def __init__(self, pb_file=None, message_type=None, datafile=None):
self.samples_np = Message_np(pb_file, message_type, datafile)
self.data = np.ma.array(self.samples_np.get_messages_np())
self.dtype = self.samples_np.message_npdtype_map[message_type]
self.full_fields = []
self.cm = plt.get_cmap('gist_rainbow')
self.dtype_c = {}
self.data_c = {}
self._set_full_fields()
import os
import sys
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)),
"..", "proto"))
import numpy as np
import matplotlib.pyplot as plt
from message_np import Message_np
samples_np = Message_np('sample_pb2', 'Sample', 'samples.dat')
data = samples_np.get_messages_np()
fig, ax = plt.subplots(1)
ax.plot(data['system_time'], data['mpu6050']['gyroscope_x'],
data['system_time'], data['mpu6050']['gyroscope_y'],
data['system_time'], data['mpu6050']['gyroscope_z'])
ax.legend(('x', 'y', 'z'), loc=0)
ax.set_xlabel('time [s]')
ax.set_ylabel('angular velocity [rad/s^2]')
ax.set_title('MPU-6050 rate gyroscope measurements')
plt.show()
class PlotData(object):
"""Class used for plotting data of a Message_np object.
"""
def __init__(self, pb_file=None, message_type=None, datafile=None):
self.samples_np = Message_np(pb_file, message_type, datafile)
self.data = np.ma.array(self.samples_np.get_messages_np())
self.dtype = self.samples_np.message_npdtype_map[message_type]
self.full_fields = []
self.cm = plt.get_cmap('gist_rainbow')
self.dtype_c = {}
self.data_c = {}
self._set_full_fields()
def _get_field_type_data(self, field):
"""Returns the datatype and data for the specified field.
"""
if field in self.dtype_c:
return (self.dtype_c[field], self.data_c[field])
rdata = self.data
rdtype = self.dtype
for subfield in field.split(SUBTYPE_SEP):
rdata = rdata[subfield]
rdtype = rdtype[subfield]
return (rdtype, rdata)
def get_field_type(self, field):
"""Returns the datatype for the specified field.
"""
return self._get_field_type_data(field)[0]
def get_field_data(self, field):
"""Returns the data for the specified field.
"""
return self._get_field_type_data(field)[1]
def _set_full_fields(self):
"""Set the list of full field names.
Sets a list of the field names for the message type. If a field has
subfields, the an entry is added for each subfield, where the field and
subfield with a seperator between the two. The superfield is excluded
from this list.
Example
=======
Message A has fields a1, a2, a3 where a1 is of type Message B.
Message B has fields b1, b2.
self.full_fields = ['a1.b1', 'a1.b2', 'a2', 'a3']
"""
self.full_fields = []
field_stack = self.dtype.fields.keys()
while field_stack:
field = field_stack.pop()
subfields = self.get_field_type(field).fields
if not subfields:
self.full_fields.insert(0, field)
else:
for subfield in sorted(subfields.keys()):
field_stack.append(SUBTYPE_SEP.join([field, subfield]))
def expand_field(self, field):
"""Returns a list of all the full field names for each subfield in
'field'. Returns a list with single element 'field' if it has no
subfields.
"""
if field in self.dtype_c:
return [field]
subfields = self.get_field_type(field).fields
if subfields:
return [ff for ff in self.full_fields if ff.startswith(field)]
return [field]
def print_fields(self):
"""Print the data fields.
"""
def print_stats(data):
r = "\t"*4
return r + "\t".join(str(x) for x in [np.min(data), np.max(data),
np.mean(data), np.std(data)])
print("\t"*6 + "min\tmax\tmean\tstd")
subfield_prefix = "\t"
print_fields = OrderedDict()
for ff in self.full_fields:
superfield = ""
for subfield in ff.split(SUBTYPE_SEP):
superfield = (SUBTYPE_SEP.join([superfield, subfield])
if superfield else subfield)
print_fields[superfield] = True
initial_offset = -1
if self.dtype_c.keys():
print("Initial fields:")
initial_offset += 1
for pf in print_fields:
subfields = self.get_field_type(pf).fields
if subfields:
stats = ""
else:
stats = print_stats(self.get_field_data(pf))
subfields = pf.split(SUBTYPE_SEP)
print(subfield_prefix * (len(subfields) + initial_offset) +
subfields[-1] + stats)
if self.dtype_c.keys():
print("\nCreated fields:")
for field in sorted(self.dtype_c.keys()):
stats = print_stats(self.data_c[field])
print(subfield_prefix + field + stats)
def _set_color_cycle(self, axes, num_colors):
"""Set the color cycle for the plots in an axes.
"""
c_norm = colors.Normalize(vmin=0, vmax=num_colors-1)
scalar_map = mplcm.ScalarMappable(norm=c_norm, cmap=self.cm)
axes.set_color_cycle([scalar_map.to_rgba(i) for i in range(num_colors)])
def plot(self, x, y=None, data=None, norm=False, *args, **kwargs):
"""Returns the figure used in plotting field 'y' vs field 'x'.
'x' and 'y' are fields as shown in print_fields(). 'y' can be a list of
fields and will result in all plots displayed on the same figure.
'data' is an array of data that can be plotted against 'x'.
'norm' can be used to normalize each 'y'.
'args' and 'kwargs' are passed to axes.plot().
"""
if y is None and data is None:
return
if y is None:
y = []
if data is None:
data = []
fig, ax = plt.subplots(1)
x_field = self.expand_field(x)[0]
x_data = self.get_field_data(x_field)
if not isinstance(y, list):
y = [y]
if not isinstance(data, list):
data= [data]
y_fields = [y_field for y_ in y for y_field in self.expand_field(y_)]
self._set_color_cycle(ax, len(y_fields) + len(data) + 1)
for y_field in y_fields:
y_data = self.get_field_data(y_field)
mag = 1.0
if norm:
mag = np.float(np.amax(np.absolute(y_data)))
if mag < 1e-12:
mag = 1.0
ax.plot(x_data, y_data / mag, label=y_field, *args, **kwargs)
for i, d in enumerate(data):
ax.plot(x_data, d, label="additional data {0}".format(i), *args, **kwargs)
y_label = PLOTY_SEP.join(y) + (" (normalized)" if norm else "")
ax.set_xlabel(x_field)
ax.set_ylabel(y_label)
ax.set_title(y_label + ' vs. ' + x_field)
ax.legend(loc=2)
ax.grid(True)
plt.show()
return fig, ax
def hist(self, field=None, data=None, *args, **kwargs):
"""Plots a histogram for the specified 'field' or with 'data' using the
same arguments as matplotlib.pyplot.hist().
"""
if field is None and data is None:
return
fig, ax = plt.subplots(1)
if field:
efield = self.expand_field(field)[0]
data = self.get_field_data(efield)
ax.hist(data, *args, **kwargs)
ax.set_xlabel(efield)
ax.set_ylabel('occurances')
ax.set_title('histogram of {0}\nmean = {1}, stddev = {2}'.format(
efield, np.mean(data), np.std(data)))
plt.show()
return fig
import os
import sys
sys.path.append(
os.path.join(os.path.dirname(os.path.realpath(__file__)), "..", "proto"))
import numpy as np
import matplotlib.pyplot as plt
from message_np import Message_np
samples_np = Message_np('sample_pb2', 'Sample', 'samples.dat')
data = samples_np.get_messages_np()
fig, ax = plt.subplots(1)
ax.plot(data['system_time'], data['mpu6050']['gyroscope_x'],
data['system_time'], data['mpu6050']['gyroscope_y'],
data['system_time'], data['mpu6050']['gyroscope_z'])
ax.legend(('x', 'y', 'z'), loc=0)
ax.set_xlabel('time [s]')
ax.set_ylabel('angular velocity [rad/s^2]')
ax.set_title('MPU-6050 rate gyroscope measurements')
plt.show()
