danpy 1.1.1

Helpful functions for python.

Collection of useful python functions/features.

Prepared by: Daniel A Hagen

Installation

pip install danpy

Installation from GitHub

git clone https://github.com/danhagen/danpy.git && cd danpy
pip install -r requirements.txt
pip install .

Statusbar for Python for/while loops with danpy.sb

This helpful statusbar can be used with for/while loops to keep track of how much time has elapsed as well as how much time remains. Simply place inside the loop (after initializing the statusbar -- dsb -- with finalValue) and update with the current timestep (i). A title can be added to the statusbar to keep track of individual function/loops and it is recommended that any function that runs a loop uses arbitrary_function_name.__name__ to automatically assign an appropriate title. The initialValue can also be initialized or left at default (0).

Initialize statusbar before running a for/while loop.

from danpy.sb import *
from time import sleep

initialValue = 0
finalValue = 10
statusbar = dsb(initialValue,finalValue,title='a Loop')
for i in range(finalValue):
  sleep(0.5)
  statusbar.update(i)

It is useful to either reset the statusbar instance. However, loops run in succession will automatically reset if the loops are of the same size.

from danpy.sb import *
from time import sleep

initialValue = 0
finalValue = 10
numberOfOutsideLoops = 3
statusbar = dsb(initialValue,finalValue,title="Loop-D-Loops")
for j in range(numberOfOutsideLoops):
  for i in range(finalValue):
    sleep(0.5)
    statusbar.update(i)

It is also possible to rename loops when they are run in succession by using the updating title.

from danpy.sb import *
from time import sleep

initialValue = 0
finalValue = 10
statusbar = dsb(initialValue,finalValue,title="a Loop")
for i in range(finalValue):
  sleep(0.5)
  statusbar.update(i)

for i in range(finalValue):
  sleep(0.5)
  statusbar.update(i,title="a Different Loop")

However, these automatic reset features will only work if the length of each loop is the same and they have the same starting value. If you wish to run consecutive loops with different starting values or loop lengths, then you can reset the statusbar. It should be noted that the automatic reset, although convenient, will initialize the start_time after the first iteration of the loop. Therefore it is not the most accurate representation of runtime. We recommend a hard reset between trials or a redefinition of the statusbar before each loop.

Resetting Statusbar

A statusbar can be reset by calling the builtin function reset one of two way; reset() will return a statusbar with the previously used initialValue, finalValue, and title, or reset(**kwargs) can manually reset any of those values (while the others are kept as previously define).

from danpy.sb import *
from time import sleep

initialValue = 0
finalValue = 10
statusbar = dsb(initialValue,finalValue,title='One Loop')
for i in range(finalValue):
  sleep(0.5)
  statusbar.update(i)

aDifferentFinalValue = 1010
aDifferentInitialValue = 1000
statusbar.reset(
  initialValue=aDifferentInitialValue,
  finalValue=aDifferentFinalValue,
  title="Another Loop")
for i in range(aDifferentInitialValue,aDifferentFinalValue):
  sleep(0.5)
  statusbar.update(i)

Using while Loops

If using a while loop, the statusbar will still update, but depending on the nature of the code in the loop, the extrapolation to determine time remaining may be off.

from danpy.sb import *
from time import sleep

count = 0
finalCount = 10
statusbar = dsb(count,finalCount,title="a while Loop")
while count<finalCount:
  sleep(0.5)
  statusbar.update(count)
  count+=1

Only compatible with while loops that utilize a count metric where the loop continues while count<finalValue. The "<" ensures that the statusbar terminates at 100%. If you use "<=" then the input to the statusbar will be statusbar.update(i,finalValue+1,**kwargs).

Useful Functions for Python with danpy.useful_functions

Included in this package are the functions is_number and save_figures.

Simple test function for asserting a variable is, in fact, a number.

In order to quickly test if a variable is a number (and not a str or bool), simply type is_number(variable,variableName) as such:

from danpy.useful_function import is_number

myVariable = 3.1415926536
is_number(myVariable,"myVariable")

This will not raise an AssertionError as myVariable is a number. To make the debugging easier to locate, the additional arguments default and notes have been added.

from danpy.useful_functions import is_number

myVariable = "Not a number"
defaultValue = 3.1415926536
notes = "This is where I would put notes pertaining to the variable like relative magnitude, units, etc."

is_number(myVariable,"myVariable",
  default=defaultValue,
  notes=notes
)

which will raise the AssertionError:

AssertionError: myVariable must be an int, float, float32, float64, or numpy.float not <class 'str'>. Default is 3.1415926536. This is where I would put notes pertaining to the variable like relative magnitude, units, etc.

Simple function to save all current figures.

The function save_figures is designed to save all current figures in a convenient location for easy recovery and comparison. I find that this works best if you create a "figures/ "folder first so that your figures automatically get organized in a location other than your code.

In order to save your figures, you must specify the destination of the figures (in this case, "figures/"), the baseFileName (which can be used to further identify the figures), and a dictionary of the parameters (params) used to create these plots. This last part is a little different, but proves to be incredibly useful when you need to compare trials across parameters. This will also be used to create a notes.txt file that allows for quick reference of the used parameters. As an example, try:

from danpy.useful_functions import save_figures
import matplotlib.pyplot as plt
import numpy as np

dt = 0.01
signalAmplitude = 1
signalFrequency = 0.5 # Hz
durationOfSignal = 10 # seconds

params = {
  "Time Step" : dt,
  "Signal Amplitude" : signalAmplitude,
  "Signal Frequency" : signalFrequency,
  "Duration Of Signal" : durationOfSignal
}

time = np.arange(0,durationOfSignal+dt,dt)
signal1 = signalAmplitude*np.sin(2*np.pi*signalFrequency*time)
signal2 = signalAmplitude*np.cos(2*np.pi*signalFrequency*time)

fig1 = plt.figure()
ax1 = plt.gca()
ax1.plot(time,signal1)
ax1.set_xlabel("Time (s)")
ax1.set_ylabel("Signal 1")

fig2 = plt.figure()
ax2 = plt.gca()
ax2.plot(time,signal2)
ax2.set_xlabel("Time (s)")
ax2.set_ylabel("Signal 2")

save_figures(
  "figures/",
  "Signal_figures",
  params
)

plt.show()

This code will create a subfolder in "figures/" that is time stamped that contains three files ("Signal_figures_01-01.png","Signal_figures_01-02.png", and "notes.txt"). The first two files have the base file name "Signal_figures" followed by the number 01 (which corresponds to the trial number) and then the figure number. This can be useful when you wish to add figures to the same subfolder, when the parameters don't change (but more on that later).

The notes will appear as such,

[Created 2020/01/03 at 09:28.42]

##############################
########### Notes ############
##############################

		NONE

##############################
######### Parameters #########
##############################

		Time Step: 0.01
		Signal Amplitude: 1
		Signal Frequency: 0.5
		Duration Of Signal: 10

##############################

Note that all of the parameters have been listed conveniently as well as the date and time that the file was generated. You can also add your own notes to further categorize your results.

kwargs for save_figures

There are multiple ways to adjust the behavior of this function with kwargs. Specifically,

• fileType (default is "png") - You can change the file extension to any of the following: "eps", "pdf", "pgf", "png", "ps", "raw", "rgba", "svg", "svgz". Note that saving them as "pdf" will save each figure individually, where the kwargs saveAsPDF will combine them into a single file.
• subFolderName (default is the time stamped folder name) - Sometimes it is more convenient to name the subfolder yourself or to send files to a previously defined location. In this case, just specify the subFolderName and it will send the figures there. Note that this should only be done for trials where the parameters do not change as the notes.txt files is only generated when the subfolder is created.
• saveAsPDF (default False) - If true, in addition to saving the figures as the specified filetype, a single PDF will be constructed to include all figures generated.
• returnPath (default False) - If you intend on saving additional figures to the folder location, this option allows you to return the path of the subfolder. Use this for the first trial and the subFolderName argument for any additional trials to send new figures to the same location.
• figs (default will save every figure open) - You can alternatively specify the specific figures that you wish to save. This should be a list of figures.