def render_simple_plot(name, vars, title, legloc, ylabel, ncols=1, ymin=None, ymax=None):
import matplotlib.pyplot as plt
import math
xlocales.set_matplotlib()
# Location of results (relative to extention directory)
resdir = os.path.abspath(os.path.join(os.path.dirname(__file__),
"..", "..", "..", "results"))
var0name = vars[0]["name"]
fn = os.path.join(resdir, name+"_res.mat")
res = DyMatFile(fn)
fig, ax = plt.subplots()
# Set background to be transparent
#fig.patch.set_facecolor('none')
#fig.patch.set_alpha(0.0);
#ax.patch.set_facecolor('none')
#ax.patch.set_alpha(0.0);
try:
t = res.abscissa(var0name, valuesOnly=True)
print "len(t) = "+str(len(t))
except KeyError as e:
raise NameError("Unknown key: "+var0name+" among "+str(res.names()))
for var in vars:
varname = var["name"]
scale = var["scale"]
legend = var["legend"]
style = var["style"]
try:
x = res.data(varname)
except KeyError as e:
raise NameError("Unknown key: "+varname+" among "+str(res.names()))
if len(x)==2:
xv = x[0]
print "xv = "+str(xv)
x = [xv]*len(t)
x = map(lambda y: y*scale, x)
print "len("+varname+") = "+str(len(x))
ax.plot(t, x, style, label=legend)
#legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
legend = ax.legend(shadow=True, ncol=ncols, loc=legloc)
if title==None:
title = name.replace("_", ".")
plt.title(title)
plt.ylabel(ylabel)
plt.xlabel(_('Time [s]'))
if ymax!=None:
plt.axis(ymax=ymax)
if ymin!=None:
plt.axis(ymin=ymin)
plt.show()
def render_comp_plot(name1, vars1, name2, vars2, title, legloc, ylabel):
import matplotlib.pyplot as plt
import math
xlocales.set_matplotlib()
if len(vars1) != len(vars2):
raise BaseException("Mismatch in variable arrays, %d vs %s" %
(len(vars1), len(vars2)))
# Location of results (relative to extention directory)
resdir = os.path.abspath(
os.path.join(os.path.dirname(__file__), "..", "..", "..", "results"))
fn1 = os.path.join(resdir, name1 + "_res.mat")
res1 = DyMatFile(fn1)
fn2 = os.path.join(resdir, name2 + "_res.mat")
res2 = DyMatFile(fn2)
fig, ax = plt.subplots()
# Set background to be transparent
#fig.patch.set_facecolor('none')
#fig.patch.set_alpha(0.0);
#ax.patch.set_facecolor('none')
#ax.patch.set_alpha(0.0);
var0name = vars1[0]["name"]
t1 = res1.abscissa(vars1[0]["name"], valuesOnly=True)
t2 = res2.abscissa(vars2[0]["name"], valuesOnly=True)
for i in range(0, len(vars1)):
v1 = vars1[i]
v2 = vars2[i]
x1 = res1.data(v1["name"])
x2 = res2.data(v2["name"])
l1 = v1["legend"]
l2 = v2["legend"]
if len(x1) == 2:
x1 = [x1[0]] * len(t1)
if len(x2) == 2:
x2 = [x2[0]] * len(t2)
ax.plot(t1, x1, "-", label=l1)
ax.plot(t2, x2, v2.get("style", "-."), label=l2)
legend = ax.legend(loc=legloc, shadow=True)
if title == None:
title = name1.replace("_", ".")
plt.title(title)
plt.ylabel(ylabel)
plt.xlabel(_('Time [s]'))
plt.show()
def render_simple_plot(name, vars, title, legloc, ylabel, ncols=1, ymax=None):
import matplotlib.pyplot as plt
import math
# Location of results (relative to extention directory)
resdir = os.path.abspath(
os.path.join(os.path.dirname(__file__), "..", "..", "..", "results"))
var0name = vars[0]["name"]
fn = os.path.join(resdir, name + "_res.mat")
res = DyMatFile(fn)
fig, ax = plt.subplots()
# Set background to be transparent
#fig.patch.set_facecolor('none')
#fig.patch.set_alpha(0.0);
#ax.patch.set_facecolor('none')
#ax.patch.set_alpha(0.0);
try:
t = res.abscissa(var0name, valuesOnly=True)
print "len(t) = " + str(len(t))
except KeyError as e:
raise NameError("Unknown key: " + var0name + " among " +
str(res.names()))
for var in vars:
varname = var["name"]
scale = var["scale"]
legend = var["legend"]
style = var["style"]
try:
x = res.data(varname)
except KeyError as e:
raise NameError("Unknown key: " + varname + " among " +
str(res.names()))
if len(x) == 2:
xv = x[0]
print "xv = " + str(xv)
x = [xv] * len(t)
x = map(lambda y: y * scale, x)
print "len(" + varname + ") = " + str(len(x))
ax.plot(t, x, style, label=legend)
#legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
legend = ax.legend(shadow=True, ncol=ncols, loc=legloc)
if title == None:
title = name.replace("_", ".")
plt.title(title)
plt.ylabel(ylabel)
plt.xlabel('Time [s]')
if ymax != None:
plt.axis(ymax=ymax)
plt.show()
def render_comp_plot(name1, vars1, name2, vars2, title, legloc, ylabel):
import matplotlib.pyplot as plt
import math
xlocales.set_matplotlib()
if len(vars1)!=len(vars2):
raise BaseException("Mismatch in variable arrays, %d vs %s" % (len(vars1), len(vars2)))
# Location of results (relative to extention directory)
resdir = os.path.abspath(os.path.join(os.path.dirname(__file__),
"..", "..", "..", "results"))
fn1 = os.path.join(resdir, name1+"_res.mat")
res1 = DyMatFile(fn1)
fn2 = os.path.join(resdir, name2+"_res.mat")
res2 = DyMatFile(fn2)
fig, ax = plt.subplots()
# Set background to be transparent
#fig.patch.set_facecolor('none')
#fig.patch.set_alpha(0.0);
#ax.patch.set_facecolor('none')
#ax.patch.set_alpha(0.0);
var0name = vars1[0]["name"]
t1 = res1.abscissa(vars1[0]["name"], valuesOnly=True)
t2 = res2.abscissa(vars2[0]["name"], valuesOnly=True)
for i in range(0,len(vars1)):
v1 = vars1[i]
v2 = vars2[i]
x1 = res1.data(v1["name"])
x2 = res2.data(v2["name"])
l1 = v1["legend"]
l2 = v2["legend"]
if len(x1)==2:
x1 = [x1[0]]*len(t1)
if len(x2)==2:
x2 = [x2[0]]*len(t2)
ax.plot(t1, x1, "-", label=l1)
ax.plot(t2, x2, v2.get("style", "-."), label=l2)
legend = ax.legend(loc=legloc, shadow=True)
if title==None:
title = name1.replace("_", ".")
plt.title(title)
plt.ylabel(ylabel)
plt.xlabel(_('Time [s]'))
plt.show()
def dsres2meld(df, mfp, verbose=False, compression=True, single=True):
"""
This function reads in a file in 'dsres' format and then writes it
back out in meld format. Note there is a dependency in this code
on numpy and dymat.
"""
import numpy
from dymat import DyMatFile
# Read dsres file
mf = DyMatFile(df)
# Open a meld file to write to
meld = MeldWriter(mfp, compression=compression, single=single)
# Initialize a couple of internal data structures
tables = {}
signal_map = {}
alias_map = {}
# This is the key to use for "description" fields
DESC = "desc"
# We loop over the blocks in the dsres file and each block
# will end up being a table.
for block in mf.blocks():
# Extract the abscissa data for this block
if verbose:
print "Block: "+str(block)
(abscissa, aname, adesc) = mf.abscissa(block)
# Determine all columns in the dsres file and associate
# the signals and aliases with these columns
columns = {}
if verbose:
print "Abscissa: "+str(aname)+" '"+adesc+"'"
signals = []
aliases = []
# Loop over all variables in this block and either make them
# signals or aliases (if some other variable has already
# claimed that column)
for name in mf.names(block):
col = mf._vars[name][2]
if col in columns:
if verbose:
print " Alias "+name+" (of: "+columns[col]+")"
aliases.append((name, mf._vars[name][0],
columns[col], mf._vars[name][3]))
else:
if verbose:
print " Signal "+name+" ("+str(col)+")"
columns[col] = name
signals.append(name)
if verbose:
print "Number of columns: "+str(len(columns.keys()))
print "Number of signals: "+str(len(signals))
print "Number of aliases: "+str(len(aliases))
signal_map[block] = signals
alias_map[block] = aliases
# Generate table for this block (and store it away for later)
tables[block] = meld.add_table("T"+str(block))
# Add abscissa
tables[block].add_signal(aname, metadata={DESC: adesc})
for signal in signals:
tables[block].add_signal(signal, metadata={DESC: mf.description(signal)})
# Add aliases (and their metadata)
for alias in aliases:
transform = None
if alias[3]<0.0:
tables[block].add_alias(alias=alias[0], of=alias[2],
transform="aff(-1,0)",
metadata={DESC:mf.description(alias[0])})
else:
tables[block].add_alias(alias=alias[0], of=alias[2],
metadata={DESC:mf.description(alias[0])})
# Finalize structure
meld.finalize()
# Now loop again, this time with the intention to write data
for block in mf.blocks():
# Write abscissa for this block
(abscissa, aname, adesc) = mf.abscissa(block)
abscissa = list(abscissa.astype(numpy.float))
tables[block].write(aname, list(abscissa))
signals = signal_map[block]
print "Block: "+str(block)
print " Writing signals: "+str(signals)
# Then write signals (no need to write aliases)
for signal in signals:
vec = list(mf.data(signal).astype(numpy.float))
tables[block].write(signal, vec)
# Close the MeldWriter
meld.close()