USE DATATHIEF WITH NO AXIS CODE
USE DATATHIEF WITH NO AXIS TRIAL

The contribution to variance of each input parameter to each forecast variable is calculated by rank correlation coefficient using Monte Carlo-based techno-economic simulation run data for the base case in which Pearson correlation coefficients are not included, the results of which are described in the data file, 08. Forecast univariate sensitivity charts (base case). Forecast univariate sensitivity data (base case) and 07. Univariate sensitivity of the forecast variables to the input parameters is investigated using tornado plots and spider charts in the data files, 06. Forecast variable normality (base case + facility oversizing), as assessments of normality. Box plots and quantile-quantile plots are shown in the data file, 05. Statistical test results (base case + facility oversizing).

The forecast variable output data are compared between the base case and facility oversizing scenarios using two-sample t-tests for evaluation of the means and Kolmogorv-Smirnov tests for evaluation of the distributions, which is summarized in the data file, 04. 1.2 Analysis of techno-economic forecast variable outputs Equipment oversizing specification (base case + facility oversizing). The details of the equipment oversizing scenarios of the techno-economic process model to accommodate the uncertainty of production are described in the data file, 03.

USE DATATHIEF WITH NO AXIS TRIAL

Simulation trial data (base case + facility oversizing). These assumptions distribution trial data feed into the techno-economic process model (publicly available at ) to generate the forecast variable output data in the base case scenario and facility oversizing scenarios (in which the equipment of the facility is sized larger to accommodate the uncertainty of production). The input parameter assumption distributions and associated Monte Carlo sampling-based trial data for the base case techno-economic process model are described in the data file, 0.1 Assumption distribution & trial data (base case). The purpose of the article is to make techno-economic and associated uncertainty data available to be leveraged and adapted for other research purposes. The data have been acquired using deterministic techno-economic process model simulation in SuperPro Designer integrated with stochastic Monte Carlo-based simulation in Microsoft Excel using the Crystal Ball plug-in. 128 (2021) 153–165.” The raw and analyzed data presented are related to generation, analysis, and optimization of ultra-large-scale field-grown plant-based manufacturing of high-value recombinant protein under uncertainty.

McDonald, Introducing uncertainty quantification to techno-economic models of manufacturing field-grown plant-made products, Food Bioprod. tVerticalScrollBarPolicy(QtCore.Qt.This data article is related to the research article, “M.J.

QFigWidget2 = QtGui.QWidget(qScrollContents)įig2 = Figure(figsize=(5.0, 5.0), dpi=100) QFigWidget1 = QtGui.QWidget(qScrollContents)įig1 = Figure(figsize=(5.0, 1.0), dpi=100)ĬtSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed) QScrollLayout = QtGui.QVBoxLayout(qScrollContents)

By setting subplots_adjust I can get the y axis as close as I can to zero, but setting bottom any larget (bottom=0.9 I get a ValueError(bottom cannot be >= top) from PyQt4 import QtCore, QtGuiįrom _qt4agg import FigureCanvasQTAgg as FigureCanvas

USE DATATHIEF WITH NO AXIS CODE

The code below gives some idea, but I want the top plot to show just a horizontal line and x values, the y axis should have no dimension. I haven't seen any documentation of changing the actual plot dimensions, only the figure dimensions. I want to show just the x axis for a figure and have another figure below plotting the data (the lower one with the same x axis values as to top plot but not showing any ticks or labels).

Use datathief with no axis