Could you help me to solve the following problem,please ?
I did write a module in python . For the next module I need the following variables or values:
lastprice and lastpivotprice
What definition or script change is necessary, that this 2 variables are global variables)?
Actually if i try to call lastpivotprice outside the module i get the following error message:
nameError: name 'pivots' is not defined
Module Code: checkpivots.py
try:
df['High'].plot(label='high')
pivots =[]
dates = []
counter = 0
lastPivot = 0
Range = [0,0,0,0,0,0,0,0,0,0]
daterange = [0,0,0,0,0,0,0,0,0,0]
for i in df.index:
currentMax = max(Range , default=0)
value=round(df["High"][i],2)
Range=Range[1:9]
Range.append(value)
daterange=daterange[1:9]
daterange.append(i)
if currentMax == max(Range , default=0):
counter+=1
else:
counter = 0
if counter == 5:
lastPivot=currentMax
dateloc =Range.index(lastPivot)
lastDate = daterange[dateloc]
pivots.append(lastPivot)
dates.append(lastDate)
except Exception:
print("-")
lastpivotprice = pivots[-1]
lastprice=df.iloc[-1]['Close'] #read value in the last row in col 'close'
lastprice2 = df['Close'].values[-2] #read value in the last row minus2 in col 'close'
#print (lastprice)
# print (lastpivotprice)
# print (lastprice2)
If you want to take your variables in every module as globals, you have to set them as global variables. For example see this code below:
c = 0 # global variable
def add():
global c
c = c + 2 # increment by 2
print("Inside add():", c)
add()
print("In main:", c)
If you delete global from c, the c remains 0 in MAIN.
Related
I have the following example:
using DifferentialEquations
function test1(du,u,p,t)
a,b,c = p
d=a^0.1*(t+1)
e=u[1]/a
f=u[2]/d
du[1] = a*u[1]
du[2] = d*u[2]
du[3] = b*u[2] - c*u[3]
end
p = (2,0.75,0.8)
u0 = [1.0;1.0;1.0]
tspan = (0.0,3.0)
prob = ODEProblem(test1,u0,tspan,p)
sol = solve(prob,saveat=0.3)
The sol objects contain state outputs but, I need efficiently other variables ("d","e","f") as well.
The closest I can get is:
function test2(du,u,p,t)
global i
global Out_values
global sampletimes
a,b,c = p
d=a^0.1*(t+1)
e=u[1]/a
f=u[2]/d
if t in sampletimes
Out_values[1,i] = d
Out_values[2,i] = e
Out_values[3,i] = f
i=i+1
end
du[1] = a*u[1]
du[2] = d*u[2]
du[3] = b*u[2] - c*u[3]
end
sampletimes = tspan[1]:0.3:tspan[2]
Out_values = Array{Float64}(undef, 3, 2*11)
i=1
prob = ODEProblem(test2,u0,tspan,p)
sol = solve(prob,saveat=0.3,tstops=sampletimes)
However, this solution is not ideal because:
it duplicates saveat and I get two sets of slightly different outputs (not sure why), and
it can't expand if I decide not to use saveat and I want to output all solutions, i.e. sol = solve(prob).
Any help is appreciated.
i am extracting selected pages from a pdf file. and want to assign dataframe name based on the pages extracted:
file = "abc"
selected_pages = ['10','11'] #can be any combination eg ['6','14','20]
for i in selected_pages():
df{str(i)} = read_pdf(path + file + ".pdf",encoding = 'ISO-8859-1', stream = True,area = [100,10,740,950],pages= (i), index = False)
print (df{str(i)} )
The idea, ultimately, as in above example, is to have dataframes: df10, df11. I have tried "df" + str(i), "df" & str(i) & df{str(i)}. however all are giving error msg: SyntaxError: invalid syntax
Or any better way of doing it is most welcome. thanks
This is where a dictionary would be a much better option.
Also note the error you have at the start of the loop. selected_pages is a list, so you can't do selected_pages().
file = "abc"
selected_pages = ['10','11'] #can be any combination eg ['6','14','20]
df = {}
for i in selected_pages:
df[i] = read_pdf(path + file + ".pdf",encoding = 'ISO-8859-1', stream = True, area = [100,10,740,950], pages= (i), index = False)
i = int(i) - 1 # this will bring it to 10
dfB = df[str(i)]
#select row number to drop: 0:4
dfB.drop(dfB.index[0:4],axis =0, inplace = True)
dfB.columns = ['col1','col2','col3','col4','col5']
im trying to append an array by repeatedly calling a function. When I put the append command in a loop this works fine, but not when the loop calls the function that's supposed to do the append.
import numpy as np
test_value = 555
i = 0
j = 0
test_array = np.empty([0, 3])
def test(test_value, i, j, test_array):
test_temp = []
test_temp.append(i)
test_temp.append(j)
test_temp.append(test_value)
test_temp_1 = test_temp
test_temp_2 = np.array(test_temp_1)
test_temp_2 = np.reshape(test_temp_2, (1,3))
test_array = np.append(test_array, test_temp_2, axis=0)
return test_array
for i in range(0,10):
i = i + 1
j = j + 2
test(test_value, i, j, test_array)
print ("test array", test_array)
Ideally what would happen is that test_array gets a new row added each time its looped, but so the final print of test_array stays empty.
Cheers
I'm very new with Python, and I want to calculate percentile ranks by group. My group is wildlife management unit (WMU - string), and ranks are based the value of predicted moose density (PMDEN3 - FLOAT). The rank value goes into the field RankMD.
My approach was to use the for loop to calculate the 3 ranks within each WMU, but the result is that 3 ranks are created for the entire dbf file (about 23,000 records), without respect to WMU. Any help is much appreciated.
import arcpy
import numpy as np
input = r'K:\Moose\KrigStratPython\TestRank3.dbf'
arr = arcpy.da.TableToNumPyArray(input, ('PMDEN3', 'Wmu'))
c_arr = [float(x[0]) for x in np.ndarray.flatten(arr)]
for Wmu in arr:
##to create 3 rank for example
p1 = np.percentile(c_arr, 33) # rank = 0
p2 = np.percentile(c_arr, 67) # rank = 1
p3 = np.percentile(c_arr, 100) # rank = 2
#use cursor to update the new rank field
with arcpy.da.UpdateCursor(input , ['PMDEN3','RankMD']) as cursor:
for row in cursor:
if row[0] < p1:
row[1] = 0 #rank 0
elif p1 <= row[0] and row[0] < p2:
row[1] = 1
else:
row[1] = 2
cursor.updateRow(row)
Your for loop is correct, however, your UpdateCursor is iterating over all rows in the table. To get your desired result you need to select out a subset of the table, and then use the update cursor on that. You can do this by passing a query to the where_clause parameter of the UpdateCursor function.
So you would have a query like this:
current_wmu = WMU['wmu'] # This should be the value of the wmu that the for loop is currently on I think it would be WMU['wmu'] but i'm not positive
where_clause = "WMU = '{}'".format(current_wmu) # format the above variable into a query string
and then your UpdateCursor would now be:
with arcpy.da.UpdateCursor(input , ['PMDEN3','RankMD'], where_clause) as cursor:
Based on suggestion from BigGerman, I revised my code and this is now working. Script loops through each WMU value, and calculates rank percentile within each group based on PMDEN. To improve the script I should create an array of WMU values from my input file rather than manually creating the array.
import arcpy
import numpy as np
#fields to be calculated
fldPMDEN = "PMDEN"
fldRankWMU = "RankWMU"
input = r'K:\Moose\KrigStratPython\TestRank3.dbf'
arcpy.MakeFeatureLayer_management(input, "stratLayerShpNoNullsLyr")
WMUs = ["10", "11A", "11B", "11Q", "12A"]
for current_wmu in WMUs:
##to create 3 rank for example
where_clause = "Wmu = '{}'".format(current_wmu) # format the above variable into a query
with arcpy.da.UpdateCursor("stratLayerShpNoNullsLyr", [fldPMDEN,fldRankWMU], where_clause) as cursor:
arr1 = arcpy.da.TableToNumPyArray("stratLayerShpNoNullsLyr", [fldPMDEN,fldRankWMU], where_clause)
c_arrS = [float(x[0]) for x in np.ndarray.flatten(arr1)]
p1 = np.percentile(c_arrS, 33) # rank = 3
p2 = np.percentile(c_arrS, 67) # rank = 2
p3 = np.percentile(c_arrS, 100) # rank = 1 (highest density)
for row in cursor:
if row[0] < p1:
row[1] = 3 #rank 0
elif p1 <= row[0] and row[0] < p2:
row[1] = 2
else:
row[1] = 1
cursor.updateRow(row)
I'm trying to plot a function of two variables with pyplot in Julia. The working starting-point is the following (found here at StackOverflow):
function f(z,t)
return z*t
end
z = linspace(0,5,11)
t = linspace(0,40,4)
for tval in t
plot(z, f(z, tval))
end
show()
This works right for me and is giving me exactly what I wanted:
a field of lines.
My own functions are as follows:
## needed functions ##
const gamma_0 = 6
const Ksch = 1.2
const Kver = 1.5
function Kvc(vc)
if vc <= 0
return 0
elseif vc < 20
return (100/vc)^0.1
elseif vc < 100
return 2.023/(vc^0.153)
elseif vc == 100
return 1
elseif vc > 100
return 1.380/(vc^0.07)
else
return 0
end
end
function Kgamma(gamma_t)
return 1-((gamma_t-gamma_0)/100)
end
function K(gamma_t, vc)
return Kvc(vc)*Kgamma(gamma_t)*Ksch*Kver
end
I've tried to plot them as follows:
i = linspace(0,45,10)
j = linspace(0,200,10)
for i_val in i
plot(i,K(i,j))
end
This gives me the following Error:
isless has no method matching isless(::Int64, ::Array{Float64,1})
while loading In[51], in expression starting on line 3
in Kvc at In[17]:2 in anonymous at no file:4
Obviously, my function cant deal with an array.
Next try:
i = linspace(0,200,11)
j = linspace(0,45,11)
for i_val in i
plot(i_val,map(K,i_val,j))
end
gives me a empty plot only with axes
Can anybody please give me a hint...
EDIT
A simpler example:
using PyPlot
function P(n,M)
return (M*n^3)/9550
end
M = linspace(1,5,5)
n = linspace(0,3000,3001)
for M_val in M
plot(n,P(n,M_val))
end
show()
Solution
OK, with your help I found this solution for the shortened example which works for me as intended:
function P(n,M)
result = Array(Float64, length(n))
for (idx, val) in enumerate(n)
result[idx] = (M*val^3)/9550
end
return result
end
n = linspace(0,3000,3001)
for M_val = 1:5
plot(n,P(n,M_val))
end
show()
This gives me what I wanted for this shortened example. The remainig question is: could it be done in a simpler more elegant way?
I'll try to apply it to the original example and post it when I'll succed.
I don't completely follow all the details of what you're trying to accomplish, but here are examples on how you can modify a couple of your functions so that they accept and return arrays:
function Kvc(vc)
result = Array(Float64, length(vc))
for (idx, val) in enumerate(vc)
if val <= 0
result[idx] = 0
elseif val < 20
result[idx] = (100/val)^0.1
elseif val < 100
result[idx] = 2.023/(val^0.153)
elseif val == 100
result[idx] = 1
elseif val > 100
result[idx] = 1.380/(val^0.07)
else
result[idx] = 0
end
end
return result
end
function Kgamma(gamma_t)
return ones(length(gamma_t))-((gamma_t - gamma_0)/100)
end
Also, for your loop, I think you probably want something like:
for i_val in i
plot(i_val,K(i_val,j))
end
rather than plot(i, K(i,j), as that would just print the same thing over and over.
< is defined for scalars. I think you need to broadcast it for arrays, i.e. use .<. Example:
julia> x = 2
2
julia> x < 3
true
julia> x < [3 4]
ERROR: MethodError: no method matching isless(::Int64, ::Array{Int64,2})
Closest candidates are:
isless(::Real, ::AbstractFloat)
isless(::Real, ::Real)
isless(::Integer, ::Char)
in <(::Int64, ::Array{Int64,2}) at .\operators.jl:54
in eval(::Module, ::Any) at .\boot.jl:234
in macro expansion at .\REPL.jl:92 [inlined]
in (::Base.REPL.##1#2{Base.REPL.REPLBackend})() at .\event.jl:46
julia> x .< [3 4]
1x2 BitArray{2}:
true true