def gitm_alt_slices(zkey,
gData,
lat_index,
lon_index,
title=None,
figname=None,
draw=True,
degrees=True,
color="k",
marker="o",
line=":",
zmax=None,
zmin=None,
amax=None,
amin=None,
xmax=None,
xmin=None,
zcolor=True,
zcenter=False,
add_hmf2=False,
hcolor="k",
hline="--",
*args,
**kwargs):
'''
Creates a contour altitude map with several linear slices as a function of
altitude for a specified GITM variable. A list of latitude and longitude
indexes should be specified. One list should consist of a single value,
the other will be the x variable in the contour plot. The degree flag
determines whether x will be ploted in radians or degrees.
Input: zkey = key for z variable (ie 'e-')
gData = gitm bin structure
lat_index = list of latitude indices
lon_index = list of longitude indices
title = plot title
figname = file name to save figure as (default is none)
draw = Draw the figure to screen (default=True)
degrees = plot x label in radians (False) or degrees (default True)
color = line color for linear plots (default black)
marker = marker type for linear plots (default circle)
line = line type for linear plots (default dotted line)
zmax = z key maximum (or None to compute automatically, default)
zmin = z key minimum (or None to compute automatically, default)
amax = a key maximum (or None to compute automatically, default)
amin = a key minimum (or None to compute automatically, default)
xmax = x key maximum for countour plots (or None to compute
automatically, default)
xmin = x key minimum for contour plots (or None to compute
automatically, default)
zcolor = Color plot or B&W (default is True for color)
zcenter = Should the z range be centered about zero (default is
False, for uncentered)
add_hmf2 = Add line showing hmF2? (default=False)
hcolor = Line color for hmF2 line (default=black)
hline = Line style for hmF2 line (default=dashes)
'''
module_name = "gitm_alt_slices"
# Process the index lists
lat_len = len(lat_index)
lon_len = len(lon_index)
pnum = max([lat_len, lon_len])
if (pnum < 1):
print module_name, "ERROR: no altitude slices specified"
return
if (lat_len > 1 and lon_len > 1):
print module_name, "ERROR: one geographic variable must be constant"
return
lat_range = False
lon_range = False
if lat_len == 1:
xkey = "Longitude"
x_indices = lon_index
lon_index = [0, gData.attrs['nLon']]
lon_range = True
if title:
title = "{:s} at {:5.2f}$^\circ$ N".format(
title, gData['dLat'][1, ilat_index[0], 1])
else:
title = " {:5.2f}$^\circ$ N".format(gData['dLat'][1, lat_index[0],
1])
if degrees:
xkey = "dLon"
x_data = np.array(gData[xkey][:, lat_index[0], :])
alt_data = np.array(gData['Altitude'][:, lat_index[0], :] / 1000.0)
z_data = np.array(gData[zkey][:, lat_index[0], :])
else:
xkey = "Latitude"
x_indices = lat_index
lat_index = [0, gData.attrs['nLat']]
lat_range = True
if title:
title = "{:s} at {:5.2f}$^\circ$ E".format(
title, gData['dLon'][lon_index[0], 1, 1])
else:
title = "{:5.2f}$^\circ$ E".format(gData['dLon'][lon_index[0], 1,
1])
if degrees:
xkey = "dLat"
x_data = np.array(gData[xkey][lon_index[0], :, :])
alt_data = np.array(gData['Altitude'][lon_index[0], :, :] / 1000.0)
z_data = np.array(gData[zkey][lon_index[0], :, :])
# Initialize the x,y,z variable limits
alt_index = [0, gData.attrs['nAlt']]
alt_range = True
if amin == None or amax == None:
tmin, tmax = gpr.find_data_limits_ivalues([gData],
"Altitude",
lat_index,
lon_index,
alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=False)
if amin == None:
amin = math.ceil(tmin / 10000.0) * 10.0
if amax == None:
amax = math.floor(tmax / 10000.0) * 10.0
if zmin == None or zmax == None:
tmin, tmax = gpr.find_data_limits_ivalues([gData],
zkey,
lat_index,
lon_index,
alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=True)
if zmin == None:
zmin = tmin
if zmax == None:
zmax = tmax
if xmin == None or xmax == None:
tmin, tmax = gpr.find_data_limits_ivalues([gData],
xkey,
lat_index,
lon_index,
alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=True)
if xmin == None:
xmin = tmin
if xmax == None:
xmax = tmax
# Initialize the new figure
f, axc, axl = pap.plot_alt_slices(x_data,
alt_data,
z_data,
0,
x_indices,
gData[xkey].attrs['name'],
gData[xkey].attrs['scale'],
gData[xkey].attrs['units'],
"km",
gData[zkey].attrs['name'],
gData[zkey].attrs['scale'],
gData[zkey].attrs['units'],
xmin=xmin,
xmax=xmax,
amin=amin,
amax=amax,
zmin=zmin,
zmax=zmax,
title=title,
draw=False,
color=color,
marker=marker,
line=line,
zcolor=zcolor,
zcenter=zcenter)
# Add hmF2 lines, if desired
if add_hmf2:
# Add hmF2 lines to the linear plots
ilon = lon_index[0]
ilat = lat_index[0]
xlen = len(x_indices) - 1
for i, iax in enumerate(axl):
if lon_len > 1:
ilon = x_indices[xlen - i]
else:
ilat = x_indices[xlen - i]
x = np.array([zmin, zmax])
y = np.array(
[gData['hmF2'][ilon, ilat, 0], gData['hmF2'][ilon, ilat, 0]])
y = y.reshape(2)
iax.plot(x, y, color=hcolor, linestyle=hline, linewidth=2)
# Add hmF2 lines to the contour plot
datadim = list()
if lat_len == 1:
lonmin = 0
lonmax = gData.attrs['nLon']
latmin = lat_index[0]
latmax = latmin + 1
datadim.append(lonmax)
else:
lonmin = lon_index[0]
lonmax = lonmin + 1
latmin = 0
latmax = gData.attrs['nLat']
datadim.append(latmax)
x = np.array(x_data[:, 0])
x = x.reshape(datadim)
y = np.array(gData['hmF2'][lonmin:lonmax, latmin:latmax, 0])
y = y.reshape(datadim)
axc.plot(x, y, color=hcolor, linestyle=hline, linewidth=2)
if draw:
# Draw to screen.
if plt.isinteractive():
plt.draw() #In interactive mode, you just "draw".
else:
# W/o interactive mode, "show" stops the user from typing more
# at the terminal until plots are drawn.
plt.show()
# Save output file
if figname is not None:
plt.savefig(figname)
return f, axc, axl
def gitm_alt_slices(zkey, gData, lat_index, lon_index, title=None, figname=None,
draw=True, degrees=True, color="k", marker="o", line=":",
zmax=None, zmin=None, amax=None, amin=None, xmax=None,
xmin=None, zcolor=True, zcenter=False, add_hmf2=False,
hcolor="k", hline="--", *args, **kwargs):
'''
Creates a contour altitude map with several linear slices as a function of
altitude for a specified GITM variable. A list of latitude and longitude
indexes should be specified. One list should consist of a single value,
the other will be the x variable in the contour plot. The degree flag
determines whether x will be ploted in radians or degrees.
Input: zkey = key for z variable (ie 'e-')
gData = gitm bin structure
lat_index = list of latitude indices
lon_index = list of longitude indices
title = plot title
figname = file name to save figure as (default is none)
draw = Draw the figure to screen (default=True)
degrees = plot x label in radians (False) or degrees (default True)
color = line color for linear plots (default black)
marker = marker type for linear plots (default circle)
line = line type for linear plots (default dotted line)
zmax = z key maximum (or None to compute automatically, default)
zmin = z key minimum (or None to compute automatically, default)
amax = a key maximum (or None to compute automatically, default)
amin = a key minimum (or None to compute automatically, default)
xmax = x key maximum for countour plots (or None to compute
automatically, default)
xmin = x key minimum for contour plots (or None to compute
automatically, default)
zcolor = Color plot or B&W (default is True for color)
zcenter = Should the z range be centered about zero (default is
False, for uncentered)
add_hmf2 = Add line showing hmF2? (default=False)
hcolor = Line color for hmF2 line (default=black)
hline = Line style for hmF2 line (default=dashes)
'''
module_name = "gitm_alt_slices"
# Process the index lists
lat_len = len(lat_index)
lon_len = len(lon_index)
pnum = max([lat_len, lon_len])
if(pnum < 1):
print module_name, "ERROR: no altitude slices specified"
return
if(lat_len > 1 and lon_len > 1):
print module_name, "ERROR: one geographic variable must be constant"
return
lat_range = False
lon_range = False
if lat_len == 1:
xkey = "Longitude"
x_indices = lon_index
lon_index = [0, gData.attrs['nLon']]
lon_range = True
if title:
title = "{:s} at {:5.2f}$^\circ$ N".format(title, gData['dLat'][1,ilat_index[0],1])
else:
title = " {:5.2f}$^\circ$ N".format(gData['dLat'][1,lat_index[0],1])
if degrees:
xkey = "dLon"
x_data = np.array(gData[xkey][:,lat_index[0],:])
alt_data = np.array(gData['Altitude'][:,lat_index[0],:] / 1000.0)
z_data = np.array(gData[zkey][:,lat_index[0],:])
else:
xkey = "Latitude"
x_indices = lat_index
lat_index = [0, gData.attrs['nLat']]
lat_range = True
if title:
title = "{:s} at {:5.2f}$^\circ$ E".format(title, gData['dLon'][lon_index[0],1,1])
else:
title = "{:5.2f}$^\circ$ E".format(gData['dLon'][lon_index[0],1,1])
if degrees:
xkey = "dLat"
x_data = np.array(gData[xkey][lon_index[0],:,:])
alt_data = np.array(gData['Altitude'][lon_index[0],:,:] / 1000.0)
z_data = np.array(gData[zkey][lon_index[0],:,:])
# Initialize the x,y,z variable limits
alt_index = [0, gData.attrs['nAlt']]
alt_range = True
if amin == None or amax == None:
tmin, tmax = gpr.find_data_limits_ivalues([gData],"Altitude",lat_index,
lon_index,alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=False)
if amin == None:
amin = math.ceil(tmin / 10000.0) * 10.0
if amax == None:
amax = math.floor(tmax / 10000.0) * 10.0
if zmin == None or zmax == None:
tmin, tmax = gpr.find_data_limits_ivalues([gData], zkey, lat_index,
lon_index, alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=True)
if zmin == None:
zmin = tmin
if zmax == None:
zmax = tmax
if xmin == None or xmax == None:
tmin, tmax = gpr.find_data_limits_ivalues([gData], xkey, lat_index,
lon_index, alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=True)
if xmin == None:
xmin = tmin
if xmax == None:
xmax = tmax
# Initialize the new figure
f, axc, axl = pap.plot_alt_slices(x_data, alt_data, z_data, 0, x_indices,
gData[xkey].attrs['name'],
gData[xkey].attrs['scale'],
gData[xkey].attrs['units'], "km",
gData[zkey].attrs['name'],
gData[zkey].attrs['scale'],
gData[zkey].attrs['units'], xmin=xmin,
xmax=xmax, amin=amin, amax=amax,
zmin=zmin, zmax=zmax, title=title,
draw=False, color=color, marker=marker,
line=line, zcolor=zcolor, zcenter=zcenter)
# Add hmF2 lines, if desired
if add_hmf2:
# Add hmF2 lines to the linear plots
ilon = lon_index[0]
ilat = lat_index[0]
xlen = len(x_indices) - 1
for i,iax in enumerate(axl):
if lon_len > 1:
ilon = x_indices[xlen-i]
else:
ilat = x_indices[xlen-i]
x = np.array([zmin,zmax])
y = np.array([gData['hmF2'][ilon,ilat,0],
gData['hmF2'][ilon,ilat,0]])
y = y.reshape(2)
iax.plot(x, y, color=hcolor, linestyle=hline, linewidth=2)
# Add hmF2 lines to the contour plot
datadim = list()
if lat_len == 1:
lonmin = 0
lonmax = gData.attrs['nLon']
latmin = lat_index[0]
latmax = latmin + 1
datadim.append(lonmax)
else:
lonmin = lon_index[0]
lonmax = lonmin + 1
latmin = 0
latmax = gData.attrs['nLat']
datadim.append(latmax)
x = np.array(x_data[:,0])
x = x.reshape(datadim)
y = np.array(gData['hmF2'][lonmin:lonmax,latmin:latmax,0])
y = y.reshape(datadim)
axc.plot(x, y, color=hcolor, linestyle=hline, linewidth=2)
if draw:
# Draw to screen.
if plt.isinteractive():
plt.draw() #In interactive mode, you just "draw".
else:
# W/o interactive mode, "show" stops the user from typing more
# at the terminal until plots are drawn.
plt.show()
# Save output file
if figname is not None:
plt.savefig(figname)
return f, axc, axl
def gitm_mult_alt_images(plot_type,
zkey,
gData,
lat_index,
lon_index,
title=None,
figname=None,
draw=True,
xkey="dLat",
color="b",
marker="o",
line=":",
zmax=None,
zmin=None,
amax=None,
amin=None,
xmax=None,
xmin=None,
zcenter=False,
add_hmf2=False,
hcolor="k",
hline="--",
*args,
**kwargs):
'''
Creates a linear or contour altitude map for a specified altitude range.
A list of latitude and longitude indexes should be specified. They may
be of equal length (for paired values), or for a constant value in one
coordinate, a length of list one can be specified.
Input: plot_type = key to determine plot type (linear, contour)
zkey = key for z variable (ie 'Vertical TEC')
gData = gitm bin structure
lat_index = list of latitude indices (empty list for all)
lon_index = list of longitude indices (empty list for all)
title = plot title
figname = file name to save figure as (default is none)
draw = Draw figure to screen (default is True)
xkey = x coordinate for contour plots (default dLat)
color = line color for linear plots (default blue)
marker = marker type for linear plots (default circle)
line = line type for linear plots (default dotted line)
zmax = z key maximum (or None to compute automatically, default)
zmin = z key minimum (or None to compute automatically, default)
amax = a key maximum (or None to compute automatically, default)
amin = a key minimum (or None to compute automatically, default)
xmax = x key maximum for countour plots (or None to compute
automatically, default)
xmin = x key minimum for contour plots (or None to compute
automatically, default)
zcenter = Should the z range be centered about zero (default is
False, for uncentered)
add_hmf2 = Add line showing hmF2? (default=False)
hcolor = Line color for hmF2 line (default=black)
hline = Line style for hmF2 line (default=dashes)
'''
module_name = "gitm_mult_alt_images"
# Process the index lists
lat_len = len(lat_index)
lon_len = len(lon_index)
if lat_len != lon_len and lat_len > 1 and lon_len > 1:
print module_name, "ERROR: improperly paired lat/lon indices"
return
if lat_len <= 1:
y_label = [
"{:.1f}$^\circ$ Lon".format(gData['dLon'][l, 1, 1])
for l in lon_index
]
elif lon_len <= 1:
y_label = [
"{:.1f}$^\circ$ Lat".format(gData['dLat'][1, l, 1])
for l in lat_index
]
else:
y_label = [
"{:.1f}$^\circ$ Lat, {:.1f}$^\circ$ Lon".format(
gData['dLat'][1, l, 1], gData['dLon'][lon_index[i], 1, 1])
for i, l in enumerate(lat_index)
]
# Initialize the input data indices
subindices = [lon_index, lat_index]
# Initialize the x,y,z variable limits if desired
alt_index = [0, gData.attrs['nAlt']]
alt_range = True
lat_range = False
lon_range = False
if lat_len == 0:
lat_index = [0, gData.attrs['nLat']]
lat_range = True
if lon_len == 0:
lon_index = [0, gData.attrs['nLon']]
lon_range = True
if amin == None or amax == None:
tmin, tmax = gpr.find_data_limits_ivalues([gData],
"Altitude",
lat_index,
lon_index,
alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=False)
if amin == None:
amin = math.ceil(tmin / 10000.0) * 10.0
if amax == None:
amax = math.floor(tmax / 10000.0) * 10.0
if zmin == None or zmax == None:
if gData[zkey].attrs['scale'].find("exp") >= 0:
rvals = False
else:
rvals = True
tmin, tmax = gpr.find_data_limits_ivalues([gData],
zkey,
lat_index,
lon_index,
alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=rvals)
if zmin == None:
zmin = tmin
if zmax == None:
zmax = tmax
if (xmin == None or xmax == None) and plot_type.find("linear") < 0:
tmin, tmax = gpr.find_data_limits_ivalues([gData],
xkey,
lat_index,
lon_index,
alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=True)
if xmin == None:
xmin = tmin
if xmax == None:
xmax = tmax
# Initialize the x and z data
if plot_type.find("linear") >= 0:
x_data = np.array(gData[zkey])
x_name = gData[zkey].attrs['name']
x_scale = gData[zkey].attrs['scale']
x_units = gData[zkey].attrs['units']
xmin = zmin
xmax = zmax
z_data = []
z_name = ""
z_scale = ""
z_units = ""
else:
x_data = np.array(gData[xkey])
x_name = gData[xkey].attrs['name']
x_scale = gData[xkey].attrs['scale']
x_units = gData[xkey].attrs['units']
z_data = np.array(gData[zkey])
z_name = gData[zkey].attrs['name']
z_scale = gData[zkey].attrs['scale']
z_units = gData[zkey].attrs['units']
if color.find('k') == 0:
color = False
else:
color = True
marker = True
line = zcenter
# Initialize the new figure
alt_data = np.array(gData['Altitude'] / 1000.0)
f, ax = pap.plot_mult_alt_images(plot_type,
subindices,
x_data,
alt_data,
z_data,
x_name,
x_scale,
x_units,
"km",
y_label=y_label,
z_name=z_name,
z_scale=z_scale,
z_units=z_units,
xmin=xmin,
xmax=xmax,
amin=amin,
amax=amax,
zmin=zmin,
zmax=zmax,
title=title,
figname=None,
draw=False,
color1=color,
color2=marker,
color3=line)
# Add the hmF2 lines, if desired
if add_hmf2 and not gData.has_key("hmF2"):
gData.calc_2dion()
if not gData.has_key("hmF2"):
print module_name, "WARNING: hmF2 data is not available"
add_hmF2 = False
if add_hmf2:
# Initialize lat/lon indexes that won't change
datadim = list()
if lon_len == 0:
datadim.append(gData.attrs['nLon'])
lonmin = 0
lonmax = gData.attrs['nLon']
elif lon_len == 1:
lonmin = lon_index[0]
lonmax = lonmin + 1
if lat_len == 0:
datadim.append(gData.attrs['nLat'])
latmin = 0
latmax = gData.attrs['nLat']
elif lat_len == 1:
latmin = lat_index[0]
latmax = latmin + 1
# Iterate over all subplot axes
for i, iax in enumerate(ax):
# Initialize changing lat/lon indexes
if lon_len > 1:
lonmin = lon_index[i]
lonmax = lonmin + 1
if lat_len > 1:
latmin = lat_index[i]
latmax = latmin + 1
# Initialize the hmF2 data by plot type
if plot_type.find("linear") >= 0:
x = np.array([xmin, xmax])
y = np.array([
gData['hmF2'][lonmin:lonmax, latmin:latmax, 0],
gData['hmF2'][lonmin:lonmax, latmin:latmax, 0]
])
y = y.reshape(2)
else:
x = x_data[lonmin:lonmax, latmin:latmax, 0]
x = x.reshape(datadim)
y = np.array(gData['hmF2'][lonmin:lonmax, latmin:latmax, 0])
y = y.reshape(datadim)
# Plot the hmF2 line
iax.plot(x, y, color=hcolor, linestyle=hline, linewidth=2)
if draw:
# Draw to screen.
if plt.isinteractive():
plt.draw() #In interactive mode, you just "draw".
else:
# W/o interactive mode, "show" stops the user from typing more
# at the terminal until plots are drawn.
plt.show()
# Save output file
if figname is not None:
plt.savefig(figname)
return f
def gitm_mult_alt_images(plot_type, zkey, gData, lat_index, lon_index,
title=None, figname=None, draw=True, xkey="dLat",
color="b", marker="o", line=":", zmax=None, zmin=None,
amax=None, amin=None, xmax=None, xmin=None,
zcenter=False, add_hmf2=False, hcolor="k", hline="--",
*args, **kwargs):
'''
Creates a linear or contour altitude map for a specified altitude range.
A list of latitude and longitude indexes should be specified. They may
be of equal length (for paired values), or for a constant value in one
coordinate, a length of list one can be specified.
Input: plot_type = key to determine plot type (linear, contour)
zkey = key for z variable (ie 'Vertical TEC')
gData = gitm bin structure
lat_index = list of latitude indices (empty list for all)
lon_index = list of longitude indices (empty list for all)
title = plot title
figname = file name to save figure as (default is none)
draw = Draw figure to screen (default is True)
xkey = x coordinate for contour plots (default dLat)
color = line color for linear plots (default blue)
marker = marker type for linear plots (default circle)
line = line type for linear plots (default dotted line)
zmax = z key maximum (or None to compute automatically, default)
zmin = z key minimum (or None to compute automatically, default)
amax = a key maximum (or None to compute automatically, default)
amin = a key minimum (or None to compute automatically, default)
xmax = x key maximum for countour plots (or None to compute
automatically, default)
xmin = x key minimum for contour plots (or None to compute
automatically, default)
zcenter = Should the z range be centered about zero (default is
False, for uncentered)
add_hmf2 = Add line showing hmF2? (default=False)
hcolor = Line color for hmF2 line (default=black)
hline = Line style for hmF2 line (default=dashes)
'''
module_name = "gitm_mult_alt_images"
# Process the index lists
lat_len = len(lat_index)
lon_len = len(lon_index)
if lat_len != lon_len and lat_len > 1 and lon_len > 1:
print module_name, "ERROR: improperly paired lat/lon indices"
return
if lat_len <= 1:
y_label = ["{:.1f}$^\circ$ Lon".format(gData['dLon'][l,1,1])
for l in lon_index]
elif lon_len <= 1:
y_label = ["{:.1f}$^\circ$ Lat".format(gData['dLat'][1,l,1])
for l in lat_index]
else:
y_label = ["{:.1f}$^\circ$ Lat, {:.1f}$^\circ$ Lon".format(gData['dLat'][1,l,1], gData['dLon'][lon_index[i],1,1]) for i,l in enumerate(lat_index)]
# Initialize the input data indices
subindices = [lon_index, lat_index]
# Initialize the x,y,z variable limits if desired
alt_index = [0, gData.attrs['nAlt']]
alt_range = True
lat_range = False
lon_range = False
if lat_len == 0:
lat_index = [0, gData.attrs['nLat']]
lat_range = True
if lon_len == 0:
lon_index = [0, gData.attrs['nLon']]
lon_range = True
if amin == None or amax == None:
tmin, tmax = gpr.find_data_limits_ivalues([gData],"Altitude",lat_index,
lon_index,alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=False)
if amin == None:
amin = math.ceil(tmin / 10000.0) * 10.0
if amax == None:
amax = math.floor(tmax / 10000.0) * 10.0
if zmin == None or zmax == None:
if gData[zkey].attrs['scale'].find("exp") >= 0:
rvals = False
else:
rvals = True
tmin, tmax = gpr.find_data_limits_ivalues([gData], zkey, lat_index,
lon_index, alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=rvals)
if zmin == None:
zmin = tmin
if zmax == None:
zmax = tmax
if (xmin == None or xmax == None) and plot_type.find("linear") < 0:
tmin, tmax = gpr.find_data_limits_ivalues([gData], xkey, lat_index,
lon_index, alt_index,
lat_range=lat_range,
lon_range=lon_range,
alt_range=alt_range,
rvals=True)
if xmin == None:
xmin = tmin
if xmax == None:
xmax = tmax
# Initialize the x and z data
if plot_type.find("linear") >= 0:
x_data = np.array(gData[zkey])
x_name = gData[zkey].attrs['name']
x_scale = gData[zkey].attrs['scale']
x_units = gData[zkey].attrs['units']
xmin = zmin
xmax = zmax
z_data = []
z_name = ""
z_scale = ""
z_units = ""
else:
x_data = np.array(gData[xkey])
x_name = gData[xkey].attrs['name']
x_scale = gData[xkey].attrs['scale']
x_units = gData[xkey].attrs['units']
z_data = np.array(gData[zkey])
z_name = gData[zkey].attrs['name']
z_scale = gData[zkey].attrs['scale']
z_units = gData[zkey].attrs['units']
if color.find('k') == 0:
color = False
else:
color = True
marker=True
line=zcenter
# Initialize the new figure
alt_data = np.array(gData['Altitude'] / 1000.0)
f, ax = pap.plot_mult_alt_images(plot_type, subindices, x_data, alt_data,
z_data, x_name, x_scale, x_units, "km",
y_label=y_label, z_name=z_name,
z_scale=z_scale, z_units=z_units,
xmin=xmin, xmax=xmax, amin=amin, amax=amax,
zmin=zmin, zmax=zmax, title=title,
figname=None, draw=False, color1=color,
color2=marker, color3=line)
# Add the hmF2 lines, if desired
if add_hmf2 and not gData.has_key("hmF2"):
gData.calc_2dion()
if not gData.has_key("hmF2"):
print module_name, "WARNING: hmF2 data is not available"
add_hmF2 = False
if add_hmf2:
# Initialize lat/lon indexes that won't change
datadim = list()
if lon_len == 0:
datadim.append(gData.attrs['nLon'])
lonmin = 0
lonmax = gData.attrs['nLon']
elif lon_len == 1:
lonmin = lon_index[0]
lonmax = lonmin + 1
if lat_len == 0:
datadim.append(gData.attrs['nLat'])
latmin = 0
latmax = gData.attrs['nLat']
elif lat_len == 1:
latmin = lat_index[0]
latmax = latmin + 1
# Iterate over all subplot axes
for i,iax in enumerate(ax):
# Initialize changing lat/lon indexes
if lon_len > 1:
lonmin = lon_index[i]
lonmax = lonmin + 1
if lat_len > 1:
latmin = lat_index[i]
latmax = latmin + 1
# Initialize the hmF2 data by plot type
if plot_type.find("linear") >= 0:
x = np.array([xmin, xmax])
y = np.array([gData['hmF2'][lonmin:lonmax,latmin:latmax,0],
gData['hmF2'][lonmin:lonmax,latmin:latmax,0]])
y = y.reshape(2)
else:
x = x_data[lonmin:lonmax,latmin:latmax,0]
x = x.reshape(datadim)
y = np.array(gData['hmF2'][lonmin:lonmax,latmin:latmax,0])
y = y.reshape(datadim)
# Plot the hmF2 line
iax.plot(x, y, color=hcolor, linestyle=hline, linewidth=2)
if draw:
# Draw to screen.
if plt.isinteractive():
plt.draw() #In interactive mode, you just "draw".
else:
# W/o interactive mode, "show" stops the user from typing more
# at the terminal until plots are drawn.
plt.show()
# Save output file
if figname is not None:
plt.savefig(figname)
return f
