Python Forum

Here's my errpr message, last time I got this I had a logic error in a loop, but I can't find anything like that in this. Does anyone spot my problem?

Error:
runfile('C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction/Main Program.py', wdir='C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction')
C:\Python27\lib\site-packages\IPython\core\formatters.py:239: FormatterWarning: Exception in image/png formatter: Could not allocate memory for image
  FormatterWarning,
<matplotlib.figure.Figure at 0x2309ef0>
Traceback (most recent call last):

  File "<ipython-input-28-225e42a16155>", line 1, in <module>
    runfile('C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction/Main Program.py', wdir='C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction')

  File "C:\Python27\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 685, in runfile
    execfile(filename, namespace)

  File "C:\Python27\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 71, in execfile
    exec(compile(scripttext, filename, 'exec'), glob, loc)

  File "C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction/Main Program.py", line 100, in <module>
    ax.plot(x, yFunction(veganGrowth, initialPopOmni, popGrowthFactor), 'p-', lw=1, alpha=0.6, label='Major Graph')

  File "C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction/Main Program.py", line 62, in yFunction
    y = initialPop - totFunctions*y

MemoryError

Here's the code it's based on.

import numpy as np
from scipy.stats import lognorm
import matplotlib.pyplot as plt
from math import exp
fig, ax = plt.subplots(1, 1)

initialPop = int(326300000)
initialPopOmni = 315532100
popGrowthFactor = 0.007


def runLognormal(start, current, mean, cumImpact, peakFactor):
    scale = exp(mean)
    return lognorm.pdf(current, peakFactor, start, scale)*cumImpact
    
def runLinear(start, stop, slope):
    numQRun = start-stop
    y=[]
    time = start
    while time <= stop:
        time = time + 1
        y.append(slope*(time-start))
    return y[1:numQRun]
    
    
def veganuary(x):
    veg = []
    tTime = 48
    while tTime <= 136:
        tTime = tTime + 4
        veg.append(runLognormal(tTime, x, 0.002885, 0.00577, 0.55)-runLognormal(tTime+1, x, 0.00173, 0.00376, 0.55))
    return sum(veg[1:22])
    
def veganuary2(x):
    veg2 = []
    tTime = 136
    while tTime <= 212:
        tTime = tTime + 4
        veg2.append(runLognormal(tTime, x, 0.0043275, 0.008655, 0.55)-runLognormal(tTime+1, x, 0.002592, 0.00519, 0.55))
    return sum(veg2[1:19])
    
        
def yFunction(totFunctions, initialPop, popGrowthFactor):
    x = 0
    Y = []
    y = initialPop * np.exp(popGrowthFactor * x/4)
    while x < 212:
        Y.append(y)
        y = initialPop - totFunctions*y
        x = x + 0.01
    return Y[1:21200]
        
        
    


     
x = np.linspace(0, 212, num=21200)
tax1 = runLognormal(92, x, 0.036, 0.071, 0.55)
tax2 = runLognormal(112, x, 0.036, 0.071, 0.55)
tax3 = runLognormal(132, x, 0.071, 0.142, 0.55)
tax4 = runLognormal(152, x, 0.036, 0.071, 0.55)
tax5 = runLognormal(200, x, 0.1065, 0.213, 0.55)
tariff = runLognormal(56, x, 0.018, 0.036, 0.55)
ad1 = runLognormal(4, x, 0.000575, 0.00115, 0.55)
ad2 = runLognormal(44, x, 0.00019, 0.00038, 0.55)
ad3 = runLognormal(84, x, 0.00019, 0.00038, 0.55)
ad4 = runLognormal(124, x, 0.000385, 0.00077, 0.55)
ad5 = runLognormal(144, x, 0.000575, 0.00115, 0.55)
ad6 = runLognormal(176, x, 0.00095, 0.0019, 0.55)
ad7 = runLognormal(200, x, 0.000575, 0.00115, 0.55)
news1 = runLognormal(1, x, 0.000345, 0.00069, 0.55)-runLognormal(2, x, 0.000207, 0.000414, 0.55)
veg = veganuary(x)
veg2 = veganuary2(x)
label1 = runLinear(80, 160, 0.0006875)
label2 = runLinear(160, 212, 0.003125)
#consumptionBase =
#popBase = 
#popOmniBase =
#popVegBase =
#popVeganBase =
veganGrowth = tax1 + tax2 + tax3 + tax4 + tax5 + tariff + ad1 + ad2 + ad3 + ad4 + ad5 + ad6 + ad7 + news1 + veg + veg2# + label1 + label2

ax.set_title('Decrease in Omnivore Population')
ax.set_xlabel('$Quarter$')
ax.set_ylabel('$Population Omnivores$')
ax.plot(x, yFunction(veganGrowth, initialPopOmni, popGrowthFactor), 'p-', lw=1, alpha=0.6, label='Major Graph')

The error message doesn't match the code.
Error message shows error on line 62, but in your listing, it's line
49.
Please post error traceback that matches code.

oh, sorry, that's just because this is abbreviated code. I cut out a bunch of repeat stuff so that it would be easier to read, the traceback error is the same though.

When debugging code, you never use two versions. Get them in sync!

They're the same code, but here's the error code for the abbreviated version I'm using to debug (it's the exact same code, just minus repeated functions that I know work fine).

First error

Error:
Traceback (most recent call last):

  File "<ipython-input-1-1ea6155a3286>", line 1, in <module>
    runfile('C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction/Linear function.py', wdir='C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction')

  File "C:\Python27\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 685, in runfile
    execfile(filename, namespace)

  File "C:\Python27\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 71, in execfile
    exec(compile(scripttext, filename, 'exec'), glob, loc)

  File "C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction/Linear function.py", line 37, in <module>
    lbl1.plot(label1X, runLinear(80, 160, 0.0006875, label1X))

  File "C:\Python27\lib\site-packages\matplotlib\axes\_axes.py", line 1373, in plot
    for line in self._get_lines(*args, **kwargs):

  File "C:\Python27\lib\site-packages\matplotlib\axes\_base.py", line 304, in _grab_next_args
    for seg in self._plot_args(remaining, kwargs):

  File "C:\Python27\lib\site-packages\matplotlib\axes\_base.py", line 282, in _plot_args
    x, y = self._xy_from_xy(x, y)

  File "C:\Python27\lib\site-packages\matplotlib\axes\_base.py", line 223, in _xy_from_xy
    raise ValueError("x and y must have same first dimension")

ValueError: x and y must have same first dimension

Second error (with the lbl1 print commented out

Error:
runfile('C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction/Linear function.py', wdir='C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction')
Traceback (most recent call last):

  File "<ipython-input-2-1ea6155a3286>", line 1, in <module>
    runfile('C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction/Linear function.py', wdir='C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction')

  File "C:\Python27\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 685, in runfile
    execfile(filename, namespace)

  File "C:\Python27\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 71, in execfile
    exec(compile(scripttext, filename, 'exec'), glob, loc)

  File "C:/Users/after/OneDrive/Distinction Project Files 2017/Python Scripts for Distinction/Distinction/Linear function.py", line 40, in <module>
    veganGrowth = tax1 + label1

ValueError: operands could not be broadcast together with shapes (21200,) (0,) 

Here's the code:

import numpy as np
from scipy.stats import lognorm
import matplotlib.pyplot as plt
from math import exp


def runLognormal(start, current, mean, cumImpact, peakFactor):
    scale = exp(mean)
    return lognorm.pdf(current, peakFactor, start, scale)*cumImpact
    
def runLinear(start, stop, changePerQ, x):
    y = np.array([])
    time = start
    while time <= stop:
        np.append(y, changePerQ)
        time = time + 0.01
    return y

     
x = np.linspace(0, 212, num=21200)
tax1 = runLognormal(92, x, 0.036, 0.071, 0.55)
label1 = runLinear(80, 160, 0.0006875, x)


############################################### GRAPH LABEL 1
fig, lbl1 = plt.subplots(1, 1)
label1X = np.linspace(80, 160, num = 8000)
lbl1.set_title('Text Based Labels')
lbl1.set_xlabel('Quarter')
lbl1.set_ylabel('Cumulative Effect')
lbl1.plot(label1X, runLinear(80, 160, 0.0006875, label1X))
##############################################################

veganGrowth = tax1 + label1

fig, ax = plt.subplots(1, 1)
ax.set_title('Instantaneous Rate of Change in Population')
ax.set_xlabel('$Quarter$')
ax.set_ylabel('$Population Omnivores$')
ax.plot(x, veganGrowth)