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WIP - Pep8 style changes #335

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WIP - Pep8 style changes #335

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8aeb990
put tc_activity in PEP8 style
burlen Feb 21, 2020
5d01591
put tc_trajectory_scalars in PEP8 style
burlen Feb 21, 2020
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120 changes: 69 additions & 51 deletions alg/teca_tc_activity.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,20 +2,26 @@
import teca_py
import numpy as np


class teca_tc_activity(teca_py.teca_python_algorithm):
"""
Computes summary statistics, histograms on sorted, classified,
TC trajectory output.
"""
def __init__(self):
# defer import so that user may select a backend
global plt, plt_mp, plt_tick
import matplotlib.pyplot as plt
import matplotlib.patches as plt_mp
import matplotlib.ticker as plt_tick
self.basename = 'activity'
self.dpi = 100
self.interactive = False
self.rel_axes = True
self.color_map = None

def __str__(self):
return 'basename=%s, dpi=%d, interactive=%s, rel_axes=%s'%( \
return 'basename=%s, dpi=%d, interactive=%s, rel_axes=%s' % (
self.basename, self.dpi, str(self.interactive), str(self.rel_axes))

def set_basename(self, basename):
Expand Down Expand Up @@ -58,13 +64,8 @@ def execute(self, port, data_in, req):
and plots. returns summary table with counts of annual
storms and their categories.
"""
global plt
global plt_mp
global plt_tick

import matplotlib.pyplot as plt
import matplotlib.patches as plt_mp
import matplotlib.ticker as plt_tick
if plt is None:
raise RuntimeError('Missing Python module matplotlib')

# store matplotlib state we modify
legend_frame_on_orig = plt.rcParams['legend.frameon']
Expand Down Expand Up @@ -102,27 +103,27 @@ def execute(self, port, data_in, req):
n_year = len(uyear)
ureg = sorted(set(zip(region_id, region_name, region_long_name)))

self.accum_by_year_and_region(uyear, \
ureg, year, region_id, start_y, ACE, regional_ACE)
self.accum_by_year_and_region(uyear, ureg, year, region_id,
start_y, ACE, regional_ACE)

self.accum_by_year_and_region(uyear, \
ureg, year, region_id, start_y, PDI, regional_PDI)
self.accum_by_year_and_region(uyear, ureg, year, region_id,
start_y, PDI, regional_PDI)

# now plot the organized data in various ways
if self.color_map is None:
self.color_map = plt.cm.jet

self.plot_individual(uyear, \
ureg, regional_ACE,'ACE', '$10^4 kn^2$')
self.plot_individual(uyear, ureg, regional_ACE,
'ACE', '$10^4 kn^2$')

self.plot_individual(uyear, \
ureg, regional_PDI, 'PDI', '$m^3 s^{-2}$')
self.plot_individual(uyear, ureg, regional_PDI,
'PDI', '$m^3 s^{-2}$')

self.plot_cumulative(uyear, \
ureg, regional_ACE, 'ACE', '$10^4 kn^2$')
self.plot_cumulative(uyear, ureg, regional_ACE,
'ACE', '$10^4 kn^2$')

self.plot_cumulative(uyear, \
ureg, regional_PDI, 'PDI', '$m^3 s^{-2}$')
self.plot_cumulative(uyear, ureg, regional_PDI,
'PDI', '$m^3 s^{-2}$')

if (self.interactive):
plt.show()
Expand All @@ -137,20 +138,22 @@ def execute(self, port, data_in, req):
def two_digit_year_fmt(x, pos):
q = int(x)
q = q - q/100*100
return '%02d'%q
return '%02d' % q

@staticmethod
def accum_by_year_and_region(uyear,ureg,year,region_id,start_y,var,var_out):
def accum_by_year_and_region(uyear, ureg, year, region_id,
start_y, var, var_out):

for yy in uyear:
yids = np.where(year==yy)
yids = np.where(year == yy)
# break these down by year
yvar = var[yids]
# break down by year and region
rr = region_id[yids]
max_reg = np.max(rr)
tot = 0
for r,n,l in ureg:
rids = np.where(rr==r)
for r, n, l in ureg:
rids = np.where(rr == r)
rvar = yvar[rids]
var_out.append(np.sum(rvar))
# south
Expand All @@ -166,7 +169,8 @@ def accum_by_year_and_region(uyear,ureg,year,region_id,start_y,var,var_out):
var_out.append(np.sum(yvar))

def plot_individual(self, uyear, ureg, var, var_name, units):
n_reg = len(ureg) + 3 # add 2 for n & s hemi, 1 for global
# add 2 for n & s hemi, 1 for global
n_reg = len(ureg) + 3
n_year = len(uyear)

# now plot the organized data in various ways
Expand All @@ -177,10 +181,10 @@ def plot_individual(self, uyear, ureg, var, var_name, units):
reg_t_fig = plt.figure()

rnms = list(zip(*ureg))[2]
rnms += ('Southern','Northern','Global')
rnms += ('Southern', 'Northern', 'Global')

n_plots = n_reg + 1
n_left = n_plots%n_cols
n_left = n_plots % n_cols
n_rows = n_plots/n_cols + (1 if n_left else 0)
wid = 2.5*n_cols
ht = 2.0*n_rows
Expand All @@ -203,46 +207,51 @@ def plot_individual(self, uyear, ureg, var, var_name, units):
plt.subplot(n_rows, n_cols, q+1)
ax = plt.gca()
ax.grid(zorder=0)
ax.xaxis.set_major_formatter(plt_tick.FuncFormatter( \

ax.xaxis.set_major_formatter(plt_tick.FuncFormatter(
teca_tc_activity.two_digit_year_fmt))

plt.plot(uyear, var[q::n_reg],'-',color=fill_col[q],linewidth=2)
plt.plot(uyear, var[q::n_reg], '-', color=fill_col[q], linewidth=2)
ax.set_xticks(uyear[:] if n_year < 10 else uyear[::2])
ax.set_xlim([uyear[0], uyear[-1]])

if self.rel_axes and q < n_reg - 1:
ax.set_ylim([0, 1.05*(max_y_reg if q < n_reg - 3 else max_y_hem)])
if (q%n_cols == 0):
ax.set_ylim(
[0, 1.05*(max_y_reg if q < n_reg - 3 else max_y_hem)])

if (q % n_cols == 0):
plt.ylabel(units, fontweight='normal', fontsize=10)

if (q >= (n_reg - n_cols)):
plt.xlabel('Year', fontweight='normal', fontsize=10)
plt.title('%s'%(rnms[q]), fontweight='bold', fontsize=11)

plt.title('%s' % (rnms[q]), fontweight='bold', fontsize=11)
plt.grid(True)

q += 1

plt.suptitle('%s Individual Region'%(var_name), fontweight='bold')
plt.suptitle('%s Individual Region' % (var_name), fontweight='bold')
plt.subplots_adjust(wspace=0.35, hspace=0.6, top=0.92)

plt.savefig('%s_%s_individual_%d.png'%( \
plt.savefig('%s_%s_individual_%d.png' % (
self.basename, var_name, self.dpi), dpi=self.dpi)

return

def plot_cumulative(self, uyear, ureg, var, var_name, units):

n_reg = len(ureg) + 3 # add 2 for n & s hemi, 1 for global
# add 2 for n & s hemi, 1 for global
n_reg = len(ureg) + 3
n_year = len(uyear)

rnms = list(zip(*ureg))[2]
rnms += ('Southern','Northern','Global')
rnms += ('Southern', 'Northern', 'Global')

fill_col = [self.color_map(i) for i in np.linspace(0, 1, n_reg)]

# stacked plot by region
nhsh_stack_fig = plt.figure()
ax = plt.gca()
ax.xaxis.set_major_formatter(plt_tick.FuncFormatter( \
ax.xaxis.set_major_formatter(plt_tick.FuncFormatter(
teca_tc_activity.two_digit_year_fmt))

base = np.zeros(n_year)
Expand All @@ -251,8 +260,13 @@ def plot_cumulative(self, uyear, ureg, var, var_name, units):
vals = var[q::n_reg]
bot = base
top = bot + vals
ax.fill_between(uyear, bot, top, facecolor=fill_col[q], alpha=0.75, zorder=3)
ax.plot(uyear, top, color=fill_col[q], linewidth=2, label=rnms[q], zorder=3)

ax.fill_between(uyear, bot, top, facecolor=fill_col[q],
alpha=0.75, zorder=3)

ax.plot(uyear, top, color=fill_col[q],
linewidth=2, label=rnms[q], zorder=3)

base = top
q += 1

Expand All @@ -263,20 +277,20 @@ def plot_cumulative(self, uyear, ureg, var, var_name, units):
ylim = ax.get_ylim()
ax.set_ylim([0, ylim[1]])

leg=plt.legend(loc=2, bbox_to_anchor=(1.0, 1.01))
leg = plt.legend(loc=2, bbox_to_anchor=(1.0, 1.01))
plt.subplots_adjust(right=0.78)

plt.ylabel(units)
plt.xlabel('Year')
plt.title('%s by Region'%(var_name), fontweight='bold')
plt.title('%s by Region' % (var_name), fontweight='bold')

plt.savefig('%s_%s_regions_%d.png'%( \
plt.savefig('%s_%s_regions_%d.png' % (
self.basename, var_name, self.dpi), dpi=self.dpi)

# stacked plot of northern, southern hemispheres
nhsh_stack_fig = plt.figure()
ax = plt.gca()
ax.xaxis.set_major_formatter(plt_tick.FuncFormatter( \
ax.xaxis.set_major_formatter(plt_tick.FuncFormatter(
teca_tc_activity.two_digit_year_fmt))

base = np.zeros(n_year)
Expand All @@ -285,8 +299,13 @@ def plot_cumulative(self, uyear, ureg, var, var_name, units):
vals = var[q::n_reg]
bot = base
top = bot + vals
ax.fill_between(uyear, bot, top, facecolor=fill_col[q], alpha=0.75, zorder=3)
ax.plot(uyear, top, color=fill_col[q], linewidth=2, label=rnms[q], zorder=3)

ax.fill_between(uyear, bot, top, facecolor=fill_col[q],
alpha=0.75, zorder=3)

ax.plot(uyear, top, color=fill_col[q], linewidth=2,
label=rnms[q], zorder=3)

base = top
q += 1

Expand All @@ -297,15 +316,14 @@ def plot_cumulative(self, uyear, ureg, var, var_name, units):
ylim = ax.get_ylim()
ax.set_ylim([0, ylim[1]])

leg=plt.legend(loc=2, bbox_to_anchor=(1.0, 1.01))
leg = plt.legend(loc=2, bbox_to_anchor=(1.0, 1.01))
plt.subplots_adjust(right=0.78)

plt.xlabel('Year')
plt.ylabel(units)
plt.title('%s by Hemisphere'%(var_name), fontweight='bold')
plt.title('%s by Hemisphere' % (var_name), fontweight='bold')

plt.savefig('%s_%s_hemispheres_%d.png'%( \
plt.savefig('%s_%s_hemispheres_%d.png' % (
self.basename, var_name, self.dpi), dpi=self.dpi)

return

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