def __init__(self):
self.X = np.linspace(0, 4 * np.pi, 200)
self.pt = Plotter(1, 2, width=700, height=500, useAgg=True)
self.pt.set_xlabel("X")
self.pt.use_grid()
self.pt.add_annotation(0, "First")
self.pt.add_annotation(199, "Last")
def __init__(self):
"""
Constructs a Yampex Plotter object for a figure with two subplots.
"""
self.pt = Plotter(2, width=self.width, height=self.height)
self.pt.use_grid()
self.pt.set_title("Exponentials plotted from {:.1f} to {:.1f}",
self.xMin, self.xMax)
self.pt.set_xlabel("X")
self.pt.set_ylabel("a*exp(-b*X)")
def __init__(self):
"""
Constructs a Yampex Plotter object for a figure with two subplots.
"""
self.mList = []
# Small MOSFET in an IC
self.mList.append(MOSFET(2.5e-9, 5e17))
# High-current Power MOSFET
self.mList.append(MOSFET(4e-9, 2.7e19))
# Plotter
self.N_sp = len(self.mList)
self.pt = Plotter(self.N_sp, width=self.width, height=self.height)
self.pt.use_grid()
self.pt.set_xlabel("Vgst")
self.pt.set_ylabel("Vdsp")
self.pt.add_legend("Vgst/n")
self.pt.add_legend("(Vgst-f(x))/n")
self.pt.use_labels()
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS
# IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
# express or implied. See the License for the specific language
# governing permissions and limitations under the License.
"""
A log plot, with several plots in one subplot, all done in one
call to the subplotting tool in context.
"""
import numpy as np
from yampex import Plotter
# Construct a Plotter object for a 1000x800 pixel (100 DPI) figure
# with a single subplot.
pt = Plotter(1, width=10.0, height=8.0)
# The plots will be of different bases raised to powers.
X = np.linspace(0, 10, 100)
pt.set_title("Different Bases Raised to Power 0-10")
# The x label will say "Power" and the subplot will have a grid.
pt.set_xlabel("Power")
pt.use_grid()
# Make a subplotting context and work with the single subplot via the
# subplot tool sp. It's actually just a reference to pt, but set up
# for subplotting.
with pt as sp:
# Compute the vectors all at once
Y2 = np.power(2, X)
Y3 = np.power(3, X)
Y10 = np.power(10, X)
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS
# IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
# express or implied. See the License for the specific language
# governing permissions and limitations under the License.
"""
A sine and cosine plot in each of two subplots, with a call to the
L{SpecialAx} object.
"""
import numpy as np
from yampex import Plotter
# Construct a Plotter object for a 700x500 pixel (100 DPI) figure with
# two subplots.
pt = Plotter(1, 2, width=7.0, height=5.0)
# The plots, one in each subplot, will be of a sine and cosine with
# 200 points from 0 to 4*pi.
funcNames = ('sin', 'cos')
X = np.linspace(0, 4 * np.pi, 200)
pt.set_title("Sine and Cosine")
# Each subplot will have an x-axis label of "X" and a grid.
pt.set_xlabel("X")
pt.use_grid()
# Each plot will have an annotation labeled "Last" at its last
# point. Note that we can use negative indices referenced to the last
# element, just as with Python sequences.
pt.add_annotation(-1, "Last")
# Make a subplotting context and work with the two subplots via the
# subplot tool sp. It's actually just a reference to pt, but set up
def __init__(self):
"""
Constructs a Yampex Plotter object for a figure with two subplots.
"""
self.pt = Plotter(2, width=self.width, height=self.height)
self.pt.use_grid()
Illustrates the use of L{options.OptsBase.use_timex} and calls to a
subplot-context instance of L{plot.Plotter} with multiple y-axis
arguments. Also shows a couple of intelligently-positioned
annotations.
"""
import numpy as np
from yampex import Plotter
EQs = ("sin(10*t)*cos(10000*t)", "cos(10*t)*cos(10000*t)")
N = 6
t = np.linspace(0, 2E-6, 1000)
# This time, we specify the plot dimensions in pixels with a tuple
pt = Plotter(N, figSize=(1600, 1200))
pt.set_title("With {:d} time scales: {}, {}", N, *EQs)
pt.use_timex()
pt.use_grid()
for eq in EQs:
pt.add_legend(eq)
with pt as sp:
for mult in range(N):
X = t * 10**mult
Y1 = np.sin(10 * X) * np.sin(10000 * X)
Y2 = np.cos(10 * X) * np.cos(10000 * X)
sp.set_title("0 - {:.5g} seconds", X[-1])
if mult < 5 and np.any(Y2 < 0):
sp.add_annotation(0.0, "Zero Crossing", kVector=1, y=True)
sp(X, Y1, Y2)
pt.show()
Illustrates the use of L{options.OptsBase.use_timex} and calls to a
subplot-context instance of L{plot.Plotter} with multiple y-axis
arguments.
Also illustrates how simply a row can be made twice as high as the
others.
"""
import numpy as np
from yampex import Plotter
N_sp = 4
N_pts = 200
X = np.linspace(0, 4 * np.pi, N_pts)
pt = Plotter(1, 4, width=10, height=10, h2=0)
pt.set_title("Sin(X) with increasingly noisy versions")
pt.set_zeroLine()
with pt as sp:
Y = None
for mult in np.logspace(-1.5, +0.5, N_sp):
if Y is None:
sp.add_textBox("SW",
"This subplot is twice as high as the others.")
Y = np.sin(X)
Y_noisy = Y + mult * np.random.randn(N_pts)
k = np.argmax(np.abs(Y - Y_noisy))
sp.add_textBox("NE", "Worst: {:+.3g} vs. {:+.3g}", Y_noisy[k], Y[k])
ax = sp(X, Y)
ax.plot(X, Y_noisy, 'r.')
pt.show()
def vectors(N):
"""
Returns a list with X and C{k*sin(k*X)} for I{k} from 1 to I{N},
where X is a 1-D Numpy vector having 200 points from 0 to M{4*pi}.
"""
X = np.linspace(0, 4 * np.pi, 200)
return [X] + [k * np.sin(k * X) for k in range(1, N + 1)]
# The number of waveforms
N = 3
# Construct a Plotter object for a 800x500 pixel (specified directly
# in pixels) figure with a single subplot.
pt = Plotter(1, width=800, height=500)
# As with many methods of opts.OptsBase, you can specify the title
# with a string formatting prototype and its argument(s).
pt.set_title("Sine Waves with {:d} frequency & amplitude multipliers", N)
# The x label will say "X" and the subplot will have a grid.
pt.set_xlabel("X")
pt.use_grid()
# Make a subplotting context and work with the single subplot via the
# subplot tool sp. It's actually just a reference to pt, but set up
# for subplotting.
with pt as sp:
# Add legends for the plots. Again, a string formatting prototype
# and its argument are used for convenience.
for mult in range(1, N + 1):
sp.add_legend("x{:d}", mult)