Traceback (most recent call last)
<ipython-input-29-f8881ecb569a> in <module>()
----> 1 get_ipython().run_cell_magic('R', '', 'wide_combined[, DIF := IOPT_DIAT_55 - IOPT_DIAT_42]')

/home/jpetrie/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py in run_cell_magic(self, magic_name, line, cell)
   2118             magic_arg_s = self.var_expand(line, stack_depth)
   2119             with self.builtin_trap:
-> 2120                 result = fn(magic_arg_s, cell)
   2121             return result
   2122 

<decorator-gen-128> in R(self, line, cell, local_ns)

/home/jpetrie/anaconda3/lib/python3.5/site-packages/IPython/core/magic.py in <lambda>(f, *a, **k)
    191     # but it's overkill for just that one bit of state.
    192     def magic_deco(arg):
--> 193         call = lambda f, *a, **k: f(*a, **k)
    194 
    195         if callable(arg):

/home/jpetrie/anaconda3/lib/python3.5/site-packages/rpy2/ipython/rmagic.py in R(self, line, cell, local_ns)
    680                     old_writeconsole_regular = ri.get_writeconsole_regular()
    681                     ri.set_writeconsole_regular(self.write_console_regular)
--> 682                     ro.r.show(result)
    683                     text_output += self.flush()
    684                     ri.set_writeconsole_regular(old_writeconsole_regular)

/home/jpetrie/anaconda3/lib/python3.5/site-packages/rpy2/robjects/functions.py in __call__(self, *args, **kwargs)
    176                 v = kwargs.pop(k)
    177                 kwargs[r_k] = v
--> 178         return super(SignatureTranslatedFunction, self).__call__(*args, **kwargs)
    179 
    180 pattern_link = re.compile(r'\\link\{(.+?)\}')

/home/jpetrie/anaconda3/lib/python3.5/site-packages/rpy2/robjects/functions.py in __call__(self, *args, **kwargs)
    104         for k, v in kwargs.items():
    105             new_kwargs[k] = conversion.py2ri(v)
--> 106         res = super(Function, self).__call__(*new_args, **new_kwargs)
    107         res = conversion.ri2ro(res)
    108         return res

RRuntimeError: Error in SYS[[length(SYS) - 3L]][[1L]] == "knit_print.default" : 
  comparison (1) is possible only for atomic and list types

In [3]:

%%R -i combined,var_name -h 4200 -w 2400 -r 400
combined = data.table(combined)
ggplot(combined[deptht < 25,], aes_string(y = "deptht", x = var_name)) + 
    geom_path() + ylim(25,0) +
    facet_wrap(~time_counter, ncol = 3)

ERROR: Cell magic `%%R` not found.

In [36]:

combined

Out[36]:

	time_counter	deptht	time_centered	MEAN_NO3	DATA_SOURCE
0	2016-04-12 00:30:00	0.500000	2016-04-12 00:30:00	5.214778	IOPT_DIAT_55
1	2016-04-12 00:30:00	1.500003	2016-04-12 00:30:00	5.452885	IOPT_DIAT_55
2	2016-04-12 00:30:00	2.500011	2016-04-12 00:30:00	5.486822	IOPT_DIAT_55
3	2016-04-12 00:30:00	3.500031	2016-04-12 00:30:00	5.594474	IOPT_DIAT_55
4	2016-04-12 00:30:00	4.500071	2016-04-12 00:30:00	5.920553	IOPT_DIAT_55
5	2016-04-12 00:30:00	5.500151	2016-04-12 00:30:00	6.151240	IOPT_DIAT_55
6	2016-04-12 00:30:00	6.500310	2016-04-12 00:30:00	6.447138	IOPT_DIAT_55
7	2016-04-12 00:30:00	7.500623	2016-04-12 00:30:00	6.792811	IOPT_DIAT_55
8	2016-04-12 00:30:00	8.501236	2016-04-12 00:30:00	7.200050	IOPT_DIAT_55
9	2016-04-12 00:30:00	9.502433	2016-04-12 00:30:00	7.727039	IOPT_DIAT_55
10	2016-04-12 00:30:00	10.504766	2016-04-12 00:30:00	8.421840	IOPT_DIAT_55
11	2016-04-12 00:30:00	11.509312	2016-04-12 00:30:00	9.241469	IOPT_DIAT_55
12	2016-04-12 00:30:00	12.518167	2016-04-12 00:30:00	10.177139	IOPT_DIAT_55
13	2016-04-12 00:30:00	13.535412	2016-04-12 00:30:00	11.197317	IOPT_DIAT_55
14	2016-04-12 00:30:00	14.568982	2016-04-12 00:30:00	12.282061	IOPT_DIAT_55
15	2016-04-12 00:30:00	15.634288	2016-04-12 00:30:00	13.473866	IOPT_DIAT_55
16	2016-04-12 00:30:00	16.761173	2016-04-12 00:30:00	14.781768	IOPT_DIAT_55
17	2016-04-12 00:30:00	18.007135	2016-04-12 00:30:00	16.144154	IOPT_DIAT_55
18	2016-04-12 00:30:00	19.481785	2016-04-12 00:30:00	17.475997	IOPT_DIAT_55
19	2016-04-12 00:30:00	21.389978	2016-04-12 00:30:00	18.891814	IOPT_DIAT_55
20	2016-04-12 00:30:00	24.100256	2016-04-12 00:30:00	20.516083	IOPT_DIAT_55
21	2016-04-12 00:30:00	28.229916	2016-04-12 00:30:00	22.333914	IOPT_DIAT_55
22	2016-04-12 00:30:00	34.685757	2016-04-12 00:30:00	24.324998	IOPT_DIAT_55
23	2016-04-12 00:30:00	44.517723	2016-04-12 00:30:00	26.184282	IOPT_DIAT_55
24	2016-04-12 00:30:00	58.484333	2016-04-12 00:30:00	27.685490	IOPT_DIAT_55
25	2016-04-12 00:30:00	76.585587	2016-04-12 00:30:00	28.915714	IOPT_DIAT_55
26	2016-04-12 00:30:00	98.062958	2016-04-12 00:30:00	29.956416	IOPT_DIAT_55
27	2016-04-12 00:30:00	121.866516	2016-04-12 00:30:00	30.934335	IOPT_DIAT_55
28	2016-04-12 00:30:00	147.089462	2016-04-12 00:30:00	31.828866	IOPT_DIAT_55
29	2016-04-12 00:30:00	173.114487	2016-04-12 00:30:00	32.697370	IOPT_DIAT_55
...	...	...	...	...	...
1890	2016-04-12 23:30:00	10.504766	2016-04-12 23:30:00	8.792402	IOPT_DIAT_42
1891	2016-04-12 23:30:00	11.509312	2016-04-12 23:30:00	9.443269	IOPT_DIAT_42
1892	2016-04-12 23:30:00	12.518167	2016-04-12 23:30:00	10.178115	IOPT_DIAT_42
1893	2016-04-12 23:30:00	13.535412	2016-04-12 23:30:00	10.986300	IOPT_DIAT_42
1894	2016-04-12 23:30:00	14.568982	2016-04-12 23:30:00	11.851626	IOPT_DIAT_42
1895	2016-04-12 23:30:00	15.634288	2016-04-12 23:30:00	12.771132	IOPT_DIAT_42
1896	2016-04-12 23:30:00	16.761173	2016-04-12 23:30:00	13.818082	IOPT_DIAT_42
1897	2016-04-12 23:30:00	18.007135	2016-04-12 23:30:00	15.014769	IOPT_DIAT_42
1898	2016-04-12 23:30:00	19.481785	2016-04-12 23:30:00	16.283267	IOPT_DIAT_42
1899	2016-04-12 23:30:00	21.389978	2016-04-12 23:30:00	17.844842	IOPT_DIAT_42
1900	2016-04-12 23:30:00	24.100256	2016-04-12 23:30:00	19.783106	IOPT_DIAT_42
1901	2016-04-12 23:30:00	28.229916	2016-04-12 23:30:00	21.978578	IOPT_DIAT_42
1902	2016-04-12 23:30:00	34.685757	2016-04-12 23:30:00	24.191177	IOPT_DIAT_42
1903	2016-04-12 23:30:00	44.517723	2016-04-12 23:30:00	26.089551	IOPT_DIAT_42
1904	2016-04-12 23:30:00	58.484333	2016-04-12 23:30:00	27.568494	IOPT_DIAT_42
1905	2016-04-12 23:30:00	76.585587	2016-04-12 23:30:00	28.797396	IOPT_DIAT_42
1906	2016-04-12 23:30:00	98.062958	2016-04-12 23:30:00	29.944437	IOPT_DIAT_42
1907	2016-04-12 23:30:00	121.866516	2016-04-12 23:30:00	31.001501	IOPT_DIAT_42
1908	2016-04-12 23:30:00	147.089462	2016-04-12 23:30:00	31.909937	IOPT_DIAT_42
1909	2016-04-12 23:30:00	173.114487	2016-04-12 23:30:00	32.749400	IOPT_DIAT_42
1910	2016-04-12 23:30:00	199.573044	2016-04-12 23:30:00	33.508556	IOPT_DIAT_42
1911	2016-04-12 23:30:00	226.260300	2016-04-12 23:30:00	34.428200	IOPT_DIAT_42
1912	2016-04-12 23:30:00	253.066635	2016-04-12 23:30:00	35.240501	IOPT_DIAT_42
1913	2016-04-12 23:30:00	279.934540	2016-04-12 23:30:00	36.002680	IOPT_DIAT_42
1914	2016-04-12 23:30:00	306.834198	2016-04-12 23:30:00	36.545321	IOPT_DIAT_42
1915	2016-04-12 23:30:00	333.750183	2016-04-12 23:30:00	36.801954	IOPT_DIAT_42
1916	2016-04-12 23:30:00	360.674530	2016-04-12 23:30:00	37.012192	IOPT_DIAT_42
1917	2016-04-12 23:30:00	387.603210	2016-04-12 23:30:00	37.074555	IOPT_DIAT_42
1918	2016-04-12 23:30:00	414.534088	2016-04-12 23:30:00	37.063028	IOPT_DIAT_42
1919	2016-04-12 23:30:00	441.466095	2016-04-12 23:30:00	NaN	IOPT_DIAT_42

1920 rows × 5 columns

In [ ]: