# Removing colored axis markers from Python plot

edit: to improve the example code / upload the improved image

I am using pylab to plot a graph in Python (sample code is shown below). The plot is displayed correctly, however I cannot find a way to remove the lines connecting the colored axes (shown in the graph below), which makes the graph rather unsightly.

I searched the forums and didn't find a similar question, so any help would be appreciated.

thank

Code instance used for the graph:

Code based on the example shown here: http://code.activestate.com/recipes/578256-script-that-compares-various-interest-rate-term-st/

```
from pylab import plot, title, xlabel, ylabel, show
r0 = 0.5 # current UK funding rate
b = 2.0 # 1 % long term interest rate
a = 0.1#speed of reversion
beta = 0.2#SD
n = 1 # number of simulation trials
T = 15. # time of projection
m = 15. # subintervals
dt = T/m # difference in time each subinterval
r = np.zeros(shape=(n, m), dtype=float) # matrix to hold short rate paths
#loop used to simulate interest rates and plot points
for i in np.arange(1,m):
r[j,i] = r[j,i-1] + a*(b-r[j,i-1])*dt + beta*sqrt(dt)*standard_normal();
plot(np.arange(0, T, dt), r[j],linestyle='--')
show()
```

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If I understand correctly, you are just drawing all rows for index j.

What you want is perhaps just r [0 ,:] for the first simulation. If so, after the next i j for-look, do this

```
figure() # create a new figure canvas
plot(np.arange(0, T, dt), r[0,:], ,linestyle='--')
```

Does this help solve the problem?

(edit) Then the problem is probably that you want intermediate results. I just took the maximum intermediate result and plotted it as a thicker line.

```
from pylab import *
r0 = 0.5 # current UK funding rate
b = 2.0 # 1 % long term interest rate
a = 0.1#speed of reversion
beta = 0.2#SD
n = 1 # number of simulation trials
T = 15. # time of projection
m = 15. # subintervals
dt = T/m # difference in time each subinterval
r = np.zeros(shape=(n, m), dtype=float) # matrix to hold short rate paths
temp = [] # to save intermediate results
j = 0
clf()
x = np.arange(0, T, dt)
#loop used to simulate interest rates and plot points
for i in np.arange(1,m):
r[j,i] = r[j,i-1] + a*(b-r[j,i-1])*dt + beta*sqrt(dt)*standard_normal()
temp.append(r[j,:])
plot(x, r[j,:],linestyle='--')
results = np.array(temp)
plot( x, results.max(axis=0), linewidth=2 )
```

(edit2)

In fact, the end result is the same as max. So

```
plot(x, results[-1,:])
```

enough ...

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