mikofski

"""
Approximately duplicates plot on this pvsyst help here:
https://www.pvsyst.com/help/iam_loss.htm
"""

import numpy as np
import matplotlib.pyplot as plt
plt.ion()

mikofski

#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Attribution: Hijacked from tracservice.py by Florent Xicluna <laxyf@yahoo.fr>
# http://trac-hacks.org/wiki/WindowsServiceScript
#
# To use this class, users must do the following:
# 1. Download and install the PyWin32all package
#    (http://starship.python.net/crew/mhammond/win32/)
# 2. Edit the constants section with the proper information.

mikofski

mikofski

#! /usr/bin/env python

import numpy as np
from datetime import datetime, time, timedelta
import pytz

class Timeseries(object):
    def __init__(self, x, t):
        self.x = np.array(x)
        self.t = np.array(t,dtype='datetime64[s]')

mikofski

mikofski

mikofski

function [p,S,mu] = polyfitZero(x,y,degree)
% POLYFITZERO Fit polynomial to data, forcing y-intercept to zero.
%   P = POLYFITZERO(X,Y,N) is similar POLYFIT(X,Y,N) except that the
%   y-intercept is forced to zero, i.e. P(N) = 0. In the same way as
%   POLYFIT, the coefficients, P(1:N-1), fit the data Y best in the least-
%   squares sense. You can also use Y = POLYVAL(PZERO,X) to evaluate the
%   polynomial because the output is the same as POLYFIT.
%
%   [P,S,MU] = POLYFITZERO() Return structure, S, similar to POLYFIT for use
%   with POLYVAL to calculate error estimates of predictions with P.

mikofski

#! python

import ftplib
import io
import json
import logging
import pathlib
import sys
import threading
import time

mikofski

mikofski

import os
import pvlib
import pandas as pd
from matplotlib import pyplot as plt
import seaborn as sns
sns.set()
plt.ion()

INVERTERS = pvlib.pvsystem.retrieve_sam('CECInverter')
INVERTER_10K = INVERTERS['SMA_America__SB10000TL_US__240V_']