Setting y-limit for plot with logarithmic axis (using plt.semilogy)

Question

I'd like to limit the y-scale for my plot with a logarithmic axis. However, adding plt.ylim((10^(-1),10^(0))) doesn't seem to change anything. Should I use a different command seeing as I'm using plt.semilogy? Below is the code and the data.

# Generate loss plots
    # --------------- Latex Plot Beautification --------------------------
    fig_width_pt = 492.0 #246.0  # Get this from LaTeX using \showthe\columnwidth
    inches_per_pt = 1.0/72.27               # Convert pt to inch
    golden_mean = (np.sqrt(5)-1.0)/2.0         # Aesthetic ratio
    fig_width = fig_width_pt*inches_per_pt  # width in inches
    fig_height = fig_width*golden_mean      # height in inches
    fig_size =  [fig_width+1,fig_height+1]
    params = {'backend': 'ps',
              'axes.labelsize': 12,
              'font.size': 12,
              'legend.fontsize': 10,
              'xtick.labelsize': 10,
              'ytick.labelsize': 10,
              'text.usetex': False,
              'figure.figsize': fig_size}
    plt.rcParams.update(params)
    # --------------- Latex Plot Beautification --------------------------

    train = {}

    tmp = list()
    with open('loss.csv', 'rb') as csv_file:
        reader = csv.reader(csv_file)
        for i, row in enumerate(reader):
            if i != 0:
                tmp.append(row)   


    tmp     = np.array(tmp)    

    train['iters'], train['seconds'], train['loss'], train['learn_rate'] = tmp[:,0], tmp[:,1], tmp[:,2], tmp[:,3]

    plt.subplot(211)
    plt.semilogy(train['iters'],train['loss'],'b',lw=2)
    plt.ylabel('loss')
    plt.ylim((10^(-1),10^(0)))

    plt.subplot(212)
    plt.semilogy(train['iters'],train['learn_rate'],'b',lw=2)
    plt.xlabel('iterations')
    plt.ylabel('learning rate')

    plt.show()

loss.csv

   NumIters,Seconds,TrainingLoss,LearningRate
    0.0,0.486213,0.693148,nan
    1000.0,7.557165,0.0961085,0.05
    2000.0,14.041684,0.00384812,0.05
    3000.0,20.410506,7.34072,0.05
    4000.0,26.772446,4.78843,0.05
    5000.0,34.117291,2.45869,0.05
    6000.0,40.249146,0.179548,0.05
    7000.0,46.377004,0.0033729,0.05
    8000.0,52.499923,0.00020626,0.05
    9000.0,59.317026,2.0962,0.05
    10000.0,66.679739,1.20523,0.05
    11000.0,72.846874,0.00894074,0.05
    12000.0,78.87727,2.37395,0.05
    13000.0,84.950737,0.00172985,0.05
    14000.0,91.036988,8.13143,0.05
    15000.0,98.153062,2.90689,0.05
    16000.0,104.252995,1.78791,0.05
    17000.0,110.286827,5.10336,0.05
    18000.0,116.47252,3.34482,0.05
    19000.0,122.683825,0.00838974,0.05
    20000.0,129.637347,0.00341582,0.05
    21000.0,135.640689,1.66777,0.05
    22000.0,141.66995,3.30503,0.05
    23000.0,147.721727,2.53775,0.05
    24000.0,154.084407,1.35748,0.05
    25000.0,161.426044,2.28748,0.05
    26000.0,168.492162,0.00397386,0.05
    27000.0,174.669545,0.000113542,0.05
    28000.0,180.803535,2.5192,0.05
    29000.0,187.004627,0.0019179,0.05
    30000.0,194.150244,4.36825,0.05
    31000.0,200.404565,1.38513,0.05
    32000.0,206.412659,0.0108084,0.05
    33000.0,212.437014,6.41096,0.05
    34000.0,218.56177,0.000235395,0.05
    35000.0,225.853988,7.88834,0.05
    36000.0,231.888062,0.00109338,0.05
    37000.0,238.976116,4.46498,0.05
    38000.0,246.112036,0.00246135,0.05
    39000.0,252.92424,0.00154073,0.05
    40000.0,261.114472,1.49658,0.05
    41000.0,268.695987,3.09471,0.05
    42000.0,275.331985,0.000266829,0.05
    43000.0,282.34568,1.06778,0.05
    44000.0,290.059307,5.98044,0.05
    45000.0,299.376506,0.00154176,0.05
    46000.0,306.722876,9.46019,0.05
    47000.0,314.33918,1.1353,0.05
    48000.0,321.358202,7.14507,0.05
    49000.0,328.710997,1.00035,0.05
    50000.0,335.206681,4.40056,0.05

Answer 1

The ^ operator performs bitwise exclusive or: 10^-1 = -11, 10^0 is 10 (ref: Python operators). Use ** to raise to a power, or use the pow() function. So you could use either:

plt.ylim( (10**-1,10**0) )

or if you want to be more verbose:

plt.ylim( (pow(10,-1),pow(10,0)) )