Python matplotlib.gridspec 模块，GridSpecFromSubplotSpec() 实例源码
我们从Python开源项目中，提取了以下18个代码示例，用于说明如何使用matplotlib.gridspec.GridSpecFromSubplotSpec()。
def __init__(self, fig, gs, label='mean', color='black', alpha=1.0, min_itr=10):
self._fig = fig
self._gs = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs)
self._ax = plt.subplot(self._gs[0])
self._label = label
self._color = color
self._alpha = alpha
self._min_itr = min_itr
self._ts = np.empty((1, 0))
self._data_mean = np.empty((1, 0))
self._plots_mean = self._ax.plot([], [], '-x', markeredgewidth=1.0,
color=self._color, alpha=1.0, label=self._label)[0]
self._ax.set_xlim(0-0.5, self._min_itr+0.5)
self._ax.set_ylim(0, 1)
self._ax.minorticks_on()
self._ax.legend(loc='upper right', bbox_to_anchor=(1, 1))
self._init = False
self._fig.canvas.draw()
self._fig.canvas.flush_events() # Fixes bug with Qt4Agg backend
def __init__(self, fig, gs, label='mean', color='black', alpha=1.0, min_itr=10):
self._fig = fig
self._gs = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs)
self._ax = plt.subplot(self._gs[0])
self._label = label
self._color = color
self._alpha = alpha
self._min_itr = min_itr
self._ts = np.empty((1, 0))
self._data_mean = np.empty((1, 0))
self._plots_mean = self._ax.plot([], [], '-x', markeredgewidth=1.0,
color=self._color, alpha=1.0, label=self._label)[0]
self._ax.set_xlim(0-0.5, self._min_itr+0.5)
self._ax.set_ylim(0, 1)
self._ax.minorticks_on()
self._ax.legend(loc='upper right', bbox_to_anchor=(1, 1))
self._init = False
self._fig.canvas.draw()
self._fig.canvas.flush_events() # Fixes bug with Qt4Agg backend
def _get_axes(self,fig):
# TODO is attaching these to the figure a good idea? why not save them
# here and reuse them if we recognize the figure being passed in
sz = self._fig_sz
if hasattr(fig,'_feature_ax') and hasattr(fig,'_stateseq_axs'):
return fig._feature_ax, fig._stateseq_axs
else:
if len(self.states_list) <= 2:
gs = GridSpec(sz+len(self.states_list),1)
feature_ax = plt.subplot(gs[:sz,:])
stateseq_axs = [plt.subplot(gs[sz+idx]) for idx in range(len(self.states_list))]
else:
gs = GridSpec(1,2)
sgs = GridSpecFromSubplotSpec(len(self.states_list),1,subplot_spec=gs[1])
feature_ax = plt.subplot(gs[0])
stateseq_axs = [plt.subplot(sgs[idx]) for idx in range(len(self.states_list))]
for ax in stateseq_axs:
ax.grid('off')
fig._feature_ax, fig._stateseq_axs = feature_ax, stateseq_axs
return feature_ax, stateseq_axs
def __init__(self, fig, gs, time_window=500, labels=None, alphas=None):
self._fig = fig
self._gs = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs)
self._ax = plt.subplot(self._gs[0])
self._time_window = time_window
self._labels = labels
self._alphas = alphas
self._init = False
if self._labels:
self.init(len(self._labels))
self._fig.canvas.draw()
self._fig.canvas.flush_events() # Fixes bug with Qt4Agg backend
def __init__(self, fig, gs, log_filename=None, max_display_size=10,
border_on=False, bgcolor=mpl.rcParams['figure.facecolor'], bgalpha=1.0,
fontsize=12, font_family='sans-serif'):
self._fig = fig
self._gs = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs)
self._ax = plt.subplot(self._gs[0])
self._log_filename = log_filename
self._text_box = self._ax.text(0.01, 0.95, '', color='black',
va='top', ha='left', transform=self._ax.transAxes,
fontsize=fontsize, family=font_family)
self._text_arr = []
self._max_display_size = max_display_size
self._ax.set_xticks([])
self._ax.set_yticks([])
if not border_on:
self._ax.spines['top'].set_visible(False)
self._ax.spines['right'].set_visible(False)
self._ax.spines['bottom'].set_visible(False)
self._ax.spines['left'].set_visible(False)
self._fig.canvas.draw()
self._fig.canvas.flush_events() # Fixes bug with Qt4Agg backend
self.set_bgcolor(bgcolor, bgalpha) # this must come after fig.canvas.draw()
#TODO: Add docstrings here.
def __init__(self, fig, gs, num_plots, rows=None, cols=None):
if cols is None:
cols = int(np.floor(np.sqrt(num_plots)))
if rows is None:
rows = int(np.ceil(float(num_plots)/cols))
assert num_plots <= rows*cols, 'Too many plots to put into gridspec.'
self._fig = fig
self._gs = gridspec.GridSpecFromSubplotSpec(8, 1, subplot_spec=gs)
self._gs_legend = self._gs[0:1, 0]
self._gs_plot = self._gs[1:8, 0]
self._ax_legend = plt.subplot(self._gs_legend)
self._ax_legend.get_xaxis().set_visible(False)
self._ax_legend.get_yaxis().set_visible(False)
self._gs_plots = gridspec.GridSpecFromSubplotSpec(rows, cols, subplot_spec=self._gs_plot)
self._axarr = [plt.subplot(self._gs_plots[i], projection='3d') for i in range(num_plots)]
self._lims = [None for i in range(num_plots)]
self._plots = [[] for i in range(num_plots)]
for ax in self._axarr:
ax.tick_params(pad=0)
ax.locator_params(nbins=5)
for item in (ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels()):
item.set_fontsize(10)
self._fig.canvas.draw()
self._fig.canvas.flush_events() # Fixes bug with Qt4Agg backend
def __init__(self, fig, gs, rows, cols, actions_arr):
"""
Constructs an ActionPanel assuming actions_arr is an array of
fully initialized actions.
Each action must have: key, name, func.
Each action can have: axis_pos, keyboard_binding, ps3_binding.
"""
assert len(actions_arr) <= rows*cols, 'Too many actions to put into gridspec.'
self._fig = fig
self._gs = gridspec.GridSpecFromSubplotSpec(rows, cols, subplot_spec=gs)
self._axarr = [plt.subplot(self._gs[i]) for i in range(len(actions_arr))]
# Read keyboard_bindings and ps3_bindings from config
self._actions = {action.key: action for action in actions_arr}
for key, action in self._actions.iteritems():
if key in config['keyboard_bindings']:
action.kb = config['keyboard_bindings'][key]
if key in config['ps3_bindings']:
action.pb = config['ps3_bindings'][key]
self._buttons = None
self._initialize_buttons()
self._cid = self._fig.canvas.mpl_connect('key_press_event', self.on_key_press)
if ROS_ENABLED:
self._ps3_count = 0
rospy.Subscriber(config['ps3_topic'], Joy, self.ps3_callback)
def __init__(self, fig, gs, time_window=500, labels=None, alphas=None):
self._fig = fig
self._gs = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs)
self._ax = plt.subplot(self._gs[0])
self._time_window = time_window
self._labels = labels
self._alphas = alphas
self._init = False
if self._labels:
self.init(len(self._labels))
self._fig.canvas.draw()
self._fig.canvas.flush_events() # Fixes bug with Qt4Agg backend
def __init__(self, fig, gs, log_filename=None, max_display_size=10,
border_on=False, bgcolor=mpl.rcParams['figure.facecolor'], bgalpha=1.0,
fontsize=12, font_family='sans-serif'):
self._fig = fig
self._gs = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs)
self._ax = plt.subplot(self._gs[0])
self._log_filename = log_filename
self._text_box = self._ax.text(0.01, 0.95, '', color='black',
va='top', ha='left', transform=self._ax.transAxes,
fontsize=fontsize, family=font_family)
self._text_arr = []
self._max_display_size = max_display_size
self._ax.set_xticks([])
self._ax.set_yticks([])
if not border_on:
self._ax.spines['top'].set_visible(False)
self._ax.spines['right'].set_visible(False)
self._ax.spines['bottom'].set_visible(False)
self._ax.spines['left'].set_visible(False)
self._fig.canvas.draw()
self._fig.canvas.flush_events() # Fixes bug with Qt4Agg backend
self.set_bgcolor(bgcolor, bgalpha) # this must come after fig.canvas.draw()
#TODO: Add docstrings here.
def __init__(self, fig, gs, num_plots, rows=None, cols=None):
if cols is None:
cols = int(np.floor(np.sqrt(num_plots)))
if rows is None:
rows = int(np.ceil(float(num_plots)/cols))
assert num_plots <= rows*cols, 'Too many plots to put into gridspec.'
self._fig = fig
self._gs = gridspec.GridSpecFromSubplotSpec(8, 1, subplot_spec=gs)
self._gs_legend = self._gs[0:1, 0]
self._gs_plot = self._gs[1:8, 0]
self._ax_legend = plt.subplot(self._gs_legend)
self._ax_legend.get_xaxis().set_visible(False)
self._ax_legend.get_yaxis().set_visible(False)
self._gs_plots = gridspec.GridSpecFromSubplotSpec(rows, cols, subplot_spec=self._gs_plot)
self._axarr = [plt.subplot(self._gs_plots[i], projection='3d') for i in range(num_plots)]
self._lims = [None for i in range(num_plots)]
self._plots = [[] for i in range(num_plots)]
for ax in self._axarr:
ax.tick_params(pad=0)
ax.locator_params(nbins=5)
for item in (ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels()):
item.set_fontsize(10)
self._fig.canvas.draw()
self._fig.canvas.flush_events() # Fixes bug with Qt4Agg backend
def __init__(self, fig, gs, rows, cols, actions_arr):
"""
Constructs an ActionPanel assuming actions_arr is an array of
fully initialized actions.
Each action must have: key, name, func.
Each action can have: axis_pos, keyboard_binding, ps3_binding.
"""
assert len(actions_arr) <= rows*cols, 'Too many actions to put into gridspec.'
self._fig = fig
self._gs = gridspec.GridSpecFromSubplotSpec(rows, cols, subplot_spec=gs)
self._axarr = [plt.subplot(self._gs[i]) for i in range(len(actions_arr))]
# Read keyboard_bindings and ps3_bindings from config
self._actions = {action.key: action for action in actions_arr}
for key, action in self._actions.iteritems():
if key in config['keyboard_bindings']:
action.kb = config['keyboard_bindings'][key]
if key in config['ps3_bindings']:
action.pb = config['ps3_bindings'][key]
self._buttons = None
self._initialize_buttons()
self._cid = self._fig.canvas.mpl_connect('key_press_event', self.on_key_press)
if ROS_ENABLED:
self._ps3_count = 0
rospy.Subscriber(config['ps3_topic'], Joy, self.ps3_callback)
def save_image(X_test, X_predict, Y_test ,output_fn, slices=None, nslices=25 ):
'''
Writes X_test, X_predict, and Y_test to a single png image. Unless specific slices are given, function will write <nslices> evenly spaced slices.
args:
X_test -- slice of values input to model
X_predict -- slice of predicted values based on X_test
Y_test -- slice of predicted values
output_fn -- filename of output png file
slices -- axial slices to save to png file, None by default
nslices -- number of evenly spaced slices to save to png
returns: 0
'''
#if no slices are defined by user, set slices to evenly sampled slices along entire number of slices in 3d image volume
if slices == None : slices = range(0, X_test.shape[0], int(X_test.shape[0]/nslices) )
#set number of rows and columns in output image. currently, sqrt() means that the image will be a square, but this could be changed if a more vertical orientation is prefered
ncol=int(np.sqrt(nslices))
nrow=ncol
fig = plt.figure(1 )
#using gridspec because it seems to give a bit more control over the spacing of the images. define a nrow x ncol grid
outer_grid = gridspec.GridSpec(nrow, ncol,wspace=0.0, hspace=0.0 )
slice_index=0 #index value for <slices>
#iterate over columns and rows:
for col in range(ncol):
for row in range(nrow) :
s=slices[slice_index]
i=col*nrow+row
#couldn't get inner grid to work properly, so commented out for now.
#in theory, should be able to get rid of all white spacing with it
#inner_grid = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=outer_grid[i], wspace=0.0, hspace=0.0)
#normalize the three input numpy arrays. normalizing them independently is necessary so that they all have the same scale
A=normalize(X_test[s])
B=normalize(X_predict[s])
C=normalize(Y_test[s])
ABC = np.concatenate([A,B,C], axis=1)
#use imwshow to display all three images
plt.subplot(outer_grid[i] )
plt.imshow(ABC)
plt.axis('off')
plt.subplots_adjust(hspace=0.0, wspace=0.0)
slice_index+=1
outer_grid.tight_layout(fig, pad=0, h_pad=0, w_pad=0 )
plt.savefig(output_fn, dpi=750)
return 0
def plot_concept(concept, fig=None, subplot_spec=None, **kwargs):
"""Plot a concept's cause- and effect-repertoires side-by-side, with some
additional metainfo.
Examples:
>>> # Create an 8-inch by 2-inch figure and plot on it.
>>> A = pyphi.compute.concept(sub, ('A',))
>>> fig = matplotlib.pyplot.figure(1, (8, 2))
>>> plot_concept(A, fig=fig, state_fmt='ABC') # use node labels
>>> matplotlib.pyplot.show()
Args:
concept (pyphi.models.Concept): The concept to plot.
Keyword args:
fig (matplotlib.Figure): A figure on which to plot. If none is provided,
a new figure is created and used. Default *None*.
subplot_spec (matplotlib.gridspec.GridSpec): A gridspec object indicating
where on a figure to plot. If none is provided, the whole figure is
used. Default *None*.
Any unmatched kwargs are passed to `plot_cause_repertoire` and
`plot_effect_repertoire`.
"""
if fig is None:
fig = plt.figure()
if subplot_spec is None and fig is not None:
# Divide the plotting area into a 1-row by 9-column grid.
gs = gridspec.GridSpec(1, 9)
else:
gs = gridspec.GridSpecFromSubplotSpec(1, 9, subplot_spec=subplot_spec)
summary_ax = plt.Subplot(fig, gs[0, 4]) # Use the middle column for metainfo
cause_ax = plt.Subplot(fig, gs[0, 0:4]) # Span the leftmost 4 columns
effect_ax = plt.Subplot(fig, gs[0, 5:9]) # Span the rightmost 4 columns
fig.add_subplot(summary_ax)
fig.add_subplot(cause_ax)
fig.add_subplot(effect_ax)
summary_ax.text(.5, .5, fmt.concept_summary(concept),
horizontalalignment='center', verticalalignment='center',
multialignment='center')
summary_ax.axis('off')
plot_cause_repertoire(concept, ax=cause_ax, **kwargs)
plot_effect_repertoire(concept, ax=effect_ax, **kwargs)
effect_ax.set_yticklabels([])
fig.tight_layout()
def build_figure(self):
# plot each markevery case for linear x and y scales
figsize = (10, 8)
fig = plt.figure(num=1, figsize=figsize)
axes_list = []
num_rows = len(self.row_list)
outer_grid = gridspec.GridSpec(num_rows, 1)
for row in range(num_rows):
# outer_ax = fig.add_subplot(outer_grid[row])
# if self.row_list[row][1] != '':
# outer_ax.set_title(self.row_list[1])
inner_grid = gridspec.GridSpecFromSubplotSpec(1, self.num_ex,
subplot_spec=outer_grid[row], wspace=0.0, hspace=0.0)
image_row = self.row_list[row][0]
for col in range(self.num_ex):
ax = plt.Subplot(fig, inner_grid[col])
ax.set_xticks([])
ax.set_yticks([])
axes_list.append(fig.add_subplot(ax))
if row==0:
axes_list[-1].set_title('ex{}'.format(col))
axes_list[-1].imshow(image_row[0][col], interpolation='none')
plt.axis('off')
fig.tight_layout()
plt.show()
# initialization function: plot the background of each frame
# Set up formatting for the movie files
Writer = animation.writers['imagemagick_file']
writer = Writer(fps=15, metadata=dict(artist='Me'), bitrate=1800)
# call the animator. blit=True means only re-draw the parts that have changed.
anim = animation.FuncAnimation(fig, self.animate, init_func=self.init,
frames=13, interval=50, blit=True)
anim.save('basic_animation.gif', writer='imagemagick')
plt.show()
def plot_pairs_by_layer_semdeprel_schemes2(df, pairs, majs, mfls, figname, fignum, ymin=0, ymax=100, plot_maj=True):
fig = plt.figure(fignum)
default_size = fig.get_size_inches()
fig.set_size_inches( (default_size[0]*2.5, default_size[1]*2.5) )
outer = gridspec.GridSpec(3, 1, wspace=0.2, hspace=0.5)
xsubs, ysubs = 3, 2
#f, _ = plt.subplots(ysubs, xsubs) #, sharex=True, sharey=True)
#default_size = f.get_size_inches()
#f.set_size_inches( (default_size[0]*1.8, default_size[1]*1.8) )
schemes = df.scheme.unique()
maj_line, mfl_line = '', ''
for s in range(3):
inner = gridspec.GridSpecFromSubplotSpec(2, 3, subplot_spec=outer[s], wspace=0.5, hspace=1)
for i, ((source, target), maj, mfl) in enumerate(zip(pairs[s], majs[s], mfls[s])):
ax = plt.Subplot(fig, inner[i])
df_source_target_scheme = df[(df['source'] == source) & (df['target'] == target) & (df['scheme'] == schemes[s])]
accs = get_accs_from_df(df_source_target_scheme)
layers = df_source_target_scheme.layer.values
hide_xlabel = True if i < (ysubs-1)*xsubs else False
hide_ylabel = True if i % xsubs > 0 else False
maj_line, mfl_line = plot_pair_by_layer(ax, layers, accs, maj, mfl, pretty_lang_names[source] + u"\u2192" + pretty_lang_names[target],
hide_xlabel=hide_xlabel, hide_ylabel=hide_ylabel, ymin=ymin, ymax=ymax, plot_maj=plot_maj, nbins=3, delta_above=False)
fig.add_subplot(ax)
# hide unused axes
#axarr[-1, -1].axis('off')
#for ax in f.axes[len(pairs):-1]:
# ax.axis('off')
# if plot_maj:
# f.legend([maj_line, mfl_line], ['maj', 'mfl'], loc='lower left', bbox_to_anchor=(0.8,0.1), markerscale=1.5, fontsize='medium', frameon=True, title='Legend', edgecolor='black', labelspacing=1)
# else:
# f.legend([mfl_line], ['mfl'], loc='lower left', bbox_to_anchor=(0.8,0.1), markerscale=1.5, fontsize='medium', frameon=True, title='Legend', edgecolor='black', labelspacing=1)
#plt.tight_layout()
plt.savefig(figname)
return fignum + 1
def main(ds):
"""
Creates an overview plot for the Lyman-Alpha total water content probe (TWC).
It calls all plotting functions and sets up axes layout.
"""
#Setup up axes layout
gs=gridspec.GridSpec(2, 1, height_ratios=[1,4])
top_cell=gs[0,0]
bottom_cell=gs[1,0]
#sets up bottom 4 axes; dp timeseries, twc timeseries, twc status and cloud status
gs1=gridspec.GridSpecFromSubplotSpec(4,1, bottom_cell, height_ratios=[1,1,10,10], hspace=0.05)
fig=QaQc_Figure().setup()
ax_dp_ts=fig.add_subplot(gs1[3])
ax_twc_temperatures_ts=fig.add_subplot(gs1[2], sharex=fig.get_axes()[0])
ax_twc_status=fig.add_subplot(gs1[1], sharex=fig.get_axes()[0])
ax_cloud_ts=fig.add_subplot(gs1[0], sharex=fig.get_axes()[0])
#sets up top 2 axes; ge scatter and wvss2r scatter
gs2=gridspec.GridSpecFromSubplotSpec(1,2, top_cell)
ax_scatter_ge=fig.add_subplot(gs2[0], aspect='equal')
ax_scatter_wvss2r=fig.add_subplot(gs2[1], aspect='equal')
set_suptitle(fig, ds, 'QA-Total Water Content Probe')
data=get_data(ds, VARIABLE_NAMES)
for k in data.keys():
if not 'int' in str(data[k].dtype):
data[k][data[k] == -9999.] = np.nan
#Call the plotting methods below:
plot_dp_timeseries(ax_dp_ts, data)
plot_twc_temperatures(ax_twc_temperatures_ts, data)
plot_twc_status(ax_twc_status, data)
plot_cloud(ax_cloud_ts, data)
plot_twc_vs_ge(ax_scatter_ge, data)
plot_twc_vs_wvss2f(ax_scatter_wvss2r, data)
#adds grey bar showing takeoff/landing and only plots the flight
ax=fig.get_axes()[0]
zoom_to_flight_duration(ax, data)
add_time_buffer(ax)
for ax in fig.get_axes()[0:4]:
add_takeoff(ax, data)
add_landing(ax, data)
return fig
#plt.close('all')
#ds = netCDF4.Dataset('./data/twc_extract_20160215_b943.nc', 'r')
#ds=d
#fig = main(ds)
#fig.savefig('/home/axel/test.png')
def main(ds):
"""
Creates overview plot for humidity during a single flight
"""
# Setup up axes layout: 4 axes in one column
gs = gridspec.GridSpec(2, 1, height_ratios=[1,4])
top_cell = gs[0,0]
bottom_cell = gs[1,0]
gs1 = gridspec.GridSpecFromSubplotSpec(3, 1,
bottom_cell,
height_ratios=[2,5,10],
hspace=0.05)
fig = QaQc_Figure().setup()
fig.add_subplot(gs1[2,:])
fig.add_subplot(gs1[1,:], sharex=fig.get_axes()[0])
fig.add_subplot(gs1[0,:], sharex=fig.get_axes()[0])
gs2=gridspec.GridSpecFromSubplotSpec(1,1, top_cell)
fig.add_subplot(gs2[0,:], aspect='equal')
set_suptitle(fig, ds, 'QA-Humidity')
data = get_data(ds, VARIABLE_NAMES)
data['VMR_CR2'][data['VMR_CR2'] < 0] = np.nan # remove unreasonable data
tdew_ge=data['TDEW_GE'][:,0].ravel()
ps_rvsm=data['PS_RVSM'][:,0].ravel()
vp_ge = dp2vp(tdew_ge)
vmr_ge = vp2vmr(vp_ge, ps_rvsm)
vmr_ge = vmr_ge*1E6
#call the plotting methods below
plot_humidity(fig.get_axes()[0], data)
plot_alt(fig.get_axes()[1], data)
plot_lwc(fig.get_axes()[2], data)
plot_humidity_scatter(fig.get_axes()[3], data)
# adds grey bar showing takeoff/landing and only plots the flight
ax = fig.get_axes()[0]
zoom_to_flight_duration(ax, data)
add_time_buffer(ax)
for ax in fig.get_axes()[:-1]:
add_takeoff(ax, data)
add_landing(ax, data)
fig.canvas.draw()
return fig
def main(ds):
"""
Creates an overview plot for the Rosemount temperature sensors; deiced and non-deiced sensors.
It calls all plotting functions and sets up axes layout.
"""
#Setup up axes layout: 3 axes in one column
gs=gridspec.GridSpec(2, 1, height_ratios=[1,4])
top_cell=gs[0,0]
bottom_cell=gs[1,0]
gs1=gridspec.GridSpecFromSubplotSpec(4,1, bottom_cell, height_ratios=[1,1,10,10], hspace=0.05)
fig=QaQc_Figure().setup()
ax_tat_ts=fig.add_subplot(gs1[3]) # axes for true air temperature time series
ax_iat_ts=fig.add_subplot(gs1[2], sharex=fig.get_axes()[0]) # axes for indicated air temperature time series
ax_lwc_ts=fig.add_subplot(gs1[1], sharex=fig.get_axes()[0]) # axes for cloud indicator
ax_heater_ts=fig.add_subplot(gs1[0], sharex=fig.get_axes()[0]) # axes for heater indicator
gs2=gridspec.GridSpecFromSubplotSpec(1,3, top_cell, hspace=0.15)
ax_scatter=fig.add_subplot(gs2[0], aspect='equal') # axes for scatter plot
ax_hist=fig.add_subplot(gs2[1]) # axes for histogram
ax_ps=fig.add_subplot(gs2[2]) # axes for power spectrum
set_suptitle(fig, ds, 'QA-Temperature')
data =get_data(ds, VARIABLE_NAMES)
for var in ['ITDI', 'NDTI', 'TAT_DI_R', 'TAT_ND_R']:
data[var][data[var] <= 0] = np.nan
# call all plotting methods
plot_tat(ax_tat_ts, data)
plot_iat(ax_iat_ts, data)
plot_lwc(ax_lwc_ts, data)
plot_heater(ax_heater_ts, data)
plot_iat_scatter(ax_scatter, data)
plot_iat_histogram(ax_hist, data)
plot_power_spectrum(ax_ps, data)
for ax in fig.get_axes()[0:4]:
add_takeoff(ax, data)
add_landing(ax, data)
ax=fig.get_axes()[0]
zoom_to_flight_duration(ax, data)
add_time_buffer(ax)
return fig
#ds = netCDF4.Dataset('D:\\netcdf-test-files\\temperature_qa_extract_20160215_b943.nc', 'r')
#plt.close('all')
#ds = netCDF4.Dataset('./data/temperature_qa_extract_20160215_b943.nc', 'r')
#ds=d
#fig = main(ds)
#data=get_data(ds, VARIABLE_NAMES)
#close('all')
#fig=figure()
#ax=gca()
#plot_power_spectrum(ax, data)
#fig.savefig('/home/axel/test.png')